ci: release OpenCode Browser with publish-browser-extension

cli/package.json is now the one release version: the store zip and the extension bundled in the npm helper are stamped with it. Bumped to 0.0.2 (0.0.1 is on npm and in the store draft). .github/workflows/publish-browser-extension.yml runs on a browser-extension-v<version> tag (checked against cli/package.json) or by hand: typecheck, build the helper and the store zip, smoke test the helper, upload the zip as an artifact, then publish opencode-browser-cli to npm with provenance (trusted publishing, or OPENCODE_BROWSER_NPM_TOKEN; skipped when the version exists) and attach the zip to a GitHub release. Manual runs only build unless `publish` is checked. Verified: actionlint (only the repo's custom runner label is unknown to it); locally, cli build + `bun run package` produced version 0.0.2 in both the zip (no key) and the bundled extension, the built helper ran, and `npm pack --dry-run` packs 0.0.2.
refactor: drop opencode browser from the CLI in favor of the npx helper
2026-10-05 15:06:16 +00:00 · 2026-10-03 19:25:25 -04:00 · 2026-10-03 19:25:25 -04:00 · 2026-10-03 19:19:23 -04:00 · 2026-10-03 16:23:08 -04:00 · 2026-10-03 16:23:08 -04:00
1104 changed files with 28369 additions and 35379 deletions
@@ -18,20 +18,9 @@ jobs:
    steps:
      - name: Checkout repository
        uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
-        with:
-          # A pull request checks out its merge into the current base; the first parent is that base.
-          fetch-depth: 2

      - name: Setup Bun
        uses: ./.github/actions/setup-bun

      - name: Run checks
        run: bun run check
-
-      # Every GUI package file (app, desktop, gui-extensions, ui, session-ui) a pull request adds or edits must be free of
-      # oxlint problems, warn-level rules (anti-slop) included. Other packages are not affected.
-      - name: Lint changed files
-        if: github.event_name == 'pull_request'
-        # Against the merge's first parent, so base-branch commits the pull request has not merged are not counted as its
-        # changes (the event's base SHA can predate them).
-        run: bun run lint:changed HEAD^1
@@ -2,9 +2,9 @@ name: nix-eval

 on:
  push:
-    branches: [dev, v2]
+    branches: [dev]
  pull_request:
-    branches: [dev, v2]
+    branches: [dev]
  workflow_dispatch:

 concurrency:
@@ -0,0 +1,105 @@
+name: publish-browser-extension
+
+# Releases OpenCode Browser (packages/browser-extension): publishes the opencode-browser-cli helper to npm and
+# attaches the Chrome Web Store zip to a GitHub release. The version is packages/browser-extension/cli/package.json;
+# push a matching tag (browser-extension-v<version>) or run it by hand to rebuild the artifacts.
+
+on:
+  workflow_dispatch:
+    inputs:
+      publish:
+        description: "Publish to npm and create the GitHub release (otherwise build only)"
+        type: boolean
+        default: false
+  push:
+    tags:
+      - "browser-extension-v*.*.*"
+
+concurrency: ${{ github.workflow }}-${{ github.ref }}
+
+permissions:
+  contents: write
+  # npm trusted publishing (OIDC) and provenance.
+  id-token: write
+
+jobs:
+  publish:
+    runs-on: blacksmith-4vcpu-ubuntu-2404
+    if: github.repository == 'anomalyco/opencode'
+    steps:
+      - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
+
+      - uses: ./.github/actions/setup-bun
+
+      - uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
+        with:
+          node-version: "24"
+          registry-url: "https://registry.npmjs.org"
+
+      - name: Read version
+        id: version
+        env:
+          REF_TYPE: ${{ github.ref_type }}
+          REF_NAME: ${{ github.ref_name }}
+        run: |
+          version=$(node -p "require('./packages/browser-extension/cli/package.json').version")
+          echo "version=$version" >> "$GITHUB_OUTPUT"
+          if [ "$REF_TYPE" = "tag" ] && [ "$REF_NAME" != "browser-extension-v$version" ]; then
+            echo "::error::Tag $REF_NAME does not match cli/package.json version $version"
+            exit 1
+          fi
+
+      - name: Typecheck
+        run: bun typecheck
+        working-directory: packages/browser-extension
+
+      - name: Build the helper and the store zip
+        run: |
+          bun run build
+          cd .. && bun run package
+        working-directory: packages/browser-extension/cli
+
+      - name: Smoke test the helper
+        run: node dist/cli.mjs | grep -q "npx opencode-browser-cli install"
+        working-directory: packages/browser-extension/cli
+
+      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        with:
+          name: opencode-browser-${{ steps.version.outputs.version }}
+          path: packages/browser-extension/release/opencode-browser-${{ steps.version.outputs.version }}.zip
+          if-no-files-found: error
+
+      # Trusted publishing needs npm 11.5.1 or newer.
+      - name: Update npm
+        if: github.ref_type == 'tag' || inputs.publish
+        run: npm install -g npm@^11.5.1
+
+      - name: Publish to npm
+        if: github.ref_type == 'tag' || inputs.publish
+        working-directory: packages/browser-extension/cli
+        env:
+          VERSION: ${{ steps.version.outputs.version }}
+          # Unset when the package uses npm trusted publishing for this workflow.
+          NODE_AUTH_TOKEN: ${{ secrets.OPENCODE_BROWSER_NPM_TOKEN }}
+        run: |
+          if npm view "opencode-browser-cli@$VERSION" version >/dev/null 2>&1; then
+            echo "opencode-browser-cli@$VERSION is already published"
+            exit 0
+          fi
+          # dist/ and extension/ are already built; skip prepublishOnly's rebuild.
+          npm publish --access public --provenance --ignore-scripts
+
+      - name: GitHub release
+        if: github.ref_type == 'tag' || inputs.publish
+        env:
+          GH_TOKEN: ${{ github.token }}
+          VERSION: ${{ steps.version.outputs.version }}
+        run: |
+          tag="browser-extension-v$VERSION"
+          zip="packages/browser-extension/release/opencode-browser-$VERSION.zip"
+          if gh release view "$tag" >/dev/null 2>&1; then
+            gh release upload "$tag" "$zip" --clobber
+          else
+            gh release create "$tag" "$zip" --target "$GITHUB_SHA" --title "OpenCode Browser $VERSION" --prerelease \
+              --notes "Helper: \`npx opencode-browser-cli@$VERSION install\`. Upload the zip in the Chrome Web Store dashboard."
+          fi
@@ -252,13 +252,6 @@ jobs:
          CI: true
        timeout-minutes: 15

-      - name: Run app component tests
-        if: ${{ !cancelled() && env.E2E_ENABLED == 'true' }}
-        run: bun --cwd packages/app test:components
-        env:
-          CI: true
-        timeout-minutes: 15
-
      - name: Upload Playwright artifacts
        if: always() && env.E2E_ENABLED == 'true'
        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
@@ -271,5 +264,3 @@ jobs:
            packages/app/e2e/playwright-report
            packages/session-ui/component-tests/test-results
            packages/session-ui/component-tests/playwright-report
-            packages/app/component-tests/test-results
-            packages/app/component-tests/playwright-report
@@ -63,60 +63,8 @@
        "anti-slop-effect/prefer-effect-match": "warn"
      }
    },
-    {
-      "files": ["packages/gui-extensions/src/*.ts", "packages/gui-extensions/src/*.tsx"],
-      "rules": {
-        "no-restricted-imports": [
-          "error",
-          {
-            "paths": [
-              {
-                "name": "solid-js",
-                "importNames": ["createEffect", "createRenderEffect", "createComputed"],
-                "message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
-              }
-            ]
-          }
-        ]
-      }
-    },
    {
      "files": ["packages/gui-extensions/src/*/**"],
-      "rules": {
-        "no-restricted-imports": [
-          "error",
-          {
-            "paths": [
-              {
-                "name": "solid-js",
-                "importNames": ["createEffect", "createRenderEffect", "createComputed"],
-                "message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
-              }
-            ],
-            "patterns": [
-              {
-                "regex": "^@opencode/(app|desktop)(/|$)",
-                "message": "GUI extensions never import the app or desktop packages. Use the SDK."
-              },
-              {
-                "regex": "^@/",
-                "message": "GUI extensions never import app internals. Use the SDK."
-              },
-              {
-                "group": ["../*/*", "!../*/contract", "!../sdk/*"],
-                "message": "Import another extension only through its contract.ts."
-              },
-              {
-                "regex": "\\.css$",
-                "message": "Import CSS with ?inline and contribute it with ctx.add(Style, css)."
-              }
-            ]
-          }
-        ]
-      }
-    },
-    {
-      "files": ["packages/gui-extensions/src/sdk/**"],
      "rules": {
        "no-restricted-imports": [
          "error",
@@ -33,7 +33,7 @@
    },
    "packages/ai": {
      "name": "@opencode/ai",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/credential-providers": "3.1057.0",
        "@opencode/schema": "workspace:*",
@@ -55,7 +55,7 @@
    },
    "packages/app": {
      "name": "@opencode/app",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@corvu/drawer": "catalog:",
        "@dnd-kit/abstract": "0.5.0",
@@ -110,9 +110,34 @@
        "vite-plugin-solid": "2.11.14",
      },
    },
+    "packages/browser-extension": {
+      "name": "@opencode/browser-extension",
+      "version": "2.0.22",
+      "dependencies": {
+        "@opencode/client": "workspace:*",
+        "@opencode/plugin-browser": "workspace:*",
+        "@opencode/session-ui": "workspace:*",
+        "@opencode/ui": "workspace:*",
+        "effect": "catalog:",
+        "solid-js": "catalog:",
+      },
+      "devDependencies": {
+        "@opencode/plugin": "workspace:*",
+        "@tailwindcss/vite": "4.3.3",
+        "@tsconfig/node22": "catalog:",
+        "@types/bun": "catalog:",
+        "@types/chrome": "0.3.4",
+        "@typescript/native-preview": "catalog:",
+        "devtools-protocol": "0.0.1687809",
+        "tailwindcss": "catalog:",
+        "typescript": "catalog:",
+        "vite": "8.2.2",
+        "vite-plugin-solid": "2.11.14",
+      },
+    },
    "packages/cli": {
      "name": "@opencode/cli",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "bin": {
        "opencode": "./bin/opencode.cjs",
        "opencode2": "./bin/opencode2.cjs",
@@ -122,7 +147,7 @@
        "@clack/core": "1.0.0-alpha.1",
        "@clack/prompts": "1.0.0-alpha.1",
        "@effect/platform-node": "catalog:",
-        "@opencode-ai/pty": "0.2.0",
+        "@opencode-ai/pty": "0.1.13",
        "@opencode/client": "workspace:*",
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -179,7 +204,7 @@
    },
    "packages/client": {
      "name": "@opencode/client",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/protocol": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -205,7 +230,7 @@
    },
    "packages/codemode": {
      "name": "@opencode/codemode",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "acorn": "8.15.0",
        "effect": "catalog:",
@@ -218,7 +243,7 @@
    },
    "packages/console/app": {
      "name": "@opencode/console-app",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@ibm/plex": "6.4.1",
@@ -254,7 +279,7 @@
    },
    "packages/console/core": {
      "name": "@opencode/console-core",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/client-sts": "3.782.0",
        "@jsx-email/render": "1.1.1",
@@ -281,7 +306,7 @@
    },
    "packages/console/function": {
      "name": "@opencode/console-function",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@openauthjs/openauth": "0.0.0-20250322224806",
        "@opencode/console-core": "workspace:*",
@@ -298,7 +323,7 @@
    },
    "packages/console/mail": {
      "name": "@opencode/console-mail",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@jsx-email/all": "2.2.3",
        "@jsx-email/cli": "1.4.3",
@@ -322,7 +347,7 @@
    },
    "packages/console/support": {
      "name": "@opencode/console-support",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@opencode/console-core": "workspace:*",
@@ -342,7 +367,7 @@
    },
    "packages/core": {
      "name": "@opencode/core",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@ai-sdk/cohere": "3.0.27",
        "@ai-sdk/gateway": "3.0.104",
@@ -355,7 +380,7 @@
        "@lydell/node-pty": "catalog:",
        "@modelcontextprotocol/client": "2.0.0",
        "@modelcontextprotocol/core": "2.0.0",
-        "@opencode-ai/pty": "0.2.0",
+        "@opencode-ai/pty": "0.1.13",
        "@opencode/ai": "workspace:*",
        "@opencode/codemode": "workspace:*",
        "@opencode/plugin": "workspace:*",
@@ -365,7 +390,7 @@
        "@parcel/watcher": "2.5.1",
        "@silvia-odwyer/photon-node": "0.3.4",
        "@standard-schema/spec": "catalog:",
-        "bun-pty": "0.4.9",
+        "bun-pty": "0.4.8",
        "diff": "catalog:",
        "drizzle-orm": "catalog:",
        "effect": "catalog:",
@@ -383,6 +408,7 @@
        "mime-types": "3.0.2",
        "tree-sitter-bash": "0.25.0",
        "tree-sitter-powershell": "0.25.10",
+        "venice-ai-sdk-provider": "2.1.1",
        "web-tree-sitter": "0.25.10",
        "which": "6.0.1",
        "zod": "catalog:",
@@ -410,7 +436,7 @@
    },
    "packages/desktop": {
      "name": "@opencode/desktop",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@zip.js/zip.js": "2.7.62",
        "electron-context-menu": "5.0.0",
@@ -455,7 +481,7 @@
    },
    "packages/enterprise": {
      "name": "@opencode/enterprise",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@hono/standard-validator": "catalog:",
        "@opencode-ai/sdk": "1.18.21",
@@ -492,7 +518,7 @@
    },
    "packages/function": {
      "name": "@opencode/function",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@octokit/auth-app": "8.0.1",
        "@octokit/rest": "catalog:",
@@ -508,7 +534,7 @@
    },
    "packages/gui-extensions": {
      "name": "@opencode/gui-extensions",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@dnd-kit/abstract": "0.5.0",
        "@dnd-kit/dom": "0.5.0",
@@ -553,7 +579,7 @@
    },
    "packages/http-recorder": {
      "name": "@opencode/http-recorder",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@effect/platform-node-shared": "4.0.0-rc.112",
      },
@@ -572,7 +598,7 @@
    },
    "packages/httpapi-codegen": {
      "name": "@opencode/httpapi-codegen",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "effect": "catalog:",
        "prettier": "3.6.2",
@@ -585,7 +611,7 @@
    },
    "packages/latex": {
      "name": "@opencode/latex",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -599,7 +625,7 @@
    },
    "packages/merman": {
      "name": "@opencode/merman",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -614,7 +640,7 @@
    },
    "packages/plugin": {
      "name": "@opencode/plugin",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@ai-sdk/provider": "3.0.8",
        "@opencode/ai": "workspace:*",
@@ -653,7 +679,7 @@
    },
    "packages/plugin-browser": {
      "name": "@opencode/plugin-browser",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -683,7 +709,7 @@
    },
    "packages/protocol": {
      "name": "@opencode/protocol",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/schema": "workspace:*",
        "effect": "catalog:",
@@ -698,7 +724,7 @@
    },
    "packages/schema": {
      "name": "@opencode/schema",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@standard-schema/spec": "catalog:",
        "effect": "catalog:",
@@ -722,7 +748,7 @@
    },
    "packages/sdk": {
      "name": "@opencode/sdk",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -743,7 +769,7 @@
    },
    "packages/server": {
      "name": "@opencode/server",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@effect/platform-node": "catalog:",
        "@effect/platform-node-shared": "catalog:",
@@ -765,7 +791,7 @@
    },
    "packages/session-ui": {
      "name": "@opencode/session-ui",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode/client": "workspace:*",
@@ -800,7 +826,7 @@
    },
    "packages/simulation": {
      "name": "@opencode/simulation",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/ai": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -820,7 +846,7 @@
    },
    "packages/stats/app": {
      "name": "@opencode/stats-app",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@ibm/plex": "6.4.1",
        "@kobalte/core": "catalog:",
@@ -854,7 +880,7 @@
    },
    "packages/stats/core": {
      "name": "@opencode/stats-core",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/client-athena": "3.933.0",
        "@planetscale/database": "1.19.0",
@@ -873,7 +899,7 @@
    },
    "packages/stats/server": {
      "name": "@opencode/stats-server",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/client-firehose": "3.933.0",
        "@effect/platform-node": "catalog:",
@@ -919,7 +945,7 @@
    },
    "packages/theme": {
      "name": "@opencode/theme",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opentui/core": "catalog:",
        "effect": "catalog:",
@@ -933,7 +959,7 @@
    },
    "packages/tui": {
      "name": "@opencode/tui",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -967,7 +993,7 @@
    },
    "packages/ui": {
      "name": "@opencode/ui",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@pierre/diffs": "catalog:",
@@ -1002,7 +1028,7 @@
    },
    "packages/util": {
      "name": "@opencode/util",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@effect/opentelemetry": "catalog:",
        "@effect/platform-node": "catalog:",
@@ -1040,7 +1066,7 @@
    },
    "packages/web": {
      "name": "@opencode/web",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@astrojs/cloudflare": "12.6.3",
        "@astrojs/markdown-remark": "6.3.1",
@@ -1081,7 +1107,7 @@
    },
    "services/update": {
      "name": "@opencode/update",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "jose": "6.0.11",
        "semver": "catalog:",
@@ -2166,19 +2192,19 @@

    "@opencode-ai/protocol": ["@opencode-ai/protocol@0.0.0-beta-18050", "", { "dependencies": { "@opencode-ai/schema": "0.0.0-beta-18050", "effect": "4.0.0-rc.111" } }, "sha512-HDQMnvGp8IU0MdBRbEuydX1WQm09BZ4HJm9iSMQwzweJuQ2HNscgzHJPIH6P02BsbbtfJ8J7sZGPItrz1tWSgw=="],

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@@ -2188,6 +2214,8 @@

    "@opencode/app": ["@opencode/app@workspace:packages/app"],

+    "@opencode/browser-extension": ["@opencode/browser-extension@workspace:packages/browser-extension"],
+
    "@opencode/cli": ["@opencode/cli@workspace:packages/cli"],

    "@opencode/client": ["@opencode/client@workspace:packages/client"],
@@ -3110,6 +3138,8 @@

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@@ -3182,12 +3212,18 @@

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@@ -3326,6 +3362,8 @@

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+    "@workflow/serde": ["@workflow/serde@4.1.0", "", {}, "sha512-pav4F2BoirECWR7Nf1TKt+2eETcBj7jj4cBefQ8VXQCA6NPkaKeLfj/zMgi+3zYV5ZIBT4GuUiphsj0/b9hPQQ=="],
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@@ -3366,6 +3404,8 @@

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@@ -3544,7 +3584,7 @@

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+    "bun-pty": ["bun-pty@0.4.8", "", {}, "sha512-rO70Mrbr13+jxHHHu2YBkk2pNqrJE5cJn29WE++PUr+GFA0hq/VgtQPZANJ8dJo6d7XImvBk37Innt8GM7O28w=="],

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@@ -5718,6 +5758,8 @@

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+    "venice-ai-sdk-provider": ["venice-ai-sdk-provider@2.1.1", "", { "dependencies": { "@ai-sdk/openai-compatible": "^2.0.51", "@ai-sdk/provider": "^3.0.10", "@ai-sdk/provider-utils": "^4.0.30" }, "peerDependencies": { "ai": "^6.0.90" } }, "sha512-w3OHkuzzKZ3r2TOxER6myBYzZJNoDqol+DUHu3NnfBN/GETnUVxecZJab0CHQQ8GZc0jjzpFymepjcLDPS4SQg=="],
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@@ -6214,6 +6256,8 @@

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+    "@opencode/browser-extension/tailwindcss": ["tailwindcss@4.1.11", "", {}, "sha512-2E9TBm6MDD/xKYe+dvJZAmg3yxIEDNRc0jwlNyDg/4Fil2QcSLjFKGVff0lAf1jjeaArlG/M75Ey/EYr/OJtBA=="],
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@@ -6386,6 +6430,12 @@

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@@ -6690,6 +6740,12 @@

    "unzipper/fs-extra": ["fs-extra@11.3.1", "", { "dependencies": { "graceful-fs": "^4.2.0", "jsonfile": "^6.0.1", "universalify": "^2.0.0" } }, "sha512-eXvGGwZ5CL17ZSwHWd3bbgk7UUpF6IFHtP57NYYakPvHOs8GDgDe5KJI36jIJzDkJ6eJjuzRA8eBQb6SkKue0g=="],

+    "venice-ai-sdk-provider/@ai-sdk/openai-compatible": ["@ai-sdk/openai-compatible@2.0.69", "", { "dependencies": { "@ai-sdk/provider": "3.0.15", "@ai-sdk/provider-utils": "4.0.46" }, "peerDependencies": { "zod": "^3.25.76 || ^4.1.8" } }, "sha512-C99M0T0SpRkcCClmJxbQkpSqGmxLfh3NhTsNF3aNaUQZZ7oXN5sPWi9LGs49X5Q/r9FWxBYeZARXs15xxtGIig=="],
+
+    "venice-ai-sdk-provider/@ai-sdk/provider": ["@ai-sdk/provider@3.0.14", "", { "dependencies": { "json-schema": "^0.4.0" } }, "sha512-5X1k57JBJ4H7H1QjX7CnJYAB1I19r/trVZTMcSms7/kLNZ8RaU4Nt2agcwZzv82Hfx6Q7/TOLU7agAKeFfc8cA=="],
+
+    "venice-ai-sdk-provider/@ai-sdk/provider-utils": ["@ai-sdk/provider-utils@4.0.40", "", { "dependencies": { "@ai-sdk/provider": "3.0.14", "@standard-schema/spec": "^1.1.0", "eventsource-parser": "^3.0.8" }, "peerDependencies": { "zod": "^3.25.76 || ^4.1.8" } }, "sha512-OL5IrpUm9Y8Dwy+w/vvFwPotS6m52O9W0op2oXgXdCROMJIBalBI0oro6OIBYkPxvm5Xg02GSkoQN25RlR0bnw=="],
+
    "vite-plugin-dynamic-import/acorn": ["acorn@8.18.0", "", { "bin": { "acorn": "bin/acorn" } }, "sha512-lGq+9yr1/GuAWaVYIHRjvvySG5/4VfKIvC8EWxStPdcDh/Ka7FG3twP6v4d5BkravUilhIAsG4Qj83t02LWUPQ=="],

    "vite-plugin-icons-spritesheet/chalk": ["chalk@5.6.2", "", {}, "sha512-7NzBL0rN6fMUW+f7A6Io4h40qQlG+xGmtMxfbnH/K7TAtt8JQWVQK+6g0UXKMeVJoyV5EkkNsErQ8pVD3bLHbA=="],
@@ -7238,6 +7294,8 @@

    "@vitest/expect/@vitest/utils/@vitest/pretty-format": ["@vitest/pretty-format@3.2.4", "", { "dependencies": { "tinyrainbow": "^2.0.0" } }, "sha512-IVNZik8IVRJRTr9fxlitMKeJeXFFFN0JaB9PHPGQ8NKQbGpfjlTx9zO4RefN8gp7eqjNy8nyK3NZmBzOPeIxtA=="],

+    "ai/@ai-sdk/provider-utils/undici": ["undici@7.29.0", "", {}, "sha512-IDxfleLmmbSskfWSUATiN1nfn2rDuvnMOqb5CWR92iIfojA0Ud+ulOAAEQ57LPr9rWmsreUyf5lwyao+7GNNVw=="],
+
    "ansi-align/string-width/emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],

    "ansi-align/string-width/strip-ansi": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
@@ -7536,6 +7594,10 @@

    "tw-to-css/tailwindcss/postcss": ["postcss@8.5.26", "", { "dependencies": { "nanoid": "^3.3.17", "picocolors": "^1.1.1", "source-map-js": "^1.2.1" } }, "sha512-u82N74LFzG8ca+dD8puPnplTXoGH4fTPpVGuIbt36G3qvNlkvfD0lEAZSxaly3KX8TS/L1A1gsCEmvKmBcVbkQ=="],

+    "venice-ai-sdk-provider/@ai-sdk/openai-compatible/@ai-sdk/provider": ["@ai-sdk/provider@3.0.15", "", { "dependencies": { "json-schema": "^0.4.0" } }, "sha512-XeZW1CcDF2GMbH4wejW6xBRI2QCOgnkVYUnxoeDadB1mf85riL2bMUeDoh+6gJ/r4mjNfzUPW8OjLjvwTP0u1Q=="],
+
+    "venice-ai-sdk-provider/@ai-sdk/openai-compatible/@ai-sdk/provider-utils": ["@ai-sdk/provider-utils@4.0.46", "", { "dependencies": { "@ai-sdk/provider": "3.0.15", "@standard-schema/spec": "^1.1.0", "eventsource-parser": "^3.0.8", "undici": "^6.28.0" }, "peerDependencies": { "zod": "^3.25.76 || ^4.1.8" } }, "sha512-tEtld97plCFiYevsJuOkGkeuhQndeMWFBVrJS4AjnbD5AqrNSXRCe0p+BZ3Cju/sxDeeZ9ym3q9YUV8fASA7aQ=="],
+
    "vitest/@vitest/expect/chai": ["chai@6.2.2", "", {}, "sha512-NUPRluOfOiTKBKvWPtSD4PhFvWCqOi0BGStNWs57X9js7XGTprSmFoz5F0tWhR4WPjNeR9jXqdC7/UpSJTnlRg=="],

    "vscode-languageserver/vscode-languageserver-protocol/vscode-jsonrpc": ["vscode-jsonrpc@8.2.0", "", {}, "sha512-C+r0eKJUIfiDIfwJhria30+TYWPtuHJXHtI7J0YlOmKAo7ogxP20T0zxB7HZQIFhIyvoBPwWskjxrvAtfjyZfA=="],
@@ -8414,6 +8476,8 @@

    "tw-to-css/tailwindcss/chokidar/readdirp": ["readdirp@3.6.0", "", { "dependencies": { "picomatch": "^2.2.1" } }, "sha512-hOS089on8RduqdbhvQ5Z37A0ESjsqz6qnRcffsMU3495FuTdqSm+7bhJ29JvIOsBDEEnan5DPu9t3To9VRlMzA=="],

+    "venice-ai-sdk-provider/@ai-sdk/openai-compatible/@ai-sdk/provider-utils/undici": ["undici@6.28.0", "", {}, "sha512-LIY910g9TI13YS95lrMFrs8Rm/u/irgHeTWoKCoteeJ04CUJ92eEfj0rVn+7VKMPBpUPiUoBKfhNyLI23EE/KA=="],
+
    "yargs/string-width/strip-ansi/ansi-regex": ["ansi-regex@5.0.1", "", {}, "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="],

    "@astrojs/cloudflare/@cloudflare/vite-plugin/miniflare/sharp/@img/sharp-darwin-arm64": ["@img/sharp-darwin-arm64@0.35.2", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.3.1" }, "os": "darwin", "cpu": "arm64" }, "sha512-eEieHsMksAW4IiO5NzauESRl2D2qz3J/kwUxUrSfV06A93eEaRfMpHXyUb1mAqrR7i8U9A0GRqE9pjn6u1Jjpg=="],
@@ -40,8 +40,6 @@ stdenv.mkDerivation (finalAttrs: {
    copyDesktopItems
  ]
  ++ lib.optionals stdenv.hostPlatform.isDarwin [
-    darwin.cctools
-    darwin.sigtool
    # Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
    darwin.autoSignDarwinBinariesHook
  ];
@@ -1,7 +1,7 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-4AqU8dPEwo0ukoyEX1SuDVzsXQ7G/fIPnxoL400zH4M=",
-    "aarch64-linux": "sha256-p75sJYtR8a4oVKb1+Dgp8Kl+1onSmUw5NRv95bbV1+E=",
-    "aarch64-darwin": "sha256-Psyvbw/lGulysQlhK/MqcHVIwx2aCDTr+Pfr+gRWsG4="
+    "x86_64-linux": "sha256-EEBz2IQ14YPShAzY13zpZ7btq/EuSw86pZ6nrizc9BI=",
+    "aarch64-linux": "sha256-X7om4U4OlKL4OddEMcyKL+1DCQXc9/f1xzzopE16Zmk=",
+    "aarch64-darwin": "sha256-3bejEuX3AGv4SR/16O8KjNSO2t9WDaWCHRbBXsJ6z8A="
  }
 }
@@ -2,7 +2,7 @@
  "$schema": "https://json.schemastore.org/package.json",
  "name": "opencode",
  "description": "AI-powered development tool",
-  "version": "2.0.23",
+  "version": "2.0.22",
  "private": true,
  "type": "module",
  "packageManager": "bun@1.4.2",
@@ -18,8 +18,7 @@
    "dev:www": "bun run --cwd services/www dev",
    "dev:storybook": "bun --cwd packages/storybook storybook",
    "bench:devex": "bun run --cwd packages/app test:bench:devex",
-    "lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml && bun script/sdk-docs.ts",
-    "lint:changed": "bun script/lint-changed.ts",
+    "lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml",
    "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",
    "lint:effect-simplifications": "ast-grep scan -c script/ast-grep/effect-simplifications/sgconfig.yml --off=unused-suppression packages",
    "test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
@@ -27,31 +27,6 @@ Run `LLM.stream(...)` instead of `generate` when you want incremental `LLMEvent`
 `LLM.request(...)`. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses,
 Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.

-### Google Interactions
-
-`Google.configure({ apiKey }).interactions(modelID)` selects the Interactions API; `.model(modelID)` still selects
-GenerateContent. The package entrypoint is `@opencode/ai/providers/google/interactions`.
-
-```ts
-const model = Google.configure({ apiKey }).interactions("gemini-3.8-flash")
-const response = yield* LLM.generate({
-  model,
-  prompt: "Say hello.",
-  providerOptions: { thinkingLevel: "low", thinkingSummaries: "auto", store: true },
-})
-```
-
-Interactions supports text output, streamed function calls, native tool results, thought signatures, and multimodal
-input. Full-history replay is the default (`store: false`); implicit caching works without retained interactions.
-For server-side continuation, set `store: true` on the predecessor, read `interactionId` from the final event's
-`providerMetadata.google`, and pass `previousInteractionId` on the next request with **only new messages**. Repeat
-the system instructions and tool declarations on each request. Set `store: true` on each response you intend to
-continue from. The package does not automatically select or persist continuation IDs.
-
-Raw usage is preserved in `usage.providerMetadata.google`. `inputTokens` follows Google's top-level accounting;
-`contextTokens` uses its full `raw_prompt_token` count when supplied. These can differ substantially with server-side
-continuation. Explicit caches, hosted tools, and generated media are not supported by this initial protocol.
-
 The same configured facade names image, video, speech, and transcription models. `Image.generate` resolves the
 provider's image route from the model and returns `Media.Asset`s with lazily decoded bytes:

@@ -106,41 +81,6 @@ for await (const event of ai.llm.stream(ai.llm.request(input))) {
 await ai.dispose()
 ```

-## Venice AI
-
-`Venice` provides native Chat Completions with streaming tools and reasoning. `model` and `chat`
-select the same API; credentials default to `VENICE_API_KEY`.
-
-```ts
-import { LLM } from "@opencode/ai"
-import { Venice } from "@opencode/ai/providers"
-import { Effect } from "effect"
-
-const program = Effect.gen(function* () {
-  const response = yield* LLM.generate({
-    model: Venice.configure({ apiKey: process.env.VENICE_API_KEY }).chat("qwen3-6-27b"),
-    prompt: "Explain this design.",
-    providerOptions: {
-      reasoningEffort: "high",
-      veniceParameters: { includeVeniceSystemPrompt: false },
-    },
-  })
-  console.log(response.text)
-})
-```
-
-Effort lowers to `reasoning.effort`; `reasoning.enabled` and `reasoning.summary` are also available.
-Supported effort levels and toggles depend on the selected model. Omitted controls preserve its defaults.
-Venice's added system prompt is disabled by default, matching the previous OpenCode Venice SDK behavior.
-
-Replay complete `response.message` values to retain signed/encrypted reasoning and Gemini thought
-signatures, including per-tool signatures. Venice's encrypted scalar trailers are excluded from visible
-reasoning but retained in provider metadata for replay. Cache affinity uses `promptCacheKey`, and cache-write
-usage reads Venice's `cache_creation_input_tokens` field.
-
-The native package entrypoint is `@opencode/ai/providers/venice`. Image generation, embeddings, Responses, and
-client-side E2EE are not implemented by this provider.
-
 ## Experimental evaluation

 Evaluation models compare shared state with typed choice, score, and boolean questions. The API is
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "2.0.23",
+  "version": "2.0.22",
  "name": "@opencode/ai",
  "type": "module",
  "license": "MIT",
@@ -42,7 +42,6 @@ const RESPECTS_INLINE_HINTS = new Set([
  "alibaba-messages",
  "anthropic-messages",
  "anthropic-compatible-messages",
-  "bedrock-mantle-messages",
  "cloudflare-ai-gateway-messages",
  "google-vertex-messages",
  "meta-messages",
@@ -1,7 +1,7 @@
 import { Effect, Schema } from "effect"
 import { Protocol } from "../route/protocol.js"
 import { OpenResponses } from "./open-responses.js"
-import { JsonObject, ProviderShared } from "./shared.js"
+import { JsonObject, optionalArray, ProviderShared } from "./shared.js"
 import { OpenResponsesOptions } from "./utils/open-responses-options.js"
 import { ResponsesHostedTools } from "./utils/responses-hosted-tools.js"

@@ -25,6 +25,8 @@ const WebExtractorItem = Schema.StructWithRest(
 )
 const Body = Schema.Struct({
  ...OpenResponses.coreFields,
+  input: Schema.Array(Schema.Union([OpenResponses.InputItem, WebExtractorItem])),
+  tools: optionalArray(Schema.Union([OpenResponses.Tool, NativeTool])),
  enable_thinking: Options.fields.enableThinking,
  previous_response_id: Options.fields.previousResponseId,
  conversation: Options.fields.conversation,
@@ -50,7 +52,7 @@ export const protocol = Protocol.make({
      const opts = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(req.providerOptions ?? {})
      const body = yield* OpenResponses.fromRequestWithAdapter(req, adapter)
      const choice = body.tool_choice
-      return {
+      return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))({
        ...body,
        enable_thinking: opts.enableThinking,
        previous_response_id: opts.previousResponseId,
@@ -60,7 +62,7 @@ export const protocol = Protocol.make({
          typeof choice === "object" && choice.type === "function"
            ? { type: "allowed_tools" as const, mode: "required" as const, tools: [choice] }
            : choice,
-      }
+      })
    }),
  },
  stream: {
@@ -584,7 +584,10 @@ const serverToolResultType = (name: string): AnthropicServerToolResultType | und
  return undefined
 }

-const lowerServerToolResult = Effect.fnUntraced(function* (part: ToolResultPart, providerMetadataKey: string) {
+const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult")(function* (
+  part: ToolResultPart,
+  providerMetadataKey: string,
+) {
  const wireType = serverToolResultType(part.name)
  if (!wireType)
    return yield* invalid(`Anthropic Messages does not know how to round-trip server tool result for ${part.name}`)
@@ -654,7 +657,10 @@ const citationsFromMetadata = (metadata: MediaPart["metadata"]): AnthropicDocume

 const isHttpUrl = (value: string) => /^https?:\/\//i.test(value.trim())

-const lowerMedia = Effect.fnUntraced(function* (part: MediaPart, breakpoints?: Cache.Breakpoints) {
+const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
+  part: MediaPart,
+  breakpoints?: Cache.Breakpoints,
+) {
  const mime = part.media.mediaType.toLowerCase()
  const cacheControlValue = breakpoints ? cacheControl(breakpoints, part.cache) : undefined
  const fileId = fileIdFromMetadata(part.metadata)
@@ -798,6 +804,9 @@ const requireThinkingSignature = (request: LLMRequest) => {
  return true
 }

+// Mid-conversation system messages became available with Opus 4.8 and version
+// 5 of the other supported Claude families. Treat later family versions as
+// compatible without assuming that every Anthropic Messages model is Claude.
 // Opus 4.8 and every Claude 5 model accept mid-conversation system messages; later versions inherit support.
 const supportsNativeSystemUpdates = (request: LLMRequest) => {
  const version = claudeVersion(String(request.model.id))
@@ -806,9 +815,25 @@ const supportsNativeSystemUpdates = (request: LLMRequest) => {
  return version.major >= 5
 }

-// Native system messages must follow a user turn (tool results count) or a paused server-tool turn.
-const acceptsNativeSystemAfter = (message: AnthropicMessage | undefined) =>
-  message?.role === "user" || (message?.role === "assistant" && message.content.at(-1)?.type === "server_tool_use")
+const endsInServerToolUse = (message: LLMRequest["messages"][number]) => {
+  const last = message.content.at(-1)
+  return message.role === "assistant" && last?.type === "tool-call" && last.providerExecuted === true
+}
+
+const canUseNativeSystemUpdate = (request: LLMRequest, index: number) => {
+  const previous = request.messages[index - 1]
+  const next = request.messages[index + 1]
+  // Vertex currently rejects/404s for a system message after local tool results,
+  // so fold it into the user tool-result turn across continuations and history.
+  if (request.model.route.id === "google-vertex-messages" && previous?.role === "tool") return false
+  return (
+    previous !== undefined &&
+    previous.role !== "system" &&
+    (previous.role === "user" || previous.role === "tool" || endsInServerToolUse(previous)) &&
+    next?.role !== "system" &&
+    (next === undefined || next.role === "assistant")
+  )
+}

 const splitsLocalToolResults = (messages: LLMRequest["messages"], index: number) => {
  const pending = new Set<string>()
@@ -822,7 +847,7 @@ const splitsLocalToolResults = (messages: LLMRequest["messages"], index: number)
  return pending.size > 0
 }

-const lowerNativeSystemUpdate = Effect.fnUntraced(function* (
+const lowerNativeSystemUpdate = Effect.fn("AnthropicMessages.lowerNativeSystemUpdate")(function* (
  message: LLMRequest["messages"][number],
  breakpoints: Cache.Breakpoints,
 ) {
@@ -837,34 +862,12 @@ const lowerNativeSystemUpdate = Effect.fnUntraced(function* (
  }
 })

-const lowerWrappedSystemUpdate = Effect.fnUntraced(function* (
-  message: LLMRequest["messages"][number],
+const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
+  request: LLMRequest,
  breakpoints: Cache.Breakpoints,
 ) {
-  const part = yield* ProviderShared.wrappedSystemUpdate("Anthropic Messages", message)
-  return { type: "text" as const, text: part.text, cache_control: cacheControl(breakpoints, part.cache) }
-})
-
-const appendToUserTurn = (messages: AnthropicMessage[], block: AnthropicUserBlock) => {
-  const last = messages.at(-1)
-  if (last?.role === "user") messages[messages.length - 1] = { role: "user", content: [...last.content, block] }
-  else messages.push({ role: "user", content: [block] })
-}
-
-const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoints: Cache.Breakpoints) {
  const messages: AnthropicMessage[] = []
  const providerMetadataKey = request.model.route.providerMetadataKey ?? String(request.model.provider)
-  // Text updates stay where they are unless a user turn follows them; then they move after the latest
-  // user turn, the nearest spot where Anthropic accepts a native system message.
-  const holdUpdates = supportsNativeSystemUpdates(request)
-  const held: Array<LLMRequest["messages"][number]> = []
-  const releaseHeld = Effect.fnUntraced(function* () {
-    const native = acceptsNativeSystemAfter(messages.findLast((message) => message.role !== "system"))
-    for (const update of held.splice(0)) {
-      if (native) messages.push(yield* lowerNativeSystemUpdate(update, breakpoints))
-      else appendToUserTurn(messages, yield* lowerWrappedSystemUpdate(update, breakpoints))
-    }
-  })

  for (const [index, message] of request.messages.entries()) {
    if (message.role === "system") {
@@ -876,8 +879,16 @@ const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoi
      }
      if (splitsLocalToolResults(request.messages, index))
        return yield* invalid("Anthropic Messages system updates cannot split a local tool call from its tool result")
-      if (holdUpdates) held.push(message)
-      else appendToUserTurn(messages, yield* lowerWrappedSystemUpdate(message, breakpoints))
+      if (supportsNativeSystemUpdates(request) && canUseNativeSystemUpdate(request, index)) {
+        messages.push(yield* lowerNativeSystemUpdate(message, breakpoints))
+        continue
+      }
+      const part = yield* ProviderShared.wrappedSystemUpdate("Anthropic Messages", message)
+      const block = { type: "text" as const, text: part.text, cache_control: cacheControl(breakpoints, part.cache) }
+      const previous = messages.at(-1)
+      if (previous?.role === "user")
+        messages[messages.length - 1] = { role: "user", content: [...previous.content, block] }
+      else messages.push({ role: "user", content: [block] })
      continue
    }

@@ -953,9 +964,7 @@ const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoi
          `Anthropic Messages assistant messages only support text, reasoning, and tool-call content for now`,
        )
      }
-      if (content.length === 0) continue
-      yield* releaseHeld()
-      messages.push({ role: "assistant", content })
+      if (content.length > 0) messages.push({ role: "assistant", content })
      continue
    }

@@ -976,14 +985,10 @@ const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoi
      messages[messages.length - 1] = { role: "user", content: [...previous.content, ...content] }
    else messages.push({ role: "user", content })
  }
-  yield* releaseHeld()

  return messages
 })

-// TODO: Move per-model capability heuristics (`supportsEffortUpdates`, `supportsNativeSystemUpdates`,
-// `supportsThinkingBlockBinding`) into explicit model/provider `compatibility` metadata so the protocol
-// only reads `request.model.compatibility`.
 // Per-turn effort started with Claude Opus 5 and every Claude 5.1 model; later versions of any family inherit it.
 const supportsEffortUpdates = (model: LLMRequest["model"]) => {
  const override = model.compatibility?.supportsEffortUpdates
@@ -1295,7 +1300,7 @@ const onContentBlockStart = (
  return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, [...events, result]]
 }

-const onContentBlockDelta = Effect.fnUntraced(function* (
+const onContentBlockDelta = Effect.fn("AnthropicMessages.onContentBlockDelta")(function* (
  state: ParserState,
  event: AnthropicEvent & { readonly delta: AnthropicStreamDelta },
 ) {
@@ -1363,7 +1368,7 @@ const onContentBlockDelta = Effect.fnUntraced(function* (
  return [state, NO_EVENTS] satisfies StepResult
 })

-const onContentBlockStop = Effect.fnUntraced(function* (
+const onContentBlockStop = Effect.fn("AnthropicMessages.onContentBlockStop")(function* (
  state: ParserState,
  event: AnthropicEvent,
 ) {
@@ -1434,7 +1439,7 @@ const onMessageDelta = (
  ]
 }

-const onMessageStop = Effect.fnUntraced(function* (state: ParserState) {
+const onMessageStop = Effect.fn("AnthropicMessages.onMessageStop")(function* (state: ParserState) {
  if (Object.keys(state.compactions).length)
    return yield* ProviderShared.eventError(ADAPTER, "Response ended with an incomplete compaction block")
  const result = yield* ToolStream.finishAll(ADAPTER, state.tools)
@@ -285,7 +285,7 @@ const lowerToolCall = (part: ToolCallPart, normalizeID: (id: string) => string):
  },
 })

-const lowerToolResultContent = Effect.fnUntraced(function* (
+const lowerToolResultContent = Effect.fn("BedrockConverse.lowerToolResultContent")(function* (
  part: ToolResultPart,
  documentNames: Set<string>,
 ) {
@@ -305,7 +305,7 @@ const lowerToolResultContent = Effect.fnUntraced(function* (
  return content
 })

-const lowerToolResult = Effect.fnUntraced(function* (
+const lowerToolResult = Effect.fn("BedrockConverse.lowerToolResult")(function* (
  part: ToolResultPart,
  documentNames: Set<string>,
  normalizeID: (id: string) => string,
@@ -322,7 +322,7 @@ const lowerToolResult = Effect.fnUntraced(function* (
 // Keep Claude and Nova tool-result images inline; put other models' images beside the result.
 const keepToolImagesInline = (id: string) => id.includes("anthropic.claude-") || id.includes("amazon.nova-")

-const lowerMessages = Effect.fnUntraced(function* (
+const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
  request: LLMRequest,
  breakpoints: BedrockCache.Breakpoints,
 ) {
@@ -75,7 +75,7 @@ const usesSse = (request: MediaProtocol.Addressed<Request>) => request.mode ===

 const CONTAINERS: Readonly<Record<string, "raw" | "wav" | "mp3">> = { pcm: "raw", wav: "wav", mp3: "mp3" }

-const outputFormat = Effect.fnUntraced(function* (request: MediaProtocol.Addressed<Request>) {
+const outputFormat = Effect.fn("CartesiaSpeech.outputFormat")(function* (request: MediaProtocol.Addressed<Request>) {
  const sse = usesSse(request)
  const format = request.format ?? (sse ? "pcm" : "mp3")
  const container = CONTAINERS[format]
@@ -121,7 +121,7 @@ const fromRequest = Effect.fn("CartesiaSpeech.fromRequest")(function* (request:
 // 6. Stream parsing
 // ---------------------------------------------------------------------------

-const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
+const onEvent = Effect.fn("CartesiaSpeech.onEvent")(function* (state: State, frame: string) {
  const event = yield* decodeEvent(frame)
  if (event.type === "chunk" && event.data !== undefined) return SpeechStream.delta(state, event.data)
  if (event.type === "timestamps" && event.word_timestamps !== undefined) {
@@ -140,7 +140,7 @@ const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
  return [state, []] as const
 })

-const finish = Effect.fnUntraced(function* (
+const finish = Effect.fn("CartesiaSpeech.finish")(function* (
  state: State,
  context: MediaProtocol.ResponseContext<Request>,
 ) {
@@ -124,15 +124,7 @@ const fromRequest = Effect.fn("CohereChat.fromRequest")(function* (request: LLMR
  const options = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(request.providerOptions ?? {})
  const flattened = ProviderShared.flattenToolRequest(request)
  const messages: (typeof Message.Type)[] = request.system.length
-    ? [
-        {
-          role: "system",
-          content:
-            request.system.length === 1
-              ? request.system[0].text
-              : request.system.map((part) => ({ type: "text", text: part.text })),
-        },
-      ]
+    ? [{ role: "system", content: ProviderShared.joinText(request.system) }]
    : []
  for (const message of flattened.request.messages) {
    if (message.role === "system") {
@@ -252,7 +244,7 @@ const mapUsage = (usage: typeof NativeUsage.Type) =>
  })

 // Lifecycle deltas open blocks on demand and ends are no-ops for closed blocks, so content-start needs no handling.
-const step = Effect.fnUntraced(function* (state: State, event: Event) {
+const step = Effect.fn("CohereChat.step")(function* (state: State, event: Event) {
  const events: LLMEvent[] = []
  switch (event.type) {
    case "message-start":
@@ -95,7 +95,7 @@ const OUTPUT_FORMATS: Readonly<Record<string, string>> = {
 }

 /** WAV is served only by the non-streaming endpoints. */
-const outputFormat = Effect.fnUntraced(function* (request: MediaProtocol.Addressed<Request>) {
+const outputFormat = Effect.fn("ElevenLabsSpeech.outputFormat")(function* (request: MediaProtocol.Addressed<Request>) {
  const format = request.providerOptions?.outputFormat ?? OUTPUT_FORMATS[request.format ?? "mp3"]
  if (format === undefined)
    return yield* route.unsupported(
@@ -138,7 +138,7 @@ const path = (request: MediaProtocol.Addressed<Request>) =>
 // 6. Stream parsing
 // ---------------------------------------------------------------------------

-const onRecord = Effect.fnUntraced(function* (state: State, frame: string) {
+const onRecord = Effect.fn("ElevenLabsSpeech.onRecord")(function* (state: State, frame: string) {
  const record = yield* decodeRecord(frame)
  const [next, events] = SpeechStream.delta(state, record.audio_base64)
  const alignment = record.alignment
@@ -169,7 +169,7 @@ const describeOutput = (format: string) => {
  return encoding === undefined ? SpeechStream.container(codec, sampleRate) : SpeechStream.pcm(encoding, sampleRate)
 }

-const finish = Effect.fnUntraced(function* (
+const finish = Effect.fn("ElevenLabsSpeech.finish")(function* (
  state: State,
  context: MediaProtocol.ResponseContext<Request>,
 ) {
@@ -283,7 +283,7 @@ const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
    tool: (name) => ({ functionCallingConfig: { mode: "ANY" as const, allowedFunctionNames: [name] } }),
  })

-const lowerContentPart = Effect.fnUntraced(function* (part: TextPart | MediaPart) {
+const lowerContentPart = Effect.fn("Gemini.lowerContentPart")(function* (part: TextPart | MediaPart) {
  if (part.type === "text") return { text: part.text }
  return yield* GeminiGenerateContent.mediaPart("Gemini", part.media)
 })
@@ -302,7 +302,7 @@ const lowerToolCall = (part: ToolCallPart, omitIds: boolean, metadataKey: string
  thoughtSignature: thoughtSignature(part.providerMetadata, metadataKey),
 })

-const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest) {
+const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMRequest) {
  const contents: GeminiContent[] = []
  const metadataKey = request.model.route.providerMetadataKey ?? String(request.model.provider)
  const omitCallIds = omitsFunctionCallIds(request.model.id)
@@ -475,7 +475,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
    safetySettings: options.safetySettings,
    serviceTier: options.serviceTier,
    systemInstruction:
-      request.system.length === 0 ? undefined : { parts: request.system.map((part) => ({ text: part.text })) },
+      request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
    tools: hasTools
      ? [
          {
@@ -1,561 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Route } from "../route/client.js"
-import { Auth } from "../route/auth.js"
-import { Endpoint } from "../route/endpoint.js"
-import { Framing } from "../route/framing.js"
-import { Protocol } from "../route/protocol.js"
-import {
-  AIError,
-  LLMEvent,
-  ProviderID,
-  Usage,
-  type LLMRequest,
-  type ProviderMetadata,
-  type ToolResultPart,
-} from "../schema/index.js"
-import { Media } from "../media.js"
-import { classifyProviderFailure, providerErrorMessage } from "../provider-error.js"
-import { encodeJson } from "../utils/json.js"
-import { JsonObject, knownString, lenient, optionalNull, ProviderShared } from "./shared.js"
-import { Lifecycle } from "./utils/lifecycle.js"
-import { MediaInput } from "./utils/media-input.js"
-import { ToolStream } from "./utils/tool-stream.js"
-
-const ADAPTER = "google-interactions"
-export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
-
-// =============================================================================
-// Public Model Input
-// =============================================================================
-const ThinkingLevel = knownString<"minimal" | "low" | "medium" | "high">()
-const Options = Schema.Struct({
-  previousInteractionId: lenient(Schema.String),
-  store: lenient(Schema.Boolean),
-  thinkingLevel: lenient(ThinkingLevel),
-  thinkingSummaries: lenient(knownString<"auto" | "none">()),
-  serviceTier: lenient(knownString<"standard" | "flex" | "priority">()),
-})
-export type OptionsInput = typeof Options.Encoded
-export type ProviderOptionsInput = OptionsInput
-const decodeOptions = ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))
-
-// =============================================================================
-// Request Body Schema
-// =============================================================================
-const Text = Schema.Struct({ type: Schema.Literal("text"), text: Schema.String })
-const MediaContent = Schema.Struct({
-  type: Schema.Literals(["image", "audio", "video", "document"]),
-  data: Schema.optional(Schema.String),
-  uri: Schema.optional(Schema.String),
-  mime_type: Schema.String,
-})
-const Content = Schema.Union([Text, MediaContent])
-const InputStep = Schema.Union([
-  Schema.Struct({ type: Schema.Literals(["user_input", "model_output"]), content: Schema.Array(Content) }),
-  Schema.Struct({
-    type: Schema.Literal("thought"),
-    signature: Schema.optional(Schema.String),
-    summary: Schema.optional(Schema.Array(Text)),
-  }),
-  Schema.Struct({
-    type: Schema.Literal("function_call"),
-    id: Schema.String,
-    name: Schema.String,
-    arguments: Schema.Unknown,
-    signature: Schema.optional(Schema.String),
-  }),
-  Schema.Struct({
-    type: Schema.Literal("function_result"),
-    call_id: Schema.String,
-    name: Schema.String,
-    result: Schema.Unknown,
-    is_error: Schema.optional(Schema.Boolean),
-  }),
-])
-type InputStep = typeof InputStep.Type
-const ToolChoice = Schema.Union([
-  Schema.Literals(["auto", "any", "none"]),
-  Schema.Struct({ allowed_tools: Schema.Struct({ mode: Schema.Literal("any"), tools: Schema.Array(Schema.String) }) }),
-])
-const Body = Schema.Struct({
-  model: Schema.String,
-  input: Schema.Array(InputStep),
-  stream: Schema.Literal(true),
-  store: Schema.Boolean,
-  previous_interaction_id: Schema.optional(Schema.String),
-  system_instruction: Schema.optional(Schema.String),
-  service_tier: Schema.optional(Schema.String),
-  tools: Schema.optional(
-    Schema.Array(
-      Schema.Struct({
-        type: Schema.Literal("function"),
-        name: Schema.String,
-        description: Schema.String,
-        parameters: JsonObject,
-      }),
-    ),
-  ),
-  generation_config: Schema.Struct({
-    max_output_tokens: Schema.optional(Schema.Number),
-    temperature: Schema.optional(Schema.Number),
-    top_p: Schema.optional(Schema.Number),
-    seed: Schema.optional(Schema.Number),
-    stop_sequences: Schema.optional(Schema.Array(Schema.String)),
-    thinking_level: Schema.optional(ThinkingLevel),
-    thinking_summaries: Schema.optional(Schema.String),
-    tool_choice: Schema.optional(ToolChoice),
-  }),
-})
-
-// =============================================================================
-// Streaming Event Schema
-// =============================================================================
-const RawUsage = Schema.StructWithRest(
-  Schema.Struct({
-    total_input_tokens: optionalNull(Schema.Number),
-    total_cached_tokens: optionalNull(Schema.Number),
-    total_output_tokens: optionalNull(Schema.Number),
-    total_thought_tokens: optionalNull(Schema.Number),
-    total_tokens: optionalNull(Schema.Number),
-    raw_prompt_token: optionalNull(Schema.Number),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-type RawUsage = typeof RawUsage.Type
-const OutputStep = Schema.Struct({
-  type: Schema.String,
-  id: Schema.optional(Schema.String),
-  name: Schema.optional(Schema.String),
-  arguments: Schema.optional(JsonObject),
-  signature: Schema.optional(Schema.String),
-  summary: Schema.optional(Schema.Array(Text)),
-  content: Schema.optional(Schema.Array(Schema.Struct({ type: Schema.String, text: Schema.optional(Schema.String) }))),
-})
-type OutputStep = typeof OutputStep.Type
-const Delta = Schema.Union([
-  Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("arguments_delta"), arguments: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("thought_signature"), signature: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("thought_summary"), content: Text }),
-  // Unknown output modalities must fail explicitly rather than disappearing from a successful response.
-  Schema.Struct({ type: Schema.String }),
-])
-const Interaction = Schema.StructWithRest(
-  Schema.Struct({
-    id: Schema.optional(Schema.String),
-    status: Schema.String,
-    usage: Schema.optional(RawUsage),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Event = Schema.Union([
-  Schema.Struct({ event_type: Schema.Literal("step.start"), index: Schema.Number, step: OutputStep }),
-  Schema.Struct({ event_type: Schema.Literal("step.delta"), index: Schema.Number, delta: Delta }),
-  Schema.Struct({ event_type: Schema.Literal("step.stop"), index: Schema.Number }),
-  Schema.Struct({
-    event_type: Schema.Literal("interaction.created"),
-    interaction: Schema.Struct({ id: Schema.optional(Schema.String) }),
-  }),
-  Schema.Struct({
-    event_type: Schema.Literal("interaction.status_update"),
-    interaction_id: Schema.optional(Schema.String),
-    status: Schema.String,
-  }),
-  Schema.Struct({ event_type: Schema.Literal("interaction.completed"), interaction: Interaction }),
-  Schema.Struct({ event_type: Schema.Literal("error"), error: Schema.Unknown }),
-])
-type Event = typeof Event.Type
-
-// =============================================================================
-// Parser State
-// =============================================================================
-interface ParserState {
-  readonly route: string
-  readonly metadataKey: string
-  readonly lifecycle: Lifecycle.State
-  readonly steps: Partial<Record<number, OutputStep>>
-  readonly tools: ToolStream.State<number>
-  readonly completed: boolean
-}
-type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
-
-// =============================================================================
-// Request Body Construction
-// =============================================================================
-const mediaContent = Effect.fnUntraced(function* (asset: Media.Asset) {
-  if (
-    asset.kind !== "image" &&
-    asset.kind !== "audio" &&
-    asset.kind !== "video" &&
-    asset.mediaType !== "application/pdf" &&
-    asset.mediaType !== "text/csv"
-  )
-    return yield* ProviderShared.invalidRequest(
-      `Google Interactions does not support ${asset.mediaType} document input`,
-    )
-  const type: (typeof MediaContent.Type)["type"] =
-    asset.kind === "image" || asset.kind === "audio" || asset.kind === "video" ? asset.kind : "document"
-  const uri = MediaInput.refID(asset, ProviderID.make("google"))
-  if (uri !== undefined) return { type, uri, mime_type: asset.mediaType }
-  const inline = yield* ProviderShared.requireInlineMedia("Google Interactions", asset)
-  return { type, data: inline.base64, mime_type: inline.mime }
-})
-
-const signature = (metadata: ProviderMetadata | undefined, key: string) => {
-  const value = metadata?.[key]
-  return ProviderShared.isRecord(value) && typeof value.interactionSignature === "string"
-    ? value.interactionSignature
-    : undefined
-}
-
-const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest) {
-  const steps: InputStep[] = []
-  const key = request.model.route.providerMetadataKey ?? String(request.model.provider)
-  for (const message of request.messages) {
-    if (message.role === "system") {
-      const part = yield* ProviderShared.wrappedSystemUpdate("Google Interactions", message)
-      steps.push({ type: "user_input", content: [{ type: "text", text: part.text }] })
-      continue
-    }
-    const start = steps.length
-    // Consecutive ordinary content remains one native message; tools and thoughts retain their chronology.
-    const append = (content: typeof Content.Type) => {
-      const type = message.role === "assistant" ? "model_output" : "user_input"
-      const last = steps.at(-1)
-      if (steps.length > start && last?.type === type)
-        steps[steps.length - 1] = { type, content: [...last.content, content] }
-      else steps.push({ type, content: [content] })
-    }
-    for (const part of message.content) {
-      if (message.role === "tool") {
-        if (part.type !== "tool-result")
-          return yield* ProviderShared.unsupportedContent(ADAPTER, "tool", ["tool-result"])
-        steps.push({
-          type: "function_result",
-          call_id: part.id,
-          name: part.name,
-          result: yield* lowerToolResult(part),
-          is_error: part.result.type === "error" || undefined,
-        })
-        continue
-      }
-      if (part.type === "text") {
-        append({ type: "text", text: part.text })
-        continue
-      }
-      if (part.type === "media") {
-        append(yield* mediaContent(part.media))
-        continue
-      }
-      if (message.role === "assistant" && part.type === "reasoning") {
-        steps.push({
-          type: "thought",
-          signature: signature(part.providerMetadata, key),
-          summary: part.text ? [{ type: "text", text: part.text }] : undefined,
-        })
-        continue
-      }
-      if (message.role === "assistant" && part.type === "tool-call") {
-        steps.push({
-          type: "function_call",
-          id: part.id,
-          name: part.name,
-          arguments: part.input,
-          signature: signature(part.providerMetadata, key),
-        })
-        continue
-      }
-      return yield* ProviderShared.unsupportedContent(
-        ADAPTER,
-        message.role,
-        message.role === "user" ? ["text", "media"] : ["text", "media", "reasoning", "tool-call"],
-      )
-    }
-  }
-  return steps
-})
-
-const lowerToolResult = Effect.fnUntraced(function* (part: ToolResultPart) {
-  if (part.result.type === "json" && ProviderShared.isRecord(part.result.value)) return part.result.value
-  if (part.result.type !== "content") return ProviderShared.toolResultText(part)
-
-  return yield* Effect.forEach(part.result.value, (item): Effect.Effect<typeof Content.Type, AIError> => {
-    if (item.type === "text") return Effect.succeed({ type: "text", text: item.text })
-    return mediaContent(ProviderShared.toolFileMedia(item).media)
-  })
-})
-
-const fromRequest = Effect.fn("GoogleInteractions.fromRequest")(function* (request: LLMRequest) {
-  const options = yield* decodeOptions(request.providerOptions ?? {})
-  const flattened = ProviderShared.flattenToolRequest(request)
-  if (flattened.tools.some((tool) => tool.native !== undefined))
-    return yield* ProviderShared.invalidRequest("Google Interactions hosted tools are not supported")
-  if (
-    request.generation?.topK !== undefined ||
-    request.generation?.frequencyPenalty !== undefined ||
-    request.generation?.presencePenalty !== undefined
-  )
-    return yield* ProviderShared.invalidRequest(
-      "Google Interactions does not support topK, frequencyPenalty, or presencePenalty",
-    )
-  const choice =
-    request.toolChoice === undefined
-      ? undefined
-      : yield* ProviderShared.matchToolChoice(ADAPTER, request.toolChoice, {
-          auto: () => "auto" as const,
-          none: () => "none" as const,
-          required: () => "any" as const,
-          tool: (name) => ({ allowed_tools: { mode: "any" as const, tools: [name] } }),
-        })
-  return {
-    model: request.model.id,
-    input: yield* lowerMessages(flattened.request),
-    stream: true as const,
-    // Full-history replay need not create retained provider resources. Continuation callers opt in to storage.
-    store: options.store ?? false,
-    previous_interaction_id: options.previousInteractionId,
-    system_instruction: request.system.length ? ProviderShared.joinText(request.system) : undefined,
-    service_tier: options.serviceTier,
-    tools: flattened.tools.length
-      ? flattened.tools.map((tool) => ({
-          type: "function" as const,
-          name: tool.name,
-          description: tool.description,
-          parameters: tool.inputSchema,
-        }))
-      : undefined,
-    generation_config: {
-      max_output_tokens: request.generation?.maxTokens,
-      temperature: request.generation?.temperature,
-      top_p: request.generation?.topP,
-      seed: request.generation?.seed,
-      stop_sequences: request.generation?.stop,
-      thinking_level: options.thinkingLevel,
-      thinking_summaries: options.thinkingSummaries,
-      tool_choice: choice,
-    },
-  }
-})
-
-// =============================================================================
-// Stream Parsing
-// =============================================================================
-const metadata = (state: ParserState, step: OutputStep): ProviderMetadata => ({
-  [state.metadataKey]: { interactionSignature: step.signature },
-})
-const mapUsage = (usage: RawUsage | undefined, key: string) => {
-  if (!usage) return undefined
-  const input = usage.total_input_tokens ?? undefined
-  const cached = usage.total_cached_tokens ?? undefined
-  const reasoning = usage.total_thought_tokens ?? undefined
-  const output =
-    usage.total_output_tokens === undefined || usage.total_output_tokens === null
-      ? undefined
-      : usage.total_output_tokens + (reasoning ?? 0)
-  return new Usage({
-    contextTokens: usage.raw_prompt_token ?? input,
-    inputTokens: input,
-    outputTokens: output,
-    nonCachedInputTokens: ProviderShared.subtractTokens(input, cached),
-    cacheReadInputTokens: cached,
-    reasoningTokens: reasoning,
-    totalTokens: usage.total_tokens ?? undefined,
-    providerMetadata: { [key]: usage },
-  })
-}
-
-const onStart = Effect.fnUntraced(function* (
-  state: ParserState,
-  index: number,
-  step: OutputStep,
-) {
-  const events: LLMEvent[] = []
-  let lifecycle = Lifecycle.stepStart(state.lifecycle, events)
-  let tools = state.tools
-  const id = String(index)
-  if (step.type === "thought") {
-    lifecycle = Lifecycle.reasoningStart(lifecycle, events, id, metadata(state, step))
-    for (const part of step.summary ?? []) lifecycle = Lifecycle.reasoningDelta(lifecycle, events, id, part.text)
-  } else if (step.type === "model_output") {
-    lifecycle = Lifecycle.textStart(lifecycle, events, id)
-    for (const part of step.content ?? []) {
-      if (part.type !== "text")
-        return yield* ProviderShared.eventError(
-          ADAPTER,
-          `Unsupported Interactions output: ${part.type}`,
-          encodeJson(step),
-        )
-      if (part.text) lifecycle = Lifecycle.textDelta(lifecycle, events, id, part.text)
-    }
-  } else if (step.type === "function_call") {
-    if (!step.id || !step.name)
-      return yield* ProviderShared.eventError(ADAPTER, "Interactions function call lacks id or name", encodeJson(step))
-    tools = ToolStream.start(tools, index, {
-      id: step.id,
-      name: step.name,
-      providerMetadata: metadata(state, step),
-      input: step.arguments && Object.keys(step.arguments).length ? encodeJson(step.arguments) : "",
-    })
-    events.push(LLMEvent.toolInputStart({ id: step.id, name: step.name, providerMetadata: metadata(state, step) }))
-  } else
-    return yield* ProviderShared.eventError(ADAPTER, `Unsupported Interactions step: ${step.type}`, encodeJson(step))
-  return [{ ...state, lifecycle, tools, steps: { ...state.steps, [index]: step } }, events] satisfies StepResult
-})
-
-const onDelta = Effect.fnUntraced(function* (
-  state: ParserState,
-  index: number,
-  delta: typeof Delta.Type,
-) {
-  const step = state.steps[index]
-  if (!step)
-    return yield* ProviderShared.eventError(ADAPTER, "Interactions delta without step.start", encodeJson(delta))
-  const events: LLMEvent[] = []
-  if (delta.type === "text" && "text" in delta && step.type === "model_output")
-    return [
-      { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, String(index), delta.text) },
-      events,
-    ] satisfies StepResult
-  if (delta.type === "thought_summary" && "content" in delta && step.type === "thought")
-    return [
-      { ...state, lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, String(index), delta.content.text) },
-      events,
-    ] satisfies StepResult
-  if (delta.type === "thought_signature" && "signature" in delta) {
-    const next = { ...step, signature: delta.signature }
-    const tool = state.tools[index]
-    return [
-      {
-        ...state,
-        steps: { ...state.steps, [index]: next },
-        tools: tool ? { ...state.tools, [index]: { ...tool, providerMetadata: metadata(state, next) } } : state.tools,
-      },
-      events,
-    ] satisfies StepResult
-  }
-  if (delta.type === "arguments_delta" && "arguments" in delta && step.type === "function_call") {
-    const result = ToolStream.appendExisting(
-      ADAPTER,
-      state.tools,
-      index,
-      delta.arguments,
-      "Interactions arguments without function call",
-    )
-    if (ToolStream.isError(result)) return yield* result
-    return [{ ...state, tools: result.tools }, result.events] satisfies StepResult
-  }
-  return yield* ProviderShared.eventError(ADAPTER, `Unsupported Interactions delta: ${delta.type}`, encodeJson(delta))
-})
-
-const onStop = Effect.fnUntraced(function* (state: ParserState, index: number) {
-  const step = state.steps[index]
-  if (!step) return yield* ProviderShared.eventError(ADAPTER, "Interactions step.stop without step.start")
-  const events: LLMEvent[] = []
-  if (step.type === "thought")
-    return [
-      { ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, String(index), metadata(state, step)) },
-      events,
-    ] satisfies StepResult
-  if (step.type === "model_output")
-    return [
-      { ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, String(index)) },
-      events,
-    ] satisfies StepResult
-  const result = yield* ToolStream.finish(ADAPTER, state.tools, index)
-  return [{ ...state, tools: result.tools }, result.events ?? []] satisfies StepResult
-})
-
-const step = Effect.fnUntraced(function* (state: ParserState, event: Event) {
-  switch (event.event_type) {
-    case "step.start":
-      return yield* onStart(state, event.index, event.step)
-    case "step.delta":
-      return yield* onDelta(state, event.index, event.delta)
-    case "step.stop":
-      return yield* onStop(state, event.index)
-    case "interaction.created":
-    case "interaction.status_update":
-      return [state, []] satisfies StepResult
-    case "error":
-      return yield* new AIError({
-        reason: classifyProviderFailure({
-          message: providerErrorMessage(encodeJson(event)) ?? "Google Interactions stream error",
-          data: event.error,
-          rawBody: encodeJson(event),
-        }),
-      })
-    case "interaction.completed": {
-      const interaction = event.interaction
-      if (interaction.status === "failed" || interaction.status === "cancelled")
-        return yield* new AIError({
-          reason: classifyProviderFailure({
-            message: `Google Interactions ${interaction.status}`,
-            data: interaction,
-            rawBody: encodeJson(event),
-          }),
-        })
-      if (!["completed", "requires_action", "incomplete"].includes(interaction.status))
-        return yield* ProviderShared.eventError(
-          ADAPTER,
-          `Unexpected terminal Interactions status: ${interaction.status}`,
-          encodeJson(event),
-        )
-      const pending = yield* ToolStream.finishAll(ADAPTER, state.tools)
-      const events = [...pending.events]
-      const lifecycle = Lifecycle.finish(state.lifecycle, events, {
-        reason: {
-          normalized:
-            interaction.status === "requires_action"
-              ? "tool-calls"
-              : interaction.status === "incomplete"
-                ? "length"
-                : "stop",
-          raw: interaction.status,
-        },
-        usage: mapUsage(interaction.usage, state.metadataKey),
-        providerMetadata: { [state.metadataKey]: { interactionId: interaction.id } },
-      })
-      return [{ ...state, lifecycle, tools: pending.tools, completed: true }, events] satisfies StepResult
-    }
-  }
-})
-
-// =============================================================================
-// Protocol And Route
-// =============================================================================
-export const protocol = Protocol.make({
-  id: ADAPTER,
-  sanitizer: "gemini",
-  body: { schema: Body, from: fromRequest },
-  stream: {
-    event: Protocol.jsonEvent(Event),
-    initial: (request): ParserState => ({
-      route: `${request.model.provider}/${ADAPTER}`,
-      metadataKey: request.model.route.providerMetadataKey ?? String(request.model.provider),
-      lifecycle: Lifecycle.initial(),
-      steps: {},
-      tools: ToolStream.empty<number>(),
-      completed: false,
-    }),
-    step,
-    terminal: (event) => event.event_type === "interaction.completed",
-    onHalt: (state) =>
-      state.completed
-        ? Effect.succeed([])
-        : Effect.fail(
-            ProviderShared.eventError(ADAPTER, "Google Interactions stream ended before interaction.completed"),
-          ),
-  },
-})
-
-export const route = Route.make({
-  id: ADAPTER,
-  provider: "google",
-  providerMetadataKey: "google",
-  protocol,
-  endpoint: Endpoint.path("/interactions", { baseURL: DEFAULT_BASE_URL }),
-  auth: Auth.none,
-  framing: Framing.sse,
-})
-
-export * as GoogleInteractions from "./google-interactions.js"
@@ -94,7 +94,7 @@ const fromRequest = Effect.fn("GoogleSpeech.fromRequest")(function* (request: Me
 // 6. Stream parsing
 // ---------------------------------------------------------------------------

-const step = Effect.fnUntraced(function* (state: State, frame: string) {
+const step = Effect.fn("GoogleSpeech.step")(function* (state: State, frame: string) {
  const chunk = yield* decodeChunk(frame)
  const blocked = GeminiGenerateContent.blocked(route.name, chunk, frame)
  if (blocked !== undefined) return yield* blocked
@@ -138,7 +138,7 @@ const turn = (part: Schema.Schema.Type<typeof AudioTranscription>) => {
  }
 }

-const step = Effect.fnUntraced(function* (state: State, frame: string) {
+const step = Effect.fn("GoogleTranscription.step")(function* (state: State, frame: string) {
  const chunk = yield* decodeChunk(frame)
  const blocked = GeminiGenerateContent.blocked(route.name, chunk, frame)
  if (blocked !== undefined) return yield* blocked
@@ -2,7 +2,6 @@ export * as AnthropicMessages from "./anthropic-messages.js"
 export * as BedrockConverse from "./bedrock-converse.js"
 export * as CohereChat from "./cohere-chat.js"
 export * as Gemini from "./gemini.js"
-export * as GoogleInteractions from "./google-interactions.js"
 export * as MistralChat from "./mistral-chat.js"
 export * as OpenAIChat from "./openai-chat.js"
 export * as OpenAIImages from "./openai-images.js"
@@ -1,5 +1,6 @@
 import { Effect, Encoding, Schema } from "effect"
 import { Protocol } from "../route/protocol.js"
+import { HttpTransport } from "../route/transport/index.js"
 import { LLMEvent, LLMRequest, Message, ToolResultPart } from "../schema/index.js"
 import { OpenResponses } from "./open-responses.js"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
@@ -43,6 +44,13 @@ const ImageItem = Schema.Struct({
  error: Schema.optional(Schema.Unknown),
 })

+const Body = Schema.Struct({
+  ...OpenResponses.coreFields,
+  input: Schema.Array(Schema.Union([OpenResponses.InputItem, ImageItem])),
+  tools: optionalArray(Schema.Union([OpenResponses.Tool, NativeTool])),
+  stream: Schema.Literal(true),
+})
+
 const MessageAnnotations = Schema.Struct({
  content: Schema.Array(Schema.Struct({ annotations: optionalArray(JsonObject) })),
 })
@@ -54,13 +62,12 @@ interface ParserState extends OpenResponses.ParserState {
 const adapter = {
  id: ADAPTER,
  name: NAME,
-  nativeTool: (native) => ProviderShared.validateWith(Schema.decodeUnknownEffect(NativeTool))(native.meta),
  restoreHostedToolItem: (item: unknown) => (Schema.is(ImageItem)(item) ? item : undefined),
 } satisfies OpenResponses.ProviderAdapter

 const fromRequest = Effect.fn("MetaResponses.fromRequest")(function* (request: LLMRequest) {
  const key = request.model.route.providerMetadataKey ?? String(request.model.provider)
-  return yield* OpenResponses.fromRequestWithAdapter(
+  const projected = ProviderShared.flattenToolRequest(
    LLMRequest.update(request, {
      messages: request.messages.map((message) =>
        Message.make({
@@ -86,8 +93,23 @@ const fromRequest = Effect.fn("MetaResponses.fromRequest")(function* (request: L
        }),
      ),
    }),
-    adapter,
  )
+  return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))({
+    ...(yield* OpenResponses.lowerConversation(projected.request, adapter)),
+    ...OpenResponses.lowerGeneration(request),
+    tools:
+      projected.tools.length === 0
+        ? undefined
+        : yield* Effect.forEach(projected.tools, (tool) =>
+            Effect.gen(function* () {
+              if (tool.native === undefined) return yield* OpenResponses.lowerTool(NAME, tool)
+              return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(NativeTool))(tool.native.meta)
+            }),
+          ),
+    tool_choice:
+      OpenResponses.allowedToolChoice(request) ??
+      (request.toolChoice ? yield* OpenResponses.lowerToolChoice(NAME, request.toolChoice) : undefined),
+  })
 })

 const HOSTED_TOOLS = {
@@ -95,7 +117,7 @@ const HOSTED_TOOLS = {
  image_generation_call: {
    name: "image_generation",
    input: () => ({}),
-    result: Effect.fnUntraced(function* (raw: ResponsesHostedTools.Item) {
+    result: Effect.fn("MetaResponses.imageResult")(function* (raw: ResponsesHostedTools.Item) {
      const item = yield* Schema.decodeUnknownEffect(ImageItem)(raw).pipe(
        Effect.mapError((cause) =>
          ProviderShared.eventError(
@@ -136,7 +158,7 @@ const HOSTED_TOOLS = {
  },
 } satisfies ResponsesHostedTools.Definitions

-const onEvent = Effect.fnUntraced(function* (
+const onEvent = Effect.fn("MetaResponses.onEvent")(function* (
  state: OpenResponses.ParserState,
  input: OpenResponses.Event,
 ) {
@@ -173,7 +195,7 @@ const onEvent = Effect.fnUntraced(function* (
  ] satisfies OpenResponses.StepResult
 })

-const step = Effect.fnUntraced(function* (state: ParserState, input: OpenResponses.Event) {
+const step = Effect.fn("MetaResponses.step")(function* (state: ParserState, input: OpenResponses.Event) {
  const completedItems = new Set(state.completedItems)
  const event = OpenResponses.normalize(state, input)
  if (event.type === "response.output_item.done" && event.item && completedItems.has(event.item.id))
@@ -200,7 +222,7 @@ const step = Effect.fnUntraced(function* (state: ParserState, input: OpenRespons

 export const protocol = Protocol.make({
  id: ADAPTER,
-  body: { schema: OpenResponses.OpenResponsesBody, from: fromRequest },
+  body: { schema: Body, from: fromRequest },
  stream: {
    event: OpenResponses.protocol.stream.event,
    initial: (request): ParserState => ({ ...OpenResponses.initial(request, adapter), completedItems: new Set() }),
@@ -209,6 +231,6 @@ export const protocol = Protocol.make({
  },
 })

-export const httpTransport = OpenResponses.httpTransport
+export const httpTransport = HttpTransport.sseJson.with<Schema.Schema.Type<typeof Body>>()

 export * as MetaResponses from "./meta-responses.js"
@@ -68,10 +68,7 @@ const MistralAssistantToolCall = Schema.Struct({
 type MistralAssistantToolCall = Schema.Schema.Type<typeof MistralAssistantToolCall>

 const MistralMessage = Schema.Union([
-  Schema.Struct({
-    role: Schema.Literal("system"),
-    content: Schema.Union([Schema.String, Schema.Array(MistralTextContent)]),
-  }),
+  Schema.Struct({ role: Schema.Literal("system"), content: Schema.String }),
  Schema.Struct({
    role: Schema.Literal("user"),
    content: Schema.Union([Schema.String, Schema.Array(MistralUserContent)]),
@@ -226,7 +223,7 @@ const MistralEvent = Schema.StructWithRest(
 type MistralEvent = Schema.Schema.Type<typeof MistralEvent>
 const MistralStreamEvent = Schema.Union([Schema.Literal(DONE), Protocol.jsonEvent(MistralEvent)])

-const lowerMedia = Effect.fnUntraced(function* (part: MediaPart) {
+const lowerMedia = Effect.fn("MistralChat.lowerMedia")(function* (part: MediaPart) {
  const mime = part.media.mediaType.toLowerCase()
  const url =
    ProviderShared.mediaUrl(part.media) ??
@@ -236,7 +233,7 @@ const lowerMedia = Effect.fnUntraced(function* (part: MediaPart) {
  return yield* ProviderShared.invalidRequest(`Mistral Chat does not support media type ${part.media.mediaType}`)
 })

-const lowerUser = Effect.fnUntraced(function* (message: LLMRequest["messages"][number]) {
+const lowerUser = Effect.fn("MistralChat.lowerUser")(function* (message: LLMRequest["messages"][number]) {
  const content: MistralUserContent[] = []
  for (const part of message.content) {
    if (part.type === "text") {
@@ -260,7 +257,7 @@ const lowerToolCall = (part: ToolCallPart, normalizeID: (id: string) => string):
  function: { name: part.name, arguments: ProviderShared.encodeJson(part.input) },
 })

-const lowerAssistant = Effect.fnUntraced(function* (
+const lowerAssistant = Effect.fn("MistralChat.lowerAssistant")(function* (
  message: LLMRequest["messages"][number],
  normalizeID: (id: string) => string,
  prefix: boolean,
@@ -298,7 +295,7 @@ const lowerAssistant = Effect.fnUntraced(function* (
  }
 })

-const lowerToolResults = Effect.fnUntraced(function* (
+const lowerToolResults = Effect.fn("MistralChat.lowerToolResults")(function* (
  message: LLMRequest["messages"][number],
  normalizeID: (id: string) => string,
 ) {
@@ -335,20 +332,10 @@ const lowerToolResults = Effect.fnUntraced(function* (
  return output
 })

-const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest) {
+const lowerMessages = Effect.fn("MistralChat.lowerMessages")(function* (request: LLMRequest) {
  const normalizeID = MistralToolID.normalizer(request)
  const messages: MistralMessage[] =
-    request.system.length === 0
-      ? []
-      : [
-          {
-            role: "system",
-            content:
-              request.system.length === 1
-                ? request.system[0].text
-                : request.system.map((part) => ({ type: "text", text: part.text })),
-          },
-        ]
+    request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
  for (const message of request.messages) {
    if (message.role === "system") {
      const update = yield* ProviderShared.wrappedSystemUpdate("Mistral Chat", message)
@@ -596,7 +583,7 @@ const toolText = (tool: MistralToolDelta) => {
  return value === null || value === undefined ? "" : ProviderShared.encodeJson(value)
 }

-const appendTools = Effect.fnUntraced(function* (
+const appendTools = Effect.fn("MistralChat.appendTools")(function* (
  initial: ParserState,
  events: LLMEvent[],
  deltas: ReadonlyArray<MistralToolDelta>,
@@ -662,7 +649,7 @@ const hasLateContent = (event: MistralEvent) => {
  )
 }

-const step = Effect.fnUntraced(function* (state: ParserState, event: MistralEvent) {
+const step = Effect.fn("MistralChat.step")(function* (state: ParserState, event: MistralEvent) {
  if (event.error) {
    const body = ProviderShared.encodeJson(event)
    return yield* new AIError({
@@ -726,7 +713,7 @@ const step = Effect.fnUntraced(function* (state: ParserState, event: MistralEven
  ] as const
 })

-const finishEvents = Effect.fnUntraced(function* (state: ParserState) {
+const finishEvents = Effect.fn("MistralChat.finishEvents")(function* (state: ParserState) {
  if (!state.finishReason)
    return yield* new AIError({
      reason: new InvalidProviderOutputError({
@@ -168,20 +168,10 @@ export const ConfigurationUpdate = Schema.Struct({
  type: Schema.Literal("configuration_update"),
  reasoning: Schema.Struct({ effort: OpenResponsesOptions.ReasoningEffort }),
 })
-export type ConfigurationUpdate = Schema.Schema.Type<typeof ConfigurationUpdate>
-
-export const HostedToolReplay = Schema.StructWithRest(
-  Schema.Struct({
-    type: Schema.String,
-    id: Schema.String,
-  }),
-  [JsonObject],
-)
-export type HostedToolReplayItem = Schema.Schema.Type<typeof HostedToolReplay>
+type ConfigurationUpdate = Schema.Schema.Type<typeof ConfigurationUpdate>

 export const InputItem = Schema.Union([
  CompactionItem,
-  ConfigurationUpdate,
  Schema.Struct({ type: Schema.tag("message"), role: Schema.tag("system"), content: Schema.String }),
  Schema.Struct({ type: Schema.tag("message"), role: Schema.tag("developer"), content: Schema.String }),
  Schema.Struct({
@@ -214,9 +204,24 @@ export const InputItem = Schema.Union([
    output: OpenResponsesFunctionCallOutput,
  }),
  HostedToolItem,
-  HostedToolReplay,
 ])
 type OpenResponsesInputItem = Schema.Schema.Type<typeof InputItem>
+export type HostedToolReplayItem = {
+  readonly type: string
+  readonly id: string
+  readonly [key: string]: unknown
+}
+type LoweredInputItem =
+  | OpenResponsesInputItem
+  | HostedToolReplayItem
+  | ConfigurationUpdate
+  | {
+      readonly type: "message"
+      readonly id?: string
+      readonly role: "assistant"
+      readonly content: ReadonlyArray<{ readonly type: "output_text"; readonly text: string }>
+      readonly phase?: MessagePhase | null
+    }

 // Mutable counterpart of the schema reasoning item so `lowerMessages` can fold
 // multiple streamed summary parts into the same item before flushing.
@@ -234,14 +239,6 @@ export const Tool = Schema.Struct({
  strict: Schema.optional(Schema.Boolean),
 })

-export const HostedTool = Schema.StructWithRest(
-  Schema.Struct({
-    type: Schema.String,
-  }),
-  [JsonObject],
-)
-export type HostedTool = Schema.Schema.Type<typeof HostedTool>
-
 export const ToolChoice = Schema.Union([
  Schema.Literals(["auto", "none", "required"]),
  Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
@@ -260,7 +257,7 @@ export const coreFields = {
  model: Schema.String,
  input: Schema.Array(InputItem),
  instructions: Schema.optional(Schema.String),
-  tools: optionalArray(Schema.Union([Tool, HostedTool])),
+  tools: optionalArray(Tool),
  tool_choice: Schema.optional(ToolChoice),
  store: Schema.optional(Schema.Boolean),
  metadata: Schema.optional(Schema.Record(Schema.String, Schema.String)),
@@ -295,7 +292,7 @@ export const coreFields = {
  frequency_penalty: Schema.optional(Schema.Number),
 }

-export const OpenResponsesBody = Schema.Struct({
+const OpenResponsesBody = Schema.Struct({
  ...coreFields,
  stream: Schema.Literal(true),
 })
@@ -400,7 +397,9 @@ export const decodeChannelEvent = (frame: string) =>
 export interface ProviderAdapter {
  readonly id: string
  readonly name: string
-  readonly nativeTool?: (native: NonNullable<ToolDefinition["native"]>) => Effect.Effect<HostedTool, AIError>
+  readonly nativeTool?: (
+    native: NonNullable<ToolDefinition["native"]>,
+  ) => Effect.Effect<{ readonly type: string }, AIError>
  readonly lowerMedia?: (input: {
    readonly part: MediaPart
    readonly media: Media.Inline | undefined
@@ -442,7 +441,7 @@ interface ReasoningStreamItem {
 // =============================================================================
 // Request Lowering
 // =============================================================================
-export const lowerTool = Effect.fnUntraced(function* (protocolName: string, tool: ToolDefinition) {
+export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (protocolName: string, tool: ToolDefinition) {
  if (tool.native !== undefined)
    return yield* ProviderShared.invalidRequest(`${protocolName} does not support provider-native tool ${tool.name}`)
  return {
@@ -456,10 +455,8 @@ export const lowerTool = Effect.fnUntraced(function* (protocolName: string, tool
 })

 export const lowerTools = (tools: ReadonlyArray<ToolDefinition>, adapter: ProviderAdapter) =>
-  Effect.forEach(
-    tools,
-    (tool): Effect.Effect<Schema.Schema.Type<typeof Tool> | HostedTool, AIError> =>
-      tool.native !== undefined && adapter.nativeTool ? adapter.nativeTool(tool.native) : lowerTool(adapter.name, tool),
+  Effect.forEach(tools, (tool) =>
+    tool.native !== undefined && adapter.nativeTool ? adapter.nativeTool(tool.native) : lowerTool(adapter.name, tool),
  )

 export const lowerToolChoice = (protocolName: string, toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -507,10 +504,7 @@ const lowerReasoning = (part: ReasoningPart, providerMetadataKey: string): OpenR
  }
 }

-const decodeImageDetail = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesInputImage.fields.detail))
-const decodeMessageMetadata = ProviderShared.validateWith(Schema.decodeUnknownEffect(MessageMetadata))
-
-const lowerMedia = Effect.fnUntraced(function* (
+const lowerMedia = Effect.fn("OpenResponses.lowerMedia")(function* (
  part: MediaPart,
  request: LLMRequest,
  adapter: ProviderAdapter,
@@ -519,8 +513,9 @@ const lowerMedia = Effect.fnUntraced(function* (
  const media = part.media.inline()
  const providerMedia = adapter.lowerMedia?.({ part, media, request })
  if (providerMedia) return providerMedia
-  const rawDetail = part.providerMetadata?.[metadataKey(request.model)]?.detail
-  const detail = rawDetail === undefined ? undefined : yield* decodeImageDetail(rawDetail)
+  const detail = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesInputImage.fields.detail))(
+    part.providerMetadata?.[metadataKey(request.model)]?.detail,
+  )
  const mime = part.media.mediaType.toLowerCase()
  const url = ProviderShared.mediaUrl(part.media)
  const location = url ?? (yield* ProviderShared.requireInlineMedia(adapter.name, part.media)).dataUrl
@@ -593,16 +588,17 @@ const lowerToolResultOutput = Effect.fnUntraced(function* (

 const DEFAULT_EFFORT = "medium"

-const lowerMessages = Effect.fnUntraced(function* (
+const lowerMessages = Effect.fn("OpenResponses.lowerMessages")(function* (
  request: LLMRequest,
  adapter: ProviderAdapter,
 ) {
-  const input: OpenResponsesInputItem[] = []
+  const input: LoweredInputItem[] = []
  const providerMetadataKey = metadataKey(request.model)

  for (const message of request.messages) {
-    const rawMetadata = message.providerMetadata?.[providerMetadataKey]
-    const metadata = rawMetadata === undefined ? undefined : yield* decodeMessageMetadata(rawMetadata)
+    const metadata = yield* ProviderShared.validateWith(
+      Schema.decodeUnknownEffect(Schema.UndefinedOr(MessageMetadata)),
+    )(message.providerMetadata?.[providerMetadataKey])
    if (message.role === "system") {
      const update = effortUpdate(message)
      if (update) {
@@ -756,7 +752,7 @@ const lowerMessages = Effect.fnUntraced(function* (
  return input
 })

-export const lowerConversation = Effect.fnUntraced(function* (
+export const lowerConversation = Effect.fn("OpenResponses.lowerConversation")(function* (
  request: LLMRequest,
  adapter: ProviderAdapter,
 ) {
@@ -831,7 +827,11 @@ export const fromRequestWithAdapter = Effect.fn("OpenResponses.fromRequestWithAd
  }
 })

-export const fromRequest = (request: LLMRequest) => fromRequestWithAdapter(request, BASE_ADAPTER)
+const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesBody))
+
+export const fromRequest = Effect.fn("OpenResponses.fromRequest")(function* (request: LLMRequest) {
+  return yield* decodeBody(yield* fromRequestWithAdapter(request, BASE_ADAPTER))
+})

 // =============================================================================
 // Stream Parsing
@@ -1143,7 +1143,7 @@ const onReasoningSummaryPartDone = (state: ParserState, event: Event): StepResul
  ]
 }

-const onFunctionCallArgumentsDelta = Effect.fnUntraced(function* (
+const onFunctionCallArgumentsDelta = Effect.fn("OpenResponses.onFunctionCallArgumentsDelta")(function* (
  state: ParserState,
  event: Event,
 ) {
@@ -1174,7 +1174,7 @@ const onFunctionCallArgumentsDelta = Effect.fnUntraced(function* (
  return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
 })

-const onOutputItemDone = Effect.fnUntraced(function* (
+const onOutputItemDone = Effect.fn("OpenResponses.onOutputItemDone")(function* (
  state: ParserState,
  item: NormalizedEvent["item"],
 ) {
@@ -1310,7 +1310,7 @@ const onOutputItemDone = Effect.fnUntraced(function* (
  return [state, NO_EVENTS] satisfies StepResult
 })

-const onResponseFinish = Effect.fnUntraced(function* (state: ParserState, event: Event) {
+const onResponseFinish = Effect.fn("OpenResponses.onResponseFinish")(function* (state: ParserState, event: Event) {
  let current = state
  const events: LLMEvent[] = []
  if (event.type === "response.completed") {
@@ -14,6 +14,7 @@ import {
  ProviderInternalError,
  UnknownProviderError,
  Usage,
+  type FinishReason,
  type FinishReasonDetails,
  type CacheHint,
  type LLMRequest,
@@ -45,6 +46,12 @@ const OpenAIChatCacheControl = Schema.Struct({
 })
 type OpenAIChatCacheControl = Schema.Schema.Type<typeof OpenAIChatCacheControl>

+const OpenAIChatFunction = Schema.Struct({
+  name: Schema.String,
+  description: Schema.String,
+  parameters: JsonObject,
+})
+
 const OpenAIChatTool = Schema.Struct({
  type: Schema.tag("function"),
  function: Schema.Struct({
@@ -65,7 +72,7 @@ const ExtraContent = Schema.Struct({
 })
 const decodeExtraContent = (value: unknown) => Option.getOrUndefined(Schema.decodeUnknownOption(ExtraContent)(value))

-export const OpenAIChatAssistantToolCall = Schema.Struct({
+const OpenAIChatAssistantToolCall = Schema.Struct({
  id: Schema.String,
  type: Schema.tag("function"),
  function: Schema.Struct({
@@ -134,7 +141,7 @@ const OpenAIChatUserContent = Schema.Union([
 ])
 type OpenAIChatUserContent = Schema.Schema.Type<typeof OpenAIChatUserContent>

-export const OpenAIChatMessage = Schema.Union([
+const OpenAIChatMessage = Schema.Union([
  Schema.Struct({
    role: Schema.Literal("system"),
    content: Schema.Union([Schema.String, Schema.Array(OpenAIChatUserContent)]),
@@ -200,7 +207,7 @@ export type OpenAIChatBody = Schema.Schema.Type<typeof OpenAIChatBody>
 // 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.
-export const OpenAIChatUsage = Schema.StructWithRest(
+const OpenAIChatUsage = Schema.StructWithRest(
  Schema.Struct({
    prompt_tokens: optionalNull(Schema.Number),
    completion_tokens: optionalNull(Schema.Number),
@@ -238,7 +245,7 @@ const OpenAIChatToolCallDeltaFunction = Schema.Struct({
  arguments: optionalNull(Schema.String),
 })

-export const OpenAIChatToolCallDelta = Schema.Struct({
+const OpenAIChatToolCallDelta = Schema.Struct({
  index: optionalNull(Schema.Number),
  id: optionalNull(Schema.String),
  function: optionalNull(OpenAIChatToolCallDeltaFunction),
@@ -246,7 +253,7 @@ export const OpenAIChatToolCallDelta = Schema.Struct({
 })
 type OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta>

-export const OpenAIChatDelta = Schema.StructWithRest(
+const OpenAIChatDelta = Schema.StructWithRest(
  Schema.Struct({
    content: optionalNull(Schema.String),
    refusal: optionalNull(Schema.String),
@@ -259,7 +266,7 @@ export const OpenAIChatDelta = Schema.StructWithRest(
  [Schema.Record(Schema.String, Schema.Unknown)],
 )

-export const OpenAIChatChoice = Schema.StructWithRest(
+const OpenAIChatChoice = Schema.StructWithRest(
  Schema.Struct({
    delta: optionalNull(OpenAIChatDelta),
    finish_reason: optionalNull(Schema.String),
@@ -326,8 +333,6 @@ export interface ParserState {
 interface LoweringOptions {
  readonly cacheControl?: (cache: CacheHint | undefined) => OpenAIChatCacheControl | undefined
  readonly toolCallID?: (id: string) => string
-  /** Project provider-specific fields from the exact source, even when other messages are dropped during lowering. */
-  readonly assistant?: (source: LLMRequest["messages"][number], message: OpenAIChatMessage) => OpenAIChatMessage
 }

 const lowerTool = (tool: ToolDefinition, options: LoweringOptions, supportsStrictMode: boolean): OpenAIChatTool => ({
@@ -362,7 +367,7 @@ const lowerToolCall = (
  extra_content: decodeExtraContent(part.providerMetadata?.[options.providerMetadataKey]?.extraContent),
 })

-const lowerMedia = Effect.fnUntraced(function* (part: MediaPart) {
+const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart) {
  // Chat Completions accepts PDFs, and no other documents, as inline `file` parts; file URLs are not supported.
  if (part.media.mediaType.toLowerCase() === "application/pdf")
    return {
@@ -408,7 +413,7 @@ const lowerReasoningDetail = (detail: ReasoningDetail) => {

 const isKimiDetail = (detail: { readonly type: string }) => detail.type === "summary" || detail.type === "encrypted"

-const lowerUserMessage = Effect.fnUntraced(function* (
+const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (
  message: OpenAIChatRequestMessage,
  options: LoweringOptions,
 ) {
@@ -432,7 +437,7 @@ const lowerUserMessage = Effect.fnUntraced(function* (
  return { role: "user" as const, content }
 })

-const lowerAssistantMessage = Effect.fnUntraced(function* (
+const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(function* (
  message: OpenAIChatRequestMessage,
  configuredField: string | undefined,
  requireReasoning: boolean,
@@ -497,7 +502,7 @@ const lowerAssistantMessage = Effect.fnUntraced(function* (
  return { ...result, [field]: reasoningText }
 })

-const lowerToolMessages = Effect.fnUntraced(function* (
+const lowerToolMessages = Effect.fn("OpenAIChat.lowerToolMessages")(function* (
  message: OpenAIChatRequestMessage,
  options: LoweringOptions,
 ) {
@@ -534,21 +539,19 @@ const toolMessage = (toolCallID: string, text: string, cacheControl: OpenAIChatC
  content: cacheControl === undefined ? text : [{ type: "text" as const, text, cache_control: cacheControl }],
 })

-const lowerMessage = Effect.fnUntraced(function* (
+const lowerMessage = Effect.fn("OpenAIChat.lowerMessage")(function* (
  message: OpenAIChatRequestMessage,
  reasoningField: string | undefined,
  requireReasoning: boolean,
  options: LoweringOptions & { readonly providerMetadataKey: string },
 ) {
  if (message.role === "user") return [yield* lowerUserMessage(message, options)]
-  if (message.role === "assistant") {
-    const lowered = yield* lowerAssistantMessage(message, reasoningField, requireReasoning, options)
-    return [options.assistant?.(message, lowered) ?? lowered]
-  }
+  if (message.role === "assistant")
+    return [yield* lowerAssistantMessage(message, reasoningField, requireReasoning, options)]
  return (yield* lowerToolMessages(message, options)).messages
 })

-const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, options: LoweringOptions) {
+const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request: LLMRequest, options: LoweringOptions) {
  const system: OpenAIChatMessage[] =
    request.system.length === 0
      ? []
@@ -859,7 +862,7 @@ export const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (
 // 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 = Effect.fnUntraced(function* (event: OpenAIChatEvent, reason: string) {
+const mapFinishReason = Effect.fn("OpenAIChat.mapFinishReason")(function* (event: OpenAIChatEvent, reason: string) {
  switch (reason) {
    case "error":
      return yield* new AIError({
@@ -1218,7 +1221,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
    ] as const
  })

-export const finishEvents = Effect.fnUntraced(function* (state: ParserState) {
+const finishEvents = Effect.fn("OpenAIChat.finishEvents")(function* (state: ParserState) {
  if (state.finishReason === undefined && state.requireFinishReason)
    return yield* new AIError({
      reason: new InvalidProviderOutputError({
@@ -208,7 +208,7 @@ const eventImage = (frame: string, label: string, data: string, format: string,
    info: info(format, size),
  })

-const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
+const onEvent = Effect.fn("OpenAIImages.onEvent")(function* (state: State, frame: string) {
  const event = yield* decodeEvent(frame)
  const format = event.output_format
  if ("partial_image_index" in event) {
@@ -229,7 +229,7 @@ const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
  ] as const
 })

-const onDocument = Effect.fnUntraced(function* (frame: Exclude<Frame, string>) {
+const onDocument = Effect.fn("OpenAIImages.onDocument")(function* (frame: Exclude<Frame, string>) {
  const invalid = (message: string, cause?: unknown) => route.frameError(message, frame.document, cause)
  const decoded = yield* decodeDocument(frame.document).pipe(
    Effect.mapError((cause) => invalid(`${route.name} returned an invalid response`, cause)),
@@ -103,8 +103,15 @@ const OpenAIResponsesToolChoice = Schema.Union([
  Schema.Struct({ type: Schema.tag("image_generation") }),
 ])

+const OpenAIResponsesInputItem = Schema.Union([
+  OpenResponses.InputItem,
+  OpenAIResponsesHostedToolItem,
+  OpenResponses.ConfigurationUpdate,
+])
+
 const OpenAIResponsesCoreFields = {
  ...OpenResponses.coreFields,
+  input: Schema.Array(OpenAIResponsesInputItem),
  tools: optionalArray(OpenAIResponsesTools),
  tool_choice: Schema.optional(OpenAIResponsesToolChoice),
  context_management: Schema.optional(
@@ -127,7 +134,7 @@ export type OpenAIResponsesBody = Schema.Schema.Type<typeof OpenAIResponsesBody>
 export const CompactionTrigger = Schema.Struct({ type: Schema.Literal("compaction_trigger") })
 const CheckpointBody = Schema.Struct({
  ...OpenAIResponsesBody.fields,
-  input: Schema.Array(Schema.Union([OpenResponses.InputItem, CompactionTrigger])),
+  input: Schema.Array(Schema.Union([OpenAIResponsesInputItem, CompactionTrigger])),
 })

 const adapter = {
@@ -157,7 +164,7 @@ const nativeImageTool = (tool: ToolDefinition) => {
  return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
 }

-const lowerTool = Effect.fnUntraced(function* (tool: ToolDefinition) {
+const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition) {
  const native = nativeImageToolInput(tool)
  if (native !== undefined) {
    if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
@@ -168,7 +175,7 @@ const lowerTool = Effect.fnUntraced(function* (tool: ToolDefinition) {

 // Native namespaces hold only function tools, so deeper levels flatten into
 // the leaf names the same way non-native protocols flatten the whole tree.
-const lowerToolEntry = Effect.fnUntraced(function* (tool: ToolEntry) {
+const lowerToolEntry = Effect.fn("OpenAIResponses.lowerToolEntry")(function* (tool: ToolEntry) {
  if (tool.type === "tool") return yield* lowerTool(tool)
  // OpenAI requires a namespace description; fall back to a generic one so a
  // missing description never blocks the request.
@@ -195,13 +202,15 @@ const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tool
        : { type: "function" as const, name },
  })

+const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIResponsesBody))
+
 const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request: LLMRequest) {
  const management = yield* ProviderShared.validateWith(
    Schema.decodeUnknownEffect(Schema.UndefinedOr(ContextManagement)),
  )(request.providerOptions?.contextManagement)
  const options = OpenResponsesOptions.resolve(request)
  const updates = resolveEffortUpdates(request, options.reasoningEffort)
-  return {
+  return yield* decodeBody({
    ...(yield* OpenResponses.lowerConversation(updates.request, adapter)),
    ...OpenResponses.lowerGeneration(request, { ...options, reasoningEffort: updates.effort }),
    context_management: management?.map((edit) => ({ type: edit.type, compact_threshold: edit.compactThreshold })),
@@ -211,7 +220,7 @@ const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request:
        ? undefined
        : (OpenResponses.allowedToolChoice(request) ??
          (request.toolChoice ? yield* lowerToolChoice(request.toolChoice, request.tools) : undefined)),
-  }
+  })
 })

 const checkpointBody = {
@@ -237,7 +246,7 @@ const checkpointBody = {
  }),
 }

-const hostedToolResult = Effect.fnUntraced(function* (item: ResponsesHostedTools.Item) {
+const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: ResponsesHostedTools.Item) {
  const isError = item.error !== undefined && item.error !== null
  if (item.type === "image_generation_call" && item.result) {
    yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
@@ -94,7 +94,7 @@ const fromRequest = Effect.fn("OpenAISpeech.fromRequest")(function* (request: Me

 const isSse = (body: MediaProtocol.Body) => body.type === "json" && body.value.stream_format === "sse"

-const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
+const onEvent = Effect.fn("OpenAISpeech.onEvent")(function* (state: State, frame: string) {
  const event = yield* decodeEvent(frame)
  if (event.type === "speech.audio.delta") return SpeechStream.delta(state, event.audio)
  const usage = event.usage
@@ -210,7 +210,7 @@ const segment = (value: Schema.Schema.Type<typeof Segment>): TranscriptionSegmen
  speaker: value.speaker,
 })

-const onEvent = Effect.fnUntraced(function* (state: State, frame: string) {
+const onEvent = Effect.fn("OpenAITranscription.onEvent")(function* (state: State, frame: string) {
  if (!EVENT_TYPES.has((yield* decodeEventType(frame)).type)) return [state, []] as const
  const event = yield* decodeEvent(frame)
  if (event.type === "error")
@@ -154,7 +154,7 @@ export const wrapSystemUpdate = (parts: ReadonlyArray<{ readonly text: string }>
 * raw retrieved, tool, or web content into privileged updates: keep untrusted
 * data in ordinary user/tool messages instead.
 */
-export const systemUpdateText = Effect.fnUntraced(function* (
+export const systemUpdateText = Effect.fn("ProviderShared.systemUpdateText")(function* (
  route: string,
  message: LLMRequest["messages"][number],
 ) {
@@ -167,7 +167,7 @@ export const systemUpdateText = Effect.fnUntraced(function* (
 })

 /** Lower an unsupported privileged update into visible, in-order user text. */
-export const wrappedSystemUpdate = Effect.fnUntraced(function* (
+export const wrappedSystemUpdate = Effect.fn("ProviderShared.wrappedSystemUpdate")(function* (
  route: string,
  message: LLMRequest["messages"][number],
 ) {
@@ -82,7 +82,7 @@ const endpoint = (model: string) => (model.startsWith("sd3") ? "sd3" : model)

 const RESERVED_FORM_FIELDS = new Set(["image", "prompt", "mode", "model"])

-const form = Effect.fnUntraced(function* (
+const form = Effect.fn("StabilityImages.form")(function* (
  identity: MediaProtocol.Identity,
  fields: Record<string, unknown>,
  native: Record<string, unknown> | undefined,
@@ -76,7 +76,7 @@ function documentName(filename: string | undefined, names: Set<string>) {
  return name
 }

-const mediaBase64 = Effect.fnUntraced(function* (part: MediaPart) {
+const mediaBase64 = Effect.fn("BedrockMedia.mediaBase64")(function* (part: MediaPart) {
  const media = yield* ProviderShared.requireInlineMedia("Bedrock Converse", part.media)
  const bytes = yield* Effect.fromResult(Encoding.decodeBase64(media.base64)).pipe(
    Effect.mapError((cause) =>
@@ -91,7 +91,7 @@ const mediaBase64 = Effect.fnUntraced(function* (part: MediaPart) {
 // document block. Image MIME types not in `IMAGE_FORMATS` (e.g. `image/svg+xml`)
 // get an image-specific error so the caller knows it's a format-support issue,
 // not a kind-detection issue.
-export const lower = Effect.fnUntraced(function* (part: MediaPart, documentNames: Set<string>) {
+export const lower = Effect.fn("BedrockMedia.lower")(function* (part: MediaPart, documentNames: Set<string>) {
  const mime = part.media.mediaType.toLowerCase()
  const imageFormat = IMAGE_FORMATS[mime as keyof typeof IMAGE_FORMATS]
  if (imageFormat) {
@@ -11,7 +11,7 @@ interface State {
  readonly responseID?: string
 }

-const onOutputItem = Effect.fnUntraced(function* (
+const onOutputItem = Effect.fn("ResponsesCheckpoint.onOutputItem")(function* (
  state: State,
  input: OpenResponses.Event,
 ) {
@@ -63,7 +63,7 @@ export const make = <Body>(body: RouteBody<Body>): TriggerCompactOperation =>
          checkpoints: {},
        }),
        terminal: OpenResponses.terminal,
-        step: Effect.fnUntraced(function* (state: State, event: OpenResponses.Event) {
+        step: Effect.fn("ResponsesCheckpoint.step")(function* (state: State, event: OpenResponses.Event) {
          if (event.response?.id && state.responseID && event.response.id !== state.responseID)
            return yield* ProviderShared.eventError(source.id, "Compaction response ID changed during execution")
          if (event.type === "response.created") return [{ ...state, responseID: event.response?.id }, []] as const
@@ -33,7 +33,7 @@ export const onDone: (
  state: OpenResponses.ParserState,
  item: Item,
  tools: Definitions,
-) => Effect.Effect<OpenResponses.StepResult, AIError> = Effect.fnUntraced(
+) => Effect.Effect<OpenResponses.StepResult, AIError> = Effect.fn("ResponsesHostedTools.onDone")(
  function* (state, item, tools) {
    const tool = tools[item.type]
    if (!tool) return [state, []] satisfies OpenResponses.StepResult
@@ -60,21 +60,14 @@ const inputStart = (tool: PendingTool) =>
    providerMetadata: tool.providerMetadata,
  })

-const inputDelta = (tool: PendingTool, text: string): LLMEvent => {
-  const raw = tool.input
-  let parsed: unknown
-  return {
-    ...LLMEvent.toolInputDelta({
-      id: tool.id,
-      name: tool.name,
-      namespace: tool.namespace,
-      text,
-    }),
-    get input() {
-      return (parsed ??= Option.getOrElse(parsePartialInput(raw), () => ({})))
-    },
-  }
-}
+const inputDelta = (tool: PendingTool, text: string) =>
+  LLMEvent.toolInputDelta({
+    id: tool.id,
+    name: tool.name,
+    namespace: tool.namespace,
+    text,
+    input: Option.getOrElse(parsePartialInput(tool.input), () => ({})),
+  })

 const toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {
  const raw = inputOverride ?? tool.input
@@ -1,374 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Protocol } from "../route/protocol.js"
-import { AIError, LLMEvent, type LanguageModelCompatibility, type LLMRequest } from "../schema/index.js"
-import { classifyProviderFailure } from "../provider-error.js"
-import { OpenAIChat } from "./openai-chat.js"
-import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
-import { cacheControl } from "./utils/cache.js"
-
-// ---------------------------------------------------------------------------
-// Public options and request body
-// ---------------------------------------------------------------------------
-
-export type ReasoningEffort = "none" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max" | (string & {})
-
-const Parameters = Schema.Struct({
-  enableWebSearch: Schema.optional(Schema.String),
-  enableWebScraping: Schema.optional(Schema.Boolean),
-  enableWebCitations: Schema.optional(Schema.Boolean),
-  enableXSearch: Schema.optional(Schema.Boolean),
-  stripThinkingResponse: Schema.optional(Schema.Boolean),
-  disableThinking: Schema.optional(Schema.Boolean),
-  includeVeniceSystemPrompt: Schema.optional(Schema.Boolean),
-  characterSlug: Schema.optional(Schema.String),
-  includeSearchResultsInStream: Schema.optional(Schema.Boolean),
-  returnSearchResultsAsDocuments: Schema.optional(Schema.Boolean),
-})
-
-const Reasoning = Schema.Struct({
-  effort: Schema.optional(Schema.String),
-  enabled: Schema.optional(Schema.Boolean),
-  summary: Schema.optional(Schema.String),
-})
-
-export type OptionsInput = {
-  readonly reasoningEffort?: ReasoningEffort
-  readonly reasoning?: {
-    readonly effort?: ReasoningEffort
-    readonly enabled?: boolean
-    readonly summary?: "auto" | "concise" | "detailed" | (string & {})
-  }
-  readonly veniceParameters?: Omit<typeof Parameters.Type, "enableWebSearch"> & {
-    readonly enableWebSearch?: "off" | "on" | "auto" | (string & {})
-  }
-  readonly promptCacheKey?: string
-  readonly promptCacheRetention?: "default" | "extended" | "24h" | (string & {})
-  readonly parallelToolCalls?: boolean
-  readonly maxCompletionTokens?: number
-  readonly maxTokens?: number
-  readonly minP?: number
-  readonly repetitionPenalty?: number
-  readonly stopTokenIds?: readonly number[]
-  readonly logprobs?: boolean
-  readonly topLogprobs?: number
-  readonly maxTemp?: number
-  readonly minTemp?: number
-  readonly responseFormat?: Readonly<Record<string, unknown>>
-  readonly user?: string
-}
-
-const Options = Schema.Struct({
-  reasoningEffort: Schema.optional(Schema.String),
-  reasoning: Schema.optional(Reasoning),
-  veniceParameters: Schema.optional(Parameters),
-  promptCacheKey: Schema.optional(Schema.String),
-  promptCacheRetention: Schema.optional(Schema.String),
-  parallelToolCalls: Schema.optional(Schema.Boolean),
-  maxCompletionTokens: Schema.optional(Schema.Number),
-  maxTokens: Schema.optional(Schema.Number),
-  minP: Schema.optional(Schema.Number),
-  repetitionPenalty: Schema.optional(Schema.Number),
-  stopTokenIds: Schema.optional(Schema.Array(Schema.Number)),
-  logprobs: Schema.optional(Schema.Boolean),
-  topLogprobs: Schema.optional(Schema.Number),
-  maxTemp: Schema.optional(Schema.Number),
-  minTemp: Schema.optional(Schema.Number),
-  responseFormat: Schema.optional(JsonObject),
-  user: Schema.optional(Schema.String),
-})
-
-const ToolCall = Schema.Struct({
-  ...OpenAIChat.OpenAIChatAssistantToolCall.fields,
-  thought_signature: Schema.optional(Schema.String),
-})
-const Assistant = Schema.StructWithRest(
-  Schema.Struct({
-    ...OpenAIChat.OpenAIChatMessage.cases.assistant.schema.fields,
-    tool_calls: optionalArray(ToolCall),
-    thought_signature: Schema.optional(Schema.String),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Messages = Schema.Array(
-  Schema.Union([
-    OpenAIChat.OpenAIChatMessage.cases.system,
-    OpenAIChat.OpenAIChatMessage.cases.user,
-    Assistant,
-    OpenAIChat.OpenAIChatMessage.cases.tool,
-  ]),
-)
-const Body = Schema.Struct({
-  ...OpenAIChat.bodyFields,
-  messages: Messages,
-  reasoning: Schema.optional(Reasoning),
-  venice_parameters: Schema.Record(Schema.String, Schema.Union([Schema.String, Schema.Boolean])),
-  prompt_cache_retention: Options.fields.promptCacheRetention,
-  parallel_tool_calls: Options.fields.parallelToolCalls,
-  min_p: Options.fields.minP,
-  top_k: Schema.optional(Schema.Number),
-  repetition_penalty: Options.fields.repetitionPenalty,
-  stop_token_ids: Options.fields.stopTokenIds,
-  logprobs: Options.fields.logprobs,
-  top_logprobs: Options.fields.topLogprobs,
-  max_temp: Options.fields.maxTemp,
-  min_temp: Options.fields.minTemp,
-  response_format: Options.fields.responseFormat,
-  user: Options.fields.user,
-})
-
-// ---------------------------------------------------------------------------
-// Streaming schemas and state
-// ---------------------------------------------------------------------------
-
-const ToolDelta = Schema.Struct({
-  ...OpenAIChat.OpenAIChatToolCallDelta.fields,
-  thought_signature: optionalNull(Schema.String),
-})
-const Delta = Schema.StructWithRest(
-  Schema.Struct({
-    ...OpenAIChat.OpenAIChatDelta.schema.fields,
-    tool_calls: optionalNull(Schema.Array(ToolDelta)),
-    thought_signature: optionalNull(Schema.String),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Choice = Schema.StructWithRest(
-  Schema.Struct({ ...OpenAIChat.OpenAIChatChoice.schema.fields, delta: optionalNull(Delta) }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Usage = Schema.StructWithRest(
-  Schema.Struct({
-    ...OpenAIChat.OpenAIChatUsage.schema.fields,
-    prompt_tokens_details: optionalNull(
-      Schema.StructWithRest(
-        Schema.Struct({
-          cached_tokens: optionalNull(Schema.Number),
-          cache_write_tokens: optionalNull(Schema.Number),
-          cache_creation_input_tokens: optionalNull(Schema.Number),
-        }),
-        [Schema.Record(Schema.String, Schema.Unknown)],
-      ),
-    ),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Event = Schema.StructWithRest(
-  Schema.Struct({
-    ...OpenAIChat.OpenAIChatEvent.schema.fields,
-    choices: optionalNull(Schema.Array(Choice)),
-    usage: optionalNull(Usage),
-    error: optionalNull(Schema.Union([Schema.String, OpenAIChat.OpenAIChatEvent.schema.fields.error.schema])),
-    issues: optionalArray(
-      Schema.Struct({
-        message: Schema.String,
-        path: Schema.optional(Schema.Array(Schema.Union([Schema.String, Schema.Number]))),
-      }),
-    ),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-
-interface State {
-  readonly shared: OpenAIChat.ParserState
-  readonly pending: string
-  readonly reasoning: string
-  readonly encrypted: boolean
-  readonly signature?: string
-  readonly tools: Readonly<Record<string, string>>
-}
-
-const MARKER = "__ENCRYPTED_REASONING__"
-
-// ---------------------------------------------------------------------------
-// Request lowering
-// ---------------------------------------------------------------------------
-
-const fromRequest = Effect.fn("VeniceChat.fromRequest")(function* (request: LLMRequest) {
-  const options = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(request.providerOptions ?? {})
-  const body = yield* OpenAIChat.fromRequest(request, {
-    cacheControl: cacheControl(),
-    assistant: (source, message) => {
-      if (message.role !== "assistant") return message
-      const parts = source.content.filter(
-        (part) => part.type === "text" || part.type === "reasoning" || part.type === "tool-call",
-      )
-      const calls = source.content.filter((part) => part.type === "tool-call")
-      const signature = parts
-        .map((part) => part.providerMetadata?.venice?.messageThoughtSignature)
-        .find((value) => typeof value === "string")
-      const raw = parts
-        .map((part) => part.providerMetadata?.venice?.encryptedReasoningContent)
-        .find((value) => typeof value === "string")
-      return {
-        ...message,
-        ...(signature === undefined ? {} : { thought_signature: signature }),
-        ...(raw === undefined ? {} : { reasoning_content: raw }),
-        tool_calls: message.tool_calls?.map((call, index) => {
-          const signature = calls[index]?.providerMetadata?.venice?.thoughtSignature
-          return { ...call, ...(typeof signature === "string" ? { thought_signature: signature } : {}) }
-        }),
-      }
-    },
-  })
-  return {
-    ...body,
-    max_completion_tokens: options.maxCompletionTokens ?? options.maxTokens ?? request.generation?.maxTokens,
-    reasoning_effort: undefined,
-    reasoning:
-      options.reasoningEffort === undefined
-        ? options.reasoning
-        : { ...options.reasoning, effort: options.reasoningEffort },
-    // Match the previous Venice SDK default, not the gateway's added prompt.
-    venice_parameters: Object.fromEntries(
-      Object.entries({
-        ...options.veniceParameters,
-        includeVeniceSystemPrompt: options.veniceParameters?.includeVeniceSystemPrompt ?? false,
-      })
-        .filter(([, value]) => value !== undefined)
-        .map(([key, value]) => [key.replace(/[A-Z]/g, (letter) => `_${letter.toLowerCase()}`), value]),
-    ),
-    prompt_cache_retention: options.promptCacheRetention,
-    parallel_tool_calls: options.parallelToolCalls,
-    min_p: options.minP,
-    top_k: request.generation?.topK,
-    repetition_penalty: options.repetitionPenalty,
-    stop_token_ids: options.stopTokenIds,
-    logprobs: options.logprobs,
-    top_logprobs: options.topLogprobs,
-    max_temp: options.maxTemp,
-    min_temp: options.minTemp,
-    response_format: options.responseFormat,
-    user: options.user,
-  }
-})
-
-// ---------------------------------------------------------------------------
-// Venice normalization around the shared Chat state machine
-// ---------------------------------------------------------------------------
-
-const step = Effect.fn("VeniceChat.step")(function* (state: State, event: typeof Event.Type) {
-  if (typeof event.error === "string")
-    return yield* new AIError({
-      reason: classifyProviderFailure({
-        message: [
-          event.error,
-          ...(event.issues ?? []).map(
-            (issue) => `${issue.path?.length ? `${issue.path.join(".")}: ` : ""}${issue.message}`,
-          ),
-        ].join("; "),
-        rawBody: ProviderShared.encodeJson(event),
-      }),
-    })
-  const delta = event.choices?.[0]?.delta
-  const scalar = delta?.reasoning_content ?? ""
-  const text = state.pending + scalar
-  const marker = text.indexOf(MARKER)
-  const pending =
-    marker >= 0 || state.encrypted
-      ? 0
-      : (Array.from({ length: Math.min(text.length, MARKER.length - 1) }, (_, index) => index + 1)
-          .filter((length) => text.endsWith(MARKER.slice(0, length)))
-          .at(-1) ?? 0)
-  const visible = state.encrypted ? "" : marker >= 0 ? text.slice(0, marker) : text.slice(0, text.length - pending)
-  const result = yield* OpenAIChat.protocol.stream.step(state.shared, {
-    ...event,
-    error: event.error,
-    usage: event.usage
-      ? {
-          ...event.usage,
-          prompt_tokens_details: event.usage.prompt_tokens_details
-            ? {
-                ...event.usage.prompt_tokens_details,
-                cache_write_tokens:
-                  event.usage.prompt_tokens_details.cache_write_tokens ??
-                  event.usage.prompt_tokens_details.cache_creation_input_tokens,
-              }
-            : event.usage.prompt_tokens_details,
-        }
-      : event.usage,
-    choices: event.choices?.map((choice, index) =>
-      index === 0 && choice.delta
-        ? {
-            ...choice,
-            delta: {
-              ...choice.delta,
-              reasoning_content: visible || undefined,
-              // Opaque-only scalar reasoning still needs a canonical part for replay.
-              reasoning_details: choice.delta.reasoning_details ?? (marker >= 0 ? [] : undefined),
-            },
-          }
-        : choice,
-    ),
-  })
-  const tools = { ...state.tools }
-  for (const call of delta?.tool_calls ?? []) {
-    if (!call.thought_signature) continue
-    const index = call.index ?? result[0].latestToolIndex
-    const id =
-      call.id ?? (index === undefined ? undefined : (result[0].tools[index]?.id ?? result[0].pendingTools[index]?.id))
-    if (id) tools[id] = call.thought_signature
-  }
-  return [
-    {
-      shared: result[0],
-      pending: pending ? text.slice(-pending) : "",
-      reasoning: state.reasoning + scalar,
-      encrypted: state.encrypted || marker >= 0,
-      signature: delta?.thought_signature ?? state.signature,
-      tools,
-    },
-    result[1],
-  ] as const
-})
-
-const onHalt = Effect.fn("VeniceChat.onHalt")(function* (state: State) {
-  const events = yield* OpenAIChat.finishEvents(state.shared)
-  return events.flatMap((event): LLMEvent[] => {
-    if (
-      event.type !== "reasoning-end" &&
-      event.type !== "text-end" &&
-      event.type !== "tool-call" &&
-      event.type !== "tool-input-end"
-    )
-      return [event]
-    const signature = event.type === "tool-call" || event.type === "tool-input-end" ? state.tools[event.id] : undefined
-    const providerMetadata = {
-      ...event.providerMetadata,
-      venice: {
-        ...event.providerMetadata?.venice,
-        ...(state.signature ? { messageThoughtSignature: state.signature } : {}),
-        ...(signature ? { thoughtSignature: signature } : {}),
-        ...(event.type === "reasoning-end" && state.encrypted ? { encryptedReasoningContent: state.reasoning } : {}),
-      },
-    }
-    if (event.type === "reasoning-end" && state.pending)
-      return [LLMEvent.reasoningDelta({ id: event.id, text: state.pending }), { ...event, providerMetadata }]
-    return [{ ...event, providerMetadata }]
-  })
-})
-
-export const compatibility = {
-  maxTokensField: "max_completion_tokens",
-  supportsStore: false,
-  supportsPromptCacheKey: true,
-} satisfies LanguageModelCompatibility
-
-export const protocol = Protocol.make({
-  id: "venice-chat",
-  body: { schema: Body, from: fromRequest },
-  stream: {
-    event: Schema.Union([Schema.Literal("[DONE]"), Protocol.jsonEvent(Event)]),
-    initial: (request): State => ({
-      shared: OpenAIChat.protocol.stream.initial(request),
-      pending: "",
-      reasoning: "",
-      encrypted: false,
-      tools: {},
-    }),
-    step: (state: State, event) => (event === "[DONE]" ? Effect.succeed([state, []] as const) : step(state, event)),
-    terminal: (event) => event === "[DONE]",
-    onHalt,
-  },
-})
-
-export * as VeniceChat from "./venice-chat.js"
@@ -31,12 +31,19 @@ const XAIResponsesHostedToolItem = Schema.Union([
  ),
 ])

+const XAIResponsesBody = Schema.Struct({
+  ...OpenResponses.coreFields,
+  input: Schema.Array(Schema.Union([OpenResponses.InputItem, XAIResponsesHostedToolItem])),
+  stream: Schema.Literal(true),
+})
+
 const adapter = {
  id: ADAPTER,
  name: NAME,
  restoreHostedToolItem: (item: unknown) => (Schema.is(XAIResponsesHostedToolItem)(item) ? item : undefined),
 } satisfies OpenResponses.ProviderAdapter

+const decodeBody = ProviderShared.validateWith(Schema.decodeUnknownEffect(XAIResponsesBody))
 const fromRequest = Effect.fn("XAIResponses.fromRequest")(function* (request: LLMRequest) {
  if (request.providerOptions?.contextManagement !== undefined)
    return yield* ProviderShared.unsupportedOperation({
@@ -46,7 +53,7 @@ const fromRequest = Effect.fn("XAIResponses.fromRequest")(function* (request: LL
      message:
        "xAI requires explicit compaction through LLMClient.compact; automatic context management is not supported",
    })
-  return yield* OpenResponses.fromRequestWithAdapter(request, adapter)
+  return yield* decodeBody(yield* OpenResponses.fromRequestWithAdapter(request, adapter))
 })

 const HOSTED_TOOLS = {
@@ -76,7 +83,7 @@ const step = (state: OpenResponses.ParserState, input: OpenResponses.Event) => {
 export const protocol = Protocol.make({
  id: ADAPTER,
  body: {
-    schema: OpenResponses.OpenResponsesBody,
+    schema: XAIResponsesBody,
    from: fromRequest,
  },
  stream: {
@@ -1,20 +1,15 @@
 import { Route, type RouteDefaultsInput } from "../route/client.js"
 import { Endpoint } from "../route/endpoint.js"
 import type { ProviderPackage } from "../provider-package.js"
-import { AnthropicMessages } from "../protocols/anthropic-messages.js"
 import { OpenAIChat } from "../protocols/openai-chat.js"
 import { OpenResponses } from "../protocols/open-responses.js"
 import { BedrockAuth, type Credentials } from "../protocols/utils/bedrock-auth.js"
-import { claudeVersion } from "../protocols/utils/claude-model.js"
 import { ProviderConfigurationError, ProviderID, type ModelID } from "../schema/index.js"
 import { withOpenAIOptions, type OpenAIProviderOptionsInput } from "./openai-options.js"

 export const id = ProviderID.make("amazon-bedrock")

-export type OpenAIOptionsInput = OpenAIProviderOptionsInput
-export type MessagesOptionsInput = AnthropicMessages.ProviderOptionsInput
-
-export type Config = Omit<RouteDefaultsInput, "providerOptions"> & {
+export type Config = RouteDefaultsInput & {
  /** Bedrock API key. Falls back to `AWS_BEARER_TOKEN_BEDROCK`; bearer auth takes precedence over SigV4. */
  readonly apiKey?: string
  /** `sigv4` ignores `apiKey` fallbacks from the environment; `bearer` requires a token. */
@@ -25,11 +20,11 @@ export type Config = Omit<RouteDefaultsInput, "providerOptions"> & {
  /** Shared config profile for the default credential chain. */
  readonly profile?: string
  readonly region?: string
-  readonly providerOptions?: OpenAIProviderOptionsInput | AnthropicMessages.ProviderOptionsInput
+  readonly providerOptions?: OpenAIProviderOptionsInput
 }

-export type Settings<Options = OpenAIProviderOptionsInput> = ProviderPackage.Settings &
-  Options & {
+export type Settings = ProviderPackage.Settings &
+  OpenAIProviderOptionsInput & {
    readonly apiKey?: string
    readonly auth?: "bearer" | "sigv4"
    readonly baseURL?: string
@@ -39,8 +34,6 @@ export type Settings<Options = OpenAIProviderOptionsInput> = ProviderPackage.Set
    readonly topP?: number
  }

-export type MessagesSettings = Settings<AnthropicMessages.ProviderOptionsInput>
-
 const responsesRoute = Route.make({
  id: "bedrock-mantle-responses",
  provider: id,
@@ -57,35 +50,12 @@ const chatRoute = OpenAIChat.route.with({
  providerMetadataKey: "mantle",
 })

-const messagesRoute = Route.make({
-  id: "bedrock-mantle-messages",
-  provider: id,
-  providerMetadataKey: "mantle",
-  protocol: {
-    ...AnthropicMessages.protocol,
-    // Mantle rejects mid-conversation `output_config` on Opus 5.0; support starts at 5.1+.
-    supportsEffortUpdates: (request) => {
-      const override = request.model.compatibility?.supportsEffortUpdates
-      if (override !== undefined) return override
-      const version = claudeVersion(request.model.id)
-      return version !== undefined && (version.major > 5 || (version.major === 5 && version.minor >= 1))
-    },
-  },
-  endpoint: Endpoint.path(AnthropicMessages.PATH),
-  transport: AnthropicMessages.transport<AnthropicMessages.AnthropicMessagesBody>(),
-  headers: () => ({ "anthropic-version": "2023-06-01" }),
-})
+export const routes = [responsesRoute, chatRoute]

-export const routes = [responsesRoute, chatRoute, messagesRoute]
-
-const configuredRoute = <Body, Prepared>(
-  route: Route<Body, Prepared>,
-  input: Config,
-  defaultBaseURL = (region: string) => `https://bedrock-mantle.${region}.api.aws/v1`,
-) => {
+const configuredRoute = <Body, Prepared>(route: Route<Body, Prepared>, input: Config) => {
  const region = BedrockAuth.resolveRegion(input)
  return route.with({
-    endpoint: { baseURL: input.baseURL ?? defaultBaseURL(region) },
+    endpoint: { baseURL: input.baseURL ?? `https://bedrock-mantle.${region}.api.aws/v1` },
    auth: BedrockAuth.resolveAuth(input, region, {
      service: "bedrock-mantle",
      name: "Bedrock Mantle",
@@ -117,11 +87,6 @@ export const configure = (input: Config = {}) => {
    })
  const configuredResponsesRoute = configuredRoute(responsesRoute, input)
  const configuredChatRoute = configuredRoute(chatRoute, input)
-  const configuredMessagesRoute = configuredRoute(
-    messagesRoute,
-    input,
-    (region) => `https://bedrock-mantle.${region}.api.aws/anthropic/v1`,
-  )
  const modelDefaults = defaults(input)
  const responses = (modelID: string | ModelID) =>
    configuredResponsesRoute
@@ -131,14 +96,11 @@ export const configure = (input: Config = {}) => {
    configuredChatRoute
      .with(withOpenAIOptions(modelID, modelDefaults))
      .model<OpenAIProviderOptionsInput>({ id: modelID })
-  const messages = (modelID: string | ModelID) =>
-    configuredMessagesRoute.with(modelDefaults).model<AnthropicMessages.ProviderOptionsInput>({ id: modelID })

  return {
    id,
    model: responses,
    chat,
-    messages,
    responses,
    configure,
  }
@@ -157,7 +119,7 @@ const fromSettings = ({
  region,
  topP,
  ...providerOptions
-}: Settings<Config["providerOptions"]>) =>
+}: Settings) =>
  configure({
    apiKey,
    auth,
@@ -175,10 +137,6 @@ export const chatModel: ProviderPackage.Definition<Settings, OpenAIProviderOptio
  modelID,
  settings,
 ) => fromSettings(settings).chat(modelID)
-export const messagesModel: ProviderPackage.Definition<
-  MessagesSettings,
-  AnthropicMessages.ProviderOptionsInput
->["model"] = (modelID, settings) => fromSettings(settings).messages(modelID)
 export const responsesModel: ProviderPackage.Definition<Settings, OpenAIProviderOptionsInput>["model"] = (
  modelID,
  settings,
@@ -1,2 +0,0 @@
-export { messagesModel as model } from "../../amazon-bedrock-mantle.js"
-export type { MessagesSettings as Settings } from "../../amazon-bedrock-mantle.js"
@@ -5,7 +5,6 @@ import { MediaRoute } from "../route/media.js"
 import type { ProviderPackage } from "../provider-package.js"
 import { ProviderID, type ModelID } from "../schema/index.js"
 import { Gemini } from "../protocols/gemini.js"
-import { GoogleInteractions } from "../protocols/google-interactions.js"
 import { GoogleImages } from "../protocols/google-images.js"
 import { GoogleSpeech } from "../protocols/google-speech.js"
 import { GoogleTranscription } from "../protocols/google-transcription.js"
@@ -17,16 +16,15 @@ export type { GoogleTranscriptionOptions } from "../protocols/google-transcripti
 export type { GoogleVideoOptions } from "../protocols/google-video.js"
 export type GeminiOptionsInput = Gemini.OptionsInput
 export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
-export type GoogleInteractionsOptionsInput = GoogleInteractions.OptionsInput

 export const id = ProviderID.make("google")

-export const routes = [Gemini.route, GoogleInteractions.route]
+export const routes = [Gemini.route]

 export type Config = RouteDefaultsInput &
  ProviderAuthOption<"optional"> & {
    readonly baseURL?: string
-    readonly providerOptions?: Gemini.ProviderOptionsInput & GoogleInteractions.ProviderOptionsInput
+    readonly providerOptions?: Gemini.ProviderOptionsInput
  }

 export type Settings = ProviderPackage.Settings &
@@ -47,19 +45,12 @@ const configuredRoute = (input: Config) => {
  return Gemini.route.with({ ...rest, endpoint: { baseURL }, auth: auth(input) })
 }

-const interactionsRoute = (input: Config) => {
-  const { apiKey: _, auth: _auth, baseURL, ...rest } = input
-  return GoogleInteractions.route.with({ ...rest, endpoint: { baseURL }, auth: auth(input) })
-}
-
 export const configure = (input: Config = {}) => {
  const route = configuredRoute(input)
  const media = MediaRoute.deployment(input, auth(input))
  return {
    id,
    model: (modelID: string | ModelID) => route.model<Gemini.ProviderOptionsInput>({ id: modelID }),
-    interactions: (modelID: string | ModelID) =>
-      interactionsRoute(input).model<GoogleInteractions.ProviderOptionsInput>({ id: modelID }),
    image: (modelID: string | ModelID) => GoogleImages.model({ ...media, id: modelID }),
    video: (modelID: string | ModelID) => GoogleVideo.model({ ...media, id: modelID }),
    speech: (modelID: string | ModelID) => GoogleSpeech.model({ ...media, id: modelID }),
@@ -82,7 +73,6 @@ export const model: ProviderPackage.Definition<Settings, Gemini.ProviderOptionsI
  }).model(modelID)

 export const image = provider.image
-export const interactions = provider.interactions
 export const video = provider.video
 export const speech = provider.speech
 export const transcription = provider.transcription
@@ -1,21 +0,0 @@
-import { configure } from "../google.js"
-import type { ProviderPackage } from "../../provider-package.js"
-import type { GoogleInteractions } from "../../protocols/google-interactions.js"
-
-export type Settings = ProviderPackage.Settings &
-  GoogleInteractions.ProviderOptionsInput & {
-    readonly apiKey?: string
-    readonly baseURL?: string
-  }
-
-export const model: ProviderPackage.Definition<Settings, GoogleInteractions.ProviderOptionsInput>["model"] = (
-  modelID,
-  { apiKey, baseURL, body, headers, ...providerOptions },
-) =>
-  configure({
-    apiKey,
-    baseURL,
-    headers: headers === undefined ? undefined : { ...headers },
-    http: body === undefined ? undefined : { body: { ...body } },
-    providerOptions,
-  }).interactions(modelID)
@@ -40,7 +40,6 @@ export * as Stability from "./stability.js"
 export * as TogetherAI from "./togetherai.js"
 export * as TypeSafeAI from "./typesafe-ai.js"
 export * as VercelAIGateway from "./vercel-ai-gateway.js"
-export * as Venice from "./venice.js"
 export * as XAI from "./xai.js"
 export * as ZAI from "./zai.js"
 export * as ZAICodingPlan from "./zai-coding-plan.js"
@@ -50,7 +50,7 @@ export const gpt5DefaultOptions = (modelID: string): ProviderOptions | undefined
 export const openAIDefaultOptions = (modelID: string): ProviderOptions | undefined =>
  mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID))

-export const withOpenAIOptions = <Options extends { readonly providerOptions?: ProviderOptions }>(
+export const withOpenAIOptions = <Options extends { readonly providerOptions?: OpenAIProviderOptionsInput }>(
  modelID: string,
  options: Options,
 ): Omit<Options, "providerOptions"> & { readonly providerOptions?: ProviderOptions } => {
@@ -1,62 +0,0 @@
-import type { ProviderPackage } from "../provider-package.js"
-import { VeniceChat } from "../protocols/venice-chat.js"
-import { OpenAIChat } from "../protocols/openai-chat.js"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { Route, type RouteDefaultsInput } from "../route/client.js"
-import { Endpoint } from "../route/endpoint.js"
-import { ProviderID, type ModelID } from "../schema/index.js"
-
-export const id = ProviderID.make("venice")
-export type ChatOptionsInput = VeniceChat.OptionsInput
-export type Config = Omit<RouteDefaultsInput, "providerOptions"> &
-  ProviderAuthOption<"optional"> & {
-    readonly baseURL?: string
-    readonly queryParams?: Readonly<Record<string, string>>
-    readonly providerOptions?: ChatOptionsInput
-  }
-export type Settings = ProviderPackage.Settings &
-  ChatOptionsInput & {
-    readonly apiKey?: string
-    readonly baseURL?: string
-    readonly queryParams?: Readonly<Record<string, string>>
-  }
-
-const route = Route.make({
-  id: "venice-chat",
-  provider: id,
-  providerMetadataKey: "venice",
-  protocol: VeniceChat.protocol,
-  endpoint: Endpoint.path("/chat/completions", { baseURL: "https://api.venice.ai/api/v1" }),
-  framing: OpenAIChat.framing,
-})
-export const routes = [route]
-
-export const configure = (input: Config = {}) => {
-  const { apiKey: _apiKey, auth: _auth, baseURL, queryParams, ...rest } = input
-  const chat = (modelID: string | ModelID) =>
-    route
-      .with({
-        ...rest,
-        endpoint: { baseURL: baseURL ?? route.endpoint.baseURL, query: queryParams },
-        auth: AuthOptions.bearer(input, "VENICE_API_KEY"),
-      })
-      .model<ChatOptionsInput>({ id: modelID, compatibility: VeniceChat.compatibility })
-  return { id, model: chat, chat, configure }
-}
-
-export const provider = configure()
-export const chat = provider.chat
-export const model: ProviderPackage.Definition<Settings, ChatOptionsInput>["model"] = (
-  modelID,
-  { apiKey, baseURL, queryParams, body, headers, ...providerOptions },
-) =>
-  configure({
-    apiKey,
-    baseURL,
-    queryParams,
-    headers,
-    http: body === undefined ? undefined : { body: { ...body } },
-    providerOptions,
-  }).model(modelID)
-
-export * as Venice from "./venice.js"
@@ -358,6 +358,7 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
  input: MakeTransportInput<Body, Prepared, Frame, Event, State>,
 ): Route<Body, Prepared> {
  const protocol = input.protocol
+  const encodeBody = Schema.encodeSync(Schema.fromJsonString(protocol.body.schema))
  const decodeEventEffect = Schema.decodeUnknownEffect(protocol.stream.event)
  const decodeEvent = (route: string) => (frame: Frame) =>
    decodeEventEffect(frame).pipe(
@@ -416,7 +417,7 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
          request,
          endpoint: routeInput.endpoint,
          auth: routeInput.auth ?? Auth.none,
-          encodeBody: ProviderShared.encodeJson,
+          encodeBody,
          middleware: options?.http,
          webSocket: options?.webSocket,
        }),
@@ -575,7 +576,9 @@ const compile = Effect.fn("LLM.compile")(function* (request: LLMRequest, options
  const resolved = prepareRequest(request)
  const route = resolved.model.route

-  const body = yield* route.body.from(resolved)
+  const body = yield* route.body
+    .from(resolved)
+    .pipe(Effect.flatMap(ProviderShared.validateWith(Schema.decodeUnknownEffect(route.body.schema))))
  const prepared = yield* route.prepareTransport(body, resolved, options)

  return {
@@ -1,5 +1,5 @@
 import { Effect, Stream } from "effect"
-import { makeParser } from "effect/unstable/encoding/Sse"
+import { makeParser, type Event } from "effect/unstable/encoding/Sse"
 import { AIError, InvalidProviderOutputError } from "../schema/index.js"

 /**
@@ -42,39 +42,43 @@ export const sseFraming = (
    Stream.decodeText(),
    Stream.mapAccumEffect(
      () => {
-        const output: string[] = []
+        const output: Event[] = []
        return {
          output,
          parser: makeParser((event) => {
-            if (
-              event._tag === "Event" &&
-              (events === undefined || events.has(event.event)) &&
-              event.data.length > 0 &&
-              // Some OpenAI-compatible proxies serialize an empty flush as a bare
-              // `data: null`, between events or after `[DONE]`. No protocol has a
-              // null event, so it carries nothing and must not abort the stream.
-              event.data !== "null" &&
-              // Vertex AI partner models (e.g. `xai/grok-4.6`) send their SSE
-              // keepalive comment as `data: : keepalive` while reasoning.
-              event.data !== ": keepalive" &&
-              (event.data !== "[DONE]" || includeDone || (events !== undefined && event.event !== "message"))
-            )
-              output.push(event.data)
+            if (event._tag === "Event") output.push(event)
          }),
        }
      },
-      (state, chunk) => {
-        const error = state.parser.feed(chunk)
-        if (!error) return Effect.succeed([state, state.output.splice(0)] as const)
-        const reason = new InvalidProviderOutputError({
-          route: "sse",
-          message: error.message,
-          body: chunk,
-          cause: error,
-        })
-        return Effect.fail(new AIError({ reason }))
-      },
+      (state, chunk) =>
+        Effect.gen(function* () {
+          const error = state.parser.feed(chunk)
+          if (error)
+            return yield* new AIError({
+              reason: new InvalidProviderOutputError({
+                route: "sse",
+                message: error.message,
+                body: chunk,
+                cause: error,
+              }),
+            })
+          return [state, state.output.splice(0)] as const
+        }),
    ),
+    Stream.filter(
+      (event) =>
+        (events === undefined || events.has(event.event)) &&
+        event.data.length > 0 &&
+        // Some OpenAI-compatible proxies serialize an empty flush as a bare
+        // `data: null`, between events or after `[DONE]`. No protocol has a
+        // null event, so it carries nothing and must not abort the stream.
+        event.data !== "null" &&
+        // Vertex AI partner models (e.g. `xai/grok-4.6`) send their SSE
+        // keepalive comment as `data: : keepalive` while reasoning.
+        event.data !== ": keepalive" &&
+        (event.data !== "[DONE]" || includeDone || (events !== undefined && event.event !== "message")),
+    ),
+    Stream.map((event) => event.data),
  )

 /** Server-Sent Events framing. Used by every JSON-streaming HTTP provider. */
@@ -14,6 +14,7 @@ import * as GoogleVertexChat from "../src/providers/google-vertex-chat.js"
 import * as GoogleVertexMessages from "../src/providers/google-vertex-messages.js"
 import * as GoogleVertexResponses from "../src/providers/google-vertex-responses.js"
 import * as OpenAI from "../src/providers/openai.js"
+import * as OpenAICompatible from "../src/providers/openai-compatible.js"
 import * as OpenRouter from "../src/providers/openrouter.js"
 import * as XAI from "../src/providers/xai.js"

@@ -1,12 +1,13 @@
 import { describe, expect, test } from "bun:test"
 import { Effect } from "effect"
-import { LLM, Message, ToolCallPart } from "../src/index.js"
+import { LLM, LLMRequest, Message, ToolCallPart } from "../src/index.js"
 import { Auth, LLMClient } from "../src/route.js"
 import { compileRequest } from "../src/route/client.js"
 import { AnthropicMessages } from "../src/protocols/anthropic-messages.js"
 import { OpenAIResponses } from "../src/protocols/openai-responses.js"
 import { Gemini } from "../src/protocols/gemini.js"
-import { AmazonBedrockMantle, GoogleVertexMessages, OpenAI } from "../src/providers.js"
+import { GoogleVertexMessages, OpenAI } from "../src/providers.js"
+import { applyCachePolicy } from "../src/cache-policy.js"
 import { applyEffortUpdates } from "../src/effort-updates.js"
 import { it, testEffect } from "./lib/effect.js"
 import { dynamicResponse } from "./lib/http.js"
@@ -171,33 +172,6 @@ describe("Anthropic Messages effort updates", () => {
    }),
  )

-  it.effect("releases a held system update next to an effort marker as one valid section", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: opus5,
-          messages: [
-            Message.user("Fix it."),
-            Message.assistant("Done."),
-            lowFromHigh,
-            Message.system("Update."),
-            Message.user("Next."),
-          ],
-          providerOptions: { effort: "low" },
-          cache: "none",
-        }),
-      )
-
-      expect(prepared.body.messages).toEqual([
-        { role: "user", content: [{ type: "text", text: "Fix it." }] },
-        { role: "assistant", content: [{ type: "text", text: "Done." }] },
-        { role: "system", content: [], output_config: { effort: "low" } },
-        { role: "user", content: [{ type: "text", text: "Next." }] },
-        { role: "system", content: [{ type: "text", text: "Update.", cache_control: undefined }] },
-      ])
-    }),
-  )
-
  it.effect("falls back to a plain top-level effort when history drifted from the current effort", () =>
    Effect.gen(function* () {
      const drifted = yield* compileRequest(
@@ -268,31 +242,6 @@ describe("Anthropic Messages effort updates", () => {
    }),
  )

-  it.effect("strips markers for Opus 5.0 on Bedrock Mantle Messages while lowering Opus 5.5", () =>
-    Effect.gen(function* () {
-      const mantle = AmazonBedrockMantle.configure({ apiKey: "test", region: "us-east-1" })
-      const opus50 = yield* compileRequest(
-        LLM.request({
-          model: mantle.messages("anthropic.claude-opus-5"),
-          messages: conversation,
-          providerOptions: { effort: "low" },
-        }),
-      )
-      const opus55 = yield* compileRequest(
-        LLM.request({
-          model: mantle.messages("anthropic.claude-opus-5-5"),
-          messages: conversation,
-          providerOptions: { effort: "low" },
-        }),
-      )
-
-      expect(systemMessages(opus50.body)).toHaveLength(0)
-      expect(opus50.body.output_config).toEqual({ effort: "low" })
-      expect(systemMessages(opus55.body)).toEqual([{ role: "system", content: [], output_config: { effort: "low" } }])
-      expect(opus55.body.output_config).toEqual({ effort: "high" })
-    }),
-  )
-
  it.effect("strips markers on the Vertex Anthropic route, whose protocol wrapper does not forward support", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/accepts-malformed-assistant-tool-order-with-default-patch",
+    "recordedAt": "2026-05-05T20:09:16.245Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01SikJVFaMR1XLMtavUhvuog\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":638,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":1,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}               }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}          }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"The\"}     }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\" weather in Paris is currently 72°F.\"}        }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":638,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":14}              }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"             }\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,56 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/claude-opus-4-7-drives-a-tool-loop",
+    "recordedAt": "2026-05-03T19:59:44.186Z",
+    "tags": [
+      "prefix:anthropic-messages",
+      "provider:anthropic",
+      "protocol:anthropic-messages",
+      "tool",
+      "tool-loop",
+      "golden",
+      "flagship"
+    ]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-opus-4-7\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool, then answer in one short sentence.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-opus-4-7\",\"id\":\"msg_01DgAEgLgB1ZhavZon4qGE1t\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":798,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":0,\"service_tier\":\"standard\",\"inference_geo\":\"global\"}}    }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}}              }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \"}              }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"Pa\"}    }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"ris\\\"}\"}  }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0           }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":798,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":66}             }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"            }\n\n"
+      }
+    },
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-opus-4-7\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool, then answer in one short sentence.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-opus-4-7\",\"id\":\"msg_011KJqj32QjkrUAiBFxhmEoG\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":895,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":5,\"service_tier\":\"standard\",\"inference_geo\":\"global\"}}       }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}            }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Paris is curr\"}   }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ently sunny at 22°C.\"}           }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0        }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":895,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":19}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/rejects-malformed-assistant-tool-order-without-patch",
+    "recordedAt": "2026-05-05T20:08:42.597Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool", "sad-path"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}},{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
+      },
+      "response": {
+        "status": 400,
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"type\":\"error\",\"error\":{\"type\":\"invalid_request_error\",\"message\":\"messages.1: `tool_use` ids were found without `tool_result` blocks immediately after: call_1. Each `tool_use` block must have a corresponding `tool_result` block in the next message.\"},\"request_id\":\"req_011Cak2XdJgnzxKCY2BC2Beh\"}"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/streams-text",
+    "recordedAt": "2026-04-28T21:18:45.535Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"You are concise.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply with exactly: Hello!\"}]}],\"stream\":true,\"max_tokens\":20,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01UodR8c3ezAK8rAfi8HAs8g\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":18,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":2,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}          }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}    }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Hello!\"}    }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0   }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":18,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":5}             }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"         }\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/streams-tool-call",
+    "recordedAt": "2026-04-28T21:18:46.878Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"Call tools exactly as requested.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Call get_weather with city exactly Paris.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"tool_choice\":{\"type\":\"tool\",\"name\":\"get_weather\"},\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01RYgU7NUPMK4B9v8S7gVpCS\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":16,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}             }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_012rmAruviySvUXSjgCPWVRu\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}}      }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"}             }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\":\"}    }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\" \\\"Paris\\\"}\"}     }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0     }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":33}              }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"     }\n\n"
+      }
+    }
+  ]
+}
@@ -1,57 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "anthropic.claude-opus-5-5",
-    "tags": [
-      "prefix:bedrock-mantle-messages",
-      "provider:amazon-bedrock",
-      "protocol:anthropic-messages",
-      "reasoning",
-      "effort-update"
-    ],
-    "name": "bedrock-mantle-messages/applies-mid-conversation-effort-updates-and-thinking-block-binding-on-opus-5-5",
-    "recordedAt": "2026-10-04T03:56:23.139Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://bedrock-mantle.us-east-1.api.aws/anthropic/v1/messages",
-        "headers": {
-          "anthropic-beta": "interleaved-thinking-2025-05-14,thinking-binding-controls-2026-08-01",
-          "anthropic-version": "2023-06-01",
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"anthropic.claude-opus-5-5\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Compute 37 * 43 step by step, then reply with only the integer.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"stream\":true,\"max_tokens\":2048,\"thinking\":{\"type\":\"adaptive\",\"display\":\"summarized\",\"block_binding\":{\"prefix_mismatch_behavior\":\"drop_block\"}},\"output_config\":{\"effort\":\"high\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
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-{
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1) × \"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"23\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"\\n= 20 × 23 \"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"- 23\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"\\n= 460 - 23\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"\\n= 437\\n\\nSo\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\" the\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\" answer is 437.\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"signature_delta\",\"signature\":\"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\"}}\n\nevent: content_block_stop\ndata: {Line truncated
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-{
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@@ -1,37 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
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-    "tags": [
-      "prefix:bedrock-mantle-messages",
-      "provider:amazon-bedrock",
-      "protocol:anthropic-messages",
-      "reasoning",
-      "effort-update"
-    ],
-    "name": "bedrock-mantle-messages/strips-unsupported-mid-conversation-effort-updates-on-opus-5-0",
-    "recordedAt": "2026-10-04T03:56:23.956Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
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-        "url": "https://bedrock-mantle.us-east-1.api.aws/anthropic/v1/messages",
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-          "anthropic-version": "2023-06-01",
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-        },
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-}
@@ -6,7 +6,7 @@
      "provider:cohere"
    ],
    "name": "cohere/continues-a-native-tool-call",
-    "recordedAt": "2026-10-03T04:09:51.600Z"
+    "recordedAt": "2026-10-02T02:36:16.143Z"
  },
  "interactions": [
    {
@@ -17,14 +17,14 @@
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{\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" have\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" access\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" to\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" a\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" get\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\"_weather\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" function\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" that\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" takes\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" a\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" city\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" parameter\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\".\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" The\"}}}}\n\nevent: content-delta\ndata: 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{\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" tool\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" exactly\"}}}}\n\nevent: conteLine truncated
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    },
    {
@@ -35,14 +35,14 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"command-a-plus-05-2026\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once.\"},{\"type\":\"text\",\"text\":\"After the tool result, reply exactly: Paris is sunny.\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"thinking\",\"thinking\":\"The user is asking for the weather in Paris. I have a get_weather function available that takes a city parameter. The user specifically mentioned \\\"Paris\\\" as the city. I need to use the get_weather tool exactly once as per the policies, and I have all the required parameters (city = \\\"Paris\\\").\\n\\nLet me call the function with the city parameter set to \\\"Paris\\\".\"}],\"tool_calls\":[{\"id\":\"get_weather_vfp5ryredwrg\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"}}]},{\"role\":\"tool\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\",\"tool_call_id\":\"get_weather_vfp5ryredwrg\"}],\"stream\":true,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}}],\"max_tokens\":2048}"
+        "body": "{\"model\":\"command-a-plus-05-2026\",\"messages\":[{\"role\":\"system\",\"content\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\"},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"thinking\",\"thinking\":\"The user is asking about the weather in Paris. I have access to a get_weather function that takes a city parameter. The instructions say to use the get_weather tool exactly once, and then reply exactly \\\"Paris is sunny\\\" after getting the tool result.\\n\\nLet me call the get_weather function with \\\"Paris\\\" as the city parameter.\"}],\"tool_calls\":[{\"id\":\"get_weather_mdhvw7kbf1e3\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"}}]},{\"role\":\"tool\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\",\"tool_call_id\":\"get_weather_mdhvw7kbf1e3\"}],\"stream\":true,\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}}],\"max_tokens\":2048}"
      },
      "response": {
        "status": 200,
        "headers": {
          "content-type": "text/event-stream"
        },
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@@ -1,66 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/continues-tool-results-with-previous-interaction-id",
-    "recordedAt": "2026-10-03T18:10:17.900Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]}],\"stream\":true,\"store\":true,\"system_instruction\":\"Use get_weather for weather questions. Answer concisely after receiving the result.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"generation_config\":{\"max_output_tokens\":2048,\"thinking_level\":\"low\",\"tool_choice\":\"any\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: interaction.created\ndata: {\"interaction\":{\"id\":\"v1_ChdCMFhCYXRqeURhVDdxdHNQNWJLTXNBURIXQjBYQmF0anlEYVQ3cXRzUDViS01zQVE\",\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"interaction_id\":\"v1_ChdCMFhCYXRqeURhVDdxdHNQNWJLTXNBURIXQjBYQmF0anlEYVQ3cXRzUDViS01zQVE\",\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"EoACCv0BAWkUfRMR9cx79IeL9V4HvDAHann4OEdOjz7FebGRwlCFGJHqLGG1lG1d+9xzzyPXN0d60gjMwbeix1bE4cCckDeMV0vAkOfR/epPhvmcfI+vWK1nURu+3UcgUBQ9on4VlZFcnOg7SoihuvxuQB4qqT65EAyqi8ybd3P8NB+V/FNcTBvMmJuNNCNxI5KgwsHjdT+xLdssTieljIG3H99rSz3/Nv90dYEJIr0WsQ1a3ZevpD6gPts/8Id/Z92zQ3aq4LAr47rdItCVF5h63Lchi9QFrav5LGf6lNVAOnlHIyXBrlAnVbdLsAdzlemlHY+oIWNMncL/NKayCt+qvQ==\",\"type\":\"thought_signature\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":0,\"event_type\":\"step.stop\"}\n\nevent: step.start\ndata: {\"index\":1,\"step\":{\"id\":\"call_326996\",\"signature\":\"AWkUfRMR9cx79IeL9V4HvDAHann4OEdOjz7FebGRwlCFGJHqLGG1lG1d+9xzzyPXN0d60gjMwbeix1bE4cCckDeMV0vAkOfR/epPhvmcfI+vWK1nURu+3UcgUBQ9on4VlZFcnOg7SoihuvxuQB4qqT65EAyqi8ybd3P8NB+V/FNcTBvMmJuNNCNxI5KgwsHjdT+xLdssTieljIG3H99rSz3/Nv90dYEJIr0WsQ1a3ZevpD6gPts/8Id/Z92zQ3aq4LAr47rdItCVF5h63Lchi9QFrav5LGf6lNVAOnlHIyXBrlAnVbdLsAdzlemlHY+oIWNMncL/NKayCt+qvQ==\",\"type\":\"function_call\",\"name\":\"get_weather\",\"arguments\":{}},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\",\"type\":\"arguments_delta\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":1,\"event_type\":\"step.stop\"}\n\nevent: interaction.completed\ndata: {\"interaction\":{\"id\":\"v1_ChdCMFhCYXRqeURhVDdxdHNQNWJLTXNBURIXQjBYQmF0anlEYVQ3cXRzUDViS01zQVE\",\"status\":\"requires_action\",\"usage\":{\"total_tokens\":114,\"total_input_tokens\":68,\"input_tokens_by_modality\":[{\"modality\":\"text\",\"tokens\":68}],\"total_cached_tokens\":0,\"total_output_tokens\":16,\"total_tool_use_tokens\":0,\"total_thought_tokens\":30,\"raw_prompt_token\":107,\"model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":107}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":22}],\"thoughts_tokens_details\":[{\"modality\":\"text\",\"tokens\":30}]}],\"non_grounding_model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":107}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":22}],\"thoughts_tokens_details\":[{\"modality\":\"text\",\"tokens\":30}]}]},\"created\":\"2026-10-03T18:10:16Z\",\"updated\":\"2026-10-03T18:10:16Z\",\"service_tier\":\"standard\",\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.completed\"}\n\nevent: done\ndata: [DONE]\n\n"
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
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-{
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-  "metadata": {
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-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
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-}
@@ -1,32 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
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-    "name": "google-interactions/streams-reasoning-and-retains-thought-signatures",
-    "recordedAt": "2026-10-03T18:08:37.674Z"
-  },
-  "interactions": [
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-      "transport": "http",
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-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
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-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"Find the smallest positive integer that leaves remainder 1 modulo 7, 2 modulo 9, and 3 modulo 11. Explain briefly.\"}]}],\"stream\":true,\"store\":false,\"generation_config\":{\"max_output_tokens\":4096,\"thinking_level\":\"high\",\"thinking_summaries\":\"auto\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: interaction.created\ndata: {\"interaction\":{\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"content\":{\"text\":\"**Analyzing Congruences**\\n\\nI'm tackling a system of congruences to find the smallest positive integer x. Currently, I'm reviewing the Chinese Remainder Theorem as a potential solution, or considering a direct congruence-based approach. The congruences are as follows: $x \\\\equiv 1 \\\\pmod{7}$, $x \\\\equiv 2 \\\\pmod{9}$, $x \\\\equiv 3 \\\\pmod{11}$. 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I simplified the expression to 8k ≡ 7 (mod 11) and am looking to multiply both sides to eliminate the coefficient of k.\\n\\n\\n\",\"type\":\"text\"},\"type\":\"thought_summary\"},\"event_type\":\"step.delta\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"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 truncated
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@@ -1,32 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/streams-text-and-reports-usage",
-    "recordedAt": "2026-10-03T18:08:32.334Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"Reply with exactly one word: hello\"}]}],\"stream\":true,\"store\":false,\"generation_config\":{\"max_output_tokens\":2048,\"thinking_level\":\"low\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
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+}
@@ -1,75 +0,0 @@
-{
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-}
@@ -1,75 +0,0 @@
-{
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-  "metadata": {
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-    "tags": [
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-      "provider:venice",
-      "protocol:venice-chat",
-      "reasoning",
-      "tool",
-      "tool-loop",
-      "continuation",
-      "usage",
-      "scalar"
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-    "name": "venice-chat/deepseek-v4-flash-preserves-reasoning-through-a-tool-loop-and-follow-up",
-    "recordedAt": "2026-10-05T02:59:53.799Z"
-  },
-  "interactions": [
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-      "transport": "http",
-      "request": {
-        "method": "POST",
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-        "headers": {
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-      },
-      "response": {
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-        "headers": {
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-      }
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-    {
-      "transport": "http",
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-    }
-  ]
-}
@@ -1,75 +0,0 @@
-{
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-  "metadata": {
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-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "reasoning",
-      "tool",
-      "tool-loop",
-      "continuation",
-      "usage",
-      "details"
-    ],
-    "name": "venice-chat/gemini-3-1-pro-preview-preserves-reasoning-through-a-tool-loop-and-follow-up",
-    "recordedAt": "2026-10-05T03:00:58.104Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
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-        },
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@@ -1,71 +0,0 @@
-{
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-      "provider:venice",
-      "protocol:venice-chat",
-      "tool",
-      "parallel",
-      "signature"
-    ],
-    "name": "venice-chat/gemini-preserves-per-call-signatures-through-parallel-tools",
-    "recordedAt": "2026-10-05T03:21:54.383Z"
-  },
-  "interactions": [
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@@ -1,75 +0,0 @@
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You must use lookup_rate before answering.\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"call_onp7EArhOgXu0hGRF6Y5WHLu\",\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"arguments\":\"{\\\"code\\\":\\\"ZEBRA\\\"}\"}}],\"reasoning_details\":[{\"type\":\"reasoning.encrypted\",\"data\":\"gAAAAABqwxLxEN4vtmI2WcZ_aDDttdmPwAHgnV2gLZBo_f_mmTdGm4oZzE2JVzcj72AeXHyABmmo2VQN4nXaZK9GSSUZRlYL8mECMxKTj9AMgL8zlnuN5WDexxU-e9SduGP36RN9nH56-go4dz8eu5DEMvMf_TMoTnxz5AnC_UWbty63Vp8jEgkD-DoRjd0cg9LjthP_FLyMvP2Wj9qMJxEuO7Mw2_Pu4I3YeChnygLvmRfRR2QkamL5vjb9yHkl0Lb502vEGB2DW_czNEpHxisifvwRBjA7vk0mbn2dlhiR80aNHO71hC-QqrtUfPXx2HIbVLfbPdJf0saI0wD7ZuCJSQCBfB7fMCnj2ZLQeXa67lgXwsZDLBg4HmSJFvsMinx1IHIjUk7iebsKvmYx40cjqpXL3wj7htZWk2hO9OyGGUwlRsn5THdhTsgwg2SPbuHxb-sLPQnEFZ7bRp5lsVm31X2dlHDa1uZ7KLJZyy9g2CLIKsBwFFoCK7jY3HBXfL21ac5TAkOzVmz-XKl6OMPSl-PSdByOO15uHHpyOcJvJvuaea5Tj1nihtuDlhUP5EQPi7MiWpJMFo9AhDCafAbaQOEF5W8AQPeb_GXvPTzhySRAC8PxrhraEcZ4fjpjLqkv6mi_A1YHwbHEHHWjcK5VEKc3dadlIM_s6djclFBocVXrvnQQElVhWBDM-RtK9sgR07BFj5LVk6fYvg0b6gQnbDuQH18jhtPoj0SX0lN921XEQ1ebMCWGLANND2ew_wyNShYouJohefLULicWG57xh_yV1KEG1ufBedq2CPvCHA9Hm5UssbeJx5yBriyUA2Yh4D7j2UBT_KDWEHydDLQ4mWEyLTfQn0ZB3ZOqkU79z3HpK2w_VHUnkl5nEYEU2bmF5lsG33B4gtbQIBtZT76-fizXsvVZx__taOWXg96VMi3CD3DY0TS76B4U92KFmAFJ4aeiM8bkPuzf1Qd202EWE39CotUDoxAM6mzQu0NObTDnGQE776P6kzUoIKUmP8sDwYG5xot8ZTuXcBYysvj4-pFC_fvqMhsdfgonbke78SIjHtmePsOkfHBnCjSSUFKEbaM0nm8jJ6nYVwiYFuXBKD31QD462TAC7ORVIn32sWSgV2t3Sd7vq4ws2Yy7nUoILRAt_NYQUEXt7_R8J5YWj1L6Ruagk7Vtt-CAWxT6FhVyU4JhMb6-tJrYHgdmtunYrjpHBiOVdQR25aOmLbc_WlDvpO4azcRazpgkASAjPaaDycYceKcheiyUDBgFrvcSYrS1fJb6YZrTzOKw1Ztd0YsklS4nc3jffLNLrBQVvnkajj0OHjGcW8wkP93TCMJyt8tfIH0Rd5hIZLY5EqUWj9yZgXO7CuDKQZIEI0oZXef3mjfQqH8Q9rZsSgS3DI3mCF3CN003R_ZKKLGWkG8VzwlvdocNxaV_Z-ujp_O0YMyOcmEoTJI-j3JP3nefNboyP7EWND6VWDjJbqg64dvu0PK0EW5L0lnAu0l-WVb2qmXLYao_7bOlD8JLFZOyUgHAWmetmnm0NuxzevJEVBkNUu1jQatPzf2Jzf9SGKM_3bM_z0TM5McCZ2Pikzwp96QlaiEEWV_j2g02PT5Y3td-lfpoKxoFD5tltGNY9TlPzK-4a9Iz0hloiCprxWMLGKw2JzctrPF1xr42PKGNgPE84xAQ3sQ4mQ==\",\"id\":\"rs_014406f0f45e19c6016ac312f01d2487d2a5f2bdb7fbc42f76\",\"format\":\"openai-responses-v1\",\"index\":0}],\"reasoning_content\":\"**Calculating private data**\\n\\nI need to follow the developer's instructions and use the provided tool to handle private data. First, I should look up the rate for \\\"ZEBRA\\\" before I answer. After that, I’ll multiply the rate by 17 and then add 9 to get the required number. It’s important to give only the requested number and avoid making another tool call. I’ll likely use the commentary channel for this tool call.\\n\\n__ENCRYPTED_REASONING__id=rs_014406f0f45e19c6016ac312f01d2487d2a5f2bdb7fbc42f76\\ngAAAAABqwxLxEN4vtmI2WcZ_aDDttdmPwAHgnV2gLZBo_f_mmTdGm4oZzE2JVzcj72AeXHyABmmo2VQN4nXaZK9GSSUZRlYL8mECMxKTj9AMgL8zlnuN5WDexxU-e9SduGP36RN9nH56-go4dz8eu5DEMvMf_TMoTnxz5AnC_UWbty63Vp8jEgkD-DoRjd0cg9LjthP_FLyMvP2Wj9qMJxEuO7Mw2_Pu4I3YeChnygLvmRfRR2QkamL5vjb9yHkl0Lb502vEGB2DW_czNEpHxisifvwRBjA7vk0mbn2dlhiR80aNHO71hC-QqrtUfPXx2HIbVLfbPdJf0saI0wD7ZuCJSQCBfB7fMCnj2ZLQeXa67lgXwsZDLBg4HmSJFvsMinx1IHIjUk7iebsKvmYx40cjqpXL3wj7htZWk2hO9OyGGUwlRsn5THdhTsgwg2SPbuHxb-sLPQnEFZ7bRp5lsVm31X2dlHDa1uZ7KLJZyy9g2CLIKsBwFFoCK7jY3HBXfL21ac5TAkOzVmz-XKl6OMPSl-PSdByOO15uHHpyOcJvJvuaea5Tj1nihtuDlhUP5EQPi7MiWpJMFo9AhDCafAbaQOEF5W8AQPeb_GXvPTzhySRAC8PxrhraEcZ4fjpjLqkv6mi_A1YHwbHEHHWjcK5VEKc3dadlIM_s6djclFBocVXrvnQQElVhWBDM-RtK9sgR07BFj5LVk6fYvg0b6gQnbDuQH18jhtPoj0SX0lN921XEQ1ebMCWGLANND2ew_wyNShYouJohefLULicWG57xh_yV1KEG1ufBedq2CPvCHA9Hm5UssbeJx5yBriyUA2Yh4D7j2UBT_KDWEHydDLQ4mWEyLTfQn0ZB3ZOqkU79z3HpK2w_VHUnkl5nEYEU2bmF5lsG33B4gtbQIBtZT76-fizXsvVZx__taOWXg96VMi3CD3DY0TS76B4U92KFmAFJ4aeiM8bkPuzf1Qd202EWE39CotUDoxAM6mzQu0NObTDnGQE776P6kzUoIKUmP8sDwYG5xot8ZTuXcBYysvj4-pFC_fvqMhsdfgonbke78SIjHtmePsOkfHBnCjSSUFKEbaM0nm8jJ6nYVwiYFuXBKD31QD462TAC7ORVIn32sWSgV2t3Sd7vq4ws2Yy7nUoILRAt_NYQUEXt7_R8J5YWj1L6Ruagk7Vtt-CAWxT6FhVyU4JhMb6-tJrYHgdmtunYrjpHBiOVdQR25aOmLbc_WlDvpO4azcRazpgkASAjPaaDycYceKcheiyUDBgFrvcSYrS1fJb6YZrTzOKw1Ztd0YsklS4nc3jffLNLrBQVvnkajj0OHjGcW8wkP93TCMJyt8tfIH0Rd5hIZLY5EqUWj9yZgXO7CuDKQZIEI0oZXef3mjfQqH8Q9rZsSgS3DI3mCF3CN003R_ZKKLGWkG8VzwlvdocNxaV_Z-ujp_O0YMyOcmEoTJI-j3JP3nefNboyP7EWND6VWDjJbqg64dvu0PK0EW5L0lnAu0l-WVb2qmXLYao_7bOlD8JLFZOyUgHAWmetmnm0NuxzevJEVBkNUu1jQatPzf2Jzf9SGKM_3bM_z0TM5McCZ2Pikzwp96QlaiEEWV_j2g02PT5Y3td-lfpoKxoFD5tltGNY9TlPzK-4a9Iz0hloiCprxWMLGKw2JzctrPF1xr42PKGNgPE84xAQ3sQ4mQ==\"},{\"role\":\"tool\",\"tool_call_id\":\"call_onp7EArhOgXu0hGRF6Y5WHLu\",\"content\":\"{\\\"code\\\":\\\"ZEBRA\\\",\\\"rate\\\":23}\"},{\"role\":\"assistant\",\"content\":\"400\",\"reasoning_details\":[{\"type\":\"reasoning.encrypted\",\"data\":\"gAAAAABqwxL0Nl6Jl5EZuOLine truncated
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\"**Calculating a simple addition**\\n\\nThe\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" user\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" wants\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" me\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" to\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" add\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" 7\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" to\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" the\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" previous\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" final\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" answer\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\",\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" which\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" was\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" 400\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\".\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" This\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"Line truncated
-      }
-    }
-  ]
-}
@@ -1,35 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "text",
-      "reasoning",
-      "toggle"
-    ],
-    "name": "venice-chat/qwen-disables-reasoning",
-    "recordedAt": "2026-10-05T02:59:04.614Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"qwen3-6-27b\",\"messages\":[{\"role\":\"user\",\"content\":\"What is 23 multiplied by 17 plus 9? Reply with just the number.\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"reasoning\":{\"enabled\":false},\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"service_tier\":null,\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"4\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"0\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"0\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":\"stop\"}]}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[],\"usage\":{\"prompt_tokens\":32,\"completion_tokens\":4,\"total_tokens\":36},\"cost\":{\"usd\":0.0000234,\"diem\":0}}\n\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -1,33 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "error"
-    ],
-    "name": "venice-chat/surfaces-venice-model-errors",
-    "recordedAt": "2026-10-05T02:59:11.768Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"no-such-model-xyz\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 404,
-        "headers": {
-          "content-type": "application/json; charset=utf-8"
-        },
-        "body": "{\"error\":\"Specified model not found: no-such-model-xyz. Did you mean: z-ai-glm-5-3, z-ai-glm-5-3-flash, z-ai-glm-5-turbo?\"}"
-      }
-    }
-  ]
-}
@@ -8,6 +8,7 @@ import {
  type ProviderMetadata,
  type ToolCallPart,
  ToolResultPart,
+  type ToolResultValue,
  type Usage,
 } from "../../src/schema/index.js"
 import { type Tools, toDefinitions } from "../../src/tool.js"
@@ -39,7 +39,9 @@ describe("provider error classification", () => {
    ]

    expect(failures).toEqual(
-      failures.map(() => expect.objectContaining({ _tag: "InvalidRequest", classification: "payload-too-large" })),
+      failures.map((failure) =>
+        expect.objectContaining({ _tag: "InvalidRequest", classification: "payload-too-large" }),
+      ),
    )
  })

@@ -1,26 +0,0 @@
-import { LLM } from "../../src/index.js"
-import { Venice } from "../../src/providers.js"
-
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  providerOptions: { reasoningEffort: "high", reasoning: { summary: "concise" }, veniceParameters: { includeVeniceSystemPrompt: false } },
-})
-LLM.request({
-  model: Venice.configure({ providerOptions: { reasoningEffort: "future-effort" } }).model("future-model"),
-  providerOptions: { reasoning: { enabled: false }, promptCacheRetention: "future-retention", parallelToolCalls: false },
-})
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  // @ts-expect-error Thinking toggles are boolean.
-  providerOptions: { reasoning: { enabled: "false" } },
-})
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  // @ts-expect-error Venice uses nested reasoning, not Anthropic thinking controls.
-  providerOptions: { thinking: { type: "disabled" } },
-})
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  // @ts-expect-error Venice's system-prompt toggle is boolean.
-  providerOptions: { veniceParameters: { includeVeniceSystemPrompt: "false" } },
-})
@@ -7,6 +7,67 @@ const configuration = (provider: string, message: string) =>
  expect.objectContaining({ _tag: "ProviderConfiguration", provider, message })

 describe("provider package entrypoints", () => {
+  test("semantic API aliases expose the same contract", async () => {
+    const modules = await Promise.all([
+      import("@opencode/ai/providers/openai"),
+      import("@opencode/ai/providers/openai/responses"),
+      import("@opencode/ai/providers/openai/chat"),
+      import("@opencode/ai/providers/anthropic"),
+      import("@opencode/ai/providers/anthropic-compatible"),
+      import("@opencode/ai/providers/openai-compatible"),
+      import("@opencode/ai/providers/openai-compatible/responses"),
+      import("@opencode/ai/providers/amazon-bedrock"),
+      import("@opencode/ai/providers/azure"),
+      import("@opencode/ai/providers/azure/responses"),
+      import("@opencode/ai/providers/azure/chat"),
+      import("@opencode/ai/providers/google"),
+      import("@opencode/ai/providers/google-vertex"),
+      import("@opencode/ai/providers/google-vertex/gemini"),
+      import("@opencode/ai/providers/google-vertex/chat"),
+      import("@opencode/ai/providers/google-vertex/responses"),
+      import("@opencode/ai/providers/google-vertex/messages"),
+      import("@opencode/ai/providers/openrouter"),
+      import("@opencode/ai/providers/xai"),
+      import("@opencode/ai/providers/amazon-bedrock/mantle"),
+      import("@opencode/ai/providers/amazon-bedrock/mantle/chat"),
+      import("@opencode/ai/providers/amazon-bedrock/mantle/responses"),
+      import("@opencode/ai/providers/togetherai"),
+      import("@opencode/ai/providers/cerebras"),
+      import("@opencode/ai/providers/deepinfra"),
+      import("@opencode/ai/providers/groq"),
+      import("@opencode/ai/providers/baseten"),
+      import("@opencode/ai/providers/deepseek"),
+      import("@opencode/ai/providers/fireworks"),
+      import("@opencode/ai/providers/cloudflare-ai-gateway"),
+      import("@opencode/ai/providers/cloudflare-workers-ai"),
+      import("@opencode/ai/providers/minimax"),
+      import("@opencode/ai/providers/minimax/messages"),
+      import("@opencode/ai/providers/minimax/chat"),
+      import("@opencode/ai/providers/minimax/responses"),
+      import("@opencode/ai/providers/moonshot"),
+      import("@opencode/ai/providers/moonshot/chat"),
+      import("@opencode/ai/providers/moonshot/messages"),
+      import("@opencode/ai/providers/moonshot/responses"),
+      import("@opencode/ai/providers/zai"),
+      import("@opencode/ai/providers/zai/chat"),
+      import("@opencode/ai/providers/zai-coding-plan"),
+      import("@opencode/ai/providers/zai-coding-plan/chat"),
+      import("@opencode/ai/providers/zai-coding-plan/messages"),
+      import("@opencode/ai/providers/zai-coding-plan/responses"),
+      import("@opencode/ai/providers/alibaba"),
+      import("@opencode/ai/providers/alibaba/chat"),
+      import("@opencode/ai/providers/alibaba/messages"),
+      import("@opencode/ai/providers/alibaba/responses"),
+    ])
+
+    for (const module of modules) expect(module.model).toBeFunction()
+    expect(modules[0].model).toBe(modules[1].model)
+    expect(modules[8].model).toBe(modules[9].model)
+    expect(modules[12].model).toBe(modules[13].model)
+    expect(modules[19].model).toBe(modules[21].model)
+    expect(modules[19].model).not.toBe(modules[20].model)
+  })
+
  test("maps Alibaba API entrypoints onto explicit regional routes", async () => {
    const modules = await Promise.all([
      import("@opencode/ai/providers/alibaba"),
@@ -14,6 +75,7 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/alibaba/messages"),
      import("@opencode/ai/providers/alibaba/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
    const settings = {
      region: "eu-central-1",
      workspaceID: "llm-fixture",
@@ -41,6 +103,7 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/moonshot/messages"),
      import("@opencode/ai/providers/moonshot/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
    const settings = {
      apiKey: "fixture",
      baseURL: "https://gateway.example/v1",
@@ -84,6 +147,7 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/minimax/chat"),
      import("@opencode/ai/providers/minimax/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
    const settings = {
      apiKey: "fixture",
      baseURL: "https://gateway.example/v1",
@@ -110,6 +174,8 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/zai-coding-plan/messages"),
      import("@opencode/ai/providers/zai-coding-plan/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
+    expect(modules[2].model).toBe(modules[3].model)
    const routes = [
      "zai-chat",
      "zai-chat",
@@ -364,7 +430,6 @@ describe("provider package entrypoints", () => {

  test("maps Google package settings onto the Gemini model", async () => {
    const Google = await import("@opencode/ai/providers/google")
-    const GoogleInteractions = await import("@opencode/ai/providers/google/interactions")
    const selected = Google.model("gemini-2.5-flash", {
      apiKey: "fixture",
      baseURL: "https://generativelanguage.test/v1beta",
@@ -378,20 +443,11 @@ describe("provider package entrypoints", () => {
    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
    expect(selected.route.defaults.http?.body).toEqual({ safetySettings: [] })
    expect(selected.route.defaults.providerOptions).toEqual({ thinkingConfig: { thinkingBudget: 1_024 } })
-    const interactions = GoogleInteractions.model("gemini-3.8-flash", {
-      apiKey: "fixture",
-      baseURL: "https://generativelanguage.test/v1beta",
-      thinkingLevel: "low",
-      store: true,
-    })
-    expect(interactions.route.id).toBe("google-interactions")
-    expect(interactions.route.endpoint.baseURL).toBe("https://generativelanguage.test/v1beta")
-    expect(interactions.route.defaults.providerOptions).toEqual({ thinkingLevel: "low", store: true })
-    expect(Google.configure().interactions("gemini-3.8-flash").route.protocol).toBe("google-interactions")
  })

  test("selects Vertex entrypoints with the same model contract", async () => {
    const GoogleVertex = await import("@opencode/ai/providers/google-vertex")
+    const GoogleVertexGemini = await import("@opencode/ai/providers/google-vertex/gemini")
    const GoogleVertexChat = await import("@opencode/ai/providers/google-vertex/chat")
    const GoogleVertexResponses = await import("@opencode/ai/providers/google-vertex/responses")
    const GoogleVertexMessages = await import("@opencode/ai/providers/google-vertex/messages")
@@ -416,6 +472,7 @@ describe("provider package entrypoints", () => {
      project: "vertex-project",
    })

+    expect(GoogleVertexGemini.model).toBe(GoogleVertex.model)
    expect(gemini.route.id).toBe("google-vertex-gemini")
    expect(gemini.route.protocol).toBe("gemini")
    expect(gemini.route.endpoint.baseURL).toBe("https://aiplatform.googleapis.com/v1/publishers/google")
@@ -431,115 +431,42 @@ describe("Anthropic Messages route", () => {
        (yield* compileRequest(
          LLM.request({
            model: opus48,
-            messages: [
-              Message.user("Start."),
-              Message.assistant("One."),
-              Message.system("Update."),
-              Message.assistant("Two."),
-            ],
+            messages: [Message.user("Before."), Message.system("One."), Message.system("Two.")],
            cache: "none",
          }),
        )).body.messages,
      ).toEqual([
-        { role: "user", content: [{ type: "text", text: "Start." }] },
-        { role: "assistant", content: [{ type: "text", text: "One." }] },
-        { role: "user", content: [{ type: "text", text: "<system-update>\nUpdate.\n</system-update>" }] },
-        { role: "assistant", content: [{ type: "text", text: "Two." }] },
+        {
+          role: "user",
+          content: [
+            { type: "text", text: "Before." },
+            { type: "text", text: "<system-update>\nOne.\n</system-update>" },
+            { type: "text", text: "<system-update>\nTwo.\n</system-update>" },
+          ],
+        },
      ])
    }),
  )

-  it.effect("moves system updates to the next assistant turn and sends consecutive updates together", () =>
-    Effect.gen(function* () {
-      const lower = (messages: ReadonlyArray<Message>) =>
-        compileRequest(LLM.request({ model: opus48, messages: [...messages], cache: "none" })).pipe(
-          Effect.map((prepared) => prepared.body.messages),
-        )
-      const system = (text: string) => ({ role: "system", content: [{ type: "text", text, cache_control: undefined }] })
-      const user = (text: string) => ({ role: "user", content: [{ type: "text", text }] })
-      const assistant = (text: string) => ({ role: "assistant", content: [{ type: "text", text }] })
-
-      expect(
-        yield* lower([
-          Message.user("Fix it."),
-          Message.assistant("Done."),
-          Message.system("Update."),
-          Message.user("Next."),
-        ]),
-      ).toEqual([user("Fix it."), assistant("Done."), user("Next."), system("Update.")])
-      expect(yield* lower([Message.user("Before."), Message.system("One."), Message.system("Two.")])).toEqual([
-        user("Before."),
-        system("One."),
-        system("Two."),
-      ])
-      expect(
-        yield* lower([
-          Message.user("Fix it."),
-          Message.assistant("Done."),
-          Message.system("One."),
-          Message.user("Next."),
-          Message.system("Two."),
-          Message.assistant("After."),
-        ]),
-      ).toEqual([
-        user("Fix it."),
-        assistant("Done."),
-        user("Next."),
-        system("One."),
-        system("Two."),
-        assistant("After."),
-      ])
-      expect(
-        yield* lower([
-          Message.user("Use the tool."),
-          Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: {} })]),
-          Message.tool({ id: "call_1", name: "lookup", result: "Done." }),
-          Message.system("Update."),
-          Message.user("Also check tests."),
-        ]),
-      ).toEqual([
-        user("Use the tool."),
-        { role: "assistant", content: [{ type: "tool_use", id: "call_1", name: "lookup", input: {} }] },
-        { role: "user", content: [{ type: "tool_result", tool_use_id: "call_1", content: '"Done."' }] },
-        user("Also check tests."),
-        system("Update."),
-      ])
-    }),
-  )
-
-  it.effect("keeps wrapped system updates in place for models without native system updates", () =>
+  it.effect("keeps a terminal Vertex system update in the tool-result turn", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(
        LLM.request({
-          model,
+          model: vertexOpus48,
          messages: [
-            Message.user("Fix it."),
-            Message.assistant("Done."),
-            Message.system("Update."),
-            Message.user("Next."),
+            Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: {} })]),
+            Message.tool({ id: "call_1", name: "lookup", result: "Done." }),
+            Message.system("Operator update."),
          ],
          cache: "none",
        }),
      )

      expect(prepared.body.messages).toEqual([
-        { role: "user", content: [{ type: "text", text: "Fix it." }] },
-        { role: "assistant", content: [{ type: "text", text: "Done." }] },
-        { role: "user", content: [{ type: "text", text: "<system-update>\nUpdate.\n</system-update>" }] },
-        { role: "user", content: [{ type: "text", text: "Next." }] },
-      ])
-    }),
-  )
-
-  it.effect("sends Vertex system updates after local tool results as native system messages", () =>
-    Effect.gen(function* () {
-      const toolTurn = [
-        Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: {} })]),
-        Message.tool({ id: "call_1", name: "lookup", result: "Done." }),
-        Message.system("Operator update."),
-      ]
-      const lowered = [
-        { role: "assistant", content: [{ type: "tool_use", id: "call_1", name: "lookup", input: {} }] },
+        {
+          role: "assistant",
+          content: [{ type: "tool_use", id: "call_1", name: "lookup", input: {} }],
+        },
        {
          role: "user",
          content: [
@@ -550,23 +477,55 @@ describe("Anthropic Messages route", () => {
              is_error: undefined,
              cache_control: undefined,
            },
+            {
+              type: "text",
+              text: "<system-update>\nOperator update.\n</system-update>",
+              cache_control: undefined,
+            },
          ],
        },
-        { role: "system", content: [{ type: "text", text: "Operator update.", cache_control: undefined }] },
-      ]
+      ])
+    }),
+  )

-      const terminal = yield* compileRequest(LLM.request({ model: vertexOpus48, messages: toolTurn, cache: "none" }))
-      const history = yield* compileRequest(
+  it.effect("preserves folded tool-result system updates across multi-turn Vertex history", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
        LLM.request({
          model: vertexOpus48,
-          messages: [...toolTurn, Message.assistant("Acknowledged."), Message.user("Next step.")],
+          messages: [
+            Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: {} })]),
+            Message.tool({ id: "call_1", name: "lookup", result: "Done." }),
+            Message.system("Operator update."),
+            Message.assistant("Acknowledged."),
+            Message.user("Next step."),
+          ],
          cache: "none",
        }),
      )

-      expect(terminal.body.messages).toEqual(lowered)
-      expect(history.body.messages).toEqual([
-        ...lowered,
+      expect(prepared.body.messages).toEqual([
+        {
+          role: "assistant",
+          content: [{ type: "tool_use", id: "call_1", name: "lookup", input: {} }],
+        },
+        {
+          role: "user",
+          content: [
+            {
+              type: "tool_result",
+              tool_use_id: "call_1",
+              content: '"Done."',
+              is_error: undefined,
+              cache_control: undefined,
+            },
+            {
+              type: "text",
+              text: "<system-update>\nOperator update.\n</system-update>",
+              cache_control: undefined,
+            },
+          ],
+        },
        { role: "assistant", content: [{ type: "text", text: "Acknowledged." }] },
        { role: "user", content: [{ type: "text", text: "Next step." }] },
      ])
@@ -21,6 +21,7 @@ import {
 import { LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
 import { AmazonBedrock } from "../../src/providers.js"
+import * as BedrockConverse from "../../src/protocols/bedrock-converse.js"
 import { it } from "../lib/effect.js"
 import { withProcessEnv } from "../lib/env.js"
 import { dynamicResponse, fixedResponse } from "../lib/http.js"
@@ -1,8 +1,9 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { LLM, LLMEvent, LLMRequest, Message, ToolDefinition } from "../../src/index.js"
+import { LLM, Message } from "../../src/index.js"
 import { AmazonBedrockMantle } from "../../src/providers.js"
+import { model } from "../../src/providers/amazon-bedrock/mantle.js"
 import { OpenResponses } from "../../src/protocols/open-responses.js"
 import { compileRequest, LLMClient } from "../../src/route/client.js"
 import { it } from "../lib/effect.js"
@@ -18,14 +19,14 @@ const credentials = {
 }

 describe("Amazon Bedrock Mantle provider", () => {
-  it.effect("uses Responses by default and exposes Chat and Messages explicitly", () =>
+  it.effect("uses Responses by default and exposes Chat explicitly", () =>
    Effect.gen(function* () {
      const provider = AmazonBedrockMantle.configure({ credentials })
+      expect(provider.model).toBe(provider.responses)
+      expect(AmazonBedrockMantle.model).toBe(AmazonBedrockMantle.responsesModel)
+      expect(model).toBe(AmazonBedrockMantle.responsesModel)
      expect(provider.model("openai.gpt-oss-120b").route.transport).toBe(OpenResponses.httpTransport)
      const chat = yield* compileRequest(LLM.request({ model: provider.chat("openai.gpt-oss-120b"), prompt: "Hi" }))
-      const messages = yield* compileRequest(
-        LLM.request({ model: provider.messages("anthropic.claude-opus-4-8"), prompt: "Hi", cache: "none" }),
-      )
      const responses = yield* compileRequest(
        LLM.request({ model: provider.model("openai.gpt-oss-120b"), prompt: "Hi" }),
      )
@@ -35,11 +36,6 @@ describe("Amazon Bedrock Mantle provider", () => {
        protocol: "openai-chat",
        body: { model: "openai.gpt-oss-120b" },
      })
-      expect(messages).toMatchObject({
-        route: "bedrock-mantle-messages",
-        protocol: "anthropic-messages",
-        body: { model: "anthropic.claude-opus-4-8", stream: true },
-      })
      expect(responses).toMatchObject({
        route: "bedrock-mantle-responses",
        protocol: "open-responses",
@@ -47,77 +43,43 @@ describe("Amazon Bedrock Mantle provider", () => {
      })
      expect(provider.model("openai.gpt-oss-120b").route.providerMetadataKey).toBe("mantle")
      expect(provider.chat("openai.gpt-oss-120b").route.providerMetadataKey).toBe("mantle")
-      expect(provider.messages("anthropic.claude-opus-4-8").route.providerMetadataKey).toBe("mantle")
    }),
  )

-  it.effect("preserves configured top-p generation defaults for Chat, Messages, and Responses", () =>
+  it.effect("preserves configured top-p generation defaults for Chat and Responses", () =>
    Effect.gen(function* () {
      const settings = { apiKey: "test-key", topP: 0.8 }
      const chat = yield* compileRequest(
        LLM.request({ model: AmazonBedrockMantle.chatModel("openai.gpt-oss-safeguard-20b", settings), prompt: "Hi" }),
      )
-      const messages = yield* compileRequest(
-        LLM.request({ model: AmazonBedrockMantle.messagesModel("anthropic.claude-opus-4-8", settings), prompt: "Hi" }),
-      )
      const responses = yield* compileRequest(
        LLM.request({ model: AmazonBedrockMantle.responsesModel("openai.gpt-oss-120b", settings), prompt: "Hi" }),
      )

      expect(chat.body.top_p).toBe(0.8)
-      expect(messages.body.top_p).toBe(0.8)
      expect(responses.body.top_p).toBe(0.8)
    }),
  )

-  it.effect("uses the Mantle endpoint and signing service across Responses and Messages", () =>
+  it.effect("uses the Mantle endpoint and signing service", () =>
    Effect.gen(function* () {
      const seen: Array<{ readonly url: string; readonly authorization: string | undefined }> = []
-      const configured = AmazonBedrockMantle.configure({ credentials, region: "us-west-1" })
-      for (const selected of [
-        configured.responses("openai.gpt-oss-120b"),
-        configured.messages("anthropic.claude-opus-4-8"),
-      ]) {
-        yield* LLMClient.generate(LLM.request({ model: selected, prompt: "Hi" })).pipe(
-          Effect.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request)
-                seen.push({ url: request.url, authorization: request.headers.get("authorization") ?? undefined })
-                return input.respond("", { headers: { "content-type": "text/event-stream" } })
-              }),
-            ),
+      const model = AmazonBedrockMantle.configure({ credentials, region: "us-west-1" }).responses("openai.gpt-oss-120b")
+      yield* LLMClient.generate(LLM.request({ model, prompt: "Hi" })).pipe(
+        Effect.provide(
+          dynamicResponse((input) =>
+            Effect.gen(function* () {
+              const request = yield* HttpClientRequest.toWeb(input.request)
+              seen.push({ url: request.url, authorization: request.headers.get("authorization") ?? undefined })
+              return input.respond("", { headers: { "content-type": "text/event-stream" } })
+            }),
          ),
-          Effect.flip,
-        )
-      }
-
-      expect(seen.map((item) => item.url)).toEqual([
-        "https://bedrock-mantle.us-west-1.api.aws/v1/responses",
-        "https://bedrock-mantle.us-west-1.api.aws/anthropic/v1/messages",
-      ])
-      expect(seen.every((item) => item.authorization?.includes("/us-west-1/bedrock-mantle/aws4_request"))).toBe(true)
-    }).pipe(withProcessEnv({ AWS_BEARER_TOKEN_BEDROCK: undefined })),
-  )
-
-  it.effect("applies inline cache breakpoints on Mantle Messages", () =>
-    Effect.gen(function* () {
-      const model = AmazonBedrockMantle.configure({ apiKey: "test-key" }).messages("anthropic.claude-opus-4-8")
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model,
-          system: "You are concise.",
-          messages: [Message.user("Hello")],
-          cache: "auto",
-        }),
+        ),
+        Effect.flip,
      )

-      expect(prepared.body.system).toEqual([
-        { type: "text", text: "You are concise.", cache_control: { type: "ephemeral" } },
-      ])
-      expect(prepared.body.messages).toEqual([
-        { role: "user", content: [{ type: "text", text: "Hello", cache_control: { type: "ephemeral" } }] },
-      ])
+      expect(seen[0]?.url).toBe("https://bedrock-mantle.us-west-1.api.aws/v1/responses")
+      expect(seen[0]?.authorization).toContain("/us-west-1/bedrock-mantle/aws4_request")
    }),
  )

@@ -239,198 +201,3 @@ describe("Amazon Bedrock Mantle recorded", () => {
    }),
  )
 })
-
-const recordedMessages = recordedTests({
-  prefix: "bedrock-mantle-messages",
-  provider: "amazon-bedrock",
-  protocol: "anthropic-messages",
-  requires: ["AWS_BEARER_TOKEN_BEDROCK"],
-  options: { redact: { allowRequestHeaders: ["anthropic-version", "anthropic-beta"] } },
-})
-
-const mantleMessages = (modelID: string) =>
-  AmazonBedrockMantle.configure({
-    apiKey: process.env.AWS_BEARER_TOKEN_BEDROCK ?? "fixture",
-    region: "us-east-1",
-  }).messages(modelID)
-
-const weatherTool = ToolDefinition.make({
-  name: "get_weather",
-  description: "Get the current weather in a city",
-  inputSchema: {
-    type: "object",
-    properties: { city: { type: "string", enum: ["Paris"] } },
-    required: ["city"],
-    additionalProperties: false,
-  },
-})
-
-describe("Amazon Bedrock Mantle Messages recorded", () => {
-  recordedMessages.effect.with(
-    "replays signed thinking through a tool loop and native system update",
-    { tags: ["tool", "tool-loop", "reasoning", "system-update"], metadata: { model: "anthropic.claude-opus-4-8" } },
-    () =>
-      Effect.gen(function* () {
-        const model = mantleMessages("anthropic.claude-opus-4-8")
-        const initial = LLM.request({
-          model,
-          system: "You are a concise assistant.",
-          prompt:
-            "First calculate 37 * 43. Then call get_weather for Paris. After receiving the tool result, state both the product and the weather.",
-          tools: [weatherTool],
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "medium",
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const first = yield* LLMClient.generate(initial)
-        expect(first.finishReason.normalized).toBe("tool-calls")
-        expect(first.toolCalls).toMatchObject([{ name: "get_weather", input: { city: "Paris" } }])
-        expect(first.reasoning.length).toBeGreaterThan(0)
-        expect(first.events.some(LLMEvent.is.toolInputDelta)).toBe(true)
-        const reasoningPart = first.message.content.find((part) => part.type === "reasoning")
-        const signature = (reasoningPart?.providerMetadata?.mantle as { readonly signature?: unknown } | undefined)
-          ?.signature
-        expect(typeof signature).toBe("string")
-
-        const followUp = LLMRequest.update(initial, {
-          messages: [
-            ...initial.messages,
-            first.message,
-            ...first.toolCalls.map((call) =>
-              Message.tool({ id: call.id, name: call.name, result: { condition: "sunny", temperatureC: 18 } }),
-            ),
-            Message.system("Reply in French in one short sentence."),
-          ],
-        })
-        const compiled = yield* compileRequest(followUp)
-        expect(compiled.body.messages[1]?.content[0]).toEqual({
-          type: "thinking",
-          thinking: first.reasoning,
-          signature: signature as string,
-        })
-        expect(compiled.body.messages.at(-1)).toEqual({
-          role: "system",
-          content: [
-            { type: "text", text: "Reply in French in one short sentence.", cache_control: { type: "ephemeral" } },
-          ],
-        })
-
-        const second = yield* LLMClient.generate(followUp)
-        expect(second.finishReason.normalized).toBe("stop")
-        expect(second.text).toContain("1591")
-        expect(second.text).toContain("18")
-      }),
-    120_000,
-  )
-
-  recordedMessages.effect.with(
-    "lowers system updates to wrapped user text on Haiku 4.5 with budget thinking",
-    { tags: ["reasoning", "system-update"], metadata: { model: "anthropic.claude-haiku-4-5" } },
-    () =>
-      Effect.gen(function* () {
-        const request = LLM.request({
-          model: mantleMessages("anthropic.claude-haiku-4-5"),
-          messages: [Message.user("What is 19 multiplied by 23?"), Message.system("Reply with only the integer.")],
-          providerOptions: {
-            thinking: { type: "enabled", budgetTokens: 1024 },
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const compiled = yield* compileRequest(request)
-        expect(compiled.body.thinking).toEqual({ type: "enabled", budget_tokens: 1024 })
-        expect(compiled.body.messages.some((message) => message.role === "system")).toBe(false)
-
-        const response = yield* LLMClient.generate(request)
-        expect(response.finishReason.normalized).toBe("stop")
-        expect(response.reasoning.length).toBeGreaterThan(0)
-        expect(response.text.trim()).toContain("437")
-      }),
-    120_000,
-  )
-
-  recordedMessages.effect.with(
-    "applies mid-conversation effort updates and thinking block binding on Opus 5.5",
-    { tags: ["reasoning", "effort-update"], metadata: { model: "anthropic.claude-opus-5-5" } },
-    () =>
-      Effect.gen(function* () {
-        const model = mantleMessages("anthropic.claude-opus-5-5")
-        const firstRequest = LLM.request({
-          model,
-          prompt: "Compute 37 * 43 step by step, then reply with only the integer.",
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "high",
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const firstCompiled = yield* compileRequest(firstRequest)
-        expect(firstCompiled.body.thinking).toEqual({
-          type: "adaptive",
-          display: "summarized",
-          block_binding: { prefix_mismatch_behavior: "drop_block" },
-        })
-
-        const first = yield* LLMClient.generate(firstRequest)
-        expect(first.finishReason.normalized).toBe("stop")
-        expect(first.reasoning.length).toBeGreaterThan(0)
-        expect(first.text.replaceAll(",", "")).toContain("1591")
-
-        const secondRequest = LLM.request({
-          model,
-          messages: [
-            ...firstRequest.messages,
-            first.message,
-            Message.effort({ effort: "low", previous: "high" }),
-            Message.user("Add 9 to that result. Reply with only the integer."),
-          ],
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "low",
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const secondCompiled = yield* compileRequest(secondRequest)
-        expect(secondCompiled.body.output_config).toEqual({ effort: "high" })
-        expect(secondCompiled.body.messages.filter((message) => message.role === "system")).toEqual([
-          { role: "system", content: [], output_config: { effort: "low" } },
-        ])
-
-        const second = yield* LLMClient.generate(secondRequest)
-        expect(second.finishReason.normalized).toBe("stop")
-        expect(second.text.replaceAll(",", "")).toContain("1600")
-      }),
-    120_000,
-  )
-
-  recordedMessages.effect.with(
-    "strips unsupported mid-conversation effort updates on Opus 5.0",
-    { tags: ["reasoning", "effort-update"], metadata: { model: "anthropic.claude-opus-5" } },
-    () =>
-      Effect.gen(function* () {
-        const request = LLM.request({
-          model: mantleMessages("anthropic.claude-opus-5"),
-          messages: [
-            Message.user("What is 12 + 30?"),
-            Message.assistant("42"),
-            Message.effort({ effort: "low", previous: "high" }),
-            Message.user("Add 8 to that result. Reply with only the integer."),
-          ],
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "low",
-          },
-          generation: { maxTokens: 1024 },
-        })
-        const compiled = yield* compileRequest(request)
-        expect(compiled.body.output_config).toEqual({ effort: "low" })
-        expect(compiled.body.messages.some((message) => message.role === "system")).toBe(false)
-
-        const response = yield* LLMClient.generate(request)
-        expect(response.finishReason.normalized).toBe("stop")
-        expect(response.text.trim()).toContain("50")
-      }),
-    120_000,
-  )
-})
@@ -1,4 +1,4 @@
-import { describe, expect } from "bun:test"
+import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect, Schema } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
 import { LLM, LLMEvent } from "../../src/index.js"
@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, LLMRequest, SystemPart } from "../../src/index.js"
+import { LLM, LLMEvent } from "../../src/index.js"
 import { Cohere } from "../../src/providers/cohere.js"
 import { LLMClient } from "../../src/route.js"
 import { expectWeatherToolLoop, goldenWeatherToolLoopRequest, runWeatherToolLoop } from "../recorded-scenarios.js"
@@ -55,20 +55,12 @@ recorded.effect(
  () =>
    Effect.gen(function* () {
      const events = yield* runWeatherToolLoop(
-        LLMRequest.update(
-          goldenWeatherToolLoopRequest({
-            id: "cohere-tool-loop",
-            model: cohere.model("command-a-plus-05-2026"),
-            maxTokens: 2048,
-            temperature: false,
-          }),
-          {
-            system: [
-              SystemPart.make("Use the get_weather tool exactly once."),
-              SystemPart.make("After the tool result, reply exactly: Paris is sunny."),
-            ],
-          },
-        ),
+        goldenWeatherToolLoopRequest({
+          id: "cohere-tool-loop",
+          model: cohere.model("command-a-plus-05-2026"),
+          maxTokens: 2048,
+          temperature: false,
+        }),
      )
      expectWeatherToolLoop(events)
      expect(events.some(LLMEvent.is.toolInputDelta)).toBe(true)
@@ -1,6 +1,6 @@
 import { expect, test } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMClient, LLMEvent, Media, Message, SystemPart, isRetryable } from "../../src/index.js"
+import { LLM, LLMClient, LLMEvent, Media, Message, isRetryable } from "../../src/index.js"
 import { Cohere } from "../../src/providers/cohere.js"
 import { compileRequest } from "../../src/route/client.js"
 import { it } from "../lib/effect.js"
@@ -23,7 +23,7 @@ it.effect("Cohere lowers native history, thinking, tools, and sampling", () =>
    const prepared = yield* compileRequest(
      LLM.request({
        model: cohere.model("command-a-reasoning-08-2025"),
-        system: [SystemPart.make("Be concise.\nKeep this newline."), SystemPart.make("Second instructions.")],
+        system: "Be concise.",
        messages: [
          Message.user("Lookup Paris"),
          Message.assistant([{ type: "tool-call", id: "lookup-1", name: "lookup", input: { city: "Paris" } }]),
@@ -44,13 +44,7 @@ it.effect("Cohere lowers native history, thinking, tools, and sampling", () =>
      thinking: { type: "enabled", token_budget: 128 },
      tool_choice: "REQUIRED",
      messages: [
-        {
-          role: "system",
-          content: [
-            { type: "text", text: "Be concise.\nKeep this newline." },
-            { type: "text", text: "Second instructions." },
-          ],
-        },
+        { role: "system", content: "Be concise." },
        { role: "user", content: [{ type: "text", text: "Lookup Paris" }] },
        {
          role: "assistant",
@@ -52,6 +52,7 @@ describe("experimental Evaluation recorded", () => {
  typesafe.effect("evaluates choice score and boolean questions", () =>
    assertEvaluation(
      TypeSafeAI.configure({ apiKey: process.env.TYPESAFE_API_KEY ?? "fixture" }).experimental.evaluation("jev-latest"),
+      "typesafe",
    ),
  )

@@ -60,6 +61,7 @@ describe("experimental Evaluation recorded", () => {
      OpenCodeZen.configure({ apiKey: process.env.OPENCODE_API_KEY ?? "fixture" }).experimental.evaluation(
        "jev-1.13-free",
      ),
+      "opencode",
    ),
  )

@@ -68,11 +70,15 @@ describe("experimental Evaluation recorded", () => {
      OpenRouter.configure({ apiKey: process.env.OPENROUTER_API_KEY ?? "fixture" }).experimental.evaluation(
        "typesafe/jev-1.13",
      ),
+      "openrouter",
    ),
  )
 })

-const assertEvaluation = <Options extends EvaluationOptions>(model: EvaluationModel<Options>) =>
+const assertEvaluation = <Options extends EvaluationOptions>(
+  model: EvaluationModel<Options>,
+  metadataKey: "typesafe" | "opencode" | "openrouter",
+) =>
  Effect.gen(function* () {
    const response = yield* Evaluation.run({ model, state, questions })
    expect(response.model).toContain("jev-")
@@ -1,169 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Schema } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { LLM, LLMEvent, Message } from "../../src/index.js"
-import { Google } from "../../src/providers.js"
-import { LLMClient, RequestExecutor } from "../../src/route.js"
-import { recordedTests } from "../recorded-test.js"
-import { weatherTool } from "../recorded-scenarios.js"
-
-const model = Google.configure({ apiKey: process.env.GEMINI_API_KEY ?? "fixture" }).interactions("gemini-3.8-flash")
-const recorded = recordedTests({
-  prefix: "google-interactions",
-  provider: "google",
-  protocol: "google-interactions",
-  requires: ["GEMINI_API_KEY"],
-})
-const InteractionMetadata = Schema.Struct({ interactionId: Schema.String })
-
-describe("Google Interactions recorded", () => {
-  recorded.effect("streams text and reports usage", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model,
-          prompt: "Reply with exactly one word: hello",
-          generation: { maxTokens: 2048 },
-          providerOptions: { thinkingLevel: "low" },
-        }),
-      )
-
-      expect(response.text.trim().toLowerCase()).toBe("hello")
-      expect(response.events.some(LLMEvent.is.textDelta)).toBe(true)
-      expect(response.finishReason.normalized).toBe("stop")
-      expect(response.events.filter(LLMEvent.is.finish)).toHaveLength(1)
-      expect(response.usage?.inputTokens).toBeGreaterThan(0)
-      expect(response.usage?.contextTokens).toBeGreaterThan(0)
-      expect(response.usage?.providerMetadata?.google).toMatchObject({ total_input_tokens: expect.any(Number) })
-    }),
-  )
-
-  recorded.effect(
-    "streams reasoning and retains thought signatures",
-    () =>
-      Effect.gen(function* () {
-        const response = yield* LLMClient.generate(
-          LLM.request({
-            model,
-            prompt:
-              "Find the smallest positive integer that leaves remainder 1 modulo 7, 2 modulo 9, and 3 modulo 11. Explain briefly.",
-            generation: { maxTokens: 4096 },
-            providerOptions: { thinkingLevel: "high", thinkingSummaries: "auto" },
-          }),
-        )
-
-        expect(response.reasoning.length).toBeGreaterThan(0)
-        expect(response.events.some(LLMEvent.is.reasoningDelta)).toBe(true)
-        expect(response.events.filter(LLMEvent.is.reasoningEnd)).toEqual(
-          expect.arrayContaining([
-            expect.objectContaining({
-              providerMetadata: { google: { interactionSignature: expect.any(String) } },
-            }),
-          ]),
-        )
-        expect(response.text.length).toBeGreaterThan(0)
-        expect(response.finishReason.normalized).toBe("stop")
-      }),
-    120_000,
-  )
-
-  recorded.effect(
-    "replays native tool results and signatures statelessly",
-    () =>
-      Effect.gen(function* () {
-        const request = LLM.request({
-          model,
-          system: "Use get_weather for weather questions. Answer concisely after receiving the result.",
-          prompt: "What is the weather in Paris?",
-          tools: [weatherTool],
-          toolChoice: { type: "tool", name: weatherTool.name },
-          generation: { maxTokens: 2048 },
-          providerOptions: { thinkingLevel: "low", thinkingSummaries: "auto" },
-        })
-        const first = yield* LLMClient.generate(request)
-
-        expect(first.toolCalls).toHaveLength(1)
-        expect(first.events.some(LLMEvent.is.toolInputDelta)).toBe(true)
-        expect(first.finishReason.normalized).toBe("tool-calls")
-        const call = first.toolCalls[0]
-        if (!call) throw new Error("Missing recorded weather tool call")
-        expect(call.name).toBe(weatherTool.name)
-        expect(call.input).toEqual({ city: "Paris" })
-        expect(call.providerMetadata?.google).toHaveProperty("interactionSignature")
-        const second = yield* LLMClient.generate(
-          LLM.request({
-            model,
-            system: request.system,
-            tools: [weatherTool],
-            toolChoice: "none",
-            generation: { maxTokens: 2048 },
-            providerOptions: { thinkingLevel: "low", thinkingSummaries: "auto" },
-            messages: [
-              ...request.messages,
-              first.message,
-              Message.tool({ id: call.id, name: call.name, result: { temperature: 22, condition: "sunny" } }),
-            ],
-          }),
-        )
-
-        expect(second.text.toLowerCase()).toContain("sunny")
-        expect(second.text).toContain("22")
-        expect(second.toolCalls).toHaveLength(0)
-        expect(second.finishReason.normalized).toBe("stop")
-      }),
-    120_000,
-  )
-
-  recorded.effect(
-    "continues tool results with previous interaction id",
-    () =>
-      Effect.gen(function* () {
-        const request = LLM.request({
-          model,
-          system: "Use get_weather for weather questions. Answer concisely after receiving the result.",
-          prompt: "What is the weather in Paris?",
-          tools: [weatherTool],
-          toolChoice: "required",
-          generation: { maxTokens: 2048 },
-          providerOptions: { thinkingLevel: "low", store: true },
-        })
-        const first = yield* LLMClient.generate(request)
-        const metadata = yield* Schema.decodeUnknownEffect(InteractionMetadata)(
-          first.events.find(LLMEvent.is.finish)?.providerMetadata?.google,
-        )
-        const executor = yield* RequestExecutor.Service
-        const cleanup = executor
-          .execute(
-            HttpClientRequest.delete(
-              `https://generativelanguage.googleapis.com/v1beta/interactions/${metadata.interactionId}`,
-            ).pipe(HttpClientRequest.setHeader("x-goog-api-key", process.env.GEMINI_API_KEY ?? "fixture")),
-          )
-          .pipe(Effect.orDie)
-
-        yield* Effect.gen(function* () {
-          expect(first.toolCalls).toHaveLength(1)
-          const call = first.toolCalls[0]
-          if (!call) throw new Error("Missing recorded weather tool call")
-          const second = yield* LLMClient.generate(
-            LLM.request({
-              model,
-              system: request.system,
-              tools: [weatherTool],
-              toolChoice: "none",
-              generation: { maxTokens: 2048 },
-              providerOptions: { thinkingLevel: "low", previousInteractionId: metadata.interactionId, store: false },
-              messages: [
-                Message.tool({ id: call.id, name: call.name, result: { temperature: 22, condition: "sunny" } }),
-              ],
-            }),
-          )
-
-          expect(second.text.toLowerCase()).toContain("sunny")
-          expect(second.text).toContain("22")
-          expect(second.toolCalls).toHaveLength(0)
-          expect(second.finishReason.normalized).toBe("stop")
-        }).pipe(Effect.ensuring(cleanup))
-      }),
-    120_000,
-  )
-})
@@ -1,7 +1,7 @@
 import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { LLM, LLMEvent, Message, SystemPart, ToolDefinition, Media } from "../../src/index.js"
+import { LLM, LLMEvent, Message, ToolDefinition, Media } from "../../src/index.js"
 import { Mistral } from "../../src/providers/index.js"
 import { MistralChat } from "../../src/protocols/index.js"
 import { LLMClient } from "../../src/route.js"
@@ -41,7 +41,7 @@ describe("Mistral Chat", () => {
      const prepared = yield* compileRequest(
        LLM.request({
          model,
-          system: [SystemPart.make("Initial\nKeep this newline."), SystemPart.make("Second instructions.")],
+          system: "Initial",
          messages: [
            Message.system("Updated"),
            Message.user([
@@ -105,13 +105,7 @@ describe("Mistral Chat", () => {
        reasoning_effort: "high",
      })
      expect(prepared.body.messages.slice(0, 4)).toMatchObject([
-        {
-          role: "system",
-          content: [
-            { type: "text", text: "Initial\nKeep this newline." },
-            { type: "text", text: "Second instructions." },
-          ],
-        },
+        { role: "system", content: "Initial" },
        { role: "user", content: "<system-update>\nUpdated\n</system-update>" },
        {
          role: "user",
@@ -1,7 +1,7 @@
 import { configure } from "@opencode/ai/providers/mistral"
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, LLMRequest, Message, SystemPart, ToolChoice, ToolDefinition } from "../../src/index.js"
+import { LLM, LLMEvent, LLMRequest, Message, ToolChoice, ToolDefinition } from "../../src/index.js"
 import { LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
 import { recordedTests } from "../recorded-test.js"
@@ -97,10 +97,7 @@ describe("Mistral recorded", () => {
        const model = configure({ apiKey, providerOptions: { reasoningEffort: "none" } }).model("mistral-small-latest")
        const firstRequest = LLM.request({
          model,
-          system: [
-            SystemPart.make("Call lookup_weather exactly once with Paris."),
-            SystemPart.make("After the tool result, describe the weather briefly."),
-          ],
+          system: "Call lookup_weather exactly once with Paris.",
          prompt: "What is the weather?",
          tools: [weather],
          toolChoice: weather,
@@ -43,7 +43,6 @@ describe("native OpenAI-compatible providers", () => {
      [Azure.configure({ resourceName: "resource", apiKey: "test" }).responses("model"), "azure"],
      [AmazonBedrock.configure({ apiKey: "test" }).model("model"), "bedrock"],
      [AmazonBedrockMantle.configure({ apiKey: "test" }).chat("model"), "mantle"],
-      [AmazonBedrockMantle.configure({ apiKey: "test" }).messages("model"), "mantle"],
      [AmazonBedrockMantle.configure({ apiKey: "test" }).responses("model"), "mantle"],
      [Google.configure({ apiKey: "test" }).model("model"), "google"],
      [GoogleVertex.configure(vertex).model("model"), "vertex"],