fix(core): improve patch errors

Co-authored-by: Kit Langton <kit.langton@gmail.com>

.changeset/calm-services-start.md

@@ -0,0 +1,7 @@
+---
+"@opencode-ai/client": patch
+"@opencode-ai/protocol": patch
+"@opencode-ai/cli": patch
+---
+
+Expose background-service lifecycle status, preserve one process-held owner through startup and failure, reconnect TUIs without activating replacement, and stop exact service instances gracefully.

.changeset/calm-sessions-header.md

@@ -0,0 +1,5 @@
+---
+"@opencode-ai/cli": patch
+---
+
+Expose a TUI plugin slot at the top of the session view.

.changeset/clean-sessions-generate.md

@@ -0,0 +1,7 @@
+---
+"@opencode-ai/client": patch
+"@opencode-ai/plugin": patch
+"@opencode-ai/protocol": patch
+---
+
+Expose transient, read-only session generation through the HTTP API, generated clients, and V2 plugin session context.

.changeset/fresh-composers-slot.md

@@ -0,0 +1,5 @@
+---
+"@opencode-ai/cli": patch
+---
+
+Expose a TUI plugin slot above the session composer.

.gitattributes

@@ -1,2 +1,3 @@
 packages/core/migration/**/snapshot.json linguist-generated
 packages/core/src/database/migration.gen.ts linguist-generated
+packages/core/src/**/*.txt text eol=lf

.github/ISSUE_TEMPLATE/config.yml

@@ -2,4 +2,4 @@ blank_issues_enabled: false
 contact_links:
   - name: 💬 Discord Community
     url: https://discord.gg/opencode
-    about: For quick questions or real-time discussion. Note that issues are searchable and help others with the same question.
+    about: For support, troubleshooting, how-to questions, and real-time discussion.

.github/ISSUE_TEMPLATE/question.yml

@@ -1,10 +0,0 @@
-name: Question
-description: Ask a question
-body:
-  - type: textarea
-    id: question
-    attributes:
-      label: Question
-      description: What's your question?
-    validations:
-      required: true

.github/TEAM_MEMBERS

@@ -1,4 +1,5 @@
 adamdotdevin
+arvsrn
 Brendonovich
 fwang
 Hona
@@ -7,11 +8,14 @@ jayair
 jlongster
 kitlangton
 kommander
+ludvigrask
 MrMushrooooom
 nexxeln
 R44VC0RP
 rekram1-node
 thdxr
 simonklee
+Slickstef11
+usrnk1
 vimtor
-starptech
+StarpTech

.github/actions/setup-bun/action.yml

@@ -8,6 +8,13 @@ inputs:
 runs:
   using: "composite"
   steps:
+    # node-gyp@latest (invoked via bunx for native install scripts) requires Node >=22;
+    # some runner images ship an older system Node on PATH
+    - name: Setup Node
+      uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+      with:
+        node-version: "24"
+
     - name: Get baseline download URL
       id: bun-url
       shell: bash

.github/workflows/compliance-close.yml

@@ -34,10 +34,48 @@ jobs:
 
             const now = Date.now();
             const twoHours = 2 * 60 * 60 * 1000;
+            const orgMemberAssociations = new Set(['OWNER', 'MEMBER']);
+            const agentLogin = 'opencode-agent[bot]';
+            const { data: file } = await github.rest.repos.getContent({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              path: '.github/TEAM_MEMBERS',
+              ref: 'dev',
+            });
+            const teamMembers = new Set(
+              Buffer.from(file.content, 'base64')
+                .toString()
+                .split('\n')
+                .map((line) => line.trim().toLowerCase())
+                .filter(Boolean)
+            );
+
+            function isExempt(item) {
+              const login = item.user?.login?.toLowerCase();
+              return (
+                login === agentLogin ||
+                orgMemberAssociations.has(item.author_association) ||
+                (login && teamMembers.has(login))
+              );
+            }
 
             for (const item of items) {
               const isPR = !!item.pull_request;
               const kind = isPR ? 'PR' : 'issue';
+              const login = item.user?.login;
+
+              if (isExempt(item)) {
+                core.info(`Skipping ${kind} #${item.number}; author ${login || 'unknown'} is exempt`);
+                try {
+                  await github.rest.issues.removeLabel({
+                    owner: context.repo.owner,
+                    repo: context.repo.repo,
+                    issue_number: item.number,
+                    name: 'needs:compliance',
+                  });
+                } catch (e) {}
+                continue;
+              }
 
               const { data: comments } = await github.rest.issues.listComments({
                 owner: context.repo.owner,

.github/workflows/duplicate-issues.yml

@@ -17,12 +17,31 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Check exempt issue author
+        id: author
+        run: |
+          LOGIN="${{ github.event.issue.user.login }}"
+          ASSOCIATION="${{ github.event.issue.author_association }}"
+
+          if [ "$LOGIN" = "opencode-agent[bot]" ] ||
+             [ "$ASSOCIATION" = "OWNER" ] ||
+             [ "$ASSOCIATION" = "MEMBER" ] ||
+             grep -qxiF "$LOGIN" .github/TEAM_MEMBERS; then
+            echo "skip=true" >> "$GITHUB_OUTPUT"
+            echo "Skipping issue automation for exempt author: $LOGIN ($ASSOCIATION)"
+          else
+            echo "skip=false" >> "$GITHUB_OUTPUT"
+          fi
+
       - uses: ./.github/actions/setup-bun
+        if: steps.author.outputs.skip != 'true'
 
       - name: Install opencode
+        if: steps.author.outputs.skip != 'true'
         run: curl -fsSL https://opencode.ai/install | bash
 
       - name: Check duplicates and compliance
+        if: steps.author.outputs.skip != 'true'
         env:
           OPENCODE_API_KEY: ${{ secrets.OPENCODE_API_KEY }}
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -38,6 +57,7 @@ jobs:
           opencode run -m opencode/claude-sonnet-4-6 "A new issue has been created:
 
           Issue number: ${{ github.event.issue.number }}
+          Issue author association: ${{ github.event.issue.author_association }}
 
           Lookup this issue with gh issue view ${{ github.event.issue.number }}.
 
@@ -49,6 +69,8 @@ jobs:
 
           Check whether the issue follows our contributing guidelines and issue templates.
 
+          If the issue author association is OWNER or MEMBER, skip this compliance check. Do not add the needs:compliance label for organization-owned issues.
+
           This project has three issue templates that every issue MUST use one of:
 
           1. Bug Report - requires a Description field with real content
@@ -83,7 +105,7 @@ jobs:
 
           Based on your findings, post a SINGLE comment on issue #${{ github.event.issue.number }}. Build the comment as follows:
 
-          If the issue is NOT compliant, start the comment with:
+          If the issue is NOT compliant and the author association is not OWNER or MEMBER, start the comment with:
           <!-- issue-compliance -->
           Then explain what needs to be fixed and that they have 2 hours to edit the issue before it is automatically closed. Also add the label needs:compliance to the issue using: gh issue edit ${{ github.event.issue.number }} --add-label needs:compliance
 
@@ -129,12 +151,31 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Check exempt issue author
+        id: author
+        run: |
+          LOGIN="${{ github.event.issue.user.login }}"
+          ASSOCIATION="${{ github.event.issue.author_association }}"
+
+          if [ "$LOGIN" = "opencode-agent[bot]" ] ||
+             [ "$ASSOCIATION" = "OWNER" ] ||
+             [ "$ASSOCIATION" = "MEMBER" ] ||
+             grep -qxiF "$LOGIN" .github/TEAM_MEMBERS; then
+            echo "skip=true" >> "$GITHUB_OUTPUT"
+            echo "Skipping issue automation for exempt author: $LOGIN ($ASSOCIATION)"
+          else
+            echo "skip=false" >> "$GITHUB_OUTPUT"
+          fi
+
       - uses: ./.github/actions/setup-bun
+        if: steps.author.outputs.skip != 'true'
 
       - name: Install opencode
+        if: steps.author.outputs.skip != 'true'
         run: curl -fsSL https://opencode.ai/install | bash
 
       - name: Recheck compliance
+        if: steps.author.outputs.skip != 'true'
         env:
           OPENCODE_API_KEY: ${{ secrets.OPENCODE_API_KEY }}
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -148,9 +189,12 @@ jobs:
             }
         run: |
           opencode run -m opencode/claude-sonnet-4-6 "Issue #${{ github.event.issue.number }} was previously flagged as non-compliant and has been edited.
+          Issue author association: ${{ github.event.issue.author_association }}
 
           Lookup this issue with gh issue view ${{ github.event.issue.number }}.
 
+          If the issue author association is OWNER or MEMBER, remove the needs:compliance label if present, delete the previous compliance comment if present, and do not post a new comment.
+
           Re-check whether the issue now follows our contributing guidelines and issue templates.
 
           This project has three issue templates that every issue MUST use one of:

.github/workflows/publish.yml

@@ -6,6 +6,7 @@ on:
     branches:
       - ci
       - dev
+      - v2
       - beta
       - fix/npm-native-binary-install
       - snapshot-*
@@ -31,6 +32,9 @@ permissions:
   contents: write
   packages: write
 
+env:
+  OPENCODE_CHANNEL: ${{ (github.ref_name == 'v2' && 'next') || '' }}
+
 jobs:
   version:
     runs-on: blacksmith-4vcpu-ubuntu-2404
@@ -86,11 +90,18 @@ jobs:
           opencode-app-id: ${{ vars.OPENCODE_APP_ID }}
           opencode-app-secret: ${{ secrets.OPENCODE_APP_SECRET }}
 
-      - name: Build
+      - name: Build legacy CLI
+        if: github.ref_name != 'v2'
+        run: ./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
+        env:
+          OPENCODE_VERSION: ${{ needs.version.outputs.version }}
+          OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
+          GH_REPO: ${{ needs.version.outputs.repo }}
+          GH_TOKEN: ${{ steps.committer.outputs.token }}
+
+      - name: Build preview CLI
         id: build
-        run: |
-          ./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
-          ./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
+        run: ./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
         env:
           OPENCODE_VERSION: ${{ needs.version.outputs.version }}
           OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
@@ -98,6 +109,7 @@ jobs:
           GH_TOKEN: ${{ steps.committer.outputs.token }}
 
       - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        if: github.ref_name != 'v2'
         with:
           name: opencode-cli
           path: |
@@ -105,6 +117,7 @@ jobs:
             packages/opencode/dist/opencode-linux*
 
       - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        if: github.ref_name != 'v2'
         with:
           name: opencode-cli-windows
           path: packages/opencode/dist/opencode-windows*
@@ -117,12 +130,61 @@ jobs:
     outputs:
       version: ${{ needs.version.outputs.version }}
 
+  build-node-cli:
+    needs: version
+    if: github.repository == 'anomalyco/opencode'
+    strategy:
+      fail-fast: false
+      matrix:
+        settings:
+          - target: linux-arm64
+            host: blacksmith-4vcpu-ubuntu-2404-arm
+          - target: linux-x64
+            host: blacksmith-4vcpu-ubuntu-2404
+          - target: darwin-arm64
+            host: macos-26
+          - target: windows-arm64
+            host: blacksmith-4vcpu-windows-2025
+          - target: windows-x64
+            host: blacksmith-4vcpu-windows-2025
+    runs-on: ${{ matrix.settings.host }}
+    defaults:
+      run:
+        shell: bash
+    steps:
+      - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
+
+      - uses: ./.github/actions/setup-bun
+        with:
+          install-flags: --os=* --cpu=*
+
+      - uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+        with:
+          node-version: "26.4.0"
+
+      - name: Build
+        run: bun packages/cli/script/build-node.ts --target=${{ matrix.settings.target }} --skip-install --outdir=dist/node
+        env:
+          OPENCODE_VERSION: ${{ needs.version.outputs.version }}
+          OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
+
+      - name: Verify service lifecycle
+        if: matrix.settings.target != 'windows-arm64'
+        working-directory: packages/cli
+        run: bun run script/service-smoke.ts --node
+
+      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: opencode-node-cli-${{ matrix.settings.target }}
+          path: packages/cli/dist/node/cli-node-*
+          if-no-files-found: error
+
   sign-cli-windows:
     needs:
       - build-cli
       - version
     runs-on: blacksmith-4vcpu-windows-2025
-    if: github.repository == 'anomalyco/opencode'
+    if: github.repository == 'anomalyco/opencode' && github.ref_name != 'v2'
     env:
       AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
       AZURE_TENANT_ID: ${{ secrets.AZURE_TENANT_ID }}
@@ -221,7 +283,7 @@ jobs:
     needs:
       - build-cli
       - version
-    if: github.repository == 'anomalyco/opencode'
+    if: github.repository == 'anomalyco/opencode' && github.ref_name != 'v2'
     continue-on-error: false
     env:
       AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
@@ -325,6 +387,7 @@ jobs:
         run: bun run build
         working-directory: packages/desktop
         env:
+          NODE_OPTIONS: --max-old-space-size=4096
           OPENCODE_CHANNEL: ${{ (github.ref_name == 'beta' && 'beta') || 'prod' }}
           SENTRY_AUTH_TOKEN: ${{ secrets.SENTRY_AUTH_TOKEN }}
           SENTRY_ORG: ${{ vars.SENTRY_ORG }}
@@ -408,6 +471,7 @@ jobs:
     needs:
       - version
       - build-cli
+      - build-node-cli
       - sign-cli-windows
       - build-electron
     if: always() && !failure() && !cancelled()
@@ -436,16 +500,19 @@ jobs:
           registry-url: "https://registry.npmjs.org"
 
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        if: github.ref_name != 'v2'
         with:
           name: opencode-cli
           path: packages/opencode/dist
 
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        if: github.ref_name != 'v2'
         with:
           name: opencode-cli-windows
           path: packages/opencode/dist
 
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        if: github.ref_name != 'v2'
         with:
           name: opencode-cli-signed-windows
           path: packages/opencode/dist
@@ -455,6 +522,12 @@ jobs:
           name: opencode-preview-cli
           path: packages/cli/dist
 
+      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        with:
+          pattern: opencode-node-cli-*
+          path: packages/cli/dist/node
+          merge-multiple: true
+
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
         if: needs.version.outputs.release
         with:

.github/workflows/storybook.yml

@@ -9,6 +9,7 @@ on:
       - "bun.lock"
       - "packages/storybook/**"
       - "packages/ui/**"
+      - "packages/session-ui/**"
   pull_request:
     branches: [dev]
     paths:
@@ -17,6 +18,7 @@ on:
       - "bun.lock"
       - "packages/storybook/**"
       - "packages/ui/**"
+      - "packages/session-ui/**"
   workflow_dispatch:
 
 concurrency:

.github/workflows/test.yml

@@ -4,6 +4,7 @@ on:
   push:
     branches:
       - dev
+      - v2
   pull_request:
   workflow_dispatch:
 
@@ -65,17 +66,40 @@ jobs:
 
       - name: Run unit tests
         timeout-minutes: 20
-        run: bun turbo test --output-logs=errors-only --log-order=grouped --log-prefix=none
+        run: GITHUB_ACTIONS=false bun turbo test
         env:
           OPENCODE_EXPERIMENTAL_DISABLE_FILEWATCHER: ${{ runner.os == 'Windows' && 'true' || 'false' }}
 
-      - name: Run HttpApi exerciser gates
+      - name: Verify compiled service lifecycle
+        if: always()
+        timeout-minutes: 10
+        working-directory: packages/cli
+        run: |
+          bun run script/build.ts --single --skip-install
+          bun run script/service-smoke.ts
+
+      - name: Setup Node build runtime
+        if: always()
+        uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+        with:
+          node-version: "26.4.0"
+
+      - name: Verify Node build
+        if: always()
+        timeout-minutes: 15
+        working-directory: packages/cli
+        run: |
+          bun run script/build-node.ts --single --skip-install --outdir=dist/node
+          bun run script/service-smoke.ts --node
+
+      - name: Check generated client
         if: runner.os == 'Linux'
-        working-directory: packages/opencode
-        run: bun run test:httpapi
+        working-directory: packages/client
+        run: bun run check:generated
 
   e2e:
     name: e2e (${{ matrix.settings.name }})
+    if: github.ref_name != 'v2' && github.head_ref != 'v2'
     strategy:
       fail-fast: false
       matrix:

.github/workflows/triage.yml

@@ -16,13 +16,32 @@ jobs:
         with:
           fetch-depth: 1
 
+      - name: Check exempt issue author
+        id: author
+        run: |
+          LOGIN="${{ github.event.issue.user.login }}"
+          ASSOCIATION="${{ github.event.issue.author_association }}"
+
+          if [ "$LOGIN" = "opencode-agent[bot]" ] ||
+             [ "$ASSOCIATION" = "OWNER" ] ||
+             [ "$ASSOCIATION" = "MEMBER" ] ||
+             grep -qxiF "$LOGIN" .github/TEAM_MEMBERS; then
+            echo "skip=true" >> "$GITHUB_OUTPUT"
+            echo "Skipping issue automation for exempt author: $LOGIN ($ASSOCIATION)"
+          else
+            echo "skip=false" >> "$GITHUB_OUTPUT"
+          fi
+
       - name: Setup Bun
+        if: steps.author.outputs.skip != 'true'
         uses: ./.github/actions/setup-bun
 
       - name: Install opencode
+        if: steps.author.outputs.skip != 'true'
         run: curl -fsSL https://opencode.ai/install | bash
 
       - name: Triage issue
+        if: steps.author.outputs.skip != 'true'
         env:
           OPENCODE_API_KEY: ${{ secrets.OPENCODE_API_KEY }}
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/typecheck.yml

@@ -2,9 +2,9 @@ name: typecheck
 
 on:
   push:
-    branches: [dev]
+    branches: [dev, v2]
   pull_request:
-    branches: [dev]
+    branches: [dev, v2]
   workflow_dispatch:
 
 jobs:

.gitignore

@@ -11,8 +11,10 @@ node_modules
 playground
 tmp
 dist
+dist-node
 ts-dist
 .turbo
+.typecheck-profiles
 **/.serena
 .serena/
 **/.omo
@@ -24,6 +26,7 @@ Session.vim
 a.out
 target
 .scripts
+.cache
 .direnv/
 
 # Local dev files

.opencode/command/translate.md

@@ -1,6 +1,6 @@
 ---
 description: translate English to other languages
-model: opencode/claude-opus-4-8
+model: opencode/gpt-5.6-sol
 ---
 
 run git diff and translate changed english doc and UI copy files to other international languages. Translate all languages in parallel to save time.

.opencode/skills/opencode-drive/SKILL.md

@@ -0,0 +1,254 @@
+---
+name: opencode-drive
+description: Use when an agent needs drive OpenCode via a script or interact with an isolated instance
+---
+
+# OpenCode Drive
+
+Use `opencode-drive` to launch an isolated OpenCode instance and control it via commands or a script.
+
+There are two modes. Always default to using a script unless specifically directed to be interactive (connect
+to an existing running instance, or start a new one, and make a few changes to the UI and read it, and iterate
+on changes).
+
+Scripts allow you to run a full walkthrough in one run. When the script is done opencode-drive exits,
+stops all processes, and cleans up all artifacts.
+
+# Prepare The Environment
+
+Use `init` when files must be added to the isolated home or project before OpenCode starts. It prints the artifact directory without launching OpenCode. A later `start` with the same name reuses it.
+
+```bash
+artifacts=$(opencode-drive init --name demo)
+cp -R ./fixtures/home/. "$artifacts/"
+cp -R ./fixtures/project/. "$artifacts/files/"
+opencode-drive start --name demo --dev ~/projects/opencode
+```
+
+The simulated project is under `$artifacts/files`. Running `start` without a prior `init` initializes the artifacts automatically.
+
+# Scripted usage
+
+You can write scripts that walk through entire flows, and gives you full access to controlling
+the backend too. See examples of the script API at the bottom of this file.
+
+After creating or editing a script, always typecheck it before running. Never skip this step:
+
+```bash
+opencode-drive check ./reproduce-stale-exploring-empty.ts
+```
+
+Run it by passing `--script` to start:
+
+```bash
+opencode-drive start --name auto-stop-reproduction --script ./reproduce-stale-exploring-empty.ts
+```
+
+It will output information about the run, including paths to log files which you can read
+to inspect what happened. If you need to dig into failures that aren't clear, read those log
+files. If the script is unsuccessful, automatically fix the script and run it again.
+
+Scripts use one typed definition object. `setup` runs before OpenCode starts,
+and `fs.writeFile` always writes inside the simulated project.
+
+You can read the full typed API here: https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/src/script/types.ts
+
+```ts
+import { defineScript } from "opencode-drive"
+
+export default defineScript({
+  async setup({ fs, config }) {
+    config.autoupdate = false
+    await fs.writeFile("src/example.ts", "export const value = 1\n")
+  },
+
+  async run({ ui, llm }) {
+    await ui.submit("Open src/example.ts")
+    await llm.send(llm.text("The file exports `value`."))
+    await ui.waitFor("The file exports `value`.")
+  },
+})
+```
+
+`setup` receives the current OpenCode config object, which starts from the
+default drive config unless the prepared instance already has one. When a script
+needs custom config, mutate this `config` parameter instead of generating and
+writing a new config object from scratch, so the script keeps the default
+provider/model settings unless it intentionally changes them.
+
+Note that the simulated model is a GPT model type, and opencode uses the `patch` tool for working with files Do not use a `edit` or `write` tool to edit files.
+
+Use `launch: "manual"` when the script needs to launch the server and every TUI
+itself (this is extremely rare, do not use this unless explicitly asked). In this
+mode `ui` is typed as `null`; call `server.launch()` exactly
+once before launching clients. Each `clients.launch(name)` result provides the
+same UI methods as the automatic client. You can see an example of this API
+here: https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/examples/multiple-clients.ts
+
+Use the exported `wait(milliseconds)` utility for an unconditional delay.
+
+`await llm.send(...)` waits for the next request and resolves after OpenCode
+acknowledges its complete response. `llm.queue(...)` declares responses in
+advance. Chunks may be built with `text`, `reasoning`, `toolCall`, `raw`,
+`finish`, and `disconnect`. A normal response receives `finish("stop")`
+automatically unless it yields or queues an explicit terminal event.
+
+`llm.text(text, { delay, chunkSize })` defaults to a 2 ms delay and a
+15-character target varied by plus or minus 5 per chunk.
+
+`llm.reasoning` accepts the same options, and `llm.pause(milliseconds)` adds a
+delay between any two outputs.
+
+Use `llm.serve` for an ongoing typed response generator:
+
+```ts
+llm.serve(async function* (request, index) {
+  yield llm.reasoning(`Handling request ${index + 1}`)
+  yield llm.text(`Received ${request.id}`)
+  yield llm.finish("stop")
+})
+```
+
+The backend connection, response cleanup, cancellation, and recording
+completion are automatic.
+
+You can see some example scripts here:
+
+- https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/examples/simple.ts
+- https://raw.githubusercontent.com/jlongster/opencode-drive/refs/heads/main/examples/serve.ts
+
+## Prune
+
+- `prune` removes artifact directories. These are always cleaned up after running a script
+  successfully, but leftover on failed runs. Always call this if a script fails.
+
+```bash
+opencode-drive prune --name demo
+
+// --force cleans up all artifcat directories
+opencode-dirve prune --force
+```
+
+# Live interaction usage
+
+- Always give headless instances a unique `--name`. Visible instances may omit it.
+- A normal headless `start` detaches automatically and returns after the instance is ready.
+- Do not add `&`; the long-running owner already runs in the background.
+- Configure simulated model responses after startup when needed.
+- Send ordered UI commands with `send`.
+- Always stop the instance when finished.
+
+```bash
+opencode-drive start --name demo
+
+opencode-drive send --name demo \
+  --command.ui.type '{"text":"Explain this project"}' \
+  --command.ui.enter
+
+opencode-drive stop --name demo
+```
+
+## Send UI Commands
+
+- Every `send` opens a connection to the named instance, runs its commands in order, and exits.
+- Combine typing and Enter in one command when submitting a prompt.
+- JSON-valued commands require one JSON argument.
+- Multiple command flags execute from left to right.
+
+Commands:
+
+- `--command.ui.type <json>` types into the focused editor. Arguments: `text` string.
+- `--command.ui.press <json>` presses a key. Arguments: `key` string; optional `modifiers` object with boolean `ctrl`, `shift`, `meta`, `super`, or `hyper`.
+- `--command.ui.enter` presses Enter. Arguments: none.
+- `--command.ui.arrow <json>` presses an arrow key. Arguments: `direction` is `up`, `down`, `left`, or `right`.
+- `--command.ui.focus <json>` focuses an element. Arguments: `target` is the numeric element `num` returned by `ui.state`.
+- `--command.ui.click <json>` clicks an element. Arguments: numeric `target`, `x`, and `y`; use the element `num` returned by `ui.state` as `target`.
+- `--command.ui.state` prints focus and interactive element metadata as JSON. Arguments: none.
+- `--command.ui.matches <json>` prints whether literal, case-sensitive text appears on screen. Arguments: `text` string.
+
+```bash
+opencode-drive send --name demo \
+  --command.ui.type '{"text":"Find the relevant code and explain it"}' \
+  --command.ui.enter
+
+opencode-drive send --name demo \
+  --command.ui.press '{"key":"p","modifiers":{"ctrl":true}}'
+
+opencode-drive send --name demo \
+  --command.ui.arrow '{"direction":"down"}'
+
+opencode-drive send --name demo \
+  --command.ui.focus '{"target":12}'
+
+opencode-drive send --name demo \
+  --command.ui.click '{"target":12,"x":4,"y":1}'
+
+opencode-drive send --name demo \
+  --command.ui.matches '{"text":"OpenCode"}'
+```
+
+To read the UI state and see information about interactable elements, use the `ui.state` command:
+
+```bash
+opencode-drive send --name demo --command.ui.state
+```
+
+## Configure LLM Responses
+
+- `responses` controls what the LLM responds with
+- Only use this if you are wanting to reproduce an exact type of response
+- Defaults are `text,reasoning,diff,tool` with `write,apply_patch`.
+- Supported types are `text`, `reasoning`, `diff`, and `tool`.
+- `--tools` limits generated tool calls to names offered by OpenCode.
+
+```bash
+opencode-drive responses --name demo \
+  --types text,reasoning,diff,tool \
+  --tools write,apply_patch
+
+opencode-drive responses --name demo \
+  --types tool \
+  --tools read,glob,grep
+```
+
+## Inspect The UI
+
+- `ui.state` prints focus and interactive element metadata as JSON.
+- `ui.matches` checks for literal, case-sensitive screen text.
+- `screenshot` prints the generated image path.
+
+```bash
+opencode-drive screenshot --name demo
+```
+
+## Lifecycle
+
+- `stop` waits for recording export and owner cleanup before returning.
+
+```bash
+opencode-drive stop --name demo
+```
+
+# Record The UI
+
+- Start with `--record` to capture a headless instance from its first rendered frame.
+- `stop` finishes the recording, exports an MP4, and prints its path.
+
+```bash
+opencode-drive start --name demo --record
+
+opencode-drive send --name demo \
+  --command.ui.type '{"text":"Show me the current architecture"}' \
+  --command.ui.enter
+
+opencode-drive stop --name demo
+```
+
+# Artifacts dir
+
+- `dir` prints the artifact directory for the instance.
+
+```bash
+opencode-drive dir --name demo
+```
+

.opencode/skills/sample-skill/SKILL.md

@@ -0,0 +1,31 @@
+---
+name: sample-skill
+description: Use when the user says sample skill, skill demo, or asks how an opencode SKILL.md should be structured; demonstrates a tiny project-local skill with practical assistant workflow guidance.
+---
+
+# Sample Skill
+
+This is a minimal project-local opencode skill. It exists as a reference for how a skill is structured and as a tiny reusable workflow the assistant can load when the user asks for a skill example.
+
+## When To Use
+
+- Use when the user asks for a sample skill or skill template.
+- Use when demonstrating the required `SKILL.md` frontmatter and body format.
+- Do not use for unrelated coding tasks just because a skill exists.
+
+## Workflow
+
+- Confirm the specific outcome the user wants if the request is ambiguous.
+- Inspect the relevant files before changing anything.
+- Make the smallest correct change.
+- Verify the result with a focused read, typecheck, test, or other lightweight check when available.
+- Summarize the changed files and any required restart or reload step.
+
+## Example Response Style
+
+When this skill is relevant, keep responses direct and actionable:
+
+```text
+I created a project-local skill at .opencode/skills/sample-skill/SKILL.md.
+Restart opencode for the new skill to be discovered by future sessions.
+```

.opencode/tool/github-triage.ts

@@ -4,7 +4,7 @@ import { tool } from "@opencode-ai/plugin"
 const TEAM = {
   tui: ["kommander", "simonklee"],
   desktop_web: ["Hona", "Brendonovich"],
-  core: ["jlongster", "rekram1-node", "nexxeln", "kitlangton", "starptech"],
+  core: ["jlongster", "rekram1-node", "nexxeln", "kitlangton"],
   inference: ["fwang", "MrMushrooooom", "starptech"],
   windows: ["Hona"],
 } as const

.prettierignore

@@ -1,2 +1,4 @@
 sst-env.d.ts
 packages/desktop/src/bindings.ts
+packages/client/src/generated/
+packages/client/src/generated-effect/

AGENTS.md

@@ -1,4 +1,7 @@
-- To regenerate the JavaScript SDK, run `./packages/sdk/js/script/build.ts`.
+- To regenerate the legacy JavaScript SDK, run `./packages/sdk/js/script/build.ts`.
+- After changing the public Protocol or Server `HttpApi`, run `bun run generate` from `packages/client`. Do not edit `src/generated` or `src/generated-effect` directly.
+- Keep runtime dependencies directed from Schema to Core and Protocol, then from Core and Protocol to Server. Client runtime code may depend on Schema and Protocol but never Core or Server; `sdk-next` composes Client, Core, and Server.
+- Do not modify `packages/opencode` unless the user explicitly asks for V1 work. `packages/opencode` is the V1 implementation and is present for reference only. New implementation changes should land in the V2 package set: `packages/core`, `packages/cli`, `packages/server`, `packages/protocol`, `packages/schema`, and related generated client surfaces when required.
 - The default branch in this repo is `dev`.
 - Local `main` ref may not exist; use `dev` or `origin/dev` for diffs.
 
@@ -22,12 +25,14 @@ Examples: `fix(tui): simplify thinking toggle styling`, `docs: update contributi
 
 - Keep things in one function unless composable or reusable
 - Do not extract single-use helpers preemptively. Inline the logic at the call site unless the helper is reused, hides a genuinely complex boundary, or has a clear independent name that improves the caller.
+- Before adding complexity for a speculative or vanishingly unlikely race or security edge case, explain the concrete failure mode, likelihood, and complexity cost to the user and get their buy-in. Do not silently expand scope for theoretical robustness.
 - Avoid `try`/`catch` where possible
 - Avoid using the `any` type
 - Use Bun APIs when possible, like `Bun.file()`
 - Rely on type inference when possible; avoid explicit type annotations or interfaces unless necessary for exports or clarity
 - Prefer functional array methods (flatMap, filter, map) over for loops; use type guards on filter to maintain type inference downstream
 - In `src/config`, follow the existing self-export pattern at the top of the file (for example `export * as ConfigAgent from "./agent"`) when adding a new config module.
+- In Effect generators, bind services to named variables before calling methods. Do not use nested service yields such as `yield* (yield* Foo.Service).bar()`.
 
 Reduce total variable count by inlining when a value is only used once.
 
@@ -147,12 +152,15 @@ const table = sqliteTable("session", {
 
 ## V2 Session Core
 
-- Keep durable prompt admission separate from model execution. `SessionV2.prompt(...)` admits one durable `session_input` row before scheduling advisory `SessionExecution.wake(sessionID)` unless `resume: false` requests admit-only behavior. The serialized runner promotes admitted inputs into visible user messages at safe boundaries.
-- Reusing a Session ID adopts the existing Session. Reusing a prompt message ID reconciles an exact retry only when Session, prompt, and delivery mode match; conflicting reuse fails. Historical projected prompts lazily synthesize promoted inbox records during exact retry.
-- Keep `SessionExecution` process-global and Session-ID based. Its local implementation owns the process-local Session coordinator and discovers placement through `SessionStore` plus `LocationServiceMap.get(session.location)` only when a drain starts; no layer should take a Session ID. V2 interruption targets the active process-local ownership chain for that Session; idle or missing interruption is a no-op.
+- Keep durable events minimal: record irreducible new facts and do not repeat state derivable by folding the ordered aggregate history. Enrich projections and read models with previous or derived state when consumers need self-contained views.
+- Keep durable prompt admission separate from model execution. `SessionV2.prompt(...)` admits one durable `session_pending` row before scheduling advisory `SessionExecution.wake(sessionID)` unless `resume: false` requests admit-only behavior. The serialized runner promotes admitted inputs into visible user messages at safe boundaries, consuming the pending row in the same event transaction; `session_pending` stores only unconsumed work.
+- Reusing a Session ID adopts the existing Session. Reusing a prompt message ID reconciles an exact retry only when Session, prompt, and delivery mode match; conflicting reuse fails. Retry of an already-promoted input reconciles against the projected message and the durable admitted event rather than a retained row.
+- Keep `SessionExecution` process-global and Session-ID based. Its local implementation owns the process-local Session coordinator and discovers placement through `SessionStore` plus `LocationServiceMap.get(session.location)` only when a drain starts; no layer should take a Session ID. V2 interruption targets the active process-local ownership chain for that Session; interruption of a known but idle or locally unowned Session is a no-op, while the public API rejects an unknown Session.
 - Keep `SessionRunner`, model resolution, tool registry, permissions, and filesystem Location-scoped. Omitted `Location.workspaceID` means implicit-local placement; explicit workspace identity remains reserved for future placement semantics.
-- Preserve one explicit `llm.stream(request)` call per provider turn and reload projected history before durable continuation. Do not bridge through legacy `SessionPrompt.loop(...)` or delegate orchestration to an in-memory tool loop.
+- Preserve one explicit `llm.stream(request)` call per Physical Attempt and reload projected history before durable continuation. Most Steps have one Physical Attempt; overflow-triggered compaction recovery may rebuild one Step for a second attempt. Do not bridge through legacy `SessionPrompt.loop(...)` or delegate orchestration to an in-memory tool loop.
 - Keep local Session drains process-local until clustering is implemented. `SessionRunCoordinator` joins explicit same-Session resumes, coalesces prompt wakeups, and allows different Sessions to run concurrently. Advisory wakes drain eligible durable inbox rows only; post-crash continuation recovery requires a separate explicit design before it may retry provider work. A drain has no durable identity or transcript boundary.
-- Keep delivery vocabulary explicit. Prompts steer by default and promote at the next safe provider-turn boundary while the current drain requires continuation. An explicit `queue` input remains pending until the Session would otherwise become idle; promote one queued input at that boundary, then reevaluate continuation before promoting another. Promoting any new user input resets the selected agent's provider-turn allowance; a batch of steers resets it once.
+- Keep delivery vocabulary explicit. Prompts steer by default and promote at the next safe step boundary while the current drain requires continuation. An explicit `queue` input remains pending until the Session would otherwise become idle; promote one queued input at that boundary, then reevaluate continuation before promoting another. Promoting any new user input resets the selected agent's step allowance; a batch of steers resets it once.
+- One step is one logical LLM call; its durable record covers only the model-visible span. Do not write "provider turn", and do not use bare "turn" for a single call: "turn" is reserved for the future assistant-turn unit containing all steps from prompt promotion until the session would go idle.
 - Keep EventV2 replay owner claims separate from clustered Session execution ownership.
-- Keep the System Context algebra, registry, and built-ins in `src/system-context`; keep Context Source producers with their observed domains, and keep Session History selection plus Context Epoch persistence Session-owned.
+- Keep the Instructions algebra and built-ins in `src/instructions`; keep instruction producers with their observed domains, and keep Session History selection plus `InstructionState` and `InstructionEntry` persistence Session-owned. `InstructionDiscovery` observes ambient global and upward-project instructions. The runner composes built-ins, discovery, guidance, and entries explicitly in `loadInstructions`; there is no instruction registry.
+- `session.instructions.updated` stores only changed source keys and content hashes. Blob values live once in `instruction_blob`; `instruction_state` is a rebuildable fold cache, never primary state. Render initial instructions and chronological updates from values during request assembly. Completed compaction moves the instruction epoch; Session movement and committed revert clear it. Unavailable sources retain the last value and block only the initial complete delta.

CONTEXT.md

@@ -1,143 +0,0 @@
-# OpenCode Session Runtime
-
-OpenCode sessions preserve durable conversational history while assembling the runtime context an agent needs to act correctly in its current environment.
-
-## Language
-
-**System Context**:
-The structured collection of contextual facts presented to the model as initial instructions and chronological updates.
-_Avoid_: System prompt
-
-**Session History**:
-The projected chronological conversation selected for a provider turn after applying the active compaction and **Context Epoch** cutoffs.
-_Avoid_: Session Context
-
-**Context Source**:
-One independently observed typed value within the **System Context**, represented by a stable key, JSON codec, infallible loader, pure baseline/update renderers, and an optional removal renderer for dynamic sources.
-_Avoid_: Prompt fragment
-
-**System Context Registry**:
-The Location-scoped registry of ordered, scoped producers that contribute to the current **System Context**.
-
-**Mid-Conversation System Message**:
-A durable chronological instruction that tells the model the newly effective state of a changed **Context Source**.
-_Avoid_: System update, system notification, raw text diff
-
-**Context Epoch**:
-The span during which one initially rendered **System Context** remains the immutable provider-cache baseline, ending at completed compaction, Session movement, or an incompatible context transition that requires a fresh baseline.
-
-**Baseline System Context**:
-The full **System Context** rendered at the start of a **Context Epoch**.
-_Avoid_: Live system prompt
-
-**Context Snapshot**:
-The overwriteable model-hidden JSON state used to compare each **Context Source** with the value last admitted to a provider turn.
-
-**Unavailable Context**:
-An expected temporary inability to observe a **Context Source** value; the runtime retains its prior effective state and emits no update, or omits it until first successfully loaded.
-
-**Safe Provider-Turn Boundary**:
-The point immediately before a provider call, after durable input promotion and any required tool settlement, where context changes may be admitted chronologically.
-
-**Admitted Prompt**:
-A durable user input accepted into the Session inbox but not yet included in **Session History**.
-
-**Prompt Promotion**:
-The durable transition that removes an **Admitted Prompt** from pending input and appends its user message to **Session History**.
-
-**Provider Turn**:
-One request to a model provider and the response projected from that request.
-
-**Session Drain**:
-One process-local execution span that promotes eligible input and runs required **Provider Turns** until no immediate continuation remains. A Session Drain has no durable identity or transcript boundary.
-
-**Model Tool Output**:
-The bounded projection of a Core-executed tool result persisted in Session history and replayed to the model. A tool may shape this projection semantically, but the Tool Registry enforces the final size limit.
-
-**Managed Tool Output File**:
-A temporary file created under OpenCode's shared tool-output directory to retain complete output that was too large for Session history.
-
-**Model Request Options**:
-Provider-semantic model settings selected from the Catalog and active Session variant before the LLM protocol adapter encodes them for a provider request.
-_Avoid_: Request body, wire options
-
-**Generation Controls**:
-Provider-neutral sampling and output controls, partitioned from provider semantics and compatibility wire fields when model metadata enters the Catalog.
-
-**PTY Environment**:
-The host-supplied environment overlay applied by the server when creating a PTY, observed for the request Location and resolved PTY working directory.
-
-## Relationships
-
-- A **System Context** is an opaque carrier composed from zero or more **Context Sources**.
-- **Session History** contains projected conversational messages and admitted **Mid-Conversation System Messages**; the active **Baseline System Context** remains separate provider-request state.
-- The **System Context Registry** uses stable-keyed scoped contributions to assemble the current **System Context**; contributor removal naturally removes its sources at the next **Safe Provider-Turn Boundary**.
-- A changed **Context Source** may produce one **Mid-Conversation System Message** containing its newly effective state.
-- A **Mid-Conversation System Message** persists the exact combined rendered text sent to the model.
-- The current **Context Snapshot** advances atomically with the corresponding durable **Mid-Conversation System Message**.
-- A **Context Snapshot** stores one codec-encoded JSON value and, for removable dynamic sources, a pre-rendered removal message per stable **Context Source** key.
-- Changes from multiple **Context Sources** admitted at one safe boundary combine into one **Mid-Conversation System Message**.
-- Context changes are sampled and admitted lazily at a **Safe Provider-Turn Boundary**, never pushed asynchronously when their source changes.
-- At a **Safe Provider-Turn Boundary**, newly promoted user input or settled tool results precede any combined **Mid-Conversation System Message**.
-- An **Admitted Prompt** is replayable pending input, not yet model-visible **Session History**.
-- **Prompt Promotion** atomically consumes the pending inbox entry and appends its model-visible user message.
-- Steering prompts promote at the next **Safe Provider-Turn Boundary** while the current **Session Drain** still requires continuation. Promoting any newly admitted user input resets the selected agent's provider-turn allowance; multiple prompts promoted at one boundary reset it once.
-- A queued prompt does not promote while the current **Session Drain** requires continuation. The runner promotes one queued prompt when the Session would otherwise become idle, then reevaluates continuation before promoting another.
-- A **Session Drain** is process-local coordination rather than a durable domain entity. Durable recovery must reason from prompts, projected history, provider attempts, and tool state rather than inventing an enclosing execution identity.
-- The first provider turn renders the latest complete **Baseline System Context** and initializes its **Context Snapshot** without emitting a redundant **Mid-Conversation System Message**; unavailable initial context blocks the turn instead of persisting an incomplete baseline.
-- Initial **System Context** preparation precedes the first durable input promotion so an unavailable baseline leaves that input pending and retryable; ordinary reconciliation remains after promotion.
-- Compaction starts a new **Context Epoch** with a freshly rendered **Baseline System Context** and **Context Snapshot**; prior **Mid-Conversation System Messages** remain durable audit history but leave projected model history.
-- A newly registered core or plugin-defined **Context Source** absent from the current snapshot emits its baseline rendering once at the next **Safe Provider-Turn Boundary**.
-- **Context Source** keys are stable and namespaced; duplicate keys fail composition. `SystemContext.combine(...)` preserves caller order; the **System Context Registry** evaluates producers concurrently and combines them in stable contribution-key order so rendered context remains deterministic.
-- Each **Context Source** loader returns one coherent typed value. `SystemContext.make(...)` hides that value type so differently typed sources compose uniformly. Its codec compares and stores that value; its pure renderers produce model-visible baseline, update, and removal text only when needed.
-- `SystemContext.initialize(...)` observes a composed **System Context** once and produces a fresh **Baseline System Context** with its **Context Snapshot**.
-- `SystemContext.reconcile(...)` observes a composed **System Context** once and returns exactly one next action: unchanged, updated, replacement ready, or replacement blocked.
-- `SystemContext.replace(...)` renders a fresh generation after completed compaction or another baseline-replacing transition; it reports replacement blocked while previously admitted context is unavailable.
-- **Unavailable Context** uses stale-while-revalidate semantics and is distinct from a successfully loaded absence, which may emit removal text.
-- Ordinary **Context Source** loaders return values directly; loaders that intentionally use stale-while-revalidate may explicitly return **Unavailable Context**.
-- Nested project instruction discovery after successful reads remains a follow-up; when implemented, discovered instructions must be admitted durably at the next **Safe Provider-Turn Boundary**.
-- Location-scoped services naturally re-resolve effective context when a moved session next runs in its destination location.
-- Moving a Session clears its active **Context Epoch**, so the destination must initialize a complete baseline before another prompt can promote.
-- Instruction discovery, source identity, persistence, and file loading belong to the instruction service; the **System Context** abstraction only composes effectful producers and renders loaded values.
-- The first instruction-service slice observes global and upward project `AGENTS.md` files as one ordered aggregate **Context Source** at each **Safe Provider-Turn Boundary**.
-- Built-in and instruction context producers register through the **System Context Registry** with stable contribution keys. Plugin-defined context registration and hot-reload lifecycle remain a follow-up built on the same scoped registry seam.
-- Selected-agent available-skill guidance is a **Context Source** composed with Location-wide registry sources immediately before Context Epoch admission. It lists only names and descriptions permitted for that agent; skill bodies and locations are exposed only through the permission-checked `skill` tool.
-- The selected agent and model are sampled when a provider turn starts. Changes admitted after that boundary apply to the next provider turn and do not restart the current turn.
-- Selected-agent available-skill guidance remains a **Context Source**. An agent switch that changes that guidance produces a **Mid-Conversation System Message** while preserving the current baseline.
-- Local tool authorization and pending permission requests retain the effective agent of the provider turn that issued the call; a later agent switch cannot change that call's policy.
-- Context source changes never wake idle sessions; the next naturally scheduled **Safe Provider-Turn Boundary** loads and compares current values lazily.
-- Once admitted, a **Mid-Conversation System Message** remains durable even if the following provider attempt fails and is replayed unchanged on retry.
-- **Mid-Conversation System Messages** remain durable Session-message history; normal user-facing transcript surfaces may hide them.
-- The date **Context Source** initially preserves host-local calendar-date behavior; a configured user timezone may replace that default later.
-- A **Context Epoch** begins with one immutable **Baseline System Context**.
-- A **Baseline System Context** is stored durably and reused verbatim across process restarts within its **Context Epoch**.
-- A **Baseline System Context** durably preserves the exact joined text used for the active provider-cache prefix.
-- Completed compaction starts a new **Context Epoch** on the next provider attempt, folding the current complete **System Context** into a fresh baseline and removing earlier **Mid-Conversation System Messages** from active model history.
-- A model/provider switch preserves the current **Context Epoch** and chronological conversation history; the new selection applies to the next provider turn.
-- **Model Request Options** remain provider-semantic through Catalog resolution. The Session runner maps them into the LLM package's provider-option namespace; the selected protocol adapter alone owns provider wire encoding.
-- **Generation Controls**, protocol-semantic **Model Request Options**, and compatibility request body fields are separate Catalog domains. A shared ingestion adapter partitions legacy and models.dev AI-SDK-shaped options before routing.
-- The **PTY Environment** is a server concern rather than a Core PTY concern. PTY creation merges caller values, then the host overlay, then Core-forced terminal invariants such as `TERM` and `OPENCODE_TERMINAL`.
-- A **PTY Environment** adapter observes plugins in the request Location while passing the resolved PTY working directory to the hook; standalone servers use an empty adapter.
-- A **Mid-Conversation System Message** lowers to the provider's native chronological instruction role when supported and to a wrapped chronological fallback otherwise.
-- When the effective aggregate instruction set changes, its **Mid-Conversation System Message** includes the complete current ordered set and supersedes the prior aggregate value; when no ambient instructions remain, the message states that previously loaded instructions no longer apply.
-- Ambient project instruction discovery honors `OPENCODE_DISABLE_PROJECT_CONFIG`; global instructions remain eligible.
-- Oversized textual **Model Tool Output** retains a bounded preview in Session history while its complete text moves to managed tool-output storage. Arbitrary structured-result size is a separate concern.
-- One tool settlement receives one aggregate textual limit, using the configured maximum lines or UTF-8 bytes, whichever is reached first. The limit is provider-independent; token pressure belongs to context assembly and compaction.
-- Generic truncation preserves the beginning and end of textual output. Tools may apply a more meaningful strategy before the Tool Registry enforces the final limit.
-- A truncated **Model Tool Output** identifies its complete text both in the bounded model-visible preview and as a typed managed output path. Managed output paths do not modify the tool's validated structured result.
-- A **Managed Tool Output File** is temporary and may expire after its retention period. The bounded **Model Tool Output**, not the file, is the durable replayable record.
-- Failure to retain a **Managed Tool Output File** does not change a successful tool operation into a failed one. The Session records an explicitly lossy bounded output without a path, while operators receive diagnostics for the storage failure.
-- Once a tool operation succeeds, bounding its **Model Tool Output** and publishing its one durable settlement form an interruption-safe completion region. Raw oversized success is never published before a later correction.
-- When a structured-only result would exceed the **Model Tool Output** limit, its validated structured value remains unchanged for Session consumers while model replay uses a bounded textual JSON preview and optional managed output path.
-- Existing tool-managed output paths survive generic bounding. A fallback file retains exactly the complete projected text received by the Tool Registry and never claims to reconstruct output already discarded by tool-specific shaping.
-- **Managed Tool Output Files** use globally unique names in one shared flat directory. Their absolute paths are readable and searchable by ordinary tools; other absolute paths remain outside Location-scoped filesystem authority.
-- Provider-executed tool results remain provider-native transcript facts outside generic Tool Registry bounding. Their context control requires provider-aware pruning or compaction because some providers require exact structured round-trip payloads.
-
-## Example dialogue
-
-> **Dev:** "The date changed while the session was active. Should the **Mid-Conversation System Message** say what the old date was?"
-> **Domain expert:** "No. Emit the newly effective date so the agent can act on the current **System Context**."
-
-## Flagged ambiguities
-
-- Legacy `experimental.chat.system.transform` can mutate the assembled baseline system prompt arbitrarily, but V2 plugins do not yet expose an equivalent hook. Decide separately whether to port it, replace dynamic uses with plugin-defined **Context Sources**, or narrow its semantics.

README.zh.md

@@ -125,4 +125,4 @@ OpenCode 内置两种 Agent，可用 `Tab` 键快速切换：
 
 ---
 
-**加入我们的社区** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=738j8655-cd59-4633-a30a-1124e0096789&qr_code=true) | [X.com](https://x.com/opencode)
+**加入我们的社区** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=52ao9352-5623-4fa0-b7dd-3407c392c1af&qr_code=true) | [X.com](https://x.com/opencode)

README.zht.md

@@ -125,4 +125,4 @@ OpenCode 內建了兩種 Agent，您可以使用 `Tab` 鍵快速切換。
 
 ---
 
-**加入我們的社群** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=738j8655-cd59-4633-a30a-1124e0096789&qr_code=true) | [X.com](https://x.com/opencode)
+**加入我們的社群** [飞书](https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=52ao9352-5623-4fa0-b7dd-3407c392c1af&qr_code=true) | [X.com](https://x.com/opencode)

artifacts/glm52-rise-video/.gitignore

@@ -0,0 +1,3 @@
+node_modules
+.remotion
+out/frame-*.png

artifacts/glm52-rise-video/bun.lock

@@ -0,0 +1,483 @@
+{
+  "lockfileVersion": 1,
+  "configVersion": 1,
+  "workspaces": {
+    "": {
+      "name": "glm52-rise-video",
+      "dependencies": {
+        "@remotion/cli": "^4.0.384",
+        "react": "^19.2.3",
+        "react-dom": "^19.2.3",
+        "remotion": "^4.0.384",
+      },
+      "devDependencies": {
+        "@types/react": "^19.2.8",
+        "@types/react-dom": "^19.2.3",
+        "typescript": "^5.8.2",
+      },
+    },
+  },
+  "packages": {
+    "@babel/helper-string-parser": ["@babel/helper-string-parser@7.29.7", "", {}, "sha512-Pb5ijPrZ89GDH8223L4UP8i6QApWxs04RbPQJTeWDV0/keR2E36MeKnyr6LYmUUvqRRI+Iv87SuF1W6ErINzYw=="],
+
+    "@babel/helper-validator-identifier": ["@babel/helper-validator-identifier@7.29.7", "", {}, "sha512-qehxGkRj55h/ff8EMaJ+cYhyaKlHIxqYDn682wQD7RNp9UujOQsHog2uS0r2vzr4pW+sXf90NeeayjcNaX3fFg=="],
+
+    "@babel/parser": ["@babel/parser@7.24.1", "", { "bin": "./bin/babel-parser.js" }, "sha512-Zo9c7N3xdOIQrNip7Lc9wvRPzlRtovHVE4lkz8WEDr7uYh/GMQhSiIgFxGIArRHYdJE5kxtZjAf8rT0xhdLCzg=="],
+
+    "@babel/types": ["@babel/types@7.24.0", "", { "dependencies": { "@babel/helper-string-parser": "^7.23.4", "@babel/helper-validator-identifier": "^7.22.20", "to-fast-properties": "^2.0.0" } }, "sha512-+j7a5c253RfKh8iABBhywc8NSfP5LURe7Uh4qpsh6jc+aLJguvmIUBdjSdEMQv2bENrCR5MfRdjGo7vzS/ob7w=="],
+
+    "@emnapi/core": ["@emnapi/core@1.11.1", "", { "dependencies": { "@emnapi/wasi-threads": "1.2.2", "tslib": "^2.4.0" } }, "sha512-RSvbQmHzdKzNsLYa/wHrbc3KN4sYLKAdPZxqiM2HATqv/SBk2/ENSHpvXGaLOMcsAyz0poEGqkmmKYG3OWiJEQ=="],
+
+    "@emnapi/runtime": ["@emnapi/runtime@1.11.1", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-vgj7R3y3Wgx24IQaGPA/R6YFXLHVMOZ0uVEyIQPaWs+rd1AzfEMXlAC22FYwO1XkKR6NPsq7mUandH8oIRdZFw=="],
+
+    "@emnapi/wasi-threads": ["@emnapi/wasi-threads@1.2.2", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-c95qOXkHdydNKhscBTebqEC1CVAZpyqOfVfBzQ1qgzyl3gfeldUjIggDbIZgDKsHLgnsM+igH7TJ/eAasaVuMA=="],
+
+    "@esbuild/aix-ppc64": ["@esbuild/aix-ppc64@0.28.1", "", { "os": "aix", "cpu": "ppc64" }, "sha512-Svl7tq8k/08+p6CXPpRjQ1fKX+1odH/BQbb48fV6fj3CWHhsoIOoY87w1oHXm0qEpkIK3ZfVgp0hed3XBXzXMQ=="],
+
+    "@esbuild/android-arm": ["@esbuild/android-arm@0.28.1", "", { "os": "android", "cpu": "arm" }, "sha512-0k2F129Xdio1TdJfzJ8sy1Q47vUD2NnwdhiAf7drUN1EBTfPf4hsFCtmMgu/6m8JSzsBrlmVjudMBQqOfG8usQ=="],
+
+    "@esbuild/android-arm64": ["@esbuild/android-arm64@0.28.1", "", { "os": "android", "cpu": "arm64" }, "sha512-34EGEbCIAgosYz6goLcopX6Mo7NyGv9tfwEM2/7Ce2VcVRk568iSvniGWcUXIy7wEDR1wzolcxcriFVrWYcwBg=="],
+
+    "@esbuild/android-x64": ["@esbuild/android-x64@0.28.1", "", { "os": "android", "cpu": "x64" }, "sha512-dbwY7ltSMDWsRatcRpCnES4F+im88OCUgGZjy52shC7GqHRE/cYlxNbB4Z4UpJswpcc4Qxd2oE/ufM0p61IKng=="],
+
+    "@esbuild/darwin-arm64": ["@esbuild/darwin-arm64@0.28.1", "", { "os": "darwin", "cpu": "arm64" }, "sha512-TZbWkQY7kvTAXbXUT7uVACR5cMHsDiSz9z7ZKAX/RTq/WJEk3QyRr0wZpNhBDX+/0CtdqUIJlOiodQcta6tY3Q=="],
+
+    "@esbuild/darwin-x64": ["@esbuild/darwin-x64@0.28.1", "", { "os": "darwin", "cpu": "x64" }, "sha512-zfdzgK9ACBNZLI/CyHTOx81SyNbM6YXn7rxSgX97VjyiPl9W1i4Ka4fgKECEoFCKGpvBj5qArWIGgQjOwkgskQ=="],
+
+    "@esbuild/freebsd-arm64": ["@esbuild/freebsd-arm64@0.28.1", "", { "os": "freebsd", "cpu": "arm64" }, "sha512-wG2EA8ENdEI0qhkSZMjfqrdY+ziCYCPMmtZjjIwOmXFjmyzEHn+UUxk5of+SYsjtfs3VpnlC7QLzSI5hY/rOAw=="],
+
+    "@esbuild/freebsd-x64": ["@esbuild/freebsd-x64@0.28.1", "", { "os": "freebsd", "cpu": "x64" }, "sha512-i7dZ9vQgnvSCzi/rYCXNgtF/U+eKZNJBzu3eTQbRgHnM7tNSizLOkRFAl3qzVc/Op/u5YkHHa4pf/3DOYHthLQ=="],
+
+    "@esbuild/linux-arm": ["@esbuild/linux-arm@0.28.1", "", { "os": "linux", "cpu": "arm" }, "sha512-qVXBOHQS+d5Y722GwJzJUtOLlX7km3CraOaGormF1pDtPd2C/l1SHRPgjLunLGe51Sh5YYWKMFDyV4SxgMQYTQ=="],
+
+    "@esbuild/linux-arm64": ["@esbuild/linux-arm64@0.28.1", "", { "os": "linux", "cpu": "arm64" }, "sha512-yHs+0uc8+nvEAfAfxrWQKK5peSNzBc4PegcMO0EJ2hT71uA7vB8Ihg2e77R2P7SG5uYjPbHlLLmve4LLLRCf0g=="],
+
+    "@esbuild/linux-ia32": ["@esbuild/linux-ia32@0.28.1", "", { "os": "linux", "cpu": "ia32" }, "sha512-d1z4ZuP0ajrfz/FhGT4vv278rX8KnPPJx8i5+AtK7TYbx9Le9F1hyzurZpkEyjkGa9dUGhQow4C1NmeGvqxN2w=="],
+
+    "@esbuild/linux-loong64": ["@esbuild/linux-loong64@0.28.1", "", { "os": "linux", "cpu": "none" }, "sha512-M5sRjUVZrkm1OAPR3dlOYzNmN+loZKGVi1VUQGrwuqLcbR6qeAz+famMhjASeH3YVKvZz+zT1jlh/keC3Rj/lg=="],
+
+    "@esbuild/linux-mips64el": ["@esbuild/linux-mips64el@0.28.1", "", { "os": "linux", "cpu": "none" }, "sha512-mRObBZeHh2OxcBFPWE/FjylkRgZdYuiTR3vaTozquCGOH14iP9oN4x4Ge81CoIDYQrXmIxpFumJBu5MtZpnQJQ=="],
+
+    "@esbuild/linux-ppc64": ["@esbuild/linux-ppc64@0.28.1", "", { "os": "linux", "cpu": "ppc64" }, "sha512-slScBsMAb3GFDcdrCgLwZtPYRoH2H/youv10QiZyRjmsP48fznoveWytSgCI/R0ZcUgpc0ZhIUEx6LHts8yrfQ=="],
+
+    "@esbuild/linux-riscv64": ["@esbuild/linux-riscv64@0.28.1", "", { "os": "linux", "cpu": "none" }, "sha512-kw0owk1o0GFETUJyW0jc0G4Yzs0BHZn0JDZ8JRT088vjJYX777BAs1fDGxAC+q831qOs2DTC96mNsG2opdfyyQ=="],
+
+    "@esbuild/linux-s390x": ["@esbuild/linux-s390x@0.28.1", "", { "os": "linux", "cpu": "s390x" }, "sha512-/lAIjX8aYFRByhh6L5rYtPEDRqa9de/4V/juOXcta5frjvzXO4/sqEtyytse0g3zZFuWu5cDN0MkLz2qRDD2Ag=="],
+
+    "@esbuild/linux-x64": ["@esbuild/linux-x64@0.28.1", "", { "os": "linux", "cpu": "x64" }, "sha512-u/anNYF2mmVOEDwLtnQ1wOr3EZ9sTNGLWrsYGYwHWzGA3Si84IOkHXlbWTD1NB+9/1lcnweYKO54uhxZydNzfA=="],
+
+    "@esbuild/netbsd-arm64": ["@esbuild/netbsd-arm64@0.28.1", "", { "os": "none", "cpu": "arm64" }, "sha512-oks0DYbLwWMmaakTsCb+zL4E+aHRVLom9IJZOAthMQEPiQmydXHkziYEsGYRx0uNV/IjEKGAV941JzH02pflqw=="],
+
+    "@esbuild/netbsd-x64": ["@esbuild/netbsd-x64@0.28.1", "", { "os": "none", "cpu": "x64" }, "sha512-aeL6lAnN89Hz43Mlh1G8ARasbuoYvSITDEx0tHh5b7jJnHcssqgjy9Yx430GDpmCa6OyrKoS0aNRjKundRizGg=="],
+
+    "@esbuild/openbsd-arm64": ["@esbuild/openbsd-arm64@0.28.1", "", { "os": "openbsd", "cpu": "arm64" }, "sha512-MEFJe5C3R8pwXdZ5Y21oo6m7ePiS0d9pWucn99O/wvyJZChoIQKrQDxKrGeW8F5+T0okTHesAmDeiHDTIq0V/Q=="],
+
+    "@esbuild/openbsd-x64": ["@esbuild/openbsd-x64@0.28.1", "", { "os": "openbsd", "cpu": "x64" }, "sha512-i/ZLIOafE0Z8cI/XANJAixoJL/uRAoS2xOA3rb0xN+KK0K177cMAsQYkzHtBrtMXAKuAc7HGgcWiZ/sRC1Nxgw=="],
+
+    "@esbuild/openharmony-arm64": ["@esbuild/openharmony-arm64@0.28.1", "", { "os": "none", "cpu": "arm64" }, "sha512-ge+Z7EXFNt2BO1oAMsVpiQ8EwndV9i1xXerAeTIK7AtPs3bKFXQM7nlRxDSIUIMeueR1CNXxqztLzdNeReKBJg=="],
+
+    "@esbuild/sunos-x64": ["@esbuild/sunos-x64@0.28.1", "", { "os": "sunos", "cpu": "x64" }, "sha512-BEjgtECkL3vY+SaSQ6nzVfiALUeFxpawyp8Jmf5PtYhf1Ug40N1h/hxlhts+f1FvSvarEigdxS3BlSMI2PJLcQ=="],
+
+    "@esbuild/win32-arm64": ["@esbuild/win32-arm64@0.28.1", "", { "os": "win32", "cpu": "arm64" }, "sha512-lCv9eK/H6ZJWbE7bh2nw54CZ9M2nupBxJcTsdk/QQnWkdSjKGuxmmH8/GWrlT1eMmZfn4dGcCjRte397WqfQXA=="],
+
+    "@esbuild/win32-ia32": ["@esbuild/win32-ia32@0.28.1", "", { "os": "win32", "cpu": "ia32" }, "sha512-zvb/mB2bSCoJOpoCBgYKKpX6YM6mJBlBUVUtVj41DlZJVEB6/0CKlRYxP5wWl1C1ILiCoAU5wZZ4q1P3qeS6Eg=="],
+
+    "@esbuild/win32-x64": ["@esbuild/win32-x64@0.28.1", "", { "os": "win32", "cpu": "x64" }, "sha512-bm4Mowrv+GXMlpWX++EcXw/iLyd1o3+bJkC2DkWXYVvgZCqD/bSj9ctZeAMC3cIxgjRVR2Dufaiu4YPxr5gW1A=="],
+
+    "@jridgewell/gen-mapping": ["@jridgewell/gen-mapping@0.3.13", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.0", "@jridgewell/trace-mapping": "^0.3.24" } }, "sha512-2kkt/7niJ6MgEPxF0bYdQ6etZaA+fQvDcLKckhy1yIQOzaoKjBBjSj63/aLVjYE3qhRt5dvM+uUyfCg6UKCBbA=="],
+
+    "@jridgewell/resolve-uri": ["@jridgewell/resolve-uri@3.1.2", "", {}, "sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw=="],
+
+    "@jridgewell/source-map": ["@jridgewell/source-map@0.3.11", "", { "dependencies": { "@jridgewell/gen-mapping": "^0.3.5", "@jridgewell/trace-mapping": "^0.3.25" } }, "sha512-ZMp1V8ZFcPG5dIWnQLr3NSI1MiCU7UETdS/A0G8V/XWHvJv3ZsFqutJn1Y5RPmAPX6F3BiE397OqveU/9NCuIA=="],
+
+    "@jridgewell/sourcemap-codec": ["@jridgewell/sourcemap-codec@1.5.5", "", {}, "sha512-cYQ9310grqxueWbl+WuIUIaiUaDcj7WOq5fVhEljNVgRfOUhY9fy2zTvfoqWsnebh8Sl70VScFbICvJnLKB0Og=="],
+
+    "@jridgewell/trace-mapping": ["@jridgewell/trace-mapping@0.3.31", "", { "dependencies": { "@jridgewell/resolve-uri": "^3.1.0", "@jridgewell/sourcemap-codec": "^1.4.14" } }, "sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw=="],
+
+    "@mediabunny/aac-encoder": ["@mediabunny/aac-encoder@1.47.0", "", { "peerDependencies": { "mediabunny": "^1.0.0" } }, "sha512-JNzgdJoHMFFnv5imi1+dmjZMudsJ1zNCUCEkKjBh90cqGhAFg8xu4V2gsyxE2i6oq/YpWx23P+OvoANLSMcDzA=="],
+
+    "@mediabunny/flac-encoder": ["@mediabunny/flac-encoder@1.47.0", "", { "peerDependencies": { "mediabunny": "^1.0.0" } }, "sha512-VpKmJO0xlYcFCRD6JvJlMbNQ6d/6YMHdO1gFIqWlZABHjSSL6BquNNEgWSCv5vdF8ELDBwIYBVZEslakIB/7GA=="],
+
+    "@mediabunny/mp3-encoder": ["@mediabunny/mp3-encoder@1.47.0", "", { "peerDependencies": { "mediabunny": "^1.0.0" } }, "sha512-JyzZyGeGRm2HVUQaGJ/VZT9OG+kG00mA8SLP/f3CO7+qWAmBncKc16WYXWHbZEo8Jn/ZGA6De32S5R2bTQbDqA=="],
+
+    "@module-federation/error-codes": ["@module-federation/error-codes@0.22.0", "", {}, "sha512-xF9SjnEy7vTdx+xekjPCV5cIHOGCkdn3pIxo9vU7gEZMIw0SvAEdsy6Uh17xaCpm8V0FWvR0SZoK9Ik6jGOaug=="],
+
+    "@module-federation/runtime": ["@module-federation/runtime@0.22.0", "", { "dependencies": { "@module-federation/error-codes": "0.22.0", "@module-federation/runtime-core": "0.22.0", "@module-federation/sdk": "0.22.0" } }, "sha512-38g5iPju2tPC3KHMPxRKmy4k4onNp6ypFPS1eKGsNLUkXgHsPMBFqAjDw96iEcjri91BrahG4XcdyKi97xZzlA=="],
+
+    "@module-federation/runtime-core": ["@module-federation/runtime-core@0.22.0", "", { "dependencies": { "@module-federation/error-codes": "0.22.0", "@module-federation/sdk": "0.22.0" } }, "sha512-GR1TcD6/s7zqItfhC87zAp30PqzvceoeDGYTgF3Vx2TXvsfDrhP6Qw9T4vudDQL3uJRne6t7CzdT29YyVxlgIA=="],
+
+    "@module-federation/runtime-tools": ["@module-federation/runtime-tools@0.22.0", "", { "dependencies": { "@module-federation/runtime": "0.22.0", "@module-federation/webpack-bundler-runtime": "0.22.0" } }, "sha512-4ScUJ/aUfEernb+4PbLdhM/c60VHl698Gn1gY21m9vyC1Ucn69fPCA1y2EwcCB7IItseRMoNhdcWQnzt/OPCNA=="],
+
+    "@module-federation/sdk": ["@module-federation/sdk@0.22.0", "", {}, "sha512-x4aFNBKn2KVQRuNVC5A7SnrSCSqyfIWmm1DvubjbO9iKFe7ith5niw8dqSFBekYBg2Fwy+eMg4sEFNVvCAdo6g=="],
+
+    "@module-federation/webpack-bundler-runtime": ["@module-federation/webpack-bundler-runtime@0.22.0", "", { "dependencies": { "@module-federation/runtime": "0.22.0", "@module-federation/sdk": "0.22.0" } }, "sha512-aM8gCqXu+/4wBmJtVeMeeMN5guw3chf+2i6HajKtQv7SJfxV/f4IyNQJUeUQu9HfiAZHjqtMV5Lvq/Lvh8LdyA=="],
+
+    "@napi-rs/wasm-runtime": ["@napi-rs/wasm-runtime@1.0.7", "", { "dependencies": { "@emnapi/core": "^1.5.0", "@emnapi/runtime": "^1.5.0", "@tybys/wasm-util": "^0.10.1" } }, "sha512-SeDnOO0Tk7Okiq6DbXmmBODgOAb9dp9gjlphokTUxmt8U3liIP1ZsozBahH69j/RJv+Rfs6IwUKHTgQYJ/HBAw=="],
+
+    "@remotion/bundler": ["@remotion/bundler@4.0.483", "", { "dependencies": { "@remotion/media-parser": "4.0.483", "@remotion/studio": "4.0.483", "@remotion/studio-shared": "4.0.483", "@remotion/timeline-utils": "4.0.483", "@rspack/core": "1.7.11", "@rspack/plugin-react-refresh": "1.6.1", "css-loader": "7.1.4", "esbuild": "0.28.1", "react-refresh": "0.18.0", "remotion": "4.0.483", "style-loader": "4.0.0", "webpack": "5.105.0" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-5fQRMYgr2sxZPBOThnIVuFwHBq/FhusJ+Ke6xopga8io8ecK/mj9GaRXC3tgfMa+YWuu8ZSXZ0U9EsMZjjP5YQ=="],
+
+    "@remotion/canvas-capture": ["@remotion/canvas-capture@4.0.483", "", { "dependencies": { "mediabunny": "1.47.0", "remotion": "4.0.483" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-JABgbfvXwjFp1E61tlDN9gVAH8OoeF4kUUELNwG9kcNOE4ex8+vCYEO6VKIaXZ4l8A1PEAQ5EK//NheTJ80gfw=="],
+
+    "@remotion/cli": ["@remotion/cli@4.0.483", "", { "dependencies": { "@remotion/bundler": "4.0.483", "@remotion/media-utils": "4.0.483", "@remotion/player": "4.0.483", "@remotion/renderer": "4.0.483", "@remotion/studio": "4.0.483", "@remotion/studio-server": "4.0.483", "@remotion/studio-shared": "4.0.483", "dotenv": "17.3.1", "minimist": "1.2.6", "prompts": "2.4.2", "remotion": "4.0.483" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" }, "bin": { "remotion": "remotion-cli.js", "remotionb": "remotionb-cli.js", "remotiond": "remotiond-cli.js" } }, "sha512-z4TQcgTfQbSIV4GQpCvIihDL77M+leQelbxv962PmfSKTT7z3XnNN732PcZ4sei2+Xg+d2SD95K4tI5XBYs5Gw=="],
+
+    "@remotion/compositor-darwin-arm64": ["@remotion/compositor-darwin-arm64@4.0.483", "", { "os": "darwin", "cpu": "arm64" }, "sha512-CkEJXouGEoCs5PX3KOufkXrlT/Kgn0ZF7SEQ4meCYGYMZD+QPVtsmS1MXH8pQ4RHlFO6Tk7g0CIHMT3Y4yzpuA=="],
+
+    "@remotion/compositor-darwin-x64": ["@remotion/compositor-darwin-x64@4.0.483", "", { "os": "darwin", "cpu": "x64" }, "sha512-vDZK5U8FYbHGMjFC2lUgJRBz8KXwbwFSvEQi8FATD0roNg75SoaEJWrqAOIVv8v5eBjPvo18znDc36NLRYn1Eg=="],
+
+    "@remotion/compositor-linux-arm64-gnu": ["@remotion/compositor-linux-arm64-gnu@4.0.483", "", { "os": "linux", "cpu": "arm64" }, "sha512-1LzfYDY/DQxy3MIc9pCbTn1ObcBDcyI6MzODOwe1bTZl8TZxdUUt1M3hDrQ60AB6iHwruBAnzT9dnogiMIdSew=="],
+
+    "@remotion/compositor-linux-arm64-musl": ["@remotion/compositor-linux-arm64-musl@4.0.483", "", { "os": "linux", "cpu": "arm64" }, "sha512-nG1btxg0HXuLzulIqAg9NnxWyewZNrA0iLe82HdniaJjeWLORreGo4cEEJz1SjbDpQuPEY562XGkTO2DLKK5mA=="],
+
+    "@remotion/compositor-linux-x64-gnu": ["@remotion/compositor-linux-x64-gnu@4.0.483", "", { "os": "linux", "cpu": "x64" }, "sha512-CV4h6r2rNYh4P8utUzP6RM2vW2vq43nA3IvVOwRSuh9LwJh/7rwG53Oco4HanY/sstaNuymGpT57wdXwONU5CQ=="],
+
+    "@remotion/compositor-linux-x64-musl": ["@remotion/compositor-linux-x64-musl@4.0.483", "", { "os": "linux", "cpu": "x64" }, "sha512-moKvavbkoz5nteJZA4K6LMgTTlewhwIbtO7DYARZ3LK3ClGUKnYfFcmaPS15hMun02JPTOMIWbrlaszdR75mxA=="],
+
+    "@remotion/compositor-win32-x64-msvc": ["@remotion/compositor-win32-x64-msvc@4.0.483", "", { "os": "win32", "cpu": "x64" }, "sha512-eDpWe6Vy7ySHugwxlgaeohqdBwR1etxiymXzT13cgbPw2+p6d55z1tJ7VPTXyfu0o+UdyRTauWqD4msoxN0wow=="],
+
+    "@remotion/licensing": ["@remotion/licensing@4.0.483", "", {}, "sha512-GRtjykrxMmB5Cjpq1oVqeYIRXI95vid6afX0LTLfp1shD6MR4lTZRoRuopxrrZp1E4XFGXoY64b6dlIudgTyBQ=="],
+
+    "@remotion/media-parser": ["@remotion/media-parser@4.0.483", "", {}, "sha512-iva9Eof7QQX+3hGxH/N8pGi80wgdGuzOr825Zn7IuEe7IWdtRYWlFpCEghmyfhrwgaWa7RY51wg77ycR3c3nRg=="],
+
+    "@remotion/media-utils": ["@remotion/media-utils@4.0.483", "", { "dependencies": { "mediabunny": "1.47.0", "remotion": "4.0.483" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-4T4WQh/U95kCBzgmz/EL/HL8Zeox/AKAL5ufsehrZFgwlcvH1EsKNJH/RWaAtNPRLF+pskEOgFzPYaczHeI8hg=="],
+
+    "@remotion/player": ["@remotion/player@4.0.483", "", { "dependencies": { "remotion": "4.0.483" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-yyIQ9vinUqqS0fQeL52bPCWQIr8qDXCqQ4iys8P7dSZncdu8V29p4W2a0/4eKV8bv5+mjnJQ/U6nl9NxBF1hdA=="],
+
+    "@remotion/renderer": ["@remotion/renderer@4.0.483", "", { "dependencies": { "@remotion/licensing": "4.0.483", "@remotion/streaming": "4.0.483", "execa": "5.1.1", "remotion": "4.0.483", "source-map": "0.8.0-beta.0", "ws": "8.21.0" }, "optionalDependencies": { "@remotion/compositor-darwin-arm64": "4.0.483", "@remotion/compositor-darwin-x64": "4.0.483", "@remotion/compositor-linux-arm64-gnu": "4.0.483", "@remotion/compositor-linux-arm64-musl": "4.0.483", "@remotion/compositor-linux-x64-gnu": "4.0.483", "@remotion/compositor-linux-x64-musl": "4.0.483", "@remotion/compositor-win32-x64-msvc": "4.0.483" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-eSKdQqm8rcl+GNyOhFsBgcPYWMcxTJWHL5xaNrd037piCaL3sdJ57OEO/AbfEvvOO14zwUvlsONKjlkLlEVyKg=="],
+
+    "@remotion/streaming": ["@remotion/streaming@4.0.483", "", {}, "sha512-96rqrk+l5AfriHOqmqxMn8rI6UJfFY7r5UMDZoSKqXWzTOwj+0VWHTRl9ilZQMXhYACaMSA/5yrL9jgQEK8Yuw=="],
+
+    "@remotion/studio": ["@remotion/studio@4.0.483", "", { "dependencies": { "@jridgewell/trace-mapping": "0.3.31", "@remotion/canvas-capture": "4.0.483", "@remotion/media-utils": "4.0.483", "@remotion/player": "4.0.483", "@remotion/renderer": "4.0.483", "@remotion/studio-shared": "4.0.483", "@remotion/timeline-utils": "4.0.483", "@remotion/web-renderer": "4.0.483", "@remotion/zod-types": "4.0.483", "mediabunny": "1.47.0", "memfs": "3.4.3", "open": "8.4.2", "remotion": "4.0.483", "semver": "7.5.3", "zod": "4.3.6" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-gNa1Lw8NmHl0jwFb5fk7rzA+WFTJQpGDT/49A38t9jpEwoF+h1mKTgY8gA202apzjBHrEECdFE450npnBOUpUw=="],
+
+    "@remotion/studio-server": ["@remotion/studio-server@4.0.483", "", { "dependencies": { "@babel/parser": "7.24.1", "@babel/types": "7.24.0", "@remotion/bundler": "4.0.483", "@remotion/renderer": "4.0.483", "@remotion/studio-shared": "4.0.483", "memfs": "3.4.3", "open": "8.4.2", "prettier": "3.8.1", "recast": "0.23.11", "remotion": "4.0.483", "semver": "7.5.3" } }, "sha512-2FSLbVN5N8bgtQPX+RQRbis557tJJnVTOZuEBZndfC9NOoPdARlSgEnwVer9tBNczUlc6B3KrPxyPSlS3UjL+Q=="],
+
+    "@remotion/studio-shared": ["@remotion/studio-shared@4.0.483", "", { "dependencies": { "remotion": "4.0.483" } }, "sha512-aXxBYUgsWgphHVq7T7bz+ICMGzfii7pcX1IxS5hbLMLJHqlDtk9g+qcxm4kJ2Fjj/Gb5gERKiNzYym8WZTIM2Q=="],
+
+    "@remotion/timeline-utils": ["@remotion/timeline-utils@4.0.483", "", { "dependencies": { "mediabunny": "1.47.0" } }, "sha512-KTTMdpNA5uRLX+iisAITO+V9cJBk17F8EWvuUnAEVmAFOQTbGIyPI9HNw5pZmL7SlzOJdFjAtksTjipeYGkEug=="],
+
+    "@remotion/web-renderer": ["@remotion/web-renderer@4.0.483", "", { "dependencies": { "@mediabunny/aac-encoder": "1.47.0", "@mediabunny/flac-encoder": "1.47.0", "@mediabunny/mp3-encoder": "1.47.0", "@remotion/licensing": "4.0.483", "mediabunny": "1.47.0", "remotion": "4.0.483" }, "peerDependencies": { "react": ">=18.0.0", "react-dom": ">=18.0.0" } }, "sha512-14iURfVWA/hcF/rJvkid1ZR5nmnVhkTIf071FabCFi6kdViOSVBugSglJ8tUPvWVbWmxlXGDGQD9CSU18IATww=="],
+
+    "@remotion/zod-types": ["@remotion/zod-types@4.0.483", "", { "dependencies": { "remotion": "4.0.483" }, "peerDependencies": { "zod": "4.3.6" } }, "sha512-KIVYIzFpZBDB0wxGGQu5tDBr4XOYRzvrPXjmo6O/FI5Xx7O8hgvJmBs9VDkEwonAOft86sg79hI19F1DTX1p4w=="],
+
+    "@rspack/binding": ["@rspack/binding@1.7.11", "", { "optionalDependencies": { "@rspack/binding-darwin-arm64": "1.7.11", "@rspack/binding-darwin-x64": "1.7.11", "@rspack/binding-linux-arm64-gnu": "1.7.11", "@rspack/binding-linux-arm64-musl": "1.7.11", "@rspack/binding-linux-x64-gnu": "1.7.11", "@rspack/binding-linux-x64-musl": "1.7.11", "@rspack/binding-wasm32-wasi": "1.7.11", "@rspack/binding-win32-arm64-msvc": "1.7.11", "@rspack/binding-win32-ia32-msvc": "1.7.11", "@rspack/binding-win32-x64-msvc": "1.7.11" } }, "sha512-2MGdy2s2HimsDT444Bp5XnALzNRxuBNc7y0JzyuqKbHBywd4x2NeXyhWXXoxufaCFu5PBc9Qq9jyfjW2Aeh06Q=="],
+
+    "@rspack/binding-darwin-arm64": ["@rspack/binding-darwin-arm64@1.7.11", "", { "os": "darwin", "cpu": "arm64" }, "sha512-oduECiZVqbO5zlVw+q7Vy65sJFth99fWPTyucwvLJJtJkPL5n17Uiql2cYP6Ijn0pkqtf1SXgK8WjiKLG5bIig=="],
+
+    "@rspack/binding-darwin-x64": ["@rspack/binding-darwin-x64@1.7.11", "", { "os": "darwin", "cpu": "x64" }, "sha512-a1+TtTE9ap6RalgFi7FGIgkJP6O4Vy6ctv+9WGJy53E4kuqHR0RygzaiVxCI/GMc/vBT9vY23hyrpWb3d1vtXA=="],
+
+    "@rspack/binding-linux-arm64-gnu": ["@rspack/binding-linux-arm64-gnu@1.7.11", "", { "os": "linux", "cpu": "arm64" }, "sha512-P0QrGRPbTWu6RKWfN0bDtbnEps3rXH0MWIMreZABoUrVmNQKtXR6e73J3ub6a+di5s2+K0M2LJ9Bh2/H4UsDUA=="],
+
+    "@rspack/binding-linux-arm64-musl": ["@rspack/binding-linux-arm64-musl@1.7.11", "", { "os": "linux", "cpu": "arm64" }, "sha512-6ky7R43VMjWwmx3Yx7Jl7faLBBMAgMDt+/bN35RgwjiPgsIByz65EwytUVuW9rikB43BGHvA/eqlnjLrUzNBqw=="],
+
+    "@rspack/binding-linux-x64-gnu": ["@rspack/binding-linux-x64-gnu@1.7.11", "", { "os": "linux", "cpu": "x64" }, "sha512-cuOJMfCOvb2Wgsry5enXJ3iT1FGUjdPqtGUBVupQlEG4ntSYsQ2PtF4wIDVasR3wdxC5nQbipOrDiN/u6fYsdQ=="],
+
+    "@rspack/binding-linux-x64-musl": ["@rspack/binding-linux-x64-musl@1.7.11", "", { "os": "linux", "cpu": "x64" }, "sha512-CoK37hva4AmHGh3VCsQXmGr40L36m1/AdnN5LEjUX6kx5rEH7/1nEBN6Ii72pejqDVvk9anEROmPDiPw10tpFg=="],
+
+    "@rspack/binding-wasm32-wasi": ["@rspack/binding-wasm32-wasi@1.7.11", "", { "dependencies": { "@napi-rs/wasm-runtime": "1.0.7" }, "cpu": "none" }, "sha512-OtrmnPUVJMxjNa3eDMfHyPdtlLRmmp/aIm0fQHlAOATbZvlGm12q7rhPW5BXTu1yh+1rQ1/uqvz+SzKEZXuJaQ=="],
+
+    "@rspack/binding-win32-arm64-msvc": ["@rspack/binding-win32-arm64-msvc@1.7.11", "", { "os": "win32", "cpu": "arm64" }, "sha512-lObFW6e5lCWNgTBNwT//yiEDbsxm9QG4BYUojqeXxothuzJ/L6ibXz6+gLMvbOvLGV3nKgkXmx8GvT9WDKR0mA=="],
+
+    "@rspack/binding-win32-ia32-msvc": ["@rspack/binding-win32-ia32-msvc@1.7.11", "", { "os": "win32", "cpu": "ia32" }, "sha512-0pYGnZd8PPqNR68zQ8skamqNAXEA1sUfXuAdYcknIIRq2wsbiwFzIc0Pov1cIfHYab37G7sSIPBiOUdOWF5Ivw=="],
+
+    "@rspack/binding-win32-x64-msvc": ["@rspack/binding-win32-x64-msvc@1.7.11", "", { "os": "win32", "cpu": "x64" }, "sha512-EeQXayoQk/uBkI3pdoXfQBXNIUrADq56L3s/DFyM2pJeUDrWmhfIw2UFIGkYPTMSCo8F2JcdcGM32FGJrSnU0Q=="],
+
+    "@rspack/core": ["@rspack/core@1.7.11", "", { "dependencies": { "@module-federation/runtime-tools": "0.22.0", "@rspack/binding": "1.7.11", "@rspack/lite-tapable": "1.1.0" }, "peerDependencies": { "@swc/helpers": ">=0.5.1" }, "optionalPeers": ["@swc/helpers"] }, "sha512-rsD9b+Khmot5DwCMiB3cqTQo53ioPG3M/A7BySu8+0+RS7GCxKm+Z+mtsjtG/vsu4Tn2tcqCdZtA3pgLoJB+ew=="],
+
+    "@rspack/lite-tapable": ["@rspack/lite-tapable@1.1.0", "", {}, "sha512-E2B0JhYFmVAwdDiG14+DW0Di4Ze4Jg10Pc4/lILUrd5DRCaklduz2OvJ5HYQ6G+hd+WTzqQb3QnDNfK4yvAFYw=="],
+
+    "@rspack/plugin-react-refresh": ["@rspack/plugin-react-refresh@1.6.1", "", { "dependencies": { "error-stack-parser": "^2.1.4", "html-entities": "^2.6.0" }, "peerDependencies": { "react-refresh": ">=0.10.0 <1.0.0", "webpack-hot-middleware": "2.x" }, "optionalPeers": ["webpack-hot-middleware"] }, "sha512-eqqW5645VG3CzGzFgNg5HqNdHVXY+567PGjtDhhrM8t67caxmsSzRmT5qfoEIfBcGgFkH9vEg7kzXwmCYQdQDw=="],
+
+    "@tybys/wasm-util": ["@tybys/wasm-util@0.10.3", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-F3fo1MYrRJYL3zER0OUOmkutjr1Vp23m7OsSgp7nq4SP6OqX6C/56XFIPAl5bt3zaBRjmW7SGz3u/6LwFpYcOg=="],
+
+    "@types/dom-mediacapture-transform": ["@types/dom-mediacapture-transform@0.1.11", "", { "dependencies": { "@types/dom-webcodecs": "*" } }, "sha512-Y2p+nGf1bF2XMttBnsVPHUWzRRZzqUoJAKmiP10b5umnO6DDrWI0BrGDJy1pOHoOULVmGSfFNkQrAlC5dcj6nQ=="],
+
+    "@types/dom-webcodecs": ["@types/dom-webcodecs@0.1.13", "", {}, "sha512-O5hkiFIcjjszPIYyUSyvScyvrBoV3NOEEZx/pMlsu44TKzWNkLVBBxnxJz42in5n3QIolYOcBYFCPZZ0h8SkwQ=="],
+
+    "@types/eslint": ["@types/eslint@9.6.1", "", { "dependencies": { "@types/estree": "*", "@types/json-schema": "*" } }, "sha512-FXx2pKgId/WyYo2jXw63kk7/+TY7u7AziEJxJAnSFzHlqTAS3Ync6SvgYAN/k4/PQpnnVuzoMuVnByKK2qp0ag=="],
+
+    "@types/eslint-scope": ["@types/eslint-scope@3.7.7", "", { "dependencies": { "@types/eslint": "*", "@types/estree": "*" } }, "sha512-MzMFlSLBqNF2gcHWO0G1vP/YQyfvrxZ0bF+u7mzUdZ1/xK4A4sru+nraZz5i3iEIk1l1uyicaDVTB4QbbEkAYg=="],
+
+    "@types/estree": ["@types/estree@1.0.9", "", {}, "sha512-GhdPgy1el4/ImP05X05Uw4cw2/M93BCUmnEvWZNStlCzEKME4Fkk+YpoA5OiHNQmoS7Cafb8Xa3Pya8m1Qrzeg=="],
+
+    "@types/json-schema": ["@types/json-schema@7.0.15", "", {}, "sha512-5+fP8P8MFNC+AyZCDxrB2pkZFPGzqQWUzpSeuuVLvm8VMcorNYavBqoFcxK8bQz4Qsbn4oUEEem4wDLfcysGHA=="],
+
+    "@types/node": ["@types/node@26.0.1", "", { "dependencies": { "undici-types": "~8.3.0" } }, "sha512-fc3KiUoBt6kie0N9bIW3E47vZsuaMf0PM2AaUpLCLT0s/LvX1nxAim6Fc049cNxODPpGm6qRAuUOB86SkRuPQw=="],
+
+    "@types/react": ["@types/react@19.2.17", "", { "dependencies": { "csstype": "^3.2.2" } }, "sha512-MXfmqaVPEVgkBT/aY0aGCkRWWtByiYQXo3xdQ8r5RzuFrPiRn8Gar2tQdXSUQ2GKV3bkXckek89V8wQBY2Q/Aw=="],
+
+    "@types/react-dom": ["@types/react-dom@19.2.3", "", { "peerDependencies": { "@types/react": "^19.2.0" } }, "sha512-jp2L/eY6fn+KgVVQAOqYItbF0VY/YApe5Mz2F0aykSO8gx31bYCZyvSeYxCHKvzHG5eZjc+zyaS5BrBWya2+kQ=="],
+
+    "@webassemblyjs/ast": ["@webassemblyjs/ast@1.14.1", "", { "dependencies": { "@webassemblyjs/helper-numbers": "1.13.2", "@webassemblyjs/helper-wasm-bytecode": "1.13.2" } }, "sha512-nuBEDgQfm1ccRp/8bCQrx1frohyufl4JlbMMZ4P1wpeOfDhF6FQkxZJ1b/e+PLwr6X1Nhw6OLme5usuBWYBvuQ=="],
+
+    "@webassemblyjs/floating-point-hex-parser": ["@webassemblyjs/floating-point-hex-parser@1.13.2", "", {}, "sha512-6oXyTOzbKxGH4steLbLNOu71Oj+C8Lg34n6CqRvqfS2O71BxY6ByfMDRhBytzknj9yGUPVJ1qIKhRlAwO1AovA=="],
+
+    "@webassemblyjs/helper-api-error": ["@webassemblyjs/helper-api-error@1.13.2", "", {}, "sha512-U56GMYxy4ZQCbDZd6JuvvNV/WFildOjsaWD3Tzzvmw/mas3cXzRJPMjP83JqEsgSbyrmaGjBfDtV7KDXV9UzFQ=="],
+
+    "@webassemblyjs/helper-buffer": ["@webassemblyjs/helper-buffer@1.14.1", "", {}, "sha512-jyH7wtcHiKssDtFPRB+iQdxlDf96m0E39yb0k5uJVhFGleZFoNw1c4aeIcVUPPbXUVJ94wwnMOAqUHyzoEPVMA=="],
+
+    "@webassemblyjs/helper-numbers": ["@webassemblyjs/helper-numbers@1.13.2", "", { "dependencies": { "@webassemblyjs/floating-point-hex-parser": "1.13.2", "@webassemblyjs/helper-api-error": "1.13.2", "@xtuc/long": "4.2.2" } }, "sha512-FE8aCmS5Q6eQYcV3gI35O4J789wlQA+7JrqTTpJqn5emA4U2hvwJmvFRC0HODS+3Ye6WioDklgd6scJ3+PLnEA=="],
+
+    "@webassemblyjs/helper-wasm-bytecode": ["@webassemblyjs/helper-wasm-bytecode@1.13.2", "", {}, "sha512-3QbLKy93F0EAIXLh0ogEVR6rOubA9AoZ+WRYhNbFyuB70j3dRdwH9g+qXhLAO0kiYGlg3TxDV+I4rQTr/YNXkA=="],
+
+    "@webassemblyjs/helper-wasm-section": ["@webassemblyjs/helper-wasm-section@1.14.1", "", { "dependencies": { "@webassemblyjs/ast": "1.14.1", "@webassemblyjs/helper-buffer": "1.14.1", "@webassemblyjs/helper-wasm-bytecode": "1.13.2", "@webassemblyjs/wasm-gen": "1.14.1" } }, "sha512-ds5mXEqTJ6oxRoqjhWDU83OgzAYjwsCV8Lo/N+oRsNDmx/ZDpqalmrtgOMkHwxsG0iI//3BwWAErYRHtgn0dZw=="],
+
+    "@webassemblyjs/ieee754": ["@webassemblyjs/ieee754@1.13.2", "", { "dependencies": { "@xtuc/ieee754": "^1.2.0" } }, "sha512-4LtOzh58S/5lX4ITKxnAK2USuNEvpdVV9AlgGQb8rJDHaLeHciwG4zlGr0j/SNWlr7x3vO1lDEsuePvtcDNCkw=="],
+
+    "@webassemblyjs/leb128": ["@webassemblyjs/leb128@1.13.2", "", { "dependencies": { "@xtuc/long": "4.2.2" } }, "sha512-Lde1oNoIdzVzdkNEAWZ1dZ5orIbff80YPdHx20mrHwHrVNNTjNr8E3xz9BdpcGqRQbAEa+fkrCb+fRFTl/6sQw=="],
+
+    "@webassemblyjs/utf8": ["@webassemblyjs/utf8@1.13.2", "", {}, "sha512-3NQWGjKTASY1xV5m7Hr0iPeXD9+RDobLll3T9d2AO+g3my8xy5peVyjSag4I50mR1bBSN/Ct12lo+R9tJk0NZQ=="],
+
+    "@webassemblyjs/wasm-edit": ["@webassemblyjs/wasm-edit@1.14.1", "", { "dependencies": { "@webassemblyjs/ast": "1.14.1", "@webassemblyjs/helper-buffer": "1.14.1", "@webassemblyjs/helper-wasm-bytecode": "1.13.2", "@webassemblyjs/helper-wasm-section": "1.14.1", "@webassemblyjs/wasm-gen": "1.14.1", "@webassemblyjs/wasm-opt": "1.14.1", "@webassemblyjs/wasm-parser": "1.14.1", "@webassemblyjs/wast-printer": "1.14.1" } }, "sha512-RNJUIQH/J8iA/1NzlE4N7KtyZNHi3w7at7hDjvRNm5rcUXa00z1vRz3glZoULfJ5mpvYhLybmVcwcjGrC1pRrQ=="],
+
+    "@webassemblyjs/wasm-gen": ["@webassemblyjs/wasm-gen@1.14.1", "", { "dependencies": { "@webassemblyjs/ast": "1.14.1", "@webassemblyjs/helper-wasm-bytecode": "1.13.2", "@webassemblyjs/ieee754": "1.13.2", "@webassemblyjs/leb128": "1.13.2", "@webassemblyjs/utf8": "1.13.2" } }, "sha512-AmomSIjP8ZbfGQhumkNvgC33AY7qtMCXnN6bL2u2Js4gVCg8fp735aEiMSBbDR7UQIj90n4wKAFUSEd0QN2Ukg=="],
+
+    "@webassemblyjs/wasm-opt": ["@webassemblyjs/wasm-opt@1.14.1", "", { "dependencies": { "@webassemblyjs/ast": "1.14.1", "@webassemblyjs/helper-buffer": "1.14.1", "@webassemblyjs/wasm-gen": "1.14.1", "@webassemblyjs/wasm-parser": "1.14.1" } }, "sha512-PTcKLUNvBqnY2U6E5bdOQcSM+oVP/PmrDY9NzowJjislEjwP/C4an2303MCVS2Mg9d3AJpIGdUFIQQWbPds0Sw=="],
+
+    "@webassemblyjs/wasm-parser": ["@webassemblyjs/wasm-parser@1.14.1", "", { "dependencies": { "@webassemblyjs/ast": "1.14.1", "@webassemblyjs/helper-api-error": "1.13.2", "@webassemblyjs/helper-wasm-bytecode": "1.13.2", "@webassemblyjs/ieee754": "1.13.2", "@webassemblyjs/leb128": "1.13.2", "@webassemblyjs/utf8": "1.13.2" } }, "sha512-JLBl+KZ0R5qB7mCnud/yyX08jWFw5MsoalJ1pQ4EdFlgj9VdXKGuENGsiCIjegI1W7p91rUlcB/LB5yRJKNTcQ=="],
+
+    "@webassemblyjs/wast-printer": ["@webassemblyjs/wast-printer@1.14.1", "", { "dependencies": { "@webassemblyjs/ast": "1.14.1", "@xtuc/long": "4.2.2" } }, "sha512-kPSSXE6De1XOR820C90RIo2ogvZG+c3KiHzqUoO/F34Y2shGzesfqv7o57xrxovZJH/MetF5UjroJ/R/3isoiw=="],
+
+    "@xtuc/ieee754": ["@xtuc/ieee754@1.2.0", "", {}, "sha512-DX8nKgqcGwsc0eJSqYt5lwP4DH5FlHnmuWWBRy7X0NcaGR0ZtuyeESgMwTYVEtxmsNGY+qit4QYT/MIYTOTPeA=="],
+
+    "@xtuc/long": ["@xtuc/long@4.2.2", "", {}, "sha512-NuHqBY1PB/D8xU6s/thBgOAiAP7HOYDQ32+BFZILJ8ivkUkAHQnWfn6WhL79Owj1qmUnoN/YPhktdIoucipkAQ=="],
+
+    "acorn": ["acorn@8.17.0", "", { "bin": { "acorn": "bin/acorn" } }, "sha512-xRQbDb9BnwDafYNn6Vwl839DYVjqXYb1XVGtWAZ1kcDc6iwAL4hg3B1dZlRiuENFeO2H53gFG3in621AdERVAg=="],
+
+    "acorn-import-phases": ["acorn-import-phases@1.0.4", "", { "peerDependencies": { "acorn": "^8.14.0" } }, "sha512-wKmbr/DDiIXzEOiWrTTUcDm24kQ2vGfZQvM2fwg2vXqR5uW6aapr7ObPtj1th32b9u90/Pf4AItvdTh42fBmVQ=="],
+
+    "ajv": ["ajv@8.20.0", "", { "dependencies": { "fast-deep-equal": "^3.1.3", "fast-uri": "^3.0.1", "json-schema-traverse": "^1.0.0", "require-from-string": "^2.0.2" } }, "sha512-Thbli+OlOj+iMPYFBVBfJ3OmCAnaSyNn4M1vz9T6Gka5Jt9ba/HIR56joy65tY6kx/FCF5VXNB819Y7/GUrBGA=="],
+
+    "ajv-formats": ["ajv-formats@2.1.1", "", { "dependencies": { "ajv": "^8.0.0" } }, "sha512-Wx0Kx52hxE7C18hkMEggYlEifqWZtYaRgouJor+WMdPnQyEK13vgEWyVNup7SoeeoLMsr4kf5h6dOW11I15MUA=="],
+
+    "ajv-keywords": ["ajv-keywords@5.1.0", "", { "dependencies": { "fast-deep-equal": "^3.1.3" }, "peerDependencies": { "ajv": "^8.8.2" } }, "sha512-YCS/JNFAUyr5vAuhk1DWm1CBxRHW9LbJ2ozWeemrIqpbsqKjHVxYPyi5GC0rjZIT5JxJ3virVTS8wk4i/Z+krw=="],
+
+    "ast-types": ["ast-types@0.16.1", "", { "dependencies": { "tslib": "^2.0.1" } }, "sha512-6t10qk83GOG8p0vKmaCr8eiilZwO171AvbROMtvvNiwrTly62t+7XkA8RdIIVbpMhCASAsxgAzdRSwh6nw/5Dg=="],
+
+    "baseline-browser-mapping": ["baseline-browser-mapping@2.10.40", "", { "bin": { "baseline-browser-mapping": "dist/cli.cjs" } }, "sha512-BSSLZ9/Cjjv7Gtj5B68ZzXcXUg8iOf3fme+FCuh8rC/Go+Kmh8cox7M3A8dolou16s64QjLPOSdngh7GxXvkSw=="],
+
+    "browserslist": ["browserslist@4.28.4", "", { "dependencies": { "baseline-browser-mapping": "^2.10.38", "caniuse-lite": "^1.0.30001799", "electron-to-chromium": "^1.5.376", "node-releases": "^2.0.48", "update-browserslist-db": "^1.2.3" }, "bin": { "browserslist": "cli.js" } }, "sha512-MTc8i/x9jBQd1iMw2CFGS+rwMa07eYjLR0CCTLDACl9xhxy+nIs3KeML/biicXtk9JrZ6dnnTatmc7ErPXIxqw=="],
+
+    "buffer-from": ["buffer-from@1.1.2", "", {}, "sha512-E+XQCRwSbaaiChtv6k6Dwgc+bx+Bs6vuKJHHl5kox/BaKbhiXzqQOwK4cO22yElGp2OCmjwVhT3HmxgyPGnJfQ=="],
+
+    "caniuse-lite": ["caniuse-lite@1.0.30001799", "", {}, "sha512-hG1bReV+OUU+MOqK4t/ZWI0tZOyz3rqS9XuhOUz1cIcbwBKjOyJEJuw9ER5JuNyqxNk8u/JUVbGibBOL1yrjFw=="],
+
+    "chrome-trace-event": ["chrome-trace-event@1.0.4", "", {}, "sha512-rNjApaLzuwaOTjCiT8lSDdGN1APCiqkChLMJxJPWLunPAt5fy8xgU9/jNOchV84wfIxrA0lRQB7oCT8jrn/wrQ=="],
+
+    "commander": ["commander@2.20.3", "", {}, "sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ=="],
+
+    "cross-spawn": ["cross-spawn@7.0.6", "", { "dependencies": { "path-key": "^3.1.0", "shebang-command": "^2.0.0", "which": "^2.0.1" } }, "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA=="],
+
+    "css-loader": ["css-loader@7.1.4", "", { "dependencies": { "icss-utils": "^5.1.0", "postcss": "^8.4.40", "postcss-modules-extract-imports": "^3.1.0", "postcss-modules-local-by-default": "^4.0.5", "postcss-modules-scope": "^3.2.0", "postcss-modules-values": "^4.0.0", "postcss-value-parser": "^4.2.0", "semver": "^7.6.3" }, "peerDependencies": { "@rspack/core": "0.x || ^1.0.0 || ^2.0.0-0", "webpack": "^5.27.0" }, "optionalPeers": ["@rspack/core", "webpack"] }, "sha512-vv3J9tlOl04WjiMvHQI/9tmIrCxVrj6PFbHemBB1iihpeRbi/I4h033eoFIhwxBBqLhI0KYFS7yvynBFhIZfTw=="],
+
+    "cssesc": ["cssesc@3.0.0", "", { "bin": { "cssesc": "bin/cssesc" } }, "sha512-/Tb/JcjK111nNScGob5MNtsntNM1aCNUDipB/TkwZFhyDrrE47SOx/18wF2bbjgc3ZzCSKW1T5nt5EbFoAz/Vg=="],
+
+    "csstype": ["csstype@3.2.3", "", {}, "sha512-z1HGKcYy2xA8AGQfwrn0PAy+PB7X/GSj3UVJW9qKyn43xWa+gl5nXmU4qqLMRzWVLFC8KusUX8T/0kCiOYpAIQ=="],
+
+    "define-lazy-prop": ["define-lazy-prop@2.0.0", "", {}, "sha512-Ds09qNh8yw3khSjiJjiUInaGX9xlqZDY7JVryGxdxV7NPeuqQfplOpQ66yJFZut3jLa5zOwkXw1g9EI2uKh4Og=="],
+
+    "dotenv": ["dotenv@17.3.1", "", {}, "sha512-IO8C/dzEb6O3F9/twg6ZLXz164a2fhTnEWb95H23Dm4OuN+92NmEAlTrupP9VW6Jm3sO26tQlqyvyi4CsnY9GA=="],
+
+    "electron-to-chromium": ["electron-to-chromium@1.5.379", "", {}, "sha512-v/qV5aV5EUA2pGilzUCq5/eyOloZAqDZBu9UMBIzgPpLlprjSR6zswsWBTv0KpqxLGUAZEwhO95ZCt7srymNVA=="],
+
+    "enhanced-resolve": ["enhanced-resolve@5.24.1", "", { "dependencies": { "graceful-fs": "^4.2.4", "tapable": "^2.3.3" } }, "sha512-7DdUaTjmNwMcH2gLr1qycesKII3BK4RLy/mdAb7x10Lq7bR4aNKHt1BR1ZALSv0rPM/hF5wYF0PhGop/rJm8vw=="],
+
+    "error-stack-parser": ["error-stack-parser@2.1.4", "", { "dependencies": { "stackframe": "^1.3.4" } }, "sha512-Sk5V6wVazPhq5MhpO+AUxJn5x7XSXGl1R93Vn7i+zS15KDVxQijejNCrz8340/2bgLBjR9GtEG8ZVKONDjcqGQ=="],
+
+    "es-module-lexer": ["es-module-lexer@2.1.0", "", {}, "sha512-n27zTYMjYu1aj4MjCWzSP7G9r75utsaoc8m61weK+W8JMBGGQybd43GstCXZ3WNmSFtGT9wi59qQTW6mhTR5LQ=="],
+
+    "esbuild": ["esbuild@0.28.1", "", { "optionalDependencies": { "@esbuild/aix-ppc64": "0.28.1", "@esbuild/android-arm": "0.28.1", "@esbuild/android-arm64": "0.28.1", "@esbuild/android-x64": "0.28.1", "@esbuild/darwin-arm64": "0.28.1", "@esbuild/darwin-x64": "0.28.1", "@esbuild/freebsd-arm64": "0.28.1", "@esbuild/freebsd-x64": "0.28.1", "@esbuild/linux-arm": "0.28.1", "@esbuild/linux-arm64": "0.28.1", "@esbuild/linux-ia32": "0.28.1", "@esbuild/linux-loong64": "0.28.1", "@esbuild/linux-mips64el": "0.28.1", "@esbuild/linux-ppc64": "0.28.1", "@esbuild/linux-riscv64": "0.28.1", "@esbuild/linux-s390x": "0.28.1", "@esbuild/linux-x64": "0.28.1", "@esbuild/netbsd-arm64": "0.28.1", "@esbuild/netbsd-x64": "0.28.1", "@esbuild/openbsd-arm64": "0.28.1", "@esbuild/openbsd-x64": "0.28.1", "@esbuild/openharmony-arm64": "0.28.1", "@esbuild/sunos-x64": "0.28.1", "@esbuild/win32-arm64": "0.28.1", "@esbuild/win32-ia32": "0.28.1", "@esbuild/win32-x64": "0.28.1" }, "bin": { "esbuild": "bin/esbuild" } }, "sha512-HrJrvZv5ayxBzPfwphOoNzkzOIIlifzk0KJrGK2c8R4+LKpMtpYLQeUdjnwjWv/LZlkH2laZk+4w78pi99D4Vw=="],
+
+    "escalade": ["escalade@3.2.0", "", {}, "sha512-WUj2qlxaQtO4g6Pq5c29GTcWGDyd8itL8zTlipgECz3JesAiiOKotd8JU6otB3PACgG6xkJUyVhboMS+bje/jA=="],
+
+    "eslint-scope": ["eslint-scope@5.1.1", "", { "dependencies": { "esrecurse": "^4.3.0", "estraverse": "^4.1.1" } }, "sha512-2NxwbF/hZ0KpepYN0cNbo+FN6XoK7GaHlQhgx/hIZl6Va0bF45RQOOwhLIy8lQDbuCiadSLCBnH2CFYquit5bw=="],
+
+    "esprima": ["esprima@4.0.1", "", { "bin": { "esparse": "./bin/esparse.js", "esvalidate": "./bin/esvalidate.js" } }, "sha512-eGuFFw7Upda+g4p+QHvnW0RyTX/SVeJBDM/gCtMARO0cLuT2HcEKnTPvhjV6aGeqrCB/sbNop0Kszm0jsaWU4A=="],
+
+    "esrecurse": ["esrecurse@4.3.0", "", { "dependencies": { "estraverse": "^5.2.0" } }, "sha512-KmfKL3b6G+RXvP8N1vr3Tq1kL/oCFgn2NYXEtqP8/L3pKapUA4G8cFVaoF3SU323CD4XypR/ffioHmkti6/Tag=="],
+
+    "estraverse": ["estraverse@4.3.0", "", {}, "sha512-39nnKffWz8xN1BU/2c79n9nB9HDzo0niYUqx6xyqUnyoAnQyyWpOTdZEeiCch8BBu515t4wp9ZmgVfVhn9EBpw=="],
+
+    "events": ["events@3.3.0", "", {}, "sha512-mQw+2fkQbALzQ7V0MY0IqdnXNOeTtP4r0lN9z7AAawCXgqea7bDii20AYrIBrFd/Hx0M2Ocz6S111CaFkUcb0Q=="],
+
+    "execa": ["execa@5.1.1", "", { "dependencies": { "cross-spawn": "^7.0.3", "get-stream": "^6.0.0", "human-signals": "^2.1.0", "is-stream": "^2.0.0", "merge-stream": "^2.0.0", "npm-run-path": "^4.0.1", "onetime": "^5.1.2", "signal-exit": "^3.0.3", "strip-final-newline": "^2.0.0" } }, "sha512-8uSpZZocAZRBAPIEINJj3Lo9HyGitllczc27Eh5YYojjMFMn8yHMDMaUHE2Jqfq05D/wucwI4JGURyXt1vchyg=="],
+
+    "fast-deep-equal": ["fast-deep-equal@3.1.3", "", {}, "sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q=="],
+
+    "fast-uri": ["fast-uri@3.1.2", "", {}, "sha512-rVjf7ArG3LTk+FS6Yw81V1DLuZl1bRbNrev6Tmd/9RaroeeRRJhAt7jg/6YFxbvAQXUCavSoZhPPj6oOx+5KjQ=="],
+
+    "fs-monkey": ["fs-monkey@1.0.3", "", {}, "sha512-cybjIfiiE+pTWicSCLFHSrXZ6EilF30oh91FDP9S2B051prEa7QWfrVTQm10/dDpswBDXZugPa1Ogu8Yh+HV0Q=="],
+
+    "get-stream": ["get-stream@6.0.1", "", {}, "sha512-ts6Wi+2j3jQjqi70w5AlN8DFnkSwC+MqmxEzdEALB2qXZYV3X/b1CTfgPLGJNMeAWxdPfU8FO1ms3NUfaHCPYg=="],
+
+    "glob-to-regexp": ["glob-to-regexp@0.4.1", "", {}, "sha512-lkX1HJXwyMcprw/5YUZc2s7DrpAiHB21/V+E1rHUrVNokkvB6bqMzT0VfV6/86ZNabt1k14YOIaT7nDvOX3Iiw=="],
+
+    "graceful-fs": ["graceful-fs@4.2.11", "", {}, "sha512-RbJ5/jmFcNNCcDV5o9eTnBLJ/HszWV0P73bc+Ff4nS/rJj+YaS6IGyiOL0VoBYX+l1Wrl3k63h/KrH+nhJ0XvQ=="],
+
+    "has-flag": ["has-flag@4.0.0", "", {}, "sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ=="],
+
+    "html-entities": ["html-entities@2.6.0", "", {}, "sha512-kig+rMn/QOVRvr7c86gQ8lWXq+Hkv6CbAH1hLu+RG338StTpE8Z0b44SDVaqVu7HGKf27frdmUYEs9hTUX/cLQ=="],
+
+    "human-signals": ["human-signals@2.1.0", "", {}, "sha512-B4FFZ6q/T2jhhksgkbEW3HBvWIfDW85snkQgawt07S7J5QXTk6BkNV+0yAeZrM5QpMAdYlocGoljn0sJ/WQkFw=="],
+
+    "icss-utils": ["icss-utils@5.1.0", "", { "peerDependencies": { "postcss": "^8.1.0" } }, "sha512-soFhflCVWLfRNOPU3iv5Z9VUdT44xFRbzjLsEzSr5AQmgqPMTHdU3PMT1Cf1ssx8fLNJDA1juftYl+PUcv3MqA=="],
+
+    "is-docker": ["is-docker@2.2.1", "", { "bin": { "is-docker": "cli.js" } }, "sha512-F+i2BKsFrH66iaUFc0woD8sLy8getkwTwtOBjvs56Cx4CgJDeKQeqfz8wAYiSb8JOprWhHH5p77PbmYCvvUuXQ=="],
+
+    "is-stream": ["is-stream@2.0.1", "", {}, "sha512-hFoiJiTl63nn+kstHGBtewWSKnQLpyb155KHheA1l39uvtO9nWIop1p3udqPcUd/xbF1VLMO4n7OI6p7RbngDg=="],
+
+    "is-wsl": ["is-wsl@2.2.0", "", { "dependencies": { "is-docker": "^2.0.0" } }, "sha512-fKzAra0rGJUUBwGBgNkHZuToZcn+TtXHpeCgmkMJMMYx1sQDYaCSyjJBSCa2nH1DGm7s3n1oBnohoVTBaN7Lww=="],
+
+    "isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
+
+    "jest-worker": ["jest-worker@27.5.1", "", { "dependencies": { "@types/node": "*", "merge-stream": "^2.0.0", "supports-color": "^8.0.0" } }, "sha512-7vuh85V5cdDofPyxn58nrPjBktZo0u9x1g8WtjQol+jZDaE+fhN+cIvTj11GndBnMnyfrUOG1sZQxCdjKh+DKg=="],
+
+    "json-parse-even-better-errors": ["json-parse-even-better-errors@2.3.1", "", {}, "sha512-xyFwyhro/JEof6Ghe2iz2NcXoj2sloNsWr/XsERDK/oiPCfaNhl5ONfp+jQdAZRQQ0IJWNzH9zIZF7li91kh2w=="],
+
+    "json-schema-traverse": ["json-schema-traverse@1.0.0", "", {}, "sha512-NM8/P9n3XjXhIZn1lLhkFaACTOURQXjWhV4BA/RnOv8xvgqtqpAX9IO4mRQxSx1Rlo4tqzeqb0sOlruaOy3dug=="],
+
+    "kleur": ["kleur@3.0.3", "", {}, "sha512-eTIzlVOSUR+JxdDFepEYcBMtZ9Qqdef+rnzWdRZuMbOywu5tO2w2N7rqjoANZ5k9vywhL6Br1VRjUIgTQx4E8w=="],
+
+    "loader-runner": ["loader-runner@4.3.2", "", {}, "sha512-DFEqQ3ihfS9blba08cLfYf1NRAIEm+dDjic073DRDc3/JspI/8wYmtDsHwd3+4hwvdxSK7PGaElfTmm0awWJ4w=="],
+
+    "lodash.sortby": ["lodash.sortby@4.7.0", "", {}, "sha512-HDWXG8isMntAyRF5vZ7xKuEvOhT4AhlRt/3czTSjvGUxjYCBVRQY48ViDHyfYz9VIoBkW4TMGQNapx+l3RUwdA=="],
+
+    "lru-cache": ["lru-cache@6.0.0", "", { "dependencies": { "yallist": "^4.0.0" } }, "sha512-Jo6dJ04CmSjuznwJSS3pUeWmd/H0ffTlkXXgwZi+eq1UCmqQwCh+eLsYOYCwY991i2Fah4h1BEMCx4qThGbsiA=="],
+
+    "mediabunny": ["mediabunny@1.47.0", "", { "dependencies": { "@types/dom-mediacapture-transform": "^0.1.11", "@types/dom-webcodecs": "0.1.13" } }, "sha512-XQMZAcaKPkJ7hQ/Q2fvBdl3ZazQl2WVxDysUbJWh4PuAnLoerdsQBdPTDWdUdK6hh26LQ8Ue94MLLnmpWvlUYg=="],
+
+    "memfs": ["memfs@3.4.3", "", { "dependencies": { "fs-monkey": "1.0.3" } }, "sha512-eivjfi7Ahr6eQTn44nvTnR60e4a1Fs1Via2kCR5lHo/kyNoiMWaXCNJ/GpSd0ilXas2JSOl9B5FTIhflXu0hlg=="],
+
+    "merge-stream": ["merge-stream@2.0.0", "", {}, "sha512-abv/qOcuPfk3URPfDzmZU1LKmuw8kT+0nIHvKrKgFrwifol/doWcdA4ZqsWQ8ENrFKkd67Mfpo/LovbIUsbt3w=="],
+
+    "mime-db": ["mime-db@1.52.0", "", {}, "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg=="],
+
+    "mime-types": ["mime-types@2.1.35", "", { "dependencies": { "mime-db": "1.52.0" } }, "sha512-ZDY+bPm5zTTF+YpCrAU9nK0UgICYPT0QtT1NZWFv4s++TNkcgVaT0g6+4R2uI4MjQjzysHB1zxuWL50hzaeXiw=="],
+
+    "mimic-fn": ["mimic-fn@2.1.0", "", {}, "sha512-OqbOk5oEQeAZ8WXWydlu9HJjz9WVdEIvamMCcXmuqUYjTknH/sqsWvhQ3vgwKFRR1HpjvNBKQ37nbJgYzGqGcg=="],
+
+    "minimist": ["minimist@1.2.6", "", {}, "sha512-Jsjnk4bw3YJqYzbdyBiNsPWHPfO++UGG749Cxs6peCu5Xg4nrena6OVxOYxrQTqww0Jmwt+Ref8rggumkTLz9Q=="],
+
+    "nanoid": ["nanoid@3.3.15", "", { "bin": { "nanoid": "bin/nanoid.cjs" } }, "sha512-y7Wygv/7mEOvxTuEQDB8StXdMRBWf1kR/tlhAzBRUFkB2jfcLOAxO/SHmOO2zgz1pVgK29/kyupn059/bCHdjA=="],
+
+    "neo-async": ["neo-async@2.6.2", "", {}, "sha512-Yd3UES5mWCSqR+qNT93S3UoYUkqAZ9lLg8a7g9rimsWmYGK8cVToA4/sF3RrshdyV3sAGMXVUmpMYOw+dLpOuw=="],
+
+    "node-releases": ["node-releases@2.0.50", "", {}, "sha512-J6l92tKHX6w8Jy5nO1Vuc01NoIiRGi/d6qBKVxh+IQ8Cr3b6HbVNfKiF8ZpFKufTwpwxMmce2W3iQZ861ZRyTg=="],
+
+    "npm-run-path": ["npm-run-path@4.0.1", "", { "dependencies": { "path-key": "^3.0.0" } }, "sha512-S48WzZW777zhNIrn7gxOlISNAqi9ZC/uQFnRdbeIHhZhCA6UqpkOT8T1G7BvfdgP4Er8gF4sUbaS0i7QvIfCWw=="],
+
+    "onetime": ["onetime@5.1.2", "", { "dependencies": { "mimic-fn": "^2.1.0" } }, "sha512-kbpaSSGJTWdAY5KPVeMOKXSrPtr8C8C7wodJbcsd51jRnmD+GZu8Y0VoU6Dm5Z4vWr0Ig/1NKuWRKf7j5aaYSg=="],
+
+    "open": ["open@8.4.2", "", { "dependencies": { "define-lazy-prop": "^2.0.0", "is-docker": "^2.1.1", "is-wsl": "^2.2.0" } }, "sha512-7x81NCL719oNbsq/3mh+hVrAWmFuEYUqrq/Iw3kUzH8ReypT9QQ0BLoJS7/G9k6N81XjW4qHWtjWwe/9eLy1EQ=="],
+
+    "path-key": ["path-key@3.1.1", "", {}, "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q=="],
+
+    "picocolors": ["picocolors@1.1.1", "", {}, "sha512-xceH2snhtb5M9liqDsmEw56le376mTZkEX/jEb/RxNFyegNul7eNslCXP9FDj/Lcu0X8KEyMceP2ntpaHrDEVA=="],
+
+    "postcss": ["postcss@8.5.15", "", { "dependencies": { "nanoid": "^3.3.12", "picocolors": "^1.1.1", "source-map-js": "^1.2.1" } }, "sha512-FfR8sjd4em2T6fb3I2MwAJU7HWVMr9zba+enmQeeWFfCbm+UOC/0X4DS8XtpUTMwWMGbjKYP7xjfNekzyGmB3A=="],
+
+    "postcss-modules-extract-imports": ["postcss-modules-extract-imports@3.1.0", "", { "peerDependencies": { "postcss": "^8.1.0" } }, "sha512-k3kNe0aNFQDAZGbin48pL2VNidTF0w4/eASDsxlyspobzU3wZQLOGj7L9gfRe0Jo9/4uud09DsjFNH7winGv8Q=="],
+
+    "postcss-modules-local-by-default": ["postcss-modules-local-by-default@4.2.0", "", { "dependencies": { "icss-utils": "^5.0.0", "postcss-selector-parser": "^7.0.0", "postcss-value-parser": "^4.1.0" }, "peerDependencies": { "postcss": "^8.1.0" } }, "sha512-5kcJm/zk+GJDSfw+V/42fJ5fhjL5YbFDl8nVdXkJPLLW+Vf9mTD5Xe0wqIaDnLuL2U6cDNpTr+UQ+v2HWIBhzw=="],
+
+    "postcss-modules-scope": ["postcss-modules-scope@3.2.1", "", { "dependencies": { "postcss-selector-parser": "^7.0.0" }, "peerDependencies": { "postcss": "^8.1.0" } }, "sha512-m9jZstCVaqGjTAuny8MdgE88scJnCiQSlSrOWcTQgM2t32UBe+MUmFSO5t7VMSfAf/FJKImAxBav8ooCHJXCJA=="],
+
+    "postcss-modules-values": ["postcss-modules-values@4.0.0", "", { "dependencies": { "icss-utils": "^5.0.0" }, "peerDependencies": { "postcss": "^8.1.0" } }, "sha512-RDxHkAiEGI78gS2ofyvCsu7iycRv7oqw5xMWn9iMoR0N/7mf9D50ecQqUo5BZ9Zh2vH4bCUR/ktCqbB9m8vJjQ=="],
+
+    "postcss-selector-parser": ["postcss-selector-parser@7.1.4", "", { "dependencies": { "cssesc": "^3.0.0", "util-deprecate": "^1.0.2" } }, "sha512-HeP7D2wyhkR+XaK6v4W8oRF62Dsz4flyuczALJp61GckGm42u1saSSJ/0auvcBqxs3jMRFEcPK34At/0JBKdOg=="],
+
+    "postcss-value-parser": ["postcss-value-parser@4.2.0", "", {}, "sha512-1NNCs6uurfkVbeXG4S8JFT9t19m45ICnif8zWLd5oPSZ50QnwMfK+H3jv408d4jw/7Bttv5axS5IiHoLaVNHeQ=="],
+
+    "prettier": ["prettier@3.8.1", "", { "bin": { "prettier": "bin/prettier.cjs" } }, "sha512-UOnG6LftzbdaHZcKoPFtOcCKztrQ57WkHDeRD9t/PTQtmT0NHSeWWepj6pS0z/N7+08BHFDQVUrfmfMRcZwbMg=="],
+
+    "prompts": ["prompts@2.4.2", "", { "dependencies": { "kleur": "^3.0.3", "sisteransi": "^1.0.5" } }, "sha512-NxNv/kLguCA7p3jE8oL2aEBsrJWgAakBpgmgK6lpPWV+WuOmY6r2/zbAVnP+T8bQlA0nzHXSJSJW0Hq7ylaD2Q=="],
+
+    "punycode": ["punycode@2.3.1", "", {}, "sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg=="],
+
+    "react": ["react@19.2.7", "", {}, "sha512-HNe9WslTbXmFK8o8cmwgAeJFSBvt1bPdHCVKtaaV+WlAN36mpT4hcRpwbf3fY56ar2oIXzsBpOAiIRHAdY0OlQ=="],
+
+    "react-dom": ["react-dom@19.2.7", "", { "dependencies": { "scheduler": "^0.27.0" }, "peerDependencies": { "react": "^19.2.7" } }, "sha512-t0BRVXvbiE/o20Hfw669rLbMCDWtYZLvmJigy2f0MxsXF+71pxhR3xOkspmsO8h3ZlNzyibAmtCa3l4lYKk6gQ=="],
+
+    "react-refresh": ["react-refresh@0.18.0", "", {}, "sha512-QgT5//D3jfjJb6Gsjxv0Slpj23ip+HtOpnNgnb2S5zU3CB26G/IDPGoy4RJB42wzFE46DRsstbW6tKHoKbhAxw=="],
+
+    "recast": ["recast@0.23.11", "", { "dependencies": { "ast-types": "^0.16.1", "esprima": "~4.0.0", "source-map": "~0.6.1", "tiny-invariant": "^1.3.3", "tslib": "^2.0.1" } }, "sha512-YTUo+Flmw4ZXiWfQKGcwwc11KnoRAYgzAE2E7mXKCjSviTKShtxBsN6YUUBB2gtaBzKzeKunxhUwNHQuRryhWA=="],
+
+    "remotion": ["remotion@4.0.483", "", { "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-lf4xq4Twn75TQeTavFLrTE4zdck7EKBSx07ZrPv4om40Sist+3G0kq7NNzSjMeJ6G2Wx6vI+0oICD/vv4sGWtg=="],
+
+    "require-from-string": ["require-from-string@2.0.2", "", {}, "sha512-Xf0nWe6RseziFMu+Ap9biiUbmplq6S9/p+7w7YXP/JBHhrUDDUhwa+vANyubuqfZWTveU//DYVGsDG7RKL/vEw=="],
+
+    "scheduler": ["scheduler@0.27.0", "", {}, "sha512-eNv+WrVbKu1f3vbYJT/xtiF5syA5HPIMtf9IgY/nKg0sWqzAUEvqY/xm7OcZc/qafLx/iO9FgOmeSAp4v5ti/Q=="],
+
+    "schema-utils": ["schema-utils@4.3.3", "", { "dependencies": { "@types/json-schema": "^7.0.9", "ajv": "^8.9.0", "ajv-formats": "^2.1.1", "ajv-keywords": "^5.1.0" } }, "sha512-eflK8wEtyOE6+hsaRVPxvUKYCpRgzLqDTb8krvAsRIwOGlHoSgYLgBXoubGgLd2fT41/OUYdb48v4k4WWHQurA=="],
+
+    "semver": ["semver@7.5.3", "", { "dependencies": { "lru-cache": "^6.0.0" }, "bin": { "semver": "bin/semver.js" } }, "sha512-QBlUtyVk/5EeHbi7X0fw6liDZc7BBmEaSYn01fMU1OUYbf6GPsbTtd8WmnqbI20SeycoHSeiybkE/q1Q+qlThQ=="],
+
+    "shebang-command": ["shebang-command@2.0.0", "", { "dependencies": { "shebang-regex": "^3.0.0" } }, "sha512-kHxr2zZpYtdmrN1qDjrrX/Z1rR1kG8Dx+gkpK1G4eXmvXswmcE1hTWBWYUzlraYw1/yZp6YuDY77YtvbN0dmDA=="],
+
+    "shebang-regex": ["shebang-regex@3.0.0", "", {}, "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A=="],
+
+    "signal-exit": ["signal-exit@3.0.7", "", {}, "sha512-wnD2ZE+l+SPC/uoS0vXeE9L1+0wuaMqKlfz9AMUo38JsyLSBWSFcHR1Rri62LZc12vLr1gb3jl7iwQhgwpAbGQ=="],
+
+    "sisteransi": ["sisteransi@1.0.5", "", {}, "sha512-bLGGlR1QxBcynn2d5YmDX4MGjlZvy2MRBDRNHLJ8VI6l6+9FUiyTFNJ0IveOSP0bcXgVDPRcfGqA0pjaqUpfVg=="],
+
+    "source-map": ["source-map@0.8.0-beta.0", "", { "dependencies": { "whatwg-url": "^7.0.0" } }, "sha512-2ymg6oRBpebeZi9UUNsgQ89bhx01TcTkmNTGnNO88imTmbSgy4nfujrgVEFKWpMTEGA11EDkTt7mqObTPdigIA=="],
+
+    "source-map-js": ["source-map-js@1.2.1", "", {}, "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA=="],
+
+    "source-map-support": ["source-map-support@0.5.21", "", { "dependencies": { "buffer-from": "^1.0.0", "source-map": "^0.6.0" } }, "sha512-uBHU3L3czsIyYXKX88fdrGovxdSCoTGDRZ6SYXtSRxLZUzHg5P/66Ht6uoUlHu9EZod+inXhKo3qQgwXUT/y1w=="],
+
+    "stackframe": ["stackframe@1.3.4", "", {}, "sha512-oeVtt7eWQS+Na6F//S4kJ2K2VbRlS9D43mAlMyVpVWovy9o+jfgH8O9agzANzaiLjclA0oYzUXEM4PurhSUChw=="],
+
+    "strip-final-newline": ["strip-final-newline@2.0.0", "", {}, "sha512-BrpvfNAE3dcvq7ll3xVumzjKjZQ5tI1sEUIKr3Uoks0XUl45St3FlatVqef9prk4jRDzhW6WZg+3bk93y6pLjA=="],
+
+    "style-loader": ["style-loader@4.0.0", "", { "peerDependencies": { "webpack": "^5.27.0" } }, "sha512-1V4WqhhZZgjVAVJyt7TdDPZoPBPNHbekX4fWnCJL1yQukhCeZhJySUL+gL9y6sNdN95uEOS83Y55SqHcP7MzLA=="],
+
+    "supports-color": ["supports-color@8.1.1", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-MpUEN2OodtUzxvKQl72cUF7RQ5EiHsGvSsVG0ia9c5RbWGL2CI4C7EpPS8UTBIplnlzZiNuV56w+FuNxy3ty2Q=="],
+
+    "tapable": ["tapable@2.3.3", "", {}, "sha512-uxc/zpqFg6x7C8vOE7lh6Lbda8eEL9zmVm/PLeTPBRhh1xCgdWaQ+J1CUieGpIfm2HdtsUpRv+HshiasBMcc6A=="],
+
+    "terser": ["terser@5.48.0", "", { "dependencies": { "@jridgewell/source-map": "^0.3.3", "acorn": "^8.15.0", "commander": "^2.20.0", "source-map-support": "~0.5.20" }, "bin": { "terser": "bin/terser" } }, "sha512-J/9An6vs9Us6wKRriSFXBWdRZapREHqFzdNUKk0pmu804EMR6dr6winwo7e5JDxN4xahxQsuysyYFwlwj4XN/Q=="],
+
+    "terser-webpack-plugin": ["terser-webpack-plugin@5.6.1", "", { "dependencies": { "@jridgewell/trace-mapping": "^0.3.25", "jest-worker": "^27.4.5", "schema-utils": "^4.3.0", "terser": "^5.31.1" }, "peerDependencies": { "webpack": "^5.1.0" } }, "sha512-201R5j+sJpK8nFWwKVyNfZot8FaJbLZDq5evriVzbV1wDtSXDjRUDRfJzHpAaxFDMEhsZL1QkeqM61wgsS3KaQ=="],
+
+    "tiny-invariant": ["tiny-invariant@1.3.3", "", {}, "sha512-+FbBPE1o9QAYvviau/qC5SE3caw21q3xkvWKBtja5vgqOWIHHJ3ioaq1VPfn/Szqctz2bU/oYeKd9/z5BL+PVg=="],
+
+    "to-fast-properties": ["to-fast-properties@2.0.0", "", {}, "sha512-/OaKK0xYrs3DmxRYqL/yDc+FxFUVYhDlXMhRmv3z915w2HF1tnN1omB354j8VUGO/hbRzyD6Y3sA7v7GS/ceog=="],
+
+    "tr46": ["tr46@1.0.1", "", { "dependencies": { "punycode": "^2.1.0" } }, "sha512-dTpowEjclQ7Kgx5SdBkqRzVhERQXov8/l9Ft9dVM9fmg0W0KQSVaXX9T4i6twCPNtYiZM53lpSSUAwJbFPOHxA=="],
+
+    "tslib": ["tslib@2.8.1", "", {}, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
+
+    "typescript": ["typescript@5.9.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw=="],
+
+    "undici-types": ["undici-types@8.3.0", "", {}, "sha512-j375ScV60dom+YkPFIfTLcOiPxkN/buHz5GobjLhixFuANaNs3C9l4GmrWqejgXWJ7BbJcFYpTEUkS1Ge8bpZQ=="],
+
+    "update-browserslist-db": ["update-browserslist-db@1.2.3", "", { "dependencies": { "escalade": "^3.2.0", "picocolors": "^1.1.1" }, "peerDependencies": { "browserslist": ">= 4.21.0" }, "bin": { "update-browserslist-db": "cli.js" } }, "sha512-Js0m9cx+qOgDxo0eMiFGEueWztz+d4+M3rGlmKPT+T4IS/jP4ylw3Nwpu6cpTTP8R1MAC1kF4VbdLt3ARf209w=="],
+
+    "util-deprecate": ["util-deprecate@1.0.2", "", {}, "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw=="],
+
+    "watchpack": ["watchpack@2.5.2", "", { "dependencies": { "graceful-fs": "^4.1.2" } }, "sha512-6i/00NBjP4yGPs+caKSyRfpTF/8Torsu0MOW3mMzIbhgISFder8i7xbqgHlLMwJrdiN8ndBV3UA1/AfzPSr+jg=="],
+
+    "webidl-conversions": ["webidl-conversions@4.0.2", "", {}, "sha512-YQ+BmxuTgd6UXZW3+ICGfyqRyHXVlD5GtQr5+qjiNW7bF0cqrzX500HVXPBOvgXb5YnzDd+h0zqyv61KUD7+Sg=="],
+
+    "webpack": ["webpack@5.105.0", "", { "dependencies": { "@types/eslint-scope": "^3.7.7", "@types/estree": "^1.0.8", "@types/json-schema": "^7.0.15", "@webassemblyjs/ast": "^1.14.1", "@webassemblyjs/wasm-edit": "^1.14.1", "@webassemblyjs/wasm-parser": "^1.14.1", "acorn": "^8.15.0", "acorn-import-phases": "^1.0.3", "browserslist": "^4.28.1", "chrome-trace-event": "^1.0.2", "enhanced-resolve": "^5.19.0", "es-module-lexer": "^2.0.0", "eslint-scope": "5.1.1", "events": "^3.2.0", "glob-to-regexp": "^0.4.1", "graceful-fs": "^4.2.11", "json-parse-even-better-errors": "^2.3.1", "loader-runner": "^4.3.1", "mime-types": "^2.1.27", "neo-async": "^2.6.2", "schema-utils": "^4.3.3", "tapable": "^2.3.0", "terser-webpack-plugin": "^5.3.16", "watchpack": "^2.5.1", "webpack-sources": "^3.3.3" }, "bin": { "webpack": "bin/webpack.js" } }, "sha512-gX/dMkRQc7QOMzgTe6KsYFM7DxeIONQSui1s0n/0xht36HvrgbxtM1xBlgx596NbpHuQU8P7QpKwrZYwUX48nw=="],
+
+    "webpack-sources": ["webpack-sources@3.5.0", "", {}, "sha512-HPuy+uuoTCaaoEoI1LQ3JN9+vrPBvEesnnX1jADHy728cHSMlq4wUc4afYqahq2B1mhQVZxCXOkNTnXltr+2vQ=="],
+
+    "whatwg-url": ["whatwg-url@7.1.0", "", { "dependencies": { "lodash.sortby": "^4.7.0", "tr46": "^1.0.1", "webidl-conversions": "^4.0.2" } }, "sha512-WUu7Rg1DroM7oQvGWfOiAK21n74Gg+T4elXEQYkOhtyLeWiJFoOGLXPKI/9gzIie9CtwVLm8wtw6YJdKyxSjeg=="],
+
+    "which": ["which@2.0.2", "", { "dependencies": { "isexe": "^2.0.0" }, "bin": { "node-which": "./bin/node-which" } }, "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA=="],
+
+    "ws": ["ws@8.21.0", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": ">=5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-Vsp28b7DRcimFQvrqu2Wek3z1iYxDCWqHYB8Qsnk/S4RfaCQzPGPyBNuVjJV3cd6UiKtUtp6sNM77gWvzcCH+g=="],
+
+    "yallist": ["yallist@4.0.0", "", {}, "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A=="],
+
+    "zod": ["zod@4.3.6", "", {}, "sha512-rftlrkhHZOcjDwkGlnUtZZkvaPHCsDATp4pGpuOOMDaTdDDXF91wuVDJoWoPsKX/3YPQ5fHuF3STjcYyKr+Qhg=="],
+
+    "css-loader/semver": ["semver@7.8.5", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-Y7/KDsb8LjooZpwaqGyulO6DQlksgCncchHGk+sZIY4SBvUocMBEFH5Ur1fI4dV+Jvl0w6cjvucaIi40puRioA=="],
+
+    "esrecurse/estraverse": ["estraverse@5.3.0", "", {}, "sha512-MMdARuVEQziNTeJD8DgMqmhwR11BRQ/cBP+pLtYdSTnf3MIO8fFeiINEbX36ZdNlfU/7A9f3gUw49B3oQsvwBA=="],
+
+    "recast/source-map": ["source-map@0.6.1", "", {}, "sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g=="],
+
+    "source-map-support/source-map": ["source-map@0.6.1", "", {}, "sha512-UjgapumWlbMhkBgzT7Ykc5YXUT46F0iKu8SGXq0bcwP5dz/h0Plj6enJqjz1Zbq2l5WaqYnrVbwWOWMyF3F47g=="],
+  }
+}

artifacts/glm52-rise-video/package.json

@@ -0,0 +1,24 @@
+{
+  "name": "glm52-rise-video",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "render": "remotion render src/index.tsx GLM52Rise out/glm-52-broke-out.mp4 --codec h264 --pixel-format yuv420p",
+    "render:sheep": "remotion render src/index.tsx NZSheep out/nz-sheep.mp4 --codec h264 --pixel-format yuv420p",
+    "render:novel": "remotion render src/index.tsx NovelTokens out/novel-1984.mp4 --codec h264 --pixel-format yuv420p",
+    "render:flash": "remotion render src/index.tsx FlashShare out/flash-share.mp4 --codec h264 --pixel-format yuv420p",
+    "render:minimax": "remotion render src/index.tsx MiniMaxClimb out/minimax-climb.mp4 --codec h264 --pixel-format yuv420p",
+    "still:june": "remotion still src/index.tsx JuneTotals out/june-totals.png --frame=0"
+  },
+  "dependencies": {
+    "@remotion/cli": "^4.0.384",
+    "react": "^19.2.3",
+    "react-dom": "^19.2.3",
+    "remotion": "^4.0.384"
+  },
+  "devDependencies": {
+    "@types/react": "^19.2.8",
+    "@types/react-dom": "^19.2.3",
+    "typescript": "^5.8.2"
+  }
+}

artifacts/glm52-rise-video/src/data.ts

@@ -0,0 +1,156 @@
+// Verified against the production opencode-stats PlanetScale DB.
+// Scope: tier='Go' (OpenCode Go), dataset='zen', client='all', source='all', grain='day'.
+// metric = total_tokens. Daily token volume per model; GLM-5.2 (zhipu) launched Jun 17.
+// Segments per day (tokens): glm-5.2, deepseek-v4-flash, deepseek-v4-pro, minimax-m3, all others.
+
+export type Day = {
+  date: string
+  total: number
+  glm: number
+  dsf: number
+  dsp: number
+  mm: number
+  others: number
+}
+
+export const days: Day[] = [
+  {
+    date: "Jun 12",
+    total: 2_283_799_449_383,
+    glm: 0,
+    dsf: 1_176_701_653_509,
+    dsp: 569_527_034_307,
+    mm: 159_016_250_684,
+    others: 378_554_510_883,
+  },
+  {
+    date: "Jun 13",
+    total: 2_008_462_388_420,
+    glm: 0,
+    dsf: 995_338_131_997,
+    dsp: 445_817_536_548,
+    mm: 211_743_241_967,
+    others: 355_563_477_908,
+  },
+  {
+    date: "Jun 14",
+    total: 2_007_785_405_251,
+    glm: 0,
+    dsf: 983_954_176_228,
+    dsp: 428_151_999_341,
+    mm: 262_476_527_930,
+    others: 333_202_701_752,
+  },
+  {
+    date: "Jun 15",
+    total: 2_694_736_103_062,
+    glm: 0,
+    dsf: 1_255_893_953_859,
+    dsp: 632_223_338_376,
+    mm: 352_507_442_991,
+    others: 454_111_367_836,
+  },
+  {
+    date: "Jun 16",
+    total: 2_838_153_758_908,
+    glm: 0,
+    dsf: 1_336_625_283_800,
+    dsp: 676_480_415_730,
+    mm: 305_268_829_013,
+    others: 519_779_230_365,
+  },
+  {
+    date: "Jun 17",
+    total: 2_778_964_711_109,
+    glm: 70_095_977_043,
+    dsf: 1_339_831_523_555,
+    dsp: 660_414_395_220,
+    mm: 251_302_096_157,
+    others: 457_320_719_134,
+  },
+  {
+    date: "Jun 18",
+    total: 2_806_992_430_656,
+    glm: 201_130_231_172,
+    dsf: 1_295_599_996_869,
+    dsp: 595_665_008_776,
+    mm: 322_205_104_324,
+    others: 392_392_089_515,
+  },
+  {
+    date: "Jun 19",
+    total: 2_419_611_630_232,
+    glm: 199_086_413_910,
+    dsf: 1_115_750_468_802,
+    dsp: 475_965_869_304,
+    mm: 303_586_698_735,
+    others: 325_222_179_481,
+  },
+  {
+    date: "Jun 20",
+    total: 2_188_278_916_865,
+    glm: 193_931_516_396,
+    dsf: 1_050_194_681_012,
+    dsp: 395_303_435_278,
+    mm: 281_998_000_337,
+    others: 266_851_283_842,
+  },
+  {
+    date: "Jun 21",
+    total: 2_042_309_961_344,
+    glm: 181_894_043_118,
+    dsf: 985_164_570_580,
+    dsp: 368_194_079_542,
+    mm: 259_812_551_324,
+    others: 247_244_716_780,
+  },
+  {
+    date: "Jun 22",
+    total: 2_893_934_325_663,
+    glm: 301_759_048_475,
+    dsf: 1_298_124_282_989,
+    dsp: 581_012_596_194,
+    mm: 371_581_117_839,
+    others: 341_457_280_166,
+  },
+  {
+    date: "Jun 23",
+    total: 3_109_009_321_480,
+    glm: 282_277_235_158,
+    dsf: 1_423_571_678_821,
+    dsp: 627_374_654_587,
+    mm: 429_416_300_508,
+    others: 346_369_452_406,
+  },
+  {
+    date: "Jun 24",
+    total: 2_939_149_971_595,
+    glm: 256_497_442_533,
+    dsf: 1_373_583_023_234,
+    dsp: 601_270_997_775,
+    mm: 391_586_493_231,
+    others: 316_212_014_822,
+  },
+  {
+    date: "Jun 25",
+    total: 3_029_641_552_948,
+    glm: 256_279_657_734,
+    dsf: 1_481_084_002_776,
+    dsp: 602_077_167_287,
+    mm: 375_985_302_874,
+    others: 314_215_422_277,
+  },
+]
+
+export const launchIndex = 5 // Jun 17, first day of GLM-5.2 usage
+// GLM-5.2 weekly token volume, Jun 19-25 (sum of glm): 1,671,725,357,324 = 1.67T
+export const glmWeekTokensT = 1.672
+
+// stacked segments, bottom -> top. GLM-5.2 is the hero (blue); the rest are the field it cut into.
+export const segments = [
+  { key: "glm", label: "GLM-5.2", color: "#3b5cf6", hero: true },
+  { key: "dsf", label: "deepseek-v4-flash", color: "#9ca3ad" },
+  { key: "dsp", label: "deepseek-v4-pro", color: "#b3b9c1" },
+  { key: "mm", label: "minimax-m3", color: "#c8cdd3" },
+  { key: "others", label: "other models", color: "#dde0e4" },
+] as const

artifacts/glm52-rise-video/src/flash.tsx

@@ -0,0 +1,185 @@
+import React from "react"
+import { AbsoluteFill, Easing, interpolate, spring, useCurrentFrame, useVideoConfig } from "remotion"
+
+// stats.opencode.ai design tokens (light theme)
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#e4e4e4",
+  gray: "#aab0b8",
+  accent: "#3b5cf6",
+  accentHi: "#5b78ff",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+// verified: OpenCode Go, week of Jun 22-28, 2026 (2026-W26). share = % of 19.64T total Go tokens.
+const bars = [
+  { label: "deepseek-v4-flash", share: 48.3, hero: true },
+  { label: "deepseek-v4-pro", share: 19.4 },
+  { label: "minimax-m3", share: 13.0 },
+  { label: "glm-5.2", share: 8.3 },
+  { label: "mimo-v2.5", share: 4.3 },
+  { label: "kimi-k2.7-code", share: 2.6 },
+  { label: "other models", share: 4.1 },
+]
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.ink }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function FlashShare() {
+  const frame = useCurrentFrame()
+  const { fps } = useVideoConfig()
+
+  const grow = (i: number) =>
+    Math.min(
+      1,
+      Math.max(0, spring({ frame: frame - 18 - i * 7, fps, config: { damping: 18, stiffness: 120, mass: 0.6 } })),
+    )
+
+  return (
+    <AbsoluteFill style={{ background: c.bg, color: c.ink, fontFamily: MONO, padding: 72, boxSizing: "border-box" }}>
+      <div style={{ height: "100%", display: "flex", flexDirection: "column" }}>
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* headline (static) */}
+        <div style={{ marginTop: 50 }}>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.muted, letterSpacing: 2 }}>
+            OPENCODE GO · SHARE OF TOKENS
+          </div>
+          <div
+            style={{ display: "flex", justifyContent: "space-between", alignItems: "baseline", gap: 24, marginTop: 14 }}
+          >
+            <div style={{ fontSize: 62, fontWeight: 600, letterSpacing: -2, lineHeight: 1 }}>DeepSeek V4 Flash</div>
+            <div
+              style={{
+                fontSize: 88,
+                fontWeight: 600,
+                letterSpacing: -2,
+                lineHeight: 1,
+                color: c.accent,
+                fontVariantNumeric: "tabular-nums",
+              }}
+            >
+              48%
+            </div>
+          </div>
+        </div>
+
+        {/* bar chart */}
+        <div style={{ flex: 1, display: "flex", flexDirection: "column", justifyContent: "center", gap: 16 }}>
+          {bars.map((b, i) => {
+            const g = grow(i)
+            const pct = b.share * g
+            return (
+              <div key={b.label} style={{ display: "flex", alignItems: "center", gap: 18 }}>
+                <div
+                  style={{
+                    width: 268,
+                    fontSize: 23,
+                    fontWeight: b.hero ? 600 : 500,
+                    color: b.hero ? c.ink : c.muted,
+                    textAlign: "right",
+                    whiteSpace: "nowrap",
+                  }}
+                >
+                  {b.label}
+                </div>
+                <div style={{ position: "relative", flex: 1, height: 48 }}>
+                  {/* dotted 100% track — height is a multiple of the 12px tile, anchored bottom, so dots never clip */}
+                  <div
+                    style={{
+                      position: "absolute",
+                      inset: 0,
+                      background: c.dot,
+                      WebkitMaskImage: DOT_MASK,
+                      maskImage: DOT_MASK,
+                      WebkitMaskSize: "12px 12px",
+                      maskSize: "12px 12px",
+                      WebkitMaskRepeat: "repeat",
+                      maskRepeat: "repeat",
+                      WebkitMaskPosition: "left bottom",
+                      maskPosition: "left bottom",
+                    }}
+                  />
+                  {/* fill */}
+                  <div
+                    style={{
+                      position: "absolute",
+                      left: 0,
+                      top: 0,
+                      bottom: 0,
+                      width: `${pct}%`,
+                      background: b.hero ? c.accent : c.gray,
+                      borderRight: b.hero ? `2px solid ${c.accentHi}` : "none",
+                    }}
+                  />
+                </div>
+                <div
+                  style={{
+                    width: 84,
+                    fontSize: 24,
+                    fontWeight: b.hero ? 600 : 500,
+                    color: b.hero ? c.accent : c.muted,
+                    textAlign: "right",
+                    fontVariantNumeric: "tabular-nums",
+                  }}
+                >
+                  {Math.round(pct)}%
+                </div>
+              </div>
+            )
+          })}
+        </div>
+
+        {/* footer */}
+        <div
+          style={{
+            display: "flex",
+            justifyContent: "space-between",
+            alignItems: "center",
+            marginTop: 24,
+            paddingTop: 22,
+            borderTop: `1px solid ${c.line}`,
+            fontSize: 20,
+            fontWeight: 500,
+          }}
+        >
+          <div style={{ display: "inline-flex", alignItems: "center", gap: 9, color: c.muted }}>
+            <span style={{ width: 13, height: 13, background: c.accent, display: "inline-block" }} />
+            DeepSeek V4 Flash · 9.48T tokens · 83.6M requests
+          </div>
+          <div style={{ color: c.ink }}>opencode.ai/data</div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/index.tsx

@@ -0,0 +1,36 @@
+import { Composition, registerRoot } from "remotion"
+import { GLM52Rise } from "./video"
+import { NZSheep } from "./sheep"
+import { NovelTokens } from "./novel"
+import { FlashShare } from "./flash"
+import { MiniMaxClimb } from "./minimax"
+import { JuneTotals } from "./june"
+
+function Root() {
+  return (
+    <>
+      <Composition id="GLM52Rise" component={GLM52Rise} durationInFrames={240} fps={30} width={1080} height={1080} />
+      <Composition id="NZSheep" component={NZSheep} durationInFrames={150} fps={30} width={1080} height={1080} />
+      <Composition
+        id="NovelTokens"
+        component={NovelTokens}
+        durationInFrames={150}
+        fps={30}
+        width={1080}
+        height={1080}
+      />
+      <Composition id="FlashShare" component={FlashShare} durationInFrames={165} fps={30} width={1080} height={1080} />
+      <Composition
+        id="MiniMaxClimb"
+        component={MiniMaxClimb}
+        durationInFrames={165}
+        fps={30}
+        width={1080}
+        height={1080}
+      />
+      <Composition id="JuneTotals" component={JuneTotals} durationInFrames={1} fps={30} width={1080} height={1080} />
+    </>
+  )
+}
+
+registerRoot(Root)

artifacts/glm52-rise-video/src/june.tsx

@@ -0,0 +1,144 @@
+import React from "react"
+import { AbsoluteFill } from "remotion"
+
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#dcdcdc",
+  accent: "#3b5cf6",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+// verified: OpenCode Go (tier=Go, dataset=zen), June 1-30, 2026.
+// 72.78T tokens · 651.4M requests · 11.42M sessions -> rounded headline figures.
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.ink }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+function DotBand() {
+  return (
+    <div
+      style={{
+        height: 12,
+        background: c.dot,
+        WebkitMaskImage: DOT_MASK,
+        maskImage: DOT_MASK,
+        WebkitMaskSize: "12px 12px",
+        maskSize: "12px 12px",
+        WebkitMaskRepeat: "repeat",
+        maskRepeat: "repeat",
+        WebkitMaskPosition: "left top",
+        maskPosition: "left top",
+      }}
+    />
+  )
+}
+
+function Metric({ value, label }: { value: string; label: string }) {
+  return (
+    <div>
+      <div
+        style={{
+          fontSize: 92,
+          fontWeight: 600,
+          letterSpacing: -3,
+          lineHeight: 1,
+          fontVariantNumeric: "tabular-nums",
+          marginLeft: -8, // align the glyph's visual left edge to the column
+        }}
+      >
+        {value}
+      </div>
+      <div style={{ marginTop: 16, fontSize: 24, fontWeight: 500, color: c.muted, letterSpacing: 1 }}>{label}</div>
+    </div>
+  )
+}
+
+export function JuneTotals() {
+  return (
+    <AbsoluteFill style={{ background: c.bg, color: c.ink, fontFamily: MONO, padding: 72, boxSizing: "border-box" }}>
+      <div style={{ height: "100%", display: "flex", flexDirection: "column" }}>
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center", marginBottom: 22 }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>MONTHLY RECAP</div>
+        </div>
+        <DotBand />
+
+        {/* hero */}
+        <div style={{ flex: 1, display: "flex", flexDirection: "column", justifyContent: "center" }}>
+          <div style={{ fontSize: 25, fontWeight: 600, color: c.muted, letterSpacing: 3 }}>OPENCODE GO · JUNE 2026</div>
+          <div style={{ marginTop: 14 }}>
+            <div
+              style={{
+                fontSize: 300,
+                fontWeight: 600,
+                letterSpacing: -10,
+                lineHeight: 0.82,
+                color: c.accent,
+                marginLeft: -22,
+              }}
+            >
+              73T
+            </div>
+            <div style={{ fontSize: 50, fontWeight: 600, color: c.ink, marginTop: 10 }}>tokens processed</div>
+          </div>
+
+          {/* supporting metrics */}
+          <div
+            style={{
+              display: "grid",
+              gridTemplateColumns: "1fr 1fr",
+              marginTop: 60,
+              paddingTop: 40,
+              borderTop: `1px solid ${c.line}`,
+            }}
+          >
+            <Metric value="650M" label="requests" />
+            <Metric value="11M" label="sessions" />
+          </div>
+        </div>
+
+        {/* footer */}
+        <DotBand />
+        <div
+          style={{
+            display: "flex",
+            justifyContent: "flex-end",
+            alignItems: "center",
+            marginTop: 22,
+            fontSize: 20,
+            fontWeight: 500,
+          }}
+        >
+          <div style={{ color: c.ink }}>opencode.ai/data</div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/minimax.tsx

@@ -0,0 +1,201 @@
+import React from "react"
+import { AbsoluteFill, interpolate, spring, useCurrentFrame, useVideoConfig } from "remotion"
+
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#e4e4e4",
+  accent: "#3b5cf6",
+  accentHi: "#5b78ff",
+  accentDim: "#aebcf3",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+// verified: minimax-m3, OpenCode Go (tier=Go, dataset=zen), weekly total_tokens.
+// W26 2.559T is +23.2% / +482.3B vs W25 2.077T.
+const weeks = [
+  { label: "May 25", t: 0.008 },
+  { label: "Jun 1", t: 0.429 },
+  { label: "Jun 8", t: 1.192 },
+  { label: "Jun 15", t: 2.077 },
+  { label: "Jun 22", t: 2.559, latest: true },
+]
+const AXIS_MAX = 3.0
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.ink }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+const CHART_H = 420 // multiple of 12 so the dotted tracks never clip
+
+export function MiniMaxClimb() {
+  const frame = useCurrentFrame()
+  const { fps } = useVideoConfig()
+
+  const grow = (i: number) =>
+    Math.min(
+      1,
+      Math.max(0, spring({ frame: frame - 22 - i * 9, fps, config: { damping: 18, stiffness: 110, mass: 0.6 } })),
+    )
+
+  return (
+    <AbsoluteFill style={{ background: c.bg, color: c.ink, fontFamily: MONO, padding: 72, boxSizing: "border-box" }}>
+      <div style={{ height: "100%", display: "flex", flexDirection: "column" }}>
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* headline (static) */}
+        <div style={{ marginTop: 50 }}>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.muted, letterSpacing: 2 }}>
+            OPENCODE GO · WEEKLY TOKENS
+          </div>
+          <div
+            style={{ display: "flex", justifyContent: "space-between", alignItems: "baseline", gap: 24, marginTop: 14 }}
+          >
+            <div style={{ fontSize: 62, fontWeight: 600, letterSpacing: -2, lineHeight: 1 }}>MiniMax M3</div>
+            <div style={{ textAlign: "right", flexShrink: 0 }}>
+              <div
+                style={{
+                  fontSize: 84,
+                  fontWeight: 600,
+                  letterSpacing: -2,
+                  lineHeight: 1,
+                  color: c.accent,
+                  fontVariantNumeric: "tabular-nums",
+                }}
+              >
+                +23.2%
+              </div>
+              <div style={{ fontSize: 19, fontWeight: 500, color: c.muted, letterSpacing: 1, marginTop: 6 }}>
+                WEEK OVER WEEK
+              </div>
+            </div>
+          </div>
+        </div>
+
+        {/* column chart */}
+        <div style={{ flex: 1, display: "flex", alignItems: "flex-end", marginTop: 30 }}>
+          <div style={{ width: "100%", display: "flex", alignItems: "flex-end", gap: 30 }}>
+            {weeks.map((w, i) => {
+              const g = grow(i)
+              const h = Math.round((w.t / AXIS_MAX) * CHART_H * g)
+              return (
+                <div key={w.label} style={{ flex: 1, display: "flex", flexDirection: "column", alignItems: "center" }}>
+                  {/* value + bar */}
+                  <div style={{ position: "relative", width: "100%", height: CHART_H }}>
+                    {/* dotted track */}
+                    <div
+                      style={{
+                        position: "absolute",
+                        inset: 0,
+                        background: c.dot,
+                        WebkitMaskImage: DOT_MASK,
+                        maskImage: DOT_MASK,
+                        WebkitMaskSize: "12px 12px",
+                        maskSize: "12px 12px",
+                        WebkitMaskRepeat: "repeat",
+                        maskRepeat: "repeat",
+                        WebkitMaskPosition: "left bottom",
+                        maskPosition: "left bottom",
+                      }}
+                    />
+                    {/* fill */}
+                    <div
+                      style={{
+                        position: "absolute",
+                        left: 0,
+                        right: 0,
+                        bottom: 0,
+                        height: h,
+                        background: w.latest ? c.accent : c.accentDim,
+                        borderTop: w.latest ? `3px solid ${c.accentHi}` : "none",
+                      }}
+                    />
+                    {/* value label */}
+                    <div
+                      style={{
+                        position: "absolute",
+                        left: 0,
+                        right: 0,
+                        bottom: h + 10,
+                        textAlign: "center",
+                        fontSize: 26,
+                        fontWeight: w.latest ? 600 : 500,
+                        color: w.latest ? c.accent : c.muted,
+                        fontVariantNumeric: "tabular-nums",
+                        opacity: interpolate(g, [0.5, 1], [0, 1], {
+                          extrapolateLeft: "clamp",
+                          extrapolateRight: "clamp",
+                        }),
+                      }}
+                    >
+                      {w.t.toFixed(2)}T
+                    </div>
+                  </div>
+                  {/* week label */}
+                  <div
+                    style={{
+                      marginTop: 14,
+                      fontSize: 18,
+                      fontWeight: 500,
+                      color: w.latest ? c.ink : c.faint,
+                    }}
+                  >
+                    {w.label}
+                  </div>
+                </div>
+              )
+            })}
+          </div>
+        </div>
+
+        {/* footer */}
+        <div
+          style={{
+            display: "flex",
+            justifyContent: "space-between",
+            alignItems: "center",
+            marginTop: 22,
+            paddingTop: 22,
+            borderTop: `1px solid ${c.line}`,
+            fontSize: 20,
+            fontWeight: 500,
+          }}
+        >
+          <div style={{ display: "inline-flex", alignItems: "center", gap: 9, color: c.muted }}>
+            <span style={{ width: 13, height: 13, background: c.accent, display: "inline-block" }} />
+            2.56T tokens last week · +482.3B added
+          </div>
+          <div style={{ color: c.ink }}>opencode.ai/data</div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/novel.tsx

@@ -0,0 +1,135 @@
+import React from "react"
+import { AbsoluteFill, Easing, Img, interpolate, staticFile, useCurrentFrame } from "remotion"
+
+const c = {
+  white: "#ffffff",
+  dim: "rgba(255,255,255,0.74)",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+// verified: OpenCode Go, week of Jun 22-28, 2026 (2026-W26)
+// 19,642,742,937,105 tokens / 173,651,197 requests = 113,116 tokens/request
+const AVG = 113116
+const K = Math.round(AVG / 1000) // 113
+
+const nf = new Intl.NumberFormat("en-US")
+
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.white }}>
+      <path opacity="0.35" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function NovelTokens() {
+  const frame = useCurrentFrame()
+
+  const k = Math.round(
+    K *
+      interpolate(frame, [18, 92], [0, 1], {
+        extrapolateLeft: "clamp",
+        extrapolateRight: "clamp",
+        easing: Easing.out(Easing.cubic),
+      }),
+  )
+
+  const zoom = interpolate(frame, [0, 150], [1.06, 1.12], {
+    extrapolateRight: "clamp",
+    easing: Easing.inOut(Easing.quad),
+  })
+
+  return (
+    <AbsoluteFill style={{ background: "#0c0c0c", overflow: "hidden" }}>
+      <Img
+        src={staticFile("book.jpg")}
+        style={{
+          position: "absolute",
+          width: "100%",
+          height: "100%",
+          objectFit: "cover",
+          objectPosition: "center 34%",
+          transform: `scale(${zoom})`,
+          transformOrigin: "center 30%",
+        }}
+      />
+
+      {/* legibility scrims */}
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          background:
+            "linear-gradient(to bottom, rgba(0,0,0,0.55) 0%, rgba(0,0,0,0) 20%, rgba(0,0,0,0.1) 44%, rgba(0,0,0,0.86) 100%)",
+        }}
+      />
+
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          boxSizing: "border-box",
+          padding: 64,
+          color: c.white,
+          fontFamily: MONO,
+          display: "flex",
+          flexDirection: "column",
+          justifyContent: "space-between",
+        }}
+      >
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.dim, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* bottom block */}
+        <div>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.dim, letterSpacing: 2, marginBottom: 8 }}>
+            OPENCODE GO · LAST WEEK
+          </div>
+          <div
+            style={{
+              fontSize: 168,
+              fontWeight: 600,
+              lineHeight: 0.92,
+              letterSpacing: -5,
+              fontVariantNumeric: "tabular-nums",
+            }}
+          >
+            {k}K
+          </div>
+          <div style={{ fontSize: 50, fontWeight: 600, letterSpacing: -1, marginTop: 4 }}>tokens per request</div>
+
+          <div
+            style={{
+              display: "flex",
+              justifyContent: "space-between",
+              alignItems: "center",
+              marginTop: 30,
+              fontSize: 20,
+              fontWeight: 500,
+            }}
+          >
+            <div style={{ color: c.dim }}>{nf.format(AVG)} tokens / request · last week</div>
+            <div style={{ color: c.white }}>opencode.ai/data</div>
+          </div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/sheep.tsx

@@ -0,0 +1,139 @@
+import React from "react"
+import { AbsoluteFill, Easing, Img, interpolate, staticFile, useCurrentFrame } from "remotion"
+
+const c = {
+  white: "#ffffff",
+  dim: "rgba(255,255,255,0.72)",
+  faint: "rgba(255,255,255,0.55)",
+}
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+
+// verified: NZ OpenCode Go, week of Jun 22-28, 2026 (2026-W26)
+const TOKENS = 40_915_594_381 // 40.9B
+const SHEEP = 23_600_000 // 23.6M
+const PER_SHEEP = Math.round(TOKENS / SHEEP) // 1,734
+const nf = new Intl.NumberFormat("en-US")
+
+// the correct opencode "DATA" wordmark (white, over photo)
+function DataWordmark({ height = 30 }: { height?: number }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color: c.white }}>
+      <path opacity="0.35" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function NZSheep() {
+  const frame = useCurrentFrame()
+
+  const count = Math.round(
+    PER_SHEEP *
+      interpolate(frame, [18, 90], [0, 1], {
+        extrapolateLeft: "clamp",
+        extrapolateRight: "clamp",
+        easing: Easing.out(Easing.cubic),
+      }),
+  )
+
+  // slow Ken Burns push-in (scale up only — never reveals an edge)
+  const zoom = interpolate(frame, [0, 150], [1.06, 1.12], {
+    extrapolateRight: "clamp",
+    easing: Easing.inOut(Easing.quad),
+  })
+
+  return (
+    <AbsoluteFill style={{ background: "#0c0c0c", overflow: "hidden" }}>
+      {/* the sheep, staring */}
+      <Img
+        src={staticFile("sheep.jpg")}
+        style={{
+          position: "absolute",
+          width: "100%",
+          height: "100%",
+          objectFit: "cover",
+          objectPosition: "center 38%",
+          transform: `scale(${zoom})`,
+          transformOrigin: "center 35%",
+        }}
+      />
+
+      {/* legibility scrims */}
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          background:
+            "linear-gradient(to bottom, rgba(0,0,0,0.5) 0%, rgba(0,0,0,0) 22%, rgba(0,0,0,0) 48%, rgba(0,0,0,0.78) 100%)",
+        }}
+      />
+
+      {/* content */}
+      <div
+        style={{
+          position: "absolute",
+          inset: 0,
+          boxSizing: "border-box",
+          padding: 64,
+          color: c.white,
+          fontFamily: MONO,
+          display: "flex",
+          flexDirection: "column",
+          justifyContent: "space-between",
+        }}
+      >
+        {/* header */}
+        <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+          <DataWordmark height={30} />
+          <div style={{ fontSize: 20, fontWeight: 500, color: c.dim, letterSpacing: 1 }}>JUN 22–28, 2026</div>
+        </div>
+
+        {/* bottom block */}
+        <div>
+          <div style={{ fontSize: 23, fontWeight: 600, color: c.dim, letterSpacing: 2, marginBottom: 8 }}>
+            OPENCODE GO · NEW ZEALAND
+          </div>
+          <div
+            style={{
+              fontSize: 168,
+              fontWeight: 600,
+              lineHeight: 0.92,
+              letterSpacing: -5,
+              fontVariantNumeric: "tabular-nums",
+            }}
+          >
+            {nf.format(count)}
+          </div>
+          <div style={{ fontSize: 50, fontWeight: 600, letterSpacing: -1, marginTop: 4 }}>tokens per sheep</div>
+
+          <div
+            style={{
+              display: "flex",
+              justifyContent: "space-between",
+              alignItems: "center",
+              marginTop: 34,
+              fontSize: 20,
+              fontWeight: 500,
+            }}
+          >
+            <div style={{ color: c.dim }}>40.9B tokens ÷ 23.6M sheep · last week</div>
+            <div style={{ color: c.white }}>opencode.ai/data</div>
+          </div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

artifacts/glm52-rise-video/src/video.tsx

@@ -0,0 +1,254 @@
+import React from "react"
+import { AbsoluteFill, Easing, interpolate, useCurrentFrame, useVideoConfig } from "remotion"
+import { days, launchIndex, glmWeekTokensT, segments } from "./data"
+
+// stats.opencode.ai design tokens (light theme)
+const c = {
+  bg: "#ffffff",
+  ink: "#161616",
+  muted: "#5c5c5c",
+  faint: "#808080",
+  line: "#e6e6e6",
+  dot: "#ededed",
+  accent: "#3b5cf6",
+  accentHi: "#5b78ff",
+}
+
+const MONO = '"IBM Plex Mono", ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, monospace'
+const W = 1080
+
+const DOT_MASK =
+  "url(\"data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E\")"
+
+const field = segments.filter((s) => !s.hero)
+const glmColor = segments.find((s) => s.hero)!.color
+
+const clamp = (v: number, lo: number, hi: number) => Math.min(hi, Math.max(lo, v))
+
+// the correct opencode "DATA" wordmark (from stats.opencode.ai header)
+function DataWordmark({ height = 30, color = c.ink }: { height?: number; color?: string }) {
+  return (
+    <svg width={(height * 66) / 20} height={height} viewBox="0 0 66 20" fill="none" style={{ color }}>
+      <path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
+      <path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
+      <path
+        d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
+        fill="currentColor"
+      />
+      <path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
+      <path
+        d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
+        fill="currentColor"
+      />
+      <path
+        d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
+        fill="currentColor"
+      />
+    </svg>
+  )
+}
+
+export function GLM52Rise() {
+  const frame = useCurrentFrame()
+  const { fps } = useVideoConfig()
+
+  // ---------- virtual camera ----------
+  // open zoomed-in on the field, pan right while the blue fills, then pull back to reveal.
+  const K = [0, 32, 150, 206, 240]
+  const ease = Easing.inOut(Easing.cubic)
+  const opt = { extrapolateLeft: "clamp" as const, extrapolateRight: "clamp" as const, easing: ease }
+  const s = interpolate(frame, K, [1.82, 1.72, 1.72, 1.0, 1.0], opt)
+  let fx = interpolate(frame, K, [420, 438, 760, 540, 540], opt)
+  let fy = interpolate(frame, K, [664, 664, 664, 540, 540], opt)
+  // keep the framing inside the 1080 canvas so edges never reveal black
+  fx = clamp(fx, 540 / s, W - 540 / s)
+  fy = clamp(fy, 540 / s, W - 540 / s)
+  const camera = `translate(${540 - fx * s}px, ${540 - fy * s}px) scale(${s})`
+
+  // ---------- blue sweep (synced to the pan) ----------
+  const p = interpolate(frame, [32, 150], [0, 1], { extrapolateLeft: "clamp", extrapolateRight: "clamp", easing: ease })
+  const revealAmount = p * (days.length - launchIndex) + 0.35
+  const fillOf = (i: number) => clamp(revealAmount - (i - launchIndex), 0, 1)
+
+  // token number climbs as the camera pulls back and the headline re-enters frame
+  const tokensT =
+    glmWeekTokensT *
+    interpolate(frame, [150, 202], [0, 1], {
+      extrapolateLeft: "clamp",
+      extrapolateRight: "clamp",
+      easing: Easing.out(Easing.cubic),
+    })
+
+  // chart geometry
+  const chartH = 440
+  const chartW = 936
+  const gap = 14
+  const EXAGGERATE = 2.876 // broken y-axis: GLM-5.2 magnified ~2.9x for emphasis
+
+  return (
+    <AbsoluteFill style={{ background: c.bg, overflow: "hidden" }}>
+      <div
+        style={{
+          position: "absolute",
+          width: W,
+          height: W,
+          background: c.bg,
+          transformOrigin: "0 0",
+          transform: camera,
+        }}
+      >
+        <div
+          style={{
+            width: W,
+            height: W,
+            boxSizing: "border-box",
+            padding: 72,
+            color: c.ink,
+            fontFamily: MONO,
+            display: "flex",
+            flexDirection: "column",
+          }}
+        >
+          {/* header */}
+          <div style={{ display: "flex", justifyContent: "space-between", alignItems: "center" }}>
+            <DataWordmark height={30} />
+            <div style={{ fontSize: 20, fontWeight: 500, color: c.faint, letterSpacing: 1 }}>JUN 12–25, 2026</div>
+          </div>
+
+          {/* headline (static) */}
+          <div style={{ marginTop: 52 }}>
+            <div style={{ fontSize: 92, fontWeight: 600, lineHeight: 0.98, letterSpacing: -2 }}>
+              GLM-5.2 <span style={{ color: c.accent }}>broke out</span>
+            </div>
+            <div style={{ marginTop: 22, fontSize: 30, fontWeight: 500, color: c.muted }}>
+              From 0 to <span style={{ color: c.ink }}>{tokensT.toFixed(2)}T tokens</span> in a week.
+            </div>
+          </div>
+
+          {/* stacked chart */}
+          <div style={{ flex: 1, display: "flex", alignItems: "flex-end", marginTop: 40 }}>
+            <div
+              style={{
+                position: "relative",
+                width: chartW,
+                height: chartH,
+                margin: "0 auto",
+                borderBottom: `2px solid ${c.ink}`,
+                boxSizing: "border-box",
+              }}
+            >
+              {/* faint dotted backdrop */}
+              <div
+                style={{
+                  position: "absolute",
+                  left: -8,
+                  right: -8,
+                  top: -8,
+                  bottom: 0,
+                  background: c.dot,
+                  WebkitMaskImage: DOT_MASK,
+                  maskImage: DOT_MASK,
+                  WebkitMaskSize: "12px 12px",
+                  maskSize: "12px 12px",
+                  WebkitMaskRepeat: "repeat",
+                  maskRepeat: "repeat",
+                }}
+              />
+
+              {/* columns */}
+              <div style={{ position: "absolute", inset: 0, display: "flex", gap, alignItems: "flex-end" }}>
+                {days.map((d, i) => {
+                  const glmShare = d.glm / d.total
+                  const blueH = Math.round(glmShare * EXAGGERATE * chartH)
+                  const filled = Math.round(blueH * fillOf(i))
+                  const slotGap = filled > 2 ? 5 : 0
+                  const fieldH = chartH - filled - slotGap
+                  const fieldTotal = d.dsf + d.dsp + d.mm + d.others
+                  return (
+                    <div key={i} style={{ position: "relative", flex: 1, height: chartH }}>
+                      {/* gray field of other models (already in place) */}
+                      <div
+                        style={{
+                          position: "absolute",
+                          top: 0,
+                          left: 0,
+                          right: 0,
+                          height: fieldH,
+                          display: "flex",
+                          flexDirection: "column-reverse",
+                        }}
+                      >
+                        {field.map((seg) => (
+                          <div
+                            key={seg.key}
+                            style={{
+                              height: Math.round(((d[seg.key as keyof typeof d] as number) / fieldTotal) * fieldH),
+                              background: seg.color,
+                              borderTop: `2px solid ${c.bg}`,
+                            }}
+                          />
+                        ))}
+                      </div>
+                      {/* GLM-5.2, animates in */}
+                      {filled > 2 && (
+                        <div
+                          style={{
+                            position: "absolute",
+                            left: 0,
+                            right: 0,
+                            bottom: 0,
+                            height: filled,
+                            background: glmColor,
+                            borderTop: `2px solid ${c.accentHi}`,
+                          }}
+                        />
+                      )}
+                    </div>
+                  )
+                })}
+              </div>
+            </div>
+          </div>
+
+          {/* day axis */}
+          <div style={{ display: "flex", gap, width: chartW, margin: "14px auto 0" }}>
+            {days.map((d, i) => (
+              <div
+                key={i}
+                style={{
+                  flex: 1,
+                  textAlign: "center",
+                  fontSize: 15,
+                  fontWeight: 500,
+                  color: i === days.length - 1 ? c.ink : c.faint,
+                }}
+              >
+                {i === 0 || i === launchIndex || i === days.length - 1 ? d.date : ""}
+              </div>
+            ))}
+          </div>
+
+          {/* footer */}
+          <div
+            style={{
+              display: "flex",
+              justifyContent: "space-between",
+              alignItems: "center",
+              marginTop: 28,
+              paddingTop: 22,
+              borderTop: `1px solid ${c.line}`,
+              fontSize: 20,
+              fontWeight: 500,
+            }}
+          >
+            <div style={{ display: "inline-flex", alignItems: "center", gap: 9, color: c.muted }}>
+              <span style={{ width: 13, height: 13, background: c.accent, display: "inline-block" }} />
+              GLM-5.2
+            </div>
+            <div style={{ color: c.ink }}>opencode.ai/data</div>
+          </div>
+        </div>
+      </div>
+    </AbsoluteFill>
+  )
+}

docs/design/service-lifecycle.md

@@ -0,0 +1,685 @@
+# Service Lifecycle: Election, Restart, and Reconnect
+
+Status: in progress
+
+Incident: [#36688](https://github.com/anomalyco/opencode/issues/36688)
+
+## Summary
+
+The managed V2 service keeps its current update policy: the background updater
+may install a new package, but only a freshly launched TUI activates that update
+after finding an older running service. Existing TUIs never replace a service;
+they only reconnect.
+
+The restart path changes in three places:
+
+1. A process-held OS lock, not the HTTP port or registration file, elects
+   exactly one server owner for its lifetime.
+2. The elected process binds and registers a minimal lifecycle surface before
+   it initializes the application, so clients can distinguish a slow winner
+   from an absent server.
+3. TUIs rediscover and reconnect indefinitely. Transport loss is never a
+   terminal error by itself.
+
+Several clients may spawn small contenders during a restart. This is safe and
+intentional: one contender acquires the lock and initializes, while every loser
+exits before expensive server boot. The design does not require clients to
+agree on a single initiator.
+
+This proposal does not introduce a supervisor process, warm candidate server,
+protocol negotiation, idle background restart, or general execution-recovery
+framework.
+
+## Architecture at a Glance
+
+```text
+                       ╭───────────────────╮
+                       │ CLI ServiceConfig │
+                       ╰─────────┬─────────╯
+                                 │
+                                 ▼
+                     ╭──────────────────────╮
+                     │ CLI ServerConnection │
+                     ╰───────────┬──────────╯
+              ╭──────────────────╰───────────────────╮
+              ▼                                      ▼
+╭──────────────────────────╮            ╭─────────────────────────╮
+│ Client Service lifecycle │            │ CLI runPromiseWith seam │
+╰─────────────┬────────────╯            ╰─────────────┬───────────╯
+              ╰─────╮                                 │
+                    ▼                                 ▼
+     ╭────────────────────────────╮            ╭─────────────╮
+     │ Background service process │            │ TUI / Solid │
+     ╰──────────────┬─────────────╯            ╰──────┬──────╯
+                    │                                 │
+                    ╰────────────◀────────────────────╯
+                     ╭───────────────────────╮
+                     │ Server HTTP transport │
+                     ╰───────────┬───────────╯
+                                 │
+                                 ▼
+                       ╭──────────────────╮
+                       │ Core application │
+                       ╰──────────────────╯
+```
+
+| Owner                                            | Responsibility                                                                                      |
+| ------------------------------------------------ | --------------------------------------------------------------------------------------------------- |
+| `packages/client/src/effect/service.ts`          | Effect-native discovery, start, and stop lifecycle operations                                       |
+| `packages/cli/src/services/service-config.ts`    | CLI registration path, installed version, and daemon command                                        |
+| `packages/cli/src/services/server-connection.ts` | Resolve an endpoint and, only for the shared service, grouped reconnect and restart Effects         |
+| `packages/cli/src/server-process.ts`             | Daemon election, registration, and server process boot                                              |
+| `packages/server/src/process.ts`                 | HTTP lifecycle shell and application transport                                                      |
+| `packages/core`                                  | Application behavior behind the transport                                                           |
+| CLI default handler                              | Convert lifecycle Effects with the outer `FileSystem` context and pass grouped Promise capabilities |
+| `packages/tui` Solid client context              | Own event-stream reconnect, endpoint replacement, status, and user-triggered restart UI             |
+
+## Implementation Status
+
+| Area                      | State                                                                 |
+| ------------------------- | --------------------------------------------------------------------- |
+| Lifetime ownership        | Implemented on this branch with a scoped OS lock                      |
+| Contender behavior        | Implemented; losers exit before the server module is imported         |
+| Registration repair       | Implemented; the owner reasserts deleted or corrupt discovery         |
+| Channel isolation         | Implemented with no-clobber migration for legacy preview discovery    |
+| Client startup waiting    | Implemented; slow winners are not killed and waiting is indefinite    |
+| Lifecycle shell           | Implemented; the owner binds and registers before application boot    |
+| Failed-state latching     | Implemented; deterministic boot failure stays bound and actionable    |
+| Recovery diagnostics      | Implemented; the TUI shows status instead of transport internals      |
+| Cross-platform validation | macOS runtime verified; Linux and Windows run in the unit-test matrix |
+
+## Context
+
+The V2 CLI runs a shared managed service that owns Sessions, location graphs,
+plugins, permissions, and tool execution. The service updater can replace the
+installed package while the current process continues running the old image.
+A later TUI launch then detects the version mismatch and replaces the service.
+
+Incident #36688 showed four failures in that replacement path:
+
+- Multiple TUIs spawned heavyweight server contenders.
+- A winner remained unobservable while it cold-booted, so another wave treated
+  it as absent and displaced it.
+- A fresh TUI exhausted its reconnect budget and crashed with an unhandled
+  transport defect.
+- A losing contender remained alive and consumed about 1 GB of RSS.
+
+The `origin/v2` baseline serializes service startup with `EffectFlock`. A
+contender acquires a three-second heartbeat lease, checks whether another
+service became discoverable, and only the winner crosses the application-boot
+boundary. This already prevents simultaneous heavy boots and makes startup
+losers exit.
+
+The lease is released immediately after registration, however, so it is not
+lifetime ownership. Registration then reverts to last-writer-wins authority: a
+deleted or corrupt registration can admit a second boot, a displaced server
+terminates itself through its 10-second registration self-check, and a stalled
+lease holder can be displaced after the three-second service staleness timeout.
+
+`Flock` and `EffectFlock` live in `packages/core/src/util` and are also used for
+config writes, MCP auth, npm installs, and repository caching. Despite the
+name, the primitive is an atomic-mkdir lease with heartbeat and staleness
+takeover, not an OS-held lock. It remains appropriate for bounded critical
+sections, including today's startup fence, but is not lifetime service
+ownership.
+
+The current implementation also mixes three different concepts:
+
+- **Ownership:** which process is allowed to be the managed server.
+- **Discovery:** where clients can reach that process.
+- **Lifecycle:** whether that process is starting, ready, stopping, or failed.
+
+This design gives each concept one authority.
+
+```definitions
+[
+  {
+    "term": "Owner",
+    "definition": "The one process holding the process-held OS service lock."
+  },
+  {
+    "term": "Contender",
+    "definition": "A small serve process attempting to acquire the service lock. It must not initialize the application before winning."
+  },
+  {
+    "term": "Registration",
+    "definition": "An atomic discovery record containing the elected owner's identity and endpoint. Registration never grants ownership."
+  },
+  {
+    "term": "Lifecycle shell",
+    "definition": "The minimal HTTP surface bound by the elected process before application initialization. It serves health and retryable startup responses."
+  },
+  {
+    "term": "Application",
+    "definition": "The full server routes and global or location-scoped modules used for normal OpenCode work."
+  }
+]
+```
+
+## Goals
+
+- At most one process initializes and serves the managed application.
+- Losing contenders exit before database, route, plugin, MCP, or location boot.
+- A slow winner becomes observable before expensive initialization.
+- Existing and freshly launched TUIs survive retryable service unavailability.
+- Reconnect follows service state instead of displaying retry counts or raw
+  transport failures.
+- Version-mismatch replacement remains triggered by a fresh TUI launch.
+- A stale or malformed registration cannot create a second owner.
+- An unresponsive owner is never killed automatically by an arbitrary TUI.
+- Every spawned contender has a bounded path to ownership or exit.
+
+## Non-goals
+
+- Restarting automatically when a background update finds an idle window.
+- Running old and candidate application servers concurrently.
+- Adding a permanent steward, proxy, or supervisor process.
+- Zero-downtime worker handoff or automatic rollback.
+- Application protocol negotiation or automatic TUI self-restart.
+- General hard-crash recovery for active Sessions.
+- Defining recovery semantics for provider attempts, tools, shells, sub-agents,
+  permissions, questions, or background jobs.
+- Automatically killing a frozen owner.
+- Bounding concurrent location cold boots after clients reconnect.
+- Multi-machine or clustered service placement.
+
+## Invariants
+
+1. **The service lock is ownership.** Exactly one process may hold the OS lock
+   for one installation channel and service profile.
+2. **Ownership precedes boot.** A contender performs no expensive application
+   initialization before it acquires the lock.
+3. **Ownership lasts for the process lifetime.** The owner holds an open lock
+   handle until the managed server exits. The OS releases it on process death
+   without a cleanup callback.
+4. **The port is transport, not election.** The owner may select a dynamic port
+   after acquiring the lock.
+5. **Registration is discovery, not election.** Deleting, corrupting, or
+   replacing registration does not invalidate a live owner's lock.
+6. **Only a fresh launch enforces package version.** Existing TUIs reconnect to
+   the current owner without initiating version replacement.
+7. **Transport loss is retryable.** It never terminates a TUI without a separate
+   diagnosed, non-retryable cause.
+8. **Clients do not kill an unresponsive owner automatically.** Destructive
+   recovery requires the explicit `service restart` command.
+9. **Lifecycle does not promise execution semantics.** Graceful replacement
+   invokes Session suspension and resumption hooks, but tool-level continuity
+   belongs to a separate design.
+
+## System Model
+
+```text
+╭───────────────────────╮                              ╭──────────────────────────────╮
+│ Fresh or existing TUI │                              │ Process-held OS service lock │
+╰───────────┬───────────╯                              ╰───────────────┬──────────────╯
+            ╰─────┬ normal requests  observe ───────────────────────╮  │
+                  │ discover               │                        ├──╯ authorizes one owner
+                  ▼                        │                        ▼
+        ╭───────────────────╮              │               ╭─────────────────╮
+        │ Registration file │              │               │ Lifecycle shell │
+        ╰───────────────────╯              │               ╰────────┬────────╯
+                                           │                        │
+                                           ├────────────────────────╯
+                                           ▼
+                               ╭──────────────────────╮
+                               │ OpenCode application │
+                               ╰──────────────────────╯
+```
+
+The lifecycle shell and application run in the same process. The distinction is
+initialization order and responsibility, not process topology.
+
+## Service Status
+
+The server reports one small status value:
+
+```typescript
+type ServiceStatus =
+  | {
+      type: "starting"
+    }
+  | {
+      type: "ready"
+    }
+  | {
+      type: "stopping"
+      targetVersion?: string
+    }
+  | {
+      type: "failed"
+      message: string
+      action: string
+    }
+```
+
+The client adds only the discovery states needed by callers:
+
+```typescript
+type Status = { type: "missing" } | { type: "unreachable" } | { type: "unresponsive" } | ServiceStatus
+```
+
+The health response retains the existing fields for old clients and adds the
+status discriminant:
+
+```typescript
+type ServiceHealth = {
+  healthy: true
+  version: string
+  pid: number
+  instanceID: string
+  status: ServiceStatus
+}
+```
+
+`healthy: true` means the registered lifecycle shell is responding and its
+identity matches registration. New clients use `status.type === "ready"` as
+the application-readiness signal.
+
+During `starting` or `stopping`, application requests are not held in memory.
+They receive an immediate retryable response:
+
+```http
+HTTP/1.1 503 Service Unavailable
+Retry-After: 1
+Content-Type: application/json
+
+{"code":"service_starting"}
+```
+
+`stopping` uses `service_stopping`. A failed application boot uses
+`service_failed` and includes a safe diagnostic message.
+
+A failed owner remains bound and keeps holding the service lock. Exiting on
+failure would let every waiting client's `ensureRunning` loop elect a new
+contender that repeats the same heavy failing boot, so staying bound turns a
+deterministic boot failure into one observable `failed` state instead of a
+client-driven respawn loop. Recovery still works: a fresh launch observes the
+failed instance through the stop path, and explicit `service restart` replaces
+it.
+
+## Registration Contract
+
+Registration contains only discovery identity:
+
+```typescript
+type ServiceRegistration = {
+  schema: 1
+  instanceID: string
+  version: string
+  url: string
+  pid: number
+}
+```
+
+Authentication continues to use the existing private service credential
+storage. The registration schema does not change that policy.
+
+The owner writes registration only after the lifecycle shell has bound:
+
+1. Bind the lifecycle shell.
+2. Write a temporary registration file with mode `0600`.
+3. Atomically rename it over the old registration.
+4. Serve lifecycle health as `starting`.
+
+On shutdown, the owner removes registration only if the current file still has
+its `instanceID`. An old finalizer can never remove a successor's registration.
+
+While running, the owner periodically asserts its registration. Because the
+lock guarantees exactly one live owner, any registration that does not name the
+owner is stale or corrupt, and the owner rewrites it. A deleted or clobbered
+registration therefore heals within one assertion interval instead of leaving
+clients waiting on absent discovery. This inverts today's self-check loop,
+which terminates the displaced process instead of repairing discovery.
+
+Legacy registration shapes are decoded by a compatibility adapter. The new
+domain type does not make fields optional to represent old formats.
+
+## Election
+
+This design promotes today's startup fence into lifetime ownership.
+Last-writer-wins registration is replaced by a process-held OS lock that is
+acquired before any expensive boot work and held for the entire service
+lifetime.
+
+A heartbeat-and-staleness lease, including the existing `Flock` utility, is not
+sufficient for service ownership: the service configures a three-second stale
+timeout, after which its lock can be broken and recreated. An event-loop stall,
+a suspended machine, or a debugger pause can therefore make a live owner appear
+stale and allow a contender to displace it. Service ownership requires a
+process-held OS lock: `flock` on Unix and an exclusively bound named pipe on
+Windows. It cannot be broken because a heartbeat exceeded a timeout. Process
+death releases the lock through the OS.
+
+Neither Bun nor Node exposes `flock` directly, the existing `Flock` utility is
+an mkdir-plus-heartbeat lease rather than an OS-held lock, and the common
+lockfile packages are staleness-based leases as well. The platform layer uses
+`bun:ffi` to call `flock` on POSIX and Node's named-pipe server support on
+Windows, where Bun FFI is not available on every shipped architecture. It lives
+alongside the existing utility in `packages/core/src/util`. This primitive is
+the foundation of the design, so the delivery sequence spikes it first.
+
+```text
+Contender           Lock            Lifecycle              Application
+    │                 │                 │                       │
+    ├─ try acquire ───▶                 │                       │
+    │                 │                 │                       │
+ ╭─ alt: lock held ────────────────────────────────────────────────╮
+ │  │                 │                 │                       │  │
+ │  ◀─ busy ──────────┤                 │                       │  │
+ │  │                 │                 │                       │  │
+ │  ├─────────╮       │                 │                       │  │
+ │  │ exit    │       │                 │                       │  │
+ │  ◀─────────╯       │                 │                       │  │
+ │  │                 │                 │                       │  │
+ ├─ else: lock acquired ───────────────────────────────────────────┤
+ │  │                 │                 │                       │  │
+ │  ◀─ owner ─────────┤                 │                       │  │
+ │  │                 │                 │                       │  │
+ │  ├─ bind, register, starting ────────▶                       │  │
+ │  │                 │                 │                       │  │
+ │  ├─ initialize ──────────────────────────────────────────────▶  │
+ │  │                 │                 │                       │  │
+ │╭─ alt: boot succeeds ──────────────────────────────────────────╮│
+ ││ │                 │                 │                       │ ││
+ ││ │                 │                 ◀─ ready ───────────────┤ ││
+ ││ │                 │                 │                       │ ││
+ │├─ else: boot fails ────────────────────────────────────────────┤│
+ ││ │                 │                 │                       │ ││
+ ││ │                 │                 ◀─ failed, stay bound ──┤ ││
+ ││ │                 │                 │                       │ ││
+ │╰───────────────────────────────────────────────────────────────╯│
+ │  │                 │                 │                       │  │
+ ╰─────────────────────────────────────────────────────────────────╯
+    │                 │                 │                       │
+```
+
+Lock acquisition by a contender is nonblocking or tightly bounded. A loser
+must exit before constructing application routes or importing startup-heavy
+modules.
+
+Several clients may spawn contenders concurrently. The design guarantees one
+heavy winner, not one process spawn. If the winner crashes during startup, the
+OS releases the lock and a later client retry starts another election.
+
+The lock is scoped by installation channel and service profile. Local, preview,
+and stable installations cannot displace one another.
+
+## Update Activation
+
+Background update behavior remains unchanged:
+
+1. The running service checks for an update.
+2. The updater installs the package in the background.
+3. The running process continues using its existing process image.
+4. No idle check or automatic restart occurs.
+
+A fresh TUI launch activates the installed update:
+
+1. Read registration and authenticate the responding service.
+2. If its package version matches the fresh client, attach normally.
+3. If the version differs, request graceful stop of that exact registered
+   instance using the existing authenticated stop path.
+4. Re-check instance identity before every signal or escalation in that path.
+5. Wait for the old process to exit and release the service lock.
+6. Call `ensureRunning` until a compatible service becomes ready.
+
+Concurrent fresh launchers may all observe the same old instance. Stopping that
+exact instance must be idempotent. Once registration names a different instance,
+a stale launcher stops signaling and returns to discovery.
+
+No durable restart-transition record is introduced. The initiating fresh TUI
+already knows the source and target versions and can display its update
+preflight. Existing TUIs may display `Updating...` if they observed `stopping`;
+otherwise `Waiting for background service...` is the honest fallback.
+
+## Fresh Launch Versus Reconnect
+
+Fresh launch and reconnect deliberately have different version policies:
+
+```typescript
+type ManagedConnection =
+  | {
+      type: "launch"
+      requiredVersion: string
+    }
+  | {
+      type: "reconnect"
+    }
+```
+
+- `launch` requires the installed package version and may activate replacement.
+- `reconnect` accepts the current owner and never activates replacement.
+
+This preserves today's permissive reconnect behavior. Explicit application
+protocol negotiation and automatic TUI re-exec remain follow-ups.
+
+## Client Reconnect
+
+Fresh and existing TUIs use the same status loop after startup:
+
+1. Read registration on every attempt. Do not retry a stale URL indefinitely.
+2. If registration is absent, call `ensureRunning` and continue waiting.
+3. If registration is unreachable, call `ensureRunning`. A live owner prevents
+   contenders from acquiring the lock; a dead owner does not.
+4. If status is `starting` or `stopping`, wait.
+5. If status is `failed`, show its actionable message.
+6. If status is `ready`, rebuild HTTP and event-stream clients for the new
+   endpoint and perform authoritative state reconciliation.
+
+Retry cadence is internal policy. Retry counts are telemetry, not user-facing
+state. The TUI waits until the service is ready or the user exits.
+
+Transport failures are handled at the TUI run boundary. A raw client transport
+error or Effect defect must not escape to the terminal. Hard exit is reserved
+for diagnosed causes such as invalid local configuration, failed authentication,
+or a foreign process occupying an explicitly configured port.
+
+The UI derives text from status:
+
+| Status                   | User-facing state                   |
+| ------------------------ | ----------------------------------- |
+| No registration          | `Starting background service...`    |
+| Registration unreachable | `Waiting for background service...` |
+| `starting`               | `Starting OpenCode vX...`           |
+| `stopping`               | `Updating to vX...`                 |
+| `failed`                 | Actionable failure message          |
+| `ready`                  | Normal TUI                          |
+
+## Graceful Session Continuity
+
+Version-mismatch replacement uses the existing graceful Session suspension and
+resumption hooks:
+
+1. The old server snapshots active Session IDs during graceful teardown.
+2. The successor schedules those Sessions for continuation.
+3. The runner reloads durable Session history before continuing.
+
+This lifecycle design does not define what an interrupted physical provider
+attempt or tool invocation means. It does not promise that external side effects
+did not occur, replay the exact interrupted tool, preserve an in-memory form, or
+recover process-local background work.
+
+Those concerns require a separate execution-continuity design covering tools,
+shells, sub-agents, permissions, questions, provider attempts, and hard-crash
+recovery.
+
+## Unresponsive Owner
+
+An unreachable registration does not prove that the owner is dead. A contender
+attempts the service lock:
+
+- If the lock is free, the contender starts a replacement.
+- If the lock is held, the contender exits and the client keeps waiting.
+
+After a bounded diagnostic threshold, the client may show:
+
+```text
+The background service owns the service lock but is not responding.
+Run `opencode service restart` to recover it.
+```
+
+Only explicit `service restart` may perform destructive recovery. It verifies
+the complete registration and process instance before signaling, waits for
+graceful exit, re-checks identity before escalation, and refuses to kill a
+process it cannot positively identify.
+
+Automatic frozen-owner recovery is deferred.
+
+## Failure Walkthroughs
+
+### Update with open TUIs
+
+1. The old service installs vNext but keeps running.
+2. A fresh vNext TUI finds the healthy vOld service and requests graceful stop.
+3. The old service reports `stopping`, suspends active Sessions, and exits.
+4. Open TUIs enter their indefinite status loops.
+5. One or more clients spawn contenders.
+6. One contender acquires the service lock. Losers exit before heavy boot.
+7. The winner binds and registers the lifecycle shell as `starting`.
+8. Clients stop spawning and wait on the observable winner.
+9. The winner initializes the application and reports `ready`.
+10. TUIs rebuild clients, reconcile state, and resume.
+
+### Server crashes while ready
+
+1. The endpoint becomes unreachable and registration may remain stale.
+2. Clients call `ensureRunning`.
+3. Process death has released the service lock.
+4. One contender wins, replaces registration, and starts normally.
+5. Detailed active-execution recovery is outside this design.
+
+### Winner crashes during startup
+
+1. Clients observed `starting` and remain alive.
+2. Process death releases the service lock.
+3. A later reconnect attempt starts another election.
+4. One new contender wins; all other contenders exit.
+
+### Registration is deleted while the owner is healthy
+
+1. Clients may call `ensureRunning` because discovery is absent.
+2. Every contender fails to acquire the owner's lock and exits.
+3. No second application initializes.
+4. The owner's next registration assertion republishes discovery.
+
+### Owner is alive but unresponsive
+
+1. Health fails, but the process still holds the service lock.
+2. Contenders fail lock acquisition and exit.
+3. Clients wait and eventually show explicit recovery guidance.
+4. No TUI kills the owner automatically.
+
+## TDD Verification
+
+Implementation should proceed test-first with real subprocesses and real locks.
+Mocks cannot establish process death, lock release, loser cleanup, or port
+behavior.
+
+### Election tests
+
+| Scenario                                              | Required result                                         |
+| ----------------------------------------------------- | ------------------------------------------------------- |
+| Ten contenders start simultaneously                   | Exactly one crosses the application-boot boundary       |
+| Winner pauses after lock acquisition                  | No loser initializes or remains alive                   |
+| Winner event loop pauses beyond the old stale timeout | Ownership is not displaced                              |
+| Winner crashes before bind                            | Lock releases; a later attempt wins                     |
+| Winner crashes after bind but before registration     | Lock releases; a later attempt replaces stale discovery |
+| Registration is deleted while owner runs              | No second owner initializes                             |
+| Registration is malformed                             | Lock still prevents a second owner                      |
+| Registration names a dead PID                         | New contender can acquire the released lock             |
+| Two installation channels start                       | Each elects an independent owner                        |
+| Explicit configured port is foreign-owned             | Fail diagnostically; do not kill the foreign process    |
+
+The fixture records a marker immediately before application initialization. The
+tests assert that only one process writes that marker and that every loser exits
+within a bounded interval. The harness should also assert that a loser's peak
+RSS stays an order of magnitude below an application boot, since import weight
+was the observed incident cost.
+
+### Lifecycle tests
+
+| Scenario                                        | Required result                                                  |
+| ----------------------------------------------- | ---------------------------------------------------------------- |
+| Winner owns lock but application boot is paused | Health reports `starting`                                        |
+| Application request arrives during startup      | Immediate retryable `503`                                        |
+| Application becomes ready                       | Status changes once from `starting` to `ready`                   |
+| Graceful replacement begins                     | Status reports `stopping` before disconnect                      |
+| Application initialization fails                | Actionable `failed` status; owner stays bound and holds the lock |
+| Registration is deleted while owner runs        | Owner republishes it within one assertion interval               |
+| Owner exits                                     | Registration is removed only if it still names that owner        |
+
+### Update tests
+
+| Scenario                               | Required result                                          |
+| -------------------------------------- | -------------------------------------------------------- |
+| Background update installs vNext       | Running vOld service does not restart                    |
+| Fresh vNext launch finds vOld          | Exact old instance stops; vNext eventually becomes ready |
+| Two fresh vNext launches race          | One heavy successor; both clients attach                 |
+| Existing vOld TUI reconnects to vNext  | It never requests replacement                            |
+| Stale launcher observes a new instance | It does not signal the new instance                      |
+
+### Reconnect tests
+
+| Scenario                                            | Required result                                    |
+| --------------------------------------------------- | -------------------------------------------------- |
+| Endpoint disappears and changes port                | TUI rediscovers and rebuilds clients               |
+| Service remains unavailable beyond old retry budget | TUI remains alive                                  |
+| Event stream reconnects                             | Client performs authoritative state reconciliation |
+| Transport returns an unexpected defect              | TUI formats it; no raw stack escapes               |
+| Owner remains unresponsive                          | TUI waits and shows explicit restart guidance      |
+
+## Delivery Sequence
+
+1. **Spike the lock primitive.** Prove a nonblocking, process-held OS lock
+   under Bun on macOS, Linux, and Windows (`bun:ffi` to `flock` on POSIX and a
+   named pipe on Windows), including release on hard kill and behavior across
+   containers and network filesystems used in CI.
+2. **Expand the subprocess test harness.** Begin from the baseline
+   two-contender test and cover ten contenders, lock release on crash, a paused
+   winner, deleted or corrupt registration, and bounded loser exit before
+   changing ownership.
+3. **Contain client failure.** Make transport loss nonterminal, rediscover on
+   every cycle, and format unexpected failures at the TUI boundary.
+4. **Promote the startup fence to process-held ownership.** Preserve the
+   existing pre-boot acquisition seam, replace its lease with the OS lock, hold
+   it until process exit, and invert the registration self-check from
+   self-termination to reassertion.
+5. **Bind the lifecycle shell first.** Publish registration and `starting`,
+   return retryable `503` for application requests, then initialize the app.
+   The health contract change is public API: regenerate clients from
+   `packages/client` with `bun run generate`.
+6. **Codify launch versus reconnect.** Fresh launch enforces installed version;
+   reconnect never activates replacement.
+7. **Integrate graceful replacement.** Preserve current background-install and
+   fresh-launch activation behavior while invoking Session continuity hooks.
+8. **Harden explicit recovery.** Verify exact process identity during explicit
+   `service restart`; never automatically kill an unresponsive owner.
+9. **Run the full multi-process suite.** Include repeated restart cycles and
+   assert that no contender or child process remains afterward.
+
+## Acceptance Criteria
+
+- Ten concurrent restart observers produce one application initialization.
+- No losing contender survives or builds a location graph.
+- A 30-second application boot remains continuously observable as `starting`.
+- A TUI remains alive through a service outage longer than the previous retry
+  budget.
+- A service endpoint change does not require restarting an existing TUI.
+- Background installation alone does not restart the service.
+- A fresh mismatched TUI eventually attaches to the installed service version.
+- Existing reconnecting TUIs never replace the current owner.
+- Registration corruption cannot produce two owners.
+- A deleted registration heals without restarting the owner or any client.
+- An unresponsive owner is not killed without an explicit recovery command.
+- Raw transport defects never escape to the terminal.
+
+## Follow-ups
+
+- Idle background update activation with an admission fence.
+- Application protocol compatibility and automatic local TUI re-exec.
+- Durable execution recovery for provider attempts and tools.
+- Shell, sub-agent, permission, question, and background-job continuity.
+- Automatic recovery for a positively identified frozen owner.
+- Cold-boot concurrency limits and interaction-prioritized location loading.
+- A steward or socket-handoff architecture if zero-downtime replacement becomes
+  a real requirement.

github/index.ts

@@ -495,7 +495,6 @@ async function subscribeSessionEvents() {
   console.log("Subscribing to session events...")
 
   const TOOL: Record<string, [string, string]> = {
-    todowrite: ["Todo", "\x1b[33m\x1b[1m"],
     bash: ["Bash", "\x1b[31m\x1b[1m"],
     edit: ["Edit", "\x1b[32m\x1b[1m"],
     glob: ["Glob", "\x1b[34m\x1b[1m"],

infra/console.ts

@@ -256,6 +256,7 @@ new sst.cloudflare.x.SolidStart("Console", {
     SECRET.UpstashRedisRestToken,
     AUTH_API_URL,
     STRIPE_WEBHOOK_SECRET,
+    SECRET.SupportApiKey,
     DISCORD_INCIDENT_WEBHOOK_URL,
     SECRET.HoneycombWebhookSecret,
     STRIPE_SECRET_KEY,

infra/enterprise.ts

@@ -7,6 +7,7 @@ new sst.cloudflare.x.SolidStart("Teams", {
   domain: shortDomain,
   path: "packages/enterprise",
   buildCommand: "bun run build:cloudflare",
+  link: [SECRET.SupportApiKey],
   environment: {
     OPENCODE_STORAGE_ADAPTER: "r2",
     OPENCODE_STORAGE_ACCOUNT_ID: sst.cloudflare.DEFAULT_ACCOUNT_ID,

infra/lake.ts

@@ -67,6 +67,10 @@ const athenaWorkgroup = new aws.athena.Workgroup("LakeAthenaWorkgroup", {
   configuration: {
     enforceWorkgroupConfiguration: true,
     publishCloudwatchMetricsEnabled: true,
+    // Athena bills $5/TB scanned; kill any query that would scan more than 2 TB
+    // so a regression cannot silently burn money. Stats sync full passes scan
+    // ~250 GB as of 2026-07.
+    bytesScannedCutoffPerQuery: 2 * 1024 ** 4,
     resultConfiguration: {
       outputLocation: $interpolate`s3://${athenaResultsBucket.bucket}/`,
     },

infra/secret.ts

@@ -9,6 +9,7 @@ export const SECRET = {
   R2SecretKey: new sst.Secret("R2SecretKey", "unknown"),
   HoneycombApiKey: new sst.Secret("HONEYCOMB_API_KEY"),
   HoneycombWebhookSecret: new random.RandomPassword("HoneycombWebhookSecret", { length: 24 }),
+  SupportApiKey: new sst.Secret("SUPPORT_API_KEY"),
   UpstashRedisRestUrl: new sst.Secret("UpstashRedisRestUrl"),
   UpstashRedisRestToken: new sst.Secret("UpstashRedisRestToken"),
 }

infra/stage.ts

@@ -8,6 +8,25 @@ export const zoneID = "430ba34c138cfb5360826c4909f99be8"
 export const awsStage = $app.stage === "production" ? "production" : "dev"
 export const deployAws = $app.stage === awsStage
 
+if ($app.stage === "production") {
+  new cloudflare.DnsRecord("TrustCenter", {
+    zoneId: zoneID,
+    name: "trust.opencode.ai",
+    type: "CNAME",
+    content: "3a69a5bb27875189.vercel-dns-016.com",
+    proxied: false,
+    ttl: 60,
+  })
+
+  new cloudflare.DnsRecord("TrustCenterVerification", {
+    zoneId: zoneID,
+    name: "opencode.ai",
+    type: "TXT",
+    content: "compai-domain-verification=org_6993a99c6200a2d642bb115d",
+    ttl: 60,
+  })
+}
+
 new cloudflare.RegionalHostname("RegionalHostname", {
   hostname: domain,
   regionKey: "us",

infra/stats.ts

@@ -42,11 +42,12 @@ const inferenceEventTable = new aws.s3tables.Table(
             { name: "request", type: "string", required: false },
             { name: "client", type: "string", required: false },
             { name: "user_agent", type: "string", required: false },
+            { name: "model", type: "string", required: false },
+            { name: "model_tier", type: "string", required: false },
             { name: "model_variant", type: "string", required: false },
             { name: "source", type: "string", required: false },
             { name: "provider", type: "string", required: false },
             { name: "provider_model", type: "string", required: false },
-            { name: "model", type: "string", required: false },
             { name: "llm_error_code", type: "int", required: false },
             { name: "llm_error_message", type: "string", required: false },
             { name: "error_response", type: "string", required: false },
@@ -56,6 +57,7 @@ const inferenceEventTable = new aws.s3tables.Table(
             { name: "error_cause2", type: "string", required: false },
             { name: "api_key", type: "string", required: false },
             { name: "workspace", type: "string", required: false },
+            { name: "user_id", type: "string", required: false },
             { name: "is_subscription", type: "boolean", required: false },
             { name: "subscription", type: "string", required: false },
             { name: "response_length", type: "long", required: false },
@@ -84,7 +86,7 @@ const inferenceEventTable = new aws.s3tables.Table(
       },
     },
   },
-  { deleteBeforeReplace: $app.stage !== "production" },
+  { deleteBeforeReplace: $app.stage !== "production", ignoreChanges: ["metadata"] },
 )
 
 export const inferenceEvent = new sst.Linkable("InferenceEvent", {
@@ -183,7 +185,9 @@ export const statSync = new sst.aws.Service("StatsSyncService", {
   cluster: lakeCluster,
   architecture: "arm64",
   cpu: "0.25 vCPU",
-  memory: "0.5 GB",
+  // 0.5 GB caused an OOM crash loop: every restart immediately re-ran the 4 Athena
+  // stats queries (~$5/pass) every ~5 minutes instead of hourly.
+  memory: "2 GB",
   image: {
     context: ".",
     dockerfile: "packages/stats/server/Dockerfile",

nix/desktop.nix

@@ -8,6 +8,8 @@
   makeWrapper,
   writableTmpDirAsHomeHook,
   autoPatchelfHook,
+  copyDesktopItems,
+  makeDesktopItem,
   opencode,
 }:
 let
@@ -27,9 +29,12 @@ stdenv.mkDerivation (finalAttrs: {
     nodejs
     makeWrapper
     writableTmpDirAsHomeHook
-  ] ++ lib.optionals stdenv.hostPlatform.isLinux [
+  ]
+  ++ lib.optionals stdenv.hostPlatform.isLinux [
     autoPatchelfHook
-  ] ++ lib.optionals stdenv.hostPlatform.isDarwin [
+    copyDesktopItems
+  ]
+  ++ lib.optionals stdenv.hostPlatform.isDarwin [
     # Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
     darwin.autoSignDarwinBinariesHook
   ];
@@ -38,20 +43,37 @@ stdenv.mkDerivation (finalAttrs: {
     (lib.getLib stdenv.cc.cc)
   ];
 
+  desktopItems = lib.optional stdenv.hostPlatform.isLinux (makeDesktopItem {
+    name = "ai.opencode.desktop";
+    desktopName = "OpenCode";
+    exec = "opencode-desktop %U";
+    icon = "ai.opencode.desktop";
+    # Electron 41 derives X11 WM_CLASS from app.name.
+    startupWMClass = "OpenCode";
+    categories = [ "Development" ];
+  });
+
   env = opencode.env // {
     ELECTRON_SKIP_BINARY_DOWNLOAD = "1";
   };
 
-  # https://github.com/electron/electron/issues/31121
-  # mac builds use a .app bundle which doesnt have this issue
-  postPatch = lib.optionalString stdenv.isLinux ''
-    BASE_PATH=packages/desktop
-    FILES=(src/main/windows.ts)
-    for file in "''${FILES[@]}"; do
-      substituteInPlace $BASE_PATH/$file \
-        --replace-fail "process.resourcesPath" "'$out/opt/opencode-desktop/resources'"
-    done
-  '';
+  postPatch =
+    # NOTE: Relax Bun version check to be a warning instead of an error
+    ''
+      substituteInPlace packages/script/src/index.ts \
+        --replace-fail 'throw new Error(`This script requires bun@''${expectedBunVersionRange}' \
+                       'console.warn(`Warning: This script requires bun@''${expectedBunVersionRange}'
+    ''
+    # https://github.com/electron/electron/issues/31121
+    # mac builds use a .app bundle which doesnt have this issue
+    + lib.optionalString stdenv.isLinux ''
+      BASE_PATH=packages/desktop
+      FILES=(src/main/windows.ts)
+      for file in "''${FILES[@]}"; do
+        substituteInPlace $BASE_PATH/$file \
+          --replace-fail "process.resourcesPath" "'$out/opt/opencode-desktop/resources'"
+      done
+    '';
 
   preBuild = ''
     cp -r "${electron.dist}" $HOME/.electron-dist
@@ -76,27 +98,38 @@ stdenv.mkDerivation (finalAttrs: {
     runHook postBuild
   '';
 
-  installPhase =
-    ''
-      runHook preInstall
-    ''
-    + lib.optionalString stdenv.hostPlatform.isDarwin ''
-      mkdir -p $out/Applications
-      mv dist/mac*/*.app $out/Applications
-      makeWrapper "$out/Applications/OpenCode.app/Contents/MacOS/OpenCode" $out/bin/opencode-desktop
-    ''
-    + lib.optionalString stdenv.hostPlatform.isLinux ''
-      mkdir -p $out/opt/opencode-desktop
-      cp -r dist/linux*-unpacked/{resources,LICENSE*} $out/opt/opencode-desktop
-      makeWrapper ${lib.getExe electron} $out/bin/opencode-desktop \
-        --inherit-argv0 \
-        --set ELECTRON_FORCE_IS_PACKAGED 1 \
-        --add-flags $out/opt/opencode-desktop/resources/app.asar \
-        --add-flags "\''${NIXOS_OZONE_WL:+\''${WAYLAND_DISPLAY:+--ozone-platform-hint=auto --enable-features=WaylandWindowDecorations --enable-wayland-ime=true}}"
-    ''
-    + ''
-      runHook postInstall
-    '';
+  installPhase = ''
+    runHook preInstall
+  ''
+  + lib.optionalString stdenv.hostPlatform.isDarwin ''
+    mkdir -p $out/Applications
+    mv dist/mac*/*.app $out/Applications
+    makeWrapper "$out/Applications/OpenCode.app/Contents/MacOS/OpenCode" $out/bin/opencode-desktop
+  ''
+  + lib.optionalString stdenv.hostPlatform.isLinux ''
+    mkdir -p $out/opt/opencode-desktop
+    cp -r dist/linux*-unpacked/{resources,LICENSE*} $out/opt/opencode-desktop
+    install -Dm644 resources/icons/32x32.png \
+      "$out/share/icons/hicolor/32x32/apps/ai.opencode.desktop.png"
+    install -Dm644 resources/icons/64x64.png \
+      "$out/share/icons/hicolor/64x64/apps/ai.opencode.desktop.png"
+    install -Dm644 resources/icons/128x128.png \
+      "$out/share/icons/hicolor/128x128/apps/ai.opencode.desktop.png"
+    install -Dm644 resources/icons/128x128@2x.png \
+      "$out/share/icons/hicolor/256x256/apps/ai.opencode.desktop.png"
+    install -Dm644 resources/icons/icon.png \
+      "$out/share/icons/hicolor/512x512/apps/ai.opencode.desktop.png"
+    install -Dm644 resources/ai.opencode.desktop.metainfo.xml \
+      "$out/share/metainfo/ai.opencode.desktop.metainfo.xml"
+    makeWrapper ${lib.getExe electron} $out/bin/opencode-desktop \
+     --inherit-argv0 \
+     --set ELECTRON_FORCE_IS_PACKAGED 1 \
+     --add-flags $out/opt/opencode-desktop/resources/app.asar \
+     --add-flags "\''${NIXOS_OZONE_WL:+\''${WAYLAND_DISPLAY:+--ozone-platform-hint=auto --enable-features=WaylandWindowDecorations --enable-wayland-ime=true}}"
+  ''
+  + ''
+    runHook postInstall
+  '';
 
   autoPatchelfIgnoreMissingDeps = [
     "libc.musl-x86_64.so.1"

nix/hashes.json

@@ -1,8 +1,8 @@
 {
   "nodeModules": {
-    "x86_64-linux": "sha256-oWSGu+SP66Aquy/0Vaq7Bgp8404ZdOWbQX+O7h3jxHU=",
-    "aarch64-linux": "sha256-UsS0+c+GwtIukmWwQeFbY/3Oaz3t4Q7C6cFMGkmlyAY=",
-    "aarch64-darwin": "sha256-CArz92ewPmXO+ORFCBkCH8LzMpU/DjyaO4ic7QL0UpI=",
-    "x86_64-darwin": "sha256-rhnz9gmG6L06wIzfMhTaXDDEf6IbMD32CavqwXoqcUs="
+    "x86_64-linux": "sha256-qt11SKmOjq0KU542QFbs+u7YyJicn4drCcwCdg325yk=",
+    "aarch64-linux": "sha256-z68doReXTrWS7HeiAjc0btIjAsvzeZZ7hXAlHr0c77Q=",
+    "aarch64-darwin": "sha256-PILYH1Pi8XBvSkuZ+1sNnUTao5kba+m5Z8iJKx6YXPo=",
+    "x86_64-darwin": "sha256-KpcJzP4m0SUavu/WaSffgzOxrHq8ljdy0GOzs9p16lo="
   }
 }

nix/opencode.nix

@@ -27,6 +27,13 @@ stdenvNoCC.mkDerivation (finalAttrs: {
     writableTmpDirAsHomeHook
   ];
 
+  postPatch = ''
+    # NOTE: Relax Bun version check to be a warning instead of an error
+    substituteInPlace packages/script/src/index.ts \
+      --replace-fail 'throw new Error(`This script requires bun@''${expectedBunVersionRange}' \
+                     'console.warn(`Warning: This script requires bun@''${expectedBunVersionRange}'
+  '';
+
   configurePhase = ''
     runHook preConfigure
 

package.json

@@ -2,23 +2,30 @@
   "$schema": "https://json.schemastore.org/package.json",
   "name": "opencode",
   "description": "AI-powered development tool",
+  "version": "0.0.0",
   "private": true,
   "type": "module",
   "packageManager": "bun@1.3.14",
   "scripts": {
-    "dev": "bun run --cwd packages/opencode --conditions=browser src/index.ts",
+    "dev": "bun run --cwd packages/cli --conditions=browser src/index.ts",
     "dev:desktop": "bun --cwd packages/desktop dev",
     "dev:web": "bun --cwd packages/app dev",
     "dev:console": "ulimit -n 10240 2>/dev/null; bun run --cwd packages/console/app dev",
     "dev:stats": "bun sst shell --stage=production -- bun run --cwd packages/stats/app dev",
+    "dev:www": "bun run --cwd packages/www dev",
     "dev:storybook": "bun --cwd packages/storybook storybook",
     "lint": "oxlint",
-    "typecheck": "bun turbo typecheck",
+    "lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/util/src packages/core/src packages/server/src packages/protocol/src packages/cli/src",
+    "test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
+    "typecheck": "bun turbo typecheck --concurrency=3",
+    "typecheck:profile": "bun script/profile-typecheck.ts",
+    "typecheck:profile:packages": "bun script/profile-typecheck-packages.ts",
     "upgrade-opentui": "bun run script/upgrade-opentui.ts",
     "postinstall": "bun run --cwd packages/core fix-node-pty",
     "prepare": "husky",
     "random": "echo 'Random script'",
     "sso": "aws sso login --sso-session=opencode --no-browser",
+    "translate:app": "bun run script/translate-app.ts",
     "test": "echo 'do not run tests from root' && exit 1"
   },
   "workspaces": {
@@ -30,22 +37,23 @@
       "packages/slack"
     ],
     "catalog": {
-      "@effect/opentelemetry": "4.0.0-beta.83",
-      "@effect/platform-node": "4.0.0-beta.83",
-      "@effect/sql-sqlite-bun": "4.0.0-beta.83",
+      "@effect/opentelemetry": "4.0.0-beta.98",
+      "@effect/platform-node": "4.0.0-beta.98",
+      "@effect/sql-sqlite-bun": "4.0.0-beta.98",
       "@npmcli/arborist": "9.4.0",
       "@types/bun": "1.3.13",
       "@types/cross-spawn": "6.0.6",
       "@octokit/rest": "22.0.0",
       "@hono/standard-validator": "0.2.0",
       "@hono/zod-validator": "0.4.2",
-      "@opentui/core": "0.3.4",
-      "@opentui/keymap": "0.3.4",
-      "@opentui/solid": "0.3.4",
-      "@tanstack/solid-virtual": "3.13.28",
+      "@opentui/core": "0.4.5",
+      "@opentui/keymap": "0.4.5",
+      "@opentui/solid": "0.4.5",
+      "@tanstack/solid-virtual": "3.13.32",
       "@shikijs/stream": "4.2.0",
       "ulid": "3.0.1",
       "@kobalte/core": "0.13.11",
+      "@corvu/drawer": "0.2.4",
       "@types/luxon": "3.7.1",
       "@types/node": "24.12.2",
       "@types/semver": "7.7.1",
@@ -61,14 +69,15 @@
       "dompurify": "3.3.1",
       "drizzle-kit": "1.0.0-rc.2",
       "drizzle-orm": "1.0.0-rc.2",
-      "effect": "4.0.0-beta.83",
+      "effect": "4.0.0-beta.98",
       "ai": "6.0.168",
       "cross-spawn": "7.0.6",
       "hono": "4.10.7",
       "hono-openapi": "1.1.2",
       "fuzzysort": "3.1.0",
+      "get-east-asian-width": "1.6.0",
       "luxon": "3.6.1",
-      "marked": "17.0.1",
+      "marked": "17.0.6",
       "marked-shiki": "1.2.1",
       "remend": "1.3.0",
       "@playwright/test": "1.59.1",
@@ -77,9 +86,11 @@
       "@typescript/native-preview": "7.0.0-dev.20251207.1",
       "zod": "4.1.8",
       "remeda": "2.26.0",
+      "resolve.exports": "2.0.3",
       "sst": "4.13.1",
       "shiki": "4.2.0",
       "solid-list": "0.3.0",
+      "string-width": "7.2.0",
       "tailwindcss": "4.1.11",
       "vite": "7.1.4",
       "@solidjs/meta": "0.29.4",
@@ -94,6 +105,9 @@
   },
   "devDependencies": {
     "@actions/artifact": "5.0.1",
+    "@ast-grep/cli": "0.44.0",
+    "@types/react": "19.2.17",
+    "@types/react-dom": "19.2.3",
     "@tsconfig/bun": "catalog:",
     "@types/mime-types": "3.0.1",
     "@typescript/native-preview": "catalog:",
@@ -104,7 +118,7 @@
     "prettier": "3.6.2",
     "semver": "^7.6.0",
     "sst": "catalog:",
-    "turbo": "2.8.13"
+    "turbo": "2.10.2"
   },
   "dependencies": {
     "@aws-sdk/client-s3": "3.933.0",
@@ -146,13 +160,13 @@
     "@silvia-odwyer/photon-node@0.3.4": "patches/@silvia-odwyer%2Fphoton-node@0.3.4.patch",
     "@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
     "solid-js@1.9.10": "patches/solid-js@1.9.10.patch",
-    "@ai-sdk/xai@3.0.82": "patches/@ai-sdk%2Fxai@3.0.82.patch",
+    "@ai-sdk/xai@3.0.102": "patches/@ai-sdk%2Fxai@3.0.102.patch",
     "gcp-metadata@8.1.2": "patches/gcp-metadata@8.1.2.patch",
     "pacote@21.5.0": "patches/pacote@21.5.0.patch",
     "@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
-    "@tanstack/solid-virtual@3.13.28": "patches/@tanstack%2Fsolid-virtual@3.13.28.patch",
     "@pierre/trees@1.0.0-beta.4": "patches/@pierre%2Ftrees@1.0.0-beta.4.patch",
     "@modelcontextprotocol/sdk@1.29.0": "patches/@modelcontextprotocol%2Fsdk@1.29.0.patch",
-    "@tanstack/virtual-core@3.17.0": "patches/@tanstack%2Fvirtual-core@3.17.0.patch"
+    "effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
+    "@tanstack/virtual-core@3.17.3": "patches/@tanstack%2Fvirtual-core@3.17.3.patch"
   }
 }

packages/ai/AGENTS.md

@@ -0,0 +1,340 @@
+# AI Package Guide
+
+## Effect
+
+- Prefer `HttpClient.HttpClient` / `HttpClientResponse.HttpClientResponse` over web `fetch` / `Response` at package boundaries.
+- Use `Stream.Stream` for streaming data flow. Avoid ad hoc async generators or manual web reader loops unless an Effect `Stream` API cannot model the behavior.
+- Use Effect Schema codecs for JSON encode/decode (`Schema.fromJsonString(...)`) instead of direct `JSON.parse` / `JSON.stringify` in implementation code.
+- In `Effect.gen`, yield yieldable errors directly (`return yield* new MyError(...)`) instead of `Effect.fail(new MyError(...))`.
+- Use `Effect.void` instead of `Effect.succeed(undefined)` when the successful value is intentionally void.
+
+## Conventions
+
+Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `Model.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, `LLM.updateRequest`, and `LLM.generateObject`. Two ways to construct the same thing is one too many.
+
+## Tests
+
+- Use `testEffect(...)` from `test/lib/effect.ts` for tests requiring Effect layers.
+- Keep provider tests fixture-first. Live provider calls must stay behind `RECORD=true` and required API-key checks.
+
+## Architecture
+
+This package is an Effect Schema-first LLM core. The Schema classes in `src/schema/` are the canonical runtime data model. Convenience functions in `src/llm.ts` are thin constructors that return those same Schema class instances; they should improve callsites without creating a second model.
+
+Primary in-repo integration point:
+
+- `packages/opencode/src/session/llm.ts` is the session-owned orchestration layer that decides whether a request uses AI SDK or this package's native route runtime.
+- `packages/opencode/src/session/llm/native-request.ts` is the lowering adapter from opencode's session/AI SDK-shaped data into this package's `LLMRequest` model.
+- `packages/opencode/src/session/llm/native-runtime.ts` is the execution adapter that calls raw `LLMClient.stream(request)` and bridges one provider turn of opencode tool calls through this package's typed dispatcher.
+- `packages/opencode/src/session/llm/ai-sdk.ts` keeps the default AI SDK path compatible by converting AI SDK stream parts into this package's shared `LLMEvent`s.
+
+Keep this package independent of session concerns. Session auth, permissions, plugins, telemetry headers, and runtime selection belong in `packages/opencode/src/session/llm.ts` and its local adapters.
+
+### Request Flow
+
+The intended callsite is:
+
+```ts
+const request = LLM.request({
+  model: OpenAI.configure({ apiKey }).responses("gpt-4o-mini"),
+  system: "You are concise.",
+  prompt: "Say hello.",
+})
+
+const response = yield * LLMClient.generate(request)
+```
+
+`LLM.request(...)` builds an `LLMRequest`. `LLMClient.generate(...)` reads the executable route carried by `request.model.route`, builds the provider-native body, asks the route's transport for a real `HttpClientRequest.HttpClientRequest`, sends it through `RequestExecutor.Service`, parses the provider stream into common `LLMEvent`s, and finally returns an `LLMResponse`.
+
+Use `LLMClient.stream(request)` when callers want incremental `LLMEvent`s. Use `LLMClient.generate(request)` when callers want those same events collected into an `LLMResponse`. Use `LLMClient.prepare<Body>(request)` to compile a request through the route pipeline without sending it — the optional `Body` type argument narrows `.body` to the route's native shape (e.g. `prepare<OpenAIChatBody>(...)` returns a `PreparedRequestOf<OpenAIChatBody>`). The runtime body is identical; the generic is a type-level assertion.
+
+Filter or narrow `LLMEvent` streams with `LLMEvent.is.*` (camelCase guards, e.g. `events.filter(LLMEvent.is.toolCall)`). The kebab-case `LLMEvent.guards["tool-call"]` form also works but prefer `is.*` in new code.
+
+### Routes
+
+A route is the registered, runnable composition of four orthogonal pieces:
+
+- **`Protocol`** (`src/route/protocol.ts`) — semantic API contract. Owns request body construction (`body.from`), the body schema (`body.schema`), the streaming-event schema (`stream.event`), and the event-to-`LLMEvent` state machine (`stream.step`). `Route.make(...)` validates and JSON-encodes the body from `body.schema` and decodes frames with `stream.event`. Examples: `OpenAIChat.protocol`, `OpenAIResponses.protocol`, `AnthropicMessages.protocol`, `Gemini.protocol`, `BedrockConverse.protocol`.
+- **`Endpoint`** (`src/route/endpoint.ts`) — URL construction. The host, path, and route query live on the endpoint. `Endpoint.path("/chat/completions", { baseURL })` is the common case; pass a function for paths that embed the model id or a body field (e.g. `Endpoint.path(({ body }) => `/model/${body.modelId}/converse-stream`)`).
+- **`Auth`** (`src/route/auth.ts`) — per-request transport authentication. Provider facades configure credentials onto the route before model selection, usually via `Auth.bearer(apiKey)` or `Auth.header(name, apiKey)`. Routes that need per-request signing (Bedrock SigV4, future Vertex IAM, Azure AAD) implement `Auth` as a function that signs the body and merges signed headers into the result.
+- **`Framing`** (`src/route/framing.ts`) — bytes → frames. SSE (`Framing.sse`) is shared; Bedrock keeps its AWS event-stream framing as a typed `Framing<object>` value alongside its protocol.
+
+Compose them via `Route.make(...)`:
+
+```ts
+export const route = Route.make({
+  id: "openai-chat",
+  provider: "openai",
+  protocol: OpenAIChat.protocol,
+  endpoint: Endpoint.path("/chat/completions", {
+    baseURL: "https://api.openai.com/v1",
+  }),
+  auth: Auth.bearer(),
+  framing: Framing.sse,
+})
+```
+
+Route defaults are request-shaping defaults such as `headers`, `limits`, `generation`, `providerOptions`, and `http`. Endpoint host/query belongs on the route endpoint. Selected `Model` values carry only model id, provider id, and the configured route value. Model capability/catalog metadata lives outside this package; protocol support is enforced by request lowering and typed `LLMError`s.
+
+The four-axis decomposition is the reason DeepSeek, TogetherAI, Cerebras, Baseten, Fireworks, and DeepInfra all reuse `OpenAIChat.protocol` verbatim — each provider deployment is a 5-15 line `Route.make(...)` call instead of a 300-400 line route clone. Bug fixes in one protocol propagate to every consumer of that protocol in a single commit.
+
+When a provider ships a non-HTTP transport (OpenAI's WebSocket Responses backend, hypothetical bidirectional streaming APIs), the seam is `Transport` — `WebSocketTransport.jsonTransport.with(...)` constructs an IO template whose `prepare` receives the route endpoint/auth at compile time, builds a WebSocket URL and message, and whose `frames` yields decoded text from the socket. Same protocol and endpoint source, different transport.
+
+### URL Construction
+
+`Endpoint` owns `{ baseURL, path, query }`. Each protocol route includes a canonical endpoint when the provider has one (e.g. `https://api.openai.com/v1`); provider helpers override endpoint fields by configuring the route before selecting a model. Routes that have no canonical URL (OpenAI-compatible Chat, GitHub Copilot) require configuration before execution.
+
+For providers where the URL is derived from typed inputs (Azure resource name, Bedrock region), the provider helper configures the route endpoint before calling `.model(...)`. Use `AtLeastOne<T>` from `route/auth-options.ts` for inputs that accept either of two derivation paths (Azure: `resourceName` or `baseURL`).
+
+### Provider Facades
+
+Provider-facing APIs are configured facades over route values. Endpoint/auth/resource/API-version setup happens before model selection, and model selectors accept only a model or deployment id:
+
+```ts
+const openai = OpenAI.configure({ apiKey, baseURL })
+const model = openai.responses("gpt-4o-mini")
+
+const azure = Azure.configure({ resourceName, apiKey, apiVersion: "v1" })
+const deployment = azure.responses("my-deployment")
+
+const gateway = CloudflareAIGateway.configure({ accountId, gatewayId, gatewayApiKey, apiKey })
+const proxied = gateway.model("openai/gpt-4o-mini")
+```
+
+Keep provider facades small and explicit:
+
+- Use branded `ProviderID.make(...)` and `ModelID.make(...)` where ids are constructed directly.
+- Use `model` for the default API path and named methods for provider-native alternatives such as OpenAI `responses`, `responsesWebSocket`, and `chat`.
+- Put provider-specific setup on `.configure(...)`; do not add `model(id, overrides)` as a duplicate construction path.
+- Export lower-level `routes` arrays separately only when advanced internal wiring needs them.
+- Prefer `apiKey` as provider-specific sugar and `auth` as the explicit override; keep them mutually exclusive in provider option types with `ProviderAuthOption`.
+- Resolve `apiKey` → `Auth` with `AuthOptions.bearer(options, "<PROVIDER>_API_KEY")` (it honors an explicit `auth` override and falls back to `Auth.config(envVar)` so missing keys surface a typed `Authentication` error rather than a runtime crash).
+- Use separate top-level facades for products with different required setup, such as `CloudflareAIGateway` and `CloudflareWorkersAI`.
+
+`Provider.make(...)` remains available for simple static provider definitions, but new built-in providers should prefer plain configured facades unless a helper removes real duplication without adding runtime behavior.
+
+### Provider Package Entrypoints
+
+Catalog-selected native providers use package-like export paths from `@opencode-ai/ai`. They are internal entrypoints in one npm package, not separately published provider packages. Every entrypoint implements `ProviderPackage.Definition` and exposes `model(modelID, settings)`, where settings are serializable provider configuration plus common `headers`, `body`, and `limits` overlays.
+
+```ts
+import { model } from "@opencode-ai/ai/providers/openai/responses"
+
+const selected = model("gpt-5", {
+  apiKey,
+  transport: "websocket",
+})
+```
+
+Keep semantic APIs as separate entrypoints, such as OpenAI `chat` and `responses`. Keep transport choices inside the semantic entrypoint settings, so OpenAI Responses HTTP and WebSocket share one entrypoint. Provider facades may still expose named selectors such as `responsesWebSocket` for direct typed call sites; the package-like contract maps its settings to those selectors before returning an executable `Model`.
+
+Do not expose `Route` in provider package settings. Route composition stays an implementation detail behind `model(...)`.
+
+### Folder layout
+
+```
+packages/ai/src/
+  schema/                   canonical Schema model, split by concern
+    ids.ts                  branded IDs, literal types, ProviderMetadata
+    options.ts              Generation/Provider/Http options, Limits, Model, cache policy
+    messages.ts             content parts, Message, ToolDefinition, LLMRequest
+    events.ts               Usage, individual events, LLMEvent, PreparedRequest, LLMResponse
+    errors.ts               error reasons, LLMError, ToolFailure
+    index.ts                barrel
+  llm.ts                    request constructors and convenience helpers
+  route/
+    index.ts                @opencode-ai/ai/route advanced barrel
+    client.ts               Route.make + LLMClient.prepare/stream/generate
+    executor.ts             RequestExecutor service + transport error mapping
+    protocol.ts             Protocol type + Protocol.make
+    endpoint.ts             Endpoint type + Endpoint.path
+    auth.ts                 Auth type + Auth.bearer / Auth.apiKeyHeader / Auth.passthrough
+    auth-options.ts         ProviderAuthOption shape, AuthOptions.bearer, AtLeastOne helper
+    framing.ts              Framing type + Framing.sse
+    transport/              transport implementations
+      index.ts              Transport type + HttpTransport / WebSocketTransport namespaces
+      http.ts               HttpTransport.httpJson — POST + framing
+      websocket.ts          WebSocketTransport.json + WebSocketExecutor service
+  protocols/
+    shared.ts               ProviderShared toolkit used inside protocol impls
+    openai-chat.ts          protocol + route (compose OpenAIChat.protocol)
+    openai-responses.ts
+    anthropic-messages.ts
+    gemini.ts
+    bedrock-converse.ts
+    bedrock-event-stream.ts framing for AWS event-stream binary frames
+    openai-compatible-chat.ts route that reuses OpenAIChat.protocol, no canonical URL
+    openai-compatible-responses.ts route that reuses OpenAIResponses.protocol, no canonical URL
+    utils/                  per-protocol helpers (auth, cache, media, tool-stream, ...)
+  providers/
+    openai-compatible.ts    generic Chat helper + family model helpers
+    openai-compatible-responses.ts generic Responses helper
+    openai-compatible-profile.ts family defaults (deepseek, togetherai, ...)
+    azure.ts / amazon-bedrock.ts / cloudflare.ts / github-copilot.ts / google.ts / xai.ts / openai.ts / anthropic.ts / openrouter.ts
+  tool.ts                   typed tool() helper
+  tool-runtime.ts           narrow one-call typed tool dispatcher
+```
+
+The dependency arrow points down: `providers/*.ts` files import protocol routes and auth-option utilities; protocol modules import `endpoint`, `auth`, `framing`, and transport pieces. Protocols do not import provider facades. Lower-level modules know nothing about provider catalog metadata.
+
+### Shared protocol helpers
+
+`ProviderShared` exports a small toolkit used inside protocol implementations to keep them focused on provider-native shapes:
+
+- `joinText(parts)` — joins an array of `TextPart` (or anything with a `.text`) with newlines. Use this anywhere a protocol flattens text content into a single string for a provider field.
+- `parseToolInput(route, name, raw)` — Schema-decodes a tool-call argument string with the canonical "Invalid JSON input for `<route>` tool call `<name>`" error message. Treats empty input as `{}`.
+- `parseJson(route, raw, message)` — generic JSON-via-Schema decode for non-tool bodies.
+- `eventError(route, message, ...)` — typed `InvalidProviderOutput` constructor for stream-time decode failures.
+- `validateWith(decoder)` — maps Schema decode errors to `InvalidRequest`. `Route.make(...)` uses this for body validation; lower-level routes can reuse it.
+- `matchToolChoice(provider, choice, branches)` — branches over `LLMRequest["toolChoice"]` for provider-specific lowering.
+
+If you find yourself copying a 3-to-5-line snippet between two protocols, lift it into `ProviderShared` next to these helpers rather than duplicating.
+
+### Chronological System Updates
+
+`LLMRequest.system` is the initial privileged prompt that applies ahead of the conversation. `Message.system(...)` is a separate, provider-neutral chronological operator update inside `LLMRequest.messages`; it applies only from its position in history onward and accepts text content only.
+
+Native chronological system messages are route/model-specific. Anthropic Messages lowers them natively for Claude Opus 4.8 (`claude-opus-4-8`). Other routes and models intentionally lower the update in place into ordinary user-compatible text using this stable escaped representation:
+
+```text
+<system-update>
+...
+</system-update>
+```
+
+The wrapped-user fallback preserves ordering while visibly lowering authority. Never silently pass a raw chronological `role: "system"` through a route that might reject it. Do not insert raw retrieved documents, tool output, or web content into privileged chronological system updates; keep untrusted content in ordinary user/tool channels.
+
+### Tools
+
+Tool loops are represented in common messages and events:
+
+```ts
+const call = ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })
+const result = Message.tool({ id: "call_1", name: "lookup", result: { forecast: "sunny" } })
+
+const followUp = LLM.request({
+  model,
+  messages: [Message.user("Weather?"), Message.assistant([call]), result],
+})
+```
+
+Routes lower these into provider-native assistant tool-call messages and tool-result messages. Streaming providers should emit `tool-input-delta` events while arguments arrive, then a final `tool-call` event with parsed input.
+
+### Tool dispatch
+
+`LLM.stream(request)` and `LLM.generate(request)` each run exactly one provider turn. Add tool schemas to `request.tools` with `Tool.toDefinitions(tools)`. When a caller wants the package's typed one-call execution behavior, pass each canonical local `tool-call` event to `ToolRuntime.dispatch(tools, call)`.
+
+```ts
+const get_weather = tool({
+  description: "Get current weather for a city",
+  parameters: Schema.Struct({ city: Schema.String }),
+  success: Schema.Struct({ temperature: Schema.Number, condition: Schema.String }),
+  execute: ({ city }) =>
+    Effect.gen(function* () {
+      // city: string  — typed from parameters Schema
+      const data = yield* WeatherApi.fetch(city)
+      return { temperature: data.temp, condition: data.cond }
+      // return type checked against success Schema
+    }),
+})
+
+const tools = { get_weather, get_time, ... }
+const events = yield* LLM.stream(
+  LLM.updateRequest(request, { tools: Tool.toDefinitions(tools) }),
+).pipe(Stream.runCollect)
+
+const call = Array.from(events).find(LLMEvent.is.toolCall)
+if (call && !call.providerExecuted) {
+  const dispatched = yield* ToolRuntime.dispatch(tools, call)
+  // Persist call + dispatched.result, then construct the next request explicitly.
+}
+```
+
+The dispatcher:
+
+- On `tool-call`: looks up the named tool, decodes input against `parameters` Schema, dispatches to the typed `execute`, encodes the result against `success` Schema, and returns canonical `tool-result` events.
+- Does not stream providers, construct Session events, schedule fibers, append history, count steps, or continue model rounds.
+- Leaves persistence and continuation to the enclosing product flow.
+
+Handler dependencies (services, permissions, plugin hooks, abort handling) are closed over by the consumer at tool-construction time. Build the tools record inside an `Effect.gen` once and reuse it across many dispatches.
+
+Errors must be expressed as `ToolFailure`. The runtime catches it and emits a `tool-error` event, then a `tool-result` of `type: "error"`, so the model can self-correct on the next step. Anything that is not a `ToolFailure` is treated as a defect and fails the stream. Three recoverable error paths produce `tool-error` events:
+
+- The model called an unknown tool name.
+- Input failed the `parameters` Schema.
+- The handler returned a `ToolFailure`.
+
+Provider-defined / hosted tools (Anthropic `web_search` / `code_execution` / `web_fetch`, OpenAI Responses `web_search_call` / `file_search_call` / `code_interpreter_call` / `mcp_call` / `local_shell_call` / `image_generation_call` / `computer_use_call`) pass through the runtime untouched:
+
+- Routes surface the model's call as a `tool-call` event with `providerExecuted: true`, and the provider's result as a matching `tool-result` event with `providerExecuted: true`.
+- Callers detect `providerExecuted` on `tool-call` and **skip local dispatch** — no handler is invoked and no `tool-error` is raised for "unknown tool". The provider already executed it.
+- Callers that continue should retain both events in explicit history when the protocol requires it. Anthropic encodes them back as `server_tool_use` + `web_search_tool_result` (or `code_execution_tool_result` / `web_fetch_tool_result`) blocks; OpenAI Responses callers typically use `previous_response_id` instead of resending hosted-tool items.
+
+Add provider-defined tools to `request.tools` (no runtime entry needed). The matching route must know how to lower the tool definition into the provider-native shape; right now Anthropic accepts `web_search` / `code_execution` / `web_fetch` and OpenAI Responses accepts the hosted tool names listed above.
+
+## Protocol File Style
+
+Protocol files should look self-similar. Provider quirks belong behind named helpers so a new route can be reviewed by comparing the same sections across files.
+
+### Section order
+
+Use this order for every protocol module:
+
+1. Public model input
+2. Request body schema
+3. Streaming event schema
+4. Parser state
+5. Request body construction (`fromRequest`)
+6. Stream parsing (`step` and per-event handlers)
+7. Protocol and route
+8. Protocol route export
+
+### Rules
+
+- Keep protocol files focused on the protocol. Move provider-specific projection, signing, media normalization, or other bulky transformations into `src/protocols/utils/*`.
+- Use `Effect.fn("Provider.fromRequest")` for request body construction entrypoints. Use `Effect.fn(...)` for event handlers that yield effects; keep purely synchronous handlers as plain functions returning a `StepResult` that the dispatcher lifts via `Effect.succeed(...)`.
+- Parser state owns terminal information. The state machine records finish reason, usage, and pending tool calls; emit one terminal `finish` event (or `provider-error`) for each completed response. If a provider splits reason and usage across events, merge them in parser state before flushing.
+- Emit exactly one terminal `finish` event for a completed response, normally after a matching `step-finish`. Use `stream.terminal` to stop reading when the provider has a completion sentinel; use `stream.onHalt` when the final event must be flushed after the framed stream ends.
+- Use shared helpers for repeated protocol policy such as text joining, usage totals, JSON parsing, and tool-call accumulation. `ToolStream` (`protocols/utils/tool-stream.ts`) accumulates streamed tool-call arguments uniformly.
+- Make intentional provider differences explicit in helper names or comments. If two protocol files differ visually, the reason should be obvious from the names.
+- Prefer dispatched per-event handlers (`onMessageStart`, `onContentBlockDelta`, ...) called from a small top-level `step` switch over a long if-chain. The dispatcher keeps the event surface visible at a glance.
+- Keep tests in the same conceptual order as the protocol: basic prepare, tools prepare, unsupported lowering, text/usage parsing, tool streaming, finish reasons, provider errors.
+
+### Review checklist
+
+- Can the file be skimmed side-by-side with `openai-chat.ts` without hunting for equivalent sections?
+- Are provider quirks named, isolated, and covered by focused tests?
+- Does request body construction validate unsupported common content at the protocol boundary?
+- Does stream parsing emit stable common events without leaking provider event order to callers?
+- Does `toolChoice: "none"` behavior read as intentional?
+
+## Recording Tests
+
+Recorded tests use one cassette file per scenario. A cassette holds an ordered array of `{ request, response }` interactions, so multi-step flows (tool loops, retries, polling) record into a single file. Use `recordedTests({ prefix, requires })` and let the helper derive cassette names from test names:
+
+```ts
+const recorded = recordedTests({ prefix: "openai-chat", requires: ["OPENAI_API_KEY"] })
+
+recorded.effect("streams text", () =>
+  Effect.gen(function* () {
+    // test body
+  }),
+)
+```
+
+Replay is the default. `RECORD=true` records fresh cassettes locally and requires the listed env vars; unset `CI` before recording because CI always forces replay. Cassettes are written as pretty-printed JSON so multi-interaction diffs stay reviewable.
+
+Pass `provider`, `protocol`, and optional `tags` to `recordedTests(...)` / `recorded.effect.with(...)` so cassettes carry searchable metadata. Use recorded-test filters to replay or record a narrow subset without rewriting a whole file:
+
+- `RECORDED_PROVIDER=openai` matches tests tagged with `provider:openai`; comma-separated values are allowed.
+- `RECORDED_PREFIX=openai-chat` matches cassette groups by `recordedTests({ prefix })`; comma-separated values are allowed.
+- `RECORDED_TAGS=tool` requires all listed tags to be present, e.g. `RECORDED_TAGS=provider:togetherai,tool`.
+- `RECORDED_TEST="streams text"` matches by test name, kebab-case test id, or cassette path.
+
+Filters apply in replay and record mode. Combine them with `RECORD=true` when refreshing only one provider or scenario.
+
+**Binary response bodies.** Most providers stream text (SSE, JSON). The recorder treats known textual media types (`text/*`, JSON/XML structured types, JavaScript, forms, YAML, and SVG) as text and stores every other response as base64 with `bodyEncoding: "base64"`. This preserves binary formats such as AWS event-stream frames without a lossy UTF-8 round trip.
+
+**Matching strategy.** A runtime request atomically claims the first unused recorded interaction that matches its method, URL, allow-listed headers, and canonical JSON body. Distinct requests may replay in any order or concurrently. Repeated identical requests consume their matching responses in cassette order, preserving deterministic retry and polling behavior. `scriptedResponses` (in `test/lib/http.ts`) is the deterministic counterpart for tests that don't need a live provider; it scripts response bodies in order without reading from disk.
+
+Do not blanket re-record an entire test file when adding one cassette. `RECORD=true` rewrites every recorded case that runs, and provider streams contain volatile IDs, timestamps, fingerprints, and obfuscation fields. Prefer deleting the one cassette you intend to refresh, or run a focused test pattern that only registers the scenario you want to record. Keep stable existing cassettes unchanged unless their request shape or expected behavior changed.

packages/ai/README.md

@@ -0,0 +1,360 @@
+# @opencode-ai/ai
+
+Schema-first AI primitives for opencode. Provider quirks live in adapters, not in calling code.
+
+```ts
+import { Effect } from "effect"
+import { LLM, LLMClient } from "@opencode-ai/ai"
+import { OpenAI } from "@opencode-ai/ai/providers"
+
+const model = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
+
+const request = LLM.request({
+  model,
+  system: "You are concise.",
+  prompt: "Say hello in one short sentence.",
+  generation: { maxTokens: 40 },
+})
+
+const program = Effect.gen(function* () {
+  const response = yield* LLMClient.generate(request)
+  console.log(response.text)
+})
+```
+
+Run `LLMClient.stream(request)` instead of `generate` when you want incremental `LLMEvent`s. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses, Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.
+
+## Image generation
+
+Use `Image.generate` with an image model for direct asset generation:
+
+```ts
+import { Image, ImageInput } from "@opencode-ai/ai"
+import { OpenAI } from "@opencode-ai/ai/providers"
+
+const program = Effect.gen(function* () {
+  const response = yield* Image.generate({
+    model: OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).image("gpt-image-2"),
+    prompt: "A robot tending a rooftop garden",
+    options: {
+      n: 2,
+      size: "1024x1024",
+      quality: "high", // inferred from the OpenAI image model
+      outputFormat: "webp",
+      future_option: true, // unknown native options pass through unchanged
+    },
+  })
+
+  return response.images // GeneratedImage[] with owned bytes or a provider URL
+})
+```
+
+Pass ordered image inputs to the same method for editing, composition, or image-conditioned generation:
+
+```ts
+const response =
+  yield *
+  Image.generate({
+    model,
+    prompt: "Combine these product photos into one studio scene",
+    images: [
+      ImageInput.bytes(firstBytes, "image/png"),
+      ImageInput.url("https://example.com/second.webp"),
+      ImageInput.file("file_123"),
+    ],
+    options,
+    http,
+  })
+```
+
+`ImageInput.fileUri(uri, mediaType)` represents provider file URIs such as Gemini Files. Raw strings are not
+accepted as image inputs, avoiding ambiguity between base64, URLs, and provider IDs. Empty or omitted `images`
+uses text-to-image generation; a non-empty array selects the provider's edit behavior without enforcing provider
+image-count limits locally. `images` is the only common image-editing field. OpenAI uses multipart for byte/data-URL
+edits and its JSON reference body for URL or file-ID edits. Its provider-specific `options.mask` accepts an
+`ImageInput` for inpainting:
+
+```ts
+yield *
+  Image.generate({
+    model: OpenAI.configure({ apiKey }).image("gpt-image-2"),
+    prompt,
+    images: [ImageInput.bytes(sourceBytes, "image/png")],
+    options: { mask: ImageInput.bytes(maskBytes, "image/png") },
+  })
+```
+
+The OpenAI adapter extracts this helper value into the edit request's native `mask` field rather than passing the
+tagged `ImageInput` object through as an ordinary option. On multipart requests, `http.body` can override option
+fields but not structural `model`, `prompt`, `image[]`, or `mask` fields, and the transport owns the multipart
+`Content-Type` boundary. For JSON requests, `http.body` remains the final raw-native overlay. Gemini does not fetch
+public HTTP URLs, and hosted Z.ai image generation does not accept image inputs. These cases fail with
+`InvalidRequest` before network I/O.
+
+Provider-native image options belong to each request. Raw `http.body` fields have final precedence over them:
+
+```ts
+const model = OpenAI.configure({ apiKey }).image("gpt-image-2")
+
+yield *
+  Image.generate({
+    model,
+    prompt,
+    options: { quality: "medium" },
+    http,
+  })
+```
+
+xAI image models use the same request API with xAI-native controls:
+
+```ts
+yield *
+  Image.generate({
+    model: XAI.configure({ apiKey }).image("any-model-id"),
+    prompt,
+    options: {
+      n: 2,
+      aspectRatio: "16:9",
+      resolution: "1k",
+      responseFormat: "b64_json",
+      future_option: true,
+    },
+    http,
+  })
+```
+
+Google's current Gemini image models use the same direct API:
+
+```ts
+import { Google } from "@opencode-ai/ai/providers"
+
+const googleProgram = Effect.gen(function* () {
+  const response = yield* Image.generate({
+    model: Google.configure({ apiKey }).image("any-model-id"),
+    prompt: "A robot tending a rooftop garden",
+    options: {
+      aspectRatio: "16:9",
+      imageSize: "2K",
+      seed: 42,
+      thinkingLevel: "HIGH",
+      includeThoughts: true,
+      futureOption: true,
+    },
+    http,
+  })
+
+  return response.images
+})
+```
+
+Google image options are request-scoped and inferred from the selected model. Known fields autocomplete while
+future string values and arbitrary native Gemini `generationConfig` fields remain available. Native fields override
+their mapped aliases, and `http.body` is the final deep overlay. The selected model ID is sent to Gemini
+`generateContent` without a local allowlist.
+
+Z.ai image models infer open Z.ai-native options from the selected model:
+
+```ts
+yield *
+  Image.generate({
+    model: ZAI.configure({ apiKey }).image("any-model-id"),
+    prompt,
+    options: {
+      quality: "hd",
+      userID: "user-123",
+      future_option: true,
+    },
+    http,
+  })
+```
+
+Z.ai does not include trustworthy MIME metadata for output URLs, so generated images use
+`application/octet-stream`. Output URLs expire after 30 days; download and persist them promptly if they must
+remain available.
+
+Conversational image generation remains part of the LLM interaction. OpenAI Responses exposes it through its hosted image tool:
+
+```ts
+const program = Effect.gen(function* () {
+  const response = yield* LLM.generate(
+    LLM.request({
+      model: OpenAI.configure({ apiKey }).responses("gpt-5"),
+      prompt: "Design a solarpunk rooftop garden, then show me.",
+      tools: [OpenAI.imageGeneration({ quality: "high" })],
+    }),
+  )
+
+  return response.message
+})
+```
+
+The hosted result is represented as a provider-executed tool call and tool result. Its image is a `file` content item with a data URI, so retaining `response.message` preserves the generated image for continuation.
+
+## Public API
+
+- **`LLM.request({...})`** — build a provider-neutral `LLMRequest`. Accepts ergonomic inputs (`system: string`, `prompt: string`) that normalize into the canonical Schema classes.
+- **`LLM.generate` / `LLM.stream`** — re-exported from `LLMClient` for one-import use.
+- **`Message.user(...)` / `Message.assistant(...)` / `Message.tool(...)`** — message constructors from the canonical schema model.
+- **`Model.make(...)` / `ToolCallPart.make(...)` / `ToolResultPart.make(...)` / `ToolDefinition.make(...)`** — model and tool-related constructors from the canonical schema model.
+- **`LLMClient.prepare(request)`** — compile a request through protocol body construction, validation, and HTTP preparation without sending. Useful for inspection and testing.
+- **`LLMEvent.is.*`** — typed guards (`is.textDelta`, `is.toolCall`, `is.finish`, …) for filtering streams.
+- **`Image.generate({...})`** — generate images through a provider-neutral image request and response model.
+- **`ImageClient`** — Effect service and layer for image execution, parallel to `LLMClient`.
+
+## Caching
+
+Prompt caching is **on by default**. Every `LLMRequest` resolves to `cache: "auto"` unless the caller opts out with `cache: "none"`. Each protocol translates `CacheHint`s to its wire format (`cache_control` on Anthropic, `cachePoint` on Bedrock; OpenAI and Gemini do implicit caching server-side and don't need inline markers — auto is a no-op there).
+
+### Auto placement
+
+`"auto"` places three breakpoints — last tool definition, last system part, latest user message. The last-user-message boundary is the load-bearing detail: in a tool-use loop, a single user turn expands into many assistant/tool round-trips, all sharing that prefix. Caching at that boundary lets every intra-turn API call hit.
+
+The math justifies the default: Anthropic's 5-minute cache write is 1.25× base, read is 0.1×, so a single reuse within 5 minutes already wins. One-shot completions below the per-model minimum-cacheable-token threshold silently no-op on the wire, so the worst case is harmless.
+
+### Opting out
+
+```ts
+LLM.request({
+  model,
+  system,
+  prompt: "one-off question",
+  cache: "none",
+})
+```
+
+### Granular policy
+
+```ts
+cache: {
+  tools?: boolean,
+  system?: boolean,
+  messages?: "latest-user-message" | "latest-assistant" | { tail: number },
+  ttlSeconds?: number,         // ≥ 3600 → 1h on Anthropic/Bedrock; else 5m
+}
+```
+
+### Manual hints
+
+Inline `CacheHint` on any text / system / tool / tool-result part overrides automatic placement. The auto policy preserves manual hints; it only fills gaps.
+
+```ts
+LLM.request({
+  model,
+  system: [
+    { type: "text", text: "stable system prompt", cache: { type: "ephemeral" } },
+  ],
+  ...
+})
+```
+
+### Provider behavior table
+
+| Protocol                | `cache: "auto"`                                                           |
+| ----------------------- | ------------------------------------------------------------------------- |
+| Anthropic Messages      | emits up to 3 `cache_control` markers (4-breakpoint cap enforced)         |
+| Bedrock Converse        | emits up to 3 `cachePoint` blocks (4-breakpoint cap enforced)             |
+| OpenAI Chat / Responses | no-op (implicit caching above 1024 tokens)                                |
+| Gemini                  | no-op (implicit caching on 2.5+; explicit `CachedContent` is out-of-band) |
+
+Normalized cache usage is read back into `response.usage.cacheReadInputTokens` and `cacheWriteInputTokens` across every provider.
+
+## Providers
+
+Provider facades configure endpoint/auth/deployment details first, then expose model selectors that take only a model or deployment id. The selected model carries the executable route value used at runtime.
+
+```ts
+import { OpenAI, CloudflareAIGateway } from "@opencode-ai/ai/providers"
+
+const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")
+const gateway = CloudflareAIGateway.configure({
+  accountId: process.env.CLOUDFLARE_ACCOUNT_ID,
+  gatewayApiKey: process.env.CLOUDFLARE_API_TOKEN,
+}).model("workers-ai/@cf/meta/llama-3.1-8b-instruct")
+```
+
+Included providers: OpenAI, Anthropic, Google (Gemini), Google Vertex Gemini and Anthropic, Amazon Bedrock, Azure OpenAI, Cloudflare AI Gateway, Cloudflare Workers AI, GitHub Copilot, OpenRouter, xAI, Z.ai, plus generic OpenAI-compatible Chat and Responses entrypoints and an Anthropic Messages-compatible entrypoint.
+
+### Package-like entrypoints
+
+Native catalog integrations load provider behavior through package-like entrypoints. These are export paths from the same `@opencode-ai/ai` npm package, not independently published packages. Each entrypoint exports the same `model(modelID, settings)` contract, and `settings` contains serializable provider configuration plus common `headers`, `body`, and `limits` overlays.
+
+```ts
+import { model } from "@opencode-ai/ai/providers/openai/responses"
+
+const selected = model("gpt-5", {
+  apiKey: process.env.OPENAI_API_KEY,
+  transport: "websocket",
+  headers: { "x-application": "opencode" },
+  limits: { context: 200_000, output: 64_000 },
+})
+```
+
+OpenAI Chat and OpenAI Responses are separate semantic entrypoints:
+
+- `@opencode-ai/ai/providers/openai/chat`
+- `@opencode-ai/ai/providers/openai/responses`
+- `@opencode-ai/ai/providers/openai-compatible/responses`
+- `@opencode-ai/ai/providers/anthropic-compatible`
+- `@opencode-ai/ai/providers/google-vertex/gemini`
+- `@opencode-ai/ai/providers/google-vertex/chat`
+- `@opencode-ai/ai/providers/google-vertex/responses`
+- `@opencode-ai/ai/providers/google-vertex/messages`
+
+Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; compatible Responses is separate at `providers/openai-compatible/responses`. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
+
+Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages are separate API entrypoints. All accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. Vertex Chat targets MaaS models through the OpenAI-compatible Chat Completions endpoint, while Vertex Responses targets Grok models and defaults `store` to `false` as required by Vertex. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
+
+Tuned Vertex Gemini deployments use model ids shaped like `endpoints/1234567890` and require OAuth or ADC; Vertex express-mode API keys support publisher models only.
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
+
+model("gemini-3.5-flash", { project: "my-project", location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
+
+model("deepseek-ai/deepseek-v3.2-maas", { project: "my-project", location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/responses"
+
+model("xai/grok-4.20-reasoning", { project: "my-project", location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
+
+model("claude-sonnet-4-6", { project: "my-project", location: "global" })
+```
+
+Provider facades such as `OpenAI.configure(...).responses(...)` remain the direct application API. Package-like entrypoints are the self-similar loading contract used when a catalog selects behavior by export path.
+
+Other provider exports listed above remain direct facades until they explicitly implement the package-like contract. Exporting a provider facade does not implicitly make it a catalog-loadable provider package.
+
+## Provider options & HTTP overlays
+
+Three escape hatches in order of stability:
+
+1. **`generation`** — portable knobs (`maxTokens`, `temperature`, `topP`, `topK`, penalties, seed, stop).
+2. **`providerOptions: { <provider>: {...} }`** — typed-at-the-facade provider-specific knobs (OpenAI `promptCacheKey`, Anthropic `thinking`, Gemini `thinkingConfig`, OpenRouter routing).
+3. **`http: { body, headers, query }`** — last-resort serializable overlays merged into the final HTTP request. Reach for this only when a stable typed path doesn't yet exist.
+
+Route/provider defaults are overridden by request-level values for each axis.
+
+## Routes
+
+Adding a new model or deployment is usually 5-15 lines using `Route.make({ protocol, endpoint, auth, framing, ... })`. The route owns endpoint/auth/framing and the protocol owns body construction plus stream parsing. Transports are reusable IO templates that receive route endpoint/auth at compile time. Capability/catalog metadata lives outside this low-level package; unsupported request shapes fail during protocol lowering. See `AGENTS.md` for the architectural detail.
+
+## Effect
+
+This package is built on Effect. Public methods return `Effect` or `Stream`; provide `LLMClient.layer` for LLM dispatch and `ImageClient.layer` for image dispatch, then import the provider/protocol modules for the routes you use. The example at `example/tutorial.ts` is a runnable walkthrough.
+
+## See also
+
+- `AGENTS.md` — architecture, route construction, contributor guide
+- `STATUS.md` — native provider parity status and AI SDK migration gaps
+- `example/tutorial.ts` — runnable end-to-end walkthrough
+- `test/provider/*.test.ts` — fixture-first protocol tests; `*.recorded.test.ts` files cover live cassettes

packages/ai/STATUS.md

@@ -0,0 +1,108 @@
+# LLM Provider Parity Status
+
+Last reviewed: 2026-07-17
+
+This file tracks the gap between the native `@opencode-ai/ai` package and the AI SDK provider packages that opencode still depends on for many catalog/runtime paths.
+
+## Existing Status Sources
+
+| File                                | What it tracks                                                          | Limitation                                              |
+| ----------------------------------- | ----------------------------------------------------------------------- | ------------------------------------------------------- |
+| `packages/ai/DESIGN.md`             | Future clean-break API proposal for `@opencode-ai/ai`.                  | Not a provider parity tracker.                          |
+| `packages/ai/example/call-sites.md` | Route/value/provider-facade migration checklist and call-site sketches. | Architecture migration only; not AI SDK package parity. |
+
+## Current Implementation Snapshot
+
+| Native slice                       | Source                                                                                         | Current state                                                                                                                                                            | Main gaps                                                                                                                                                                                                                                                 |
+| ---------------------------------- | ---------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| OpenAI Chat                        | `src/protocols/openai-chat.ts`, `src/providers/openai.ts`                                      | Usable. Streams text, reasoning deltas, tool calls, usage, images, and common generation controls.                                                                       | No typed structured-output / `response_format` path. Limited typed OpenAI option surface compared with SDK escape hatches.                                                                                                                                |
+| OpenAI Responses HTTP              | `src/protocols/openai-responses.ts`, `src/providers/openai.ts`                                 | Usable. Supports hosted-tool event surfacing, reasoning replay metadata, GPT-5 defaults, and cache usage.                                                                | No explicit `previous_response_id` path. Typed options cover only a subset of Responses fields. Structured output is still mostly synthetic-tool based.                                                                                                   |
+| OpenAI Responses WebSocket         | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts`                        | Present as `OpenAI.responsesWebSocket(...)`.                                                                                                                             | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete.                                                                                                                                         |
+| OpenAI-compatible Chat             | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts`                | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI.                                                       | Family quirks are mostly endpoint defaults, not full typed behavior.                                                                                                                                                                                      |
+| OpenAI-compatible Responses        | `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the OpenAI Responses wire protocol.                                                                                                | No named family profiles or recorded deployment coverage yet.                                                                                                                                                                                             |
+| Anthropic-compatible Messages      | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts`                 | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage.       | No named compatible family profiles yet.                                                                                                                                                                                                                  |
+| Anthropic Messages                 | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts`                            | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage.                                                                           | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass.                                                                                                                                     |
+| Gemini Developer API               | `src/protocols/gemini.ts`, `src/providers/google.ts`                                           | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage.                                                                      | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays.                                                                                                                             |
+| Vertex Gemini                      | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts`                                    | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments.               | Core runner/catalog mapping and recorded provider coverage are missing.                                                                                                                                                                                   |
+| Vertex Chat                        | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts`                          | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation.                            | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review.                                                                                                                                 |
+| Vertex Responses                   | `src/protocols/openai-responses.ts`, `src/providers/google-vertex-responses.ts`                | Usable for Grok models through OpenAI-compatible Responses with explicit OAuth tokens or ADC, project/location endpoint derivation, and storage disabled by default.     | Core runner/catalog mapping and recorded provider coverage are missing; stateful continuation is not supported by Vertex.                                                                                                                                 |
+| Vertex Messages                    | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts`               | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints.                                                           | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review.                                                                                                                                  |
+| Bedrock Converse                   | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts`                         | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
+| Azure OpenAI                       | `src/providers/azure.ts` using OpenAI Chat/Responses protocols                                 | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors.                                                               | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review.                                                                                                                          |
+| Cloudflare AI Gateway / Workers AI | `src/providers/cloudflare.ts`                                                                  | Present via OpenAI-compatible Chat routes.                                                                                                                               | Useful but not part of the critical AI SDK replacement set yet. Needs per-product recorded coverage before relying on it broadly.                                                                                                                         |
+| OpenRouter                         | `src/providers/openrouter.ts`                                                                  | Present with OpenRouter-specific usage/reasoning/prompt-cache options over Chat.                                                                                         | Responses-style OpenRouter support is absent.                                                                                                                                                                                                             |
+| xAI                                | `src/providers/xai.ts`                                                                         | Present with Responses and Chat selectors.                                                                                                                               | Needs package-parity review against the AI SDK xAI provider.                                                                                                                                                                                              |
+| GitHub Copilot                     | `src/providers/github-copilot.ts`                                                              | Present as explicit-base-URL OpenAI Chat/Responses facade.                                                                                                               | Runtime/catalog integration remains specialized and should stay separate from public OpenAI-compatible defaults.                                                                                                                                          |
+
+## V2 Runner Status
+
+`packages/core/src/session/runner/model.ts` currently resolves only this native subset from catalog `aisdk` metadata:
+
+| Catalog API                                         | Native route used today      |
+| --------------------------------------------------- | ---------------------------- |
+| `aisdk:@ai-sdk/openai`                              | `OpenAIResponses.route`      |
+| `aisdk:@ai-sdk/anthropic`                           | `AnthropicMessages.route`    |
+| `aisdk:@ai-sdk/openai-compatible` with explicit URL | `OpenAICompatibleChat.route` |
+
+Other `aisdk:` packages, including Google Vertex, Azure, and Bedrock, currently fall back through the AI SDK loader in the production runner. The dependency-free resolver seam rejects them with `SessionRunnerModel.UnsupportedPackageError`; they are not native route mappings yet.
+
+## AI SDK Package Parity Matrix
+
+| AI SDK package                    | Intended native target                                         | Status           | Biggest gaps                                                                                                                                                                                                        |
+| --------------------------------- | -------------------------------------------------------------- | ---------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `@ai-sdk/openai`                  | `OpenAI.chat`, `OpenAI.responses`, `OpenAI.responsesWebSocket` | Partial / usable | Add complete typed option coverage, structured output strategy, explicit Responses continuation support, and runner route selection between Chat/Responses/WebSocket.                                               |
+| `@ai-sdk/openai-compatible`       | Generic OpenAI-compatible Chat and Responses                   | Partial / usable | Decide per-family namespace/profile behavior and runner API selection for providers that support Responses versus Chat only.                                                                                        |
+| `@ai-sdk/anthropic`               | `AnthropicMessages`                                            | Partial / usable | Finish Messages API parity for headers/betas/metadata/newer fields and document hosted-tool continuation expectations.                                                                                              |
+| `@ai-sdk/google`                  | Gemini Developer API                                           | Partial / usable | Add typed options for safety, response schema/modalities, cached content, grounding/search/code execution, and non-text output modes where supported.                                                               |
+| `@ai-sdk/google-vertex`           | Vertex Gemini namespace/facade                                 | Partial / usable | Add runner/catalog mapping, recorded coverage, and broader provider-option parity.                                                                                                                                  |
+| `@ai-sdk/google-vertex/anthropic` | Anthropic Messages over Vertex namespace/facade                | Partial / usable | Add runner/catalog mapping, recorded coverage, and Vertex-specific hosted-tool parity.                                                                                                                              |
+| `@ai-sdk/google-vertex/maas`      | Vertex Chat                                                    | Partial / usable | Add runner/catalog mapping, recorded coverage, and MaaS family-specific request parity.                                                                                                                             |
+| `@ai-sdk/google-vertex/xai`       | Vertex Chat / Responses                                        | Partial / usable | Decide Chat/Responses selection for catalog models, add runner mapping and recorded coverage, and review xAI-specific request options.                                                                              |
+| `@ai-sdk/azure`                   | Azure OpenAI Chat/Responses facade                             | Partial          | Map runner/catalog metadata to native Azure, handle resourceName/baseURL/apiVersion variants, add AAD/token auth story, and verify Chat vs Responses deployment selection.                                          |
+| `@ai-sdk/amazon-bedrock`          | Bedrock Converse                                               | Partial          | Add default AWS credential chain/profile support, region/inference-profile model ID handling, provider option parity via `additionalModelRequestFields`, guardrails/performance config, and runner/catalog mapping. |
+| `@ai-sdk/amazon-bedrock/mantle`   | Bedrock Mantle OpenAI-compatible Chat/Responses namespace      | Missing          | Decide native Mantle shape, likely separate from Converse because it uses OpenAI-compatible Chat/Responses semantics over Bedrock. Add package mapping and tests.                                                   |
+
+## Highest-Risk Gaps
+
+1. Runner support is narrower than the LLM package. The package has native provider facades for Google, Azure, and Bedrock, but the V2 Session runner only maps OpenAI, Anthropic, and explicit OpenAI-compatible Chat from `aisdk` catalog metadata.
+2. OpenAI-compatible Responses is available as a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
+3. Bedrock native auth is not AI SDK parity. The AI SDK plugin uses the default AWS provider chain, profile, container credentials, and Bedrock bearer token env behavior. Native Bedrock currently expects explicit credentials or bearer auth on the facade.
+4. Vertex Gemini, Vertex Chat, Vertex Responses, and Vertex Messages now have native package entrypoints, but the core runner does not map catalog metadata to them yet and recorded provider coverage is still missing.
+5. Azure is only a provider facade, not a full runtime replacement. Native Azure exists, but the catalog runner does not select it, and token auth/resource variants need review.
+6. Provider option typing is uneven. OpenAI, Anthropic, Gemini, Bedrock, and OpenRouter each expose a small typed subset plus raw HTTP overlays; this is useful but not equivalent to AI SDK provider option coverage.
+7. Structured output is not provider-native yet. `LLM.generateObject` still uses a synthetic tool strategy, while the future design expects native structured output where reliable and tool fallback where needed.
+8. Package/namespace boundaries for the current native loading set are explicit in docs and exports. Other exported provider facades are not catalog package entrypoints until they implement the contract. Vertex xAI still needs catalog API selection; the missing native boundary is Bedrock Mantle.
+9. Recorded coverage is uneven. OpenAI, Anthropic, Gemini, Bedrock Converse, Cloudflare, OpenRouter, and several OpenAI-compatible Chat providers have cassettes. Azure, Vertex, and Mantle need first-class recorded scenarios before switching defaults.
+
+## Native Namespace Shape
+
+These are implementation/API slices, not separate npm packages.
+
+| API slice                     | Package-like entrypoint                                 | Purpose                                                                      |
+| ----------------------------- | ------------------------------------------------------- | ---------------------------------------------------------------------------- |
+| OpenAI Chat                   | `@opencode-ai/ai/providers/openai/chat`                 | OpenAI `/chat/completions` semantics.                                        |
+| OpenAI Responses              | `@opencode-ai/ai/providers/openai/responses`            | OpenAI `/responses` semantics with HTTP/WebSocket selected through settings. |
+| OpenAI-compatible Chat        | `@opencode-ai/ai/providers/openai-compatible`           | Generic OpenAI-compatible `/chat/completions`.                               |
+| OpenAI-compatible Responses   | `@opencode-ai/ai/providers/openai-compatible/responses` | Generic OpenAI-compatible `/responses`.                                      |
+| Anthropic-compatible Messages | `@opencode-ai/ai/providers/anthropic-compatible`        | Generic Anthropic-compatible `/messages`.                                    |
+| Anthropic Messages            | `@opencode-ai/ai/providers/anthropic`                   | Anthropic Messages API.                                                      |
+| Gemini Developer API          | `@opencode-ai/ai/providers/google`                      | Google AI Studio Gemini API.                                                 |
+| Vertex Gemini                 | `@opencode-ai/ai/providers/google-vertex/gemini`        | Vertex Gemini API; `providers/google-vertex` is the default alias.           |
+| Vertex Chat                   | `@opencode-ai/ai/providers/google-vertex/chat`          | Vertex OpenAI-compatible Chat Completions for MaaS models.                   |
+| Vertex Responses              | `@opencode-ai/ai/providers/google-vertex/responses`     | Vertex OpenAI-compatible Responses for Grok models.                          |
+| Vertex Messages               | `@opencode-ai/ai/providers/google-vertex/messages`      | Vertex-hosted Anthropic Messages API.                                        |
+| Bedrock Converse              | `@opencode-ai/ai/providers/amazon-bedrock`              | AWS Bedrock Converse API.                                                    |
+| Bedrock Mantle                | Missing                                                 | AWS Bedrock Mantle OpenAI-compatible APIs.                                   |
+| Azure OpenAI Chat             | `@opencode-ai/ai/providers/azure/chat`                  | Azure specialization of OpenAI Chat.                                         |
+| Azure OpenAI Responses        | `@opencode-ai/ai/providers/azure/responses`             | Azure specialization of OpenAI Responses.                                    |
+
+## Suggested Next Work Slices
+
+1. Add native runner/catalog mappings for `@ai-sdk/azure`, `@ai-sdk/google`, and `@ai-sdk/amazon-bedrock` where the existing native facades are already close.
+2. Add API-aware runner/catalog selection between OpenAI-compatible Chat and Responses.
+3. Bring Bedrock native auth/config to AI SDK parity: region, profile, default AWS credential chain, bearer token env, endpoint override, and cross-region inference profile handling.
+4. Add runner/catalog mappings and recorded scenarios for the native Vertex Gemini, Chat, Responses, and Messages entrypoints.
+5. Decide Chat/Responses selection for `@ai-sdk/google-vertex/xai` catalog models.
+6. Add Bedrock Mantle as a separate OpenAI-compatible Bedrock namespace after deciding whether it uses Chat, Responses, or both by model.
+7. Expand typed provider options from the existing V1 lowerer knowledge in `packages/core/src/v1/config/provider-options.ts` before adding more raw overlay examples.
+8. Add recorded provider tests for Azure, Vertex Gemini, Vertex Chat, Vertex Responses, Vertex Messages, Bedrock credential-chain behavior, and Mantle before making native runtime the default for those packages.

packages/ai/example/call-sites.md

@@ -7,7 +7,7 @@ values directly.
 ## Conversation Summary
 
 Kit and Aidan want provider-specific LLM behavior to move out of opencode's AI
-SDK transform path and into `packages/llm` where possible. The goal is not a big
+SDK transform path and into `packages/ai` where possible. The goal is not a big
 generic transform layer; the goal is small composable route definitions backed by
 recorded golden tests.
 
@@ -342,14 +342,51 @@ const response =
   )
 ```
 
-HTTP versus WebSocket is represented as named route selectors, not as model or
-request overrides. Same protocol, different transport, different route:
+For direct provider-facade calls, HTTP versus WebSocket is represented as named
+route selectors, not as model or request overrides. Same protocol, different
+transport, different route:
 
 ```ts
 OpenAI.responses("gpt-4o")
 OpenAI.responsesWebSocket("gpt-4o")
 ```
 
+The package-like OpenAI Responses entrypoint instead keeps transport scoped to
+Responses settings while preserving the same `model(...)` contract:
+
+```ts
+import { model } from "@opencode-ai/ai/providers/openai/responses"
+
+model("gpt-4o", { apiKey, transport: "websocket" })
+```
+
+Vertex keeps Gemini, Chat, Responses, and Messages as separate package-like entrypoints,
+while sharing project/location resolution and ADC authentication internally:
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
+
+model("gemini-3.5-flash", { project, location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
+
+model("deepseek-ai/deepseek-v3.2-maas", { project, location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/responses"
+
+model("xai/grok-4.20-reasoning", { project, location: "global" })
+```
+
+```ts
+import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
+
+model("claude-sonnet-4-6", { project, location: "global" })
+```
+
 The client should not require a different public layer just because a selected
 route uses WebSocket. Use one `LLMClient.layer` with HTTP and WebSocket runtime
 capabilities available; routes that do not need WebSocket simply never touch it.
@@ -468,10 +505,10 @@ const model =
 ```
 
 That boundary can branch on durable config/catalog metadata and call typed
-provider APIs directly. Transport selection belongs there too: map metadata like
-`endpoint.websocket` to `OpenAI.responsesWebSocket(apiModelID)`; otherwise use
-the normal `OpenAI.responses(apiModelID)` route. The client runtime only executes
-the route carried by the model.
+provider APIs directly. A direct provider-facade boundary maps metadata like
+`endpoint.websocket` to `OpenAI.responsesWebSocket(apiModelID)`. A package-loading
+boundary passes `transport: "websocket"` to the OpenAI Responses entrypoint.
+The client runtime only executes the route carried by the resulting model.
 
 ## Competitive Shape
 
@@ -507,8 +544,9 @@ App boundary = explicit durable-config -> typed-provider call
   id.
 - No `model(id, overrides)` escape hatch. Model selection takes the model id;
   endpoint/auth/deployment customization happens by configuring the route first.
-- No transport override on model/request. HTTP SSE versus WebSocket is a named
-  route selector such as `responses` versus `responsesWebSocket`.
+- No transport override on an executable model or request. Direct provider
+  facades use `responses` versus `responsesWebSocket`; the package-like Responses
+  entrypoint maps its scoped `transport` setting before constructing the model.
 - No separate public `LLMClient.layerWithWebSocket`. The runtime should expose one
   client layer with the available transport capabilities.
 - No executable `ModelRef`. The executable handle is `Model`; durable model

packages/ai/example/tutorial.ts

@@ -1,12 +1,12 @@
 import { Config, Effect, Formatter, Layer, Schema, Stream } from "effect"
-import { LLM, LLMClient, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/llm"
-import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/llm/route"
-import { OpenAI } from "@opencode-ai/llm/providers"
+import { LLM, LLMClient, Message, ProviderID, Tool, ToolRuntime } from "@opencode-ai/ai"
+import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor, WebSocketExecutor } from "@opencode-ai/ai/route"
+import { OpenAI } from "@opencode-ai/ai/providers"
 
 /**
  * A runnable walkthrough of the LLM package use-site API.
  *
- * Run from `packages/llm` with an OpenAI key in the environment:
+ * Run from `packages/ai` with an OpenAI key in the environment:
  *
  *   OPENAI_API_KEY=... bun example/tutorial.ts
  *
@@ -238,7 +238,7 @@ const inspectFakeProvider = Effect.gen(function* () {
 // Provide the LLM runtime and the HTTP request executor once. Keep one path
 // enabled at a time so the tutorial can demonstrate generate, prepare, stream,
 // or tool-loop behavior without spending tokens on every example.
-const requestExecutorLayer = RequestExecutor.defaultLayer
+const requestExecutorLayer = RequestExecutor.fetchLayer
 const llmDeps = Layer.mergeAll(requestExecutorLayer, WebSocketExecutor.layer)
 const llmClientLayer = LLMClient.layer.pipe(Layer.provide(llmDeps))
 

packages/ai/package.json

@@ -0,0 +1,37 @@
+{
+  "$schema": "https://json.schemastore.org/package.json",
+  "version": "1.17.20",
+  "name": "@opencode-ai/ai",
+  "type": "module",
+  "license": "MIT",
+  "scripts": {
+    "setup:recording-env": "bun run script/setup-recording-env.ts",
+    "test": "bun test --timeout 30000 --only-failures",
+    "typecheck": "tsgo --noEmit && tsgo --noEmit -p tsconfig.types.json",
+    "build": "tsc -p tsconfig.build.json"
+  },
+  "files": [
+    "dist"
+  ],
+  "exports": {
+    ".": "./src/index.ts",
+    "./*": "./src/*.ts"
+  },
+  "devDependencies": {
+    "@clack/prompts": "1.0.0-alpha.1",
+    "@effect/platform-node": "catalog:",
+    "@opencode-ai/http-recorder": "workspace:*",
+    "@tsconfig/bun": "catalog:",
+    "@types/bun": "catalog:",
+    "@typescript/native-preview": "catalog:",
+    "typescript": "catalog:"
+  },
+  "dependencies": {
+    "@smithy/eventstream-codec": "4.2.14",
+    "@smithy/util-utf8": "4.2.2",
+    "@opencode-ai/schema": "workspace:*",
+    "aws4fetch": "1.0.20",
+    "effect": "catalog:",
+    "google-auth-library": "10.5.0"
+  }
+}

packages/ai/script/publish.ts

@@ -0,0 +1,38 @@
+#!/usr/bin/env bun
+import { Script } from "@opencode-ai/script"
+import { $ } from "bun"
+import { fileURLToPath } from "url"
+
+const dir = fileURLToPath(new URL("..", import.meta.url))
+process.chdir(dir)
+
+async function published(name: string, version: string) {
+  return (await $`npm view ${name}@${version} version`.nothrow()).exitCode === 0
+}
+
+await $`bun run build`
+const originalText = await Bun.file("package.json").text()
+const pkg = JSON.parse(originalText) as {
+  name: string
+  version: string
+  exports: Record<string, string>
+}
+if (await published(pkg.name, pkg.version)) {
+  console.log(`already published ${pkg.name}@${pkg.version}`)
+} else {
+  for (const [key, value] of Object.entries(pkg.exports)) {
+    const file = value.replace("./src/", "./dist/").replace(".ts", "")
+    // @ts-ignore
+    pkg.exports[key] = {
+      import: file + ".js",
+      types: file + ".d.ts",
+    }
+  }
+  await Bun.write("package.json", JSON.stringify(pkg, null, 2))
+  try {
+    await $`bun pm pack`
+    await $`npm publish *.tgz --tag ${Script.channel} --access public`
+  } finally {
+    await Bun.write("package.json", originalText)
+  }
+}

packages/ai/script/setup-recording-env.ts

@@ -161,6 +161,18 @@ const PROVIDERS: ReadonlyArray<Provider> = [
     vars: [{ name: "TOGETHER_AI_API_KEY" }],
     validate: (env) => validateBearer("https://api.together.xyz/v1/models", Redacted.make(env.TOGETHER_AI_API_KEY)),
   },
+  {
+    id: "minimax",
+    label: "MiniMax",
+    tier: "compatible",
+    note: "Anthropic-compatible Messages text/tool recorded tests",
+    vars: [{ name: "MINIMAX_API_KEY" }],
+    validate: (env) =>
+      HttpClientRequest.get("https://api.minimax.io/anthropic/v1/models").pipe(
+        HttpClientRequest.setHeader("x-api-key", Redacted.value(Redacted.make(env.MINIMAX_API_KEY))),
+        executeRequest,
+      ),
+  },
   {
     id: "mistral",
     label: "Mistral",

packages/ai/src/image-client.ts

@@ -0,0 +1,38 @@
+import { Context, Effect, Layer } from "effect"
+import { RequestExecutor } from "./route/executor"
+import type { ImageOptions, ImageRequest, ImageRequestFor, ImageResponse } from "./image"
+import type { LLMError } from "./schema"
+
+export type Execute = RequestExecutor.Interface["execute"]
+
+export interface Interface {
+  readonly generate: <Options extends ImageOptions>(
+    request: ImageRequestFor<Options>,
+  ) => Effect.Effect<ImageResponse, LLMError>
+}
+
+export class Service extends Context.Service<Service, Interface>()("@opencode/ImageClient") {}
+
+export const generate = <Options extends ImageOptions>(
+  request: ImageRequestFor<Options>,
+): Effect.Effect<ImageResponse, LLMError> =>
+  Effect.gen(function* () {
+    const client = yield* Service
+    return yield* client.generate(request)
+  }) as Effect.Effect<ImageResponse, LLMError>
+
+export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
+  Service,
+  Effect.gen(function* () {
+    const executor = yield* RequestExecutor.Service
+    return Service.of({
+      generate: (request) => request.model.route.generate(request, executor.execute),
+    })
+  }),
+)
+
+export const ImageClient = {
+  Service,
+  layer,
+  generate,
+} as const

packages/ai/src/image.ts

@@ -0,0 +1,166 @@
+import { Effect, Schema } from "effect"
+import { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from "./schema"
+import { ImageClient, Service, type Execute as ImageExecute } from "./image-client"
+
+export interface ImageRoute<Options extends ImageOptions = ImageOptions> {
+  readonly id: string
+  readonly generate: (
+    request: ImageRequestFor<Options>,
+    execute: ImageExecute,
+  ) => Effect.Effect<ImageResponse, LLMError>
+}
+
+export type ImageOptions = Record<string, unknown>
+
+export class ImageModel<Options extends ImageOptions = ImageOptions> {
+  declare protected readonly _Options: (options: Options) => Options
+  readonly id: ModelID
+  readonly provider: ProviderID
+  readonly route: ImageRoute<Options>
+  readonly http?: HttpOptions
+
+  constructor(input: ImageModel.Input<Options>) {
+    this.id = input.id
+    this.provider = input.provider
+    this.route = input.route
+    this.http = input.http
+  }
+
+  static make<Options extends ImageOptions = ImageOptions>(input: ImageModel.MakeInput<Options>) {
+    return new ImageModel<Options>({
+      id: ModelID.make(input.id),
+      provider: ProviderID.make(input.provider),
+      route: input.route,
+      http: input.http,
+    })
+  }
+}
+
+export namespace ImageModel {
+  export interface Input<Options extends ImageOptions = ImageOptions> {
+    readonly id: ModelID
+    readonly provider: ProviderID
+    readonly route: ImageRoute<Options>
+    readonly http?: HttpOptions
+  }
+
+  export interface MakeInput<Options extends ImageOptions = ImageOptions>
+    extends Omit<Input<Options>, "id" | "provider"> {
+    readonly id: string | ModelID
+    readonly provider: string | ProviderID
+  }
+}
+
+export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
+  expected: "Image.Model",
+})
+
+const ImageBytesInput = Schema.Struct({
+  type: Schema.Literal("bytes"),
+  data: Schema.Uint8Array,
+  mediaType: Schema.String,
+})
+const ImageUrlInput = Schema.Struct({
+  type: Schema.Literal("url"),
+  url: Schema.String,
+})
+const ImageFileIDInput = Schema.Struct({
+  type: Schema.Literal("file-id"),
+  id: Schema.String,
+})
+const ImageFileURIInput = Schema.Struct({
+  type: Schema.Literal("file-uri"),
+  uri: Schema.String,
+  mediaType: Schema.String,
+})
+
+export const ImageInputSchema = Schema.Union([
+  ImageBytesInput,
+  ImageUrlInput,
+  ImageFileIDInput,
+  ImageFileURIInput,
+]).pipe(Schema.toTaggedUnion("type"))
+export type ImageInput = Schema.Schema.Type<typeof ImageInputSchema>
+
+export const ImageInput = {
+  bytes: (data: Uint8Array, mediaType: string): ImageInput => ({ type: "bytes", data, mediaType }),
+  url: (url: string): ImageInput => ({ type: "url", url }),
+  file: (id: string): ImageInput => ({ type: "file-id", id }),
+  fileUri: (uri: string, mediaType: string): ImageInput => ({ type: "file-uri", uri, mediaType }),
+} as const
+
+export class ImageRequest extends Schema.Class<ImageRequest>("Image.Request")({
+  model: ImageModelSchema,
+  prompt: Schema.String,
+  images: Schema.optional(Schema.Array(ImageInputSchema)),
+  options: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+  http: Schema.optional(HttpOptions),
+}) {
+  declare protected readonly _ImageRequest: void
+}
+
+export type ImageRequestFor<Options extends ImageOptions = ImageOptions> = Omit<ImageRequest, "model" | "options"> & {
+  readonly model: ImageModel<Options>
+  readonly options?: Options
+}
+
+export type ImageModelOptions<Model> = Model extends ImageModel<infer Options> ? Options : never
+
+export type ImageRequestInput<Model extends object = ImageModel> = Omit<
+  ConstructorParameters<typeof ImageRequest>[0],
+  "model" | "options" | "http"
+> & {
+  readonly model: Model
+  readonly options?: NoInfer<ImageModelOptions<Model>>
+  readonly http?: HttpOptions.Input
+} & (Model extends ImageModel<ImageModelOptions<Model>> ? unknown : never)
+
+export class GeneratedImage extends Schema.Class<GeneratedImage>("Image.Generated")({
+  mediaType: Schema.String,
+  data: Schema.Union([Schema.String, Schema.Uint8Array]),
+  providerMetadata: Schema.optional(ProviderMetadata),
+}) {}
+
+export class ImageResponse extends Schema.Class<ImageResponse>("Image.Response")({
+  images: Schema.Array(GeneratedImage),
+  usage: Schema.optional(Usage),
+  providerMetadata: Schema.optional(ProviderMetadata),
+}) {
+  get image() {
+    return this.images[0]
+  }
+}
+
+export function request<const Model extends object>(
+  input: ImageRequestInput<Model>,
+): ImageRequestFor<ImageModelOptions<Model>>
+export function request(input: ImageRequest): ImageRequest
+export function request(input: ImageRequest | ImageRequestInput) {
+  if (input instanceof ImageRequest) return input
+  return new ImageRequest({
+    ...input,
+    model: input.model as unknown as ImageModel,
+    http: input.http === undefined ? undefined : HttpOptions.make(input.http),
+  })
+}
+
+export function generate<const Model extends object>(
+  input: ImageRequestInput<Model>,
+): Effect.Effect<ImageResponse, LLMError, Service>
+export function generate(input: ImageRequest): Effect.Effect<ImageResponse, LLMError, Service>
+export function generate(input: ImageRequest | ImageRequestInput) {
+  return Effect.try({
+    try: () => (input instanceof ImageRequest ? input : request(input)),
+    catch: (error) =>
+      new LLMError({
+        module: "Image",
+        method: "generate",
+        reason: new InvalidRequestReason({ message: error instanceof Error ? error.message : String(error) }),
+      }),
+  }).pipe(Effect.flatMap((request) => ImageClient.generate(request as unknown as ImageRequestFor<ImageOptions>)))
+}
+
+export const Image = {
+  request,
+  generate,
+} as const

packages/ai/src/index.ts

@@ -0,0 +1,39 @@
+export { LLMClient } from "./route/client"
+export { ImageClient } from "./image-client"
+export { Auth } from "./route/auth"
+export { Provider } from "./provider"
+export { ProviderPackage } from "./provider-package"
+export { isContextOverflow, isContextOverflowFailure } from "./provider-error"
+export type {
+  RouteModelInput,
+  RouteRoutedModelInput,
+  Interface as LLMClientShape,
+  Service as LLMClientService,
+} from "./route/client"
+export * from "./schema"
+export { GeneratedImage, ImageInput, ImageInputSchema, ImageModel, ImageRequest, ImageResponse } from "./image"
+export type { ImageModelOptions, ImageOptions, ImageRequestFor, ImageRequestInput, ImageRoute } from "./image"
+export { Image } from "./image"
+export { Tool, ToolFailure, toDefinitions } from "./tool"
+export { ToolRuntime } from "./tool-runtime"
+export type { DispatchResult as ToolDispatchResult, ToolSettlement } from "./tool-runtime"
+export type {
+  AnyExecutableTool,
+  AnyTool,
+  ExecutableTool,
+  ExecutableTools,
+  Definition as ToolShape,
+  ToolExecute,
+  ToolExecuteContext,
+  ToolModelOutputInput,
+  Tools,
+  ToolSchema,
+  ToolToModelOutput,
+} from "./tool"
+export * as LLM from "./llm"
+export type {
+  Definition as ProviderDefinition,
+  ModelFactory as ProviderModelFactory,
+  ModelOptions as ProviderModelOptions,
+} from "./provider"
+export type { Definition as ProviderPackageDefinition, Settings as ProviderPackageSettings } from "./provider-package"

packages/ai/src/protocols.ts

@@ -0,0 +1 @@
+export * from "./protocols/index"

packages/ai/src/protocols/anthropic-messages.ts

@@ -5,10 +5,12 @@ import { Endpoint } from "../route/endpoint"
 import { Framing } from "../route/framing"
 import { Protocol } from "../route/protocol"
 import {
+  LLMError,
   LLMEvent,
   Usage,
   type CacheHint,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
   type MediaPart,
   type ProviderMetadata,
@@ -18,12 +20,14 @@ import {
   type ToolResultPart,
 } from "../schema"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
-import { isContextOverflow } from "../provider-error"
+import { classifyProviderFailure } from "../provider-error"
 import * as Cache from "./utils/cache"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
 
 const ADAPTER = "anthropic-messages"
+const MEDIA_MIMES = new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.PDF_MIMES])
 export const DEFAULT_BASE_URL = "https://api.anthropic.com/v1"
 export const PATH = "/messages"
 
@@ -53,6 +57,17 @@ const AnthropicImageBlock = Schema.Struct({
 })
 type AnthropicImageBlock = Schema.Schema.Type<typeof AnthropicImageBlock>
 
+const AnthropicDocumentBlock = Schema.Struct({
+  type: Schema.tag("document"),
+  source: Schema.Struct({
+    type: Schema.tag("base64"),
+    media_type: Schema.Literal("application/pdf"),
+    data: Schema.String,
+  }),
+  cache_control: Schema.optional(AnthropicCacheControl),
+})
+type AnthropicDocumentBlock = Schema.Schema.Type<typeof AnthropicDocumentBlock>
+
 const AnthropicThinkingBlock = Schema.Struct({
   type: Schema.tag("thinking"),
   thinking: Schema.String,
@@ -98,13 +113,10 @@ const AnthropicServerToolResultBlock = Schema.Struct({
 })
 type AnthropicServerToolResultBlock = Schema.Schema.Type<typeof AnthropicServerToolResultBlock>
 
-// Anthropic accepts either a plain string or an ordered array of text/image
-// blocks inside `tool_result.content`. The array form is required when a tool
-// returns image bytes (screenshot, image search, etc.) so they can be passed
-// to the model as proper image inputs instead of being JSON-stringified into
-// the prompt — which silently inflates context by megabytes and can push the
-// conversation over the model's token limit.
-const AnthropicToolResultContent = Schema.Union([AnthropicTextBlock, AnthropicImageBlock])
+// Anthropic accepts either a plain string or an ordered array of text, image, and
+// document blocks inside `tool_result.content`. The array form keeps media as native
+// model input instead of JSON-stringifying base64 into prompt text.
+const AnthropicToolResultContent = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicDocumentBlock])
 
 const AnthropicToolResultBlock = Schema.Struct({
   type: Schema.tag("tool_result"),
@@ -114,7 +126,12 @@ const AnthropicToolResultBlock = Schema.Struct({
   cache_control: Schema.optional(AnthropicCacheControl),
 })
 
-const AnthropicUserBlock = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicToolResultBlock])
+const AnthropicUserBlock = Schema.Union([
+  AnthropicTextBlock,
+  AnthropicImageBlock,
+  AnthropicDocumentBlock,
+  AnthropicToolResultBlock,
+])
 type AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>
 const AnthropicAssistantBlock = Schema.Union([
   AnthropicTextBlock,
@@ -146,9 +163,22 @@ const AnthropicToolChoice = Schema.Union([
   Schema.Struct({ type: Schema.tag("tool"), name: Schema.String }),
 ])
 
-const AnthropicThinking = Schema.Struct({
-  type: Schema.tag("enabled"),
-  budget_tokens: Schema.Number,
+const AnthropicThinking = Schema.Union([
+  Schema.Struct({
+    type: Schema.tag("enabled"),
+    budget_tokens: Schema.Number,
+  }),
+  Schema.Struct({
+    type: Schema.tag("adaptive"),
+    display: Schema.optional(Schema.Literals(["summarized", "omitted"])),
+  }),
+  Schema.Struct({
+    type: Schema.tag("disabled"),
+  }),
+])
+
+const AnthropicOutputConfig = Schema.Struct({
+  effort: Schema.optional(Schema.String),
 })
 
 const AnthropicBodyFields = {
@@ -164,8 +194,9 @@ const AnthropicBodyFields = {
   top_k: Schema.optional(Schema.Number),
   stop_sequences: optionalArray(Schema.String),
   thinking: Schema.optional(AnthropicThinking),
+  output_config: Schema.optional(AnthropicOutputConfig),
 }
-const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)
+export const AnthropicMessagesBody = Schema.Struct(AnthropicBodyFields)
 export type AnthropicMessagesBody = Schema.Schema.Type<typeof AnthropicMessagesBody>
 
 const AnthropicUsage = Schema.Struct({
@@ -256,10 +287,10 @@ const signatureFromMetadata = (metadata: ProviderMetadata | undefined): string |
   return typeof anthropic.signature === "string" ? anthropic.signature : undefined
 }
 
-const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition): AnthropicTool => ({
+const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
   name: tool.name,
   description: tool.description,
-  input_schema: tool.inputSchema,
+  input_schema: inputSchema,
   cache_control: cacheControl(breakpoints, tool.cache),
 })
 
@@ -302,12 +333,17 @@ const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult
   return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock
 })
 
-const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: MediaPart) {
-  const media = yield* ProviderShared.validateMedia(
-    "Anthropic Messages",
-    part,
-    new Set<string>(ProviderShared.IMAGE_MIMES),
-  )
+const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (part: MediaPart) {
+  const media = yield* ProviderShared.validateMedia("Anthropic Messages", part, MEDIA_MIMES)
+  if (media.mime === "application/pdf")
+    return {
+      type: "document" as const,
+      source: {
+        type: "base64" as const,
+        media_type: "application/pdf" as const,
+        data: media.base64,
+      },
+    } satisfies AnthropicDocumentBlock
   return {
     type: "image" as const,
     source: {
@@ -318,25 +354,13 @@ const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: Me
   } satisfies AnthropicImageBlock
 })
 
-// Tool results may carry structured text/images. Keep media as provider-native
+// Tool results may carry structured text, images, and documents. Keep media as provider-native
 // content instead of JSON-stringifying base64 into a prompt string.
 const lowerToolResultContentItem = Effect.fn("AnthropicMessages.lowerToolResultContentItem")(function* (
   item: ToolContent,
 ) {
   if (item.type === "text") return { type: "text" as const, text: item.text } satisfies AnthropicTextBlock
-  const media = yield* ProviderShared.validateToolFile(
-    "Anthropic Messages",
-    item,
-    new Set<string>(ProviderShared.IMAGE_MIMES),
-  )
-  return {
-    type: "image" as const,
-    source: {
-      type: "base64" as const,
-      media_type: media.mime,
-      data: media.base64,
-    },
-  } satisfies AnthropicImageBlock
+  return yield* lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name })
 })
 
 const lowerToolResultContent = Effect.fn("AnthropicMessages.lowerToolResultContent")(function* (part: ToolResultPart) {
@@ -428,7 +452,7 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
           continue
         }
         if (part.type === "media") {
-          content.push(yield* lowerImage(part))
+          content.push(yield* lowerMedia(part))
           continue
         }
         return yield* ProviderShared.unsupportedContent("Anthropic Messages", "user", ["text", "media"])
@@ -490,7 +514,18 @@ const anthropicOptions = (request: LLMRequest) => request.providerOptions?.anthr
 
 const lowerThinking = Effect.fn("AnthropicMessages.lowerThinking")(function* (request: LLMRequest) {
   const thinking = anthropicOptions(request)?.thinking
-  if (!ProviderShared.isRecord(thinking) || thinking.type !== "enabled") return undefined
+  if (!ProviderShared.isRecord(thinking)) return undefined
+  if (thinking.type === "adaptive") {
+    const display =
+      thinking.display === "summarized"
+        ? ("summarized" as const)
+        : thinking.display === "omitted"
+          ? ("omitted" as const)
+          : undefined
+    return { type: "adaptive" as const, ...(display === undefined ? {} : { display }) }
+  }
+  if (thinking.type === "disabled") return { type: "disabled" as const }
+  if (thinking.type !== "enabled") return undefined
   const budget =
     typeof thinking.budgetTokens === "number"
       ? thinking.budgetTokens
@@ -501,9 +536,16 @@ const lowerThinking = Effect.fn("AnthropicMessages.lowerThinking")(function* (re
   return { type: "enabled" as const, budget_tokens: budget }
 })
 
+const outputConfig = (request: LLMRequest) => {
+  const effort = anthropicOptions(request)?.effort
+  return typeof effort === "string" ? { effort } : undefined
+}
+
 const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (request: LLMRequest) {
   const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined
   const generation = request.generation
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
+  const outputLimit = request.model.defaults?.limits?.output ?? request.model.route.defaults.limits?.output ?? 4096
   // Allocate the 4-breakpoint budget in invalidation order: tools → system →
   // messages. Tools live highest in the cache hierarchy, so when callers
   // over-mark we keep their tool hints and shed the message-tail ones first.
@@ -511,7 +553,13 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
   const tools =
     request.tools.length === 0 || request.toolChoice?.type === "none"
       ? undefined
-      : request.tools.map((tool) => lowerTool(breakpoints, tool))
+      : request.tools.map((tool) =>
+          lowerTool(
+            breakpoints,
+            tool,
+            ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility),
+          ),
+        )
   const system =
     request.system.length === 0
       ? undefined
@@ -533,12 +581,13 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
     tools,
     tool_choice: toolChoice,
     stream: true as const,
-    max_tokens: generation?.maxTokens ?? request.model.route.defaults.limits?.output ?? 4096,
+    max_tokens: generation?.maxTokens ?? outputLimit,
     temperature: generation?.temperature,
     top_p: generation?.topP,
     top_k: generation?.topK,
     stop_sequences: generation?.stop,
     thinking: yield* lowerThinking(request),
+    output_config: outputConfig(request),
   }
 })
 
@@ -661,7 +710,14 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
           providerExecuted: block.type === "server_tool_use",
         }),
       },
-      [...events, LLMEvent.toolInputStart({ id: block.id ?? String(event.index), name: block.name ?? "" })],
+      [
+        ...events,
+        LLMEvent.toolInputStart({
+          id: block.id ?? String(event.index),
+          name: block.name ?? "",
+          providerExecuted: block.type === "server_tool_use" ? true : undefined,
+        }),
+      ],
     ]
   }
 
@@ -791,15 +847,12 @@ const providerErrorMessage = (event: AnthropicEvent): string => {
   return message || type || "Anthropic Messages stream error"
 }
 
-const onError = (state: ParserState, event: AnthropicEvent): StepResult => [
-  state,
-  [
-    LLMEvent.providerError({
-      message: providerErrorMessage(event),
-      classification: isContextOverflow(event.error?.message ?? "") ? "context-overflow" : undefined,
-    }),
-  ],
-]
+const onError = (event: AnthropicEvent) =>
+  new LLMError({
+    module: ADAPTER,
+    method: "stream",
+    reason: classifyProviderFailure({ message: providerErrorMessage(event), code: event.error?.type }),
+  })
 
 const step = (state: ParserState, event: AnthropicEvent) => {
   if (event.type === "message_start") return Effect.succeed(onMessageStart(state, event))
@@ -807,7 +860,7 @@ const step = (state: ParserState, event: AnthropicEvent) => {
   if (event.type === "content_block_delta") return onContentBlockDelta(state, event)
   if (event.type === "content_block_stop") return onContentBlockStop(state, event)
   if (event.type === "message_delta") return Effect.succeed(onMessageDelta(state, event))
-  if (event.type === "error") return Effect.succeed(onError(state, event))
+  if (event.type === "error") return onError(event)
   return Effect.succeed<StepResult>([state, NO_EVENTS])
 }
 
@@ -835,6 +888,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
   id: ADAPTER,
   provider: "anthropic",
+  providerMetadataKey: "anthropic",
   protocol,
   endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),
   auth: Auth.none,

packages/ai/src/protocols/bedrock-converse.ts

@@ -3,11 +3,14 @@ import { Route } from "../route/client"
 import { Endpoint } from "../route/endpoint"
 import { Protocol } from "../route/protocol"
 import {
+  LLMError,
   LLMEvent,
   Usage,
   type CacheHint,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
+  type ModelToolSchemaCompatibility,
   type ProviderMetadata,
   type ReasoningPart,
   type ToolCallPart,
@@ -15,12 +18,13 @@ import {
   type ToolResultPart,
 } from "../schema"
 import { BedrockEventStream } from "./bedrock-event-stream"
-import { isContextOverflow } from "../provider-error"
+import { classifyProviderFailure } from "../provider-error"
 import { JsonObject, optionalArray, ProviderShared } from "./shared"
 import { BedrockAuth } from "./utils/bedrock-auth"
 import { BedrockCache } from "./utils/bedrock-cache"
 import { BedrockMedia } from "./utils/bedrock-media"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
 
 const ADAPTER = "bedrock-converse"
@@ -48,6 +52,7 @@ const BedrockToolResultContentItem = Schema.Union([
   Schema.Struct({ text: Schema.String }),
   Schema.Struct({ json: Schema.Unknown }),
   BedrockMedia.ImageBlock,
+  BedrockMedia.DocumentBlock,
 ])
 
 const BedrockToolResultBlock = Schema.Struct({
@@ -205,18 +210,22 @@ type BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerToolSpec = (tool: ToolDefinition): BedrockToolSpec => ({
+const lowerToolSpec = (tool: ToolDefinition, inputSchema: JsonSchema): BedrockToolSpec => ({
   toolSpec: {
     name: tool.name,
     description: tool.description,
-    inputSchema: { json: tool.inputSchema },
+    inputSchema: { json: inputSchema },
   },
 })
 
-const lowerTools = (breakpoints: BedrockCache.Breakpoints, tools: ReadonlyArray<ToolDefinition>): BedrockTool[] => {
+const lowerTools = (
+  compatibility: ModelToolSchemaCompatibility | undefined,
+  breakpoints: BedrockCache.Breakpoints,
+  tools: ReadonlyArray<ToolDefinition>,
+): BedrockTool[] => {
   const result: BedrockTool[] = []
   for (const tool of tools) {
-    result.push(lowerToolSpec(tool))
+    result.push(lowerToolSpec(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, compatibility)))
     const cachePoint = BedrockCache.block(breakpoints, tool.cache)
     if (cachePoint) result.push(cachePoint)
   }
@@ -275,8 +284,6 @@ const lowerToolResultContent = Effect.fn("BedrockConverse.lowerToolResultContent
       data: item.uri,
       filename: item.name,
     })
-    if (!("image" in media))
-      return yield* ProviderShared.invalidRequest("Bedrock Converse only supports image media in tool results")
     content.push(media)
   }
   return content
@@ -386,7 +393,7 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
   const breakpoints = BedrockCache.breakpoints()
   const toolConfig =
     request.tools.length > 0 && request.toolChoice?.type !== "none"
-      ? { tools: lowerTools(breakpoints, request.tools), toolChoice }
+      ? { tools: lowerTools(request.model.compatibility?.toolSchema, breakpoints, request.tools), toolChoice }
       : undefined
   const system = request.system.length === 0 ? undefined : lowerSystem(breakpoints, request.system)
   const messages = yield* lowerMessages(request, breakpoints)
@@ -553,7 +560,9 @@ const step = (state: ParserState, event: BedrockEvent) =>
       return [
         {
           ...state,
-          hasToolCalls: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasToolCalls,
+          hasToolCalls:
+            resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
+            state.hasToolCalls,
           lifecycle,
           tools: result.tools,
           reasoningSignatures: Object.fromEntries(
@@ -579,28 +588,24 @@ const step = (state: ParserState, event: BedrockEvent) =>
       return [{ ...state, pendingFinish: { reason: state.pendingFinish?.reason ?? "stop", usage } }, []] as const
     }
 
-    if (event.internalServerException || event.modelStreamErrorException || event.serviceUnavailableException) {
-      const message =
-        event.internalServerException?.message ??
-        event.modelStreamErrorException?.message ??
-        event.serviceUnavailableException?.message ??
-        "Bedrock Converse stream error"
-      return [state, [LLMEvent.providerError({ message, retryable: true })]] as const
-    }
-
-    if (event.validationException || event.throttlingException) {
-      const message =
-        event.validationException?.message ?? event.throttlingException?.message ?? "Bedrock Converse error"
-      return [
-        state,
-        [
-          LLMEvent.providerError({
-            message,
-            classification: event.validationException && isContextOverflow(message) ? "context-overflow" : undefined,
-            retryable: event.throttlingException !== undefined,
-          }),
-        ],
+    const exception = (
+      [
+        ["internalServerException", event.internalServerException],
+        ["modelStreamErrorException", event.modelStreamErrorException],
+        ["serviceUnavailableException", event.serviceUnavailableException],
+        ["throttlingException", event.throttlingException],
+        ["validationException", event.validationException],
       ] as const
+    ).find((entry) => entry[1] !== undefined)
+    if (exception) {
+      return yield* new LLMError({
+        module: ADAPTER,
+        method: "stream",
+        reason: classifyProviderFailure({
+          message: exception[1]?.message ?? "Bedrock Converse stream error",
+          code: exception[0],
+        }),
+      })
     }
 
     return [state, []] as const
@@ -651,6 +656,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
   id: ADAPTER,
   provider: "bedrock",
+  providerMetadataKey: "bedrock",
   protocol,
   // Bedrock's URL embeds the region in the route endpoint host and the
   // validated modelId in the path. We read the validated body so the URL

packages/ai/src/protocols/bedrock-event-stream.ts

@@ -1,7 +1,7 @@
 import { EventStreamCodec } from "@smithy/eventstream-codec"
 import { fromUtf8, toUtf8 } from "@smithy/util-utf8"
 import { Effect, Stream } from "effect"
-import type { Framing } from "../route/framing"
+import { Framing } from "../route/framing"
 import { ProviderShared } from "./shared"
 
 // Bedrock streams responses using the AWS event stream binary protocol — each
@@ -79,7 +79,7 @@ const consumeFrames = (route: string) => (state: FrameBufferState, chunk: Uint8A
  * under its `:event-type` header so the chunk schema can match the JSON
  * payload directly.
  */
-export const framing = (route: string): Framing<object> => ({
+export const framing = (route: string): Framing.Definition<object> => ({
   id: "aws-event-stream",
   frame: (bytes) => bytes.pipe(Stream.mapAccumEffect(() => initialFrameBuffer, consumeFrames(route))),
 })

packages/ai/src/protocols/gemini.ts

@@ -0,0 +1,528 @@
+import { Effect, Schema } from "effect"
+import { Route } from "../route/client"
+import { Auth } from "../route/auth"
+import { Endpoint } from "../route/endpoint"
+import { Framing } from "../route/framing"
+import { Protocol } from "../route/protocol"
+import {
+  LLMEvent,
+  Usage,
+  type FinishReason,
+  type JsonSchema,
+  type LLMRequest,
+  type MediaPart,
+  type ProviderMetadata,
+  type TextPart,
+  type ToolCallPart,
+  type ToolDefinition,
+  type ToolContent,
+} from "../schema"
+import { JsonObject, optionalArray, ProviderShared } from "./shared"
+import { GeminiToolSchema } from "./utils/gemini-tool-schema"
+import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
+
+const ADAPTER = "gemini"
+const MEDIA_MIMES = new Set<string>(ProviderShared.MEDIA_MIMES)
+export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
+
+// =============================================================================
+// Request Body Schema
+// =============================================================================
+const GeminiTextPart = Schema.Struct({
+  text: Schema.String,
+  thought: Schema.optional(Schema.Boolean),
+  thoughtSignature: Schema.optional(Schema.String),
+})
+
+const GeminiInlineDataPart = Schema.Struct({
+  inlineData: Schema.Struct({
+    mimeType: Schema.String,
+    data: Schema.String,
+  }),
+})
+type GeminiInlineDataPart = Schema.Schema.Type<typeof GeminiInlineDataPart>
+
+const GeminiFunctionCallPart = Schema.Struct({
+  functionCall: Schema.Struct({
+    id: Schema.optional(Schema.String),
+    name: Schema.String,
+    args: Schema.Unknown,
+  }),
+  thoughtSignature: Schema.optional(Schema.String),
+})
+
+const GeminiFunctionResponsePart = Schema.Struct({
+  functionResponse: Schema.Struct({
+    id: Schema.optional(Schema.String),
+    name: Schema.String,
+    response: Schema.Unknown,
+    parts: Schema.optional(Schema.Array(GeminiInlineDataPart)),
+  }),
+})
+
+const GeminiContentPart = Schema.Union([
+  GeminiTextPart,
+  GeminiInlineDataPart,
+  GeminiFunctionCallPart,
+  GeminiFunctionResponsePart,
+])
+
+const GeminiContent = Schema.Struct({
+  role: Schema.Literals(["user", "model"]),
+  parts: Schema.Array(GeminiContentPart),
+})
+type GeminiContent = Schema.Schema.Type<typeof GeminiContent>
+
+const GeminiSystemInstruction = Schema.Struct({
+  parts: Schema.Array(Schema.Struct({ text: Schema.String })),
+})
+
+const GeminiFunctionDeclaration = Schema.Struct({
+  name: Schema.String,
+  description: Schema.String,
+  parameters: Schema.optional(JsonObject),
+})
+
+const GeminiTool = Schema.Struct({
+  functionDeclarations: Schema.Array(GeminiFunctionDeclaration),
+})
+
+const GeminiToolConfig = Schema.Struct({
+  functionCallingConfig: Schema.Struct({
+    mode: Schema.Literals(["AUTO", "NONE", "ANY"]),
+    allowedFunctionNames: optionalArray(Schema.String),
+  }),
+})
+
+const GeminiThinkingConfig = Schema.Struct({
+  thinkingBudget: Schema.optional(Schema.Number),
+  includeThoughts: Schema.optional(Schema.Boolean),
+})
+
+const GeminiGenerationConfig = Schema.Struct({
+  maxOutputTokens: Schema.optional(Schema.Number),
+  temperature: Schema.optional(Schema.Number),
+  topP: Schema.optional(Schema.Number),
+  topK: Schema.optional(Schema.Number),
+  stopSequences: optionalArray(Schema.String),
+  thinkingConfig: Schema.optional(GeminiThinkingConfig),
+})
+
+const GeminiBodyFields = {
+  contents: Schema.Array(GeminiContent),
+  systemInstruction: Schema.optional(GeminiSystemInstruction),
+  tools: optionalArray(GeminiTool),
+  toolConfig: Schema.optional(GeminiToolConfig),
+  generationConfig: Schema.optional(GeminiGenerationConfig),
+}
+const GeminiBody = Schema.Struct(GeminiBodyFields)
+export type GeminiBody = Schema.Schema.Type<typeof GeminiBody>
+
+const GeminiUsage = Schema.Struct({
+  cachedContentTokenCount: Schema.optional(Schema.Number),
+  thoughtsTokenCount: Schema.optional(Schema.Number),
+  promptTokenCount: Schema.optional(Schema.Number),
+  candidatesTokenCount: Schema.optional(Schema.Number),
+  totalTokenCount: Schema.optional(Schema.Number),
+})
+type GeminiUsage = Schema.Schema.Type<typeof GeminiUsage>
+
+const GeminiCandidate = Schema.Struct({
+  content: Schema.optional(GeminiContent),
+  finishReason: Schema.optional(Schema.String),
+})
+
+const GeminiEvent = Schema.Struct({
+  candidates: optionalArray(GeminiCandidate),
+  usageMetadata: Schema.optional(GeminiUsage),
+})
+type GeminiEvent = Schema.Schema.Type<typeof GeminiEvent>
+
+interface ParserState {
+  readonly finishReason?: string
+  readonly hasToolCalls: boolean
+  readonly nextToolCallId: number
+  readonly usage?: Usage
+  readonly lifecycle: Lifecycle.State
+  readonly reasoningSignature?: string
+}
+
+// =============================================================================
+// Tool Schema Conversion
+// =============================================================================
+// Tool-schema conversion has two distinct concerns:
+//
+// 1. Sanitize — fix common authoring mistakes Gemini rejects: integer/number
+//    enums (must be strings), `required` entries that don't match a property,
+//    untyped arrays (`items` must be present), and `properties`/`required`
+//    keys on non-object scalars. Mirrors OpenCode's historical Gemini rules.
+//
+// 2. Project — lossy mapping from JSON Schema to Gemini's schema dialect:
+//    drop empty objects, derive `nullable: true` from `type: [..., "null"]`,
+//    coerce `const` to `[const]` enum, recurse properties/items, propagate
+//    only an allowlisted set of keys (description, required, format, type,
+//    properties, items, allOf, anyOf, oneOf, minLength). Anything outside the
+//    allowlist (e.g. `additionalProperties`, `$ref`) is silently dropped.
+//
+// Sanitize runs first, then project. The implementation lives in
+// `utils/gemini-tool-schema` so this protocol keeps the same shape as the other
+// provider protocols.
+
+// =============================================================================
+// Request Lowering
+// =============================================================================
+const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema) => ({
+  name: tool.name,
+  description: tool.description,
+  parameters: GeminiToolSchema.convert(inputSchema),
+})
+
+const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
+  ProviderShared.matchToolChoice("Gemini", toolChoice, {
+    auto: () => ({ functionCallingConfig: { mode: "AUTO" as const } }),
+    none: () => ({ functionCallingConfig: { mode: "NONE" as const } }),
+    required: () => ({ functionCallingConfig: { mode: "ANY" as const } }),
+    tool: (name) => ({ functionCallingConfig: { mode: "ANY" as const, allowedFunctionNames: [name] } }),
+  })
+
+const lowerUserPart = Effect.fn("Gemini.lowerUserPart")(function* (part: TextPart | MediaPart) {
+  if (part.type === "text") return { text: part.text }
+  const media = yield* ProviderShared.validateMedia("Gemini", part, MEDIA_MIMES)
+  return { inlineData: { mimeType: media.mime, data: media.base64 } }
+})
+
+const googleMetadata = (metadata: Record<string, unknown>): ProviderMetadata => ({ google: metadata })
+
+const thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {
+  const google = providerMetadata?.google
+  return ProviderShared.isRecord(google) && typeof google.thoughtSignature === "string"
+    ? google.thoughtSignature
+    : undefined
+}
+
+const functionCallId = (providerMetadata: ProviderMetadata | undefined) => {
+  const google = providerMetadata?.google
+  return ProviderShared.isRecord(google) && typeof google.functionCallId === "string" ? google.functionCallId : undefined
+}
+
+const lowerToolCall = (part: ToolCallPart) => ({
+  functionCall: { id: functionCallId(part.providerMetadata), name: part.name, args: part.input },
+  thoughtSignature: thoughtSignature(part.providerMetadata),
+})
+
+const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMRequest) {
+  const contents: GeminiContent[] = []
+
+  for (const message of request.messages) {
+    if (message.role === "system") {
+      const part = yield* ProviderShared.wrappedSystemUpdate("Gemini", message)
+      const previous = contents.at(-1)
+      if (previous?.role === "user")
+        contents[contents.length - 1] = { role: "user", parts: [...previous.parts, { text: part.text }] }
+      else contents.push({ role: "user", parts: [{ text: part.text }] })
+      continue
+    }
+
+    if (message.role === "user") {
+      const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []
+      for (const part of message.content) {
+        if (!ProviderShared.supportsContent(part, ["text", "media"]))
+          return yield* ProviderShared.unsupportedContent("Gemini", "user", ["text", "media"])
+        parts.push(yield* lowerUserPart(part))
+      }
+      contents.push({ role: "user", parts })
+      continue
+    }
+
+    if (message.role === "assistant") {
+      const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []
+      for (const part of message.content) {
+        if (!ProviderShared.supportsContent(part, ["text", "reasoning", "tool-call"]))
+          return yield* ProviderShared.unsupportedContent("Gemini", "assistant", ["text", "reasoning", "tool-call"])
+        if (part.type === "text") {
+          parts.push({ text: part.text })
+          continue
+        }
+        if (part.type === "reasoning") {
+          parts.push({ text: part.text, thought: true, thoughtSignature: thoughtSignature(part.providerMetadata) })
+          continue
+        }
+        if (part.type === "tool-call") {
+          parts.push(lowerToolCall(part))
+          continue
+        }
+      }
+      contents.push({ role: "model", parts })
+      continue
+    }
+
+    const parts: Array<Schema.Schema.Type<typeof GeminiContentPart>> = []
+    for (const part of message.content) {
+      if (!ProviderShared.supportsContent(part, ["tool-result"]))
+        return yield* ProviderShared.unsupportedContent("Gemini", "tool", ["tool-result"])
+      if (part.result.type !== "content") {
+        parts.push({
+          functionResponse: {
+            id: functionCallId(part.providerMetadata),
+            name: part.name,
+            response: {
+              name: part.name,
+              content: ProviderShared.toolResultText(part),
+            },
+          },
+        })
+        continue
+      }
+      const content: ReadonlyArray<ToolContent> = part.result.value
+      const text = content.filter((item) => item.type === "text").map((item) => item.text)
+      const media: GeminiInlineDataPart[] = []
+      for (const item of content) {
+        if (item.type === "text") continue
+        const value = yield* ProviderShared.validateToolFile("Gemini", item, MEDIA_MIMES)
+        media.push({ inlineData: { mimeType: value.mime, data: value.base64 } })
+      }
+      parts.push({
+        functionResponse: {
+          id: functionCallId(part.providerMetadata),
+          name: part.name,
+          response: {
+            name: part.name,
+            content: text.join("\n"),
+          },
+          parts: media.length > 0 ? media : undefined,
+        },
+      })
+    }
+    contents.push({ role: "user", parts })
+  }
+
+  return contents
+})
+
+const geminiOptions = (request: LLMRequest) => request.providerOptions?.gemini
+
+const thinkingConfig = (request: LLMRequest) => {
+  const value = geminiOptions(request)?.thinkingConfig
+  if (!ProviderShared.isRecord(value)) return undefined
+  const result = {
+    thinkingBudget: typeof value.thinkingBudget === "number" ? value.thinkingBudget : undefined,
+    includeThoughts: typeof value.includeThoughts === "boolean" ? value.includeThoughts : undefined,
+  }
+  return Object.values(result).some((item) => item !== undefined) ? result : undefined
+}
+
+const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMRequest) {
+  const toolsEnabled = request.tools.length > 0 && request.toolChoice?.type !== "none"
+  const generation = request.generation
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
+  const generationConfig = {
+    maxOutputTokens: generation?.maxTokens,
+    temperature: generation?.temperature,
+    topP: generation?.topP,
+    topK: generation?.topK,
+    stopSequences: generation?.stop,
+    thinkingConfig: thinkingConfig(request),
+  }
+
+  return {
+    contents: yield* lowerMessages(request),
+    systemInstruction:
+      request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
+    tools: toolsEnabled
+      ? [
+          {
+            functionDeclarations: request.tools.map((tool) =>
+              lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
+            ),
+          },
+        ]
+      : undefined,
+    toolConfig: toolsEnabled && request.toolChoice ? yield* lowerToolConfig(request.toolChoice) : undefined,
+    generationConfig: Object.values(generationConfig).some((value) => value !== undefined)
+      ? generationConfig
+      : undefined,
+  }
+})
+
+// =============================================================================
+// Stream Parsing
+// =============================================================================
+// Gemini reports `promptTokenCount` (inclusive total) with a
+// `cachedContentTokenCount` subset. `candidatesTokenCount` is *exclusive*
+// of `thoughtsTokenCount` — visible-only, not a total — so we sum the two
+// to produce the inclusive `outputTokens` the rest of the contract expects.
+const mapUsage = (usage: GeminiUsage | undefined) => {
+  if (!usage) return undefined
+  const cached = usage.cachedContentTokenCount
+  const nonCached = ProviderShared.subtractTokens(usage.promptTokenCount, cached)
+  // `candidatesTokenCount` is visible-only; sum with thoughts to produce the
+  // inclusive `outputTokens` the contract expects. Only compute the total
+  // when the visible component is reported — otherwise we'd fabricate an
+  // inclusive number from a partial breakdown.
+  const outputTokens =
+    usage.candidatesTokenCount !== undefined ? usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0) : undefined
+  return new Usage({
+    inputTokens: usage.promptTokenCount,
+    outputTokens,
+    nonCachedInputTokens: nonCached,
+    cacheReadInputTokens: cached,
+    reasoningTokens: usage.thoughtsTokenCount,
+    totalTokens: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),
+    providerMetadata: { google: usage },
+  })
+}
+
+const mapFinishReason = (finishReason: string | undefined, hasToolCalls: boolean): FinishReason => {
+  if (finishReason === "STOP") return hasToolCalls ? "tool-calls" : "stop"
+  if (finishReason === "MAX_TOKENS") return "length"
+  if (
+    finishReason === "IMAGE_SAFETY" ||
+    finishReason === "RECITATION" ||
+    finishReason === "SAFETY" ||
+    finishReason === "BLOCKLIST" ||
+    finishReason === "PROHIBITED_CONTENT" ||
+    finishReason === "SPII"
+  )
+    return "content-filter"
+  if (finishReason === "MALFORMED_FUNCTION_CALL") return "error"
+  return "unknown"
+}
+
+const finish = (state: ParserState): ReadonlyArray<LLMEvent> =>
+  state.finishReason || state.usage
+    ? (() => {
+        const events: LLMEvent[] = []
+        const lifecycle = state.reasoningSignature
+          ? Lifecycle.reasoningEnd(
+              state.lifecycle,
+              events,
+              "reasoning-0",
+              googleMetadata({ thoughtSignature: state.reasoningSignature }),
+            )
+          : state.lifecycle
+        Lifecycle.finish(lifecycle, events, {
+          reason: mapFinishReason(state.finishReason, state.hasToolCalls),
+          usage: state.usage,
+        })
+        return events
+      })()
+    : []
+
+const step = (state: ParserState, event: GeminiEvent) => {
+  const nextState = {
+    ...state,
+    usage: event.usageMetadata ? (mapUsage(event.usageMetadata) ?? state.usage) : state.usage,
+  }
+  const candidate = event.candidates?.[0]
+  if (!candidate?.content)
+    return Effect.succeed([
+      { ...nextState, finishReason: candidate?.finishReason ?? nextState.finishReason },
+      [],
+    ] as const)
+
+  const events: LLMEvent[] = []
+  let hasToolCalls = nextState.hasToolCalls
+  let lifecycle = nextState.lifecycle
+  let nextToolCallId = nextState.nextToolCallId
+  let reasoningSignature = nextState.reasoningSignature
+
+  for (const part of candidate.content.parts) {
+    if ("thoughtSignature" in part && part.thoughtSignature && "thought" in part && part.thought)
+      reasoningSignature = part.thoughtSignature
+    if ("text" in part && part.text.length > 0) {
+      if (part.thought) {
+        lifecycle = Lifecycle.reasoningDelta(
+          lifecycle,
+          events,
+          "reasoning-0",
+          part.text,
+          part.thoughtSignature ? googleMetadata({ thoughtSignature: part.thoughtSignature }) : undefined,
+        )
+        continue
+      }
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,
+      )
+      lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", part.text)
+      continue
+    }
+
+    if ("functionCall" in part) {
+      const input = part.functionCall.args
+      const id = `tool_${nextToolCallId++}`
+      const metadata = {
+        ...(part.functionCall.id === undefined ? {} : { functionCallId: part.functionCall.id }),
+        ...(part.thoughtSignature === undefined ? {} : { thoughtSignature: part.thoughtSignature }),
+      }
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningSignature ? googleMetadata({ thoughtSignature: reasoningSignature }) : undefined,
+      )
+      lifecycle = Lifecycle.stepStart(lifecycle, events)
+      events.push(
+        LLMEvent.toolCall({
+          id,
+          name: part.functionCall.name,
+          input,
+          providerMetadata: Object.keys(metadata).length > 0 ? googleMetadata(metadata) : undefined,
+        }),
+      )
+      hasToolCalls = true
+    }
+  }
+
+  return Effect.succeed([
+    {
+      ...nextState,
+      hasToolCalls,
+      lifecycle,
+      nextToolCallId,
+      reasoningSignature,
+      finishReason: candidate.finishReason ?? nextState.finishReason,
+    },
+    events,
+  ] as const)
+}
+
+// =============================================================================
+// Protocol And Gemini Route
+// =============================================================================
+/**
+ * The Gemini protocol — request body construction, body schema, and the
+ * streaming-event state machine. Used by Google AI Studio Gemini and (once
+ * registered) Vertex Gemini.
+ */
+export const protocol = Protocol.make({
+  id: ADAPTER,
+  body: {
+    schema: GeminiBody,
+    from: fromRequest,
+  },
+  stream: {
+    event: Protocol.jsonEvent(GeminiEvent),
+    initial: () => ({ hasToolCalls: false, nextToolCallId: 0, lifecycle: Lifecycle.initial() }),
+    step,
+    onHalt: finish,
+  },
+})
+
+export const route = Route.make({
+  id: ADAPTER,
+  provider: "google",
+  providerMetadataKey: "google",
+  protocol,
+  // Gemini's path embeds the model id and pins SSE framing at the URL level.
+  endpoint: Endpoint.path(({ request }) => `/models/${request.model.id}:streamGenerateContent?alt=sse`, {
+    baseURL: DEFAULT_BASE_URL,
+  }),
+  auth: Auth.none,
+  framing: Framing.sse,
+})
+
+export * as Gemini from "./gemini"

packages/ai/src/protocols/google-images.ts

@@ -0,0 +1,314 @@
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import {
+  GeneratedImage,
+  ImageModel,
+  ImageResponse,
+  type ImageInput,
+  type ImageRequestFor,
+  type ImageRoute,
+} from "../image"
+import { Auth, type Definition as AuthDefinition } from "../route/auth"
+import {
+  InvalidProviderOutputReason,
+  LLMError,
+  Usage,
+  mergeHttpOptions,
+  mergeJsonRecords,
+  type HttpOptions,
+  type ProviderMetadata,
+} from "../schema"
+import { ProviderShared } from "./shared"
+import { ImageInputs } from "./utils/image-input"
+
+const ADAPTER = "google-images"
+export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
+
+export type GoogleImageString<Known extends string> = Known | (string & {})
+
+export type GoogleImageOptions = {
+  readonly aspectRatio?: GoogleImageString<
+    "1:1" | "2:3" | "3:2" | "3:4" | "4:3" | "4:5" | "5:4" | "9:16" | "16:9" | "21:9"
+  >
+  readonly imageSize?: GoogleImageString<"1K" | "2K" | "4K">
+  readonly seed?: number
+  readonly thinkingLevel?: GoogleImageString<"MINIMAL" | "LOW" | "MEDIUM" | "HIGH">
+  readonly includeThoughts?: boolean
+} & Record<string, unknown>
+
+export type GoogleImageBody = Record<string, unknown> & {
+  readonly contents: ReadonlyArray<{
+    readonly role: "user"
+    readonly parts: ReadonlyArray<Record<string, unknown>>
+  }>
+  readonly generationConfig: Record<string, unknown>
+}
+
+const GoogleUsage = Schema.StructWithRest(
+  Schema.Struct({
+    cachedContentTokenCount: Schema.optional(Schema.Number),
+    thoughtsTokenCount: Schema.optional(Schema.Number),
+    promptTokenCount: Schema.optional(Schema.Number),
+    candidatesTokenCount: Schema.optional(Schema.Number),
+    totalTokenCount: Schema.optional(Schema.Number),
+    promptTokensDetails: Schema.optional(Schema.Unknown),
+    candidatesTokensDetails: Schema.optional(Schema.Unknown),
+  }),
+  [Schema.Record(Schema.String, Schema.Unknown)],
+)
+
+const GoogleImageResponse = Schema.Struct({
+  candidates: Schema.optional(
+    Schema.Array(
+      Schema.Struct({
+        index: Schema.optional(Schema.Number),
+        content: Schema.optional(
+          Schema.Struct({
+            parts: Schema.Array(
+              Schema.Struct({
+                text: Schema.optional(Schema.String),
+                thought: Schema.optional(Schema.Boolean),
+                thoughtSignature: Schema.optional(Schema.String),
+                inlineData: Schema.optional(
+                  Schema.Struct({
+                    mimeType: Schema.String,
+                    data: Schema.String,
+                  }),
+                ),
+              }),
+            ),
+          }),
+        ),
+        finishReason: Schema.optional(Schema.String),
+        finishMessage: Schema.optional(Schema.String),
+        safetyRatings: Schema.optional(Schema.Unknown),
+        citationMetadata: Schema.optional(Schema.Unknown),
+        groundingMetadata: Schema.optional(Schema.Unknown),
+      }),
+    ),
+  ),
+  usageMetadata: Schema.optional(GoogleUsage),
+  modelVersion: Schema.optional(Schema.String),
+  responseId: Schema.optional(Schema.String),
+  promptFeedback: Schema.optional(Schema.Unknown),
+})
+
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}
+
+const nativeOptions = (options: GoogleImageOptions | undefined) => {
+  const { aspectRatio, imageSize, seed, thinkingLevel, includeThoughts, ...native } = options ?? {}
+  const image = {
+    aspectRatio,
+    imageSize,
+  }
+  const thinkingConfig = {
+    thinkingLevel,
+    includeThoughts,
+  }
+  return (
+    mergeJsonRecords(
+      {
+        responseModalities: ["IMAGE"],
+        imageConfig: Object.values(image).some((value) => value !== undefined) ? image : undefined,
+        seed,
+        thinkingConfig: Object.values(thinkingConfig).some((value) => value !== undefined) ? thinkingConfig : undefined,
+      },
+      native,
+    ) ?? { responseModalities: ["IMAGE"] }
+  )
+}
+
+const invalidOutput = (message: string, providerMetadata?: ProviderMetadata) =>
+  new LLMError({
+    module: ADAPTER,
+    method: "generate",
+    reason: new InvalidProviderOutputReason({ message, route: ADAPTER, providerMetadata }),
+  })
+
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<GoogleImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("GoogleImages.generate")(function* (request: ImageRequestFor<GoogleImageOptions>, execute) {
+      const imageParts = yield* Effect.forEach(request.images ?? [], googleImagePart)
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const requestBody = mergeJsonRecords(
+        {
+          contents: [{ role: "user", parts: [{ text: request.prompt }, ...imageParts] }],
+          generationConfig: nativeOptions(request.options),
+        },
+        http?.body,
+      ) as GoogleImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const url = applyQuery(
+        `${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}/models/${request.model.id}:generateContent`,
+        http?.query,
+      )
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      const payload = yield* response.json.pipe(
+        Effect.mapError(() => invalidOutput("Failed to read the Google Images response")),
+      )
+      const decoded = yield* Schema.decodeUnknownEffect(GoogleImageResponse)(payload).pipe(
+        Effect.mapError(() => invalidOutput("Google Images returned an invalid response")),
+      )
+      const candidates = decoded.candidates ?? []
+      const candidateMetadata = candidates.map((candidate, candidateIndex) => ({
+        index: candidate.index ?? candidateIndex,
+        finishReason: candidate.finishReason,
+        finishMessage: candidate.finishMessage,
+        safetyRatings: candidate.safetyRatings,
+        citationMetadata: candidate.citationMetadata,
+        groundingMetadata: candidate.groundingMetadata,
+        parts: (candidate.content?.parts ?? []).map((part) =>
+          part.inlineData === undefined
+            ? {
+                type: "text",
+                text: part.text,
+                thought: part.thought,
+                thoughtSignature: part.thoughtSignature,
+              }
+            : {
+                type: "inlineData",
+                mediaType: part.inlineData.mimeType,
+                thought: part.thought,
+                thoughtSignature: part.thoughtSignature,
+              },
+        ),
+      }))
+      const encoded = candidates.flatMap((candidate, candidateIndex) =>
+        (candidate.content?.parts ?? []).flatMap((part, partIndex) =>
+          part.inlineData === undefined || part.thought === true
+            ? []
+            : [{ candidate, candidateIndex, partIndex, inlineData: part.inlineData }],
+        ),
+      )
+      const images = yield* Effect.forEach(encoded, (item) =>
+        Effect.fromResult(Encoding.decodeBase64(item.inlineData.data)).pipe(
+          Effect.mapError(() =>
+            invalidOutput(
+              `Google Images candidate ${item.candidateIndex} part ${item.partIndex} contains invalid base64 data`,
+            ),
+          ),
+          Effect.map(
+            (data) =>
+              new GeneratedImage({
+                mediaType: item.inlineData.mimeType,
+                data,
+                providerMetadata: {
+                  google: {
+                    candidateIndex: item.candidate.index ?? item.candidateIndex,
+                    partIndex: item.partIndex,
+                    finishReason: item.candidate.finishReason,
+                    safetyRatings: item.candidate.safetyRatings,
+                    citationMetadata: item.candidate.citationMetadata,
+                    groundingMetadata: item.candidate.groundingMetadata,
+                    thoughtSignature: item.candidate.content?.parts[item.partIndex]?.thoughtSignature,
+                  },
+                },
+              }),
+          ),
+        ),
+      )
+      if (images.length === 0) {
+        const finishReasons = candidates.flatMap((candidate) =>
+          candidate.finishReason === undefined ? [] : [candidate.finishReason],
+        )
+        return yield* invalidOutput(
+          `Google Images returned no final images${
+            finishReasons.length === 0 ? "" : ` (finish reasons: ${finishReasons.join(", ")})`
+          }; inspect reason.providerMetadata.google for prompt feedback and candidate details`,
+          {
+            google: {
+              promptFeedback: decoded.promptFeedback,
+              candidates: candidateMetadata,
+            },
+          },
+        )
+      }
+      const usage = decoded.usageMetadata
+      const outputTokens =
+        usage?.candidatesTokenCount === undefined
+          ? undefined
+          : usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0)
+      return new ImageResponse({
+        images,
+        usage:
+          usage === undefined
+            ? undefined
+            : new Usage({
+                inputTokens: usage.promptTokenCount,
+                outputTokens,
+                nonCachedInputTokens: ProviderShared.subtractTokens(
+                  usage.promptTokenCount,
+                  usage.cachedContentTokenCount,
+                ),
+                cacheReadInputTokens: usage.cachedContentTokenCount,
+                reasoningTokens: usage.thoughtsTokenCount,
+                totalTokens: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),
+                providerMetadata: { google: usage },
+              }),
+        providerMetadata: {
+          google: {
+            modelVersion: decoded.modelVersion,
+            responseId: decoded.responseId,
+            promptFeedback: decoded.promptFeedback,
+            candidates: candidateMetadata,
+          },
+        },
+      })
+    }),
+  }
+  return ImageModel.make<GoogleImageOptions>({ id: input.id, provider: "google", route, http: input.http })
+}
+
+const googleImagePart = (image: ImageInput): Effect.Effect<Record<string, unknown>, LLMError> => {
+  if (image.type === "bytes")
+    return Effect.succeed({ inlineData: { mimeType: image.mediaType, data: Encoding.encodeBase64(image.data) } })
+  if (image.type === "file-uri") return Effect.succeed({ fileData: { mimeType: image.mediaType, fileUri: image.uri } })
+  if (image.type === "url")
+    return ImageInputs.decodeDataUrl(image.url, ADAPTER).pipe(
+      Effect.flatMap((decoded) => {
+        if (decoded === undefined)
+          return Effect.fail(
+            ImageInputs.invalid(
+              ADAPTER,
+              "Google generateContent does not fetch public image URLs; use bytes, a data URL, or a Gemini file URI",
+            ),
+          )
+        return Effect.succeed({
+          inlineData: { mimeType: decoded.mediaType, data: Encoding.encodeBase64(decoded.data) },
+        })
+      }),
+    )
+  return Effect.fail(
+    ImageInputs.invalid(ADAPTER, "Google generateContent requires Gemini file URIs rather than provider file IDs"),
+  )
+}
+
+export const GoogleImages = {
+  model,
+} as const

packages/ai/src/protocols/index.ts

@@ -0,0 +1,8 @@
+export * as AnthropicMessages from "./anthropic-messages"
+export * as BedrockConverse from "./bedrock-converse"
+export * as Gemini from "./gemini"
+export * as OpenAIChat from "./openai-chat"
+export * as OpenAIImages from "./openai-images"
+export * as OpenAICompatibleChat from "./openai-compatible-chat"
+export * as OpenAICompatibleResponses from "./openai-compatible-responses"
+export * as OpenAIResponses from "./openai-responses"

packages/ai/src/protocols/openai-chat.ts

@@ -0,0 +1,690 @@
+import { Effect, Schema } from "effect"
+import { Route } from "../route/client"
+import { Auth } from "../route/auth"
+import { Endpoint } from "../route/endpoint"
+import { HttpTransport } from "../route/transport"
+import { Protocol } from "../route/protocol"
+import {
+  LLMEvent,
+  Usage,
+  type FinishReason,
+  type JsonSchema,
+  type LLMRequest,
+  type MediaPart,
+  type ReasoningPart,
+  type TextPart,
+  type ToolCallPart,
+  type ToolDefinition,
+  type ToolContent,
+} from "../schema"
+import { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
+import { OpenAIOptions } from "./utils/openai-options"
+import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
+import { ToolStream } from "./utils/tool-stream"
+
+const ADAPTER = "openai-chat"
+const IMAGE_MIMES = new Set<string>(ProviderShared.IMAGE_MIMES)
+const RESERVED_REASONING_FIELDS = new Set(["role", "content", "tool_calls"])
+export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
+export const PATH = "/chat/completions"
+
+// =============================================================================
+// Request Body Schema
+// =============================================================================
+// The body schema is the provider-native JSON body. `fromRequest` below builds
+// this shape from the common `LLMRequest`, then `Route.make` validates and
+// JSON-encodes it before transport.
+const OpenAIChatFunction = Schema.Struct({
+  name: Schema.String,
+  description: Schema.String,
+  parameters: JsonObject,
+})
+
+const OpenAIChatTool = Schema.Struct({
+  type: Schema.tag("function"),
+  function: OpenAIChatFunction,
+})
+type OpenAIChatTool = Schema.Schema.Type<typeof OpenAIChatTool>
+
+const OpenAIChatAssistantToolCall = Schema.Struct({
+  id: Schema.String,
+  type: Schema.tag("function"),
+  function: Schema.Struct({
+    name: Schema.String,
+    arguments: Schema.String,
+  }),
+})
+type OpenAIChatAssistantToolCall = Schema.Schema.Type<typeof OpenAIChatAssistantToolCall>
+
+const OpenAIChatUserContent = Schema.Union([
+  Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
+  Schema.Struct({
+    type: Schema.Literal("image_url"),
+    image_url: Schema.Struct({ url: Schema.String }),
+  }),
+])
+
+const OpenAIChatMessage = Schema.Union([
+  Schema.Struct({ role: Schema.Literal("system"), content: Schema.String }),
+  Schema.Struct({
+    role: Schema.Literal("user"),
+    content: Schema.Union([Schema.String, Schema.Array(OpenAIChatUserContent)]),
+  }),
+  Schema.StructWithRest(
+    Schema.Struct({
+      role: Schema.Literal("assistant"),
+      content: Schema.NullOr(Schema.String),
+      tool_calls: optionalArray(OpenAIChatAssistantToolCall),
+      reasoning_content: Schema.optional(Schema.String),
+      reasoning: Schema.optional(Schema.String),
+      reasoning_text: Schema.optional(Schema.String),
+      reasoning_details: Schema.optional(Schema.Unknown),
+    }),
+    [Schema.Record(Schema.String, Schema.Unknown)],
+  ),
+  Schema.Struct({ role: Schema.Literal("tool"), tool_call_id: Schema.String, content: Schema.String }),
+]).pipe(Schema.toTaggedUnion("role"))
+type OpenAIChatMessage = Schema.Schema.Type<typeof OpenAIChatMessage>
+
+const OpenAIChatToolChoice = Schema.Union([
+  Schema.Literals(["auto", "none", "required"]),
+  Schema.Struct({
+    type: Schema.tag("function"),
+    function: Schema.Struct({ name: Schema.String }),
+  }),
+])
+
+export const bodyFields = {
+  model: Schema.String,
+  messages: Schema.Array(OpenAIChatMessage),
+  tools: optionalArray(OpenAIChatTool),
+  tool_choice: Schema.optional(OpenAIChatToolChoice),
+  stream: Schema.Literal(true),
+  stream_options: Schema.optional(Schema.Struct({ include_usage: Schema.Boolean })),
+  store: Schema.optional(Schema.Boolean),
+  reasoning_effort: Schema.optional(OpenAIOptions.OpenAIReasoningEffort),
+  max_tokens: Schema.optional(Schema.Number),
+  temperature: Schema.optional(Schema.Number),
+  top_p: Schema.optional(Schema.Number),
+  frequency_penalty: Schema.optional(Schema.Number),
+  presence_penalty: Schema.optional(Schema.Number),
+  seed: Schema.optional(Schema.Number),
+  stop: optionalArray(Schema.String),
+}
+const OpenAIChatBody = Schema.Struct(bodyFields)
+export type OpenAIChatBody = Schema.Schema.Type<typeof OpenAIChatBody>
+
+// =============================================================================
+// Streaming Event Schema
+// =============================================================================
+// The event schema is one decoded SSE `data:` payload. `Framing.sse` splits the
+// byte stream into strings, then `Protocol.jsonEvent` decodes each string into
+// this provider-native event shape.
+const OpenAIChatUsage = Schema.Struct({
+  prompt_tokens: Schema.optional(Schema.Number),
+  completion_tokens: Schema.optional(Schema.Number),
+  total_tokens: Schema.optional(Schema.Number),
+  prompt_tokens_details: optionalNull(
+    Schema.Struct({
+      cached_tokens: Schema.optional(Schema.Number),
+    }),
+  ),
+  completion_tokens_details: optionalNull(
+    Schema.Struct({
+      reasoning_tokens: Schema.optional(Schema.Number),
+    }),
+  ),
+})
+
+const OpenAIChatToolCallDeltaFunction = Schema.Struct({
+  name: optionalNull(Schema.String),
+  arguments: optionalNull(Schema.String),
+})
+
+const OpenAIChatToolCallDelta = Schema.Struct({
+  index: Schema.Number,
+  id: optionalNull(Schema.String),
+  function: optionalNull(OpenAIChatToolCallDeltaFunction),
+})
+type OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta>
+
+const OpenAIChatDelta = Schema.StructWithRest(
+  Schema.Struct({
+    content: optionalNull(Schema.String),
+    reasoning_content: optionalNull(Schema.String),
+    reasoning: optionalNull(Schema.String),
+    reasoning_text: optionalNull(Schema.String),
+    reasoning_details: optionalNull(Schema.Unknown),
+    tool_calls: optionalNull(Schema.Array(OpenAIChatToolCallDelta)),
+  }),
+  [Schema.Record(Schema.String, Schema.Unknown)],
+)
+
+const OpenAIChatChoice = Schema.Struct({
+  delta: optionalNull(OpenAIChatDelta),
+  finish_reason: optionalNull(Schema.String),
+})
+
+export const OpenAIChatEvent = Schema.Struct({
+  choices: Schema.Array(OpenAIChatChoice),
+  usage: optionalNull(OpenAIChatUsage),
+})
+export type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
+type OpenAIChatRequestMessage = LLMRequest["messages"][number]
+
+interface PendingToolDelta {
+  readonly id?: string
+  readonly name?: string
+  readonly input: string
+}
+
+export interface ParserState {
+  readonly tools: ToolStream.State<number>
+  readonly pendingTools: Partial<Record<number, PendingToolDelta>>
+  readonly toolCallEvents: ReadonlyArray<LLMEvent>
+  readonly usage?: Usage
+  readonly finishReason?: FinishReason
+  readonly lifecycle: Lifecycle.State
+  readonly reasoningField?: string
+  readonly reasoningDetails: Array<unknown>
+  readonly reasoningDetailsObserved: boolean
+  readonly reasoningEmitted: boolean
+}
+
+// =============================================================================
+// Request Lowering
+// =============================================================================
+// Lowering is the only place that knows how common LLM messages map onto the
+// OpenAI Chat wire format. Keep provider quirks here instead of leaking native
+// fields into `LLMRequest`.
+const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIChatTool => ({
+  type: "function",
+  function: {
+    name: tool.name,
+    description: tool.description,
+    parameters: ToolSchemaProjection.openAI(inputSchema),
+  },
+})
+
+const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
+  ProviderShared.matchToolChoice("OpenAI Chat", toolChoice, {
+    auto: () => "auto" as const,
+    none: () => "none" as const,
+    required: () => "required" as const,
+    tool: (name) => ({ type: "function" as const, function: { name } }),
+  })
+
+const lowerToolCall = (part: ToolCallPart): OpenAIChatAssistantToolCall => ({
+  id: part.id,
+  type: "function",
+  function: {
+    name: part.name,
+    arguments: ProviderShared.encodeJson(part.input),
+  },
+})
+
+const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart) {
+  const media = yield* ProviderShared.validateMedia("OpenAI Chat", part, IMAGE_MIMES)
+  return { type: "image_url" as const, image_url: { url: media.dataUrl } }
+})
+
+const openAICompatibleReasoningContent = (native: unknown) =>
+  isRecord(native) && typeof native.reasoning_content === "string" ? native.reasoning_content : undefined
+
+const reasoningField = (part: ReasoningPart) => {
+  const field = part.providerMetadata?.openai?.reasoningField
+  return typeof field === "string" ? field : undefined
+}
+
+const reasoningDetails = (parts: ReadonlyArray<ReasoningPart>, native: unknown) => {
+  const observed = parts.flatMap((part) => {
+    const details = part.providerMetadata?.openai?.reasoningDetails
+    return Array.isArray(details) ? details : []
+  })
+  if (parts.some((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))) return observed
+  if (isRecord(native) && Array.isArray(native.reasoning_details)) return native.reasoning_details
+}
+
+const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (message: OpenAIChatRequestMessage) {
+  const content: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
+  for (const part of message.content) {
+    if (part.type === "text") {
+      content.push({ type: "text", text: part.text })
+      continue
+    }
+    if (part.type === "media") {
+      content.push(yield* lowerMedia(part))
+      continue
+    }
+    return yield* ProviderShared.unsupportedContent("OpenAI Chat", "user", ["text", "media"])
+  }
+  if (content.every((part) => part.type === "text"))
+    return { role: "user" as const, content: content.map((part) => part.text).join("") }
+  return { role: "user" as const, content }
+})
+
+const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(function* (
+  message: OpenAIChatRequestMessage,
+  configuredField?: string,
+) {
+  const content: TextPart[] = []
+  const reasoning: ReasoningPart[] = []
+  const toolCalls: OpenAIChatAssistantToolCall[] = []
+  for (const part of message.content) {
+    if (!ProviderShared.supportsContent(part, ["text", "reasoning", "tool-call"]))
+      return yield* ProviderShared.unsupportedContent("OpenAI Chat", "assistant", ["text", "reasoning", "tool-call"])
+    if (part.type === "text") {
+      content.push(part)
+      continue
+    }
+    if (part.type === "reasoning") {
+      reasoning.push(part)
+      continue
+    }
+    if (part.type === "tool-call") {
+      toolCalls.push(lowerToolCall(part))
+      continue
+    }
+  }
+  const text = reasoning.map((part) => part.text).join("")
+  const details = reasoningDetails(reasoning, message.native?.openaiCompatible)
+  const observedField = reasoning.map(reasoningField).find((value) => value !== undefined)
+  const nativeReasoning = openAICompatibleReasoningContent(message.native?.openaiCompatible)
+  const fullyStructured = reasoning.every((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))
+  const field = (() => {
+    if (configuredField !== undefined) return configuredField
+    if (reasoning.length === 0) return undefined
+    if (observedField !== undefined) return observedField
+    if (nativeReasoning !== undefined) return "reasoning_content"
+    if (!fullyStructured) return "reasoning_content"
+  })()
+  const reasoningText = (() => {
+    if (configuredField !== undefined) return reasoning.length === 0 ? (nativeReasoning ?? "") : text
+    if (reasoning.length === 0) return nativeReasoning
+    return text
+  })()
+  const result = {
+    role: "assistant" as const,
+    content: content.length === 0 ? null : ProviderShared.joinText(content),
+    tool_calls: toolCalls.length === 0 ? undefined : toolCalls,
+    reasoning_details: details,
+  }
+  if (field === undefined || reasoningText === undefined) return result
+  return { ...result, [field]: reasoningText }
+})
+
+const lowerToolMessages = Effect.fn("OpenAIChat.lowerToolMessages")(function* (message: OpenAIChatRequestMessage) {
+  const messages: OpenAIChatMessage[] = []
+  const images: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
+  for (const part of message.content) {
+    if (!ProviderShared.supportsContent(part, ["tool-result"]))
+      return yield* ProviderShared.unsupportedContent("OpenAI Chat", "tool", ["tool-result"])
+    if (part.result.type !== "content") {
+      messages.push({ role: "tool", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })
+      continue
+    }
+    const content: ReadonlyArray<ToolContent> = part.result.value
+    const text = content.filter((item) => item.type === "text").map((item) => item.text)
+    messages.push({ role: "tool", tool_call_id: part.id, content: text.join("\n") })
+    const files = content.filter((item) => item.type === "file")
+    images.push(
+      ...(yield* Effect.forEach(files, (item) =>
+        lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name }),
+      )),
+    )
+  }
+  return { messages, images }
+})
+
+const lowerMessage = Effect.fn("OpenAIChat.lowerMessage")(function* (
+  message: OpenAIChatRequestMessage,
+  reasoningField?: string,
+) {
+  if (message.role === "user") return [yield* lowerUserMessage(message)]
+  if (message.role === "assistant") return [yield* lowerAssistantMessage(message, reasoningField)]
+  return (yield* lowerToolMessages(message)).messages
+})
+
+const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request: LLMRequest) {
+  const system: OpenAIChatMessage[] =
+    request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
+  const messages = [...system]
+  const pendingImages: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
+  const flushImages = () => {
+    if (pendingImages.length === 0) return
+    messages.push({ role: "user", content: pendingImages.splice(0) })
+  }
+  for (const message of request.messages) {
+    if (message.role === "system") {
+      const part = yield* ProviderShared.wrappedSystemUpdate("OpenAI Chat", message)
+      if (pendingImages.length > 0) {
+        messages.push({ role: "user", content: [...pendingImages.splice(0), { type: "text", text: part.text }] })
+        continue
+      }
+      const previous = messages.at(-1)
+      if (previous?.role === "user" && typeof previous.content === "string")
+        messages[messages.length - 1] = { role: "user", content: `${previous.content}\n${part.text}` }
+      else if (previous?.role === "user" && Array.isArray(previous.content))
+        messages[messages.length - 1] = {
+          role: "user",
+          content: [...previous.content, { type: "text", text: part.text }],
+        }
+      else messages.push({ role: "user", content: part.text })
+      continue
+    }
+    if (message.role === "tool") {
+      const lowered = yield* lowerToolMessages(message)
+      messages.push(...lowered.messages)
+      pendingImages.push(...lowered.images)
+      continue
+    }
+    flushImages()
+    messages.push(...(yield* lowerMessage(message, request.model.compatibility?.reasoningField)))
+  }
+  flushImages()
+  return messages
+})
+
+const lowerOptions = Effect.fn("OpenAIChat.lowerOptions")(function* (request: LLMRequest) {
+  const store = OpenAIOptions.store(request)
+  const reasoningEffort = OpenAIOptions.reasoningEffort(request)
+  return {
+    ...(store !== undefined ? { store } : {}),
+    ...(reasoningEffort ? { reasoning_effort: reasoningEffort } : {}),
+  }
+})
+
+const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (request: LLMRequest) {
+  // `fromRequest` returns the provider body only. Endpoint, auth, framing,
+  // validation, and HTTP execution are composed by `Route.make`.
+  const reasoningField = request.model.compatibility?.reasoningField
+  if (reasoningField && RESERVED_REASONING_FIELDS.has(reasoningField))
+    return yield* ProviderShared.invalidRequest(
+      `OpenAI Chat reasoning field conflicts with reserved field ${reasoningField}`,
+    )
+  const generation = request.generation
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
+  return {
+    model: request.model.id,
+    messages: yield* lowerMessages(request),
+    tools:
+      request.tools.length === 0
+        ? undefined
+        : request.tools.map((tool) =>
+            lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
+          ),
+    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
+    stream: true as const,
+    stream_options: { include_usage: true },
+    max_tokens: generation?.maxTokens,
+    temperature: generation?.temperature,
+    top_p: generation?.topP,
+    frequency_penalty: generation?.frequencyPenalty,
+    presence_penalty: generation?.presencePenalty,
+    seed: generation?.seed,
+    stop: generation?.stop,
+    ...(yield* lowerOptions(request)),
+  }
+})
+
+// =============================================================================
+// Stream Parsing
+// =============================================================================
+// Streaming parsers are small state machines: every event returns a new state
+// plus the common `LLMEvent`s produced by that event. Tool calls are accumulated
+// because OpenAI streams JSON arguments across multiple deltas.
+const mapFinishReason = (reason: string | null | undefined): FinishReason => {
+  if (reason === "stop") return "stop"
+  if (reason === "length") return "length"
+  if (reason === "content_filter") return "content-filter"
+  if (reason === "function_call" || reason === "tool_calls") return "tool-calls"
+  return "unknown"
+}
+
+// OpenAI Chat reports `prompt_tokens` (inclusive total) with a
+// `cached_tokens` subset, and `completion_tokens` (inclusive total) with
+// a `reasoning_tokens` subset. We pass the inclusive totals through and
+// derive the non-cached breakdown so the `LLM.Usage` contract is
+// satisfied on both sides.
+const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
+  if (!usage) return undefined
+  const cached = usage.prompt_tokens_details?.cached_tokens
+  const reasoning = usage.completion_tokens_details?.reasoning_tokens
+  const nonCached = ProviderShared.subtractTokens(usage.prompt_tokens, cached)
+  return new Usage({
+    inputTokens: usage.prompt_tokens,
+    outputTokens: usage.completion_tokens,
+    nonCachedInputTokens: nonCached,
+    cacheReadInputTokens: cached,
+    reasoningTokens: reasoning,
+    totalTokens: ProviderShared.totalTokens(usage.prompt_tokens, usage.completion_tokens, usage.total_tokens),
+    providerMetadata: { openai: usage },
+  })
+}
+
+const reasoningDelta = (
+  delta: Schema.Schema.Type<typeof OpenAIChatDelta> | null | undefined,
+  configuredField?: string,
+) => {
+  if (!delta) return undefined
+  const fields = new Set([configuredField, "reasoning_content", "reasoning", "reasoning_text"])
+  for (const field of fields) {
+    if (field === undefined) continue
+    const text = delta[field]
+    if (typeof text === "string" && text.length > 0) return { field, text }
+  }
+  return undefined
+}
+
+const detailText = (details: ReadonlyArray<unknown>) => {
+  const text = details.flatMap((detail) => {
+    if (!isRecord(detail)) return []
+    if (detail.type === "reasoning.text" && typeof detail.text === "string" && detail.text) return [detail.text]
+    if (detail.type === "reasoning.summary" && typeof detail.summary === "string" && detail.summary)
+      return [detail.summary]
+    return []
+  })
+  if (text.length > 0) return text.join("")
+}
+
+const appendReasoningDetails = (result: Array<unknown>, details: ReadonlyArray<unknown>) => {
+  for (const detail of details) {
+    const previous = result.at(-1)
+    if (
+      !isRecord(previous) ||
+      previous.type !== "reasoning.text" ||
+      !isRecord(detail) ||
+      detail.type !== "reasoning.text" ||
+      conflictingReasoningTextDetails(previous, detail)
+    ) {
+      result.push(detail)
+      continue
+    }
+    result[result.length - 1] = {
+      ...previous,
+      ...Object.fromEntries(Object.entries(detail).filter((entry) => entry[1] !== undefined)),
+      text: `${typeof previous.text === "string" ? previous.text : ""}${typeof detail.text === "string" ? detail.text : ""}`,
+      signature: mergeDetailValue(previous.signature, detail.signature),
+      format: mergeDetailValue(previous.format, detail.format),
+    }
+  }
+}
+
+const mergeDetailValue = (previous: unknown, current: unknown) =>
+  previous || current || (previous !== undefined ? previous : current)
+
+const conflictingReasoningTextDetails = (previous: Record<string, unknown>, current: Record<string, unknown>) =>
+  conflictingDetailValue(previous.id, current.id) ||
+  conflictingDetailValue(previous.index, current.index) ||
+  conflictingDetailValue(previous.format, current.format) ||
+  (Boolean(previous.signature) && Boolean(current.signature) && previous.signature !== current.signature)
+
+const conflictingDetailValue = (previous: unknown, current: unknown) =>
+  previous !== undefined && previous !== null && current !== undefined && current !== null && previous !== current
+
+const reasoningMetadata = (field: ParserState["reasoningField"], details?: ReadonlyArray<unknown>) => ({
+  openai: {
+    ...(field ? { reasoningField: field } : {}),
+    ...(details ? { reasoningDetails: details } : {}),
+  },
+})
+
+const step = (state: ParserState, event: OpenAIChatEvent) =>
+  Effect.gen(function* () {
+    const events: LLMEvent[] = []
+    const usage = mapUsage(event.usage) ?? state.usage
+    const choice = event.choices[0]
+    const finishReason = choice?.finish_reason ? mapFinishReason(choice.finish_reason) : state.finishReason
+    const delta = choice?.delta
+    const toolDeltas = delta?.tool_calls ?? []
+    let tools = state.tools
+    let pendingTools = state.pendingTools
+
+    let lifecycle = state.lifecycle
+
+    const reasoning = reasoningDelta(delta, state.reasoningField)
+    const reasoningField = state.reasoningField ?? (!state.lifecycle.text.has("text-0") ? reasoning?.field : undefined)
+    const detailDelta = Array.isArray(delta?.reasoning_details) ? delta.reasoning_details : undefined
+    if (detailDelta !== undefined) appendReasoningDetails(state.reasoningDetails, detailDelta)
+    const reasoningDetailsObserved = state.reasoningDetailsObserved || detailDelta !== undefined
+    const deltaMetadata = reasoningMetadata(reasoningField)
+    const text = detailDelta?.length ? (detailText(detailDelta) ?? reasoning?.text) : reasoning?.text
+    if (!state.lifecycle.text.has("text-0") && text !== undefined)
+      lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
+    else if (
+      reasoningDetailsObserved &&
+      !lifecycle.reasoning.has("reasoning-0") &&
+      (Boolean(delta?.content) || toolDeltas.length > 0)
+    )
+      lifecycle = Lifecycle.reasoningStart(lifecycle, events, "reasoning-0", deltaMetadata)
+    const reasoningEmitted = state.reasoningEmitted || lifecycle.reasoning.has("reasoning-0")
+
+    if (delta?.content) {
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningMetadata(reasoningField, reasoningDetailsObserved ? state.reasoningDetails : undefined),
+      )
+      lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.content)
+    }
+
+    for (const tool of toolDeltas) {
+      const current = tools[tool.index]
+      const pending = pendingTools[tool.index]
+      const id = current?.id ?? pending?.id ?? (tool.id || undefined)
+      const name = current?.name ?? pending?.name ?? (tool.function?.name || undefined)
+      const text = `${pending?.input ?? ""}${tool.function?.arguments ?? ""}`
+      if (!current && (!id || !name)) {
+        pendingTools = { ...pendingTools, [tool.index]: { id: id || undefined, name: name || undefined, input: text } }
+        continue
+      }
+      if (pending) {
+        pendingTools = { ...pendingTools }
+        delete pendingTools[tool.index]
+      }
+      const result = ToolStream.appendOrStart(
+        ADAPTER,
+        tools,
+        tool.index,
+        { id: id || undefined, name: name || undefined, text },
+        "OpenAI Chat tool call delta is missing id or name",
+      )
+      if (ToolStream.isError(result)) return yield* result
+      tools = result.tools
+      if (result.events.length) lifecycle = Lifecycle.stepStart(lifecycle, events)
+      events.push(...result.events)
+    }
+
+    if (finishReason !== undefined && state.finishReason === undefined && Object.keys(pendingTools).length > 0)
+      return yield* ProviderShared.eventError(ADAPTER, "OpenAI Chat tool call delta is missing id or name")
+
+    // Finalize accumulated tool inputs eagerly when finish_reason arrives so
+    // valid calls and malformed local calls settle independently.
+    const finished =
+      finishReason !== undefined && state.finishReason === undefined && Object.keys(tools).length > 0
+        ? yield* ToolStream.finishAll(ADAPTER, tools)
+        : undefined
+
+    return [
+      {
+        tools: finished?.tools ?? tools,
+        pendingTools,
+        toolCallEvents: finished?.events ?? state.toolCallEvents,
+        usage,
+        finishReason,
+        lifecycle,
+        reasoningField,
+        reasoningDetails: state.reasoningDetails,
+        reasoningDetailsObserved,
+        reasoningEmitted,
+      },
+      events,
+    ] as const
+  })
+
+const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
+  const events: LLMEvent[] = []
+  const hasToolCalls = state.toolCallEvents.length > 0
+  const reason = state.finishReason === "stop" && hasToolCalls ? "tool-calls" : state.finishReason
+  const metadata = reasoningMetadata(
+    state.reasoningField,
+    state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
+  )
+  const started =
+    state.reasoningDetailsObserved && !state.reasoningEmitted
+      ? Lifecycle.reasoningStart(state.lifecycle, events, "reasoning-0", reasoningMetadata(state.reasoningField))
+      : state.lifecycle
+  const ended = Lifecycle.reasoningEnd(started, events, "reasoning-0", metadata)
+  const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(ended, events) : ended
+  events.push(...state.toolCallEvents)
+  if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })
+  return events
+}
+
+// =============================================================================
+// Protocol And OpenAI Route
+// =============================================================================
+/**
+ * The OpenAI Chat protocol — request body construction, body schema, and the
+ * streaming-event state machine. Reused by every route that speaks OpenAI Chat
+ * over HTTP+SSE: native OpenAI, DeepSeek, TogetherAI, Cerebras, Baseten,
+ * Fireworks, DeepInfra, and (once added) Azure OpenAI Chat.
+ */
+export const protocol = Protocol.make({
+  id: ADAPTER,
+  body: {
+    schema: OpenAIChatBody,
+    from: fromRequest,
+  },
+  stream: {
+    event: Protocol.jsonEvent(OpenAIChatEvent),
+    initial: (request) => ({
+      tools: ToolStream.empty<number>(),
+      pendingTools: {},
+      toolCallEvents: [],
+      lifecycle: Lifecycle.initial(),
+      reasoningField: request.model.compatibility?.reasoningField,
+      reasoningDetails: [],
+      reasoningDetailsObserved: false,
+      reasoningEmitted: false,
+    }),
+    step,
+    onHalt: finishEvents,
+  },
+})
+
+export const httpTransport = HttpTransport.sseJson.with<OpenAIChatBody>()
+
+export const route = Route.make({
+  id: ADAPTER,
+  provider: "openai",
+  providerMetadataKey: "openai",
+  protocol,
+  endpoint: Endpoint.path(PATH, { baseURL: DEFAULT_BASE_URL }),
+  auth: Auth.none,
+  transport: httpTransport,
+})
+
+export * as OpenAIChat from "./openai-chat"

packages/ai/src/protocols/openai-compatible-chat.ts

@@ -16,6 +16,7 @@ export type OpenAICompatibleChatModelInput = RouteRoutedModelInput
  */
 export const route = Route.make({
   id: ADAPTER,
+  providerMetadataKey: "openai",
   protocol: OpenAIChat.protocol,
   endpoint: Endpoint.path("/chat/completions"),
   framing: Framing.sse,

packages/ai/src/protocols/openai-compatible-responses.ts

@@ -0,0 +1,23 @@
+import { Route, type RouteRoutedModelInput } from "../route/client"
+import { Endpoint } from "../route/endpoint"
+import { OpenAIResponses } from "./openai-responses"
+
+const ADAPTER = "openai-compatible-responses"
+
+export type OpenAICompatibleResponsesModelInput = RouteRoutedModelInput
+
+/**
+ * Route for providers that expose an OpenAI Responses-compatible `/responses`
+ * endpoint. Provider helpers configure identity, endpoint, and auth before
+ * model selection while this route reuses the OpenAI Responses protocol.
+ */
+export const route = Route.make({
+  id: ADAPTER,
+  providerMetadataKey: "openai",
+  protocol: OpenAIResponses.protocol,
+  endpoint: Endpoint.path(OpenAIResponses.PATH),
+  transport: OpenAIResponses.httpTransport,
+  defaults: { providerOptions: { openai: { store: false } } },
+})
+
+export * as OpenAICompatibleResponses from "./openai-compatible-responses"

packages/ai/src/protocols/openai-images.ts

@@ -0,0 +1,270 @@
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
+import {
+  ImageModel,
+  GeneratedImage,
+  ImageResponse,
+  type ImageInput,
+  type ImageRequestFor,
+  type ImageRoute,
+} from "../image"
+import { Auth, type Definition as AuthDefinition } from "../route/auth"
+import {
+  InvalidProviderOutputReason,
+  LLMError,
+  Usage,
+  mergeHttpOptions,
+  mergeJsonRecords,
+  type HttpOptions,
+} from "../schema"
+import { ProviderShared } from "./shared"
+import { ImageInputs } from "./utils/image-input"
+import { OpenAIImage } from "./utils/openai-image"
+
+const ADAPTER = "openai-images"
+export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
+export const PATH = "/images/generations"
+export const EDIT_PATH = "/images/edits"
+
+export type OpenAIImageString<Known extends string> = Known | (string & {})
+
+export type OpenAIImageOptions = {
+  readonly mask?: ImageInput
+  readonly n?: number
+  readonly size?: OpenAIImageString<
+    "auto" | "256x256" | "512x512" | "1024x1024" | "1536x1024" | "1024x1536" | "1792x1024" | "1024x1792"
+  >
+  readonly quality?: OpenAIImageString<"auto" | "low" | "medium" | "high" | "standard" | "hd">
+  readonly background?: OpenAIImageString<"auto" | "opaque" | "transparent">
+  readonly moderation?: OpenAIImageString<"auto" | "low">
+  readonly outputFormat?: OpenAIImageString<"png" | "jpeg" | "webp">
+  readonly outputCompression?: number
+} & Record<string, unknown>
+
+export type OpenAIImageBody = Record<string, unknown> & {
+  readonly model: string
+  readonly prompt: string
+}
+
+const OpenAIImageResponse = Schema.Struct({
+  data: Schema.Array(
+    Schema.Struct({
+      b64_json: Schema.optional(Schema.String),
+      url: Schema.optional(Schema.String),
+      revised_prompt: Schema.optional(Schema.String),
+    }),
+  ),
+  output_format: Schema.optional(Schema.String),
+  usage: Schema.optional(
+    Schema.Struct({
+      input_tokens: Schema.optional(Schema.Number),
+      output_tokens: Schema.optional(Schema.Number),
+      total_tokens: Schema.optional(Schema.Number),
+      input_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+      output_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+    }),
+  ),
+})
+
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}
+
+const nativeOptions = (options: OpenAIImageOptions | undefined) => {
+  if (!options) return undefined
+  const { mask: _, outputFormat, outputCompression, ...native } = options
+  return {
+    output_format: outputFormat,
+    output_compression: outputCompression,
+    ...native,
+  }
+}
+
+const invalidOutput = (message: string) =>
+  new LLMError({
+    module: ADAPTER,
+    method: "generate",
+    reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),
+  })
+
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<OpenAIImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("OpenAIImages.generate")(function* (request: ImageRequestFor<OpenAIImageOptions>, execute) {
+      const mask = request.options?.mask
+      if (mask !== undefined && (request.images?.length ?? 0) === 0)
+        return yield* ImageInputs.invalid(ADAPTER, "An OpenAI image mask requires at least one input image")
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const sourceImages = request.images ?? []
+      const multipartImages = yield* Effect.forEach(sourceImages, (image) => {
+        if (image.type === "bytes") return Effect.succeed({ data: image.data, mediaType: image.mediaType })
+        if (image.type === "url") return ImageInputs.decodeDataUrl(image.url, ADAPTER)
+        return Effect.succeed(undefined)
+      })
+      const multipartMask =
+        mask === undefined
+          ? undefined
+          : mask.type === "bytes"
+            ? { data: mask.data, mediaType: mask.mediaType }
+            : mask.type === "url"
+              ? yield* ImageInputs.decodeDataUrl(mask.url, ADAPTER)
+              : undefined
+      const useMultipart =
+        sourceImages.length > 0 &&
+        multipartImages.every((image) => image !== undefined) &&
+        (mask === undefined || multipartMask !== undefined)
+      const path = sourceImages.length === 0 ? PATH : EDIT_PATH
+      const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${path}`, http?.query)
+
+      if (useMultipart) {
+        const form = new FormData()
+        form.append("model", request.model.id)
+        form.append("prompt", request.prompt)
+        Object.entries(mergeJsonRecords(nativeOptions(request.options), http?.body) ?? {}).forEach(([key, value]) => {
+          if (["model", "prompt", "image", "image[]", "images", "mask"].includes(key)) return
+          form.append(key, typeof value === "string" ? value : ProviderShared.encodeJson(value))
+        })
+        multipartImages.forEach((image, index) => {
+          if (image === undefined) return
+          form.append("image[]", imageBlob(image.data, image.mediaType), `image-${index}`)
+        })
+        if (multipartMask !== undefined)
+          form.append("mask", imageBlob(multipartMask.data, multipartMask.mediaType), "mask")
+        const headers = yield* Auth.toEffect(input.auth)({
+          request,
+          method: "POST",
+          url,
+          body: "[multipart/form-data]",
+          headers: Headers.remove(Headers.fromInput({ ...input.headers, ...http?.headers }), "content-type"),
+        })
+        const response = yield* execute(
+          HttpClientRequest.post(url).pipe(HttpClientRequest.setHeaders(headers), HttpClientRequest.bodyFormData(form)),
+        )
+        return yield* parseResponse(response, request.options, http?.body)
+      }
+
+      const references = sourceImages.map((image) => {
+        if (image.type === "bytes") return { image_url: ImageInputs.dataUrl(image) }
+        if (image.type === "url") return { image_url: image.url }
+        if (image.type === "file-id") return { file_id: image.id }
+        return undefined
+      })
+      if (references.some((image) => image === undefined))
+        return yield* ImageInputs.invalid(ADAPTER, "OpenAI Images accepts image URLs, data URLs, bytes, and file IDs")
+      const maskReference =
+        mask === undefined
+          ? undefined
+          : mask.type === "bytes"
+            ? { image_url: ImageInputs.dataUrl(mask) }
+            : mask.type === "url"
+              ? { image_url: mask.url }
+              : mask.type === "file-id"
+                ? { file_id: mask.id }
+                : undefined
+      if (mask !== undefined && maskReference === undefined)
+        return yield* ImageInputs.invalid(ADAPTER, "OpenAI Images accepts masks as URLs, data URLs, bytes, or file IDs")
+      const requestBody = mergeJsonRecords(
+        {
+          model: request.model.id,
+          prompt: request.prompt,
+          images: references.length === 0 ? undefined : references,
+          mask: maskReference,
+        },
+        nativeOptions(request.options),
+        http?.body,
+      ) as OpenAIImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      return yield* parseResponse(response, request.options, http?.body)
+    }),
+  }
+  return ImageModel.make<OpenAIImageOptions>({ id: input.id, provider: "openai", route, http: input.http })
+}
+
+const parseResponse = Effect.fn("OpenAIImages.parseResponse")(function* (
+  response: HttpClientResponse.HttpClientResponse,
+  options: OpenAIImageOptions | undefined,
+  overlay: Record<string, unknown> | undefined,
+) {
+  const payload = yield* response.json.pipe(
+    Effect.mapError(() => invalidOutput("Failed to read the OpenAI Images response")),
+  )
+  const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(
+    Effect.mapError(() => invalidOutput("OpenAI Images returned an invalid response")),
+  )
+  const requestBody = mergeJsonRecords(nativeOptions(options), overlay)
+  const format =
+    decoded.output_format ?? (typeof requestBody?.output_format === "string" ? requestBody.output_format : "png")
+  const images = yield* Effect.forEach(decoded.data, (item, index) => {
+    if (item.b64_json)
+      return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
+        Effect.mapError(() => invalidOutput(`OpenAI Images result ${index} contains invalid base64 data`)),
+        Effect.map(
+          (data) =>
+            new GeneratedImage({
+              mediaType: `image/${format}`,
+              data,
+              providerMetadata:
+                item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+            }),
+        ),
+      )
+    if (item.url)
+      return Effect.succeed(
+        new GeneratedImage({
+          mediaType: `image/${format}`,
+          data: item.url,
+          providerMetadata:
+            item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+        }),
+      )
+    return Effect.fail(invalidOutput(`OpenAI Images result ${index} has neither image data nor a URL`))
+  })
+  if (images.length === 0) return yield* invalidOutput("OpenAI Images returned no images")
+  return new ImageResponse({
+    images,
+    usage:
+      decoded.usage === undefined
+        ? undefined
+        : new Usage({
+            inputTokens: decoded.usage.input_tokens,
+            outputTokens: decoded.usage.output_tokens,
+            totalTokens: decoded.usage.total_tokens,
+            providerMetadata: { openai: decoded.usage },
+          }),
+    providerMetadata: { openai: { outputFormat: format } },
+  })
+})
+
+const imageBlob = (data: Uint8Array, mediaType: string) => {
+  const buffer = new ArrayBuffer(data.byteLength)
+  new Uint8Array(buffer).set(data)
+  return new Blob([buffer], { type: mediaType })
+}
+
+export const OpenAIImages = {
+  model,
+} as const

packages/ai/src/protocols/openai-responses.ts

@@ -1,14 +1,17 @@
-import { Effect, Schema } from "effect"
+import { Effect, Encoding, Schema } from "effect"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
 import { HttpTransport, WebSocketTransport } from "../route/transport"
 import { Protocol } from "../route/protocol"
 import {
+  LLMError,
   LLMEvent,
   Usage,
   type FinishReason,
+  type JsonSchema,
   type LLMRequest,
+  type MediaPart,
   type ProviderMetadata,
   type ReasoningPart,
   type TextPart,
@@ -18,12 +21,15 @@ import {
   type ToolResultPart,
 } from "../schema"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared"
-import { isContextOverflow } from "../provider-error"
+import { classifyProviderFailure } from "../provider-error"
 import { OpenAIOptions } from "./utils/openai-options"
 import { Lifecycle } from "./utils/lifecycle"
+import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
+import { OpenAIImage } from "./utils/openai-image"
 
 const ADAPTER = "openai-responses"
+const MEDIA_MIMES = new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.PDF_MIMES])
 export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
 export const PATH = "/responses"
 
@@ -38,7 +44,17 @@ const OpenAIResponsesInputImage = Schema.Struct({
   type: Schema.tag("input_image"),
   image_url: Schema.String,
 })
-const OpenAIResponsesInputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])
+const OpenAIResponsesInputFile = Schema.Struct({
+  type: Schema.tag("input_file"),
+  filename: Schema.String,
+  file_data: Schema.String,
+  mime_type: Schema.optional(Schema.String),
+})
+const OpenAIResponsesInputContent = Schema.Union([
+  OpenAIResponsesInputText,
+  OpenAIResponsesInputImage,
+  OpenAIResponsesInputFile,
+])
 type OpenAIResponsesInputContent = Schema.Schema.Type<typeof OpenAIResponsesInputContent>
 
 const OpenAIResponsesOutputText = Schema.Struct({
@@ -53,7 +69,7 @@ const OpenAIResponsesReasoningSummaryText = Schema.Struct({
 
 const OpenAIResponsesReasoningItem = Schema.Struct({
   type: Schema.tag("reasoning"),
-  id: Schema.String,
+  id: Schema.optionalKey(Schema.String),
   summary: Schema.Array(OpenAIResponsesReasoningSummaryText),
   encrypted_content: optionalNull(Schema.String),
 })
@@ -64,9 +80,13 @@ const OpenAIResponsesItemReference = Schema.Struct({
 })
 
 // `function_call_output.output` accepts either a plain string or an ordered
-// array of content items so tools can return images in addition to text.
+// array of content items so tools can return images and files in addition to text.
 // https://platform.openai.com/docs/api-reference/responses/object
-const OpenAIResponsesFunctionCallOutputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])
+const OpenAIResponsesFunctionCallOutputContent = Schema.Union([
+  OpenAIResponsesInputText,
+  OpenAIResponsesInputImage,
+  OpenAIResponsesInputFile,
+])
 
 const OpenAIResponsesFunctionCallOutput = Schema.Union([
   Schema.String,
@@ -101,6 +121,7 @@ type OpenAIResponsesReasoningInput = {
   summary: Array<{ type: "summary_text"; text: string }>
   encrypted_content?: string | null
 }
+type OpenAIResponsesReasoningReplay = Omit<OpenAIResponsesReasoningInput, "id">
 
 const OpenAIResponsesTool = Schema.Struct({
   type: Schema.tag("function"),
@@ -109,11 +130,24 @@ const OpenAIResponsesTool = Schema.Struct({
   parameters: JsonObject,
   strict: Schema.optional(Schema.Boolean),
 })
-type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTool>
+const OpenAIResponsesImageGenerationTool = Schema.Struct({
+  type: Schema.tag("image_generation"),
+  action: Schema.optional(Schema.Literals(["auto", "generate", "edit"])),
+  background: Schema.optional(Schema.Literals(["auto", "opaque", "transparent"])),
+  input_fidelity: Schema.optional(Schema.Literals(["low", "high"])),
+  output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
+  partial_images: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(0))),
+  quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
+  size: Schema.optional(OpenAIImage.Size),
+})
+const OpenAIResponsesTools = Schema.Union([OpenAIResponsesTool, OpenAIResponsesImageGenerationTool])
+type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTools>
 
 const OpenAIResponsesToolChoice = Schema.Union([
   Schema.Literals(["auto", "none", "required"]),
   Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
+  Schema.Struct({ type: Schema.tag("image_generation") }),
 ])
 
 // Fields shared between the HTTP body and the WebSocket `response.create`
@@ -124,7 +158,7 @@ const OpenAIResponsesCoreFields = {
   model: Schema.String,
   input: Schema.Array(OpenAIResponsesInputItem),
   instructions: Schema.optional(Schema.String),
-  tools: optionalArray(OpenAIResponsesTool),
+  tools: optionalArray(OpenAIResponsesTools),
   tool_choice: Schema.optional(OpenAIResponsesToolChoice),
   store: Schema.optional(Schema.Boolean),
   service_tier: Schema.optional(OpenAIOptions.OpenAIServiceTier),
@@ -190,16 +224,18 @@ const OpenAIResponsesStreamItem = Schema.Struct({
   outputs: Schema.optional(Schema.Unknown),
   server_label: Schema.optional(Schema.String),
   output: Schema.optional(Schema.Unknown),
+  result: Schema.optional(Schema.String),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
   error: Schema.optional(Schema.Unknown),
   encrypted_content: optionalNull(Schema.String),
 })
 type OpenAIResponsesStreamItem = Schema.Schema.Type<typeof OpenAIResponsesStreamItem>
 
-// OpenAI Responses surfaces provider failures in two related shapes. The
-// streaming `error` event carries the details at the top level
-// (`{ type: "error", code, message, param, sequence_number }`), while
-// `response.failed` carries them under `response.error`. We capture both so
-// the parser can surface a useful provider-error message in either path.
+// The Responses schema puts streaming error details at the top level and
+// response failures under `response.error`. The official SDK also recognizes
+// an event-level HTTP-style `error` envelope, so accept all three shapes here.
+// https://github.com/openai/openai-openapi/blob/5162af98d3147432c14680df789e8e12d4891e6b/openapi.yaml#L67234-L67382
+// https://github.com/openai/openai-node/blob/61539248cbe04665de68a71e6fd878127ae4db87/src/core/streaming.ts#L58-L85
 const OpenAIResponsesErrorPayload = Schema.Struct({
   code: optionalNull(Schema.String),
   message: optionalNull(Schema.String),
@@ -224,9 +260,10 @@ const OpenAIResponsesEvent = Schema.Struct({
       [Schema.Record(Schema.String, Schema.Unknown)],
     ),
   ),
-  code: Schema.optional(Schema.String),
+  code: optionalNull(Schema.String),
   message: Schema.optional(Schema.String),
-  param: Schema.optional(Schema.String),
+  param: optionalNull(Schema.String),
+  error: optionalNull(OpenAIResponsesErrorPayload),
 })
 type OpenAIResponsesEvent = Schema.Schema.Type<typeof OpenAIResponsesEvent>
 
@@ -253,19 +290,41 @@ const invalid = ProviderShared.invalidRequest
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerTool = (tool: ToolDefinition): OpenAIResponsesTool => ({
-  type: "function",
-  name: tool.name,
-  description: tool.description,
-  parameters: ProviderShared.openAiToolInputSchema(tool.inputSchema),
+const nativeImageToolInput = (tool: ToolDefinition) => {
+  const native = tool.native?.openai
+  return ProviderShared.isRecord(native) && native.type === "image_generation" ? native : undefined
+}
+
+const nativeImageTool = (tool: ToolDefinition) => {
+  const native = nativeImageToolInput(tool)
+  return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
+}
+
+const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition, inputSchema: JsonSchema) {
+  const native = nativeImageToolInput(tool)
+  if (native !== undefined) {
+    if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
+    return yield* invalid("OpenAI Responses image generation tool options are invalid")
+  }
+  return {
+    type: "function" as const,
+    name: tool.name,
+    description: tool.description,
+    parameters: ToolSchemaProjection.openAI(inputSchema),
+    // TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.
+    strict: false,
+  }
 })
 
-const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
+const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tools: ReadonlyArray<ToolDefinition>) =>
   ProviderShared.matchToolChoice("OpenAI Responses", toolChoice, {
     auto: () => "auto" as const,
     none: () => "none" as const,
     required: () => "required" as const,
-    tool: (name) => ({ type: "function" as const, name }),
+    tool: (name) =>
+      tools.some((tool) => tool.name === name && nativeImageTool(tool) !== undefined)
+        ? ({ type: "image_generation" } as const)
+        : { type: "function" as const, name },
   })
 
 const lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({
@@ -300,42 +359,58 @@ const hostedToolItemID = (part: ToolResultPart) => {
     : undefined
 }
 
-const lowerUserContent = Effect.fn("OpenAIResponses.lowerUserContent")(function* (
-  part: LLMRequest["messages"][number]["content"][number],
-) {
-  if (part.type === "text") return { type: "input_text" as const, text: part.text }
-  if (part.type === "media") {
-    const media = yield* ProviderShared.validateMedia(
-      "OpenAI Responses",
-      part,
-      new Set<string>(ProviderShared.IMAGE_MIMES),
-    )
-    return { type: "input_image" as const, image_url: media.dataUrl }
+const lowerMedia = Effect.fn("OpenAIResponses.lowerMedia")(function* (part: MediaPart, provider: string) {
+  const media = yield* ProviderShared.validateMedia("OpenAI Responses", part, MEDIA_MIMES)
+  if (media.mime === "application/pdf") {
+    // xAI models inline bytes and MIME separately; OpenAI uses a data URL in file_data.
+    if (provider === "xai")
+      return {
+        type: "input_file" as const,
+        filename: part.filename ?? "document.pdf",
+        file_data: media.base64,
+        mime_type: media.mime,
+      }
+    return {
+      type: "input_file" as const,
+      filename: part.filename ?? "document.pdf",
+      file_data: media.dataUrl,
+    }
   }
-  return yield* ProviderShared.unsupportedContent("OpenAI Responses", "user", ["text", "media"])
-})
-
-// Tool results may carry structured text/images. Keep media as provider-native
-// content instead of JSON-stringifying base64 into a prompt string.
-const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultContentItem")(function* (
-  item: ToolContent,
-) {
-  if (item.type === "text") return { type: "input_text" as const, text: item.text }
-  const media = yield* ProviderShared.validateToolFile(
-    "OpenAI Responses",
-    item,
-    new Set<string>(ProviderShared.IMAGE_MIMES),
-  )
   return { type: "input_image" as const, image_url: media.dataUrl }
 })
 
-const lowerToolResultOutput = Effect.fn("OpenAIResponses.lowerToolResultOutput")(function* (part: ToolResultPart) {
+const lowerUserContent = Effect.fn("OpenAIResponses.lowerUserContent")(function* (
+  part: LLMRequest["messages"][number]["content"][number],
+  provider: string,
+) {
+  if (part.type === "text") return { type: "input_text" as const, text: part.text }
+  if (part.type === "media") return yield* lowerMedia(part, provider)
+  return yield* ProviderShared.unsupportedContent("OpenAI Responses", "user", ["text", "media"])
+})
+
+// Tool results may carry structured text, images, and files. Keep media as provider-native
+// content instead of JSON-stringifying base64 into a prompt string.
+const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultContentItem")(function* (
+  item: ToolContent,
+  provider: string,
+) {
+  if (item.type === "text") return { type: "input_text" as const, text: item.text }
+  return yield* lowerMedia(
+    { type: "media", mediaType: item.mime, data: item.uri, filename: item.name },
+    provider,
+  )
+})
+
+const lowerToolResultOutput = Effect.fn("OpenAIResponses.lowerToolResultOutput")(function* (
+  part: ToolResultPart,
+  provider: string,
+) {
   // Text/json/error results are encoded as a plain string for backward
   // compatibility with existing cassettes and provider expectations.
   if (part.result.type !== "content") return ProviderShared.toolResultText(part)
   // Preserve the narrowed array element type when compiled through a consumer package.
   const content: ReadonlyArray<ToolContent> = part.result.value
-  return yield* Effect.forEach(content, lowerToolResultContentItem)
+  return yield* Effect.forEach(content, (item) => lowerToolResultContentItem(item, provider))
 })
 
 const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (request: LLMRequest) {
@@ -358,13 +433,16 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
     }
 
     if (message.role === "user") {
-      input.push({ role: "user", content: yield* Effect.forEach(message.content, lowerUserContent) })
+      input.push({
+        role: "user",
+        content: yield* Effect.forEach(message.content, (part) => lowerUserContent(part, request.model.provider)),
+      })
       continue
     }
 
     if (message.role === "assistant") {
       const content: TextPart[] = []
-      const reasoningItems: Record<string, OpenAIResponsesReasoningInput> = {}
+      const reasoningItems: Record<string, OpenAIResponsesReasoningReplay> = {}
       const reasoningReferences = new Set<string>()
       const hostedToolReferences = new Set<string>()
       const flushText = () => {
@@ -381,7 +459,7 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
           flushText()
           const reasoning = lowerReasoning(part)
           if (!reasoning) continue
-          if (store !== false && reasoning.id) {
+          if (store !== false) {
             if (!reasoningReferences.has(reasoning.id)) input.push({ type: "item_reference", id: reasoning.id })
             reasoningReferences.add(reasoning.id)
             continue
@@ -393,8 +471,13 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
               existing.encrypted_content = reasoning.encrypted_content
             continue
           }
-          reasoningItems[reasoning.id] = reasoning
-          input.push(reasoning)
+          const replay = {
+            type: reasoning.type,
+            summary: reasoning.summary,
+            encrypted_content: reasoning.encrypted_content,
+          }
+          reasoningItems[reasoning.id] = replay
+          input.push(replay)
           continue
         }
         if (part.type === "tool-call") {
@@ -408,6 +491,15 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
           const itemID = hostedToolItemID(part)
           if (store !== false && itemID && !hostedToolReferences.has(itemID))
             input.push({ type: "item_reference", id: itemID })
+          if (store === false && part.name === "image_generation" && part.result.type === "content") {
+            const content: ReadonlyArray<ToolContent> = part.result.value
+            input.push({
+              role: "user",
+              content: yield* Effect.forEach(content, (item) =>
+                lowerToolResultContentItem(item, request.model.provider),
+              ),
+            })
+          }
           if (itemID) hostedToolReferences.add(itemID)
           continue
         }
@@ -428,7 +520,7 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
       input.push({
         type: "function_call_output",
         call_id: part.id,
-        output: yield* lowerToolResultOutput(part),
+        output: yield* lowerToolResultOutput(part, request.model.provider),
       })
     }
   }
@@ -447,8 +539,6 @@ const lowerOptions = Effect.fn("OpenAIResponses.lowerOptions")(function* (reques
   const store = OpenAIOptions.store(request)
   const promptCacheKey = OpenAIOptions.promptCacheKey(request)
   const effort = OpenAIOptions.reasoningEffort(request)
-  if (effort && !OpenAIOptions.isReasoningEffort(effort))
-    return yield* invalid(`OpenAI Responses does not support reasoning effort ${effort}`)
   const summary = OpenAIOptions.reasoningSummary(request)
   const include = OpenAIOptions.include(request)
   const verbosity = OpenAIOptions.textVerbosity(request)
@@ -468,11 +558,17 @@ const lowerOptions = Effect.fn("OpenAIResponses.lowerOptions")(function* (reques
 const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request: LLMRequest) {
   const generation = request.generation
   const options = yield* lowerOptions(request)
+  const toolSchemaCompatibility = request.model.compatibility?.toolSchema
   return {
     model: request.model.id,
     input: yield* lowerMessages(request),
-    tools: request.tools.length === 0 ? undefined : request.tools.map(lowerTool),
-    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
+    tools:
+      request.tools.length === 0
+        ? undefined
+        : yield* Effect.forEach(request.tools, (tool) =>
+            lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
+          ),
+    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice, request.tools) : undefined,
     stream: true as const,
     max_output_tokens: generation?.maxTokens,
     temperature: generation?.temperature,
@@ -558,14 +654,29 @@ const isReasoningItem = (
 
 // Round-trip the full item as the structured result so consumers can extract
 // outputs / sources / status without re-decoding.
-const hostedToolResult = (item: OpenAIResponsesStreamItem) => {
+const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: OpenAIResponsesStreamItem) {
   const isError = typeof item.error !== "undefined" && item.error !== null
+  if (item.type === "image_generation_call" && item.result) {
+    yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
+      Effect.mapError(() => ProviderShared.eventError(ADAPTER, "OpenAI Responses returned invalid image base64")),
+    )
+    return {
+      type: "content" as const,
+      value: [
+        {
+          type: "file" as const,
+          uri: `data:image/${item.output_format ?? "png"};base64,${item.result}`,
+          mime: `image/${item.output_format ?? "png"}`,
+        },
+      ],
+    }
+  }
   return isError ? { type: "error" as const, value: item.error } : { type: "json" as const, value: item }
-}
+})
 
-const hostedToolEvents = (
+const hostedToolEvents = Effect.fn("OpenAIResponses.hostedToolEvents")(function* (
   item: OpenAIResponsesStreamItem & { type: HostedToolType; id: string },
-): ReadonlyArray<LLMEvent> => {
+) {
   const tool = HOSTED_TOOLS[item.type]
   const providerMetadata = openaiMetadata({ itemId: item.id })
   return [
@@ -579,21 +690,20 @@ const hostedToolEvents = (
     LLMEvent.toolResult({
       id: item.id,
       name: tool.name,
-      result: hostedToolResult(item),
+      result: yield* hostedToolResult(item),
       providerExecuted: true,
       providerMetadata,
     }),
   ]
-}
+})
 
 type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
 
 const NO_EVENTS: StepResult["1"] = []
 
 // `response.completed` / `response.incomplete` are clean finishes that emit a
-// `finish` event; `response.failed` is a hard failure that emits a
-// `provider-error`. All three end the stream — kept in one set so `step` and
-// the protocol's `terminal` predicate stay in sync.
+// `finish` event; `response.failed` is a hard failure. All three end the stream,
+// so keep this set aligned with `step` and the protocol's terminal predicate.
 const TERMINAL_TYPES = new Set(["response.completed", "response.incomplete", "response.failed"])
 
 const onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
@@ -605,6 +715,11 @@ const onOutputTextDelta = (state: ParserState, event: OpenAIResponsesEvent): Ste
   ]
 }
 
+const onOutputTextDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
+  const events: LLMEvent[] = []
+  return [{ ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, event.item_id ?? "text-0") }, events]
+}
+
 const onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
   if (!event.delta) return [state, NO_EVENTS]
   const events: LLMEvent[] = []
@@ -796,6 +911,8 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
   const item = event.item
   if (!item) return [state, NO_EVENTS] satisfies StepResult
 
+  if (item.type === "message" && item.id) return onOutputTextDone(state, { ...event, item_id: item.id })
+
   if (item.type === "function_call") {
     if (!item.id || !item.call_id || !item.name) return [state, NO_EVENTS] satisfies StepResult
     const tools = state.tools[item.id]
@@ -813,7 +930,9 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
       {
         ...state,
         lifecycle,
-        hasFunctionCall: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasFunctionCall,
+        hasFunctionCall:
+          resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
+          state.hasFunctionCall,
         tools: result.tools,
       },
       events,
@@ -823,7 +942,7 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
   if (isHostedToolItem(item)) {
     const events: LLMEvent[] = []
     const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
-    events.push(...hostedToolEvents(item))
+    events.push(...(yield* hostedToolEvents(item)))
     return [{ ...state, lifecycle }, events] satisfies StepResult
   }
 
@@ -878,7 +997,7 @@ const onResponseFinish = (state: ParserState, event: OpenAIResponsesEvent): Step
 // the bare message — production rate limits and context-length failures used
 // to be indistinguishable from generic stream drops.
 const providerErrorMessage = (event: OpenAIResponsesEvent, fallback: string): string => {
-  const nested = event.response?.error ?? undefined
+  const nested = event.error ?? event.response?.error ?? undefined
   const message = event.message || nested?.message || undefined
   const code = event.code || nested?.code || undefined
   if (message && code) return `${code}: ${message}`
@@ -886,26 +1005,18 @@ const providerErrorMessage = (event: OpenAIResponsesEvent, fallback: string): st
 }
 
 const providerError = (event: OpenAIResponsesEvent, fallback: string) => {
-  const code = event.code || event.response?.error?.code || undefined
+  const code = event.code || event.error?.code || event.response?.error?.code || undefined
   const message = providerErrorMessage(event, fallback)
-  return LLMEvent.providerError({
-    message,
-    classification: code === "context_length_exceeded" || isContextOverflow(message) ? "context-overflow" : undefined,
+  return new LLMError({
+    module: ADAPTER,
+    method: "stream",
+    reason: classifyProviderFailure({ message, code }),
   })
 }
 
-const onResponseFailed = (state: ParserState, event: OpenAIResponsesEvent): StepResult => [
-  state,
-  [providerError(event, "OpenAI Responses response failed")],
-]
-
-const onError = (state: ParserState, event: OpenAIResponsesEvent): StepResult => [
-  state,
-  [providerError(event, "OpenAI Responses stream error")],
-]
-
 const step = (state: ParserState, event: OpenAIResponsesEvent) => {
   if (event.type === "response.output_text.delta") return Effect.succeed(onOutputTextDelta(state, event))
+  if (event.type === "response.output_text.done") return Effect.succeed(onOutputTextDone(state, event))
   if (
     event.type === "response.reasoning_text.delta" ||
     event.type === "response.reasoning_summary.delta" ||
@@ -927,8 +1038,8 @@ const step = (state: ParserState, event: OpenAIResponsesEvent) => {
   if (event.type === "response.output_item.done") return onOutputItemDone(state, event)
   if (event.type === "response.completed" || event.type === "response.incomplete")
     return Effect.succeed(onResponseFinish(state, event))
-  if (event.type === "response.failed") return Effect.succeed(onResponseFailed(state, event))
-  if (event.type === "error") return Effect.succeed(onError(state, event))
+  if (event.type === "response.failed") return providerError(event, "OpenAI Responses response failed")
+  if (event.type === "error") return providerError(event, "OpenAI Responses stream error")
   return Effect.succeed<StepResult>([state, NO_EVENTS])
 }
 
@@ -968,10 +1079,12 @@ export const httpTransport = HttpTransport.sseJson.with<OpenAIResponsesBody>()
 export const route = Route.make({
   id: ADAPTER,
   provider: "openai",
+  providerMetadataKey: "openai",
   protocol,
   endpoint,
   auth,
   transport: httpTransport,
+  defaults: { providerOptions: { openai: { store: false } } },
 })
 
 const decodeWebSocketMessage = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIResponsesWebSocketMessage))
@@ -995,10 +1108,12 @@ export const webSocketTransport = WebSocketTransport.jsonTransport.with<
 export const webSocketRoute = Route.make({
   id: `${ADAPTER}-websocket`,
   provider: "openai",
+  providerMetadataKey: "openai",
   protocol,
   endpoint,
   auth,
   transport: webSocketTransport,
+  defaults: { providerOptions: { openai: { store: false } } },
 })
 
 export * as OpenAIResponses from "./openai-responses"

packages/ai/src/protocols/shared.ts

@@ -0,0 +1,327 @@
+import { Buffer } from "node:buffer"
+import { Effect, Schema, Stream } from "effect"
+import * as Sse from "effect/unstable/encoding/Sse"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import {
+  InvalidProviderOutputReason,
+  InvalidRequestReason,
+  LLMError,
+  type ContentPart,
+  type LLMRequest,
+  type MediaPart,
+  type ToolFileContent,
+  type TextPart,
+  type ToolResultPart,
+} from "../schema"
+import { isRecord } from "../utils/record"
+export { isRecord }
+
+export const Json = Schema.fromJsonString(Schema.Unknown)
+export const decodeJson = Schema.decodeUnknownSync(Json)
+export const encodeJson = Schema.encodeSync(Json)
+const isJson = Schema.is(Schema.Json)
+export const JsonObject = Schema.Record(Schema.String, Schema.Unknown)
+export const optionalArray = <const S extends Schema.Top>(schema: S) => Schema.optional(Schema.Array(schema))
+export const optionalNull = <const S extends Schema.Top>(schema: S) => Schema.optional(Schema.NullOr(schema))
+
+/**
+ * Streaming tool-call accumulator. Adapters that build a tool call across
+ * multiple `tool-input-delta` chunks store the partial JSON input string here
+ * and finalize it with `parseToolInput` once the call completes.
+ */
+export interface ToolAccumulator {
+  readonly id: string
+  readonly name: string
+  readonly input: string
+}
+
+/**
+ * `Usage.totalTokens` policy shared by every route. Honors a provider-
+ * supplied total; otherwise falls back to `inputTokens + outputTokens` only
+ * when at least one is defined. Returns `undefined` when neither input nor
+ * output is known so routes don't publish a misleading `0`.
+ *
+ * Under the additive `LLM.Usage` contract, `inputTokens` and `outputTokens`
+ * are the non-cached input and visible output only. The provider-supplied
+ * `total` is the source of truth when present; the computed fallback
+ * under-counts cache and reasoning by design and exists mainly so
+ * Anthropic-style providers (which don't surface a total) still get a
+ * sensible aggregate on the input + output axes.
+ */
+export const totalTokens = (
+  inputTokens: number | undefined,
+  outputTokens: number | undefined,
+  total: number | undefined,
+) => {
+  if (total !== undefined) return total
+  if (inputTokens === undefined && outputTokens === undefined) return undefined
+  return (inputTokens ?? 0) + (outputTokens ?? 0)
+}
+
+/**
+ * Subtract `subtrahend` from `total`, clamping to zero if the provider
+ * reports a non-sensical breakdown (e.g. `cached_tokens > prompt_tokens`).
+ * Used by protocol mappers when deriving a non-overlapping breakdown field
+ * from a provider's inclusive total — `nonCachedInputTokens` from
+ * `inputTokens - cacheReadInputTokens - cacheWriteInputTokens`.
+ *
+ * If `total` is `undefined`, returns `undefined` (we don't fabricate
+ * counts). If `subtrahend` is `undefined`, returns `total` unchanged. The
+ * provider-native breakdown stays available on `Usage.native` for debugging.
+ */
+export const subtractTokens = (total: number | undefined, subtrahend: number | undefined): number | undefined => {
+  if (total === undefined) return undefined
+  if (subtrahend === undefined) return total
+  return Math.max(0, total - subtrahend)
+}
+
+/**
+ * Sum a list of optional token counts, returning `undefined` only when
+ * every value is `undefined` (so we don't fabricate a `0`). Used by
+ * protocol mappers to derive the inclusive `inputTokens` total from a
+ * provider that natively reports a non-overlapping breakdown
+ * (e.g. Anthropic, whose `input_tokens` is already non-cached only).
+ */
+export const sumTokens = (...values: ReadonlyArray<number | undefined>): number | undefined => {
+  if (values.every((value) => value === undefined)) return undefined
+  return values.reduce((acc: number, value) => acc + (value ?? 0), 0)
+}
+
+export const eventError = (route: string, message: string, raw?: string) =>
+  new LLMError({
+    module: "ProviderShared",
+    method: "stream",
+    reason: new InvalidProviderOutputReason({ route, message, raw }),
+  })
+
+export const parseJson = (route: string, input: string, message: string) =>
+  Effect.try({
+    try: () => decodeJson(input),
+    catch: () => eventError(route, message, input),
+  })
+
+/**
+ * Join the `text` field of a list of parts with newlines. Used by routes
+ * that flatten system / message content arrays into a single provider string
+ * (OpenAI Chat `system` content, OpenAI Responses `system` content, Gemini
+ * `systemInstruction.parts[].text`).
+ */
+export const joinText = (parts: ReadonlyArray<{ readonly text: string }>) => parts.map((part) => part.text).join("\n")
+
+const escapeSystemUpdateText = (text: string) =>
+  text.replaceAll("&", "&amp;").replaceAll("<", "&lt;").replaceAll(">", "&gt;")
+
+/**
+ * Stable fallback representation for chronological `Message.system(...)`
+ * updates on routes that do not support that privileged role natively. The
+ * wrapper remains visibly lower-authority user text, preserves the original
+ * temporal position, and XML-escapes content so it cannot close the wrapper.
+ */
+export const wrapSystemUpdate = (parts: ReadonlyArray<{ readonly text: string }>) =>
+  `<system-update>\n${escapeSystemUpdateText(joinText(parts))}\n</system-update>`
+
+/**
+ * Chronological system updates deliberately accept text only. Do not insert
+ * raw retrieved, tool, or web content into privileged updates: keep untrusted
+ * data in ordinary user/tool messages instead.
+ */
+export const systemUpdateText = Effect.fn("ProviderShared.systemUpdateText")(function* (
+  route: string,
+  message: LLMRequest["messages"][number],
+) {
+  const content: TextPart[] = []
+  for (const part of message.content) {
+    if (!supportsContent(part, ["text"])) return yield* unsupportedContent(route, "system", ["text"])
+    content.push(part)
+  }
+  return content
+})
+
+/** Lower an unsupported privileged update into visible, in-order user text. */
+export const wrappedSystemUpdate = Effect.fn("ProviderShared.wrappedSystemUpdate")(function* (
+  route: string,
+  message: LLMRequest["messages"][number],
+) {
+  const content = yield* systemUpdateText(route, message)
+  return { type: "text" as const, text: wrapSystemUpdate(content), cache: content.at(-1)?.cache }
+})
+
+/**
+ * Parse the streamed JSON input of a tool call. Treats an empty string as
+ * `"{}"` — providers occasionally finish a tool call without ever emitting
+ * input deltas (e.g. zero-arg tools). The error message is uniform across
+ * routes: `Invalid JSON input for <route> tool call <name>`.
+ */
+export const parseToolInput = (route: string, name: string, raw: string) =>
+  parseJson(route, raw || "{}", `Invalid JSON input for ${route} tool call ${name}`)
+
+export const IMAGE_MIMES = ["image/png", "image/jpeg", "image/gif", "image/webp"] as const
+export const VIDEO_MIMES = ["video/mp4", "video/webm", "video/quicktime"] as const
+export const AUDIO_MIMES = ["audio/wav", "audio/mp3", "audio/aiff", "audio/aac", "audio/ogg", "audio/flac"] as const
+export const PDF_MIMES = ["application/pdf"] as const
+export const MEDIA_MIMES = [...IMAGE_MIMES, ...VIDEO_MIMES, ...AUDIO_MIMES, ...PDF_MIMES] as const
+export const MAX_MEDIA_ENCODED_BYTES = 28 * 1024 * 1024
+export const MAX_MEDIA_DECODED_BYTES = 20 * 1024 * 1024
+
+const base64Pattern = /^(?:[A-Za-z0-9+/]{4})*(?:[A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)?$/
+
+export interface ValidatedMedia {
+  readonly mime: string
+  readonly base64: string
+  readonly dataUrl: string
+  readonly bytes: Uint8Array
+}
+
+export const validateMedia = Effect.fn("ProviderShared.validateMedia")(function* (
+  route: string,
+  part: MediaPart,
+  supportedMimes: ReadonlySet<string>,
+) {
+  const mime = part.mediaType.toLowerCase()
+  if (!supportedMimes.has(mime)) return yield* invalidRequest(`${route} does not support media type ${part.mediaType}`)
+
+  let base64: string
+  if (typeof part.data !== "string") {
+    if (part.data.byteLength > MAX_MEDIA_DECODED_BYTES)
+      return yield* invalidRequest(`${route} media exceeds the ${MAX_MEDIA_DECODED_BYTES} byte decoded limit`)
+    base64 = Buffer.from(part.data).toString("base64")
+  } else if (part.data.startsWith("data:")) {
+    const match = /^data:([^;,]+);base64,([A-Za-z0-9+/]*={0,2})$/s.exec(part.data)
+    if (!match) return yield* invalidRequest(`${route} media data URL must contain valid base64`)
+    if (match[1]!.toLowerCase() !== mime)
+      return yield* invalidRequest(`${route} media type ${part.mediaType} does not match data URL type ${match[1]}`)
+    base64 = match[2]!
+  } else {
+    base64 = part.data
+  }
+
+  if (Buffer.byteLength(base64, "utf8") > MAX_MEDIA_ENCODED_BYTES)
+    return yield* invalidRequest(`${route} media exceeds the ${MAX_MEDIA_ENCODED_BYTES} byte encoded limit`)
+  if (!base64 || base64.length % 4 !== 0 || !base64Pattern.test(base64))
+    return yield* invalidRequest(`${route} media must contain valid base64`)
+  const bytes = Buffer.from(base64, "base64")
+  if (bytes.byteLength > MAX_MEDIA_DECODED_BYTES)
+    return yield* invalidRequest(`${route} media exceeds the ${MAX_MEDIA_DECODED_BYTES} byte decoded limit`)
+  if (bytes.toString("base64") !== base64) return yield* invalidRequest(`${route} media must contain canonical base64`)
+  return { mime, base64, dataUrl: `data:${mime};base64,${base64}`, bytes } satisfies ValidatedMedia
+})
+
+export const validateToolFile = (route: string, part: ToolFileContent, supportedMimes: ReadonlySet<string>) =>
+  validateMedia(route, { type: "media", mediaType: part.mime, data: part.uri, filename: part.name }, supportedMimes)
+
+export const trimBaseUrl = (value: string) => value.replace(/\/+$/, "")
+
+export const toolResultText = (part: ToolResultPart) => {
+  if (part.result.type === "text") return String(part.result.value)
+  if (part.result.type === "error") {
+    const value = part.result.value
+    const prototype =
+      typeof value === "object" && value !== null && !Array.isArray(value) && Object.getPrototypeOf(value)
+    const structured = Array.isArray(value) || prototype === Object.prototype || prototype === null
+    return structured && isJson(value) ? encodeJson(value) : String(value)
+  }
+  return encodeJson(part.result.value)
+}
+
+export const errorText = (error: unknown) => {
+  if (error instanceof Error) return error.message
+  if (typeof error === "string") return error
+  if (typeof error === "number" || typeof error === "boolean" || typeof error === "bigint") return String(error)
+  if (error === null) return "null"
+  if (error === undefined) return "undefined"
+  return "Unknown stream error"
+}
+
+/**
+ * `framing` step for Server-Sent Events. Decodes UTF-8, runs the SSE channel
+ * decoder, and drops empty / `[DONE]` keep-alive events so the downstream
+ * `decodeChunk` sees one JSON string per element. The SSE channel emits a
+ * `Retry` control event on its error channel; we drop it here (we don't
+ * implement client-driven retries) so the public error channel stays
+ * `LLMError`.
+ */
+export const sseFraming = (bytes: Stream.Stream<Uint8Array, LLMError>): Stream.Stream<string, LLMError> =>
+  bytes.pipe(
+    Stream.decodeText(),
+    Stream.pipeThroughChannel(Sse.decode()),
+    Stream.catchTag("Retry", () => Stream.empty),
+    Stream.filter((event) => event.data.length > 0 && event.data !== "[DONE]"),
+    Stream.map((event) => event.data),
+  )
+
+/**
+ * Canonical invalid-request constructor. Lift one-line `const invalid =
+ * (message) => invalidRequest(message)` aliases out of every
+ * route so the error constructor lives in one place. If we ever extend
+ * `InvalidRequestReason` with route context or trace metadata, the change
+ * lands here.
+ */
+export const invalidRequest = (message: string) =>
+  new LLMError({
+    module: "ProviderShared",
+    method: "request",
+    reason: new InvalidRequestReason({ message }),
+  })
+
+export const matchToolChoice = <Auto, None, Required, Tool>(
+  route: string,
+  toolChoice: NonNullable<LLMRequest["toolChoice"]>,
+  cases: {
+    readonly auto: () => Auto
+    readonly none: () => None
+    readonly required: () => Required
+    readonly tool: (name: string) => Tool
+  },
+) =>
+  Effect.gen(function* () {
+    if (toolChoice.type === "auto") return cases.auto()
+    if (toolChoice.type === "none") return cases.none()
+    if (toolChoice.type === "required") return cases.required()
+    if (!toolChoice.name) return yield* invalidRequest(`${route} tool choice requires a tool name`)
+    return cases.tool(toolChoice.name)
+  })
+
+type ContentType = ContentPart["type"]
+
+const formatContentTypes = (types: ReadonlyArray<ContentType>) => {
+  if (types.length <= 1) return types[0] ?? ""
+  if (types.length === 2) return `${types[0]} and ${types[1]}`
+  return `${types.slice(0, -1).join(", ")}, and ${types.at(-1)}`
+}
+
+export const supportsContent = <const Type extends ContentType>(
+  part: ContentPart,
+  types: ReadonlyArray<Type>,
+): part is Extract<ContentPart, { readonly type: Type }> => (types as ReadonlyArray<ContentType>).includes(part.type)
+
+export const unsupportedContent = (
+  route: string,
+  role: LLMRequest["messages"][number]["role"],
+  types: ReadonlyArray<ContentType>,
+) => invalidRequest(`${route} ${role} messages only support ${formatContentTypes(types)} content for now`)
+
+/**
+ * Build a `validate` step from a Schema decoder. Replaces the per-route
+ * lambda body `(payload) => decode(payload).pipe(Effect.mapError((e) =>
+ * invalid(e.message)))`. Any decode error is translated into
+ * `LLMError` carrying the original parse-error message.
+ */
+export const validateWith =
+  <A, I, E extends { readonly message: string }>(decode: (input: I) => Effect.Effect<A, E>) =>
+  (payload: I) =>
+    decode(payload).pipe(Effect.mapError((error) => invalidRequest(error.message)))
+
+/**
+ * Build an HTTP POST with a JSON body. Sets `content-type: application/json`
+ * automatically after caller-supplied headers so routes cannot accidentally
+ * send JSON with a stale content type. The body is passed pre-encoded so
+ * routes can choose between
+ * `Schema.encodeSync(payload)` and `ProviderShared.encodeJson(payload)`.
+ */
+export const jsonPost = (input: { readonly url: string; readonly body: string; readonly headers?: Headers.Input }) =>
+  HttpClientRequest.post(input.url).pipe(
+    HttpClientRequest.setHeaders(Headers.set(Headers.fromInput(input.headers), "content-type", "application/json")),
+    HttpClientRequest.bodyText(input.body, "application/json"),
+  )
+
+export * as ProviderShared from "./shared"

packages/ai/src/protocols/utils/bedrock-media.ts

@@ -49,10 +49,10 @@ const DOCUMENT_FORMATS = {
   "text/markdown": "md",
 } as const satisfies Record<string, DocumentFormat>
 
-const documentBlock = (part: MediaPart, format: DocumentFormat, bytes: string): DocumentBlock => ({
+const documentBlock = (name: string, format: DocumentFormat, bytes: string): DocumentBlock => ({
   document: {
     format,
-    name: part.filename ?? `document.${format}`,
+    name,
     source: { bytes },
   },
 })
@@ -77,12 +77,14 @@ export const lower = Effect.fn("BedrockMedia.lower")(function* (part: MediaPart)
     return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support image media type ${part.mediaType}`)
   const documentFormat = DOCUMENT_FORMATS[mime as keyof typeof DOCUMENT_FORMATS]
   if (documentFormat) {
+    if (!part.filename)
+      return yield* ProviderShared.invalidRequest("Bedrock Converse document media requires a filename")
     const media = yield* ProviderShared.validateMedia(
       "Bedrock Converse",
       part,
       new Set<string>(Object.keys(DOCUMENT_FORMATS)),
     )
-    return documentBlock(part, documentFormat, media.base64)
+    return documentBlock(part.filename, documentFormat, media.base64)
   }
   return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.mediaType}`)
 })

packages/ai/src/protocols/utils/gemini-tool-schema.ts

@@ -1,4 +1,4 @@
-import { ProviderShared } from "../shared"
+import { isRecord } from "../../utils/record"
 
 // Gemini accepts a JSON Schema-like dialect for tool parameters, but rejects a
 // handful of common JSON Schema shapes. Keep this projection isolated so the
@@ -20,8 +20,6 @@ const SCHEMA_INTENT_KEYS = [
   "else",
 ]
 
-const isRecord = ProviderShared.isRecord
-
 const hasCombiner = (schema: unknown) =>
   isRecord(schema) && (Array.isArray(schema.anyOf) || Array.isArray(schema.oneOf) || Array.isArray(schema.allOf))
 

packages/ai/src/protocols/utils/image-input.ts

@@ -0,0 +1,34 @@
+import { Effect, Encoding } from "effect"
+import type { ImageInput } from "../../image"
+import { InvalidRequestReason, LLMError } from "../../schema"
+
+const invalid = (module: string, message: string) =>
+  new LLMError({
+    module,
+    method: "generate",
+    reason: new InvalidRequestReason({ message }),
+  })
+
+export const dataUrl = (input: Extract<ImageInput, { readonly type: "bytes" }>) =>
+  `data:${input.mediaType};base64,${Encoding.encodeBase64(input.data)}`
+
+export const decodeDataUrl = (
+  url: string,
+  module: string,
+): Effect.Effect<{ readonly mediaType: string; readonly data: Uint8Array } | undefined, LLMError> => {
+  if (!url.startsWith("data:")) return Effect.succeed(undefined)
+  const match = /^data:([^;,]+);base64,(.*)$/s.exec(url)
+  if (!match) return Effect.fail(invalid(module, "Image data URLs must contain a MIME type and base64 data"))
+  return Effect.fromResult(Encoding.decodeBase64(match[2])).pipe(
+    Effect.mapError(() => invalid(module, "Image data URL contains invalid base64 data")),
+    Effect.map((data) => ({ mediaType: match[1], data })),
+  )
+}
+
+export const invalidImageInput = invalid
+
+export const ImageInputs = {
+  dataUrl,
+  decodeDataUrl,
+  invalid: invalidImageInput,
+} as const

packages/ai/src/protocols/utils/lifecycle.ts

@@ -0,0 +1,102 @@
+import { LLMEvent, type FinishReason, type ProviderMetadata, type Usage } from "../../schema"
+
+export interface State {
+  readonly stepStarted: boolean
+  readonly text: ReadonlySet<string>
+  readonly reasoning: ReadonlySet<string>
+}
+
+export const initial = (): State => ({ stepStarted: false, text: new Set(), reasoning: new Set() })
+
+export const stepStart = (state: State, events: LLMEvent[]): State => {
+  if (state.stepStarted) return state
+  events.push(LLMEvent.stepStart({ index: 0 }))
+  return { ...state, stepStarted: true }
+}
+
+export const textDelta = (state: State, events: LLMEvent[], id: string, text: string): State => {
+  const stepped = stepStart(state, events)
+  if (stepped.text.has(id)) {
+    events.push(LLMEvent.textDelta({ id, text }))
+    return stepped
+  }
+  events.push(LLMEvent.textStart({ id }), LLMEvent.textDelta({ id, text }))
+  return { ...stepped, text: new Set([...stepped.text, id]) }
+}
+
+export const reasoningStart = (
+  state: State,
+  events: LLMEvent[],
+  id: string,
+  providerMetadata?: ProviderMetadata,
+): State => {
+  if (state.reasoning.has(id)) return state
+  const stepped = stepStart(state, events)
+  events.push(LLMEvent.reasoningStart({ id, providerMetadata }))
+  return { ...stepped, reasoning: new Set([...stepped.reasoning, id]) }
+}
+
+export const reasoningDelta = (
+  state: State,
+  events: LLMEvent[],
+  id: string,
+  text: string,
+  providerMetadata?: ProviderMetadata,
+): State => {
+  const started = reasoningStart(state, events, id, providerMetadata)
+  events.push(LLMEvent.reasoningDelta({ id, text, providerMetadata }))
+  return started
+}
+
+export const reasoningEnd = (
+  state: State,
+  events: LLMEvent[],
+  id: string,
+  providerMetadata?: ProviderMetadata,
+): State => {
+  if (!state.reasoning.has(id)) return state
+  const stepped = stepStart(state, events)
+  events.push(LLMEvent.reasoningEnd({ id, providerMetadata }))
+  const reasoning = new Set(stepped.reasoning)
+  reasoning.delete(id)
+  return { ...stepped, reasoning }
+}
+
+export const textEnd = (state: State, events: LLMEvent[], id: string, providerMetadata?: ProviderMetadata): State => {
+  if (!state.text.has(id)) return state
+  const stepped = stepStart(state, events)
+  events.push(LLMEvent.textEnd({ id, providerMetadata }))
+  const text = new Set(stepped.text)
+  text.delete(id)
+  return { ...stepped, text }
+}
+
+const closeOpenBlocks = (state: State, events: LLMEvent[]): State => {
+  for (const id of state.reasoning) events.push(LLMEvent.reasoningEnd({ id }))
+  for (const id of state.text) events.push(LLMEvent.textEnd({ id }))
+  return { ...state, text: new Set(), reasoning: new Set() }
+}
+
+export const finish = (
+  state: State,
+  events: LLMEvent[],
+  input: {
+    readonly reason: FinishReason
+    readonly usage?: Usage
+    readonly providerMetadata?: ProviderMetadata
+  },
+): State => {
+  const stepped = closeOpenBlocks(stepStart(state, events), events)
+  events.push(
+    LLMEvent.stepFinish({
+      index: 0,
+      reason: input.reason,
+      usage: input.usage,
+      providerMetadata: input.providerMetadata,
+    }),
+    LLMEvent.finish(input),
+  )
+  return { ...stepped, stepStarted: false }
+}
+
+export * as Lifecycle from "./lifecycle"

packages/ai/src/protocols/utils/openai-image.ts

@@ -0,0 +1,20 @@
+import { Schema } from "effect"
+
+const dimensions = (value: string) => {
+  const match = /^(\d+)x(\d+)$/.exec(value)
+  if (!match) return undefined
+  return { width: Number(match[1]), height: Number(match[2]) }
+}
+
+export const Size = Schema.String.check(
+  Schema.makeFilter((value) => {
+    if (value === "auto") return undefined
+    const parsed = dimensions(value)
+    if (!parsed) return "image size must be `auto` or `{width}x{height}`"
+    return parsed.width > 0 && parsed.height > 0 ? undefined : "image dimensions must be positive integers"
+  }),
+)
+
+export const OpenAIImage = {
+  Size,
+} as const

packages/ai/src/protocols/utils/openai-options.ts

@@ -1,11 +1,9 @@
 import { Schema } from "effect"
-import type { LLMRequest, ReasoningEffort, TextVerbosity as TextVerbosityValue } from "../../schema"
+import type { LLMRequest, TextVerbosity as TextVerbosityValue } from "../../schema"
 import { ReasoningEfforts, TextVerbosity } from "../../schema"
 
-export const OpenAIReasoningEfforts = ReasoningEfforts.filter(
-  (effort): effort is Exclude<ReasoningEffort, "max"> => effort !== "max",
-)
-export type OpenAIReasoningEffort = (typeof OpenAIReasoningEfforts)[number]
+export const OpenAIReasoningEfforts = ReasoningEfforts
+export type OpenAIReasoningEffort = string
 
 // Mirrors OpenAI's `ResponseIncludable` union from the official SDK. Keep this
 // in lockstep with `openai-node/src/resources/responses/responses.ts`.
@@ -23,22 +21,16 @@ export type OpenAIResponseIncludable = (typeof OpenAIResponseIncludables)[number
 export const OpenAIServiceTiers = ["auto", "default", "flex", "priority"] as const
 export type OpenAIServiceTier = (typeof OpenAIServiceTiers)[number]
 
-const REASONING_EFFORTS = new Set<string>(ReasoningEfforts)
-const OPENAI_REASONING_EFFORTS = new Set<string>(OpenAIReasoningEfforts)
 const TEXT_VERBOSITY = new Set<string>(["low", "medium", "high"])
 const INCLUDABLES = new Set<string>(OpenAIResponseIncludables)
 const SERVICE_TIERS = new Set<string>(OpenAIServiceTiers)
 
-export const OpenAIReasoningEffort = Schema.Literals(OpenAIReasoningEfforts)
+export const OpenAIReasoningEffort = Schema.String
 export const OpenAITextVerbosity = TextVerbosity
 export const OpenAIResponseIncludable = Schema.Literals(OpenAIResponseIncludables)
 export const OpenAIServiceTier = Schema.Literals(OpenAIServiceTiers)
 
-const isAnyReasoningEffort = (effort: unknown): effort is ReasoningEffort =>
-  typeof effort === "string" && REASONING_EFFORTS.has(effort)
-
-export const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort =>
-  typeof effort === "string" && OPENAI_REASONING_EFFORTS.has(effort)
+export const isReasoningEffort = (effort: unknown): effort is OpenAIReasoningEffort => typeof effort === "string"
 
 const isTextVerbosity = (value: unknown): value is TextVerbosityValue =>
   typeof value === "string" && TEXT_VERBOSITY.has(value)
@@ -50,9 +42,9 @@ export const store = (request: LLMRequest): boolean | undefined => {
   return typeof value === "boolean" ? value : undefined
 }
 
-export const reasoningEffort = (request: LLMRequest): ReasoningEffort | undefined => {
+export const reasoningEffort = (request: LLMRequest): string | undefined => {
   const value = options(request)?.reasoningEffort
-  return isAnyReasoningEffort(value) ? value : undefined
+  return typeof value === "string" ? value : undefined
 }
 
 export const reasoningSummary = (request: LLMRequest): "auto" | undefined =>

packages/ai/src/protocols/utils/tool-schema.ts

@@ -0,0 +1,86 @@
+import type { JsonSchema, ModelToolSchemaCompatibility } from "../../schema"
+import { isRecord } from "../../utils/record"
+import { GeminiToolSchema } from "./gemini-tool-schema"
+
+const removeNullSchemas = (value: unknown): unknown => {
+  if (Array.isArray(value)) return value.map(removeNullSchemas)
+  if (!isRecord(value)) return value
+  const fields = Object.fromEntries(
+    Object.entries(value)
+      .filter(([key]) => key !== "anyOf")
+      .map(([key, field]) => [key, removeNullSchemas(field)]),
+  )
+  if (!Array.isArray(value.anyOf)) return fields
+  const variants = value.anyOf.filter((variant) => !isRecord(variant) || variant.type !== "null").map(removeNullSchemas)
+  if (variants.length === 1 && isRecord(variants[0])) return { ...fields, ...variants[0] }
+  return { ...fields, anyOf: variants }
+}
+
+const tupleItemsSchema = (items: ReadonlyArray<unknown>) => {
+  const projected = items.map(moonshotNode)
+  if (projected.length === 0) return {}
+  if (projected.length === 1) return projected[0]
+  return { anyOf: projected }
+}
+
+const moonshotNode = (schema: unknown): unknown => {
+  if (Array.isArray(schema)) return schema.map(moonshotNode)
+  if (!isRecord(schema)) return schema
+  if (typeof schema.$ref === "string") return { $ref: schema.$ref }
+  return Object.fromEntries(
+    Object.entries(schema).flatMap(([key, value]) => {
+      if (key === "items" && Array.isArray(value)) return [[key, tupleItemsSchema(value)]]
+      if (key === "prefixItems") {
+        if ("items" in schema) return []
+        return [["items", tupleItemsSchema(Array.isArray(value) ? value : [])]]
+      }
+      if (key === "unevaluatedItems") return []
+      return [[key, moonshotNode(value)]]
+    }),
+  )
+}
+
+const moonshot = (schema: JsonSchema): JsonSchema => {
+  const projected = moonshotNode(schema)
+  return isRecord(projected) ? projected : {}
+}
+
+const openAI = (schema: JsonSchema): JsonSchema => {
+  const variants = Array.isArray(schema.anyOf) ? schema.anyOf.filter(isRecord) : []
+  const flattened =
+    variants.length === 0
+      ? { ...schema, type: "object" }
+      : {
+          ...Object.fromEntries(Object.entries(schema).filter(([key]) => key !== "anyOf")),
+          type: "object",
+          properties: variants.reduce(
+            (properties, variant) => ({ ...(isRecord(variant.properties) ? variant.properties : {}), ...properties }),
+            {},
+          ),
+          additionalProperties: false,
+        }
+  const normalized = removeNullSchemas(flattened)
+  return isRecord(normalized) ? normalized : { type: "object" }
+}
+
+const gemini = (schema: JsonSchema): JsonSchema => GeminiToolSchema.convert(schema) ?? {}
+
+const modelCompatibility = (
+  schema: JsonSchema,
+  compatibility: ModelToolSchemaCompatibility | undefined,
+): JsonSchema => {
+  if (compatibility === undefined) return schema
+  switch (compatibility) {
+    case "gemini":
+      return gemini(schema)
+    case "moonshot":
+      return moonshot(schema)
+  }
+}
+
+export const ToolSchemaProjection = {
+  gemini,
+  modelCompatibility,
+  moonshot,
+  openAI,
+} as const

packages/ai/src/protocols/utils/tool-stream.ts

@@ -1,5 +1,5 @@
 import { Effect } from "effect"
-import { LLMError, LLMEvent, type ProviderMetadata, type ToolCall } from "../../schema"
+import { LLMError, LLMEvent, type ProviderMetadata, type ToolCall, type ToolInputError } from "../../schema"
 import { eventError, parseToolInput, type ToolAccumulator } from "../shared"
 
 type StreamKey = string | number
@@ -53,6 +53,7 @@ const inputStart = (tool: PendingTool) =>
   LLMEvent.toolInputStart({
     id: tool.id,
     name: tool.name,
+    providerExecuted: tool.providerExecuted ? true : undefined,
     providerMetadata: tool.providerMetadata,
   })
 
@@ -63,19 +64,36 @@ const inputDelta = (tool: PendingTool, text: string) =>
     text,
   })
 
-const toolCall = (route: string, tool: PendingTool, inputOverride?: string) =>
-  parseToolInput(route, tool.name, inputOverride ?? tool.input).pipe(
-    Effect.map(
-      (input): ToolCall =>
-        LLMEvent.toolCall({
-          id: tool.id,
-          name: tool.name,
-          input,
-          providerExecuted: tool.providerExecuted ? true : undefined,
-          providerMetadata: tool.providerMetadata,
-        }),
+const toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {
+  const raw = inputOverride ?? tool.input
+  return parseToolInput(route, tool.name, raw).pipe(
+    Effect.map((input): ToolCall | ToolInputError =>
+      LLMEvent.toolCall({
+        id: tool.id,
+        name: tool.name,
+        input,
+        providerExecuted: tool.providerExecuted ? true : undefined,
+        providerMetadata: tool.providerMetadata,
+      }),
+    ),
+    Effect.catch((error) =>
+      tool.providerExecuted
+        ? Effect.fail(error)
+        : Effect.succeed(
+            LLMEvent.toolInputError({
+              id: tool.id,
+              name: tool.name,
+              raw,
+            }),
+          ),
     ),
   )
+}
+
+const finishEvents = (tool: PendingTool, event: ToolCall | ToolInputError): ReadonlyArray<LLMEvent> =>
+  event.type === "tool-input-error"
+    ? [event]
+    : [LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }), event]
 
 /** Store the updated tool and produce the optional public delta event. */
 const appendTool = <K extends StreamKey>(
@@ -122,8 +140,8 @@ export const appendOrStart = <K extends StreamKey>(
   missingToolMessage: string,
 ): AppendOutcome<K> | LLMError => {
   const current = tools[key]
-  const id = delta.id ?? current?.id
-  const name = delta.name ?? current?.name
+  const id = current?.id ?? delta.id
+  const name = current?.name ?? delta.name
   if (!id || !name) return eventError(route, missingToolMessage)
 
   const tool = {
@@ -158,8 +176,9 @@ export const appendExisting = <K extends StreamKey>(
 
 /**
  * Finalize one pending tool call: parse the accumulated raw JSON, remove it
- * from state, and return the optional public `tool-call` event. Missing keys are
- * a no-op because some providers emit stop events for non-tool content blocks.
+ * from state, and return either a call or a non-executable local input error.
+ * Missing keys are a no-op because some providers emit stop events for
+ * non-tool content blocks.
  */
 export const finish = <K extends StreamKey>(route: string, tools: State<K>, key: K) =>
   Effect.gen(function* () {
@@ -167,10 +186,7 @@ export const finish = <K extends StreamKey>(route: string, tools: State<K>, key:
     if (!tool) return { tools }
     return {
       tools: withoutTool(tools, key),
-      events: [
-        LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-        yield* toolCall(route, tool),
-      ],
+      events: finishEvents(tool, yield* toolCall(route, tool)),
     }
   })
 
@@ -185,17 +201,14 @@ export const finishWithInput = <K extends StreamKey>(route: string, tools: State
     if (!tool) return { tools }
     return {
       tools: withoutTool(tools, key),
-      events: [
-        LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-        yield* toolCall(route, tool, input),
-      ],
+      events: finishEvents(tool, yield* toolCall(route, tool, input)),
     }
   })
 
 /**
  * Finalize every pending tool call at once. OpenAI Chat has this shape: it does
- * not emit per-tool stop events, so all accumulated calls finish when the choice
- * receives a terminal `finish_reason`.
+ * not emit per-tool stop events, so all accumulated calls finish independently
+ * when the choice receives a terminal `finish_reason`.
  */
 export const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =>
   Effect.gen(function* () {
@@ -205,12 +218,7 @@ export const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =
     return {
       tools: empty<K>(),
       events: yield* Effect.forEach(pending, (tool) =>
-        toolCall(route, tool).pipe(
-          Effect.map((call) => [
-            LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-            call,
-          ]),
-        ),
+        toolCall(route, tool).pipe(Effect.map((event) => finishEvents(tool, event))),
       ).pipe(Effect.map((events) => events.flat())),
     }
   })

packages/ai/src/protocols/xai-images.ts

@@ -0,0 +1,202 @@
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image"
+import { Auth, type Definition as AuthDefinition } from "../route/auth"
+import {
+  InvalidProviderOutputReason,
+  LLMError,
+  Usage,
+  mergeHttpOptions,
+  mergeJsonRecords,
+  type HttpOptions,
+} from "../schema"
+import { ProviderShared, optionalNull } from "./shared"
+import { ImageInputs } from "./utils/image-input"
+
+const ADAPTER = "xai-images"
+export const DEFAULT_BASE_URL = "https://api.x.ai/v1"
+export const PATH = "/images/generations"
+export const EDIT_PATH = "/images/edits"
+
+export type XAIImageString<Known extends string> = Known | (string & {})
+
+export type XAIImageOptions = {
+  readonly n?: number
+  readonly aspectRatio?: XAIImageString<
+    | "1:1"
+    | "3:4"
+    | "4:3"
+    | "9:16"
+    | "16:9"
+    | "2:3"
+    | "3:2"
+    | "9:19.5"
+    | "19.5:9"
+    | "9:20"
+    | "20:9"
+    | "1:2"
+    | "2:1"
+    | "auto"
+  >
+  readonly aspect_ratio?: XAIImageString<
+    | "1:1"
+    | "3:4"
+    | "4:3"
+    | "9:16"
+    | "16:9"
+    | "2:3"
+    | "3:2"
+    | "9:19.5"
+    | "19.5:9"
+    | "9:20"
+    | "20:9"
+    | "1:2"
+    | "2:1"
+    | "auto"
+  >
+  readonly resolution?: XAIImageString<"1k" | "2k">
+  readonly responseFormat?: XAIImageString<"url" | "b64_json">
+  readonly response_format?: XAIImageString<"url" | "b64_json">
+} & Record<string, unknown>
+
+type XAIImageBody = Record<string, unknown> & {
+  readonly model: string
+  readonly prompt: string
+}
+
+const XAIImageResponse = Schema.Struct({
+  data: Schema.Array(
+    Schema.Struct({
+      b64_json: optionalNull(Schema.String),
+      url: optionalNull(Schema.String),
+      revised_prompt: optionalNull(Schema.String),
+      mime_type: optionalNull(Schema.String),
+    }),
+  ),
+  usage: Schema.optional(Schema.Unknown),
+})
+
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}
+
+const nativeOptions = (options: XAIImageOptions | undefined) => {
+  if (!options) return undefined
+  const { aspectRatio, responseFormat, ...native } = options
+  return {
+    aspect_ratio: aspectRatio,
+    response_format: responseFormat,
+    ...native,
+  }
+}
+
+const invalidOutput = (message: string) =>
+  new LLMError({
+    module: ADAPTER,
+    method: "generate",
+    reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),
+  })
+
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<XAIImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("XAIImages.generate")(function* (request: ImageRequestFor<XAIImageOptions>, execute) {
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const imageReferences = (request.images ?? []).map((image) => {
+        if (image.type === "bytes") return { url: ImageInputs.dataUrl(image), type: "image_url" as const }
+        if (image.type === "url") return { url: image.url, type: "image_url" as const }
+        if (image.type === "file-id") return { file_id: image.id }
+        return undefined
+      })
+      if (imageReferences.some((image) => image === undefined))
+        return yield* ImageInputs.invalid(ADAPTER, "xAI Images accepts image URLs, data URLs, bytes, and file IDs")
+      const requestBody = mergeJsonRecords(
+        {
+          model: request.model.id,
+          prompt: request.prompt,
+          image: imageReferences.length === 1 ? imageReferences[0] : undefined,
+          images: imageReferences.length > 1 ? imageReferences : undefined,
+        },
+        nativeOptions(request.options),
+        http?.body,
+      ) as XAIImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const url = applyQuery(
+        `${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${imageReferences.length === 0 ? PATH : EDIT_PATH}`,
+        http?.query,
+      )
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      const payload = yield* response.json.pipe(
+        Effect.mapError(() => invalidOutput("Failed to read the xAI Images response")),
+      )
+      const decoded = yield* Schema.decodeUnknownEffect(XAIImageResponse)(payload).pipe(
+        Effect.mapError(() => invalidOutput("xAI Images returned an invalid response")),
+      )
+      const images = yield* Effect.forEach(decoded.data, (item, index) => {
+        const mediaType = item.mime_type ?? "application/octet-stream"
+        if (item.b64_json)
+          return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
+            Effect.mapError(() => invalidOutput(`xAI Images result ${index} contains invalid base64 data`)),
+            Effect.map(
+              (data) =>
+                new GeneratedImage({
+                  mediaType,
+                  data,
+                  providerMetadata:
+                    item.revised_prompt === undefined || item.revised_prompt === null
+                      ? undefined
+                      : { xai: { revisedPrompt: item.revised_prompt } },
+                }),
+            ),
+          )
+        if (item.url)
+          return Effect.succeed(
+            new GeneratedImage({
+              mediaType,
+              data: item.url,
+              providerMetadata:
+                item.revised_prompt === undefined || item.revised_prompt === null
+                  ? undefined
+                  : { xai: { revisedPrompt: item.revised_prompt } },
+            }),
+          )
+        return Effect.fail(invalidOutput(`xAI Images result ${index} has neither image data nor a URL`))
+      })
+      if (images.length === 0) return yield* invalidOutput("xAI Images returned no images")
+      const usage = ProviderShared.isRecord(decoded.usage) ? decoded.usage : undefined
+      return new ImageResponse({
+        images,
+        usage: usage === undefined ? undefined : new Usage({ providerMetadata: { xai: usage } }),
+        providerMetadata: usage === undefined ? undefined : { xai: { usage } },
+      })
+    }),
+  }
+  return ImageModel.make<XAIImageOptions>({ id: input.id, provider: "xai", route, http: input.http })
+}
+
+export const XAIImages = {
+  model,
+} as const