refactor(app): plain codecs for persisted state, starting with tabs

Adds an Effect-free codec module for persisted stores with the same recovery semantics as the Persistence helpers, lets persisted() accept either a Schema or a codec while stores migrate, and ports the tab storage schemas as the first store. ServerKey keeps its brand type on both sides so ServerConnection.Key stays one type. Effect leaves the renderer's initial module graph once the remaining stores are ported.
2026-09-23 17:17:43 +00:00 · 2026-09-20 16:36:58 +10:00
595 changed files with 5415 additions and 17037 deletions
@@ -53,6 +53,8 @@ runs:
      with:
        path: ${{ steps.cache.outputs.dir }}
        key: ${{ runner.os }}-bun-${{ hashFiles('**/bun.lock') }}
+        restore-keys: |
+          ${{ runner.os }}-bun-

    - name: Install setuptools for distutils compatibility
      run: python3 -m pip install setuptools || pip install setuptools || true
@@ -64,9 +66,9 @@ runs:
        # e.g. ./patches/ for standard-openapi
        # https://github.com/oven-sh/bun/issues/28147
        if [ "$RUNNER_OS" = "Windows" ]; then
-          bun install --frozen-lockfile --linker hoisted ${{ inputs.install-flags }}
+          bun install --linker hoisted ${{ inputs.install-flags }}
        else
-          bun install --frozen-lockfile ${{ inputs.install-flags }}
+          bun install ${{ inputs.install-flags }}
        fi
      shell: bash

@@ -112,12 +112,11 @@ jobs:
      - name: Run unit tests
        timeout-minutes: 20
        run: |
-          # The runners have four vCPUs, and each Bun test process performs its own concurrent work.
          if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
-            GITHUB_ACTIONS=false bun turbo test --concurrency=3
+            GITHUB_ACTIONS=false bun turbo test
            exit 0
          fi
-          GITHUB_ACTIONS=false bun turbo test --affected --concurrency=3
+          GITHUB_ACTIONS=false bun turbo test --affected
        env:
          OPENCODE_EXPERIMENTAL_DISABLE_FILEWATCHER: ${{ runner.os == 'Windows' && 'true' || 'false' }}
          TURBO_SCM_BASE: ${{ github.event_name == 'pull_request' && format('{0}^1', github.sha) || github.event.before }}
@@ -32,7 +32,7 @@
    },
    "packages/ai": {
      "name": "@opencode/ai",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@aws-sdk/credential-providers": "3.1057.0",
        "@opencode/schema": "workspace:*",
@@ -54,7 +54,7 @@
    },
    "packages/app": {
      "name": "@opencode/app",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@corvu/drawer": "catalog:",
        "@dnd-kit/abstract": "0.5.0",
@@ -92,7 +92,6 @@
        "solid-js": "catalog:",
        "solid-presence": "0.2.0",
        "tailwindcss": "4.3.3",
-        "uqr": "0.1.3",
      },
      "devDependencies": {
        "@happy-dom/global-registrator": "20.0.11",
@@ -112,7 +111,7 @@
    },
    "packages/cli": {
      "name": "@opencode/cli",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "bin": {
        "opencode2": "./bin/opencode2.cjs",
      },
@@ -176,7 +175,7 @@
    },
    "packages/client": {
      "name": "@opencode/client",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/protocol": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -202,7 +201,7 @@
    },
    "packages/codemode": {
      "name": "@opencode/codemode",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "acorn": "8.15.0",
        "effect": "catalog:",
@@ -215,7 +214,7 @@
    },
    "packages/console/app": {
      "name": "@opencode/console-app",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@ibm/plex": "6.4.1",
@@ -251,7 +250,7 @@
    },
    "packages/console/core": {
      "name": "@opencode/console-core",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@aws-sdk/client-sts": "3.782.0",
        "@jsx-email/render": "1.1.1",
@@ -278,7 +277,7 @@
    },
    "packages/console/function": {
      "name": "@opencode/console-function",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@openauthjs/openauth": "0.0.0-20250322224806",
        "@opencode/console-core": "workspace:*",
@@ -295,7 +294,7 @@
    },
    "packages/console/mail": {
      "name": "@opencode/console-mail",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@jsx-email/all": "2.2.3",
        "@jsx-email/cli": "1.4.3",
@@ -319,7 +318,7 @@
    },
    "packages/console/support": {
      "name": "@opencode/console-support",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@opencode/console-core": "workspace:*",
@@ -339,7 +338,7 @@
    },
    "packages/core": {
      "name": "@opencode/core",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@ai-sdk/cohere": "3.0.27",
        "@ai-sdk/gateway": "3.0.104",
@@ -367,7 +366,7 @@
        "drizzle-orm": "catalog:",
        "effect": "catalog:",
        "fuzzysort": "3.1.0",
-        "gitlab-ai-provider": "6.16.0",
+        "gitlab-ai-provider": "6.12.1",
        "google-auth-library": "10.5.0",
        "gray-matter": "4.0.3",
        "htmlparser2": "8.0.2",
@@ -407,10 +406,10 @@
    },
    "packages/desktop": {
      "name": "@opencode/desktop",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@zip.js/zip.js": "2.7.62",
-        "electron-context-menu": "5.0.0",
+        "electron-context-menu": "4.1.2",
        "electron-log": "^5",
        "electron-updater": "6.8.9",
        "lighthouse": "13.4.1",
@@ -437,7 +436,7 @@
        "drizzle-kit": "catalog:",
        "drizzle-orm": "catalog:",
        "effect": "catalog:",
-        "electron": "44.4.3",
+        "electron": "42.10.1",
        "electron-builder": "26.15.7",
        "electron-vite": "6.0.0-beta.1",
        "puppeteer-core": "25.9.0",
@@ -456,7 +455,7 @@
    },
    "packages/enterprise": {
      "name": "@opencode/enterprise",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@hono/standard-validator": "catalog:",
        "@opencode-ai/sdk": "1.18.21",
@@ -493,7 +492,7 @@
    },
    "packages/function": {
      "name": "@opencode/function",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@octokit/auth-app": "8.0.1",
        "@octokit/rest": "catalog:",
@@ -509,7 +508,7 @@
    },
    "packages/http-recorder": {
      "name": "@opencode/http-recorder",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@effect/platform-node-shared": "4.0.0-rc.112",
      },
@@ -528,7 +527,7 @@
    },
    "packages/httpapi-codegen": {
      "name": "@opencode/httpapi-codegen",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "effect": "catalog:",
        "prettier": "3.6.2",
@@ -541,7 +540,7 @@
    },
    "packages/latex": {
      "name": "@opencode/latex",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -555,7 +554,7 @@
    },
    "packages/merman": {
      "name": "@opencode/merman",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -570,7 +569,7 @@
    },
    "packages/plugin": {
      "name": "@opencode/plugin",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@ai-sdk/provider": "3.0.8",
        "@opencode/ai": "workspace:*",
@@ -609,7 +608,7 @@
    },
    "packages/plugin-browser": {
      "name": "@opencode/plugin-browser",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -639,7 +638,7 @@
    },
    "packages/protocol": {
      "name": "@opencode/protocol",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/schema": "workspace:*",
        "effect": "catalog:",
@@ -654,7 +653,7 @@
    },
    "packages/schema": {
      "name": "@opencode/schema",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@standard-schema/spec": "catalog:",
        "effect": "catalog:",
@@ -678,7 +677,7 @@
    },
    "packages/sdk": {
      "name": "@opencode/sdk",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -699,7 +698,7 @@
    },
    "packages/server": {
      "name": "@opencode/server",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@effect/platform-node": "catalog:",
        "@effect/platform-node-shared": "catalog:",
@@ -721,7 +720,7 @@
    },
    "packages/session-ui": {
      "name": "@opencode/session-ui",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode/client": "workspace:*",
@@ -756,7 +755,7 @@
    },
    "packages/simulation": {
      "name": "@opencode/simulation",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/ai": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -776,7 +775,7 @@
    },
    "packages/stats/app": {
      "name": "@opencode/stats-app",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@ibm/plex": "6.4.1",
        "@kobalte/core": "catalog:",
@@ -810,7 +809,7 @@
    },
    "packages/stats/core": {
      "name": "@opencode/stats-core",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@aws-sdk/client-athena": "3.933.0",
        "@planetscale/database": "1.19.0",
@@ -829,7 +828,7 @@
    },
    "packages/stats/server": {
      "name": "@opencode/stats-server",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@aws-sdk/client-firehose": "3.933.0",
        "@effect/platform-node": "catalog:",
@@ -875,7 +874,7 @@
    },
    "packages/theme": {
      "name": "@opencode/theme",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opentui/core": "catalog:",
        "effect": "catalog:",
@@ -889,7 +888,7 @@
    },
    "packages/tui": {
      "name": "@opencode/tui",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -924,7 +923,7 @@
    },
    "packages/ui": {
      "name": "@opencode/ui",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@pierre/diffs": "catalog:",
@@ -959,7 +958,7 @@
    },
    "packages/util": {
      "name": "@opencode/util",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@effect/opentelemetry": "catalog:",
        "@effect/platform-node": "catalog:",
@@ -992,7 +991,7 @@
    },
    "packages/web": {
      "name": "@opencode/web",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "@astrojs/cloudflare": "12.6.3",
        "@astrojs/markdown-remark": "6.3.1",
@@ -1033,7 +1032,7 @@
    },
    "services/update": {
      "name": "@opencode/update",
-      "version": "2.0.14",
+      "version": "2.0.10",
      "dependencies": {
        "jose": "6.0.11",
        "semver": "catalog:",
@@ -1075,7 +1074,6 @@
    "@tanstack/virtual-core@3.17.8": "patches/@tanstack%2Fvirtual-core@3.17.8.patch",
    "ghostty-web@github:anomalyco/ghostty-web#83c0a07": "patches/ghostty-web@0.3.0.patch",
    "@modelcontextprotocol/client@2.0.0": "patches/@modelcontextprotocol%2Fclient@2.0.0.patch",
-    "pacote@21.5.1": "patches/pacote@21.5.1.patch",
    "@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
    "@npmcli/agent@4.0.2": "patches/@npmcli%2Fagent@4.0.2.patch",
    "@silvia-odwyer/photon-node@0.3.4": "patches/@silvia-odwyer%2Fphoton-node@0.3.4.patch",
@@ -3882,13 +3880,13 @@

    "ejs": ["ejs@3.1.10", "", { "dependencies": { "jake": "^10.8.5" }, "bin": { "ejs": "bin/cli.js" } }, "sha512-UeJmFfOrAQS8OJWPZ4qtgHyWExa088/MtK5UEyoJGFH67cDEXkZSviOiKRCZ4Xij0zxI3JECgYs3oKx+AizQBA=="],

-    "electron": ["electron@44.4.3", "", { "dependencies": { "@electron-internal/extract-zip": "^1.0.1", "@electron/get": "^5.0.0", "@types/node": "^24.9.0" }, "bin": { "electron": "cli.js", "install-electron": "install.js" } }, "sha512-LTpSFTB40qVCXIX5xMo+cgHI/Jjkbjw7VpB26PccEbroqOn72LBukeaDwPVo1fBYzSzs0c9iPuAucFCO7Tw81Q=="],
+    "electron": ["electron@42.10.1", "", { "dependencies": { "@electron-internal/extract-zip": "^1.0.1", "@electron/get": "^5.0.0", "@types/node": "^24.9.0" }, "bin": { "electron": "cli.js", "install-electron": "install.js" } }, "sha512-ITc1HPeoDzsxCCaH6MFsN67Nq2nUiJf5N9pBWxzhUpFfKJF0IwiAkKT3emg1lPbvC4OfFE+Cdwe4vhgdOZ1YKg=="],

    "electron-builder": ["electron-builder@26.15.7", "", { "dependencies": { "app-builder-lib": "26.15.7", "builder-util": "26.15.3", "builder-util-runtime": "9.7.0", "chalk": "^4.1.2", "ci-info": "^4.2.0", "dmg-builder": "26.15.7", "fs-extra": "^10.1.0", "lazy-val": "^1.0.5", "simple-update-notifier": "2.0.0", "yargs": "^17.6.2" }, "bin": { "electron-builder": "./cli.js", "install-app-deps": "./install-app-deps.js" } }, "sha512-DBpaNzxsPs1BvEblzFoNriSbzsBqDCy/gseIngeEhYzQG1IxfB7Hvc2tBBVmpWE2BTQGP9J1RrAvDT+Vc/uAxg=="],

    "electron-builder-squirrel-windows": ["electron-builder-squirrel-windows@26.15.7", "", { "dependencies": { "app-builder-lib": "26.15.7", "builder-util": "26.15.3", "electron-winstaller": "5.4.0" } }, "sha512-B4uvn2NzFSuf084udWqugludFull6CRJiWe2dLzMnZLl6G5hdAGk0fsBMGlBSpKjvQCJn8IPc+S7OnJ+GXqwLA=="],

-    "electron-context-menu": ["electron-context-menu@5.0.0", "", { "dependencies": { "cli-truncate": "^4.0.0", "electron-dl": "^4.0.0", "electron-is-dev": "^3.0.1" } }, "sha512-rgFpRtwY0/rhsRCoz9rE6VM4WueEsLbIpca7ucOhERVrbGB2dQrxa9xwBNLplU54jRgPuv6nTEbxoplE5bzy2A=="],
+    "electron-context-menu": ["electron-context-menu@4.1.2", "", { "dependencies": { "cli-truncate": "^4.0.0", "electron-dl": "^4.0.0", "electron-is-dev": "^3.0.1" } }, "sha512-9xYTUV0oRqKL50N9W71IrXNdVRB0LuBp3R1zkUdUc2wfIa2/QZwYYj5RLuO7Tn7ZSLVIaO3X6u+EIBK+cBvzrQ=="],

    "electron-dl": ["electron-dl@4.0.0", "", { "dependencies": { "ext-name": "^5.0.0", "pupa": "^3.1.0", "unused-filename": "^4.0.1" } }, "sha512-USiB9816d2JzKv0LiSbreRfTg5lDk3lWh0vlx/gugCO92ZIJkHVH0UM18EHvKeadErP6Xn4yiTphWzYfbA2Ong=="],

@@ -4128,7 +4126,7 @@

    "github-slugger": ["github-slugger@2.0.0", "", {}, "sha512-IaOQ9puYtjrkq7Y0Ygl9KDZnrf/aiUJYUpVf89y8kyaxbRG7Y1SrX/jaumrv81vc61+kiMempujsM3Yw7w5qcw=="],

-    "gitlab-ai-provider": ["gitlab-ai-provider@6.16.0", "", { "dependencies": { "@anthropic-ai/sdk": "^0.71.0", "@anycable/core": "^0.9.2", "graphql-request": "^6.1.0", "isomorphic-ws": "^5.0.0", "openai": "^6.16.0", "socket.io-client": "^4.8.1", "vscode-jsonrpc": "^8.2.1", "zod": "^3.25.76" }, "peerDependencies": { "@ai-sdk/provider": ">=3.0.0", "@ai-sdk/provider-utils": ">=4.0.0" } }, "sha512-HMC3sKgWYaYSsgm86Cnq2e6laHlYkhiFQ6rFD5qsVghv9//6h4Ofr7j5R2KjQx9Hl8EBercPsmzjoEjEN7dX5Q=="],
+    "gitlab-ai-provider": ["gitlab-ai-provider@6.12.1", "", { "dependencies": { "@anthropic-ai/sdk": "^0.71.0", "@anycable/core": "^0.9.2", "graphql-request": "^6.1.0", "isomorphic-ws": "^5.0.0", "openai": "^6.16.0", "socket.io-client": "^4.8.1", "vscode-jsonrpc": "^8.2.1", "zod": "^3.25.76" }, "peerDependencies": { "@ai-sdk/provider": ">=3.0.0", "@ai-sdk/provider-utils": ">=4.0.0" } }, "sha512-Qn5iHqvjG8yktI5MWaUgdRR94l7O4WtYW0CAbhsCh1Tj0Fei/DeprOYPVyf4Nht1Ix6U2PXSYM32QOHI6Z2TDw=="],

    "glob": ["glob@13.0.5", "", { "dependencies": { "minimatch": "^10.2.1", "minipass": "^7.1.2", "path-scurry": "^2.0.0" } }, "sha512-BzXxZg24Ibra1pbQ/zE7Kys4Ua1ks7Bn6pKLkVPZ9FZe4JQS6/Q7ef3LG1H+k7lUf5l4T3PLSyYyYJVYUvfgTw=="],

@@ -1,8 +1,8 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-DVimx64BQEkFaYZkW56E5eEfkGxuW5j/9C0wCImBFl4=",
-    "aarch64-linux": "sha256-MhMl/ZkvcPXE31OvysutI6nKIJ6XtUa3c71+B4hnaQc=",
-    "aarch64-darwin": "sha256-+wMPYLBnw2zTZj0if8EPwWC9O3tVqSgnhYNfQq8UZ8Q=",
-    "x86_64-darwin": "sha256-l6LxVSXDbqVoXMVcGZAzRER0bxP6wDU4dfRDolx0JGM="
+    "x86_64-linux": "sha256-8mOzCscBAuogG4tm8CroqjTX5E5yzCvTobbhKvxQP0U=",
+    "aarch64-linux": "sha256-drrRSpzxC8bfaTXBpOyaN0QAyBVV7WJzm0NstJ+8sAE=",
+    "aarch64-darwin": "sha256-YY5A/zxLPONvgnI+DZlzcD2K5Q9PIw4F2YbDxKbT4UU=",
+    "x86_64-darwin": "sha256-/c/Ew4onA+9+l6GRKXz3zWq3QFESM7j5RyGLCWRPQFw="
  }
 }
@@ -2,7 +2,7 @@
  "$schema": "https://json.schemastore.org/package.json",
  "name": "opencode",
  "description": "AI-powered development tool",
-  "version": "2.0.14",
+  "version": "2.0.10",
  "private": true,
  "type": "module",
  "packageManager": "bun@1.4.2",
@@ -173,7 +173,7 @@
    "solid-js@1.9.15": "patches/solid-js@1.9.15.patch",
    "@ai-sdk/mistral@3.0.51": "patches/@ai-sdk%2Fmistral@3.0.51.patch",
    "gcp-metadata@8.1.2": "patches/gcp-metadata@8.1.2.patch",
-    "pacote@21.5.1": "patches/pacote@21.5.1.patch",
+    "pacote@21.5.0": "patches/pacote@21.5.0.patch",
    "@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
    "@pierre/trees@1.0.0-beta.4": "patches/@pierre%2Ftrees@1.0.0-beta.4.patch",
    "@tanstack/virtual-core@3.17.8": "patches/@tanstack%2Fvirtual-core@3.17.8.patch",
@@ -10,15 +10,7 @@

 ## Conventions

-Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `Message.media(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, and `LLM.generateObject`. Use `LLMRequest.update(...)` when deriving canonical request data; do not add a duplicate `LLM.updateRequest(...)` path. Two ways to construct the same thing is one too many.
-
-Modality namespaces mirror `LLM` exactly: `Image.request`, `Image.generate`, `Image.stream` (later `Video`, `Speech`, `Transcription`). Common request fields (`images`, `mask`, `n`, `size`, `aspectRatio`, `seed`, `format`) lower natively or fail with a typed `AIError`; provider-native controls always live under `providerOptions`, never under a modality-specific `options` key.
-
-Media payloads are always `Media.Asset` (`src/media.ts`). Construct them with `Media.bytes`, `Media.base64`, `Media.url`, `Media.ref`, `Media.fromDataUrl`, or `Media.file`; never introduce a parallel `data: string | Uint8Array` shape. `MediaPart.media`, `ImageRequest.images`/`mask`, `ImageResponse.images`, and the `media` `LLMEvent` all share it. Protocols branch on `asset.source.type` and `asset.kind` and use `ProviderShared.inlineMedia` / `requireInlineMedia` / `mediaUrl` / `MediaInput.refID` rather than re-deriving base64 or URL handling.
-
-`schema/messages.ts → media.ts → route/executor-service.ts` is an accepted runtime dependency from the schema layer on the executor service tag: `Media.Asset.bytes()` must be able to download `url` sources, and the tag lives in that leaf module precisely so the schema barrel never imports the executor implementation (which imports the schema barrel back). Do not move the tag into `route/executor.ts` or import `route/executor.ts` from `src/schema/*` or `src/media.ts`.
-
-Nothing in `src/*` except `src/promise.ts` may know about Promises. `@opencode/ai/promise` (`AI.make({ layer? })`, default `ai`) is the single Promise/`AsyncIterable` surface for LLM and media; it runs the Effect APIs in one `ManagedRuntime` and rethrows `AIError` unchanged.
+Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, and `LLM.generateObject`. Use `LLMRequest.update(...)` when deriving canonical request data; do not add a duplicate `LLM.updateRequest(...)` path. Two ways to construct the same thing is one too many.

 - Prefer forward compatibility for provider-defined options that OpenCode only passes through. For pass-through string enums, expose known values for autocomplete while accepting future values with `Known | (string & {})`, and accept any string at runtime. Closed literals are appropriate when OpenCode branches on a value, transforms its associated structure, or otherwise cannot correctly handle an unknown variant. New options whose shape or behavior requires implementation remain unsupported until they are handled; do not blindly forward unknown structures.
 - Order reasoning-effort values from lowest to highest: `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, `max`. Provider-specific subsets follow the same relative order in types, schemas, option lists, and tests.
@@ -94,10 +86,6 @@ The four-axis decomposition is the reason DeepSeek, TogetherAI, Cerebras, Basete

 When a provider supports multiple physical transports, selection remains execution policy below its semantic route. `OpenResponsesChannel.transport(...)` owns the provider-neutral Responses WebSocket concept: it prepares one final request, executes HTTP by default, strips WebSocket-disallowed fields, and passes a generic channel exchange to a per-call `WebSocketChannelExecutor` when supplied. Provider-specific Responses routes opt in with handshake and connection-age policy. `Route.streamPrepared` owns decoding and acknowledges channel completion only after successful full consumption.

-### Media Routes
-
-Media does not fit the SSE-frames-to-event-state-machine LLM route. `MediaRoute.make(...)` (`src/route/media.ts`) composes a `MediaProtocol` kind with `Endpoint` and `Auth` and owns the transport plumbing: `http` option merging, URL/query rendering, auth headers, JSON vs multipart encoding, and handing the response back to the protocol. `MediaProtocol.inline` (`src/route/media-protocol.ts`) is `body.from(request)` plus `response.decode(response, context)`; use `MediaProtocol.decodeJson` / `text` / `bytes` so decode failures retain the raw body and HTTP context. `Generation` (`src/generation.ts`) is the provider-neutral handle for a queued generation over a `GenerationRoute` (`status`, `result`, `cancel`, `pollHint`); the first video route implements it. Image protocol files follow the same section order as LLM protocols and declare unsupported common fields once through `MediaInput.rejectUnsupported`.
-
 ### URL Construction

 `Endpoint` owns `{ baseURL, path, query }`. Each protocol route includes a canonical endpoint when the provider has one (e.g. `https://api.openai.com/v1`); provider helpers override endpoint fields by configuring the route before selecting a model. Generic OpenAI-compatible routes have no canonical URL and require configuration before execution.
@@ -106,12 +94,11 @@ For providers where the URL is derived from typed inputs (Azure resource name, B

 ### Provider Facades

-Provider-facing APIs are configured facades over route values. Endpoint/auth/resource/API-version setup happens before model selection, and model selectors accept only a model or deployment id. Media models use per-modality selectors on the same facade (`openai.image(id)`, later `.video` / `.speech` / `.transcription`) that mirror `openai.responses(id)`; the one-word overlap with the request namespace is accepted over a second construction path:
+Provider-facing APIs are configured facades over route values. Endpoint/auth/resource/API-version setup happens before model selection, and model selectors accept only a model or deployment id:

 ```ts
 const openai = OpenAI.configure({ apiKey, baseURL })
 const model = openai.responses("gpt-4o-mini")
-const image = openai.image("gpt-image-2")

 const azure = Azure.configure({ resourceName, apiKey, apiVersion: "v1" })
 const deployment = azure.responses("my-deployment")
@@ -8,10 +8,10 @@ import { LLM, LLMClient } from "@opencode/ai"
 import { RequestExecutor } from "@opencode/ai/route"
 import { OpenAI } from "@opencode/ai/providers"

-const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY })
+const model = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).responses("gpt-4o-mini")

 const request = LLM.request({
-  model: openai.responses("gpt-4o-mini"), // `.chat(...)` selects the Chat Completions API instead
+  model,
  system: "You are concise.",
  prompt: "Say hello in one short sentence.",
  generation: { maxTokens: 40 },
@@ -29,94 +29,6 @@ await Effect.runPromise(program.pipe(Effect.provide(llmLayer)))

 Run `LLMClient.stream(request)` instead of `generate` when you want incremental `LLMEvent`s. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses, Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.

-The same configured facade names image models. `Image.request` resolves the provider's image route from the ref and
-returns `Media.Asset`s with lazily decoded bytes:
-
-```ts
-import { NodeFileSystem } from "@effect/platform-node"
-import { Image, ImageClient, Media } from "@opencode/ai"
-
-const image = Effect.gen(function* () {
-  const response = yield* Image.generate({
-    model: openai.image("gpt-image-2"),
-    prompt: "A robot tending a rooftop garden",
-    size: "1024x1024",
-    providerOptions: { quality: "high" }, // typed per image model
-  })
-  yield* Media.write(response.image, "./garden.png")
-})
-
-// `asset.bytes()` / `Media.write` also need the executor, so merge it into the environment instead of hiding it.
-const imageLayer = ImageClient.layer.pipe(Layer.provideMerge(RequestExecutor.fetchLayer))
-
-await Effect.runPromise(image.pipe(Effect.provide(imageLayer), Effect.provide(NodeFileSystem.layer)))
-```
-
-Prefer promises? `@opencode/ai/promise` exposes the same LLM and image APIs over one managed runtime:
-
-```ts
-import { AI } from "@opencode/ai/promise"
-
-const ai = AI.make()
-const text = await ai.llm.generate({ model: openai.responses("gpt-4o-mini"), prompt: "Say hello." })
-const generated = await ai.image.generate({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" })
-for await (const event of ai.llm.stream({ model: openai.responses("gpt-4o-mini"), prompt: "Stream hello." })) {
-  // LLMEvent
-}
-await ai.dispose()
-```
-
-## Experimental evaluation
-
-Evaluation models compare shared state with typed choice, score, and boolean questions. The API is
-isolated under an experimental entrypoint and provider namespace while the contract evolves:
-
-```ts
-import { Effect } from "effect"
-import { Evaluation, EvaluationClient } from "@opencode/ai/experimental"
-import { TypeSafeAI } from "@opencode/ai/providers"
-
-const model = TypeSafeAI.configure().experimental.evaluation("jev-latest")
-
-const program = Evaluation.run({
-  model,
-  state: "I was charged twice. Please refund the duplicate payment.",
-  questions: {
-    department: {
-      type: "choice",
-      instructions: "Which team should handle this?",
-      criteria: { billing: "Payments and refunds", technical: "Bugs and outages" },
-    },
-    urgency: {
-      type: "score",
-      instructions: "How urgent is this?",
-      criteria: ["Can wait", "Needs prompt attention", "Blocking revenue"],
-    },
-    refund: { type: "boolean", instructions: "Is the customer asking for a refund?" },
-  },
-})
-
-const response = await Effect.runPromise(program.pipe(Effect.provide(EvaluationClient.fetchLayer)))
-
-console.log(response.answers.department.choice)
-console.log(response.answers.refund.probability)
-```
-
-`TypeSafeAI` reads `TYPESAFE_API_KEY`. `OpenCodeZen` exposes the same selector and reads
-`OPENCODE_API_KEY`. OpenRouter and Vercel AI Gateway use the same provider shape:
-
-```ts
-import { OpenRouter, VercelAIGateway } from "@opencode/ai/providers"
-
-OpenRouter.configure().experimental.evaluation("typesafe/jev-1.13")
-VercelAIGateway.configure().experimental.evaluation("typesafe-ai/jev")
-```
-
-OpenRouter reads `OPENROUTER_API_KEY`. Vercel reads `AI_GATEWAY_API_KEY`, then `VERCEL_OIDC_TOKEN`.
-The common API uses `boolean`; System One routes lower it to native `noul`.
-Choice and score confidence plus score legends remain available in provider metadata, and the
-provider's rounded probabilities are returned unchanged.
-
 ## Alibaba Cloud Model Studio

 `Alibaba` provides standard Model Studio inference. Configure a region explicitly, then select
@@ -402,25 +314,23 @@ citations or separate result blocks. Retain `response.message` for either API's
 Use `Image.generate` for one-off generation or editing:

 ```ts
-import { Image, Media } from "@opencode/ai"
+import { Image, ImageInput } from "@opencode/ai"

 const generation = Image.generate({
-  model: meta("muse-image-1.0"),
+  model: meta.image("muse-image-1.0"),
  prompt: "A flat black square on a white background.",
-  n: 1,
-  providerOptions: { reasoningStrength: "low" },
+  options: { n: 1, reasoningStrength: "low" },
 })

 const edit = Image.generate({
-  model: meta("muse-image-1.0"),
+  model: meta.image("muse-image-1.0"),
  prompt: "Make the square purple.",
-  images: [Media.bytes(imageBytes, "image/webp")],
-  format: "png",
-  providerOptions: { reasoningStrength: "low" },
+  images: [ImageInput.bytes(imageBytes, "image/webp")],
+  options: { outputFormat: "png", reasoningStrength: "low" },
 })
 ```

-The default image format is WEBP; `format` also accepts PNG/JPEG and `responseFormat: "url"`
+The default image format is WEBP; `outputFormat` also accepts PNG/JPEG and `responseFormat: "url"`
 returns a signed URL. `size` is an aspect-ratio hint. For conversational images, select
 `meta.responses("muse-image-1.0")` with `tools: [Meta.imageGeneration({ reasoningStrength: "low" })]`.
 Generated images are provider-executed tool results with file content. Retain `response.message` to
@@ -431,40 +341,29 @@ Meta Responses is explicitly HTTP/SSE-only and does not use WebSockets, even whe

 ## Image generation

-Use `Image.generate` with an image model for direct asset generation. `Image.request` mirrors `LLM.request`: the
-model comes from the facade's `.image(...)` selector (mirroring `.responses(...)`), common fields
-(`images`, `mask`, `n`, `size`, `aspectRatio`, `seed`, `format`) lower natively or fail typed, and
-`providerOptions` is inferred from the selected model:
+Use `Image.generate` with an image model for direct asset generation:

 ```ts
-import { Image, Media } from "@opencode/ai"
+import { Image, ImageInput } from "@opencode/ai"
 import { OpenAI } from "@opencode/ai/providers"

-const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY })
-
 const program = Effect.gen(function* () {
  const response = yield* Image.generate({
-    model: openai.image("gpt-image-2"),
+    model: OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY }).image("gpt-image-2"),
    prompt: "A robot tending a rooftop garden",
-    n: 2,
-    size: "1024x1024",
-    format: "webp",
-    providerOptions: {
+    options: {
+      n: 2,
+      size: "1024x1024",
      quality: "high", // inferred from the OpenAI image model
+      outputFormat: "webp",
      future_option: true, // unknown native options pass through unchanged
    },
  })

-  return response.images // Media.Asset[] with owned bytes or a provider URL
+  return response.images // GeneratedImage[] with owned bytes or a provider URL
 })
 ```

-`Media.Asset` is the one asset type shared by image requests, image responses, LLM messages, and tool results.
-`asset.source` is the serializable `Media.Source` (`bytes`, `base64`, `url`, or `ref`); `asset.bytes()`,
-`asset.base64()`, and `asset.dataUrl()` decode or download lazily and cache; `asset.materialize()` pulls a `url`
-asset into owned bytes before the provider URL expires. Construct assets with `Media.bytes`, `Media.base64`,
-`Media.url`, `Media.ref(provider, id)`, `Media.fromDataUrl`, or `Media.file(path)`.
-
 Pass ordered image inputs to the same method for editing, composition, or image-conditioned generation:

 ```ts
@@ -474,45 +373,49 @@ const response =
    model,
    prompt: "Combine these product photos into one studio scene",
    images: [
-      Media.bytes(firstBytes, "image/png"),
-      Media.url("https://example.com/second.webp"),
-      Media.ref("openai", "file_123"),
+      ImageInput.bytes(firstBytes, "image/png"),
+      ImageInput.url("https://example.com/second.webp"),
+      ImageInput.file("file_123"),
    ],
-    providerOptions,
+    options,
    http,
  })
 ```

-`Media.ref(provider, id)` represents provider file handles such as OpenAI file IDs or Gemini Files URIs; routes
-only forward refs that belong to their own provider. Raw strings are not accepted as image inputs, avoiding
-ambiguity between base64, URLs, and provider IDs. Empty or omitted `images` uses text-to-image generation; a
-non-empty array selects the provider's edit behavior without enforcing provider image-count limits locally. OpenAI
-uses multipart for byte/data-URL edits and its JSON reference body for URL or file-ID edits. The common `mask`
-field selects inpainting; routes that cannot honor it fail with `UnsupportedOperation`:
+`ImageInput.fileUri(uri, mediaType)` represents provider file URIs such as Gemini Files. Raw strings are not
+accepted as image inputs, avoiding ambiguity between base64, URLs, and provider IDs. Empty or omitted `images`
+uses text-to-image generation; a non-empty array selects the provider's edit behavior without enforcing provider
+image-count limits locally. `images` is the only common image-editing field. OpenAI uses multipart for byte/data-URL
+edits and its JSON reference body for URL or file-ID edits. Its provider-specific `options.mask` accepts an
+`ImageInput` for inpainting:

 ```ts
 yield *
  Image.generate({
-    model: openai.image("gpt-image-2"),
+    model: OpenAI.configure({ apiKey }).image("gpt-image-2"),
    prompt,
-    images: [Media.bytes(sourceBytes, "image/png")],
-    mask: Media.bytes(maskBytes, "image/png"),
+    images: [ImageInput.bytes(sourceBytes, "image/png")],
+    options: { mask: ImageInput.bytes(maskBytes, "image/png") },
  })
 ```

-On multipart requests, `http.body` can override option fields but not structural `model`, `prompt`, `image[]`,
-or `mask` fields, and the transport owns the multipart `Content-Type` boundary. For JSON requests, `http.body`
-remains the final raw-native overlay. Gemini does not fetch public HTTP URLs, and hosted Z.ai image generation does
-not accept image inputs. These cases fail with a typed `AIError` before network I/O.
+The OpenAI adapter extracts this helper value into the edit request's native `mask` field rather than passing the
+tagged `ImageInput` object through as an ordinary option. On multipart requests, `http.body` can override option
+fields but not structural `model`, `prompt`, `image[]`, or `mask` fields, and the transport owns the multipart
+`Content-Type` boundary. For JSON requests, `http.body` remains the final raw-native overlay. Gemini does not fetch
+public HTTP URLs, and hosted Z.ai image generation does not accept image inputs. These cases fail with
+`InvalidRequest` before network I/O.

 Provider-native image options belong to each request. Raw `http.body` fields have final precedence over them:

 ```ts
+const model = OpenAI.configure({ apiKey }).image("gpt-image-2")
+
 yield *
  Image.generate({
-    model: openai.image("gpt-image-2"),
+    model,
    prompt,
-    providerOptions: { quality: "medium" },
+    options: { quality: "medium" },
    http,
  })
 ```
@@ -522,11 +425,11 @@ xAI image models use the same request API with xAI-native controls:
 ```ts
 yield *
  Image.generate({
-    model: XAI.configure({ apiKey })("any-model-id"),
+    model: XAI.configure({ apiKey }).image("any-model-id"),
    prompt,
-    n: 2,
-    aspectRatio: "16:9",
-    providerOptions: {
+    options: {
+      n: 2,
+      aspectRatio: "16:9",
      resolution: "1k",
      responseFormat: "b64_json",
      future_option: true,
@@ -542,12 +445,12 @@ import { Google } from "@opencode/ai/providers"

 const googleProgram = Effect.gen(function* () {
  const response = yield* Image.generate({
-    model: Google.configure({ apiKey })("any-model-id"),
+    model: Google.configure({ apiKey }).image("any-model-id"),
    prompt: "A robot tending a rooftop garden",
-    aspectRatio: "16:9",
-    seed: 42,
-    providerOptions: {
+    options: {
+      aspectRatio: "16:9",
      imageSize: "2K",
+      seed: 42,
      thinkingLevel: "HIGH",
      includeThoughts: true,
      futureOption: true,
@@ -569,9 +472,9 @@ Z.ai image models infer open Z.ai-native options from the selected model:
 ```ts
 yield *
  Image.generate({
-    model: ZAI.configure({ apiKey })("any-model-id"),
+    model: ZAI.configure({ apiKey }).image("any-model-id"),
    prompt,
-    providerOptions: {
+    options: {
      quality: "hd",
      userID: "user-123",
      future_option: true,
@@ -581,8 +484,8 @@ yield *
 ```

 Z.ai does not include trustworthy MIME metadata for output URLs, so generated images use
-`application/octet-stream` until materialized. Output URLs expire after 30 days; call `asset.materialize()` and
-persist the bytes promptly if they must remain available.
+`application/octet-stream`. Output URLs expire after 30 days; download and persist them promptly if they must
+remain available.

 Conversational image generation remains part of the LLM interaction. OpenAI Responses exposes it through its hosted image tool:

@@ -600,7 +503,7 @@ const program = Effect.gen(function* () {
 })
 ```

-The hosted result is represented as a provider-executed tool call and tool result, and the generated image is also emitted as a first-class `media` `LLMEvent` (`response.message` then carries a `media` part). Gemini image-capable models emit the same `media` event for inline image output. Retaining `response.message` preserves the generated image for continuation on both routes.
+The hosted result is represented as a provider-executed tool call and tool result. Its image is a `file` content item with a data URI, so retaining `response.message` preserves the generated image for continuation.

 ## Public API

@@ -609,11 +512,8 @@ The hosted result is represented as a provider-executed tool call and tool resul
 - **`Message.user(...)` / `Message.assistant(...)` / `Message.tool(...)`** — message constructors from the canonical schema model.
 - **`LanguageModel.make(...)` / `ToolCallPart.make(...)` / `ToolResultPart.make(...)` / `ToolDefinition.make(...)`** — model and tool-related constructors from the canonical schema model.
 - **`LLMEvent.is.*`** — typed guards (`is.textDelta`, `is.toolCall`, `is.finish`, …) for filtering streams.
- **`Image.request` / `Image.generate` / `Image.stream`** — generate images through a provider-neutral image request and response model.
+- **`Image.generate({...})`** — generate images through a provider-neutral image request and response model.
 - **`ImageClient`** — Effect service and layer for image execution, parallel to `LLMClient`.
- **`Media`** — the shared asset type (`Media.Asset`, `Media.Source`) and constructors used by messages, tool results, and media requests.
- **`Generation`** — provider-neutral handle for an in-flight media generation (`await`, `refresh`, `cancel`, `events`) used by queued media routes.
- **`@opencode/ai/promise`** — `AI.make({ layer? })` and a default `ai` client exposing `llm` and `image` as Promise / `AsyncIterable` APIs.

 ## Testing

@@ -1,328 +0,0 @@
-# Media generation in `@opencode/ai` — public API direction
-
-Status: proposal. Branch `media-support`.
-
-## Goal
-
-`@opencode/ai` becomes the one package you reach for to generate anything: text, images, video, speech, transcripts, and later music and realtime. The LLM surface already exists and is shaped by three constraints: Effect-first, used by OpenCode Core, usable externally. Media has a different priority order: **external DX first**, Effect and Promise as peers, Core as one consumer among many.
-
-The design below is derived from a survey of the raw provider APIs (OpenAI, Gemini/Veo/Imagen, xAI, Stability, BFL, fal, Replicate, Runway, Luma, Kling, MiniMax, ElevenLabs, Deepgram, Cartesia, AssemblyAI, Lyria) and of existing multi-provider SDKs.
-
-## What the survey forces
-
-1. **Three execution shapes, everywhere.** Inline sync (OpenAI images, all TTS, Gemini), async job with polling or webhook (every video provider, BFL, fal, Replicate, AssemblyAI), and bidirectional streams (ElevenLabs/Cartesia/Deepgram WS, realtime). Video has no sync provider at all.
-2. **Output is never just bytes.** base64, signed URLs with TTLs from 10 minutes (BFL) to 2 days (Veo), URLs that need auth plus redirect (Veo), separate download endpoints (Sora `/content?variant=`), raw bodies (Stability, TTS). Multi-output is the norm.
-3. **Inputs have roles.** First/last frame, mask, style/subject reference, source video for edit/extend, reference audio, prior generation id, provider-side file handles (`file_id`, `gs://`, `runway://`, `mm_file://`).
-4. **Partial streaming is modality-specific.** Images: a few whole partial frames. Audio: ordered chunks plus timestamp events. Jobs: status/progress/logs. Video: none.
-5. **Usage is a union**: tokens, seconds, characters (often only in headers), credits, compute time.
-6. **Moderation can be partial success** (Veo strips audio but returns video). Deprecations are constant (Sora API shuts down 2026-09-24, Imagen on Gemini API 2026-08-17).
-
-## Where existing SDKs are weak and we should not be
-
- No streaming TTS.
- Video handles are experimental start/status pairs; the polling loop lives inside the generate call.
- Unsupported inputs become silent warnings arrays, so a request can succeed while dropping your mask.
- `n` is fanned out into hidden parallel calls, which obscures cost and idempotency.
- Each modality has its own bespoke result type; the file abstraction is a lazy base64/bytes pair with no URL, expiry, or provider ref.
- Effect's own `unstable/ai` has no media generation. Nothing in the Effect ecosystem owns this.
-
-## Design principles
-
- **Same shape as LLM.** `X.request(...)` → Schema class; `X.generate(request)` / `X.stream(request)`; `XClient.Service` + `layer`; typed `AIError`. If you know `LLM`, you know `Video`.
- **Execution shape is route policy, not API shape.** `Image.generate` returns an image whether the provider is inline or queued. Job control is available uniformly when you want it.
- **Errors, not warnings.** Unsupported common fields fail at the protocol boundary with a typed `AIError`, as the LLM routes do today. Provider-side partial results (filtered audio, moderated sample) surface as `notices` on the response, never as silent drops.
- **One asset type in, one asset type out**, shared with LLM messages and tool results.
- **Typed per-model options**, no hidden fan-out, no implicit retries that spend money.
- **Promise API is one mechanism for the whole package**, not a media-only wrapper.
- **One construction path per model.** Media models come from per-modality selectors on the configured facade (`openai.image("gpt-image-2")`), the same shape as `openai.responses("gpt-5")`.
-
-## Public API
-
-### Model selection
-
-A model value is built as `OpenAI.configure({ apiKey }).responses("gpt-5")` or `.image("gpt-image-2")`: `configure` fixes credentials, endpoint, and defaults; the selector fixes which of the provider's APIs to hit and binds the typed `providerOptions` generic. Media follows the same shape with one selector per modality — `openai.image(id)` today, `.video(id)` / `.speech(id)` / `.transcription(id)` as those modalities land — mirroring `openai.responses(id)`. `Image.request` accepts `ImageModel` only, exactly as `LLM.request` accepts `LanguageModel`.
-
-```ts
-import { OpenAI, Google } from "@opencode/ai/providers"
-
-const openai = OpenAI.configure({ apiKey })      // OpenAI(...) alone uses env auth (OPENAI_API_KEY)
-
-LLM.request({ model: openai.responses("gpt-5"), prompt })
-Image.request({ model: openai.image("gpt-image-2"), prompt })
-Video.request({ model: google.video("veo-3.1-generate-preview"), prompt })
-Speech.request({ model: openai.speech("gpt-4o-mini-tts"), text })
-Transcription.request({ model: openai.transcription("gpt-4o-transcribe"), audio })
-```
-
-The request namespace and the selector share one word (`Image.request` + `.image(...)`). That redundancy is accepted: a callable facade returning a lazily resolved ref would be a second way to construct the same model, and the type machinery to infer `providerOptions` through it is not worth one word. Where a provider has two APIs for one modality, the selectors stay explicit (`openai.chat`, a future `google.imagen`), and one default per modality per provider is part of the facade definition (OpenAI image → Images API, Google image → Gemini-native since Imagen on the Gemini API shuts down 2026-08-17). Provider package entrypoints keep `model(modelID, settings)` per modality-specific path, e.g. `@opencode/ai/providers/openai/responses`.
-
-### `Media` — the asset type
-
-Replaces `MediaPart.data: string | Uint8Array`, `ImageInput`, `GeneratedImage`, and aligns `Tool.FileContent`.
-
-```ts
-import { Media } from "@opencode/ai"
-
-Media.Source =
-  | { type: "bytes";  data: Uint8Array; mediaType: string }
-  | { type: "base64"; data: string;     mediaType: string }
-  | { type: "url";    url: string; mediaType?: string; expiresAt?: number; headers?: Record<string, string> }
-  | { type: "ref";    provider: ProviderID; id: string; mediaType?: string }   // file_id, gs://, runway://, prior generation
-
-class Media.Asset {
-  readonly source: Media.Source
-  readonly mediaType: string                    // always resolved (sniffed when the provider omits it)
-  readonly kind: "image" | "video" | "audio" | "document" | "other"
-  readonly info?: { width?; height?; durationSeconds?; sampleRate?; channels?; encoding?; format? }
-  readonly expiresAt?: number
-  readonly providerMetadata?: ProviderMetadata
-
-  bytes(): Effect<Uint8Array, AIError, RequestExecutor.Service>   // downloads/decodes lazily, cached
-  base64(): Effect<string, AIError, RequestExecutor.Service>
-  dataUrl(): Effect<string, AIError, RequestExecutor.Service>
-  materialize(): Effect<Media.Asset, AIError, RequestExecutor.Service>  // url/ref → bytes, before the URL dies
-}
-
-Media.bytes(data, mediaType?)      Media.base64(data, mediaType?)
-Media.url(url, options?)           Media.ref(provider, id)
-Media.file(path)                   // Bun/Node: reads + sniffs; Effect FileSystem variant for layers
-Media.write(asset, path)           // convenience, uses FileSystem
-```
-
-Raw-PCM outputs (Gemini TTS, Cartesia raw, Deepgram WS) carry `info.encoding/sampleRate/channels` because there is no container header.
-
-### Modality namespaces
-
-Each namespace mirrors `LLM` exactly.
-
-```ts
-import { Image, Video, Speech, Transcription } from "@opencode/ai"
-import { OpenAI, Google, ElevenLabs, Fal } from "@opencode/ai/providers"
-```
-
-#### Image
-
-```ts
-const request = Image.request({
-  model: openai.image("gpt-image-2"),
-  prompt: "A robot tending a rooftop garden",
-  images: [Media.file("./ref.png")],           // references / edit sources
-  mask: Media.file("./mask.png"),
-  n: 2,
-  size: "1536x1024",                            // or aspectRatio: "3:2"
-  seed: 7,
-  format: "webp",
-  providerOptions: { quality: "high", background: "transparent" },   // typed per model
-})
-
-const response = yield* Image.generate(request)   // ImageResponse
-response.image                                    // Media.Asset (first)
-response.images                                   // Media.Asset[]
-response.usage                                    // Usage union (see below)
-response.notices                                  // moderation / partial-result notices
-
-yield* Image.stream(request)                      // Stream<ImageEvent>
-// ImageEvent: generation-queued | generation-progress | image-partial { index, image } | image { index, image } | finish { usage }
-```
-
-Editing is not a separate function; `images`/`mask` on the request select the edit path in the route (OpenAI `/images/edits`, Gemini multimodal parts, xAI `/images/edits`). Routes that cannot honor `mask` fail with `Unsupported`.
-
-#### Video
-
-```ts
-const request = Video.request({
-  model: google.video("veo-3.1-generate-preview"),
-  prompt: "Panning wide shot of a calico kitten sleeping in the sunshine",
-  frames: { first: Media.file("./start.png"), last: Media.file("./end.png") },
-  references: [Media.url("https://…/style.png")],
-  video: Media.ref("openai", "video_123"),      // edit / extend / remix source
-  durationSeconds: 8,
-  aspectRatio: "16:9",
-  resolution: "1080p",
-  audio: true,
-  n: 1,
-  providerOptions: { personGeneration: "dont_allow", negativePrompt: "text, watermark" },
-})
-
-// Simple: wait for it.
-const response = yield* Video.generate(request, { poll: { interval: "10 seconds", timeout: "10 minutes" } })
-response.video                                     // Media.Asset (url with expiresAt, or bytes when the route downloads)
-yield* response.video.materialize()                // pull bytes before the URL expires
-
-// Explicit generation control.
-const generation = yield* Video.start(request)     // Generation<VideoResponse>
-generation.id; generation.status; generation.progress; generation.token   // token is serializable JSON
-yield* generation.await({ poll })                  // VideoResponse
-yield* generation.cancel()
-
-// Resume from another process.
-const resumed = yield* Video.resume(model, token)  // Generation<VideoResponse>
-
-// Progress as a stream.
-yield* Video.stream(request)                       // Stream<VideoEvent>: generation-queued { position } | generation-progress { progress, logs } | video { index, video } | finish
-```
-
-Webhooks: `Video.complete(model, token, webhook)` finishes a generation from a webhook payload without polling. Token shape is route-owned and opaque (Veo operation name, fal `response_url`, Runway task id).
-
-#### Speech (TTS)
-
-```ts
-const request = Speech.request({
-  model: elevenlabs.speech("eleven_v3"),
-  text: "Hello from OpenCode.",
-  voice: "JBFqnCBsd6RMkjVDRZzb",                  // name, uuid, or { id } — provider-normalized
-  format: "mp3",                                   // mp3 | wav | pcm | opus | aac | flac | (string & {})
-  speed: 1.0,
-  language: "en",
-  instructions: "Warm, unhurried.",
-  providerOptions: { stability: 0.5 },
-})
-
-const response = yield* Speech.generate(request)   // SpeechResponse: audio: Media.Asset, timestamps?, usage
-yield* Speech.stream(request)                      // Stream<SpeechEvent>: audio-delta { chunk } | timestamps { words } | finish
-```
-
-Streaming TTS is first-class on day one: OpenAI `stream_format: sse`, ElevenLabs `/stream`, Cartesia SSE, Deepgram chunked. Input-streaming TTS (WS, text arrives incrementally) is a later `Speech.session(...)` scoped resource, not part of `generate`.
-
-#### Transcription (STT)
-
-```ts
-const request = Transcription.request({
-  model: openai.transcription("gpt-4o-transcribe"),
-  audio: Media.file("./call.wav"),
-  language: "en",
-  prompt: "Names: Shoubhit, OpenCode.",
-  timestamps: "word",                              // none | segment | word
-  diarize: true,
-  providerOptions: { chunkingStrategy: "auto" },
-})
-
-const response = yield* Transcription.generate(request)
-response.text; response.segments; response.words; response.language; response.durationSeconds
-yield* Transcription.stream(request)               // Stream<TranscriptionEvent>: text-delta | segment | finish
-```
-
-Realtime STT over WebSocket is the same future `session` shape as input-streaming TTS.
-
-### `Generation` — shared async execution
-
-```ts
-class Generation<Response> {
-  readonly id: string
-  readonly model: MediaModel
-  readonly token: unknown                          // route-owned serializable JSON
-  readonly status: "queued" | "running" | "completed" | "failed" | "cancelled" | "expired"
-  readonly progress?: number                       // 0..1, normalized
-  readonly position?: number
-  readonly expiresAt?: number
-  refresh(): Effect<Generation<Response>, AIError>
-  await(options?: { poll?: Poll }): Effect<Response, AIError>
-  cancel(): Effect<void, AIError>
-  events(options?): Stream<GenerationEvent, AIError>
-}
-
-Poll = { interval?: Duration; timeout?: Duration; schedule?: Schedule }   // route may override from provider hints (`openai-poll-after-ms`)
-```
-
-`Generation` is not video-specific. Image routes on BFL, fal, and Replicate are queued; `Image.start` exists for them. A route declares itself `inline` or `queued`; `generate` on a queued route is `start` then `await`.
-
-### Usage
-
-```ts
-Usage =
-  | { type: "tokens"; input; output; total; details? }
-  | { type: "seconds"; seconds }
-  | { type: "characters"; characters }
-  | { type: "credits"; credits }
-  | { type: "compute"; seconds }
-```
-
-Header-only usage (ElevenLabs `character-cost`, Deepgram `dg-char-count`) is lifted into `usage` by the route.
-
-### Promise API — `@opencode/ai/promise`
-
-Mirrors the `packages/plugin/src/effect` and `packages/plugin/src/promise` split that already exists in this repo. One mechanism for LLM and media.
-
-```ts
-import { AI } from "@opencode/ai/promise"
-
-const ai = AI.make()                                // ManagedRuntime over RequestExecutor.fetchLayer + all clients
-// AI.make({ layer }) to inject a custom executor / recorder / middleware
-
-const image = await ai.image.generate({ model, prompt })
-await image.image.bytes()
-
-for await (const event of ai.speech.stream({ model, text, voice })) { … }
-
-const generation = await ai.video.start({ model, prompt })
-const video = await generation.await({ poll: { interval: 10_000 }, signal })
-const resumed = ai.video.resume(model, JSON.parse(saved))
-
-const text = await ai.llm.generate({ model, prompt })   // closes today's gap: LLM has no promise API either
-for await (const event of ai.llm.stream(request)) { … }
-
-await ai.dispose()
-```
-
-Streams become `AsyncIterable` via `Stream.toAsyncIterable`. `AIError` is thrown as-is. `AbortSignal` maps to interruption. Nothing in `src/*` except this entrypoint knows about promises.
-
-### Providers
-
-Existing facades gain per-modality selectors; the modality routes each facade provides:
-
-| Facade | llm | image | video | speech | transcription | other |
-|---|---|---|---|---|---|---|
-| `OpenAI` | responses (default), chat | Images API | Sora (deprecated 2026-09-24) | ✓ | ✓ | |
-| `Google` | Gemini | Gemini-native (default), `imagen` | Veo | Gemini TTS | Gemini transcribe | |
-| `XAI` | ✓ | ✓ | ✓ | | | |
-| `ElevenLabs` | | | | ✓ | Scribe | soundEffect, music |
-| `Fal` | | ✓ | ✓ | | | |
-| `Replicate`, `Runway`, `Luma`, `Kling`, `MiniMax`, `Deepgram`, `Cartesia`, `AssemblyAI`, `BlackForestLabs`, `Stability` | | per provider | | | | |
-
-New facades follow the existing one-file-per-provider rule. Package entrypoints are modality-specific, such as `@opencode/ai/providers/openai/images`, and return the concrete model.
-
-`ImageModel<Options>` already gives typed `providerOptions` per model; `VideoModel`, `SpeechModel`, `TranscriptionModel` follow the same generic. A shared `MediaModel` union is what `Generation` and the promise client key on.
-
-### Routes and protocols
-
-Media does not fit the LLM four-axis route (SSE frames → event state machine) except for streaming TTS/STT. Reuse `Endpoint`, `Auth`, `Framing`, `RequestExecutor`, and add media protocol kinds:
-
- `MediaProtocol.inline` — `body.from(request)` (JSON, multipart, or query), `response.decode(response)` (JSON, or binary body → `Media.Asset`).
- `MediaProtocol.queued` — `start`, `status`, `result`, `cancel`, optional `download`, `pollHint`, `token` schema.
- `MediaProtocol.stream` — framing + `step` state machine emitting modality events, same discipline as LLM protocols.
-
-`Route.make` for media composes one protocol kind with endpoint/auth. The existing `ImageRoute { generate(request, execute) }` is the ad-hoc version of `inline` and gets folded in.
-
-### LLM integration
-
- `MediaPart` becomes `{ type: "media"; media: Media.Asset; … }` so protocols branch on `kind` and can pass `url`/`ref` sources through natively (OpenAI `image_url`, Gemini `fileData`).
- New `LLMEvent`s: `media { media: Media.Asset }` so Gemini inline image output is first-class instead of dropped. OpenAI Responses `image_generation_call` keeps its single carrier — the provider-executed `tool-result` with `file` content — because Core consumes hosted tool-result content today and has no `media` event handling yet; it switches to the `media` carrier when Core adopts the event, so the image is never emitted twice.
- `Message.assistant([...])` accepts media parts; Gemini multi-turn image editing replays them.
- `Tool.FileContent` aligns with `Media.Source`.
-
-## Decisions
-
-All settled:
-
-1. **Per-modality selectors** (`openai.image(id)`, `.video`, `.speech`, `.transcription`) name media models, mirroring `openai.responses(id)`. The one-word overlap with the request namespace is accepted over a callable-facade `ModelRef` as a second construction path.
-2. **`providerOptions` everywhere** (rename current `Image.options`) for consistency with LLM.
-3. **No hidden `n` fan-out.** `n` lowers natively; routes that cannot do `n > 1` fail typed. Callers use `Effect.all` / `Promise.all` explicitly.
-4. **Errors over warnings** for unsupported common fields; `notices` for provider-side partial results only.
-5. **`Media.Asset` is a class** (lazy bytes, cached) with `Media.Source` as the serializable Schema for wire/persistence. `Asset.from(source)` / `asset.source` round-trip losslessly. Same pattern as `LanguageModel` today.
-6. **Promise entrypoint**: `@opencode/ai/promise` exporting `AI.make(options?: { layer? })` plus a module-level default `ai` for scripts, covering LLM too.
-7. **Modality set for v1**: `Image`, `Video`, `Speech`, `Transcription`. `Music`/`SoundEffect` and `session` (bidirectional WS, realtime) are designed-for but deferred.
-8. **Sora is skipped** (API shuts down 2026-09-24). Video launches with Veo, xAI, fal, Runway.
-
-## Build order
-
-Foundation + Image ship together as the reference implementation, serially. Video, Speech, and Transcription then proceed in parallel on separate branches. Image jobs and partial streaming come last, after Video has hardened `Generation`.
-
-## Phasing
-
-1. **Foundation** — per-modality selectors, `Media`, `Generation`, `Poll`, `Usage` union, `MediaProtocol` kinds, `@opencode/ai/promise` with `llm` + `image`. Port the five existing image protocols onto it. Unify `MediaPart` and add the `media` LLM event (fixes Gemini image output being dropped).
-2. **Video** — Veo, xAI, fal, Runway first. Then Luma, Kling, MiniMax, Replicate.
-3. **Speech + Transcription** — OpenAI, ElevenLabs, Gemini TTS, Deepgram, Cartesia, AssemblyAI. Streaming TTS from the start.
-4. **Image queued routes and partials** — BFL, fal, Replicate, Stability; OpenAI `partial_images` streaming.
-5. **Later** — ElevenLabs music/SFX, Lyria, `Speech.session` / `Transcription.session`, realtime.
-
-Core adoption (session attachments beyond png/jpeg/gif/webp/pdf, image-generation tool, TUI rendering) comes after phase 1 and is a Core concern.
@@ -1,17 +1,5 @@
 import { Config, Effect, Formatter, Layer, Schema, Stream } from "effect"
-import { NodeFileSystem } from "@effect/platform-node"
-import {
-  Image,
-  ImageClient,
-  LLM,
-  LLMClient,
-  LLMRequest,
-  Media,
-  Message,
-  ProviderID,
-  Tool,
-  ToolRuntime,
-} from "@opencode/ai"
+import { LLM, LLMClient, LLMRequest, Message, ProviderID, Tool, ToolRuntime } from "@opencode/ai"
 import { Route, Auth, Endpoint, Framing, Protocol, RequestExecutor } from "@opencode/ai/route"
 import { OpenAI } from "@opencode/ai/providers"

@@ -28,18 +16,15 @@ import { OpenAI } from "@opencode/ai/providers"

 const apiKey = Config.redacted("OPENAI_API_KEY")

-// 1. Configure a provider. The configured facade records provider identity,
-// deployment options, authentication, and defaults. Per-modality selectors pick
-// the API: `.responses(...)` / `.chat(...)` for LLM calls and `.image(...)` for
-// image generation.
-const openai = OpenAI.configure({
+// 1. Pick a model. The provider helper records provider identity, protocol
+// choice, capabilities, deployment options, authentication, and defaults.
+const model = OpenAI.configure({
  apiKey,
  generation: { maxTokens: 160 },
  providerOptions: {
    store: false,
  },
-})
-const model = openai.responses("gpt-4o-mini")
+}).model("gpt-4o-mini")

 // 2. Build a provider-neutral request. This is useful when reusing one request
 // across generate and stream examples.
@@ -224,39 +209,18 @@ const FakeEcho = {
  }),
 }

-// 8. Image generation uses the same facade and the same request/generate shape.
-// `response.image` is a `Media.Asset`: bytes decode lazily and are cached, and
-// `Media.write` persists them through the Effect `FileSystem`.
-const generateImage = Effect.gen(function* () {
-  const response = yield* Image.generate({
-    model: openai.image("gpt-image-1-mini"),
-    prompt: "A flat black circle centered on a plain white background.",
-    size: "1024x1024",
-    format: "jpeg",
-    providerOptions: { quality: "low" },
-  })
-
-  console.log("\n== image ==")
-  console.log("media type:", response.image.mediaType)
-  console.log("bytes:", (yield* response.image.bytes()).byteLength)
-  console.log("usage", Formatter.formatJson(response.usage, { space: 2 }))
-  yield* Media.write(response.image, "tutorial-image.jpg").pipe(Effect.provide(NodeFileSystem.layer))
-})
-
 // Provide the LLM runtime and the HTTP request executor once. Keep one path
 // enabled at a time so the tutorial can demonstrate generate, stream, or
 // tool-loop behavior without spending tokens on every example.
 const requestExecutorLayer = RequestExecutor.fetchLayer
 const llmClientLayer = LLMClient.layer.pipe(Layer.provide(requestExecutorLayer))
-const imageClientLayer = ImageClient.layer.pipe(Layer.provide(requestExecutorLayer))

 const program = Effect.gen(function* () {
  // yield* generateOnce
  // yield* streamText
  // yield* generateStructuredObject
  // yield* generateDynamicObject.pipe(Effect.andThen((response) => Effect.sync(() => console.log(response.object))))
-  // yield* generateImage
  yield* streamWithTools
-}).pipe(Effect.provide(Layer.mergeAll(requestExecutorLayer, llmClientLayer, imageClientLayer)))
+}).pipe(Effect.provide(Layer.mergeAll(requestExecutorLayer, llmClientLayer)))

 Effect.runPromise(program)
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "2.0.14",
+  "version": "2.0.10",
  "name": "@opencode/ai",
  "type": "module",
  "license": "MIT",
@@ -15,7 +15,6 @@
  ],
  "exports": {
    ".": "./src/index.ts",
-    "./promise": "./src/promise.ts",
    "./testing": "./src/testing.ts",
    "./*": "./src/*.ts"
  },
@@ -1,29 +0,0 @@
-export { EvaluationClient } from "./experimental/evaluation-client.js"
-export {
-  BooleanAnswer,
-  BooleanQuestion,
-  ChoiceAnswer,
-  ChoiceQuestion,
-  Evaluation,
-  EvaluationAnswer,
-  EvaluationInput,
-  EvaluationModel,
-  EvaluationModelSchema,
-  EvaluationQuestion,
-  EvaluationRequest,
-  EvaluationResponse,
-  EvaluationRounding,
-  ScoreAnswer,
-  ScoreQuestion,
-} from "./experimental/evaluation.js"
-export type {
-  AnswerFor,
-  AnswersFor,
-  EvaluationModelOptions,
-  EvaluationOptions,
-  EvaluationQuestions,
-  EvaluationRequestFor,
-  EvaluationRequestInput,
-  EvaluationResponseFor,
-  EvaluationRoute,
-} from "./experimental/evaluation.js"
@@ -1,96 +0,0 @@
-import { Context, Effect, Layer } from "effect"
-import { RequestExecutor } from "../route/executor.js"
-import { AIError, InvalidProviderOutputError, mergeHttpOptions } from "../schema/index.js"
-import { sanitizeSurrogates } from "../utils/sanitize.js"
-import {
-  type EvaluationOptions,
-  type EvaluationQuestions,
-  type EvaluationRequestFor,
-  type EvaluationResponseFor,
-} from "./evaluation.js"
-
-export type Execute = RequestExecutor.Interface["execute"]
-
-export interface Interface {
-  readonly evaluate: <Options extends EvaluationOptions, const Questions extends EvaluationQuestions>(
-    request: EvaluationRequestFor<Options, Questions>,
-  ) => Effect.Effect<EvaluationResponseFor<Questions>, AIError>
-}
-
-export class Service extends Context.Service<Service, Interface>()("@opencode/AI/Experimental/EvaluationClient") {}
-
-export const evaluate = <Options extends EvaluationOptions, const Questions extends EvaluationQuestions>(
-  request: EvaluationRequestFor<Options, Questions>,
-): Effect.Effect<EvaluationResponseFor<Questions>, AIError, Service> =>
-  Effect.flatMap(Service, (client) => client.evaluate(request))
-
-export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
-  Service,
-  Effect.gen(function* () {
-    const executor = yield* RequestExecutor.Service
-    return Service.of({
-      evaluate: (request) =>
-        request.model.route
-          .evaluate(
-            {
-              ...sanitizeSurrogates({
-                ...request,
-                model: undefined,
-                http: mergeHttpOptions(request.model.http, request.http),
-              }),
-              model: request.model,
-            },
-            executor.execute,
-          )
-          .pipe(
-            Effect.flatMap((response) => {
-              const questions = Object.entries(request.questions)
-              if (
-                questions.length === Object.keys(response.answers).length &&
-                questions.every(([id, question]) => {
-                  const answer = response.answers[id]
-                  if (question.type === "boolean") return answer?.type === "boolean"
-                  if (question.type === "choice") {
-                    if (answer?.type !== "choice" || !Object.hasOwn(question.criteria, answer.choice)) return false
-                    if (answer.probabilities === undefined) return true
-                    const keys = Object.keys(question.criteria)
-                    const probabilities = answer.probabilities
-                    return (
-                      Object.keys(probabilities).length === keys.length &&
-                      keys.every((key) => Object.hasOwn(probabilities, key))
-                    )
-                  }
-                  if (answer?.type !== "score" || answer.score < 0 || answer.score > question.criteria.length - 1)
-                    return false
-                  if (answer.probabilities === undefined) return true
-                  const keys = question.criteria.map((_, index) => String(index))
-                  const probabilities = answer.probabilities
-                  return (
-                    Object.keys(probabilities).length === keys.length &&
-                    keys.every((key) => Object.hasOwn(probabilities, key))
-                  )
-                })
-              )
-                return Effect.succeed(response as EvaluationResponseFor<typeof request.questions>)
-              return Effect.fail(
-                new AIError({
-                  reason: new InvalidProviderOutputError({
-                    route: request.model.route.id,
-                    message: "Evaluation answers do not match the requested questions",
-                    cause: response.answers,
-                  }),
-                }),
-              )
-            }),
-          ),
-    })
-  }),
-)
-export const fetchLayer = layer.pipe(Layer.provide(RequestExecutor.fetchLayer))
-
-export const EvaluationClient = {
-  Service,
-  layer,
-  fetchLayer,
-  evaluate,
-} as const
@@ -1,245 +0,0 @@
-import { Effect, Schema } from "effect"
-import {
-  AIError,
-  HttpOptions,
-  InvalidRequestError,
-  ModelID,
-  ProviderID,
-  ProviderMetadata,
-  Usage,
-} from "../schema/index.js"
-import { EvaluationClient, Service, type Execute } from "./evaluation-client.js"
-
-export const EvaluationInput = Schema.Union([Schema.String, Schema.JsonObject, Schema.Array(Schema.Json)])
-export type EvaluationInput = Schema.Schema.Type<typeof EvaluationInput>
-
-const EvaluationCriterion = Schema.NullOr(EvaluationInput)
-const ChoiceCriteria = Schema.Record(Schema.String, EvaluationCriterion).pipe(
-  Schema.refine((x): x is typeof x => Object.keys(x).length > 0, {
-    message: "Choice criteria must be a nonempty option map",
-  }),
-)
-
-export const ChoiceQuestion = Schema.Struct({
-  type: Schema.Literal("choice"),
-  instructions: EvaluationInput,
-  criteria: ChoiceCriteria,
-})
-export type ChoiceQuestion = Schema.Schema.Type<typeof ChoiceQuestion>
-
-export const ScoreQuestion = Schema.Struct({
-  type: Schema.Literal("score"),
-  instructions: EvaluationInput,
-  criteria: Schema.Array(EvaluationCriterion).check(Schema.isMinLength(2)),
-})
-export type ScoreQuestion = Schema.Schema.Type<typeof ScoreQuestion>
-
-export const BooleanQuestion = Schema.Struct({
-  type: Schema.Literal("boolean"),
-  instructions: EvaluationInput,
-  criteria: Schema.optional(
-    Schema.Struct({
-      true: Schema.optional(EvaluationCriterion),
-      false: Schema.optional(EvaluationCriterion),
-    }),
-  ),
-})
-export type BooleanQuestion = Schema.Schema.Type<typeof BooleanQuestion>
-
-export const EvaluationQuestion = Schema.Union([ChoiceQuestion, ScoreQuestion, BooleanQuestion]).pipe(
-  Schema.toTaggedUnion("type"),
-)
-export type EvaluationQuestion = Schema.Schema.Type<typeof EvaluationQuestion>
-export type EvaluationQuestions = Readonly<Record<string, EvaluationQuestion>>
-const EvaluationQuestions = Schema.Record(Schema.String, EvaluationQuestion).pipe(
-  Schema.refine((x): x is typeof x => Object.keys(x).length > 0, {
-    message: "Evaluation questions must be a nonempty map",
-  }),
-)
-
-const Probability = Schema.Number.check(Schema.isBetween({ minimum: 0, maximum: 1 }))
-
-export const ChoiceAnswer = Schema.Struct({
-  type: Schema.Literal("choice"),
-  choice: Schema.String,
-  probabilities: Schema.optional(Schema.Record(Schema.String, Probability)),
-})
-export type ChoiceAnswer = Schema.Schema.Type<typeof ChoiceAnswer>
-
-export const ScoreAnswer = Schema.Struct({
-  type: Schema.Literal("score"),
-  score: Schema.Number,
-  probabilities: Schema.optional(Schema.Record(Schema.String, Probability)),
-})
-export type ScoreAnswer = Schema.Schema.Type<typeof ScoreAnswer>
-
-export const BooleanAnswer = Schema.Struct({
-  type: Schema.Literal("boolean"),
-  probability: Probability,
-})
-export type BooleanAnswer = Schema.Schema.Type<typeof BooleanAnswer>
-
-export const EvaluationAnswer = Schema.Union([ChoiceAnswer, ScoreAnswer, BooleanAnswer]).pipe(
-  Schema.toTaggedUnion("type"),
-)
-export type EvaluationAnswer = Schema.Schema.Type<typeof EvaluationAnswer>
-
-export type AnswerFor<Question extends EvaluationQuestion> = Question extends {
-  readonly type: "choice"
-  readonly criteria: infer Criteria
-}
-  ? {
-      readonly type: "choice"
-      readonly choice: Extract<keyof Criteria, string>
-      readonly probabilities?: Readonly<Record<Extract<keyof Criteria, string>, number>>
-    }
-  : Question extends { readonly type: "score" }
-    ? ScoreAnswer
-    : BooleanAnswer
-
-export type AnswersFor<Questions extends EvaluationQuestions> = {
-  readonly [ID in keyof Questions]: AnswerFor<Questions[ID]>
-}
-
-export type EvaluationOptions = Record<string, unknown>
-
-export interface EvaluationRoute<Options extends EvaluationOptions = EvaluationOptions> {
-  readonly id: string
-  readonly evaluate: (
-    request: EvaluationRequestFor<Options>,
-    execute: Execute,
-  ) => Effect.Effect<EvaluationResponse, AIError>
-}
-
-export class EvaluationModel<Options extends EvaluationOptions = EvaluationOptions> {
-  declare protected readonly _Options: (options: Options) => Options
-  readonly id: ModelID
-  readonly provider: ProviderID
-  readonly route: EvaluationRoute<Options>
-  readonly http?: HttpOptions
-
-  constructor(input: EvaluationModel.Input<Options>) {
-    this.id = input.id
-    this.provider = input.provider
-    this.route = input.route
-    this.http = input.http
-  }
-
-  static make<Options extends EvaluationOptions = EvaluationOptions>(input: EvaluationModel.MakeInput<Options>) {
-    return new EvaluationModel<Options>({
-      id: ModelID.make(input.id),
-      provider: ProviderID.make(input.provider),
-      route: input.route,
-      http: input.http,
-    })
-  }
-}
-
-export namespace EvaluationModel {
-  export interface Input<Options extends EvaluationOptions = EvaluationOptions> {
-    readonly id: ModelID
-    readonly provider: ProviderID
-    readonly route: EvaluationRoute<Options>
-    readonly http?: HttpOptions
-  }
-
-  export interface MakeInput<Options extends EvaluationOptions = EvaluationOptions>
-    extends Omit<Input<Options>, "id" | "provider"> {
-    readonly id: string | ModelID
-    readonly provider: string | ProviderID
-  }
-}
-
-export const EvaluationModelSchema = Schema.declare(
-  (value): value is EvaluationModel => value instanceof EvaluationModel,
-  {
-    expected: "Evaluation.Model",
-  },
-)
-
-export class EvaluationRequest extends Schema.Class<EvaluationRequest>("Evaluation.Request")({
-  model: EvaluationModelSchema,
-  state: EvaluationInput,
-  questions: EvaluationQuestions,
-  options: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
-  http: Schema.optional(HttpOptions),
-}) {
-  declare protected readonly _EvaluationRequest: void
-}
-
-export type EvaluationModelOptions<Model> = Model extends EvaluationModel<infer Options> ? Options : never
-
-export type EvaluationRequestFor<
-  Options extends EvaluationOptions = EvaluationOptions,
-  Questions extends EvaluationQuestions = EvaluationQuestions,
-> = Omit<EvaluationRequest, "model" | "questions" | "options"> & {
-  readonly model: EvaluationModel<Options>
-  readonly questions: Questions
-  readonly options?: Options
-}
-
-export type EvaluationRequestInput<
-  Model extends object = EvaluationModel,
-  Questions extends EvaluationQuestions = EvaluationQuestions,
-> = Omit<ConstructorParameters<typeof EvaluationRequest>[0], "model" | "questions" | "options" | "http"> & {
-  readonly model: Model
-  readonly questions: Questions
-  readonly options?: NoInfer<EvaluationModelOptions<Model>>
-  readonly http?: HttpOptions.Input
-} & (Model extends EvaluationModel<EvaluationModelOptions<Model>> ? unknown : never)
-
-export class EvaluationRounding extends Schema.Class<EvaluationRounding>("Evaluation.Rounding")({
-  probabilityDecimals: Schema.optional(Schema.Int),
-  scoreDecimals: Schema.optional(Schema.Int),
-}) {}
-
-export class EvaluationResponse extends Schema.Class<EvaluationResponse>("Evaluation.Response")({
-  model: ModelID,
-  answers: Schema.Record(Schema.String, EvaluationAnswer),
-  usage: Schema.optional(Usage),
-  rounding: Schema.optional(EvaluationRounding),
-  providerMetadata: Schema.optional(ProviderMetadata),
-}) {}
-
-export type EvaluationResponseFor<Questions extends EvaluationQuestions> = Omit<EvaluationResponse, "answers"> & {
-  readonly answers: AnswersFor<Questions>
-}
-
-export function request<const Model extends object, const Questions extends EvaluationQuestions>(
-  input: EvaluationRequestInput<Model, Questions>,
-): EvaluationRequestFor<EvaluationModelOptions<Model>, Questions>
-export function request(input: EvaluationRequest): EvaluationRequest
-export function request(input: EvaluationRequest | EvaluationRequestInput) {
-  if (input instanceof EvaluationRequest) return input
-  return new EvaluationRequest({
-    ...input,
-    model: input.model as unknown as EvaluationModel,
-    http: input.http === undefined ? undefined : HttpOptions.make(input.http),
-  })
-}
-
-export function run<const Model extends object, const Questions extends EvaluationQuestions>(
-  input: EvaluationRequestInput<Model, Questions>,
-): Effect.Effect<EvaluationResponseFor<Questions>, AIError, Service>
-export function run(input: EvaluationRequest): Effect.Effect<EvaluationResponse, AIError, Service>
-export function run(input: EvaluationRequest | EvaluationRequestInput) {
-  return Effect.try({
-    try: () => (input instanceof EvaluationRequest ? input : request(input)),
-    catch: (cause) =>
-      new AIError({
-        reason: new InvalidRequestError({
-          message: cause instanceof Error ? cause.message : String(cause),
-          cause,
-        }),
-      }),
-  }).pipe(
-    Effect.flatMap((request) =>
-      EvaluationClient.evaluate(request as EvaluationRequestFor<EvaluationOptions, EvaluationQuestions>),
-    ),
-  )
-}
-
-export const Evaluation = {
-  request,
-  run,
-} as const
@@ -1,194 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
-import {
-  ChoiceQuestion,
-  EvaluationInput,
-  EvaluationModel,
-  EvaluationResponse,
-  EvaluationRounding,
-  ScoreQuestion,
-  type EvaluationAnswer,
-  type EvaluationOptions,
-} from "./evaluation.js"
-import { Auth, type Definition as AuthDefinition } from "../route/auth.js"
-import {
-  AIError,
-  HttpContext,
-  HttpOptions,
-  InvalidProviderOutputError,
-  InvalidRequestError,
-  ModelID,
-  Usage,
-  mergeJsonRecords,
-} from "../schema/index.js"
-
-const Noul = Schema.Struct({
-  type: Schema.Literal("noul"),
-  instructions: EvaluationInput,
-  criteria: Schema.optional(
-    Schema.Struct({
-      true: Schema.optional(Schema.NullOr(EvaluationInput)),
-      false: Schema.optional(Schema.NullOr(EvaluationInput)),
-    }),
-  ),
-})
-const Question = Schema.Union([
-  ChoiceQuestion.pipe(
-    Schema.refine((x): x is typeof x => Object.keys(x.criteria).length <= 255, {
-      message: "System One Choice questions support at most 255 options",
-    }),
-  ),
-  ScoreQuestion.pipe(
-    Schema.refine((x): x is typeof x => x.criteria.length <= 10, {
-      message: "System One Score questions support at most 10 levels",
-    }),
-  ),
-  Noul,
-])
-const Request = Schema.StructWithRest(
-  Schema.Struct({
-    model: Schema.String,
-    state: EvaluationInput,
-    questions: Schema.Record(Schema.String, Question),
-  }),
-  [Schema.Record(Schema.String, Schema.Any)],
-)
-
-const Probability = Schema.Number.check(Schema.isBetween({ minimum: 0, maximum: 1 }))
-const NoulAnswer = Schema.Struct({ type: Schema.Literal("noul"), noul: Probability })
-const Choice = Schema.Struct({
-  type: Schema.Literal("choice"),
-  choice: Schema.String,
-  probabilities: Schema.Record(Schema.String, Probability),
-  confidence: Schema.optional(Probability),
-})
-const Score = Schema.Struct({
-  type: Schema.Literal("score"),
-  score: Schema.Number,
-  probabilities: Schema.Record(Schema.String, Probability),
-  legend: Schema.optional(Schema.Record(Schema.String, Schema.Json)),
-  confidence: Schema.optional(Probability),
-})
-const Answer = Schema.Union([NoulAnswer, Choice, Score]).pipe(Schema.toTaggedUnion("type"))
-const NativeUsage = Schema.StructWithRest(
-  Schema.Struct({
-    input_tokens: Schema.optional(Schema.Number),
-    output_tokens: Schema.optional(Schema.Number),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Response = Schema.Struct({
-  model: Schema.String,
-  answers: Schema.Record(Schema.String, Answer),
-  usage: Schema.optional(NativeUsage),
-  id: Schema.optional(Schema.String),
-  provider: Schema.optional(Schema.String),
-  provider_metadata: Schema.optional(Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown))),
-})
-
-export interface ModelInput {
-  readonly id: string | ModelID
-  readonly provider: string
-  readonly providerMetadataKey: string
-  readonly auth: AuthDefinition
-  readonly baseURL: string
-  readonly headers?: Record<string, string>
-  readonly http?: HttpOptions
-}
-
-export const model = <Options extends EvaluationOptions = EvaluationOptions>(cfg: ModelInput) =>
-  EvaluationModel.make<Options>({
-    id: cfg.id,
-    provider: cfg.provider,
-    http: cfg.http,
-    route: {
-      id: "system-one",
-      evaluate: (req, send) =>
-        Effect.gen(function* () {
-          const url = new URL(`${cfg.baseURL.replace(/\/$/, "")}/systemone`)
-          Object.entries(req.http?.query ?? {}).forEach(([key, value]) => url.searchParams.set(key, value))
-          const body = yield* Schema.encodeUnknownEffect(Schema.fromJsonString(Request))({
-            ...mergeJsonRecords(req.options, req.http?.body),
-            model: req.model.id,
-            state: req.state,
-            questions: Object.fromEntries(
-              Object.entries(req.questions).map(([id, x]) => [id, x.type === "boolean" ? { ...x, type: "noul" } : x]),
-            ),
-          }).pipe(
-            Effect.mapError(
-              (cause) => new AIError({ reason: new InvalidRequestError({ message: cause.message, cause }) }),
-            ),
-          )
-          const headers = yield* Auth.toEffect(cfg.auth)({
-            request: req,
-            method: "POST",
-            url: url.toString(),
-            body,
-            headers: Headers.fromInput({ ...cfg.headers, ...req.http?.headers }),
-          })
-          const res = yield* send(
-            HttpClientRequest.post(url).pipe(
-              HttpClientRequest.setHeaders(headers),
-              HttpClientRequest.bodyText(body, "application/json"),
-            ),
-          )
-          const http = new HttpContext({ url: res.request.url, status: res.status, headers: res.headers })
-          const fail = (message: string, cause: unknown, body?: string) =>
-            new AIError({ reason: new InvalidProviderOutputError({ route: "system-one", message, body, http, cause }) })
-          const text = yield* res.text.pipe(
-            Effect.mapError((cause) => fail("Failed to read the System One response", cause)),
-          )
-          const data = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(Response))(text).pipe(
-            Effect.mapError((cause) => fail("System One returned an invalid response", cause, text)),
-          )
-
-          const confidence: Record<string, number> = {}
-          const legend: Record<string, Record<string, Schema.Json>> = {}
-          const answers = Object.fromEntries(
-            Object.entries(data.answers).map(([id, answer]): [string, EvaluationAnswer] => {
-              if (answer.type === "noul") return [id, { type: "boolean", probability: answer.noul }]
-              if (answer.type === "choice") {
-                if (answer.confidence !== undefined) confidence[id] = answer.confidence
-                return [
-                  id,
-                  {
-                    type: "choice",
-                    choice: answer.choice,
-                    probabilities: answer.probabilities,
-                  },
-                ]
-              }
-              if (answer.confidence !== undefined) confidence[id] = answer.confidence
-              if (answer.legend !== undefined) legend[id] = answer.legend
-              return [id, { type: "score", score: answer.score, probabilities: answer.probabilities }]
-            }),
-          )
-          const meta = {
-            ...(data.id === undefined ? {} : { responseId: data.id }),
-            ...(data.provider === undefined ? {} : { provider: data.provider }),
-            ...data.provider_metadata?.[cfg.providerMetadataKey],
-            ...(Object.keys(confidence).length === 0 ? {} : { confidence }),
-            ...(Object.keys(legend).length === 0 ? {} : { legend }),
-          }
-          return new EvaluationResponse({
-            model: ModelID.make(data.model),
-            answers,
-            usage: data.usage
-              ? new Usage({
-                  inputTokens: data.usage.input_tokens,
-                  outputTokens: data.usage.output_tokens,
-                  totalTokens:
-                    data.usage.input_tokens === undefined && data.usage.output_tokens === undefined
-                      ? undefined
-                      : (data.usage.input_tokens ?? 0) + (data.usage.output_tokens ?? 0),
-                  providerMetadata: { [cfg.providerMetadataKey]: data.usage },
-                })
-              : undefined,
-            rounding: new EvaluationRounding({ probabilityDecimals: 2, scoreDecimals: 2 }),
-            providerMetadata: Object.keys(meta).length === 0 ? undefined : { [cfg.providerMetadataKey]: meta },
-          })
-        }),
-    },
-  })
-
-export const SystemOne = { model } as const
@@ -1,137 +0,0 @@
-import { Duration, Effect, Schedule, Schema, Stream } from "effect"
-import { AIError, TimeoutError } from "./schema/errors.js"
-
-export const Status = Schema.Literals(["queued", "running", "completed", "failed", "cancelled", "expired"])
-export type Status = Schema.Schema.Type<typeof Status>
-
-/** Provider-neutral view of one generation observation. */
-export interface Snapshot {
-  readonly id: string
-  readonly status: Status
-  /** Normalized 0..1 when the provider reports progress. */
-  readonly progress?: number
-  readonly position?: number
-  readonly expiresAt?: number
-}
-
-/**
- * Route-owned generation operations. `token` is the route's serializable handle (operation name, task id, response URL)
- * so a generation can be resumed from another process; its shape is opaque to `Generation`.
- */
-export interface Route<Response> {
-  readonly status: (token: unknown) => Effect.Effect<Snapshot, AIError>
-  readonly result: (token: unknown) => Effect.Effect<Response, AIError>
-  readonly cancel?: (token: unknown) => Effect.Effect<void, AIError>
-  /** Provider polling hint (e.g. `openai-poll-after-ms`) that overrides the default interval for the next poll. */
-  readonly pollHint?: (snapshot: Snapshot) => Duration.Duration | undefined
-}
-
-export interface Poll {
-  readonly interval?: Duration.Input
-  readonly timeout?: Duration.Input
-  /** Full override of the polling schedule; `interval` and `pollHint` are ignored when supplied. */
-  readonly schedule?: Schedule.Schedule<unknown, Snapshot>
-}
-
-export const DEFAULT_POLL_INTERVAL = Duration.seconds(5)
-export const DEFAULT_POLL_TIMEOUT = Duration.minutes(10)
-
-export type Event =
-  | { readonly type: "generation-queued"; readonly id: string; readonly position?: number }
-  | { readonly type: "generation-progress"; readonly id: string; readonly progress?: number }
-  | { readonly type: "generation-finished"; readonly id: string; readonly status: Status }
-
-const TERMINAL: ReadonlySet<Status> = new Set(["completed", "failed", "cancelled", "expired"])
-
-export class Generation<Response> {
-  readonly id: string
-  readonly status: Status
-  readonly progress?: number
-  readonly position?: number
-  readonly expiresAt?: number
-
-  constructor(
-    readonly route: Route<Response>,
-    readonly token: unknown,
-    snapshot: Snapshot,
-  ) {
-    this.id = snapshot.id
-    this.status = snapshot.status
-    this.progress = snapshot.progress
-    this.position = snapshot.position
-    this.expiresAt = snapshot.expiresAt
-  }
-
-  get snapshot(): Snapshot {
-    return {
-      id: this.id,
-      status: this.status,
-      progress: this.progress,
-      position: this.position,
-      expiresAt: this.expiresAt,
-    }
-  }
-
-  get terminal() {
-    return TERMINAL.has(this.status)
-  }
-
-  refresh(): Effect.Effect<Generation<Response>, AIError> {
-    return this.route.status(this.token).pipe(Effect.map((snapshot) => new Generation(this.route, this.token, snapshot)))
-  }
-
-  /** Poll until the generation reaches a terminal status, then fetch the result. Fails with a `Timeout` reason on deadline. */
-  await(options?: { readonly poll?: Poll }): Effect.Effect<Response, AIError> {
-    const timeout = Duration.fromInputUnsafe(options?.poll?.timeout ?? DEFAULT_POLL_TIMEOUT)
-    const settled = this.terminal ? Effect.succeed(this) : this.poll(options?.poll)
-    return settled.pipe(
-      // Non-completed terminal states also go through `result` so the route can surface its provider failure body.
-      Effect.flatMap((generation) => generation.route.result(generation.token)),
-      Effect.timeoutOrElse({
-        duration: timeout,
-        orElse: () =>
-          new AIError({
-            reason: new TimeoutError({
-              message: `Generation ${this.id} did not finish within ${Duration.format(timeout)}`,
-              timeoutMs: Duration.toMillis(timeout),
-            }),
-          }),
-      }),
-    )
-  }
-
-  cancel(): Effect.Effect<void, AIError> {
-    return this.route.cancel?.(this.token) ?? Effect.void
-  }
-
-  /** Status observations as a stream, ending after the first terminal observation. */
-  events(options?: { readonly poll?: Poll }): Stream.Stream<Event, AIError> {
-    const observations = this.terminal
-      ? Stream.make(this)
-      : Stream.fromEffectSchedule(this.refresh(), this.schedule(options?.poll)).pipe(
-          Stream.takeUntil((generation) => generation.terminal),
-        )
-    return observations.pipe(
-      Stream.map((generation): Event => {
-        if (generation.terminal) return { type: "generation-finished", id: generation.id, status: generation.status }
-        if (generation.status === "queued") return { type: "generation-queued", id: generation.id, position: generation.position }
-        return { type: "generation-progress", id: generation.id, progress: generation.progress }
-      }),
-    )
-  }
-
-  private poll(poll: Poll | undefined) {
-    return this.refresh().pipe(Effect.repeat({ schedule: this.schedule(poll), until: (generation) => generation.terminal }))
-  }
-
-  private schedule(poll: Poll | undefined): Schedule.Schedule<unknown, Generation<Response>> {
-    if (poll?.schedule) return poll.schedule.pipe(Schedule.setInputType<Generation<Response>>())
-    const interval = poll?.interval ?? DEFAULT_POLL_INTERVAL
-    const pollHint = this.route.pollHint
-    const spaced = Schedule.spaced(interval).pipe(Schedule.setInputType<Generation<Response>>())
-    if (!pollHint) return spaced
-    return spaced.pipe(
-      Schedule.modifyDelay((metadata) => Effect.succeed(pollHint(metadata.input.snapshot) ?? interval)),
-    )
-  }
-}
@@ -1,21 +1,15 @@
-import { Context, Effect, Layer, Stream } from "effect"
+import { Context, Effect, Layer } from "effect"
 import { RequestExecutor } from "./route/executor.js"
-import type { AIError } from "./schema/index.js"
-import {
-  responseEvents,
-  type ImageEvent,
-  type ImageOptions,
-  type ImageRequestFor,
-  type ImageResponse,
-} from "./image.js"
+import { mergeHttpOptions, type AIError } from "./schema/index.js"
+import { sanitizeSurrogates } from "./utils/sanitize.js"
+import type { ImageOptions, ImageRequest, ImageRequestFor, ImageResponse } from "./image.js"
+
+export type Execute = RequestExecutor.Interface["execute"]

 export interface Interface {
  readonly generate: <Options extends ImageOptions>(
    request: ImageRequestFor<Options>,
  ) => Effect.Effect<ImageResponse, AIError>
-  readonly stream: <Options extends ImageOptions>(
-    request: ImageRequestFor<Options>,
-  ) => Stream.Stream<ImageEvent, AIError>
 }

 export class Service extends Context.Service<Service, Interface>()("@opencode/ImageClient") {}
@@ -28,27 +22,23 @@ export const generate = <Options extends ImageOptions>(
    return yield* client.generate(request)
  })

-export const stream = <Options extends ImageOptions>(
-  request: ImageRequestFor<Options>,
-): Stream.Stream<ImageEvent, AIError, Service> =>
-  Stream.unwrap(
-    Effect.gen(function* () {
-      const client = yield* Service
-      return client.stream(request)
-    }),
-  )
-
 export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
  Service,
  Effect.gen(function* () {
    const executor = yield* RequestExecutor.Service
-    const generate = <Options extends ImageOptions>(request: ImageRequestFor<Options>) =>
-      request.model.route.generate(request, executor.execute)
    return Service.of({
-      generate,
-      // Inline routes have no partial frames yet; the stream is the completed response expanded into events.
-      stream: (request) =>
-        Stream.unwrap(generate(request).pipe(Effect.map((response) => Stream.fromIterable(responseEvents(response))))),
+      generate: (request) =>
+        request.model.route.generate(
+          {
+            ...sanitizeSurrogates({
+              ...request,
+              model: undefined,
+              http: mergeHttpOptions(request.model.http, request.http),
+            }),
+            model: request.model,
+          },
+          executor.execute,
+        ),
    })
  }),
 )
@@ -57,5 +47,4 @@ export const ImageClient = {
  Service,
  layer,
  generate,
-  stream,
 } as const
@@ -1,30 +1,22 @@
-import { Effect, Schema, Stream } from "effect"
-import { Media } from "./media.js"
-import { Endpoint } from "./route/endpoint.js"
-import { MediaRoute } from "./route/media.js"
-import type { MediaProtocol } from "./route/media-protocol.js"
+import { Effect, Schema } from "effect"
 import {
-  AIError,
  HttpOptions,
  InvalidRequestError,
-  MediaUsage,
+  AIError,
  ModelID,
  ProviderID,
  ProviderMetadata,
+  Usage,
 } from "./schema/index.js"
-import { ImageClient, Service } from "./image-client.js"
+import { ImageClient, Service, type Execute as ImageExecute } from "./image-client.js"

-// ---------------------------------------------------------------------------
-// Model
-// ---------------------------------------------------------------------------
+export interface ImageRoute<Options extends ImageOptions = ImageOptions> {
+  readonly id: string
+  readonly generate: (request: ImageRequestFor<Options>, execute: ImageExecute) => Effect.Effect<ImageResponse, AIError>
+}

 export type ImageOptions = Record<string, unknown>

-export type ImageRoute<Options extends ImageOptions = ImageOptions> = MediaRoute.Route<
-  ImageRequestFor<Options>,
-  ImageResponse
->
-
 export class ImageModel<Options extends ImageOptions = ImageOptions> {
  declare protected readonly _Options: (options: Options) => Options
  readonly id: ModelID
@@ -47,26 +39,6 @@ export class ImageModel<Options extends ImageOptions = ImageOptions> {
      http: input.http,
    })
  }
-
-  /** Compose an inline image protocol with its canonical path into a model for one deployment. */
-  static fromRoute<Options extends ImageOptions = ImageOptions>(
-    route: ImageModel.RouteInput<Options>,
-    input: MediaRoute.ModelInput,
-  ) {
-    return ImageModel.make<Options>({
-      id: input.id,
-      provider: route.provider,
-      http: input.http,
-      route: MediaRoute.make({
-        id: route.id,
-        provider: route.provider,
-        protocol: route.protocol,
-        endpoint: Endpoint.path(route.path, { baseURL: input.baseURL ?? route.baseURL }),
-        auth: input.auth,
-        headers: input.headers,
-      }),
-    })
-  }
 }

 export namespace ImageModel {
@@ -82,85 +54,81 @@ export namespace ImageModel {
    readonly id: string | ModelID
    readonly provider: string | ProviderID
  }
-
-  export interface RouteInput<Options extends ImageOptions = ImageOptions> {
-    readonly id: string
-    readonly provider: string | ProviderID
-    readonly protocol: MediaProtocol.Inline<ImageRequestFor<Options>, ImageResponse>
-    readonly path: Endpoint.EndpointPart<MediaProtocol.Body, ImageRequestFor<Options>>
-    /** Canonical base URL; `ModelInput.baseURL` overrides it per deployment. */
-    readonly baseURL?: string
-  }
 }

 export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
  expected: "Image.Model",
 })

-// ---------------------------------------------------------------------------
-// Request
-// ---------------------------------------------------------------------------
+const ImageBytesInput = Schema.Struct({
+  type: Schema.Literal("bytes"),
+  data: Schema.Uint8Array,
+  mediaType: Schema.String,
+})
+const ImageUrlInput = Schema.Struct({
+  type: Schema.Literal("url"),
+  url: Schema.String,
+})
+const ImageFileIDInput = Schema.Struct({
+  type: Schema.Literal("file-id"),
+  id: Schema.String,
+})
+const ImageFileURIInput = Schema.Struct({
+  type: Schema.Literal("file-uri"),
+  uri: Schema.String,
+  mediaType: Schema.String,
+})

-export type ImageSize = `${number}x${number}`
-export const ImageSize = Schema.declare<ImageSize>(
-  (value): value is ImageSize => typeof value === "string" && /^\d+x\d+$/.test(value),
-  { title: "ImageSize" },
-)
+export const ImageInputSchema = Schema.Union([
+  ImageBytesInput,
+  ImageUrlInput,
+  ImageFileIDInput,
+  ImageFileURIInput,
+]).pipe(Schema.toTaggedUnion("type"))
+export type ImageInput = Schema.Schema.Type<typeof ImageInputSchema>

-export type ImageAspectRatio = `${number}:${number}`
-export const ImageAspectRatio = Schema.declare<ImageAspectRatio>(
-  (value): value is ImageAspectRatio => typeof value === "string" && /^\d+(?:\.\d+)?:\d+(?:\.\d+)?$/.test(value),
-  { title: "ImageAspectRatio" },
-)
-
-export type ImageFormat = "png" | "jpeg" | "webp" | (string & {})
+export const ImageInput = {
+  bytes: (data: Uint8Array, mediaType: string): ImageInput => ({ type: "bytes", data, mediaType }),
+  url: (url: string): ImageInput => ({ type: "url", url }),
+  file: (id: string): ImageInput => ({ type: "file-id", id }),
+  fileUri: (uri: string, mediaType: string): ImageInput => ({ type: "file-uri", uri, mediaType }),
+} as const

 export class ImageRequest extends Schema.Class<ImageRequest>("Image.Request")({
  model: ImageModelSchema,
  prompt: Schema.String,
-  /** Edit sources or style/subject references, in order. */
-  images: Schema.optional(Schema.Array(Media.AssetSchema)),
-  /** Inpainting mask; routes that cannot honor it fail with `UnsupportedOperation`. */
-  mask: Schema.optional(Media.AssetSchema),
-  n: Schema.optional(Schema.Int),
-  size: Schema.optional(ImageSize),
-  aspectRatio: Schema.optional(ImageAspectRatio),
-  seed: Schema.optional(Schema.Number),
-  format: Schema.optional(Schema.String),
-  providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+  images: Schema.optional(Schema.Array(ImageInputSchema)),
+  options: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
  http: Schema.optional(HttpOptions),
 }) {
  declare protected readonly _ImageRequest: void
 }

-export type ImageRequestFor<Options extends ImageOptions = ImageOptions> = Omit<
-  ImageRequest,
-  "model" | "providerOptions"
-> & {
+export type ImageRequestFor<Options extends ImageOptions = ImageOptions> = Omit<ImageRequest, "model" | "options"> & {
  readonly model: ImageModel<Options>
-  readonly providerOptions?: Options
+  readonly options?: Options
 }

 export type ImageModelOptions<Model> = Model extends ImageModel<infer Options> ? Options : never

-export type ImageRequestInput<Model extends ImageModel = ImageModel> = Omit<
+export type ImageRequestInput<Model extends object = ImageModel> = Omit<
  ConstructorParameters<typeof ImageRequest>[0],
-  "model" | "providerOptions" | "http"
+  "model" | "options" | "http"
 > & {
  readonly model: Model
-  readonly format?: ImageFormat
-  readonly providerOptions?: NoInfer<ImageModelOptions<Model>>
+  readonly options?: NoInfer<ImageModelOptions<Model>>
  readonly http?: HttpOptions.Input
-}
+} & (Model extends ImageModel<ImageModelOptions<Model>> ? unknown : never)

-// ---------------------------------------------------------------------------
-// Response and events
-// ---------------------------------------------------------------------------
+export class GeneratedImage extends Schema.Class<GeneratedImage>("Image.Generated")({
+  mediaType: Schema.String,
+  data: Schema.Union([Schema.String, Schema.Uint8Array]),
+  providerMetadata: Schema.optional(ProviderMetadata),
+}) {}

 export class ImageResponse extends Schema.Class<ImageResponse>("Image.Response")({
-  images: Schema.Array(Media.AssetSchema),
-  usage: Schema.optional(MediaUsage),
-  notices: Schema.optional(Schema.Array(Media.Notice)),
+  images: Schema.Array(GeneratedImage),
+  usage: Schema.optional(Usage),
  providerMetadata: Schema.optional(ProviderMetadata),
 }) {
  get image() {
@@ -168,43 +136,7 @@ export class ImageResponse extends Schema.Class<ImageResponse>("Image.Response")
  }
 }

-export const ImageOutputEvent = Schema.Struct({
-  type: Schema.tag("image"),
-  index: Schema.Number,
-  image: Media.AssetSchema,
-}).annotate({ identifier: "Image.Event.Image" })
-
-export const ImageFinishEvent = Schema.Struct({
-  type: Schema.tag("finish"),
-  usage: Schema.optional(MediaUsage),
-  notices: Schema.optional(Schema.Array(Media.Notice)),
-  providerMetadata: Schema.optional(ProviderMetadata),
-}).annotate({ identifier: "Image.Event.Finish" })
-
-const imageEventTagged = Schema.Union([ImageOutputEvent, ImageFinishEvent]).pipe(Schema.toTaggedUnion("type"))
-export const ImageEvent = Object.assign(imageEventTagged, {
-  is: {
-    image: imageEventTagged.guards.image,
-    finish: imageEventTagged.guards.finish,
-  },
-})
-export type ImageEvent = Schema.Schema.Type<typeof imageEventTagged>
-
-/** Inline routes produce every image at once; expand the response into the streaming event shape. */
-export const responseEvents = (response: ImageResponse): ReadonlyArray<ImageEvent> => [
-  ...response.images.map((image, index) => ImageOutputEvent.make({ index, image })),
-  ImageFinishEvent.make({
-    usage: response.usage,
-    notices: response.notices,
-    providerMetadata: response.providerMetadata,
-  }),
-]
-
-// ---------------------------------------------------------------------------
-// Request-shaped call API
-// ---------------------------------------------------------------------------
-
-export function request<const Model extends ImageModel>(
+export function request<const Model extends object>(
  input: ImageRequestInput<Model>,
 ): ImageRequestFor<ImageModelOptions<Model>>
 export function request(input: ImageRequest): ImageRequest
@@ -212,13 +144,18 @@ export function request(input: ImageRequest | ImageRequestInput) {
  if (input instanceof ImageRequest) return input
  return new ImageRequest({
    ...input,
+    model: input.model as unknown as ImageModel,
    http: input.http === undefined ? undefined : HttpOptions.make(input.http),
  })
 }

-const requestEffect = (input: ImageRequest | ImageRequestInput) =>
-  Effect.try({
-    try: () => request(input),
+export function generate<const Model extends object>(
+  input: ImageRequestInput<Model>,
+): Effect.Effect<ImageResponse, AIError, Service>
+export function generate(input: ImageRequest): Effect.Effect<ImageResponse, AIError, Service>
+export function generate(input: ImageRequest | ImageRequestInput) {
+  return Effect.try({
+    try: () => (input instanceof ImageRequest ? input : request(input)),
    catch: (error) =>
      new AIError({
        reason: new InvalidRequestError({
@@ -226,26 +163,10 @@ const requestEffect = (input: ImageRequest | ImageRequestInput) =>
          cause: error,
        }),
      }),
-  })
-
-export function generate<const Model extends ImageModel>(
-  input: ImageRequestInput<Model>,
-): Effect.Effect<ImageResponse, AIError, Service>
-export function generate(input: ImageRequest): Effect.Effect<ImageResponse, AIError, Service>
-export function generate(input: ImageRequest | ImageRequestInput) {
-  return requestEffect(input).pipe(Effect.flatMap((request) => ImageClient.generate(request)))
-}
-
-export function stream<const Model extends ImageModel>(
-  input: ImageRequestInput<Model>,
-): Stream.Stream<ImageEvent, AIError, Service>
-export function stream(input: ImageRequest): Stream.Stream<ImageEvent, AIError, Service>
-export function stream(input: ImageRequest | ImageRequestInput) {
-  return Stream.unwrap(requestEffect(input).pipe(Effect.map((request) => ImageClient.stream(request))))
+  }).pipe(Effect.flatMap((request) => ImageClient.generate(request as unknown as ImageRequestFor<ImageOptions>)))
 }

 export const Image = {
  request,
  generate,
-  stream,
 } as const
@@ -11,27 +11,9 @@ export type {
  Service as LLMClientService,
 } from "./route/client.js"
 export * from "./schema/index.js"
-export {
-  ImageAspectRatio,
-  ImageEvent,
-  ImageModel,
-  ImageModelSchema,
-  ImageRequest,
-  ImageResponse,
-  ImageSize,
-} from "./image.js"
-export type {
-  ImageFormat,
-  ImageModelOptions,
-  ImageOptions,
-  ImageRequestFor,
-  ImageRequestInput,
-  ImageRoute,
-} from "./image.js"
+export { GeneratedImage, ImageInput, ImageInputSchema, ImageModel, ImageRequest, ImageResponse } from "./image.js"
+export type { ImageModelOptions, ImageOptions, ImageRequestFor, ImageRequestInput, ImageRoute } from "./image.js"
 export { Image } from "./image.js"
-export { Media } from "./media.js"
-export { Generation } from "./generation.js"
-export type { Event as GenerationEvent, Poll, Route as GenerationRoute, Snapshot as GenerationSnapshot, Status as GenerationStatus } from "./generation.js"
 export { Tool, ToolFailure, toDefinitions } from "./tool.js"
 export { ToolRuntime } from "./tool-runtime.js"
 export type { DispatchResult as ToolDispatchResult, ToolSettlement } from "./tool-runtime.js"
@@ -1,307 +0,0 @@
-export * as Media from "./media.js"
-
-import { Effect, Encoding, FileSystem, Schema, SchemaGetter } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { ProviderID } from "./schema/ids.js"
-import { AIError, HttpContext, InvalidProviderOutputError, InvalidRequestError } from "./schema/errors.js"
-import { ProviderMetadata } from "./schema/options.js"
-import { Service } from "./route/executor-service.js"
-import { detectMediaType, extensionMediaType } from "./utils/media-type.js"
-
-export { detectMediaType } from "./utils/media-type.js"
-
-const OCTET_STREAM = "application/octet-stream"
-
-// ---------------------------------------------------------------------------
-// Source — the serializable wire/persistence form of a media asset
-// ---------------------------------------------------------------------------
-
-const BytesSource = Schema.Struct({
-  type: Schema.Literal("bytes"),
-  data: Schema.Uint8Array,
-  mediaType: Schema.String,
-})
-
-const Base64Source = Schema.Struct({
-  type: Schema.Literal("base64"),
-  data: Schema.String,
-  mediaType: Schema.String,
-})
-
-const UrlSource = Schema.Struct({
-  type: Schema.Literal("url"),
-  url: Schema.String,
-  mediaType: Schema.optional(Schema.String),
-  /** Epoch milliseconds after which the provider no longer serves the URL. */
-  expiresAt: Schema.optional(Schema.Number),
-  /** Headers required to fetch the URL, such as provider auth for Veo downloads. */
-  headers: Schema.optional(Schema.Record(Schema.String, Schema.String)),
-})
-
-/** A provider-side handle: OpenAI `file_id`, Gemini file URI, `gs://`, `runway://`, or a prior generation id. */
-const RefSource = Schema.Struct({
-  type: Schema.Literal("ref"),
-  provider: ProviderID,
-  id: Schema.String,
-  mediaType: Schema.optional(Schema.String),
-})
-
-export const Source = Schema.Union([BytesSource, Base64Source, UrlSource, RefSource])
-  .pipe(Schema.toTaggedUnion("type"))
-  .annotate({ identifier: "Media.Source" })
-export type Source = Schema.Schema.Type<typeof Source>
-
-// ---------------------------------------------------------------------------
-// Kind, Info, Notice
-// ---------------------------------------------------------------------------
-
-export const Kind = Schema.Literals(["image", "video", "audio", "document", "other"])
-export type Kind = Schema.Schema.Type<typeof Kind>
-
-export const kindOf = (mediaType: string): Kind => {
-  const lower = mediaType.toLowerCase()
-  if (lower.startsWith("image/")) return "image"
-  if (lower.startsWith("video/")) return "video"
-  if (lower.startsWith("audio/")) return "audio"
-  if (lower === "application/pdf" || lower.startsWith("text/")) return "document"
-  return "other"
-}
-
-/** Container-independent facts about the payload; raw PCM audio relies on these because it has no header. */
-export const Info = Schema.Struct({
-  width: Schema.optional(Schema.Number),
-  height: Schema.optional(Schema.Number),
-  durationSeconds: Schema.optional(Schema.Number),
-  sampleRate: Schema.optional(Schema.Number),
-  channels: Schema.optional(Schema.Number),
-  encoding: Schema.optional(Schema.String),
-  format: Schema.optional(Schema.String),
-}).annotate({ identifier: "Media.Info" })
-export type Info = Schema.Schema.Type<typeof Info>
-
-/** A provider-side partial result such as stripped audio or a moderated sample; never a silent drop. */
-export const Notice = Schema.Struct({
-  type: Schema.Literals(["moderated", "filtered", "other"]),
-  message: Schema.String,
-  providerMetadata: Schema.optional(ProviderMetadata),
-}).annotate({ identifier: "Media.Notice" })
-export type Notice = Schema.Schema.Type<typeof Notice>
-
-// ---------------------------------------------------------------------------
-// Asset
-// ---------------------------------------------------------------------------
-
-const invalid = (message: string, cause?: unknown) =>
-  new AIError({ reason: new InvalidRequestError({ message, cause }) })
-
-/** Synchronous view of an inline payload; `undefined` for `url` and `ref` sources, which carry no local bytes. */
-export interface Inline {
-  readonly mime: string
-  readonly base64: string
-  readonly dataUrl: string
-}
-
-export class Asset {
-  readonly source: Source
-  /** Derived from the source: declared type, sniffed magic bytes, then `application/octet-stream`. */
-  readonly mediaType: string
-  readonly kind: Kind
-  readonly info?: Info
-  /** Epoch milliseconds after which a `url` source stops resolving. */
-  readonly expiresAt?: number
-  readonly providerMetadata?: ProviderMetadata
-
-  // Derived payload forms are cached on the instance because every protocol lowering re-reads the same payload. The
-  // cache is check-then-set (concurrent first reads of a `url` source may both download) and is never observable
-  // through `source`, so round-tripping through `Media.from(asset.source)` stays lossless.
-  #bytes: Uint8Array | undefined
-  #base64: string | undefined
-
-  constructor(input: Asset.Input) {
-    this.source = input.source
-    this.mediaType =
-      input.source.mediaType ??
-      (input.source.type === "bytes" ? detectMediaType(input.source.data) : undefined) ??
-      OCTET_STREAM
-    this.kind = kindOf(this.mediaType)
-    this.info = input.info
-    this.expiresAt = input.source.type === "url" ? input.source.expiresAt : undefined
-    this.providerMetadata = input.providerMetadata
-  }
-
-  /** Inline payload without effects, for protocols that embed base64 or data URLs directly. */
-  inline(): Inline | undefined {
-    const source = this.source
-    if (source.type !== "bytes" && source.type !== "base64") return undefined
-    const base64 = source.type === "base64" ? source.data : (this.#base64 ??= Encoding.encodeBase64(source.data))
-    const mime = this.mediaType.toLowerCase()
-    return { mime, base64, dataUrl: `data:${mime};base64,${base64}` }
-  }
-
-  /** Decoded payload; downloads `url` sources through the request executor and caches the result. */
-  bytes(): Effect.Effect<Uint8Array, AIError, Service> {
-    return Effect.suspend(() => {
-      const source = this.source
-      if (source.type === "bytes") return Effect.succeed(source.data)
-      if (this.#bytes !== undefined) return Effect.succeed(this.#bytes)
-      if (source.type === "ref")
-        return Effect.fail(invalid(`Cannot materialize provider ref ${source.provider}:${source.id}`))
-      const decoded =
-        source.type === "base64"
-          ? Effect.fromResult(Encoding.decodeBase64(source.data)).pipe(
-              Effect.mapError((cause) => invalid(`Media asset contains invalid base64 data`, cause)),
-            )
-          : download(source)
-      return decoded.pipe(Effect.tap((data) => Effect.sync(() => (this.#bytes = data))))
-    })
-  }
-
-  base64(): Effect.Effect<string, AIError, Service> {
-    return Effect.suspend(() => {
-      const source = this.source
-      if (source.type === "base64") return Effect.succeed(source.data)
-      if (this.#base64 !== undefined) return Effect.succeed(this.#base64)
-      return this.bytes().pipe(Effect.map((data) => (this.#base64 = Encoding.encodeBase64(data))))
-    })
-  }
-
-  dataUrl(): Effect.Effect<string, AIError, Service> {
-    return this.base64().pipe(Effect.map((data) => `data:${this.mediaType};base64,${data}`))
-  }
-
-  /**
-   * The `AssetEncoded` JSON form with `bytes` sources as base64, matching `Schema.toCodecJson(AssetSchema)`, so a
-   * plain `JSON.stringify` of messages or events stays lossless and decodes back through the JSON codec.
-   */
-  toJSON() {
-    const source = this.source
-    return {
-      source: source.type === "bytes" ? { ...source, data: Encoding.encodeBase64(source.data) } : source,
-      info: this.info,
-      providerMetadata: this.providerMetadata,
-    }
-  }
-
-  /** Pull `url` sources into owned bytes before the URL expires. Inline sources return themselves. */
-  materialize(): Effect.Effect<Asset, AIError, Service> {
-    if (this.source.type === "bytes" || this.source.type === "base64") return Effect.succeed(this)
-    return this.bytes().pipe(
-      Effect.map((data) =>
-        bytes(data, this.source.mediaType, { info: this.info, providerMetadata: this.providerMetadata }),
-      ),
-    )
-  }
-}
-
-export namespace Asset {
-  export interface Input {
-    readonly source: Source
-    readonly info?: Info
-    readonly providerMetadata?: ProviderMetadata
-  }
-}
-
-/** JSON form of an asset: the serializable `Source` plus caller-supplied metadata. `bytes` sources encode as base64. */
-export const AssetEncoded = Schema.Struct({
-  source: Source,
-  info: Schema.optional(Info),
-  providerMetadata: Schema.optional(ProviderMetadata),
-}).annotate({ identifier: "Media.AssetEncoded" })
-
-const encodeAsset = (asset: Asset): typeof AssetEncoded.Type => ({
-  source: asset.source,
-  info: asset.info,
-  providerMetadata: asset.providerMetadata,
-})
-
-const AssetInstance = Schema.declare((value): value is Asset => value instanceof Asset, {
-  expected: "Media.Asset",
-})
-
-/** `Asset` in the type domain and `AssetEncoded` on the wire, so messages and events holding assets serialize. */
-export const AssetSchema = AssetEncoded.pipe(
-  Schema.decodeTo(AssetInstance, {
-    decode: SchemaGetter.transform((encoded) => new Asset(encoded)),
-    encode: SchemaGetter.transform(encodeAsset),
-  }),
-)
-
-const download = Effect.fn("Media.download")(function* (source: Extract<Source, { readonly type: "url" }>) {
-  const executor = yield* Service
-  const response = yield* executor.execute(
-    HttpClientRequest.get(source.url).pipe(HttpClientRequest.setHeaders(source.headers ?? {})),
-  )
-  const buffer = yield* response.arrayBuffer.pipe(
-    Effect.mapError(
-      (cause) =>
-        new AIError({
-          reason: new InvalidProviderOutputError({
-            message: `Failed to read media from ${source.url}`,
-            http: new HttpContext({ url: response.request.url, status: response.status, headers: response.headers }),
-            cause,
-          }),
-        }),
-    ),
-  )
-  return new Uint8Array(buffer)
-})
-
-// ---------------------------------------------------------------------------
-// Constructors
-// ---------------------------------------------------------------------------
-
-export type AssetOptions = Omit<Asset.Input, "source">
-
-export const from = (source: Source, options?: AssetOptions) => new Asset({ ...options, source })
-
-export const bytes = (data: Uint8Array, mediaType?: string, options?: AssetOptions) =>
-  from({ type: "bytes", data, mediaType: mediaType ?? detectMediaType(data) ?? OCTET_STREAM }, options)
-
-export const base64 = (data: string, mediaType: string, options?: AssetOptions) =>
-  from({ type: "base64", data, mediaType }, options)
-
-export const url = (
-  value: string,
-  options?: AssetOptions & Omit<Extract<Source, { readonly type: "url" }>, "type" | "url">,
-) => {
-  const { mediaType, expiresAt, headers, ...rest } = options ?? {}
-  return from({ type: "url", url: value, mediaType, expiresAt, headers }, rest)
-}
-
-export const ref = (provider: string | ProviderID, id: string, mediaType?: string, options?: AssetOptions) =>
-  from({ type: "ref", provider: ProviderID.make(provider), id, mediaType }, options)
-
-const DATA_URL = /^data:([^;,]+)(?:;[^,]*)*;base64,(.*)$/s
-
-/** Parse a `data:<mime>;base64,<data>` URL, or `undefined` when the value is not a base64 data URL. */
-export const parseDataUrl = (value: string, options?: AssetOptions) => {
-  const match = DATA_URL.exec(value)
-  return match === null ? undefined : base64(match[2], match[1], options)
-}
-
-/** Parse a `data:<mime>;base64,<data>` URL. Malformed input throws a typed `AIError` because constructors are sync. */
-export const fromDataUrl = (dataUrl: string, options?: AssetOptions) => {
-  const asset = parseDataUrl(dataUrl, options)
-  if (asset === undefined) throw invalid("Media data URLs must contain a MIME type and base64 data")
-  return asset
-}
-
-/** Read a file through `FileSystem` and sniff its media type from magic bytes, then the extension. */
-export const file = (path: string, options?: AssetOptions): Effect.Effect<Asset, AIError, FileSystem.FileSystem> =>
-  Effect.gen(function* () {
-    const fs = yield* FileSystem.FileSystem
-    const data = yield* fs
-      .readFile(path)
-      .pipe(Effect.mapError((cause) => invalid(`Failed to read media file ${path}`, cause)))
-    return bytes(data, detectMediaType(data) ?? extensionMediaType(path), options)
-  })
-
-/** Materialize an asset and write its bytes through `FileSystem`. */
-export const write = (asset: Asset, path: string): Effect.Effect<void, AIError, FileSystem.FileSystem | Service> =>
-  Effect.gen(function* () {
-    const fs = yield* FileSystem.FileSystem
-    const data = yield* asset.bytes()
-    yield* fs
-      .writeFile(path, data)
-      .pipe(Effect.mapError((cause) => invalid(`Failed to write media file ${path}`, cause)))
-  })
@@ -1,100 +0,0 @@
-import { Effect, Layer, ManagedRuntime, Stream } from "effect"
-import { Image, ImageModel, ImageRequest, type ImageRequestInput } from "./image.js"
-import { ImageClient } from "./image-client.js"
-import { LLM } from "./index.js"
-import { LLMClient } from "./route/client.js"
-import { RequestExecutor } from "./route/executor.js"
-import { LanguageModel, LLMRequest } from "./schema/index.js"
-import type { RequestInput } from "./llm.js"
-
-/**
- * Promise-first entrypoint for scripts and non-Effect callers. One `ManagedRuntime` hosts the LLM and image clients
- * over a request executor; every method runs the corresponding Effect API and rethrows `AIError` unchanged.
- */
-export interface Options {
-  /** Executor layer; defaults to `RequestExecutor.fetchLayer`. Inject a recorder or middleware here. */
-  readonly layer?: Layer.Layer<RequestExecutor.Service>
-}
-
-export interface RunOptions {
-  readonly signal?: AbortSignal
-}
-
-export type Services =
-  | Layer.Success<typeof LLMClient.layer>
-  | Layer.Success<typeof ImageClient.layer>
-  | RequestExecutor.Service
-
-const abortEffect = (signal: AbortSignal | undefined) =>
-  signal === undefined
-    ? Effect.never
-    : Effect.callback<void>((resume) => {
-        if (signal.aborted) {
-          resume(Effect.void)
-          return
-        }
-        const onAbort = () => resume(Effect.void)
-        signal.addEventListener("abort", onAbort, { once: true })
-        return Effect.sync(() => signal.removeEventListener("abort", onAbort))
-      })
-
-export const make = (options: Options = {}) => {
-  const runtime = ManagedRuntime.make(
-    Layer.mergeAll(LLMClient.layer, ImageClient.layer).pipe(
-      Layer.provideMerge(options.layer ?? RequestExecutor.fetchLayer),
-    ),
-  )
-
-  /** Run any package Effect (for example `asset.bytes()`) inside this runtime. */
-  const run = <A, E>(effect: Effect.Effect<A, E, Services>, options?: RunOptions) =>
-    runtime.runPromise(effect, { signal: options?.signal })
-
-  const iterate = <A, E>(stream: Stream.Stream<A, E, Services>, options?: RunOptions): AsyncIterable<A> =>
-    Stream.toAsyncIterable(
-      Stream.unwrap(
-        runtime.contextEffect.pipe(
-          Effect.map(
-            (context): Stream.Stream<A, E> =>
-              stream.pipe(Stream.interruptWhen(abortEffect(options?.signal)), Stream.provideContext(context)),
-          ),
-        ),
-      ),
-    )
-
-  // The typed `generate`/`stream` overloads take a concrete input or a request, not the union; normalize once here.
-  const llmRequest = (input: RequestInput | LLMRequest) => (input instanceof LLMRequest ? input : LLM.request(input))
-  const imageRequest = (input: ImageRequestInput | ImageRequest) =>
-    input instanceof ImageRequest ? input : Image.request(input)
-
-  return {
-    run,
-    llm: {
-      request: LLM.request,
-      generate: <const Model extends LanguageModel>(
-        input: RequestInput<Model> | LLMRequest,
-        options?: RunOptions,
-      ) => run(LLM.generate(llmRequest(input)), options),
-      stream: <const Model extends LanguageModel>(input: RequestInput<Model> | LLMRequest, options?: RunOptions) =>
-        iterate(LLM.stream(llmRequest(input)), options),
-    },
-    image: {
-      request: Image.request,
-      generate: <const Model extends ImageModel>(
-        input: ImageRequestInput<Model> | ImageRequest,
-        options?: RunOptions,
-      ) => run(Image.generate(imageRequest(input)), options),
-      stream: <const Model extends ImageModel>(
-        input: ImageRequestInput<Model> | ImageRequest,
-        options?: RunOptions,
-      ) => iterate(Image.stream(imageRequest(input)), options),
-    },
-    dispose: () => runtime.dispose(),
-  }
-}
-
-export type Client = ReturnType<typeof make>
-
-/** Default client over `RequestExecutor.fetchLayer` for scripts; the runtime builds its layer on first use. */
-export const ai = make()
-
-export * as AI from "./promise.js"
@@ -658,7 +658,7 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
  part: MediaPart,
  breakpoints?: Cache.Breakpoints,
 ) {
-  const mime = part.media.mediaType.toLowerCase()
+  const mime = part.mediaType.toLowerCase()
  const cacheControlValue = breakpoints ? cacheControl(breakpoints, part.cache) : undefined
  const fileId = fileIdFromMetadata(part.metadata)

@@ -687,9 +687,9 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
    } satisfies AnthropicDocumentBlock
  }

-  const rawString = ProviderShared.mediaUrl(part.media)?.trim()
+  const rawString = typeof part.data === "string" ? part.data.trim() : undefined
  // SDK URL sources: URLImageSource:3817 / URLPDFSource:3823 {type:"url", url}
-  if (rawString && isHttpUrl(rawString)) {
+  if (rawString && isHttpUrl(rawString) && !rawString.startsWith("data:")) {
    if (mime.startsWith("image/"))
      return {
        type: "image" as const,
@@ -714,11 +714,20 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
      } satisfies AnthropicDocumentBlock
  }

-  const media = yield* ProviderShared.requireInlineMedia("Anthropic Messages", part.media)
-
  // SDK PlainTextSource:2716 {type:"text", media_type:"text/plain", data}
  if (mime === "text/plain") {
-    const textData = Buffer.from(media.base64, "base64").toString("utf8")
+    const textData =
+      typeof part.data !== "string"
+        ? Buffer.from(part.data).toString("utf8")
+        : part.data.startsWith("data:")
+          ? (() => {
+              const comma = part.data.indexOf(",")
+              const payload = comma >= 0 ? part.data.slice(comma + 1) : part.data
+              return part.data.includes(";base64")
+                ? Buffer.from(payload, "base64").toString("utf8")
+                : decodeURIComponent(payload)
+            })()
+          : part.data
    return {
      type: "document" as const,
      source: { type: "text" as const, media_type: "text/plain" as const, data: textData },
@@ -733,6 +742,7 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
    } satisfies AnthropicDocumentBlock
  }

+  const media = ProviderShared.normalizeMedia(part)
  if (media.mime === "application/pdf")
    return {
      type: "document" as const,
@@ -751,7 +761,7 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
        : { citations: citationsFromMetadata(part.metadata)! }),
    } satisfies AnthropicDocumentBlock
  if (!media.mime.startsWith("image/"))
-    return yield* invalid(`Anthropic Messages does not support media type ${part.media.mediaType}`)
+    return yield* invalid(`Anthropic Messages does not support media type ${part.mediaType}`)
  return {
    type: "image" as const,
    source: {
@@ -770,7 +780,7 @@ const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
 // content instead of JSON-stringifying base64 into a prompt string.
 const lowerToolResultContentItem = Effect.fnUntraced(function* (item: Tool.Content) {
  if (item.type === "text") return { type: "text" as const, text: item.text } satisfies AnthropicTextBlock
-  return yield* lowerMedia(ProviderShared.toolFileMedia(item))
+  return yield* lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name })
 })

 const lowerToolResultContent = Effect.fnUntraced(function* (part: ToolResultPart) {
@@ -303,7 +303,15 @@ const lowerToolResultContent = Effect.fn("BedrockConverse.lowerToolResultContent
      content.push({ text: item.text })
      continue
    }
-    const media = yield* BedrockMedia.lower(ProviderShared.toolFileMedia(item), documentNames)
+    const media = yield* BedrockMedia.lower(
+      {
+        type: "media",
+        mediaType: item.mime,
+        data: item.uri,
+        filename: item.name,
+      },
+      documentNames,
+    )
    content.push(...media)
  }
  return content
@@ -20,7 +20,6 @@ import {
  type ToolDefinition,
 } from "../schema/index.js"
 import { classifyProviderFailure } from "../provider-error.js"
-import { Media } from "../media.js"
 import { JsonObject, knownString, lenient, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { GeminiToolSchema } from "./utils/gemini-tool-schema.js"
 import { Lifecycle } from "./utils/lifecycle.js"
@@ -75,18 +74,9 @@ const GeminiInlineDataPart = Schema.Struct({
    mimeType: Schema.String,
    data: Schema.String,
  }),
-  thoughtSignature: optionalNull(Schema.String),
 })
 type GeminiInlineDataPart = Schema.Schema.Type<typeof GeminiInlineDataPart>

-/** Gemini Files API reference; the only remote input Gemini accepts. */
-const GeminiFileDataPart = Schema.Struct({
-  fileData: Schema.Struct({
-    mimeType: Schema.String,
-    fileUri: Schema.String,
-  }),
-})
-
 const GeminiFunctionCallPart = Schema.Struct({
  functionCall: Schema.Struct({
    id: optionalNull(Schema.String),
@@ -108,7 +98,6 @@ const GeminiFunctionResponsePart = Schema.Struct({
 const GeminiContentPart = Schema.Union([
  GeminiTextPart,
  GeminiInlineDataPart,
-  GeminiFileDataPart,
  GeminiFunctionCallPart,
  GeminiFunctionResponsePart,
 ])
@@ -305,13 +294,9 @@ const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
    tool: (name) => ({ functionCallingConfig: { mode: "ANY" as const, allowedFunctionNames: [name] } }),
  })

-// Gemini does not fetch public URLs; inline payloads and Gemini Files references are the accepted inputs.
-const lowerContentPart = Effect.fn("Gemini.lowerContentPart")(function* (part: TextPart | MediaPart) {
+const lowerUserPart = Effect.fn("Gemini.lowerUserPart")(function* (part: TextPart | MediaPart) {
  if (part.type === "text") return { text: part.text }
-  const source = part.media.source
-  if (source.type === "ref" && source.provider === "google")
-    return { fileData: { mimeType: part.media.mediaType, fileUri: source.id } }
-  const media = yield* ProviderShared.requireInlineMedia("Gemini", part.media)
+  const media = ProviderShared.normalizeMedia(part)
  return { inlineData: { mimeType: media.mime, data: media.base64 } }
 })

@@ -359,7 +344,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
      for (const part of message.content) {
        if (!ProviderShared.supportsContent(part, ["text", "media"]))
          return yield* ProviderShared.unsupportedContent("Gemini", "user", ["text", "media"])
-        parts.push(yield* lowerContentPart(part))
+        parts.push(yield* lowerUserPart(part))
      }
      contents.push({ role: "user", parts })
      continue
@@ -370,23 +355,12 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
      // Parallel Gemini 3 calls may carry one signature on the first call; unsigned sibling calls are valid.
      let hasSignedToolCall = false
      for (const part of message.content) {
-        if (!ProviderShared.supportsContent(part, ["text", "reasoning", "tool-call", "media"]))
-          return yield* ProviderShared.unsupportedContent("Gemini", "assistant", [
-            "text",
-            "reasoning",
-            "tool-call",
-            "media",
-          ])
+        if (!ProviderShared.supportsContent(part, ["text", "reasoning", "tool-call"]))
+          return yield* ProviderShared.unsupportedContent("Gemini", "assistant", ["text", "reasoning", "tool-call"])
        if (part.type === "text") {
          parts.push({ text: part.text, thoughtSignature: thoughtSignature(part.providerMetadata, metadataKey) })
          continue
        }
-        // Generated images replay as model-role inline data so multi-turn image editing keeps the prior output.
-        if (part.type === "media") {
-          const lowered = yield* lowerContentPart(part)
-          parts.push({ ...lowered, thoughtSignature: thoughtSignature(part.providerMetadata, metadataKey) })
-          continue
-        }
        if (part.type === "reasoning") {
          parts.push({
            text: part.text,
@@ -436,7 +410,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
      const media: GeminiInlineDataPart[] = []
      for (const item of content) {
        if (item.type === "text") continue
-        const value = yield* ProviderShared.requireInlineMedia("Gemini", ProviderShared.toolFileMedia(item).media)
+        const value = ProviderShared.normalizeToolFile(item)
        media.push({ inlineData: { mimeType: value.mime, data: value.base64 } })
      }
      if (legacyToolMedia && media.length > 0) (pendingMedia ??= []).push(...media)
@@ -688,19 +662,6 @@ const step = (state: ParserState, event: GeminiEvent) => {
    // each block kind must retain the signature attached to its own parts.
    if (signature !== undefined && "thought" in part && part.thought) reasoningSignature = signature
    else if (signature !== undefined && "text" in part) textSignature = signature
-    // Image-capable Gemini models return generated images as inline data parts; surface them as first-class output.
-    if ("inlineData" in part) {
-      lifecycle = Lifecycle.stepStart(lifecycle, events)
-      events.push(
-        LLMEvent.media({
-          media: Media.base64(part.inlineData.data, part.inlineData.mimeType),
-          providerMetadata: signature
-            ? providerMetadata(state.providerMetadataKey, { thoughtSignature: signature })
-            : undefined,
-        }),
-      )
-      continue
-    }
    if ("text" in part && part.text.length > 0) {
      if (part.thought) {
        if (textId !== undefined) {
@@ -1,36 +1,40 @@
-import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
-import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
-import { Media } from "../media.js"
-import { MediaProtocol } from "../route/media-protocol.js"
-import { MediaRoute } from "../route/media.js"
-import { ProviderID, mergeJsonRecords, type AIError } from "../schema/index.js"
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import {
+  GeneratedImage,
+  ImageModel,
+  ImageResponse,
+  type ImageInput,
+  type ImageRequestFor,
+  type ImageRoute,
+} from "../image.js"
+import { Auth, type Definition as AuthDefinition } from "../route/auth.js"
+import { AIError, Usage, mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema/index.js"
 import { ProviderShared } from "./shared.js"
-import { MediaInput } from "./utils/media-input.js"
+import { ImageInputs } from "./utils/image-input.js"

 const ADAPTER = "google-images"
-const NAME = "Google Images"
-const PROVIDER = ProviderID.make("google")
 export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"

-// ---------------------------------------------------------------------------
-// 1. Public model input
-// ---------------------------------------------------------------------------
-
 export type GoogleImageString<Known extends string> = Known | (string & {})

-/** Provider-native options. Common fields (`aspectRatio`, `seed`, `images`) live on the request. */
 export type GoogleImageOptions = {
+  readonly aspectRatio?: GoogleImageString<
+    "1:1" | "2:3" | "3:2" | "3:4" | "4:3" | "4:5" | "5:4" | "9:16" | "16:9" | "21:9"
+  >
  readonly imageSize?: GoogleImageString<"1K" | "2K" | "4K">
+  readonly seed?: number
  readonly thinkingLevel?: GoogleImageString<"MINIMAL" | "LOW" | "MEDIUM" | "HIGH">
  readonly includeThoughts?: boolean
 } & Record<string, unknown>

-export type Request = ImageRequestFor<GoogleImageOptions>
-
-// ---------------------------------------------------------------------------
-// 2. Response schema
-// ---------------------------------------------------------------------------
+export type GoogleImageBody = Record<string, unknown> & {
+  readonly contents: ReadonlyArray<{
+    readonly role: "user"
+    readonly parts: ReadonlyArray<Record<string, unknown>>
+  }>
+  readonly generationConfig: Record<string, unknown>
+}

 const GoogleUsage = Schema.StructWithRest(
  Schema.Struct({
@@ -81,20 +85,30 @@ const GoogleImageResponse = Schema.Struct({
  promptFeedback: Schema.optional(Schema.Unknown),
 })

-// ---------------------------------------------------------------------------
-// 5. Request body construction
-// ---------------------------------------------------------------------------
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}

-const generationConfig = (request: Request) => {
-  const { imageSize, thinkingLevel, includeThoughts, ...native } = request.providerOptions ?? {}
-  const imageConfig = { aspectRatio: request.aspectRatio, imageSize }
-  const thinkingConfig = { thinkingLevel, includeThoughts }
+const nativeOptions = (options: GoogleImageOptions | undefined) => {
+  const { aspectRatio, imageSize, seed, thinkingLevel, includeThoughts, ...native } = options ?? {}
+  const image = {
+    aspectRatio,
+    imageSize,
+  }
+  const thinkingConfig = {
+    thinkingLevel,
+    includeThoughts,
+  }
  return (
    mergeJsonRecords(
      {
        responseModalities: ["IMAGE"],
-        imageConfig: Object.values(imageConfig).some((value) => value !== undefined) ? imageConfig : undefined,
-        seed: request.seed,
+        imageConfig: Object.values(image).some((value) => value !== undefined) ? image : undefined,
+        seed,
        thinkingConfig: Object.values(thinkingConfig).some((value) => value !== undefined) ? thinkingConfig : undefined,
      },
      native,
@@ -102,208 +116,176 @@ const generationConfig = (request: Request) => {
  )
 }

-// Gemini does not fetch public URLs; inline payloads or Gemini Files references are the only accepted inputs.
-const imagePart = (asset: Media.Asset): Effect.Effect<Record<string, unknown>, AIError> => {
-  const inline = asset.inline()
-  if (inline) return Effect.succeed({ inlineData: { mimeType: inline.mime, data: inline.base64 } })
-  const id = MediaInput.refID(asset, PROVIDER)
-  if (id) return Effect.succeed({ fileData: { mimeType: asset.mediaType, fileUri: id } })
-  if (asset.source.type === "ref")
-    return Effect.fail(
-      ProviderShared.invalidRequest(
-        "Google generateContent requires Gemini file references rather than other providers' file IDs",
-      ),
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<GoogleImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("GoogleImages.generate")(function* (request: ImageRequestFor<GoogleImageOptions>, execute) {
+      const imageParts = yield* Effect.forEach(request.images ?? [], googleImagePart)
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const requestBody = mergeJsonRecords(
+        {
+          contents: [{ role: "user", parts: [{ text: request.prompt }, ...imageParts] }],
+          generationConfig: nativeOptions(request.options),
+        },
+        http?.body,
+      ) as GoogleImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const url = applyQuery(
+        `${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}/models/${request.model.id}:generateContent`,
+        http?.query,
+      )
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      const output = yield* ProviderShared.imageResponse(ADAPTER, "Google Images", response)
+      const decoded = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(GoogleImageResponse))(output.body).pipe(
+        Effect.mapError((cause) => output.invalid("Google Images returned an invalid response", cause)),
+      )
+      const candidates = decoded.candidates ?? []
+      const candidateMetadata = candidates.map((candidate, candidateIndex) => ({
+        index: candidate.index ?? candidateIndex,
+        finishReason: candidate.finishReason,
+        finishMessage: candidate.finishMessage,
+        safetyRatings: candidate.safetyRatings,
+        citationMetadata: candidate.citationMetadata,
+        groundingMetadata: candidate.groundingMetadata,
+        parts: (candidate.content?.parts ?? []).map((part) =>
+          part.inlineData === undefined
+            ? {
+                type: "text",
+                text: part.text,
+                thought: part.thought,
+                thoughtSignature: part.thoughtSignature,
+              }
+            : {
+                type: "inlineData",
+                mediaType: part.inlineData.mimeType,
+                thought: part.thought,
+                thoughtSignature: part.thoughtSignature,
+              },
+        ),
+      }))
+      const encoded = candidates.flatMap((candidate, candidateIndex) =>
+        (candidate.content?.parts ?? []).flatMap((part, partIndex) =>
+          part.inlineData === undefined || part.thought === true
+            ? []
+            : [{ candidate, candidateIndex, partIndex, inlineData: part.inlineData }],
+        ),
+      )
+      const images = yield* Effect.forEach(encoded, (item) =>
+        Effect.fromResult(Encoding.decodeBase64(item.inlineData.data)).pipe(
+          Effect.mapError((cause) =>
+            output.invalid(
+              `Google Images candidate ${item.candidateIndex} part ${item.partIndex} contains invalid base64 data`,
+              cause,
+            ),
+          ),
+          Effect.map(
+            (data) =>
+              new GeneratedImage({
+                mediaType: item.inlineData.mimeType,
+                data,
+                providerMetadata: {
+                  google: {
+                    candidateIndex: item.candidate.index ?? item.candidateIndex,
+                    partIndex: item.partIndex,
+                    finishReason: item.candidate.finishReason,
+                    safetyRatings: item.candidate.safetyRatings,
+                    citationMetadata: item.candidate.citationMetadata,
+                    groundingMetadata: item.candidate.groundingMetadata,
+                    thoughtSignature: item.candidate.content?.parts[item.partIndex]?.thoughtSignature,
+                  },
+                },
+              }),
+          ),
+        ),
+      )
+      if (images.length === 0) {
+        const finishReasons = candidates.flatMap((candidate) =>
+          candidate.finishReason === undefined ? [] : [candidate.finishReason],
+        )
+        return yield* output.invalid(
+          `Google Images returned no final images${
+            finishReasons.length === 0 ? "" : ` (finish reasons: ${finishReasons.join(", ")})`
+          }; inspect body for prompt feedback and candidate details`,
+        )
+      }
+      const usage = decoded.usageMetadata
+      const outputTokens =
+        usage?.candidatesTokenCount === undefined
+          ? undefined
+          : usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0)
+      return new ImageResponse({
+        images,
+        usage:
+          usage === undefined
+            ? undefined
+            : new Usage({
+                inputTokens: usage.promptTokenCount,
+                outputTokens,
+                nonCachedInputTokens: ProviderShared.subtractTokens(
+                  usage.promptTokenCount,
+                  usage.cachedContentTokenCount,
+                ),
+                cacheReadInputTokens: usage.cachedContentTokenCount,
+                reasoningTokens: usage.thoughtsTokenCount,
+                totalTokens: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),
+                providerMetadata: { google: usage },
+              }),
+        providerMetadata: {
+          google: {
+            modelVersion: decoded.modelVersion,
+            responseId: decoded.responseId,
+            promptFeedback: decoded.promptFeedback,
+            candidates: candidateMetadata,
+          },
+        },
+      })
+    }),
+  }
+  return ImageModel.make<GoogleImageOptions>({ id: input.id, provider: "google", route, http: input.http })
+}
+
+const googleImagePart = (image: ImageInput): Effect.Effect<Record<string, unknown>, AIError> => {
+  if (image.type === "bytes")
+    return Effect.succeed({ inlineData: { mimeType: image.mediaType, data: Encoding.encodeBase64(image.data) } })
+  if (image.type === "file-uri") return Effect.succeed({ fileData: { mimeType: image.mediaType, fileUri: image.uri } })
+  if (image.type === "url")
+    return ImageInputs.decodeDataUrl(image.url).pipe(
+      Effect.flatMap((decoded) => {
+        if (decoded === undefined)
+          return Effect.fail(
+            ImageInputs.invalid(
+              "Google generateContent does not fetch public image URLs; use bytes, a data URL, or a Gemini file URI",
+            ),
+          )
+        return Effect.succeed({
+          inlineData: { mimeType: decoded.mediaType, data: Encoding.encodeBase64(decoded.data) },
+        })
+      }),
    )
  return Effect.fail(
-    ProviderShared.invalidRequest(
-      "Google generateContent does not fetch public image URLs; use bytes, a data URL, or a Gemini file reference",
-    ),
+    ImageInputs.invalid("Google generateContent requires Gemini file URIs rather than provider file IDs"),
  )
 }

-const fromRequest = Effect.fn("GoogleImages.fromRequest")(function* (request: Request) {
-  if (request.n !== undefined && request.n > 1)
-    return yield* ProviderShared.unsupportedOperation({
-      operation: "image.n",
-      provider: PROVIDER,
-      route: ADAPTER,
-      message: `${NAME} generates one image per request; call it once per image instead of n=${request.n}`,
-    })
-  const parts = yield* Effect.forEach(request.images ?? [], imagePart)
-  return MediaProtocol.json(
-    mergeJsonRecords(
-      {
-        contents: [{ role: "user", parts: [{ text: request.prompt }, ...parts] }],
-        generationConfig: generationConfig(request),
-      },
-      request.http?.body,
-    ) ?? {},
-  )
-})
-
-// ---------------------------------------------------------------------------
-// 6. Response decoding
-// ---------------------------------------------------------------------------
-
-const decodeResponse = Effect.fn("GoogleImages.decodeResponse")(function* (
-  response: HttpClientResponse.HttpClientResponse,
-) {
-  const output = yield* MediaProtocol.decodeJson(ADAPTER, NAME, GoogleImageResponse)(response)
-  const decoded = output.value
-  const candidates = decoded.candidates ?? []
-  const candidateMetadata = candidates.map((candidate, candidateIndex) => ({
-    index: candidate.index ?? candidateIndex,
-    finishReason: candidate.finishReason,
-    finishMessage: candidate.finishMessage,
-    safetyRatings: candidate.safetyRatings,
-    citationMetadata: candidate.citationMetadata,
-    groundingMetadata: candidate.groundingMetadata,
-    parts: (candidate.content?.parts ?? []).map((part) =>
-      part.inlineData === undefined
-        ? { type: "text", text: part.text, thought: part.thought, thoughtSignature: part.thoughtSignature }
-        : {
-            type: "inlineData",
-            mediaType: part.inlineData.mimeType,
-            thought: part.thought,
-            thoughtSignature: part.thoughtSignature,
-          },
-    ),
-  }))
-  // Thought parts are drafts; only non-thought inline data is a final image.
-  const encoded = candidates.flatMap((candidate, candidateIndex) =>
-    (candidate.content?.parts ?? []).flatMap((part, partIndex) =>
-      part.inlineData === undefined || part.thought === true
-        ? []
-        : [
-            {
-              candidate,
-              candidateIndex,
-              partIndex,
-              inlineData: part.inlineData,
-              thoughtSignature: part.thoughtSignature,
-            },
-          ],
-    ),
-  )
-  const images = yield* Effect.forEach(encoded, (item) =>
-    MediaInput.decodedAsset(
-      output.invalid,
-      `${NAME} candidate ${item.candidateIndex} part ${item.partIndex}`,
-      item.inlineData.data,
-      item.inlineData.mimeType,
-      {
-        providerMetadata: {
-          google: {
-            candidateIndex: item.candidate.index ?? item.candidateIndex,
-            partIndex: item.partIndex,
-            finishReason: item.candidate.finishReason,
-            safetyRatings: item.candidate.safetyRatings,
-            citationMetadata: item.candidate.citationMetadata,
-            groundingMetadata: item.candidate.groundingMetadata,
-            thoughtSignature: item.thoughtSignature,
-          },
-        },
-      },
-    ),
-  )
-  if (images.length === 0) {
-    const finishReasons = candidates.flatMap((candidate) =>
-      candidate.finishReason === undefined ? [] : [candidate.finishReason],
-    )
-    return yield* output.invalid(
-      `${NAME} returned no final images${
-        finishReasons.length === 0 ? "" : ` (finish reasons: ${finishReasons.join(", ")})`
-      }; inspect body for prompt feedback and candidate details`,
-    )
-  }
-  // Candidates that stopped for a safety or policy reason are partial results, not a silent drop.
-  const notices = [
-    ...(decoded.promptFeedback === undefined
-      ? []
-      : [
-          {
-            type: "filtered" as const,
-            message: `${NAME} reported prompt feedback`,
-            providerMetadata: { google: { promptFeedback: decoded.promptFeedback } },
-          },
-        ]),
-    ...candidates.flatMap((candidate, index) =>
-      candidate.finishReason === undefined || candidate.finishReason === "STOP"
-        ? []
-        : [
-            {
-              type: "filtered" as const,
-              message: `${NAME} candidate ${candidate.index ?? index} finished with ${candidate.finishReason}${
-                candidate.finishMessage === undefined ? "" : `: ${candidate.finishMessage}`
-              }`,
-              providerMetadata: {
-                google: {
-                  candidateIndex: candidate.index ?? index,
-                  finishReason: candidate.finishReason,
-                  finishMessage: candidate.finishMessage,
-                  safetyRatings: candidate.safetyRatings,
-                },
-              },
-            },
-          ],
-    ),
-  ]
-  const usage = decoded.usageMetadata
-  const outputTokens =
-    usage?.candidatesTokenCount === undefined ? undefined : usage.candidatesTokenCount + (usage.thoughtsTokenCount ?? 0)
-  return new ImageResponse({
-    images,
-    notices: notices.length === 0 ? undefined : notices,
-    usage:
-      usage === undefined
-        ? undefined
-        : {
-            type: "tokens",
-            input: usage.promptTokenCount,
-            output: outputTokens,
-            total: ProviderShared.totalTokens(usage.promptTokenCount, outputTokens, usage.totalTokenCount),
-            details: {
-              reasoningTokens: usage.thoughtsTokenCount,
-              cacheReadInputTokens: usage.cachedContentTokenCount,
-              google: usage,
-            },
-          },
-    providerMetadata: {
-      google: {
-        modelVersion: decoded.modelVersion,
-        responseId: decoded.responseId,
-        promptFeedback: decoded.promptFeedback,
-        candidates: candidateMetadata,
-      },
-    },
-  })
-})
-
-// ---------------------------------------------------------------------------
-// 7. Protocol and route
-// ---------------------------------------------------------------------------
-
-export const protocol = MediaProtocol.inline<Request, ImageResponse>({
-  id: ADAPTER,
-  name: NAME,
-  unsupported: ["mask", "size", "format"],
-  body: { from: fromRequest },
-  response: { decode: decodeResponse },
-})
-
-export const model = (input: MediaRoute.ModelInput) =>
-  ImageModel.fromRoute<GoogleImageOptions>(
-    {
-      id: ADAPTER,
-      provider: PROVIDER,
-      protocol,
-      baseURL: DEFAULT_BASE_URL,
-      path: ({ request }) => `/models/${request.model.id}:generateContent`,
-    },
-    input,
-  )
-
 export const GoogleImages = {
-  protocol,
  model,
 } as const
@@ -1,25 +1,17 @@
-import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
-import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
-import { Media } from "../media.js"
-import { MediaProtocol } from "../route/media-protocol.js"
-import { MediaRoute } from "../route/media.js"
-import { ProviderID, mergeJsonRecords, type AIError } from "../schema/index.js"
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image.js"
+import { Auth } from "../route/auth.js"
+import { Usage, mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema/index.js"
 import { JsonObject, ProviderShared, optionalNull } from "./shared.js"
-import { MediaInput } from "./utils/media-input.js"
-
-const ADAPTER = "meta-images"
-const NAME = "Meta Images"
-const PROVIDER = ProviderID.make("meta")
-
-// ---------------------------------------------------------------------------
-// 1. Public model input
-// ---------------------------------------------------------------------------
+import { ImageInputs } from "./utils/image-input.js"

 type OpenString<Known extends string> = Known | (string & {})
-
-/** Provider-native options. Common fields (`n`, `size`, `format`, `images`) live on the request. */
 export type ImageOptions = {
+  readonly n?: number
+  /** Aspect ratio hint, not an exact output resolution. */
+  readonly size?: string
+  readonly outputFormat?: OpenString<"webp" | "png" | "jpeg">
  readonly responseFormat?: OpenString<"b64_json" | "url">
  readonly reasoningStrength?: OpenString<"low" | "high">
  readonly toolEnablement?: {
@@ -30,19 +22,12 @@ export type ImageOptions = {
  readonly [key: string]: unknown
 }

-export type Request = ImageRequestFor<ImageOptions>
-
-// ---------------------------------------------------------------------------
-// 2. Request body and response schemas
-// ---------------------------------------------------------------------------
-
 const Body = Schema.StructWithRest(
  Schema.Struct({
    model: Schema.String,
    prompt: Schema.String,
    images: Schema.optional(Schema.Array(JsonObject)),
    n: Schema.optional(Schema.Number),
-    /** Aspect ratio hint, not an exact output resolution. */
    size: Schema.optional(Schema.String),
    output_format: Schema.optional(Schema.String),
    response_format: Schema.optional(Schema.String),
@@ -64,102 +49,85 @@ const Response = Schema.Struct({
  ),
 })

-// ---------------------------------------------------------------------------
-// 5. Request body construction
-// ---------------------------------------------------------------------------
-
-const isEdit = (request: Request) => (request.images?.length ?? 0) > 0
-
-const reference = (asset: Media.Asset): Effect.Effect<Record<string, unknown>, AIError> => {
-  const inline = asset.inline()
-  if (inline) return Effect.succeed({ image_url: inline.dataUrl })
-  const url = ProviderShared.mediaUrl(asset)
-  if (url) return Effect.succeed({ image_url: url })
-  return Effect.fail(ProviderShared.invalidRequest(`${NAME} accepts image bytes and URLs`))
+export const model = (input: {
+  readonly id: string
+  readonly auth: Auth.Definition
+  readonly baseURL: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}) => {
+  const route: ImageRoute<ImageOptions> = {
+    id: "meta-images",
+    generate: Effect.fn("MetaImages.generate")(function* (request: ImageRequestFor<ImageOptions>, execute) {
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const images = yield* Effect.forEach(request.images ?? [], (image) => {
+        if (image.type === "bytes") return Effect.succeed({ image_url: ImageInputs.dataUrl(image) })
+        if (image.type === "url") return Effect.succeed({ image_url: image.url })
+        return ImageInputs.invalid("Meta Images accepts image bytes and URLs")
+      })
+      const { outputFormat, responseFormat, reasoningStrength, toolEnablement, ...native } = request.options ?? {}
+      const payload = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))(
+        mergeJsonRecords(
+          {
+            model: request.model.id,
+            prompt: request.prompt,
+            images: images.length === 0 ? undefined : images,
+            output_format: outputFormat,
+            response_format: responseFormat,
+            reasoning_strength: reasoningStrength,
+            tool_enablement: toolEnablement,
+          },
+          native,
+          http?.body,
+        ),
+      )
+      const body = ProviderShared.encodeJson(payload)
+      const url = new URL(`${input.baseURL.replace(/\/$/, "")}/images/${images.length === 0 ? "generations" : "edits"}`)
+      Object.entries(http?.query ?? {}).forEach(([key, value]) => url.searchParams.set(key, value))
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url: url.toString(),
+        body,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url.toString()).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(body, "application/json"),
+        ),
+      )
+      const output = yield* ProviderShared.imageResponse("meta-images", "Meta Images", response)
+      const decoded = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(Response))(output.body).pipe(
+        Effect.mapError((cause) => output.invalid("Meta Images returned an invalid response", cause)),
+      )
+      const format = decoded.output_format ?? payload.output_format ?? "webp"
+      const generated = yield* Effect.forEach(decoded.data, (item, index) => {
+        if (item.b64_json)
+          return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
+            Effect.mapError((cause) => output.invalid(`Meta Images result ${index} contains invalid base64`, cause)),
+            Effect.map((data) => new GeneratedImage({ mediaType: `image/${format}`, data })),
+          )
+        if (item.url) return Effect.succeed(new GeneratedImage({ mediaType: `image/${format}`, data: item.url }))
+        return output.invalid(`Meta Images result ${index} has neither image data nor a URL`)
+      })
+      if (generated.length === 0) return yield* output.invalid("Meta Images returned no images")
+      return new ImageResponse({
+        images: generated,
+        usage:
+          decoded.usage === undefined
+            ? undefined
+            : new Usage({
+                inputTokens: decoded.usage.input_tokens,
+                outputTokens: decoded.usage.output_tokens,
+                totalTokens: decoded.usage.total_tokens,
+                providerMetadata: { meta: decoded.usage },
+              }),
+        providerMetadata: { meta: { outputFormat: format } },
+      })
+    }),
+  }
+  return ImageModel.make<ImageOptions>({ id: input.id, provider: "meta", route, http: input.http })
 }

-const fromRequest = Effect.fn("MetaImages.fromRequest")(function* (request: Request) {
-  const images = yield* Effect.forEach(request.images ?? [], reference)
-  const { responseFormat, reasoningStrength, toolEnablement, ...native } = request.providerOptions ?? {}
-  const payload = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))(
-    mergeJsonRecords(
-      {
-        model: request.model.id,
-        prompt: request.prompt,
-        images: images.length === 0 ? undefined : images,
-        n: request.n,
-        size: request.size,
-        output_format: request.format,
-        response_format: responseFormat,
-        reasoning_strength: reasoningStrength,
-        tool_enablement: toolEnablement,
-      },
-      native,
-      request.http?.body,
-    ),
-  )
-  return MediaProtocol.json(payload)
-})
-
-// ---------------------------------------------------------------------------
-// 6. Response decoding
-// ---------------------------------------------------------------------------
-
-const decodeResponse = Effect.fn("MetaImages.decodeResponse")(function* (
-  response: HttpClientResponse.HttpClientResponse,
-  context: MediaProtocol.DecodeContext<Request>,
-) {
-  const output = yield* MediaProtocol.decodeJson(ADAPTER, NAME, Response)(response)
-  const decoded = output.value
-  const requested = context.body.type === "json" ? context.body.value.output_format : undefined
-  const format = decoded.output_format ?? (typeof requested === "string" ? requested : "webp")
-  const mediaType = `image/${format}`
-  const images = yield* Effect.forEach(decoded.data, (item, index) => {
-    if (item.b64_json)
-      return MediaInput.decodedAsset(output.invalid, `${NAME} result ${index}`, item.b64_json, mediaType, {
-        info: { format },
-      })
-    if (item.url) return Effect.succeed(Media.url(item.url, { mediaType, info: { format } }))
-    return Effect.fail(output.invalid(`${NAME} result ${index} has neither image data nor a URL`))
-  })
-  if (images.length === 0) return yield* output.invalid(`${NAME} returned no images`)
-  return new ImageResponse({
-    images,
-    usage:
-      decoded.usage === undefined
-        ? undefined
-        : {
-            type: "tokens",
-            input: decoded.usage.input_tokens,
-            output: decoded.usage.output_tokens,
-            total: decoded.usage.total_tokens,
-            details: { meta: decoded.usage },
-          },
-    providerMetadata: { meta: { outputFormat: format } },
-  })
-})
-
-// ---------------------------------------------------------------------------
-// 7. Protocol and route
-// ---------------------------------------------------------------------------
-
-export const protocol = MediaProtocol.inline<Request, ImageResponse>({
-  id: ADAPTER,
-  name: NAME,
-  unsupported: ["mask", "aspectRatio", "seed"],
-  body: { from: fromRequest },
-  response: { decode: decodeResponse },
-})
-
-export const model = (input: MediaRoute.ModelInput & { readonly baseURL: string }) =>
-  ImageModel.fromRoute<ImageOptions>(
-    {
-      id: ADAPTER,
-      provider: PROVIDER,
-      protocol,
-      path: ({ request }) => `/images/${isEdit(request) ? "edits" : "generations"}`,
-    },
-    input,
-  )
-
 export * as MetaImages from "./meta-images.js"
@@ -224,13 +224,11 @@ type MistralEvent = Schema.Schema.Type<typeof MistralEvent>
 const MistralStreamEvent = Schema.Union([Schema.Literal(DONE), Protocol.jsonEvent(MistralEvent)])

 const lowerMedia = Effect.fn("MistralChat.lowerMedia")(function* (part: MediaPart) {
-  const mime = part.media.mediaType.toLowerCase()
-  const url =
-    ProviderShared.mediaUrl(part.media) ??
-    (yield* ProviderShared.requireInlineMedia("Mistral Chat", part.media)).dataUrl
-  if (mime.startsWith("image/")) return { type: "image_url" as const, image_url: url }
-  if (mime === "application/pdf") return { type: "document_url" as const, document_url: url }
-  return yield* ProviderShared.invalidRequest(`Mistral Chat does not support media type ${part.media.mediaType}`)
+  const media = ProviderShared.normalizeMedia(part)
+  const url = typeof part.data === "string" && /^(?:https?:|data:)/.test(part.data) ? part.data : media.dataUrl
+  if (media.mime.startsWith("image/")) return { type: "image_url" as const, image_url: url }
+  if (media.mime === "application/pdf") return { type: "document_url" as const, document_url: url }
+  return yield* ProviderShared.invalidRequest(`Mistral Chat does not support media type ${part.mediaType}`)
 })

 const lowerUser = Effect.fn("MistralChat.lowerUser")(function* (message: LLMRequest["messages"][number]) {
@@ -318,7 +316,7 @@ const lowerToolResults = Effect.fn("MistralChat.lowerToolResults")(function* (
        content.push({ type: "text", text: item.text })
        continue
      }
-      content.push(yield* lowerMedia(ProviderShared.toolFileMedia(item)))
+      content.push(yield* lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name }))
    }
    output.push({
      role: "tool",
@@ -18,7 +18,6 @@ import {
  type ToolDefinition,
  type ToolResultPart,
 } from "../schema/index.js"
-import type { Media } from "../media.js"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { classifyProviderFailure } from "../provider-error.js"
 import { effortUpdate } from "../effort-updates.js"
@@ -404,7 +403,7 @@ export interface ProviderAdapter {
  ) => Effect.Effect<{ readonly type: string }, AIError>
  readonly lowerMedia?: (input: {
    readonly part: MediaPart
-    readonly media: Media.Inline | undefined
+    readonly media: ProviderShared.NormalizedMedia
    readonly request: LLMRequest
  }) => MediaInput | undefined
  readonly restoreHostedToolItem?: (item: unknown) => HostedToolReplayItem | undefined
@@ -511,28 +510,29 @@ const lowerMedia = Effect.fn("OpenResponses.lowerMedia")(function* (
  adapter: ProviderAdapter,
  target: "message" | "tool-result",
 ) {
-  const media = part.media.inline()
+  const media = ProviderShared.normalizeMedia(part)
  const providerMedia = adapter.lowerMedia?.({ part, media, request })
  if (providerMedia) return providerMedia
  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
-  if (part.media.kind !== "image") {
-    if (target === "tool-result" && part.media.kind === "video")
-      return { type: "input_video" as const, video_url: location }
+  const url =
+    typeof part.data === "string" && (part.data.startsWith("https://") || part.data.startsWith("http://"))
+      ? part.data
+      : undefined
+  if (!media.mime.startsWith("image/")) {
+    if (target === "tool-result" && media.mime.startsWith("video/"))
+      return { type: "input_video" as const, video_url: url ?? media.dataUrl }
    return {
      type: "input_file" as const,
-      filename: part.filename ?? (mime === "application/pdf" ? "document.pdf" : "file"),
+      filename: part.filename ?? (media.mime === "application/pdf" ? "document.pdf" : "file"),
      detail,
-      ...(url ? { file_url: url } : { file_data: location }),
+      ...(url ? { file_url: url } : { file_data: media.dataUrl }),
    }
  }
  return {
    type: "input_image" as const,
-    image_url: location,
+    image_url: url ?? media.dataUrl,
    detail,
  }
 })
@@ -562,7 +562,12 @@ const lowerToolResultContentItem = Effect.fnUntraced(function* (
  adapter: ProviderAdapter,
 ) {
  if (item.type === "text") return { type: "input_text" as const, text: item.text }
-  return yield* lowerMedia(ProviderShared.toolFileMedia(item), request, adapter, "tool-result")
+  return yield* lowerMedia(
+    { type: "media", mediaType: item.mime, data: item.uri, filename: item.name },
+    request,
+    adapter,
+    "tool-result",
+  )
 })

 const lowerHostedToolResultContentItem = Effect.fnUntraced(function* (
@@ -571,7 +576,11 @@ const lowerHostedToolResultContentItem = Effect.fnUntraced(function* (
  adapter: ProviderAdapter,
 ) {
  if (item.type === "text") return { type: "input_text" as const, text: item.text }
-  return yield* lowerMessageMedia(ProviderShared.toolFileMedia(item), request, adapter)
+  return yield* lowerMessageMedia(
+    { type: "media", mediaType: item.mime, data: item.uri, filename: item.name },
+    request,
+    adapter,
+  )
 })

 const lowerToolResultOutput = Effect.fnUntraced(function* (
@@ -717,22 +726,11 @@ const lowerMessages = Effect.fn("OpenResponses.lowerMessages")(function* (
          })
          continue
        }
-        if (part.type === "media") {
-          flushText()
-          // Responses has no assistant-authored image item; replay generated media (e.g. from Gemini) as user input.
-          input.push({
-            type: "message",
-            role: "user",
-            content: [yield* lowerMessageMedia(part, request, adapter)],
-          })
-          continue
-        }
        return yield* ProviderShared.unsupportedContent(adapter.name, "assistant", [
          "text",
          "reasoning",
          "tool-call",
          "tool-result",
-          "media",
        ])
      }
      flushText()
@@ -1,4 +1,4 @@
-import { Effect, Option, Schema } from "effect"
+import { Effect, Schema } from "effect"
 import { Tool } from "@opencode/schema/tool"
 import { Route } from "../route/client.js"
 import { Auth } from "../route/auth.js"
@@ -76,44 +76,6 @@ const OpenAIChatAssistantToolCall = Schema.Struct({
 })
 type OpenAIChatAssistantToolCall = Schema.Schema.Type<typeof OpenAIChatAssistantToolCall>

-// `reasoning_details` carries two dialects. OpenRouter's `reasoning.*` entries
-// must be replayed unmodified (`index` included), so they keep every field they
-// arrived with. Kimi's OpenAI-compatible surface streams preserved thinking as
-// bare `summary` / `encrypted` entries keyed by a stream-only `index`; Kimi does
-// not document this publicly, so the handling follows Kimi Code (Kimi's own
-// client): merge summary deltas by `index`, replay without `index`, and always
-// send `reasoning_content` alongside. Anything else is dropped at the boundary.
-const OpenRouterDetailFields = {
-  id: Schema.optional(Schema.NullOr(Schema.String)),
-  format: Schema.optional(Schema.String),
-  index: Schema.optional(Schema.Number),
-  signature: Schema.optional(Schema.NullOr(Schema.String)),
-}
-const ReasoningDetail = Schema.Union([
-  Schema.StructWithRest(
-    Schema.Struct({ type: Schema.Literal("reasoning.text"), text: Schema.optional(Schema.String), ...OpenRouterDetailFields }),
-    [Schema.Record(Schema.String, Schema.Unknown)],
-  ),
-  Schema.StructWithRest(
-    Schema.Struct({
-      type: Schema.Literal("reasoning.summary"),
-      summary: Schema.optional(Schema.String),
-      ...OpenRouterDetailFields,
-    }),
-    [Schema.Record(Schema.String, Schema.Unknown)],
-  ),
-  Schema.StructWithRest(
-    Schema.Struct({ type: Schema.Literal("reasoning.encrypted"), data: Schema.String, ...OpenRouterDetailFields }),
-    [Schema.Record(Schema.String, Schema.Unknown)],
-  ),
-  Schema.Struct({ type: Schema.Literal("summary"), summary: Schema.String, index: Schema.optional(Schema.Number) }),
-  Schema.Struct({ type: Schema.Literal("encrypted"), encrypted: Schema.String, index: Schema.optional(Schema.Number) }),
-])
-type ReasoningDetail = Schema.Schema.Type<typeof ReasoningDetail>
-const decodeReasoningDetail = Schema.decodeUnknownOption(ReasoningDetail)
-const knownReasoningDetails = (details: ReadonlyArray<unknown>) =>
-  details.flatMap((detail) => Option.toArray(decodeReasoningDetail(detail)))
-
 // Intentionally omit Gemini's provider-specific `extra_content.google.thought_signature`
 // extension until direct Google OpenAI-compatible routing is supported here:
 // https://github.com/vercel/ai/issues/11590
@@ -303,9 +265,7 @@ export interface ParserState {
  readonly finishReason?: FinishReasonDetails
  readonly lifecycle: Lifecycle.State
  readonly reasoningField?: string
-  /** A scalar reasoning field (`reasoning_content`, ...) has carried text in this stream. */
-  readonly reasoningTextObserved: boolean
-  readonly reasoningDetails: Array<ReasoningDetail>
+  readonly reasoningDetails: Array<unknown>
  readonly reasoningDetailsObserved: boolean
  readonly reasoningEmitted: boolean
  readonly latestToolIndex?: number
@@ -360,10 +320,13 @@ const lowerToolCall = (part: ToolCallPart, options: LoweringOptions): OpenAIChat
 })

 const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart) {
-  if (part.media.kind !== "image")
-    return yield* ProviderShared.invalidRequest(`OpenAI Chat does not support media type ${part.media.mediaType}`)
+  const media = ProviderShared.normalizeMedia(part)
+  if (!media.mime.startsWith("image/"))
+    return yield* ProviderShared.invalidRequest(`OpenAI Chat does not support media type ${part.mediaType}`)
  const url =
-    ProviderShared.mediaUrl(part.media) ?? (yield* ProviderShared.requireInlineMedia("OpenAI Chat", part.media)).dataUrl
+    typeof part.data === "string" && (part.data.startsWith("https://") || part.data.startsWith("http://"))
+      ? part.data
+      : media.dataUrl
  return { type: "image_url" as const, image_url: { url } }
 })

@@ -381,21 +344,10 @@ const reasoningDetails = (parts: ReadonlyArray<ReasoningPart>, native: unknown,
    return Array.isArray(details) ? details : []
  })
  if (parts.some((part) => Array.isArray(part.providerMetadata?.[providerMetadataKey]?.reasoningDetails)))
-    return knownReasoningDetails(observed).map(lowerReasoningDetail)
-  if (isRecord(native) && Array.isArray(native.reasoning_details))
-    return knownReasoningDetails(native.reasoning_details).map(lowerReasoningDetail)
+    return observed
+  if (isRecord(native) && Array.isArray(native.reasoning_details)) return native.reasoning_details
 }

-// Kimi rejects its stream-only `index` on requests
-// ("the reasoning_details ... must not contain streaming index").
-const lowerReasoningDetail = (detail: ReasoningDetail) => {
-  if (detail.type === "summary") return { type: detail.type, summary: detail.summary }
-  if (detail.type === "encrypted") return { type: detail.type, encrypted: detail.encrypted }
-  return detail
-}
-
-const isKimiDetail = (detail: { readonly type: string }) => detail.type === "summary" || detail.type === "encrypted"
-
 const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (
  message: OpenAIChatRequestMessage,
  options: LoweringOptions,
@@ -461,9 +413,6 @@ const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(func
    if (observedField !== undefined) return observedField
    if (nativeReasoning !== undefined) return "reasoning_content"
    if (!fullyStructured || requireReasoning) return "reasoning_content"
-    // Kimi always expects `reasoning_content` on replayed assistant messages,
-    // even when thinking arrived only through structured details.
-    if (details?.some(isKimiDetail)) return "reasoning_content"
  })()
  const reasoningText = (() => {
    if (configuredField !== undefined)
@@ -511,7 +460,11 @@ const lowerToolMessages = Effect.fn("OpenAIChat.lowerToolMessages")(function* (
      cache_control: options.cacheControl?.(part.cache),
    })
    const files = content.filter((item) => item.type === "file")
-    images.push(...(yield* Effect.forEach(files, (item) => lowerMedia(ProviderShared.toolFileMedia(item)))))
+    images.push(
+      ...(yield* Effect.forEach(files, (item) =>
+        lowerMedia({ type: "media", mediaType: item.mime, data: item.uri, filename: item.name }),
+      )),
+    )
  }
  return { messages, images }
 })
@@ -765,8 +718,7 @@ const lowerOptions = (request: LLMRequest, supportsStore: boolean) => {
  // Default off: strict providers 400 on unknown body fields, so only send
  // the key where compatibility explicitly allows it. Header-based affinity
  // (x-session-affinity, x-grok-conv-id, ...) is unaffected.
-  const cacheKey =
-    (request.model.compatibility?.supportsPromptCacheKey ?? false) ? ProviderShared.promptCacheKey(request) : undefined
+  const cacheKey = (request.model.compatibility?.supportsPromptCacheKey ?? false) ? ProviderShared.promptCacheKey(request) : undefined
  return {
    ...(supportsStore && options.store !== undefined ? { store: options.store } : {}),
    // For providers that support `store`, ensure stateless `store:false` is sent
@@ -935,74 +887,44 @@ const reasoningDelta = (
  return undefined
 }

-const detailText = (details: ReadonlyArray<ReasoningDetail>, hideKimiSummary: boolean) => {
+const detailText = (details: ReadonlyArray<unknown>) => {
  const text = details.flatMap((detail) => {
-    if (detail.type === "reasoning.text") return detail.text ? [detail.text] : []
-    if (detail.type === "reasoning.summary") return detail.summary ? [detail.summary] : []
-    // Kimi streams the full thinking through `reasoning_content` and a separate
-    // summary through details; show the summary only when nothing else does.
-    if (detail.type === "summary") return detail.summary && !hideKimiSummary ? [detail.summary] : []
+    if (!isRecord(detail)) return []
+    if (detail.type === "reasoning.text" && typeof detail.text === "string" && detail.text) return [detail.text]
+    if (detail.type === "reasoning.summary" && typeof detail.summary === "string" && detail.summary)
+      return [detail.summary]
    return []
  })
  if (text.length > 0) return text.join("")
 }

-const appendReasoningDetails = (result: Array<ReasoningDetail>, details: ReadonlyArray<ReasoningDetail>) => {
+const appendReasoningDetails = (result: Array<unknown>, details: ReadonlyArray<unknown>) => {
  for (const detail of details) {
    const previous = result.at(-1)
-    const merged = previous === undefined ? undefined : mergeReasoningDetails(previous, detail)
-    if (merged === undefined) {
+    if (
+      !isRecord(previous) ||
+      previous.type !== "reasoning.text" ||
+      !isRecord(detail) ||
+      detail.type !== "reasoning.text" ||
+      conflictingReasoningTextDetails(previous, detail)
+    ) {
      result.push(detail)
      continue
    }
-    result[result.length - 1] = merged
+    result[result.length - 1] = {
+      ...previous,
+      ...Object.fromEntries(Object.entries(detail).filter((entry) => entry[1] !== undefined)),
+      text: `${typeof previous.text === "string" ? previous.text : ""}${typeof detail.text === "string" ? detail.text : ""}`,
+      signature: mergeDetailValue(previous.signature, detail.signature),
+      format: mergeDetailValue(previous.format, detail.format),
+    }
  }
 }

-// Consecutive text or summary deltas of the same kind accumulate into one
-// entry; encrypted entries are opaque and never merge.
-const mergeReasoningDetails = (previous: ReasoningDetail, detail: ReasoningDetail): ReasoningDetail | undefined => {
-  if (conflictingReasoningDetails(previous, detail)) return undefined
-  if (previous.type === "reasoning.text" && detail.type === "reasoning.text")
-    return {
-      ...previous,
-      ...detail,
-      text: `${previous.text ?? ""}${detail.text ?? ""}`,
-      ...mergeDetailIdentity(previous, detail),
-    }
-  if (previous.type === "reasoning.summary" && detail.type === "reasoning.summary")
-    return {
-      ...previous,
-      ...detail,
-      summary: `${previous.summary ?? ""}${detail.summary ?? ""}`,
-      ...mergeDetailIdentity(previous, detail),
-    }
-  if (previous.type === "summary" && detail.type === "summary")
-    return { ...previous, ...detail, summary: previous.summary + detail.summary }
-}
-
-type DetailIdentity = {
-  readonly id?: string | null
-  readonly index?: number
-  readonly format?: string
-  readonly signature?: string | null
-}
-
-// The first non-empty signature and format win; a later delta may carry the
-// signature for text that streamed earlier.
-const mergeDetailIdentity = (previous: DetailIdentity, current: DetailIdentity) => {
-  const signature = mergeDetailValue(previous.signature, current.signature)
-  const format = mergeDetailValue(previous.format, current.format)
-  return {
-    ...(signature === undefined ? {} : { signature }),
-    ...(format === undefined ? {} : { format }),
-  }
-}
-
-const mergeDetailValue = <T>(previous: T | undefined, current: T | undefined) =>
+const mergeDetailValue = (previous: unknown, current: unknown) =>
  previous || current || (previous !== undefined ? previous : current)

-const conflictingReasoningDetails = (previous: DetailIdentity, current: DetailIdentity) =>
+const conflictingReasoningTextDetails = (previous: Record<string, unknown>, current: Record<string, unknown>) =>
  conflictingDetailValue(previous.id, current.id) ||
  conflictingDetailValue(previous.index, current.index) ||
  conflictingDetailValue(previous.format, current.format) ||
@@ -1014,7 +936,7 @@ const conflictingDetailValue = (previous: unknown, current: unknown) =>
 const reasoningMetadata = (
  providerMetadataKey: string,
  field: ParserState["reasoningField"],
-  details?: ReadonlyArray<ReasoningDetail>,
+  details?: ReadonlyArray<unknown>,
 ) => ({
  [providerMetadataKey]: {
    ...(field ? { reasoningField: field } : {}),
@@ -1077,16 +999,11 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
    }

    const reasoningField = state.reasoningField ?? reasoning?.field
-    const reasoningTextObserved = state.reasoningTextObserved || reasoning !== undefined
-    const detailDelta = Array.isArray(delta?.reasoning_details)
-      ? knownReasoningDetails(delta.reasoning_details)
-      : undefined
+    const detailDelta = Array.isArray(delta?.reasoning_details) ? delta.reasoning_details : undefined
    if (detailDelta !== undefined) appendReasoningDetails(state.reasoningDetails, detailDelta)
    const reasoningDetailsObserved = state.reasoningDetailsObserved || detailDelta !== undefined
    const deltaMetadata = reasoningMetadata(state.providerMetadataKey, reasoningField)
-    const text = detailDelta?.length
-      ? (detailText(detailDelta, reasoningTextObserved) ?? reasoning?.text)
-      : reasoning?.text
+    const text = detailDelta?.length ? (detailText(detailDelta) ?? reasoning?.text) : reasoning?.text
    if (text !== undefined) lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
    else if (
      reasoningDetailsObserved &&
@@ -1182,7 +1099,6 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
        finishReason,
        lifecycle,
        reasoningField,
-        reasoningTextObserved,
        reasoningDetails: state.reasoningDetails,
        reasoningDetailsObserved,
        reasoningEmitted,
@@ -1263,7 +1179,6 @@ export const protocol = Protocol.make({
      toolCallEvents: [],
      lifecycle: Lifecycle.initial(),
      reasoningField: request.model.compatibility?.reasoningField,
-      reasoningTextObserved: false,
      reasoningDetails: [],
      reasoningDetailsObserved: false,
      reasoningEmitted: false,
@@ -1,39 +1,43 @@
-import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
-import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
-import { Media } from "../media.js"
-import { MediaProtocol } from "../route/media-protocol.js"
-import { MediaRoute } from "../route/media.js"
-import { ProviderID, mergeJsonRecords, type AIError } from "../schema/index.js"
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
+import {
+  ImageModel,
+  GeneratedImage,
+  ImageResponse,
+  type ImageInput,
+  type ImageRequestFor,
+  type ImageRoute,
+} from "../image.js"
+import { Auth, type Definition as AuthDefinition } from "../route/auth.js"
+import { Usage, mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema/index.js"
 import { ProviderShared } from "./shared.js"
-import { MediaInput } from "./utils/media-input.js"
+import { ImageInputs } from "./utils/image-input.js"
+import { OpenAIImage } from "./utils/openai-image.js"

 const ADAPTER = "openai-images"
-const NAME = "OpenAI Images"
-const PROVIDER = ProviderID.make("openai")
 export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
 export const PATH = "/images/generations"
 export const EDIT_PATH = "/images/edits"

-// ---------------------------------------------------------------------------
-// 1. Public model input
-// ---------------------------------------------------------------------------
-
 export type OpenAIImageString<Known extends string> = Known | (string & {})

-/** Provider-native options. Common fields (`n`, `size`, `format`, `images`, `mask`) live on the request. */
 export type OpenAIImageOptions = {
+  readonly mask?: ImageInput
+  readonly n?: number
+  readonly size?: OpenAIImageString<
+    "auto" | "256x256" | "512x512" | "1024x1024" | "1536x1024" | "1024x1536" | "1792x1024" | "1024x1792"
+  >
  readonly quality?: OpenAIImageString<"auto" | "low" | "medium" | "high" | "standard" | "hd">
  readonly background?: OpenAIImageString<"auto" | "opaque" | "transparent">
  readonly moderation?: OpenAIImageString<"auto" | "low">
+  readonly outputFormat?: OpenAIImageString<"png" | "jpeg" | "webp">
  readonly outputCompression?: number
 } & Record<string, unknown>

-export type Request = ImageRequestFor<OpenAIImageOptions>
-
-// ---------------------------------------------------------------------------
-// 2. Response schema
-// ---------------------------------------------------------------------------
+export type OpenAIImageBody = Record<string, unknown> & {
+  readonly model: string
+  readonly prompt: string
+}

 const OpenAIImageResponse = Schema.Struct({
  data: Schema.Array(
@@ -55,153 +59,196 @@ const OpenAIImageResponse = Schema.Struct({
  ),
 })

-// ---------------------------------------------------------------------------
-// 5. Request body construction
-// ---------------------------------------------------------------------------
-
-/** Multipart field names the route owns; `http.body` overlays cannot smuggle replacements for them. */
-const RESERVED_FORM_FIELDS = new Set(["model", "prompt", "image", "image[]", "images", "mask"])
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}

 const nativeOptions = (options: OpenAIImageOptions | undefined) => {
  if (!options) return undefined
-  const { outputCompression, ...native } = options
-  return { output_compression: outputCompression, ...native }
-}
-
-const isEdit = (request: Request) => (request.images?.length ?? 0) > 0
-
-const isInline = (asset: Media.Asset) => asset.inline() !== undefined
-
-const blob = (data: Uint8Array, mediaType: string) => {
-  const buffer = new ArrayBuffer(data.byteLength)
-  new Uint8Array(buffer).set(data)
-  return new Blob([buffer], { type: mediaType })
-}
-
-const reference = (asset: Media.Asset): Effect.Effect<Record<string, unknown>, AIError> => {
-  const inline = asset.inline()
-  if (inline) return Effect.succeed({ image_url: inline.dataUrl })
-  const url = ProviderShared.mediaUrl(asset)
-  if (url) return Effect.succeed({ image_url: url })
-  const id = MediaInput.refID(asset, PROVIDER)
-  if (id) return Effect.succeed({ file_id: id })
-  return Effect.fail(
-    ProviderShared.invalidRequest("OpenAI Images accepts image URLs, data URLs, bytes, and OpenAI file IDs"),
-  )
-}
-
-const fromRequest = Effect.fn("OpenAIImages.fromRequest")(function* (request: Request) {
-  const images = request.images ?? []
-  const mask = request.mask
-  if (mask !== undefined && images.length === 0)
-    return yield* ProviderShared.invalidRequest("An OpenAI image mask requires at least one input image")
-  const fields = mergeJsonRecords(
-    { n: request.n, size: request.size, output_format: request.format },
-    nativeOptions(request.providerOptions),
-    request.http?.body,
-  )
-
-  // Owned bytes go through multipart edits; remote URLs and file IDs use the JSON edits body instead.
-  if (images.length > 0 && images.every(isInline) && (mask === undefined || isInline(mask))) {
-    const form = new FormData()
-    form.append("model", request.model.id)
-    form.append("prompt", request.prompt)
-    Object.entries(fields ?? {}).forEach(([key, value]) => {
-      if (RESERVED_FORM_FIELDS.has(key)) return
-      form.append(key, typeof value === "string" ? value : ProviderShared.encodeJson(value))
-    })
-    const uploads = yield* Effect.forEach(images, (image) => MediaInput.inlineBytes(ADAPTER, image))
-    uploads.forEach((data, index) => form.append("image[]", blob(data, images[index].mediaType), `image-${index}`))
-    if (mask !== undefined)
-      form.append("mask", blob(yield* MediaInput.inlineBytes(ADAPTER, mask), mask.mediaType), "mask")
-    return MediaProtocol.multipart(form)
+  const { mask: _, outputFormat, outputCompression, ...native } = options
+  return {
+    output_format: outputFormat,
+    output_compression: outputCompression,
+    ...native,
  }
-
-  const references = yield* Effect.forEach(images, reference)
-  const maskReference = mask === undefined ? undefined : yield* reference(mask)
-  return MediaProtocol.json(
-    mergeJsonRecords(
-      {
-        model: request.model.id,
-        prompt: request.prompt,
-        images: references.length === 0 ? undefined : references,
-        mask: maskReference,
-      },
-      fields,
-    ) ?? {},
-  )
-})
-
-// ---------------------------------------------------------------------------
-// 6. Response decoding
-// ---------------------------------------------------------------------------
-
-const requestedFormat = (body: MediaProtocol.Body) => {
-  const value = body.type === "json" ? body.value.output_format : body.value.get("output_format")
-  return typeof value === "string" ? value : undefined
 }

-const decodeResponse = Effect.fn("OpenAIImages.decodeResponse")(function* (
-  response: HttpClientResponse.HttpClientResponse,
-  context: MediaProtocol.DecodeContext<Request>,
-) {
-  const output = yield* MediaProtocol.decodeJson(ADAPTER, NAME, OpenAIImageResponse)(response)
-  const decoded = output.value
-  const format = decoded.output_format ?? requestedFormat(context.body) ?? "png"
-  const mediaType = `image/${format}`
-  const images = yield* Effect.forEach(decoded.data, (item, index) => {
-    const providerMetadata =
-      item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } }
-    if (item.b64_json)
-      return MediaInput.decodedAsset(output.invalid, `${NAME} result ${index}`, item.b64_json, mediaType, {
-        info: { format },
-        providerMetadata,
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<OpenAIImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("OpenAIImages.generate")(function* (request: ImageRequestFor<OpenAIImageOptions>, execute) {
+      const mask = request.options?.mask
+      if (mask !== undefined && (request.images?.length ?? 0) === 0)
+        return yield* ImageInputs.invalid("An OpenAI image mask requires at least one input image")
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const sourceImages = request.images ?? []
+      const multipartImages = yield* Effect.forEach(sourceImages, (image) => {
+        if (image.type === "bytes") return Effect.succeed({ data: image.data, mediaType: image.mediaType })
+        if (image.type === "url") return ImageInputs.decodeDataUrl(image.url)
+        return Effect.undefined
      })
-    if (item.url) return Effect.succeed(Media.url(item.url, { mediaType, info: { format }, providerMetadata }))
-    return Effect.fail(output.invalid(`${NAME} result ${index} has neither image data nor a URL`))
+      const multipartMask =
+        mask === undefined
+          ? undefined
+          : mask.type === "bytes"
+            ? { data: mask.data, mediaType: mask.mediaType }
+            : mask.type === "url"
+              ? yield* ImageInputs.decodeDataUrl(mask.url)
+              : undefined
+      const useMultipart =
+        sourceImages.length > 0 &&
+        multipartImages.every((image) => image !== undefined) &&
+        (mask === undefined || multipartMask !== undefined)
+      const path = sourceImages.length === 0 ? PATH : EDIT_PATH
+      const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${path}`, http?.query)
+
+      if (useMultipart) {
+        const form = new FormData()
+        form.append("model", request.model.id)
+        form.append("prompt", request.prompt)
+        Object.entries(mergeJsonRecords(nativeOptions(request.options), http?.body) ?? {}).forEach(([key, value]) => {
+          if (["model", "prompt", "image", "image[]", "images", "mask"].includes(key)) return
+          form.append(key, typeof value === "string" ? value : ProviderShared.encodeJson(value))
+        })
+        multipartImages.forEach((image, index) => {
+          if (image === undefined) return
+          form.append("image[]", imageBlob(image.data, image.mediaType), `image-${index}`)
+        })
+        if (multipartMask !== undefined)
+          form.append("mask", imageBlob(multipartMask.data, multipartMask.mediaType), "mask")
+        const headers = yield* Auth.toEffect(input.auth)({
+          request,
+          method: "POST",
+          url,
+          body: "[multipart/form-data]",
+          headers: Headers.remove(Headers.fromInput({ ...input.headers, ...http?.headers }), "content-type"),
+        })
+        const response = yield* execute(
+          HttpClientRequest.post(url).pipe(HttpClientRequest.setHeaders(headers), HttpClientRequest.bodyFormData(form)),
+        )
+        return yield* parseResponse(response, request.options, http?.body)
+      }
+
+      const references = sourceImages.map((image) => {
+        if (image.type === "bytes") return { image_url: ImageInputs.dataUrl(image) }
+        if (image.type === "url") return { image_url: image.url }
+        if (image.type === "file-id") return { file_id: image.id }
+        return undefined
+      })
+      if (references.some((image) => image === undefined))
+        return yield* ImageInputs.invalid("OpenAI Images accepts image URLs, data URLs, bytes, and file IDs")
+      const maskReference =
+        mask === undefined
+          ? undefined
+          : mask.type === "bytes"
+            ? { image_url: ImageInputs.dataUrl(mask) }
+            : mask.type === "url"
+              ? { image_url: mask.url }
+              : mask.type === "file-id"
+                ? { file_id: mask.id }
+                : undefined
+      if (mask !== undefined && maskReference === undefined)
+        return yield* ImageInputs.invalid("OpenAI Images accepts masks as URLs, data URLs, bytes, or file IDs")
+      const requestBody = mergeJsonRecords(
+        {
+          model: request.model.id,
+          prompt: request.prompt,
+          images: references.length === 0 ? undefined : references,
+          mask: maskReference,
+        },
+        nativeOptions(request.options),
+        http?.body,
+      ) as OpenAIImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      return yield* parseResponse(response, request.options, http?.body)
+    }),
+  }
+  return ImageModel.make<OpenAIImageOptions>({ id: input.id, provider: "openai", route, http: input.http })
+}
+
+const parseResponse = Effect.fn("OpenAIImages.parseResponse")(function* (
+  response: HttpClientResponse.HttpClientResponse,
+  options: OpenAIImageOptions | undefined,
+  overlay: Record<string, unknown> | undefined,
+) {
+  const output = yield* ProviderShared.imageResponse(ADAPTER, "OpenAI Images", response)
+  const decoded = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(OpenAIImageResponse))(output.body).pipe(
+    Effect.mapError((cause) => output.invalid("OpenAI Images returned an invalid response", cause)),
+  )
+  const requestBody = mergeJsonRecords(nativeOptions(options), overlay)
+  const format =
+    decoded.output_format ?? (typeof requestBody?.output_format === "string" ? requestBody.output_format : "png")
+  const images = yield* Effect.forEach(decoded.data, (item, index) => {
+    if (item.b64_json)
+      return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
+        Effect.mapError((cause) => output.invalid(`OpenAI Images result ${index} contains invalid base64 data`, cause)),
+        Effect.map(
+          (data) =>
+            new GeneratedImage({
+              mediaType: `image/${format}`,
+              data,
+              providerMetadata:
+                item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+            }),
+        ),
+      )
+    if (item.url)
+      return Effect.succeed(
+        new GeneratedImage({
+          mediaType: `image/${format}`,
+          data: item.url,
+          providerMetadata:
+            item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+        }),
+      )
+    return Effect.fail(output.invalid(`OpenAI Images result ${index} has neither image data nor a URL`))
  })
-  if (images.length === 0) return yield* output.invalid(`${NAME} returned no images`)
+  if (images.length === 0) return yield* output.invalid("OpenAI Images returned no images")
  return new ImageResponse({
    images,
    usage:
      decoded.usage === undefined
        ? undefined
-        : {
-            type: "tokens",
-            input: decoded.usage.input_tokens,
-            output: decoded.usage.output_tokens,
-            total: decoded.usage.total_tokens,
-            details: { openai: decoded.usage },
-          },
+        : new Usage({
+            inputTokens: decoded.usage.input_tokens,
+            outputTokens: decoded.usage.output_tokens,
+            totalTokens: decoded.usage.total_tokens,
+            providerMetadata: { openai: decoded.usage },
+          }),
    providerMetadata: { openai: { outputFormat: format } },
  })
 })

-// ---------------------------------------------------------------------------
-// 7. Protocol and route
-// ---------------------------------------------------------------------------
-
-export const protocol = MediaProtocol.inline<Request, ImageResponse>({
-  id: ADAPTER,
-  name: NAME,
-  unsupported: ["aspectRatio", "seed"],
-  body: { from: fromRequest },
-  response: { decode: decodeResponse },
-})
-
-export const model = (input: MediaRoute.ModelInput) =>
-  ImageModel.fromRoute<OpenAIImageOptions>(
-    {
-      id: ADAPTER,
-      provider: PROVIDER,
-      protocol,
-      baseURL: DEFAULT_BASE_URL,
-      path: ({ request }) => (isEdit(request) ? EDIT_PATH : PATH),
-    },
-    input,
-  )
+const imageBlob = (data: Uint8Array, mediaType: string) => {
+  const buffer = new ArrayBuffer(data.byteLength)
+  new Uint8Array(buffer).set(data)
+  return new Blob([buffer], { type: mediaType })
+}

 export const OpenAIImages = {
-  protocol,
  model,
 } as const
@@ -1,13 +1,14 @@
+import { Buffer } from "node:buffer"
 import { Tool } from "@opencode/schema/tool"
 import { Effect, Option, Schema, Stream } from "effect"
 import * as Sse from "effect/unstable/encoding/Sse"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
-import { Media } from "../media.js"
+import { Headers, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
 import {
  InvalidProviderOutputError,
  InvalidRequestError,
  UnsupportedOperationError,
  AIError,
+  HttpContext,
  LLMRequest,
  Message,
  ToolDefinition,
@@ -178,34 +179,25 @@ export const wrappedSystemUpdate = Effect.fn("ProviderShared.wrappedSystemUpdate
 export const parseToolInput = (route: string, name: string, raw: string) =>
  parseJson(route, raw || "{}", `Invalid JSON input for ${route} tool call ${name}`)

-/** Inline view or a typed `InvalidRequest` for routes that cannot fetch URLs or dereference provider refs. */
-export const requireInlineMedia = (route: string, asset: Media.Asset): Effect.Effect<Media.Inline, AIError> => {
-  const inline = asset.inline()
-  return inline ? Effect.succeed(inline) : Effect.fail(inlineRequired(route, asset))
+export interface NormalizedMedia {
+  readonly mime: string
+  readonly base64: string
+  readonly dataUrl: string
 }

-export const inlineRequired = (route: string, asset: Media.Asset) =>
-  invalidRequest(
-    `${route} requires inline media (bytes or base64); ${asset.source.type} sources must be materialized first`,
-  )
-
-/** The remote URL of a `url` asset, for protocols that accept `http(s)` references natively. */
-export const mediaUrl = (asset: Media.Asset) => (asset.source.type === "url" ? asset.source.url : undefined)
-
-/**
- * Lift a tool-result file into a `MediaPart`. Tool files carry either a data URL, an `http(s)` URL, or raw base64 in
- * `uri`; the declared `mime` wins over any data-URL prefix so tool authors control the type the model sees.
- */
-export const toolFileMedia = (item: Tool.FileContent): MediaPart => {
-  const parsed = Media.parseDataUrl(item.uri)
-  const asset = parsed
-    ? Media.from({ ...parsed.source, mediaType: item.mime })
-    : /^https?:\/\//.test(item.uri)
-      ? Media.url(item.uri, { mediaType: item.mime })
-      : Media.base64(item.uri, item.mime)
-  return Message.media(asset, { filename: item.name })
+export const normalizeMedia = (part: MediaPart): NormalizedMedia => {
+  const mime = part.mediaType.toLowerCase()
+  if (typeof part.data !== "string") {
+    const base64 = Buffer.from(part.data).toString("base64")
+    return { mime, base64, dataUrl: `data:${mime};base64,${base64}` }
+  }
+  if (!part.data.startsWith("data:")) return { mime, base64: part.data, dataUrl: `data:${mime};base64,${part.data}` }
+  return { mime, base64: part.data.slice(part.data.indexOf(",") + 1), dataUrl: part.data }
 }

+export const normalizeToolFile = (part: Tool.FileContent) =>
+  normalizeMedia({ type: "media", mediaType: part.mime, data: part.uri, filename: part.name })
+
 export const trimBaseUrl = (value: string) => value.replace(/\/+$/, "")

 export const toolResultText = (part: ToolResultPart) => {
@@ -231,11 +223,11 @@ export const errorText = (error: unknown) => {

 /**
 * `framing` step for Server-Sent Events. Decodes UTF-8, runs the SSE channel
- * decoder, optionally filters named events, and drops empty and bare `null`
- * events. `[DONE]` is dropped by default or retained for protocols that use it
- * as their stream boundary. Retry control events are ignored without
- * interrupting the stream. Decoder failures become provider output errors so
- * the public error channel stays `AIError`.
+ * decoder, optionally filters named events, and drops empty events. `[DONE]`
+ * is dropped by default or retained for protocols that use it as their stream
+ * boundary. Retry control events are ignored without interrupting the stream.
+ * Decoder failures become provider output errors so the public error channel
+ * stays `AIError`.
 */
 export const sseFraming = (
  bytes: Stream.Stream<Uint8Array, AIError>,
@@ -265,10 +257,6 @@ export const sseFraming = (
      (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" &&
        (event.data !== "[DONE]" || includeDone || (events !== undefined && event.event !== "message")),
    ),
    Stream.map((event) => event.data),
@@ -337,6 +325,34 @@ export const flattenToolRequest = (request: LLMRequest) => {
  }
 }

+export const imageResponse = Effect.fn("ProviderShared.imageResponse")(function* (
+  route: string,
+  name: string,
+  response: HttpClientResponse.HttpClientResponse,
+) {
+  const http = new HttpContext({ url: response.request.url, status: response.status, headers: response.headers })
+  const body = yield* response.text.pipe(
+    Effect.mapError(
+      (cause) =>
+        new AIError({
+          reason: new InvalidProviderOutputError({
+            route,
+            message: `Failed to read the ${name} response`,
+            http,
+            cause,
+          }),
+        }),
+    ),
+  )
+  return {
+    body,
+    invalid: (message: string, cause?: unknown) =>
+      new AIError({
+        reason: new InvalidProviderOutputError({ route, message, body, http, cause }),
+      }),
+  }
+})
+
 export const matchToolChoice = <Auto, None, Required, Tool>(
  route: string,
  toolChoice: NonNullable<LLMRequest["toolChoice"]>,
@@ -77,7 +77,7 @@ function documentName(filename: string | undefined, names: Set<string>) {
 }

 const mediaBase64 = Effect.fn("BedrockMedia.mediaBase64")(function* (part: MediaPart) {
-  const media = yield* ProviderShared.requireInlineMedia("Bedrock Converse", part.media)
+  const media = ProviderShared.normalizeMedia(part)
  const bytes = yield* Effect.fromResult(Encoding.decodeBase64(media.base64)).pipe(
    Effect.mapError((cause) =>
      ProviderShared.invalidRequest("Bedrock Converse media data must be valid base64", cause),
@@ -92,15 +92,13 @@ const mediaBase64 = Effect.fn("BedrockMedia.mediaBase64")(function* (part: Media
 // get an image-specific error so the caller knows it's a format-support issue,
 // not a kind-detection issue.
 export const lower = Effect.fn("BedrockMedia.lower")(function* (part: MediaPart, documentNames: Set<string>) {
-  const mime = part.media.mediaType.toLowerCase()
+  const mime = part.mediaType.toLowerCase()
  const imageFormat = IMAGE_FORMATS[mime as keyof typeof IMAGE_FORMATS]
  if (imageFormat) {
    return [{ image: { format: imageFormat, source: { bytes: yield* mediaBase64(part) } } } satisfies ImageBlock]
  }
  if (mime.startsWith("image/"))
-    return yield* ProviderShared.invalidRequest(
-      `Bedrock Converse does not support image media type ${part.media.mediaType}`,
-    )
+    return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support image media type ${part.mediaType}`)
  const documentFormat = DOCUMENT_FORMATS[mime as keyof typeof DOCUMENT_FORMATS]
  if (documentFormat) {
    const name = documentName(part.filename, documentNames)
@@ -114,7 +112,7 @@ export const lower = Effect.fn("BedrockMedia.lower")(function* (part: MediaPart,
        ]
      : [block]
  }
-  return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.media.mediaType}`)
+  return yield* ProviderShared.invalidRequest(`Bedrock Converse does not support media type ${part.mediaType}`)
 })

 export * as BedrockMedia from "./bedrock-media.js"
@@ -0,0 +1,31 @@
+import { Effect, Encoding } from "effect"
+import type { ImageInput } from "../../image.js"
+import { InvalidRequestError, AIError } from "../../schema/index.js"
+
+const invalid = (message: string, cause?: unknown) =>
+  new AIError({
+    reason: new InvalidRequestError({ message, cause }),
+  })
+
+export const dataUrl = (input: Extract<ImageInput, { readonly type: "bytes" }>) =>
+  `data:${input.mediaType};base64,${Encoding.encodeBase64(input.data)}`
+
+export const decodeDataUrl = (
+  url: string,
+): Effect.Effect<{ readonly mediaType: string; readonly data: Uint8Array } | undefined, AIError> => {
+  if (!url.startsWith("data:")) return Effect.undefined
+  const match = /^data:([^;,]+);base64,(.*)$/s.exec(url)
+  if (!match) return Effect.fail(invalid("Image data URLs must contain a MIME type and base64 data"))
+  return Effect.fromResult(Encoding.decodeBase64(match[2])).pipe(
+    Effect.mapError((cause) => invalid("Image data URL contains invalid base64 data", cause)),
+    Effect.map((data) => ({ mediaType: match[1], data })),
+  )
+}
+
+export const invalidImageInput = invalid
+
+export const ImageInputs = {
+  dataUrl,
+  decodeDataUrl,
+  invalid: invalidImageInput,
+} as const
@@ -1,33 +0,0 @@
-import { Effect, Encoding } from "effect"
-import { Media } from "../../media.js"
-import type { AIError, ProviderID } from "../../schema/index.js"
-import { ProviderShared } from "../shared.js"
-
-/** Owned bytes for multipart uploads; decodes `base64` sources and rejects remote sources. */
-export const inlineBytes = (route: string, asset: Media.Asset): Effect.Effect<Uint8Array, AIError> => {
-  if (asset.source.type === "bytes") return Effect.succeed(asset.source.data)
-  const inline = asset.inline()
-  if (!inline) return Effect.fail(ProviderShared.inlineRequired(route, asset))
-  return Effect.fromResult(Encoding.decodeBase64(inline.base64)).pipe(
-    Effect.mapError((cause) => ProviderShared.invalidRequest(`${route} media contains invalid base64 data`, cause)),
-  )
-}
-
-/** Provider file handle when the ref belongs to this provider; refs from other providers are never forwarded. */
-export const refID = (asset: Media.Asset, provider: ProviderID) =>
-  asset.source.type === "ref" && asset.source.provider === provider ? asset.source.id : undefined
-
-/** Decode a provider's base64 output once into an owned `bytes` asset, sniffing the type when it is not declared. */
-export const decodedAsset = (
-  invalid: (message: string, cause?: unknown) => AIError,
-  label: string,
-  data: string,
-  mediaType: string | undefined,
-  options?: Media.AssetOptions,
-) =>
-  Effect.fromResult(Encoding.decodeBase64(data)).pipe(
-    Effect.mapError((cause) => invalid(`${label} contains invalid base64 data`, cause)),
-    Effect.map((bytes) => Media.bytes(bytes, mediaType, options)),
-  )
-
-export * as MediaInput from "./media-input.js"
@@ -17,7 +17,6 @@ import { RequestExecutor } from "../../route/executor.js"
 import { HttpTransport } from "../../route/transport/index.js"
 import { OpenResponses } from "../open-responses.js"
 import { JsonObject, optionalNull, ProviderShared } from "../shared.js"
-import { Media } from "../../media.js"

 const Body = Schema.Struct({
  model: Schema.String,
@@ -158,22 +157,20 @@ function toMessage(item: (typeof Response.Type.output)[number], model: LLMReques
      if (part.type === "input_image")
        return {
          type: "media",
-          media: replayMedia(part.image_url, "image/*"),
+          data: part.image_url,
+          mediaType: /^data:([^;,]+)/.exec(part.image_url)?.[1] ?? "image/*",
          providerMetadata: part.detail === undefined ? undefined : { [key]: { detail: part.detail } },
        }
+      const data = part.file_url === undefined ? part.file_data : part.file_url
      return {
        type: "media",
-        media: replayMedia(part.file_url === undefined ? part.file_data : part.file_url, "application/octet-stream"),
+        data,
        filename: part.filename,
+        mediaType: /^data:([^;,]+)/.exec(data)?.[1] ?? "application/octet-stream",
        providerMetadata: part.detail === undefined ? undefined : { [key]: { detail: part.detail } },
      }
    }),
  })
 }

-/** Replayed compaction items carry either a data URL or a remote URL; the data URL's own type wins when present. */
-const replayMedia = (value: string, fallbackType: string) =>
-  Media.parseDataUrl(value) ??
-  (/^https?:\/\//.test(value) ? Media.url(value, { mediaType: fallbackType }) : Media.base64(value, fallbackType))
-
 export * as ResponsesCompaction from "./responses-compaction.js"
@@ -1,38 +1,61 @@
-import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
-import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
-import { Media } from "../media.js"
-import { MediaProtocol } from "../route/media-protocol.js"
-import { MediaRoute } from "../route/media.js"
-import { ProviderID, mergeJsonRecords, type AIError } from "../schema/index.js"
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image.js"
+import { Auth, type Definition as AuthDefinition } from "../route/auth.js"
+import { Usage, mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema/index.js"
 import { ProviderShared, optionalNull } from "./shared.js"
-import { MediaInput } from "./utils/media-input.js"
+import { ImageInputs } from "./utils/image-input.js"

 const ADAPTER = "xai-images"
-const NAME = "xAI Images"
-const PROVIDER = ProviderID.make("xai")
 export const DEFAULT_BASE_URL = "https://api.x.ai/v1"
 export const PATH = "/images/generations"
 export const EDIT_PATH = "/images/edits"

-// ---------------------------------------------------------------------------
-// 1. Public model input
-// ---------------------------------------------------------------------------
-
 export type XAIImageString<Known extends string> = Known | (string & {})

-/** Provider-native options. Common fields (`n`, `aspectRatio`, `images`) live on the request. */
 export type XAIImageOptions = {
+  readonly n?: number
+  readonly aspectRatio?: XAIImageString<
+    | "1:1"
+    | "3:4"
+    | "4:3"
+    | "9:16"
+    | "16:9"
+    | "2:3"
+    | "3:2"
+    | "9:19.5"
+    | "19.5:9"
+    | "9:20"
+    | "20:9"
+    | "1:2"
+    | "2:1"
+    | "auto"
+  >
+  readonly aspect_ratio?: XAIImageString<
+    | "1:1"
+    | "3:4"
+    | "4:3"
+    | "9:16"
+    | "16:9"
+    | "2:3"
+    | "3:2"
+    | "9:19.5"
+    | "19.5:9"
+    | "9:20"
+    | "20:9"
+    | "1:2"
+    | "2:1"
+    | "auto"
+  >
  readonly resolution?: XAIImageString<"1k" | "2k">
  readonly responseFormat?: XAIImageString<"url" | "b64_json">
  readonly response_format?: XAIImageString<"url" | "b64_json">
 } & Record<string, unknown>

-export type Request = ImageRequestFor<XAIImageOptions>
-
-// ---------------------------------------------------------------------------
-// 2. Response schema
-// ---------------------------------------------------------------------------
+type XAIImageBody = Record<string, unknown> & {
+  readonly model: string
+  readonly prompt: string
+}

 const XAIImageResponse = Schema.Struct({
  data: Schema.Array(
@@ -46,109 +69,120 @@ const XAIImageResponse = Schema.Struct({
  usage: Schema.optional(Schema.Unknown),
 })

-// ---------------------------------------------------------------------------
-// 5. Request body construction
-// ---------------------------------------------------------------------------
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}

 const nativeOptions = (options: XAIImageOptions | undefined) => {
  if (!options) return undefined
-  const { responseFormat, ...native } = options
-  return { response_format: responseFormat, ...native }
+  const { aspectRatio, responseFormat, ...native } = options
+  return {
+    aspect_ratio: aspectRatio,
+    response_format: responseFormat,
+    ...native,
+  }
 }

-const isEdit = (request: Request) => (request.images?.length ?? 0) > 0
-
-const reference = (asset: Media.Asset): Effect.Effect<Record<string, unknown>, AIError> => {
-  const inline = asset.inline()
-  if (inline) return Effect.succeed({ url: inline.dataUrl, type: "image_url" as const })
-  const url = ProviderShared.mediaUrl(asset)
-  if (url) return Effect.succeed({ url, type: "image_url" as const })
-  const id = MediaInput.refID(asset, PROVIDER)
-  if (id) return Effect.succeed({ file_id: id })
-  return Effect.fail(ProviderShared.invalidRequest(`${NAME} accepts image URLs, data URLs, bytes, and xAI file IDs`))
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
 }

-const fromRequest = Effect.fn("XAIImages.fromRequest")(function* (request: Request) {
-  const references = yield* Effect.forEach(request.images ?? [], reference)
-  return MediaProtocol.json(
-    mergeJsonRecords(
-      {
-        model: request.model.id,
-        prompt: request.prompt,
-        // xAI takes one edit source as `image` and several as `images`.
-        image: references.length === 1 ? references[0] : undefined,
-        images: references.length > 1 ? references : undefined,
-        n: request.n,
-        aspect_ratio: request.aspectRatio,
-      },
-      nativeOptions(request.providerOptions),
-      request.http?.body,
-    ) ?? {},
-  )
-})
-
-// ---------------------------------------------------------------------------
-// 6. Response decoding
-// ---------------------------------------------------------------------------
-
-const decodeResponse = Effect.fn("XAIImages.decodeResponse")(function* (
-  response: HttpClientResponse.HttpClientResponse,
-) {
-  const output = yield* MediaProtocol.decodeJson(ADAPTER, NAME, XAIImageResponse)(response)
-  const decoded = output.value
-  const images = yield* Effect.forEach(decoded.data, (item, index) => {
-    const providerMetadata =
-      item.revised_prompt === undefined || item.revised_prompt === null
-        ? undefined
-        : { xai: { revisedPrompt: item.revised_prompt } }
-    if (item.b64_json)
-      return MediaInput.decodedAsset(
-        output.invalid,
-        `${NAME} result ${index}`,
-        item.b64_json,
-        item.mime_type ?? undefined,
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<XAIImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("XAIImages.generate")(function* (request: ImageRequestFor<XAIImageOptions>, execute) {
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const imageReferences = (request.images ?? []).map((image) => {
+        if (image.type === "bytes") return { url: ImageInputs.dataUrl(image), type: "image_url" as const }
+        if (image.type === "url") return { url: image.url, type: "image_url" as const }
+        if (image.type === "file-id") return { file_id: image.id }
+        return undefined
+      })
+      if (imageReferences.some((image) => image === undefined))
+        return yield* ImageInputs.invalid("xAI Images accepts image URLs, data URLs, bytes, and file IDs")
+      const requestBody = mergeJsonRecords(
        {
-          providerMetadata,
+          model: request.model.id,
+          prompt: request.prompt,
+          image: imageReferences.length === 1 ? imageReferences[0] : undefined,
+          images: imageReferences.length > 1 ? imageReferences : undefined,
        },
+        nativeOptions(request.options),
+        http?.body,
+      ) as XAIImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const url = applyQuery(
+        `${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${imageReferences.length === 0 ? PATH : EDIT_PATH}`,
+        http?.query,
      )
-    if (item.url)
-      return Effect.succeed(Media.url(item.url, { mediaType: item.mime_type ?? undefined, providerMetadata }))
-    return Effect.fail(output.invalid(`${NAME} result ${index} has neither image data nor a URL`))
-  })
-  if (images.length === 0) return yield* output.invalid(`${NAME} returned no images`)
-  const usage = ProviderShared.isRecord(decoded.usage) ? decoded.usage : undefined
-  // xAI reports image counts rather than tokens, seconds, or credits; the raw record stays in provider metadata.
-  return new ImageResponse({
-    images,
-    providerMetadata: usage === undefined ? undefined : { xai: { usage } },
-  })
-})
-
-// ---------------------------------------------------------------------------
-// 7. Protocol and route
-// ---------------------------------------------------------------------------
-
-export const protocol = MediaProtocol.inline<Request, ImageResponse>({
-  id: ADAPTER,
-  name: NAME,
-  unsupported: ["mask", "size", "seed", "format"],
-  body: { from: fromRequest },
-  response: { decode: decodeResponse },
-})
-
-export const model = (input: MediaRoute.ModelInput) =>
-  ImageModel.fromRoute<XAIImageOptions>(
-    {
-      id: ADAPTER,
-      provider: PROVIDER,
-      protocol,
-      baseURL: DEFAULT_BASE_URL,
-      path: ({ request }) => (isEdit(request) ? EDIT_PATH : PATH),
-    },
-    input,
-  )
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      const output = yield* ProviderShared.imageResponse(ADAPTER, "xAI Images", response)
+      const decoded = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(XAIImageResponse))(output.body).pipe(
+        Effect.mapError((cause) => output.invalid("xAI Images returned an invalid response", cause)),
+      )
+      const images = yield* Effect.forEach(decoded.data, (item, index) => {
+        const mediaType = item.mime_type ?? "application/octet-stream"
+        if (item.b64_json)
+          return Effect.fromResult(Encoding.decodeBase64(item.b64_json)).pipe(
+            Effect.mapError((cause) =>
+              output.invalid(`xAI Images result ${index} contains invalid base64 data`, cause),
+            ),
+            Effect.map(
+              (data) =>
+                new GeneratedImage({
+                  mediaType,
+                  data,
+                  providerMetadata:
+                    item.revised_prompt === undefined || item.revised_prompt === null
+                      ? undefined
+                      : { xai: { revisedPrompt: item.revised_prompt } },
+                }),
+            ),
+          )
+        if (item.url)
+          return Effect.succeed(
+            new GeneratedImage({
+              mediaType,
+              data: item.url,
+              providerMetadata:
+                item.revised_prompt === undefined || item.revised_prompt === null
+                  ? undefined
+                  : { xai: { revisedPrompt: item.revised_prompt } },
+            }),
+          )
+        return Effect.fail(output.invalid(`xAI Images result ${index} has neither image data nor a URL`))
+      })
+      if (images.length === 0) return yield* output.invalid("xAI Images returned no images")
+      const usage = ProviderShared.isRecord(decoded.usage) ? decoded.usage : undefined
+      return new ImageResponse({
+        images,
+        usage: usage === undefined ? undefined : new Usage({ providerMetadata: { xai: usage } }),
+        providerMetadata: usage === undefined ? undefined : { xai: { usage } },
+      })
+    }),
+  }
+  return ImageModel.make<XAIImageOptions>({ id: input.id, provider: "xai", route, http: input.http })
+}

 export const XAIImages = {
-  protocol,
  model,
 } as const
@@ -1,34 +1,29 @@
 import { Effect, Schema } from "effect"
-import type { HttpClientResponse } from "effect/unstable/http"
-import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
-import { Media } from "../media.js"
-import { MediaProtocol } from "../route/media-protocol.js"
-import { MediaRoute } from "../route/media.js"
-import { ProviderID, mergeJsonRecords } from "../schema/index.js"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image.js"
+import { Auth, type Definition as AuthDefinition } from "../route/auth.js"
+import { mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema/index.js"
+import { ProviderShared } from "./shared.js"
+import { ImageInputs } from "./utils/image-input.js"

 const ADAPTER = "zai-images"
-const NAME = "Z.ai Images"
-const PROVIDER = ProviderID.make("zai")
 export const DEFAULT_BASE_URL = "https://api.z.ai/api/paas/v4"
 export const PATH = "/images/generations"

-// ---------------------------------------------------------------------------
-// 1. Public model input
-// ---------------------------------------------------------------------------
-
 export type ZAIImageString<Known extends string> = Known | (string & {})

-/** Provider-native options. The common `size` field lives on the request. */
 export type ZAIImageOptions = {
+  readonly size?: ZAIImageString<
+    "1024x1024" | "768x1344" | "864x1152" | "1344x768" | "1152x864" | "1440x720" | "720x1440"
+  >
  readonly quality?: ZAIImageString<"hd" | "standard">
  readonly userID?: string
 } & Record<string, unknown>

-export type Request = ImageRequestFor<ZAIImageOptions>
-
-// ---------------------------------------------------------------------------
-// 2. Response schema
-// ---------------------------------------------------------------------------
+type ZAIImageBody = Record<string, unknown> & {
+  readonly model: string
+  readonly prompt: string
+}

 const ZAIImageResponse = Schema.Struct({
  created: Schema.optional(Schema.Int),
@@ -45,81 +40,84 @@ const ZAIImageResponse = Schema.Struct({
  ),
 })

-// ---------------------------------------------------------------------------
-// 5. Request body construction
-// ---------------------------------------------------------------------------
+export interface ModelInput {
+  readonly id: string
+  readonly auth: AuthDefinition
+  readonly baseURL?: string
+  readonly headers?: Record<string, string>
+  readonly http?: HttpOptions
+}

 const nativeOptions = (options: ZAIImageOptions | undefined) => {
  if (!options) return undefined
  const { userID, ...native } = options
-  return { user_id: userID, ...native }
+  return {
+    user_id: userID,
+    ...native,
+  }
 }

-const fromRequest = Effect.fn("ZAIImages.fromRequest")(function* (request: Request) {
-  return MediaProtocol.json(
-    mergeJsonRecords(
-      { model: request.model.id, prompt: request.prompt, size: request.size },
-      nativeOptions(request.providerOptions),
-      request.http?.body,
-    ) ?? {},
-  )
-})
+const applyQuery = (url: string, query: Record<string, string> | undefined) => {
+  if (!query) return url
+  const next = new URL(url)
+  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
+  return next.toString()
+}

-// ---------------------------------------------------------------------------
-// 6. Response decoding
-// ---------------------------------------------------------------------------
-
-const decodeResponse = Effect.fn("ZAIImages.decodeResponse")(function* (
-  response: HttpClientResponse.HttpClientResponse,
-) {
-  const output = yield* MediaProtocol.decodeJson(ADAPTER, NAME, ZAIImageResponse)(response)
-  const decoded = output.value
-  if (decoded.data.length === 0) return yield* output.invalid(`${NAME} returned no images`)
-  const filters = decoded.content_filter ?? []
-  return new ImageResponse({
-    // Z.ai returns only URLs and no content type; the media type resolves when the asset is materialized.
-    images: decoded.data.map((item) => Media.url(item.url)),
-    // Z.ai reports applied content filters alongside a successful result; surface them instead of dropping them.
-    notices:
-      filters.length === 0
-        ? undefined
-        : filters.map((filter) => ({
-            type: "moderated" as const,
-            message: `${NAME} applied a content filter${filter.role === undefined ? "" : ` for ${filter.role}`}${
-              filter.level === undefined ? "" : ` at level ${filter.level}`
-            }`,
-            providerMetadata: { zai: filter },
-          })),
-    providerMetadata: {
-      zai: {
-        created: decoded.created,
-        id: decoded.id,
-        requestID: decoded.request_id,
-        contentFilter: decoded.content_filter,
-      },
-    },
-  })
-})
-
-// ---------------------------------------------------------------------------
-// 7. Protocol and route
-// ---------------------------------------------------------------------------
-
-export const protocol = MediaProtocol.inline<Request, ImageResponse>({
-  id: ADAPTER,
-  name: NAME,
-  unsupported: ["images", "mask", "n", "aspectRatio", "seed", "format"],
-  body: { from: fromRequest },
-  response: { decode: decodeResponse },
-})
-
-export const model = (input: MediaRoute.ModelInput) =>
-  ImageModel.fromRoute<ZAIImageOptions>(
-    { id: ADAPTER, provider: PROVIDER, protocol, baseURL: DEFAULT_BASE_URL, path: PATH },
-    input,
-  )
+export const model = (input: ModelInput) => {
+  const route: ImageRoute<ZAIImageOptions> = {
+    id: ADAPTER,
+    generate: Effect.fn("ZAIImages.generate")(function* (request: ImageRequestFor<ZAIImageOptions>, execute) {
+      if ((request.images?.length ?? 0) > 0)
+        return yield* ImageInputs.invalid("Z.ai hosted image generation does not support image inputs")
+      const http = mergeHttpOptions(request.model.http, request.http)
+      const requestBody = mergeJsonRecords(
+        { model: request.model.id, prompt: request.prompt },
+        nativeOptions(request.options),
+        http?.body,
+      ) as ZAIImageBody
+      const text = ProviderShared.encodeJson(requestBody)
+      const url = applyQuery(`${(input.baseURL ?? DEFAULT_BASE_URL).replace(/\/$/, "")}${PATH}`, http?.query)
+      const headers = yield* Auth.toEffect(input.auth)({
+        request,
+        method: "POST",
+        url,
+        body: text,
+        headers: Headers.fromInput({ ...input.headers, ...http?.headers }),
+      })
+      const response = yield* execute(
+        HttpClientRequest.post(url).pipe(
+          HttpClientRequest.setHeaders(headers),
+          HttpClientRequest.bodyText(text, "application/json"),
+        ),
+      )
+      const output = yield* ProviderShared.imageResponse(ADAPTER, "Z.ai Images", response)
+      const decoded = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(ZAIImageResponse))(output.body).pipe(
+        Effect.mapError((cause) => output.invalid("Z.ai Images returned an invalid response", cause)),
+      )
+      if (decoded.data.length === 0) return yield* output.invalid("Z.ai Images returned no images")
+      return new ImageResponse({
+        images: decoded.data.map(
+          (item) =>
+            new GeneratedImage({
+              mediaType: "application/octet-stream",
+              data: item.url,
+            }),
+        ),
+        providerMetadata: {
+          zai: {
+            created: decoded.created,
+            id: decoded.id,
+            requestID: decoded.request_id,
+            contentFilter: decoded.content_filter,
+          },
+        },
+      })
+    }),
+  }
+  return ImageModel.make<ZAIImageOptions>({ id: input.id, provider: "zai", route, http: input.http })
+}

 export const ZAIImages = {
-  protocol,
  model,
 } as const
@@ -44,12 +44,7 @@ export const configure = (input: LanguageModelOptions = {}) => {
    model: (modelID: string | ModelID) =>
      configured.model<OpenAIProviderOptionsInput>({
        id: modelID,
-        compatibility: {
-          maxTokensField: "max_tokens",
-          reasoningField: "reasoning",
-          supportsStore: false,
-          supportsPromptCacheKey: true,
-        },
+        compatibility: { maxTokensField: "max_tokens", reasoningField: "reasoning", supportsStore: false, supportsPromptCacheKey: true },
      }),
    configure,
  }
@@ -47,12 +47,7 @@ export const configure = (input: LanguageModelOptions = {}) => {
    model: (modelID: string | ModelID) =>
      configured.model<OpenAIProviderOptionsInput>({
        id: modelID,
-        compatibility: {
-          maxTokensField: "max_tokens",
-          reasoningField: "reasoning_content",
-          supportsStore: false,
-          supportsPromptCacheKey: true,
-        },
+        compatibility: { maxTokensField: "max_tokens", reasoningField: "reasoning_content", supportsStore: false, supportsPromptCacheKey: true },
      }),
    configure,
  }
@@ -38,13 +38,23 @@ export type Settings = ProviderPackage.Settings &

 const fromRequest = Effect.fn("GoogleVertex.fromRequest")(function* (request: LLMRequest) {
  const { serviceTier: _, ...body } = yield* Gemini.protocol.body.from(request)
+  // Vertex's native REST schema rejects `id` on FunctionCall/FunctionResponse parts with HTTP 400,
+  // unlike AI Studio, so history minted there cannot be lowered verbatim.
+  const contents = body.contents.map((content) => ({
+    ...content,
+    parts: (content.parts ?? []).map((part) => {
+      if ("functionCall" in part) return { ...part, functionCall: { ...part.functionCall, id: undefined } }
+      if ("functionResponse" in part) return { ...part, functionResponse: { ...part.functionResponse, id: undefined } }
+      return part
+    }),
+  }))
  const value = request.providerOptions?.labels
  const labels = ProviderShared.isRecord(value)
    ? Object.fromEntries(
        Object.entries(value).filter((entry): entry is [string, string] => typeof entry[1] === "string"),
      )
    : undefined
-  return { ...body, labels }
+  return { ...body, contents, labels }
 })

 const protocol = {
@@ -24,11 +24,8 @@ export * as Moonshot from "./moonshot.js"
 export * as OpenAI from "./openai.js"
 export * as OpenAICompatible from "./openai-compatible.js"
 export * as OpenAICompatibleResponses from "./openai-compatible-responses.js"
-export * as OpenCodeZen from "./opencode-zen.js"
 export * as OpenRouter from "./openrouter.js"
 export * as TogetherAI from "./togetherai.js"
-export * as TypeSafeAI from "./typesafe-ai.js"
-export * as VercelAIGateway from "./vercel-ai-gateway.js"
 export * as XAI from "./xai.js"
 export * as ZAI from "./zai.js"
 export * as ZAICodingPlan from "./zai-coding-plan.js"
@@ -1,31 +0,0 @@
-import { HttpOptions, ProviderID, type ModelID } from "../schema/index.js"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { SystemOne } from "../experimental/system-one.js"
-
-export const id = ProviderID.make("opencode")
-const baseURL = "https://opencode.ai/zen/v1"
-
-export type Options = ProviderAuthOption<"optional"> & {
-  readonly baseURL?: string
-  readonly headers?: Record<string, string>
-  readonly http?: HttpOptions.Input
-}
-
-export const configure = (input: Options = {}) => {
-  const evaluation = (modelID: string | ModelID) =>
-    SystemOne.model({
-      id: modelID,
-      provider: id,
-      providerMetadataKey: "opencode",
-      auth: AuthOptions.bearer(input, "OPENCODE_API_KEY"),
-      baseURL: input.baseURL ?? baseURL,
-      headers: input.headers,
-      http: input.http === undefined ? undefined : HttpOptions.make(input.http),
-    })
-  return { id, experimental: { evaluation }, configure }
-}
-
-export const provider = configure()
-export const experimental = provider.experimental
-
-export * as OpenCodeZen from "./opencode-zen.js"
@@ -3,9 +3,8 @@ import { Route, type RouteDefaultsInput } from "../route/client.js"
 import { Endpoint } from "../route/endpoint.js"
 import { Protocol } from "../route/protocol.js"
 import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { HttpOptions, ProviderID, type CacheHint, type ModelID } from "../schema/index.js"
+import { ProviderID, type CacheHint, type ModelID } from "../schema/index.js"
 import type { ProviderPackage } from "../provider-package.js"
-import { SystemOne } from "../experimental/system-one.js"
 import { OpenAIChat } from "../protocols/openai-chat.js"
 import { newBreakpoints, ttlBucket } from "../protocols/utils/cache.js"
 import { isRecord } from "../protocols/shared.js"
@@ -72,14 +71,6 @@ export interface OpenRouterOptions {

 export type OpenRouterProviderOptionsInput = OpenRouterOptions

-export interface OpenRouterEvaluationOptions {
-  readonly [key: string]: unknown
-  readonly provider?: OpenRouterProviderRouting
-  readonly session_id?: string
-  readonly trace?: Readonly<Record<string, unknown>>
-  readonly user?: string
-}
-
 export type LanguageModelOptions = Omit<RouteDefaultsInput, "providerOptions"> &
  ProviderAuthOption<"optional"> & {
    readonly baseURL?: string
@@ -190,27 +181,15 @@ const configuredRoute = (input: LanguageModelOptions) => {

 export const configure = (input: LanguageModelOptions = {}) => {
  const route = configuredRoute(input)
-  const evaluation = (modelID: string | ModelID) =>
-    SystemOne.model<OpenRouterEvaluationOptions>({
-      id: modelID,
-      provider: id,
-      providerMetadataKey: "openrouter",
-      auth: AuthOptions.bearer(input, "OPENROUTER_API_KEY"),
-      baseURL: input.baseURL ?? baseURL,
-      headers: input.headers,
-      http: input.http === undefined ? undefined : HttpOptions.make(input.http),
-    })
  return {
    id,
    model: (modelID: string | ModelID) =>
      route.model<OpenRouterProviderOptionsInput>({ id: modelID, compatibility: { supportsPromptCacheKey: true } }),
-    experimental: { evaluation },
    configure,
  }
 }

 export const provider = configure()
-export const experimental = provider.experimental
 export const model: ProviderPackage.Definition<Settings, OpenRouterProviderOptionsInput>["model"] = (
  modelID,
  { apiKey, baseURL, body, headers, ...providerOptions },
@@ -1,31 +0,0 @@
-import { HttpOptions, ProviderID, type ModelID } from "../schema/index.js"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { SystemOne } from "../experimental/system-one.js"
-
-export const id = ProviderID.make("typesafe-ai")
-const baseURL = "https://api.typesafe.ai/v1"
-
-export type Options = ProviderAuthOption<"optional"> & {
-  readonly baseURL?: string
-  readonly headers?: Record<string, string>
-  readonly http?: HttpOptions.Input
-}
-
-export const configure = (input: Options = {}) => {
-  const evaluation = (modelID: string | ModelID) =>
-    SystemOne.model({
-      id: modelID,
-      provider: id,
-      providerMetadataKey: "typesafe",
-      auth: AuthOptions.bearer(input, "TYPESAFE_API_KEY"),
-      baseURL: input.baseURL ?? baseURL,
-      headers: input.headers,
-      http: input.http === undefined ? undefined : HttpOptions.make(input.http),
-    })
-  return { id, experimental: { evaluation }, configure }
-}
-
-export const provider = configure()
-export const experimental = provider.experimental
-
-export * as TypeSafeAI from "./typesafe-ai.js"
@@ -1,148 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
-import {
-  EvaluationAnswer,
-  EvaluationInput,
-  EvaluationModel,
-  EvaluationQuestion,
-  EvaluationResponse,
-  EvaluationRounding,
-} from "../experimental/evaluation.js"
-import { Auth } from "../route/auth.js"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import {
-  AIError,
-  HttpContext,
-  HttpOptions,
-  InvalidProviderOutputError,
-  InvalidRequestError,
-  ModelID,
-  ProviderID,
-  ProviderMetadata,
-  Usage,
-} from "../schema/index.js"
-
-export const id = ProviderID.make("vercel-ai-gateway")
-const baseURL = "https://ai-gateway.vercel.sh/v1"
-
-export interface EvaluationOptions {
-  readonly [key: string]: unknown
-  readonly gateway?: Readonly<{
-    readonly [key: string]: unknown
-    readonly zeroDataRetention?: boolean
-    readonly only?: ReadonlyArray<string>
-  }>
-}
-
-export type Options = ProviderAuthOption<"optional"> & {
-  readonly baseURL?: string
-  readonly headers?: Record<string, string>
-  readonly http?: HttpOptions.Input
-}
-
-const Request = Schema.StructWithRest(
-  Schema.Struct({
-    model: Schema.String,
-    state: EvaluationInput,
-    questions: Schema.Record(Schema.String, EvaluationQuestion),
-    providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
-  }),
-  [Schema.Record(Schema.String, Schema.Any)],
-)
-const Response = Schema.Struct({
-  model: Schema.optional(Schema.String),
-  answers: Schema.Record(Schema.String, EvaluationAnswer),
-  usage: Schema.optional(
-    Schema.Struct({
-      inputTokens: Schema.optional(Schema.Number),
-      outputTokens: Schema.optional(Schema.Number),
-    }),
-  ),
-  rounding: Schema.optional(EvaluationRounding),
-  providerMetadata: Schema.optional(ProviderMetadata),
-})
-
-export const configure = (input: Options = {}) => {
-  const evaluation = (modelID: string | ModelID) =>
-    EvaluationModel.make<EvaluationOptions>({
-      id: modelID,
-      provider: id,
-      http: input.http === undefined ? undefined : HttpOptions.make(input.http),
-      route: {
-        id: "vercel-evaluation",
-        evaluate: (req, send) =>
-          Effect.gen(function* () {
-            const url = new URL(`${(input.baseURL ?? baseURL).replace(/\/$/, "")}/evaluate`)
-            Object.entries(req.http?.query ?? {}).forEach(([key, value]) => url.searchParams.set(key, value))
-            const body = yield* Schema.encodeUnknownEffect(Schema.fromJsonString(Request))({
-              ...req.http?.body,
-              model: req.model.id,
-              state: req.state,
-              questions: req.questions,
-              providerOptions: req.options,
-            }).pipe(
-              Effect.mapError(
-                (cause) => new AIError({ reason: new InvalidRequestError({ message: cause.message, cause }) }),
-              ),
-            )
-            const headers = yield* Auth.toEffect(
-              AuthOptions.bearer(input, ["AI_GATEWAY_API_KEY", "VERCEL_OIDC_TOKEN"]),
-            )({
-              request: req,
-              method: "POST",
-              url: url.toString(),
-              body,
-              headers: Headers.fromInput({ ...input.headers, ...req.http?.headers }),
-            })
-            const res = yield* send(
-              HttpClientRequest.post(url).pipe(
-                HttpClientRequest.setHeaders(headers),
-                HttpClientRequest.bodyText(body, "application/json"),
-              ),
-            )
-            const http = new HttpContext({ url: res.request.url, status: res.status, headers: res.headers })
-            const fail = (message: string, cause: unknown, body?: string) =>
-              new AIError({
-                reason: new InvalidProviderOutputError({
-                  route: "vercel-evaluation",
-                  message,
-                  body,
-                  http,
-                  cause,
-                }),
-              })
-            const text = yield* res.text.pipe(
-              Effect.mapError((cause) => fail("Failed to read the Vercel AI Gateway evaluation response", cause)),
-            )
-            const data = yield* Schema.decodeUnknownEffect(Schema.fromJsonString(Response))(text).pipe(
-              Effect.mapError((cause) =>
-                fail("Vercel AI Gateway returned an invalid evaluation response", cause, text),
-              ),
-            )
-            return new EvaluationResponse({
-              model: ModelID.make(data.model ?? req.model.id),
-              answers: data.answers,
-              usage: data.usage
-                ? new Usage({
-                    inputTokens: data.usage.inputTokens,
-                    outputTokens: data.usage.outputTokens,
-                    totalTokens:
-                      data.usage.inputTokens === undefined && data.usage.outputTokens === undefined
-                        ? undefined
-                        : (data.usage.inputTokens ?? 0) + (data.usage.outputTokens ?? 0),
-                    providerMetadata: { gateway: data.usage },
-                  })
-                : undefined,
-              rounding: data.rounding,
-              providerMetadata: data.providerMetadata,
-            })
-          }),
-      },
-    })
-  return { id, experimental: { evaluation }, configure }
-}
-
-export const provider = configure()
-export const experimental = provider.experimental
-
-export * as VercelAIGateway from "./vercel-ai-gateway.js"
@@ -1,12 +1,12 @@
 import type { LLMRequest } from "../schema/index.js"
 import * as ProviderShared from "../protocols/shared.js"

-export interface EndpointInput<Body, Request = LLMRequest> {
-  readonly request: Request
+export interface EndpointInput<Body> {
+  readonly request: LLMRequest
  readonly body: Body
 }

-export type EndpointPart<Body, Request = LLMRequest> = string | ((input: EndpointInput<Body, Request>) => string)
+export type EndpointPart<Body> = string | ((input: EndpointInput<Body>) => string)

 /**
 * Declarative URL construction for one route.
@@ -17,29 +17,26 @@ export type EndpointPart<Body, Request = LLMRequest> = string | ((input: Endpoin
 *
 * `path` may be a string or a function of `EndpointInput`, for routes whose
 * URL embeds the model id, region, or another body field (e.g. Bedrock,
- * Gemini). Media routes reuse the same shape with their own request type.
+ * Gemini).
 */
-export interface Definition<Body, Request = LLMRequest> {
+export interface Definition<Body> {
  readonly baseURL?: string
-  readonly path: EndpointPart<Body, Request>
+  readonly path: EndpointPart<Body>
  readonly query?: Record<string, string>
 }

-export type EndpointPatch<Body, Request = LLMRequest> = Partial<Definition<Body, Request>>
+export type EndpointPatch<Body> = Partial<Definition<Body>>

 /** Construct an `Endpoint` from a path string or path function. */
-export const path = <Body, Request = LLMRequest>(
-  value: EndpointPart<Body, Request>,
-  options: Omit<Definition<Body, Request>, "path"> = {},
-): Definition<Body, Request> => ({
+export const path = <Body>(
+  value: EndpointPart<Body>,
+  options: Omit<Definition<Body>, "path"> = {},
+): Definition<Body> => ({
  ...options,
  path: value,
 })

-export const merge = <Body, Request = LLMRequest>(
-  base: Definition<Body, Request>,
-  patch: EndpointPatch<Body, Request>,
-): Definition<Body, Request> => ({
+export const merge = <Body>(base: Definition<Body>, patch: EndpointPatch<Body>): Definition<Body> => ({
  ...base,
  ...patch,
  baseURL: patch.baseURL ?? base.baseURL,
@@ -47,13 +44,10 @@ export const merge = <Body, Request = LLMRequest>(
  query: patch.query === undefined ? base.query : { ...base.query, ...patch.query },
 })

-const renderPart = <Body, Request>(part: EndpointPart<Body, Request>, input: EndpointInput<Body, Request>) =>
+const renderPart = <Body>(part: EndpointPart<Body>, input: EndpointInput<Body>) =>
  typeof part === "function" ? part(input) : part

-export const render = <Body, Request = LLMRequest>(
-  endpoint: Definition<Body, Request>,
-  input: EndpointInput<Body, Request>,
-) => {
+export const render = <Body>(endpoint: Definition<Body>, input: EndpointInput<Body>) => {
  const url = new URL(`${ProviderShared.trimBaseUrl(endpoint.baseURL ?? "")}${renderPart(endpoint.path, input)}`)
  for (const [key, value] of Object.entries(endpoint.query ?? {})) url.searchParams.set(key, value)
  return url
@@ -1,22 +0,0 @@
-import { Context, type Effect } from "effect"
-import type { HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
-import type { AIError } from "../schema/errors.js"
-
-// The service tag lives in its own leaf module so `Media.Asset` (imported by the schema layer) can require the
-// executor without pulling the full executor implementation, and therefore the schema barrel, into a cycle.
-export interface Interface {
-  readonly execute: (
-    request: HttpClientRequest.HttpClientRequest,
-    middleware?: HttpMiddleware,
-  ) => Effect.Effect<HttpClientResponse.HttpClientResponse, AIError>
-}
-
-export type HttpHandler = (
-  request: HttpClientRequest.HttpClientRequest,
-) => Effect.Effect<HttpClientResponse.HttpClientResponse, Error>
-export type HttpMiddleware = (
-  request: HttpClientRequest.HttpClientRequest,
-  handler: HttpHandler,
-) => Effect.Effect<HttpClientResponse.HttpClientResponse, Error>
-
-export class Service extends Context.Service<Service, Interface>()("@opencode/AI/RequestExecutor") {}
@@ -1,4 +1,4 @@
-import { Cause, Effect, Layer, Option, Schema, Stream } from "effect"
+import { Cause, Context, Effect, Layer, Option, Schema, Stream } from "effect"
 import {
  FetchHttpClient,
  Headers,
@@ -9,10 +9,23 @@ import {
 } from "effect/unstable/http"
 import { HttpContext, HttpRateLimitDetails, AIError, TransportError } from "../schema/index.js"
 import { classifyProviderFailure } from "../provider-error.js"
-import { Service, type HttpMiddleware, type Interface } from "./executor-service.js"

-export { Service } from "./executor-service.js"
-export type { HttpHandler, HttpMiddleware, Interface } from "./executor-service.js"
+export interface Interface {
+  readonly execute: (
+    request: HttpClientRequest.HttpClientRequest,
+    middleware?: HttpMiddleware,
+  ) => Effect.Effect<HttpClientResponse.HttpClientResponse, AIError>
+}
+
+export type HttpHandler = (
+  request: HttpClientRequest.HttpClientRequest,
+) => Effect.Effect<HttpClientResponse.HttpClientResponse, Error>
+export type HttpMiddleware = (
+  request: HttpClientRequest.HttpClientRequest,
+  handler: HttpHandler,
+) => Effect.Effect<HttpClientResponse.HttpClientResponse, Error>
+
+export class Service extends Context.Service<Service, Interface>()("@opencode/AI/RequestExecutor") {}

 const headerDetails = (headers: Headers.Headers) =>
  Object.fromEntries(Object.entries(headers).map(([name, value]) => [name, String(value)]))
@@ -20,8 +20,6 @@ export * from "./executor.js"
 export { Auth } from "./auth.js"
 export { AuthOptions } from "./auth-options.js"
 export { Endpoint } from "./endpoint.js"
-export { MediaRoute } from "./media.js"
-export { MediaProtocol } from "./media-protocol.js"
 export { Framing } from "./framing.js"
 export { Protocol } from "./protocol.js"
 export { HttpTransport, WebSocketTransport } from "./transport/index.js"
@@ -1,95 +0,0 @@
-import { Effect, Schema } from "effect"
-import { HttpClientResponse } from "effect/unstable/http"
-import { AIError, HttpContext, InvalidProviderOutputError } from "../schema/index.js"
-
-// ---------------------------------------------------------------------------
-// Bodies
-// ---------------------------------------------------------------------------
-
-export type Body =
-  | { readonly type: "json"; readonly value: Record<string, unknown> }
-  | { readonly type: "multipart"; readonly value: FormData }
-
-export const json = (value: Record<string, unknown>): Body => ({ type: "json", value })
-export const multipart = (value: FormData): Body => ({ type: "multipart", value })
-
-// ---------------------------------------------------------------------------
-// Protocol kinds
-// ---------------------------------------------------------------------------
-
-export interface DecodeContext<Request> {
-  readonly request: Request
-  readonly body: Body
-}
-
-/** One request, one response. JSON or multipart in; JSON or raw bytes out. */
-export interface Inline<Request, Response> {
-  readonly kind: "inline"
-  readonly id: string
-  readonly name: string
-  /** Common request fields this protocol cannot lower; the route rejects them before `body.from` runs. */
-  readonly unsupported?: ReadonlyArray<keyof Request & string>
-  readonly body: { readonly from: (request: Request) => Effect.Effect<Body, AIError> }
-  readonly response: {
-    readonly decode: (
-      response: HttpClientResponse.HttpClientResponse,
-      context: DecodeContext<Request>,
-    ) => Effect.Effect<Response, AIError>
-  }
-}
-
-export const inline = <Request, Response>(
-  input: Omit<Inline<Request, Response>, "kind">,
-): Inline<Request, Response> => ({
-  kind: "inline",
-  ...input,
-})
-
-// ---------------------------------------------------------------------------
-// Response helpers
-// ---------------------------------------------------------------------------
-
-const context = (response: HttpClientResponse.HttpClientResponse) =>
-  new HttpContext({ url: response.request.url, status: response.status, headers: response.headers })
-
-/** Read a text body while retaining the original payload and HTTP context on every downstream error. */
-export const text = Effect.fn("MediaProtocol.text")(function* (
-  route: string,
-  name: string,
-  response: HttpClientResponse.HttpClientResponse,
-) {
-  const http = context(response)
-  const body = yield* response.text.pipe(
-    Effect.mapError(
-      (cause) =>
-        new AIError({
-          reason: new InvalidProviderOutputError({
-            route,
-            message: `Failed to read the ${name} response`,
-            http,
-            cause,
-          }),
-        }),
-    ),
-  )
-  return {
-    body,
-    http,
-    invalid: (message: string, cause?: unknown) =>
-      new AIError({ reason: new InvalidProviderOutputError({ route, message, body, http, cause }) }),
-  }
-})
-
-/** Read and Schema-decode a JSON body. Decode failures keep the raw body as `reason.body`. */
-export const decodeJson = <A>(route: string, name: string, schema: Schema.Codec<A, unknown>) => {
-  const decode = Schema.decodeUnknownEffect(Schema.fromJsonString(schema))
-  return Effect.fn("MediaProtocol.decodeJson")(function* (response: HttpClientResponse.HttpClientResponse) {
-    const output = yield* text(route, name, response)
-    const value = yield* decode(output.body).pipe(
-      Effect.mapError((cause) => output.invalid(`${name} returned an invalid response`, cause)),
-    )
-    return { ...output, value }
-  })
-}
-
-export * as MediaProtocol from "./media-protocol.js"
@@ -1,116 +0,0 @@
-import { Effect } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
-import { Auth } from "./auth.js"
-import { Endpoint } from "./endpoint.js"
-import type { Interface } from "./executor-service.js"
-import { MediaProtocol } from "./media-protocol.js"
-import { ProviderShared } from "../protocols/shared.js"
-import { AIError, HttpOptions, ProviderID, mergeHttpOptions } from "../schema/index.js"
-import { sanitizeSurrogates } from "../utils/sanitize.js"
-
-export type Execute = Interface["execute"]
-
-/** The minimum a media request must carry for the route to build a transport request. */
-export interface MediaRequest {
-  readonly model: { readonly id: string; readonly provider: ProviderID; readonly http?: HttpOptions }
-  readonly http?: HttpOptions
-}
-
-/** Deployment inputs every media model factory accepts; provider facades fill these from `configure(...)`. */
-export interface ModelInput {
-  readonly id: string
-  readonly auth: Auth.Definition
-  readonly baseURL?: string
-  readonly headers?: Record<string, string>
-  readonly http?: HttpOptions
-}
-
-// ---------------------------------------------------------------------------
-// Route
-// ---------------------------------------------------------------------------
-
-export interface Route<Request extends MediaRequest, Response> {
-  readonly id: string
-  readonly provider: ProviderID
-  readonly protocol: string
-  readonly generate: (request: Request, execute: Execute) => Effect.Effect<Response, AIError>
-}
-
-export interface MakeInput<Request extends MediaRequest, Response> {
-  readonly id: string
-  readonly provider: string | ProviderID
-  readonly protocol: MediaProtocol.Inline<Request, Response>
-  readonly endpoint: Endpoint.Definition<MediaProtocol.Body, Request>
-  readonly auth: Auth.Definition
-  /** Deployment headers applied before transport authentication. */
-  readonly headers?: Record<string, string>
-}
-
-/**
- * Compose an inline media protocol with an endpoint and auth into a runnable route. The route owns the transport
- * plumbing every media protocol would otherwise duplicate: option merging, surrogate sanitizing, unsupported-field rejection, URL and query
- * rendering, auth headers, JSON vs multipart encoding, and handing the response back to the protocol for decoding.
- */
-export const make = <Request extends MediaRequest, Response>(
-  input: MakeInput<Request, Response>,
-): Route<Request, Response> => {
-  const provider = ProviderID.make(input.provider)
-  const routeHttp = input.headers === undefined ? undefined : new HttpOptions({ headers: input.headers })
-  const authorize = Auth.toEffect(input.auth)
-  return {
-    id: input.id,
-    provider,
-    protocol: input.protocol.id,
-    generate: Effect.fn(`MediaRoute.generate`)(function* (request: Request, execute: Execute) {
-      yield* rejectUnsupported(input.id, provider, request, input.protocol.unsupported)
-      const http = mergeHttpOptions(routeHttp, request.model.http, request.http)
-      // Sanitize after merging so model-level overlays are covered; the model value is restored, not sanitized.
-      const resolved: Request = { ...sanitizeSurrogates({ ...request, http }), model: request.model }
-      const body = yield* input.protocol.body.from(resolved)
-      const url = Endpoint.render(input.endpoint, { request: resolved, body })
-      for (const [key, value] of Object.entries(http?.query ?? {})) url.searchParams.set(key, value)
-      const encoded = body.type === "json" ? ProviderShared.encodeJson(body.value) : "[multipart/form-data]"
-      const baseHeaders = Headers.fromInput(http?.headers)
-      const headers = yield* authorize({
-        request: resolved,
-        method: "POST",
-        url: url.toString(),
-        body: encoded,
-        // The HTTP client sets the multipart boundary; a caller-supplied content-type would corrupt it.
-        headers: body.type === "multipart" ? Headers.remove(baseHeaders, "content-type") : baseHeaders,
-      })
-      const transport = HttpClientRequest.post(url.toString()).pipe(
-        HttpClientRequest.setHeaders(headers),
-        body.type === "json"
-          ? HttpClientRequest.bodyText(encoded, "application/json")
-          : HttpClientRequest.bodyFormData(body.value),
-      )
-      const response = yield* execute(transport)
-      return yield* input.protocol.response.decode(response, { request: resolved, body })
-    }),
-  }
-}
-
-/** Common fields are never silently dropped: a present field the protocol declared unsupported fails typed. */
-const rejectUnsupported = <Request extends object>(
-  route: string,
-  provider: ProviderID,
-  request: Request,
-  unsupported: ReadonlyArray<keyof Request & string> | undefined,
-): Effect.Effect<void, AIError> => {
-  const present = (unsupported ?? []).filter((field) => {
-    const value = request[field]
-    return Array.isArray(value) ? value.length > 0 : value !== undefined
-  })
-  if (present.length === 0) return Effect.void
-  return Effect.fail(
-    ProviderShared.unsupportedOperation({
-      operation: `media.${present[0]}`,
-      provider,
-      route,
-      message: `${provider}/${route} does not support ${present.join(", ")}`,
-    }),
-  )
-}
-
-export * as MediaRoute from "./media.js"
@@ -133,12 +133,6 @@ export class UnknownProviderError extends Schema.TaggedError<UnknownProviderErro
  ReasonFields,
 ) {}

-/** A caller-supplied deadline elapsed, such as `Generation.await` polling past its `Poll.timeout`. */
-export class TimeoutError extends Schema.TaggedError<TimeoutError>("AI.Error.Timeout")("Timeout", {
-  ...ReasonFields,
-  timeoutMs: Schema.optional(Schema.Number),
-}) {}
-
 export const AIErrorReason = Schema.Union([
  InvalidRequestError,
  UnsupportedOperationError,
@@ -151,7 +145,6 @@ export const AIErrorReason = Schema.Union([
  TransportError,
  InvalidProviderOutputError,
  UnknownProviderError,
-  TimeoutError,
 ]).pipe(Schema.toTaggedUnion("_tag"))
 export type AIErrorReason = Schema.Schema.Type<typeof AIErrorReason>

@@ -4,18 +4,18 @@ import { ContentBlockID, ToolCallID } from "./ids.js"
 import {
  Message,
  CompactionPart,
+  ProviderMetadata,
  ToolCallPart,
  ToolOutput,
  ToolResultPart,
  ToolResultValue,
  type ContentPart,
 } from "./messages.js"
-import { ProviderMetadata } from "./options.js"
 import { ProviderFailureClassification } from "./errors.js"
-import { Media } from "../media.js"

 export const FinishReason = LLM.FinishReason
 export type FinishReason = Schema.Schema.Type<typeof FinishReason>
+export { ProviderMetadata } from "./messages.js"

 /**
 * Token usage reported by an LLM provider.
@@ -91,27 +91,6 @@ export class Usage extends Schema.Class<Usage>("AI.Usage")({

 export type UsageInput = Usage | ConstructorParameters<typeof Usage>[0]

-/**
- * Usage reported by media routes. Providers bill images, video, speech, and transcription in different units, so
- * each response carries the unit it was actually metered in instead of forcing everything into tokens.
- */
-export const MediaUsage = Schema.Union([
-  Schema.Struct({
-    type: Schema.Literal("tokens"),
-    input: Schema.optional(Schema.Number),
-    output: Schema.optional(Schema.Number),
-    total: Schema.optional(Schema.Number),
-    details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
-  }),
-  Schema.Struct({ type: Schema.Literal("seconds"), seconds: Schema.Number }),
-  Schema.Struct({ type: Schema.Literal("characters"), characters: Schema.Number }),
-  Schema.Struct({ type: Schema.Literal("credits"), credits: Schema.Number }),
-  Schema.Struct({ type: Schema.Literal("compute"), seconds: Schema.Number }),
-])
-  .pipe(Schema.toTaggedUnion("type"))
-  .annotate({ identifier: "AI.MediaUsage" })
-export type MediaUsage = Schema.Schema.Type<typeof MediaUsage>
-
 /** A replacement context window, not an assistant message to append to prior history. */
 export class CompactionResponse extends Schema.Class<CompactionResponse>("LLM.CompactionResponse")({
  replacement: Schema.Array(Message),
@@ -284,14 +263,6 @@ export const Finish = Schema.Struct({
 }).annotate({ identifier: "LLM.Event.Finish" })
 export type Finish = Schema.Schema.Type<typeof Finish>

-/** A generated media asset (image, audio, …) emitted by the model as first-class output rather than a tool result. */
-export const MediaEvent = Schema.Struct({
-  type: Schema.tag("media"),
-  media: Media.AssetSchema,
-  providerMetadata: Schema.optional(ProviderMetadata),
-}).annotate({ identifier: "LLM.Event.Media" })
-export type MediaEvent = Schema.Schema.Type<typeof MediaEvent>
-
 export const ProviderErrorEvent = Schema.Struct({
  type: Schema.tag("provider-error"),
  message: Schema.String,
@@ -316,7 +287,6 @@ const llmEventTagged = Schema.Union([
  ToolCall,
  ToolResult,
  ToolError,
-  MediaEvent,
  StepFinish,
  Finish,
  ProviderErrorEvent,
@@ -362,7 +332,6 @@ export const LLMEvent = Object.assign(llmEventTagged, {
      output: input.output === undefined ? undefined : ToolOutput.make(input.output.structured, input.output.content),
    }),
  toolError: (input: WithID<ToolError, ToolCallID>) => ToolError.make({ ...input, id: toolCallID(input.id) }),
-  media: MediaEvent.make,
  stepFinish: (input: WithUsage<StepFinish>) =>
    StepFinish.make({
      ...input,
@@ -390,7 +359,6 @@ export const LLMEvent = Object.assign(llmEventTagged, {
    toolCall: llmEventTagged.guards["tool-call"],
    toolResult: llmEventTagged.guards["tool-result"],
    toolError: llmEventTagged.guards["tool-error"],
-    media: llmEventTagged.guards.media,
    stepFinish: llmEventTagged.guards["step-finish"],
    finish: llmEventTagged.guards.finish,
    providerError: llmEventTagged.guards["provider-error"],
@@ -666,13 +634,6 @@ const reduceResponseState = (state: ResponseState, event: LLMEvent): ResponseSta
      return reduceToolCall(next, event)
    case "tool-result":
      return appendContent(next, toolResultContent(event))
-    case "media":
-      return appendContent(
-        next,
-        event.providerMetadata === undefined
-          ? { type: "media", media: event.media }
-          : { type: "media", media: event.media, providerMetadata: event.providerMetadata },
-      )
    default:
      return next
  }
@@ -8,16 +8,19 @@ import {
  JsonSchema,
  LanguageModelSchema,
  type LanguageModel,
-  ProviderMetadata,
  ProviderOptions,
  ReasoningEffort,
 } from "./options.js"
 import { ProviderID } from "./ids.js"
-import { Media } from "../media.js"

 export const MessageRole = Schema.Literals(["system", "user", "assistant", "tool"])
 export type MessageRole = Schema.Schema.Type<typeof MessageRole>

+export const ProviderMetadata = Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown)).annotate({
+  identifier: "LLM.ProviderMetadata",
+})
+export type ProviderMetadata = Schema.Schema.Type<typeof ProviderMetadata>
+
 const systemPartSchema = Schema.Struct({
  type: Schema.Literal("text"),
  text: Schema.String,
@@ -47,7 +50,8 @@ export type TextPart = Schema.Schema.Type<typeof TextPart>

 export const MediaPart = Schema.Struct({
  type: Schema.Literal("media"),
-  media: Media.AssetSchema,
+  mediaType: Schema.String,
+  data: Schema.Union([Schema.String, Schema.Uint8Array]),
  filename: Schema.optional(Schema.String),
  cache: Schema.optional(CacheHint),
  metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
@@ -251,12 +255,6 @@ export namespace Message {

  export const text = (value: string): ContentPart => ({ type: "text", text: value })

-  export const media = (asset: Media.Asset, options?: Omit<MediaPart, "type" | "media">): MediaPart => ({
-    type: "media",
-    media: asset,
-    ...options,
-  })
-
  export const content = (input: ContentInput) =>
    typeof input === "string" ? [text(input)] : Array.isArray(input) ? [...input] : [input]

@@ -39,11 +39,6 @@ const mergeStringRecords = (
 export const ProviderOptions = Schema.Record(Schema.String, Schema.Unknown)
 export type ProviderOptions = Schema.Schema.Type<typeof ProviderOptions>

-export const ProviderMetadata = Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown)).annotate({
-  identifier: "LLM.ProviderMetadata",
-})
-export type ProviderMetadata = Schema.Schema.Type<typeof ProviderMetadata>
-
 export const mergeProviderOptions = (
  ...items: ReadonlyArray<ProviderOptions | undefined>
 ): ProviderOptions | undefined => mergeJsonRecords(...items)
@@ -1,46 +0,0 @@
-const ascii = (bytes: Uint8Array, start: number, end: number) => String.fromCharCode(...bytes.subarray(start, end))
-
-const startsWith = (bytes: Uint8Array, prefix: ReadonlyArray<number>) =>
-  bytes.length >= prefix.length && prefix.every((value, index) => bytes[index] === value)
-
-/**
- * Sniff a media type from leading magic bytes. Covers the containers media routes commonly return; anything else is
- * `undefined` so callers can fall back to a provider-declared type or `application/octet-stream`.
- */
-export const detectMediaType = (bytes: Uint8Array): string | undefined => {
-  if (startsWith(bytes, [0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a])) return "image/png"
-  if (startsWith(bytes, [0xff, 0xd8, 0xff])) return "image/jpeg"
-  if (startsWith(bytes, [0x47, 0x49, 0x46, 0x38])) return "image/gif"
-  if (bytes.length >= 12 && ascii(bytes, 0, 4) === "RIFF") {
-    const riffType = ascii(bytes, 8, 12)
-    if (riffType === "WEBP") return "image/webp"
-    if (riffType === "WAVE") return "audio/wav"
-  }
-  if (startsWith(bytes, [0x25, 0x50, 0x44, 0x46])) return "application/pdf"
-  if (bytes.length >= 12 && ascii(bytes, 4, 8) === "ftyp") return "video/mp4"
-  if (startsWith(bytes, [0x1a, 0x45, 0xdf, 0xa3])) return "video/webm"
-  if (startsWith(bytes, [0x49, 0x44, 0x33]) || startsWith(bytes, [0xff, 0xfb]) || startsWith(bytes, [0xff, 0xf3]))
-    return "audio/mpeg"
-  if (startsWith(bytes, [0x4f, 0x67, 0x67, 0x53])) return "audio/ogg"
-  return undefined
-}
-
-const EXTENSIONS: Readonly<Record<string, string>> = {
-  png: "image/png",
-  jpg: "image/jpeg",
-  jpeg: "image/jpeg",
-  gif: "image/gif",
-  webp: "image/webp",
-  pdf: "application/pdf",
-  mp4: "video/mp4",
-  webm: "video/webm",
-  mp3: "audio/mpeg",
-  wav: "audio/wav",
-  ogg: "audio/ogg",
-  txt: "text/plain",
-  md: "text/markdown",
-  csv: "text/csv",
-}
-
-export const extensionMediaType = (path: string): string | undefined =>
-  EXTENSIONS[path.slice(path.lastIndexOf(".") + 1).toLowerCase()]
@@ -1,11 +1,9 @@
-import { Media } from "../media.js"
 import { isRecord } from "./record.js"

 export const sanitizeSurrogates = <T>(value: T): T => {
  if (typeof value === "string") return value.toWellFormed() as T
  if (Array.isArray(value)) return value.map(sanitizeSurrogates) as T
-  // Media assets carry binary or base64 payloads and a lazy byte cache; flattening them into a record would drop both.
-  if (value instanceof Uint8Array || value instanceof Error || value instanceof Media.Asset) return value
+  if (value instanceof Uint8Array || value instanceof Error) return value
  if (isRecord(value))
    return Object.fromEntries(
      Object.entries(value).map(([key, entry]) => [key.toWellFormed(), sanitizeSurrogates(entry)]),
@@ -87,9 +87,9 @@ testEffect(fixedResponse("")).effect(
        prompt: "hello",
      })
      expect(LLMClient.canCompact(request)).toBe(false)
-      const error = yield* LLMClient.compact(request as unknown as Parameters<typeof LLMClient.compact>[0]).pipe(
-        Effect.flip,
-      )
+      const error = yield* LLMClient.compact(
+        request as unknown as Parameters<typeof LLMClient.compact>[0],
+      ).pipe(Effect.flip)
      expect(error.reason._tag).toBe("UnsupportedOperation")
      expect(error.message).toContain("does not support explicit compaction")
      if (error.reason._tag === "UnsupportedOperation") {
@@ -1,6 +1,5 @@
 import {
  LLM,
-  Media,
  Message,
  ToolCallPart,
  ToolDefinition,
@@ -60,7 +59,7 @@ export function continuationRequest(input: {

  if (features.has("user-text")) firstUser.push({ type: "text", text: "What is shown here?" })
  if (features.has("user-image"))
-    firstUser.push({ type: "media", media: Media.base64(input.image ?? "AAECAw==", "image/png") })
+    firstUser.push({ type: "media", mediaType: "image/png", data: input.image ?? "AAECAw==" })
  if (firstUser.length > 0) messages.push(Message.user(firstUser))

  if (features.has("assistant-reasoning"))
@@ -1,302 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { Evaluation, EvaluationClient } from "../src/experimental.js"
-import { OpenCodeZen, OpenRouter, TypeSafeAI, VercelAIGateway } from "../src/providers.js"
-import { it } from "./lib/effect.js"
-import { dynamicResponse } from "./lib/http.js"
-
-describe("experimental Evaluation", () => {
-  it.effect("evaluates typed questions through System One", () =>
-    Effect.gen(function* () {
-      const response = yield* Evaluation.run({
-        model: TypeSafeAI.configure({
-          apiKey: "test",
-          baseURL: "https://typesafe.test/v1/",
-          headers: { "x-default": "yes" },
-          http: { body: { deployment: "test" }, query: { api: "v1" } },
-        }).experimental.evaluation("jev-latest"),
-        state: { ticket: "Please refund the duplicate charge." },
-        questions: {
-          department: {
-            type: "choice",
-            instructions: "Which team should handle this?",
-            criteria: { billing: "Payments and refunds", technical: "Bugs and outages" },
-          },
-          urgency: {
-            type: "score",
-            instructions: "How urgent is this?",
-            criteria: ["Can wait", "Needs attention", "Blocking"],
-          },
-          refund: { type: "boolean", instructions: "Is the customer asking for a refund?" },
-        },
-        options: { trace: { enabled: true } },
-        http: { body: { request_metadata: "value" }, headers: { "x-request": "yes" }, query: { trace: "1" } },
-      })
-
-      expect(response.model).toBe("jev-1.13.0")
-      expect(response.answers.department).toEqual({
-        type: "choice",
-        choice: "billing",
-        probabilities: { billing: 0.9, technical: 0.1 },
-      })
-      expect(response.answers.urgency).toEqual({
-        type: "score",
-        score: 1.2,
-        probabilities: { "0": 0, "1": 0.8, "2": 0.2 },
-      })
-      expect(response.answers.refund).toEqual({ type: "boolean", probability: 0.97 })
-      expect(response.usage?.totalTokens).toBe(36)
-      expect(response.providerMetadata).toEqual({
-        typesafe: {
-          confidence: { department: 0.8, urgency: 0.6 },
-          legend: { urgency: { "0": "Can wait", "1": "Needs attention", "2": "Blocking" } },
-        },
-      })
-    }).pipe(
-      Effect.provide(
-        EvaluationClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.url).toBe("https://typesafe.test/v1/systemone?api=v1&trace=1")
-                expect(request.headers.get("authorization")).toBe("Bearer test")
-                expect(request.headers.get("x-default")).toBe("yes")
-                expect(request.headers.get("x-request")).toBe("yes")
-                expect(JSON.parse(input.text)).toEqual({
-                  deployment: "test",
-                  request_metadata: "value",
-                  trace: { enabled: true },
-                  model: "jev-latest",
-                  state: { ticket: "Please refund the duplicate charge." },
-                  questions: {
-                    department: {
-                      type: "choice",
-                      instructions: "Which team should handle this?",
-                      criteria: { billing: "Payments and refunds", technical: "Bugs and outages" },
-                    },
-                    urgency: {
-                      type: "score",
-                      instructions: "How urgent is this?",
-                      criteria: ["Can wait", "Needs attention", "Blocking"],
-                    },
-                    refund: { type: "noul", instructions: "Is the customer asking for a refund?" },
-                  },
-                })
-                return input.respond(
-                  JSON.stringify({
-                    model: "jev-1.13.0",
-                    answers: {
-                      department: {
-                        type: "choice",
-                        choice: "billing",
-                        probabilities: { billing: 0.9, technical: 0.1 },
-                        confidence: 0.8,
-                      },
-                      urgency: {
-                        type: "score",
-                        score: 1.2,
-                        probabilities: { "0": 0, "1": 0.8, "2": 0.2 },
-                        legend: { "0": "Can wait", "1": "Needs attention", "2": "Blocking" },
-                        confidence: 0.6,
-                      },
-                      refund: { type: "noul", noul: 0.97 },
-                    },
-                    usage: { input_tokens: 30, output_tokens: 6 },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                )
-              }),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("configures the OpenCode Zen System One endpoint", () =>
-    Evaluation.run({
-      model: OpenCodeZen.configure({ apiKey: "zen-key", baseURL: "https://zen.test/v1" }).experimental.evaluation(
-        "jev-1.13",
-      ),
-      state: "hello",
-      questions: { greeting: { type: "boolean", instructions: "Is this a greeting?" } },
-    }).pipe(
-      Effect.tap((response) =>
-        Effect.sync(() => {
-          expect(response.answers.greeting.probability).toBe(0.99)
-          expect(response.usage?.providerMetadata).toEqual({
-            opencode: { input_tokens: 10, output_tokens: 2 },
-          })
-        }),
-      ),
-      Effect.provide(
-        EvaluationClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(input.request.url).toBe("https://zen.test/v1/systemone")
-              expect(input.request.headers.authorization).toBe("Bearer zen-key")
-              return Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    model: "jev-1.13.0",
-                    answers: { greeting: { type: "noul", noul: 0.99 } },
-                    usage: { input_tokens: 10, output_tokens: 2 },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("evaluates through OpenRouter System One", () =>
-    Evaluation.run({
-      model: OpenRouter.configure({
-        apiKey: "openrouter-key",
-        baseURL: "https://openrouter.test/api/v1",
-      }).experimental.evaluation("typesafe/jev-1.13"),
-      state: "refund",
-      questions: { refund: { type: "boolean", instructions: "Is a refund requested?" } },
-      options: { user: "user-1", session_id: "session-1" },
-    }).pipe(
-      Effect.tap((response) =>
-        Effect.sync(() => {
-          expect(response.answers.refund.probability).toBe(0.98)
-          expect(response.providerMetadata?.openrouter).toMatchObject({ responseId: "gen-1", provider: "TypeSafe" })
-          expect(response.usage?.providerMetadata?.openrouter).toEqual({
-            input_tokens: 10,
-            output_tokens: 2,
-            cost: 0.0001,
-          })
-        }),
-      ),
-      Effect.provide(
-        EvaluationClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(input.request.url).toBe("https://openrouter.test/api/v1/systemone")
-              expect(input.request.headers.authorization).toBe("Bearer openrouter-key")
-              expect(JSON.parse(input.text)).toMatchObject({
-                model: "typesafe/jev-1.13",
-                user: "user-1",
-                session_id: "session-1",
-                questions: { refund: { type: "noul" } },
-              })
-              return Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    id: "gen-1",
-                    model: "typesafe/jev-1.13-20260917",
-                    provider: "TypeSafe",
-                    answers: { refund: { type: "noul", noul: 0.98 } },
-                    usage: { input_tokens: 10, output_tokens: 2, cost: 0.0001 },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("evaluates through Vercel AI Gateway", () =>
-    Evaluation.run({
-      model: VercelAIGateway.configure({
-        apiKey: "gateway-key",
-        baseURL: "https://gateway.test/v1/",
-      }).experimental.evaluation("typesafe-ai/jev"),
-      state: "refund",
-      questions: { refund: { type: "boolean", instructions: "Is a refund requested?" } },
-      options: { gateway: { zeroDataRetention: true, only: ["typesafe-ai"] } },
-    }).pipe(
-      Effect.tap((response) =>
-        Effect.sync(() => {
-          expect(response.answers.refund.probability).toBe(0.98)
-          expect(response.usage?.totalTokens).toBe(12)
-          expect(response.providerMetadata?.gateway).toMatchObject({ generationId: "gen-1", cost: "0.0001" })
-        }),
-      ),
-      Effect.provide(
-        EvaluationClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(input.request.url).toBe("https://gateway.test/v1/evaluate")
-              expect(input.request.headers.authorization).toBe("Bearer gateway-key")
-              expect(JSON.parse(input.text)).toEqual({
-                model: "typesafe-ai/jev",
-                state: "refund",
-                questions: { refund: { type: "boolean", instructions: "Is a refund requested?" } },
-                providerOptions: { gateway: { zeroDataRetention: true, only: ["typesafe-ai"] } },
-              })
-              return Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    model: "typesafe-ai/jev",
-                    answers: { refund: { type: "boolean", probability: 0.98 } },
-                    usage: { inputTokens: 10, outputTokens: 2 },
-                    providerMetadata: { gateway: { generationId: "gen-1", cost: "0.0001" } },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("rejects answers that do not match their questions", () =>
-    Evaluation.run({
-      model: VercelAIGateway.configure({
-        apiKey: "gateway-key",
-        baseURL: "https://gateway.test/v1",
-      }).experimental.evaluation("typesafe-ai/jev"),
-      state: "refund",
-      questions: { refund: { type: "boolean", instructions: "Is a refund requested?" } },
-    }).pipe(
-      Effect.flip,
-      Effect.tap((error) => Effect.sync(() => expect(error.reason._tag).toBe("InvalidProviderOutput"))),
-      Effect.provide(
-        EvaluationClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    answers: { refund: { type: "choice", choice: "yes", probabilities: { yes: 1 } } },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              ),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("rejects malformed questions before network I/O", () =>
-    Effect.gen(function* () {
-      const error = yield* Evaluation.run({
-        model: TypeSafeAI.experimental.evaluation("jev-latest"),
-        state: "hello",
-        questions: { score: { type: "score", instructions: "How much?", criteria: ["only"] } },
-      }).pipe(Effect.flip)
-      expect(error.reason._tag).toBe("InvalidRequest")
-    }).pipe(
-      Effect.provide(
-        EvaluationClient.layer.pipe(
-          Layer.provide(dynamicResponse(() => Effect.die("invalid evaluation reached the network"))),
-        ),
-      ),
-    ),
-  )
-})
@@ -1,88 +0,0 @@
-import { Effect } from "effect"
-import { Evaluation, EvaluationClient, EvaluationModel, type EvaluationRoute } from "../src/experimental.js"
-import type { Service } from "../src/experimental/evaluation-client.js"
-import { OpenCodeZen, OpenRouter, TypeSafeAI, VercelAIGateway } from "../src/providers.js"
-
-type Requirements<T> = T extends Effect.Effect<infer _A, infer _E, infer R> ? R : never
-type Success<T> = T extends Effect.Effect<infer A, infer _E, infer _R> ? A : never
-type Equal<A, B> = [A, B] extends [B, A] ? true : false
-type Assert<T extends true> = T
-
-const model = TypeSafeAI.configure({ apiKey: "test" }).experimental.evaluation("jev-latest")
-const request = Evaluation.request({
-  model,
-  state: { ticket: "refund" },
-  questions: {
-    topic: {
-      type: "choice",
-      instructions: "Which team?",
-      criteria: { billing: null, support: { includes: ["help"] } },
-    },
-    severity: { type: "score", instructions: "How severe?", criteria: ["Low", "High"] },
-    refund: { type: "boolean", instructions: "Refund?" },
-  },
-})
-
-const result = EvaluationClient.evaluate(request)
-type Result = Success<typeof result>
-type Choice = Assert<Equal<Result["answers"]["topic"]["choice"], "billing" | "support">>
-type ClientRequirements = Assert<Equal<Requirements<typeof result>, Service>>
-void (true satisfies Choice)
-void (true satisfies ClientRequirements)
-
-Effect.gen(function* () {
-  const response = yield* Evaluation.run({
-    model: OpenCodeZen.experimental.evaluation("jev-1.13"),
-    state: ["hello"],
-    questions: { greeting: { type: "boolean", instructions: "Greeting?" } },
-  })
-  response.answers.greeting.probability satisfies number
-  // @ts-expect-error Boolean answers do not contain a selected choice.
-  response.answers.greeting.choice
-  // @ts-expect-error Unknown question IDs are not exposed.
-  response.answers.missing
-})
-
-declare const route: EvaluationRoute<{ readonly temperature?: number }>
-const custom = EvaluationModel.make({ id: "custom", provider: "custom", route })
-Evaluation.run({
-  model: custom,
-  state: "hello",
-  questions: { ok: { type: "boolean", instructions: "OK?" } },
-  options: { temperature: 0.5 },
-})
-// @ts-expect-error Selected evaluation models retain their request option types.
-Evaluation.run({
-  model: custom,
-  state: "hello",
-  questions: { ok: { type: "boolean", instructions: "OK?" } },
-  options: { temperature: "high" },
-})
-
-Evaluation.run({
-  model: OpenRouter.experimental.evaluation("typesafe/jev-1.13"),
-  state: "hello",
-  questions: { ok: { type: "boolean", instructions: "OK?" } },
-  options: { provider: { zdr: true }, session_id: "session-1", user: "user-1" },
-})
-// @ts-expect-error OpenRouter session IDs are strings.
-Evaluation.run({
-  model: OpenRouter.experimental.evaluation("typesafe/jev-1.13"),
-  state: "hello",
-  questions: { ok: { type: "boolean", instructions: "OK?" } },
-  options: { session_id: 1 },
-})
-
-Evaluation.run({
-  model: VercelAIGateway.experimental.evaluation("typesafe-ai/jev"),
-  state: "hello",
-  questions: { ok: { type: "boolean", instructions: "OK?" } },
-  options: { gateway: { zeroDataRetention: true, only: ["typesafe-ai"] } },
-})
-// @ts-expect-error Vercel zero-data-retention controls are boolean.
-Evaluation.run({
-  model: VercelAIGateway.experimental.evaluation("typesafe-ai/jev"),
-  state: "hello",
-  questions: { ok: { type: "boolean", instructions: "OK?" } },
-  options: { gateway: { zeroDataRetention: "yes" } },
-})
@@ -1,5 +1,5 @@
 import { describe, expect, test } from "bun:test"
-import { AIError, LanguageModel, LLM, LLMClient, Media, Provider } from "@opencode/ai"
+import { AIError, ImageInput, LanguageModel, LLM, LLMClient, Provider } from "@opencode/ai"
 import { Route, Protocol, WebSocketTransport } from "@opencode/ai/route"
 import { Provider as ProviderSubpath } from "@opencode/ai/provider"
 import {
@@ -8,12 +8,9 @@ import {
  CloudflareWorkersAI,
  DeepSeek,
  Fireworks,
-  OpenCodeZen,
  OpenAI,
  OpenAICompatible,
  OpenRouter,
-  TypeSafeAI,
-  VercelAIGateway,
  XAI,
 } from "@opencode/ai/providers"
 import {
@@ -26,7 +23,6 @@ import {
 } from "@opencode/ai/protocols"
 import * as AnthropicMessages from "@opencode/ai/protocols/anthropic-messages"
 import { TestLLM } from "@opencode/ai/testing"
-import { Evaluation, EvaluationClient } from "@opencode/ai/experimental"

 describe("public exports", () => {
  test("root exposes app-facing runtime APIs", () => {
@@ -35,15 +31,12 @@ describe("public exports", () => {
    expect(LLMClient.layer).toBeDefined()
    expect(AIError).toBeFunction()
    expect(LanguageModel.make).toBeFunction()
-    expect(Media.bytes).toBeFunction()
+    expect(ImageInput.bytes).toBeFunction()
    expect(Provider.make).toBeFunction()
    expect(ProviderSubpath.make).toBe(Provider.make)
    expect(TestLLM.layer).toBeFunction()
    expect(TestLLM.testLayer).toBeFunction()
    expect(TestLLM.Test.of).toBeFunction()
-    expect(Evaluation.run).toBeFunction()
-    expect(EvaluationClient.layer).toBeDefined()
-    expect(EvaluationClient.fetchLayer).toBeDefined()
  })

  test("route barrel exposes route-authoring APIs", () => {
@@ -73,10 +66,6 @@ describe("public exports", () => {
    expect(CloudflareWorkersAI.configure).toBeFunction()
    expect(CloudflareWorkersAI.configure({ accountId: "fixture", apiKey: "fixture" }).model).toBeFunction()
    expect(OpenRouter.model).toBeFunction()
-    expect(OpenRouter.experimental.evaluation).toBeFunction()
-    expect(TypeSafeAI.experimental.evaluation).toBeFunction()
-    expect(OpenCodeZen.experimental.evaluation).toBeFunction()
-    expect(VercelAIGateway.experimental.evaluation).toBeFunction()
    expect(XAI.model).toBeFunction()
    expect(XAI.provider.responses).toBe(XAI.responses)
    expect(XAI.provider.chat).toBe(XAI.chat)
@@ -1,13 +1,9 @@
 {
  "version": 1,
  "metadata": {
-    "tags": [
-      "prefix:google-vertex",
-      "provider:google-vertex",
-      "protocol:gemini"
-    ],
+    "tags": ["prefix:google-vertex", "provider:google-vertex", "protocol:gemini"],
    "name": "google-vertex/calls-a-tool",
-    "recordedAt": "2026-09-22T03:46:29.725Z"
+    "recordedAt": "2026-08-23T17:21:51.036Z"
  },
  "interactions": [
    {
@@ -25,7 +21,7 @@
        "headers": {
          "content-type": "text/event-stream"
        },
-        "body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"functionCall\": {\"name\": \"lookup_weather\",\"args\": {\"city\": \"Paris\"},\"id\": \"call_28936\"},\"thoughtSignature\": \"AY89a1/MVeBxtwu9l/96clFobOrrd7Q5MTf5o8/A22fc++1EsFYVeCFx9WCGmJ+D3yW3FWlRXKtJECYfprSoxixCSOYBNiV9g8/IkejbAxF26k1vxTsHkoqts0O2s8GqqBSRAavJfKQ/taTRbPuIq+b+RKZ8SDJFoWDnFjXpdS5S164uJTjmgs4ALd8oB1oQRycMsTbAY51TmkcNUnhARpjKQfqiizz4KfSRFjx7xDnza0v4jj73m2GV86eLDhVT7trIT+Dl5DsJt6RBLOE2Amse54mcpIbsYaANlY1YDU6FKuUBqnuwpl0OfhMXwWuYMogv1tH/0rTXsqNwmHyt/b9ZZXqYCdFXpMGt8udmoZ0d\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:28.953809Z\",\"responseId\": \"FPqxatGbOsSorb8PtY2z8Q4\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 39,\"candidatesTokenCount\": 16,\"totalTokenCount\": 93,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 39}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 16}],\"thoughtsTokenCount\": 38},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:28.953809Z\",\"responseId\": \"FPqxatGbOsSorb8PtY2z8Q4\"}\r\n\r\n"
+        "body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"functionCall\": {\"name\": \"lookup_weather\",\"args\": {\"city\": \"Paris\"},\"id\": \"call_425130\"},\"thoughtSignature\": \"AY89a1+1fXnLgYhHMuN3Ak6LBhT6PcrYOW7iPav4LfsacvG/Z6l1yJ+AsU7vWhFj/JyPIbsJJQ+GjohM9sCIZ6nqUOIg3reo/7osmrCvFrVHedTHQcwiPzoz2Kp3gb+uWjFAXxk1EX4IRAKcu0ox1W/Z9PpuZvHkTerGO2a82e02N6MAF1YhhtbXFvSdqLRih2Os68rdOk5/Bcld7ol8qUgeyIZ3CtI3OJ5jwRcD8LjvK33A7ZFzH5Bxp/peUmXvqnu5iNhnGBxZaJy/vupCtxRZxjaS+ojG0/UhyrnRiKIpbzQ0FBkxePPn8GCX/LOe2y3GUc98co8lN8OOuCd9ZmEdx5AjHmQkPO9fAV9SxG6Bda6SDWVL8o/Uz3WSQYoUEfAdoajEWIBvcisoeCJjb7zgmRRZ9VQSPl3RXj5LFRvX8jn0YKV1CahYbc24jA==\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:50.308576Z\",\"responseId\": \"LiyLauDqErCErb8Pj8aWkAs\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 39,\"candidatesTokenCount\": 16,\"totalTokenCount\": 102,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 39}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 16}],\"thoughtsTokenCount\": 47},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:50.308576Z\",\"responseId\": \"LiyLauDqErCErb8Pj8aWkAs\"}\r\n\r\n"
      }
    }
  ]
@@ -1,13 +1,9 @@
 {
  "version": 1,
  "metadata": {
-    "tags": [
-      "prefix:google-vertex",
-      "provider:google-vertex",
-      "protocol:gemini"
-    ],
+    "tags": ["prefix:google-vertex", "provider:google-vertex", "protocol:gemini"],
    "name": "google-vertex/continues-after-a-tool-result",
-    "recordedAt": "2026-09-22T03:46:30.691Z"
+    "recordedAt": "2026-08-23T17:21:51.853Z"
  },
  "interactions": [
    {
@@ -18,14 +14,14 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"model\",\"parts\":[{\"functionCall\":{\"id\":\"call_paris_1\",\"name\":\"lookup_weather\",\"args\":{\"city\":\"Paris\"}},\"thoughtSignature\":\"skip_thought_signature_validator\"}]},{\"role\":\"user\",\"parts\":[{\"functionResponse\":{\"id\":\"call_paris_1\",\"name\":\"lookup_weather\",\"response\":{\"name\":\"lookup_weather\",\"content\":\"18C, light rain\"}}}]}],\"tools\":[{\"functionDeclarations\":[{\"name\":\"lookup_weather\",\"description\":\"Look up the current weather for a city\",\"parameters\":{\"required\":[\"city\"],\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}}}}]}]}"
+        "body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"model\",\"parts\":[{\"functionCall\":{\"name\":\"lookup_weather\",\"args\":{\"city\":\"Paris\"}},\"thoughtSignature\":\"skip_thought_signature_validator\"}]},{\"role\":\"user\",\"parts\":[{\"functionResponse\":{\"name\":\"lookup_weather\",\"response\":{\"name\":\"lookup_weather\",\"content\":\"18C, light rain\"}}}]}],\"tools\":[{\"functionDeclarations\":[{\"name\":\"lookup_weather\",\"description\":\"Look up the current weather for a city\",\"parameters\":{\"required\":[\"city\"],\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}}}}]}]}"
      },
      "response": {
        "status": 200,
        "headers": {
          "content-type": "text/event-stream"
        },
-        "body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"The weather\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:29.830958Z\",\"responseId\": \"Ffqxau7bMoCOrb8P_Iu5sA0\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \" in Paris is currently 18°C with light rain.\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:29.830958Z\",\"responseId\": \"Ffqxau7bMoCOrb8P_Iu5sA0\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"AY89a18aVI8Uxr2VaOI822u0DyuQdy4B00uhLnjqYb5Qb6Mkscccm018knLtYThB5UX8dRv1VFsORSQ0Qo6Gx9RCng2AK9EPce7p\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 59,\"candidatesTokenCount\": 15,\"totalTokenCount\": 74,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 59}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 15}]},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:29.830958Z\",\"responseId\": \"Ffqxau7bMoCOrb8P_Iu5sA0\"}\r\n\r\n"
+        "body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"The weather in Paris is currently 18°C with light rain.\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:51.220919Z\",\"responseId\": \"LyyLave9DbWnrb8P1IjLmQQ\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"AY89a197c+fpHJftPtcufnqMAyoRQKVEQK+KeG+RVHVx2wKil3L4jP4YWvfVbcuOFr2jio4Kre/hCrDANAoMFSvaZrdaPeo1b5bXQSmJKMH03yM5M6q6ME6JiBvXym143U4exIde4UbOh2tMeyXMvB3aWxcavIHd78g5G5QPLreo6A3LO5871cYYVeRwteY+/zbEdqfaAq1hlk6WYpWkNljYpjMyKwr15YC8rFLh3HYayS9tTN++GGrk/reZn6C3OEPlzPou/pXRATzcEAGVl/TW\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 59,\"candidatesTokenCount\": 15,\"totalTokenCount\": 98,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 59}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 15}],\"thoughtsTokenCount\": 24},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:51.220919Z\",\"responseId\": \"LyyLave9DbWnrb8P1IjLmQQ\"}\r\n\r\n"
      }
    }
  ]
@@ -1,13 +1,9 @@
 {
  "version": 1,
  "metadata": {
-    "tags": [
-      "prefix:google-vertex",
-      "provider:google-vertex",
-      "protocol:gemini"
-    ],
+    "tags": ["prefix:google-vertex", "provider:google-vertex", "protocol:gemini"],
    "name": "google-vertex/streams-text",
-    "recordedAt": "2026-09-22T03:46:28.840Z"
+    "recordedAt": "2026-08-23T17:21:50.112Z"
  },
  "interactions": [
    {
@@ -25,7 +21,7 @@
        "headers": {
          "content-type": "text/event-stream"
        },
-        "body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"Hello\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:26.748531Z\",\"responseId\": \"EvqxavPXLbqerb8P1eSViQs\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"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\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 7,\"candidatesTokenCount\": 1,\"totalTokenCount\": 285,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 7}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 1}],\"thoughtsTokenCount\": 277},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-09-22T03:46:26.748531Z\",\"responseId\": \"EvqxavPXLbqerb8P1eSViQs\"}\r\n\r\n"
+        "body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"Hello\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:48.528714Z\",\"responseId\": \"LCyLasqiIO6crb8P1sDboQc\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"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\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 7,\"candidatesTokenCount\": 1,\"totalTokenCount\": 150,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 7}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 1}],\"thoughtsTokenCount\": 142},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:48.528714Z\",\"responseId\": \"LCyLasqiIO6crb8P1sDboQc\"}\r\n\r\n"
      }
    }
  ]
@@ -1,33 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "jev-1.13-free",
-    "tags": [
-      "prefix:opencode-zen-evaluation",
-      "provider:opencode",
-      "protocol:system-one"
-    ],
-    "name": "opencode-zen-evaluation/evaluates-choice-score-and-boolean-questions",
-    "recordedAt": "2026-09-22T03:44:57.511Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://opencode.ai/zen/v1/systemone",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"jev-1.13-free\",\"state\":\"I was charged twice for the same invoice. Please refund the duplicate payment today.\",\"questions\":{\"department\":{\"type\":\"choice\",\"instructions\":\"Which team should handle this support request?\",\"criteria\":{\"billing\":\"Payments, invoices, refunds, or failed charges\",\"technical\":\"Bugs, outages, or integrations\",\"sales\":\"Pricing, upgrades, or new accounts\"}},\"urgency\":{\"type\":\"score\",\"instructions\":\"How urgent is this support request?\",\"criteria\":[\"Can wait for normal support\",\"Needs prompt attention\",\"Actively blocking revenue\"]},\"refund\":{\"type\":\"noul\",\"instructions\":\"Is the customer asking for a refund?\"}}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"jev-1.13-free\",\"answers\":{\"department\":{\"type\":\"choice\",\"choice\":\"billing\",\"confidence\":1,\"probabilities\":{\"technical\":0,\"sales\":0,\"billing\":1}},\"urgency\":{\"type\":\"score\",\"score\":1.02,\"confidence\":0.95,\"legend\":{\"0\":\"Can wait for normal support\",\"1\":\"Needs prompt attention\",\"2\":\"Actively blocking revenue\"},\"probabilities\":{\"0\":0,\"1\":0.97,\"2\":0.03}},\"refund\":{\"type\":\"noul\",\"noul\":0.99}},\"usage\":{\"input_tokens\":422,\"output_tokens\":69}}"
-      }
-    }
-  ]
-}
@@ -1,33 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "typesafe/jev-1.13",
-    "tags": [
-      "prefix:openrouter-evaluation",
-      "provider:openrouter",
-      "protocol:system-one"
-    ],
-    "name": "openrouter-evaluation/evaluates-choice-score-and-boolean-questions",
-    "recordedAt": "2026-09-22T14:54:46.656Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://openrouter.ai/api/v1/systemone",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"typesafe/jev-1.13\",\"state\":\"I was charged twice for the same invoice. Please refund the duplicate payment today.\",\"questions\":{\"department\":{\"type\":\"choice\",\"instructions\":\"Which team should handle this support request?\",\"criteria\":{\"billing\":\"Payments, invoices, refunds, or failed charges\",\"technical\":\"Bugs, outages, or integrations\",\"sales\":\"Pricing, upgrades, or new accounts\"}},\"urgency\":{\"type\":\"score\",\"instructions\":\"How urgent is this support request?\",\"criteria\":[\"Can wait for normal support\",\"Needs prompt attention\",\"Actively blocking revenue\"]},\"refund\":{\"type\":\"noul\",\"instructions\":\"Is the customer asking for a refund?\"}}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"typesafe/jev-1.13-20260917\",\"answers\":{\"department\":{\"type\":\"choice\",\"choice\":\"billing\",\"probabilities\":{\"billing\":1,\"sales\":0,\"technical\":0},\"confidence\":1},\"urgency\":{\"type\":\"score\",\"score\":1.02,\"legend\":{\"0\":\"Can wait for normal support\",\"1\":\"Needs prompt attention\",\"2\":\"Actively blocking revenue\"},\"probabilities\":{\"0\":0.01,\"1\":0.96,\"2\":0.03},\"confidence\":0.95},\"refund\":{\"type\":\"noul\",\"noul\":0.99}},\"usage\":{\"input_tokens\":422,\"output_tokens\":69,\"cost\":0.000017724},\"id\":\"gen-dec-1790088886-JRlffOLUwQdx4Lltu2se\",\"provider\":\"TypeSafe\"}"
-      }
-    }
-  ]
-}
@@ -1,33 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "jev-latest",
-    "tags": [
-      "prefix:typesafe-evaluation",
-      "provider:typesafe-ai",
-      "protocol:system-one"
-    ],
-    "name": "typesafe-evaluation/evaluates-choice-score-and-boolean-questions",
-    "recordedAt": "2026-09-22T03:44:28.626Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.typesafe.ai/v1/systemone",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"jev-latest\",\"state\":\"I was charged twice for the same invoice. Please refund the duplicate payment today.\",\"questions\":{\"department\":{\"type\":\"choice\",\"instructions\":\"Which team should handle this support request?\",\"criteria\":{\"billing\":\"Payments, invoices, refunds, or failed charges\",\"technical\":\"Bugs, outages, or integrations\",\"sales\":\"Pricing, upgrades, or new accounts\"}},\"urgency\":{\"type\":\"score\",\"instructions\":\"How urgent is this support request?\",\"criteria\":[\"Can wait for normal support\",\"Needs prompt attention\",\"Actively blocking revenue\"]},\"refund\":{\"type\":\"noul\",\"instructions\":\"Is the customer asking for a refund?\"}}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"jev-1.13.0\",\"answers\":{\"department\":{\"type\":\"choice\",\"choice\":\"billing\",\"confidence\":1.0,\"probabilities\":{\"billing\":1.0,\"sales\":0.0,\"technical\":0.0}},\"urgency\":{\"type\":\"score\",\"score\":1.01,\"confidence\":0.97,\"legend\":{\"0\":\"Can wait for normal support\",\"1\":\"Needs prompt attention\",\"2\":\"Actively blocking revenue\"},\"probabilities\":{\"0\":0.0,\"1\":0.98,\"2\":0.02}},\"refund\":{\"type\":\"noul\",\"noul\":0.99}},\"usage\":{\"input_tokens\":422,\"output_tokens\":69}}"
-      }
-    }
-  ]
-}
@@ -1,116 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Fiber, Ref, Stream } from "effect"
-import * as TestClock from "effect/testing/TestClock"
-import {
-  AIError,
-  InvalidProviderOutputError,
-  Generation,
-  type GenerationRoute,
-  type GenerationSnapshot,
-  type GenerationStatus,
-} from "../src/index.js"
-import { it } from "./lib/effect.js"
-
-/** In-memory generation route whose status advances through `statuses` on every poll. */
-const scriptedRoute = (statuses: ReadonlyArray<GenerationStatus>, result: string) =>
-  Effect.gen(function* () {
-    const polls = yield* Ref.make(0)
-    const cancelled = yield* Ref.make(false)
-    // `count` is the number of polls so far; the first poll observes `statuses[0]`.
-    const snapshot = (count: number): GenerationSnapshot => ({
-      id: "gen_1",
-      status: statuses[Math.min(Math.max(count - 1, 0), statuses.length - 1)],
-      progress: count / statuses.length,
-    })
-    const route: GenerationRoute<string> = {
-      status: () => Ref.updateAndGet(polls, (count) => count + 1).pipe(Effect.map(snapshot)),
-      result: (token) =>
-        Effect.gen(function* () {
-          const count = yield* Ref.get(polls)
-          const status = snapshot(count).status
-          if (status === "completed") return `${result}:${String(token)}`
-          return yield* new AIError({ reason: new InvalidProviderOutputError({ message: `Generation ended ${status}` }) })
-        }),
-      cancel: () => Ref.set(cancelled, true),
-    }
-    return { route, polls, cancelled }
-  })
-
-describe("Generation", () => {
-  it.effect("polls queued → running → completed and returns the result", () =>
-    Effect.gen(function* () {
-      const scripted = yield* scriptedRoute(["queued", "running", "completed"], "done")
-      const generation = new Generation(scripted.route, { op: "token_1" }, { id: "gen_1", status: "queued" })
-      expect(generation.terminal).toBe(false)
-
-      const fiber = yield* Effect.forkChild(generation.await({ poll: { interval: "1 second", timeout: "1 minute" } }))
-      yield* TestClock.adjust("3 seconds")
-      const result = yield* Fiber.join(fiber)
-
-      expect(result).toBe("done:[object Object]")
-      expect(yield* Ref.get(scripted.polls)).toBe(3)
-    }),
-  )
-
-  it.effect("returns immediately for an already terminal generation", () =>
-    Effect.gen(function* () {
-      const scripted = yield* scriptedRoute(["completed"], "done")
-      yield* Ref.set(scripted.polls, 1)
-      const generation = new Generation(scripted.route, "t", { id: "gen_1", status: "completed" })
-      expect(yield* generation.await()).toBe("done:t")
-      expect(yield* Ref.get(scripted.polls)).toBe(1)
-    }),
-  )
-
-  it.effect("fails with a Timeout reason when the generation never finishes", () =>
-    Effect.gen(function* () {
-      const scripted = yield* scriptedRoute(["running"], "never")
-      const generation = new Generation(scripted.route, "t", { id: "gen_1", status: "queued" })
-
-      const fiber = yield* Effect.forkChild(
-        generation.await({ poll: { interval: "1 second", timeout: "5 seconds" } }).pipe(Effect.flip),
-      )
-      yield* TestClock.adjust("6 seconds")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error).toBeInstanceOf(AIError)
-      expect(error.reason._tag).toBe("Timeout")
-      expect(error.message).toContain("gen_1")
-      expect(yield* Ref.get(scripted.polls)).toBeGreaterThan(1)
-    }),
-  )
-
-  it.effect("surfaces the route failure body for failed generations", () =>
-    Effect.gen(function* () {
-      const scripted = yield* scriptedRoute(["running", "failed"], "unused")
-      const generation = new Generation(scripted.route, "t", { id: "gen_1", status: "queued" })
-
-      const fiber = yield* Effect.forkChild(generation.await({ poll: { interval: "1 second" } }).pipe(Effect.flip))
-      yield* TestClock.adjust("2 seconds")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error.reason._tag).toBe("InvalidProviderOutput")
-      expect(error.message).toContain("Generation ended failed")
-    }),
-  )
-
-  it.effect("streams status events until the first terminal observation and cancels through the route", () =>
-    Effect.gen(function* () {
-      const scripted = yield* scriptedRoute(["queued", "running", "completed"], "done")
-      const generation = new Generation(scripted.route, "t", { id: "gen_1", status: "queued" })
-
-      const fiber = yield* Effect.forkChild(generation.events({ poll: { interval: "1 second" } }).pipe(Stream.runCollect))
-      yield* TestClock.adjust("3 seconds")
-      const events = Array.from(yield* Fiber.join(fiber))
-
-      expect(events).toEqual([
-        { type: "generation-queued", id: "gen_1", position: undefined },
-        { type: "generation-progress", id: "gen_1", progress: 2 / 3 },
-        { type: "generation-finished", id: "gen_1", status: "completed" },
-      ])
-
-      yield* generation.cancel()
-      expect(yield* Ref.get(scripted.cancelled)).toBe(true)
-    }),
-  )
-})
@@ -1,7 +1,7 @@
 import { describe, expect } from "bun:test"
 import { Effect, Layer } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { Image, ImageClient, Media } from "../src/index.js"
+import { Image, ImageClient, ImageInput } from "../src/index.js"
 import { Google, OpenAI, XAI, ZAI } from "../src/providers.js"
 import { it } from "./lib/effect.js"
 import { dynamicResponse } from "./lib/http.js"
@@ -48,11 +48,11 @@ describe("Image", () => {
          http: { body: { deployment: "test" }, headers: { "x-default": "yes" } },
        }).image("gpt-image-2"),
        prompt: "A robot tending a rooftop garden",
-        n: 2,
-        size: "2048x2048",
-        format: "jpeg",
-        providerOptions: {
+        options: {
+          n: 2,
+          size: "2048x2048",
          quality: "future-quality",
+          outputFormat: "jpeg",
          output_format: "avif",
          outputCompression: 30,
          output_compression: 40,
@@ -68,15 +68,14 @@ describe("Image", () => {
      })

      expect(response.images).toHaveLength(2)
-      expect(response.image.mediaType).toBe("image/webp")
-      expect(response.image.source).toEqual({ type: "bytes", data: Uint8Array.from([1, 2, 3]), mediaType: "image/webp" })
-      expect(yield* response.image.bytes()).toEqual(Uint8Array.from([1, 2, 3]))
-      expect(response.image.providerMetadata).toEqual({ openai: { revisedPrompt: "A precise robot" } })
-      expect(response.usage).toMatchObject({ type: "tokens", total: 12 })
+      expect(response.image?.mediaType).toBe("image/webp")
+      expect(response.image?.data).toEqual(Uint8Array.from([1, 2, 3]))
+      expect(response.image?.providerMetadata).toEqual({ openai: { revisedPrompt: "A precise robot" } })
+      expect(response.usage?.totalTokens).toBe(12)
    }).pipe(
      Effect.provide(
        ImageClient.layer.pipe(
-          Layer.provideMerge(
+          Layer.provide(
            dynamicResponse((input) =>
              Effect.gen(function* () {
                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
@@ -114,32 +113,6 @@ describe("Image", () => {
    ),
  )

-  it.effect("sends only model and prompt by default and decodes OpenAI bytes as png", () =>
-    Effect.gen(function* () {
-      const openai = OpenAI.configure({ apiKey: "test", baseURL: "https://openai.test/v1" })
-      expect(openai.image("gpt-image-2").route.id).toBe("openai-images")
-      const response = yield* Image.generate({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" }).pipe(
-        Effect.provide(
-          ImageClient.layer.pipe(
-            Layer.provide(
-              dynamicResponse((input) =>
-                Effect.gen(function* () {
-                  const web = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                  expect(web.url).toBe("https://openai.test/v1/images/generations")
-                  expect(JSON.parse(input.text)).toEqual({ model: "gpt-image-2", prompt: "A lighthouse" })
-                  return input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
-                    headers: { "content-type": "application/json" },
-                  })
-                }),
-              ),
-            ),
-          ),
-        ),
-      )
-      expect(response.image.source).toEqual({ type: "bytes", data: Uint8Array.from([1, 2, 3]), mediaType: "image/png" })
-    }),
-  )
-
  it.effect("preserves native snake_case and unknown request options", () =>
    Image.generate({
      model: OpenAI.configure({
@@ -147,8 +120,8 @@ describe("Image", () => {
        baseURL: "https://api.openai.test/v1",
      }).image("future-image-model"),
      prompt: "A lighthouse in fog",
-      format: "jpeg",
-      providerOptions: {
+      options: {
+        outputFormat: "jpeg",
        output_format: "avif",
        outputCompression: 30,
        output_compression: 40,
@@ -157,7 +130,7 @@ describe("Image", () => {
    }).pipe(
      Effect.tap((response) =>
        Effect.sync(() => {
-          expect(response.image.mediaType).toBe("image/avif")
+          expect(response.image?.mediaType).toBe("image/avif")
        }),
      ),
      Effect.provide(
@@ -187,9 +160,12 @@ describe("Image", () => {
    Image.generate({
      model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("future-model"),
      prompt: "Combine these images",
-      images: [Media.bytes(Uint8Array.from([1, 2, 3]), "image/png"), Media.fromDataUrl("data:image/jpeg;base64,BAUG")],
-      mask: Media.bytes(Uint8Array.from([7, 8, 9]), "image/png"),
-      providerOptions: {
+      images: [
+        ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
+        ImageInput.url("data:image/jpeg;base64,BAUG"),
+      ],
+      options: {
+        mask: ImageInput.bytes(Uint8Array.from([7, 8, 9]), "image/png"),
        quality: "high",
        future_option: true,
      },
@@ -227,8 +203,8 @@ describe("Image", () => {
    Image.generate({
      model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("future-model"),
      prompt: "Combine these images",
-      images: [Media.url("https://example.test/source.png"), Media.ref("openai", "file_123")],
-      mask: Media.ref("openai", "file_mask"),
+      images: [ImageInput.url("https://example.test/source.png"), ImageInput.file("file_123")],
+      options: { mask: ImageInput.file("file_mask") },
      http: { body: { future_option: true } },
    }).pipe(
      Effect.provide(
@@ -259,9 +235,9 @@ describe("Image", () => {
      model: XAI.configure({ apiKey: "test", baseURL: "https://api.xai.test/v1" }).image("future-model"),
      prompt: "Combine these images",
      images: [
-        Media.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
-        Media.url("https://example.test/source.jpg"),
-        Media.ref("xai", "file_123"),
+        ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
+        ImageInput.url("https://example.test/source.jpg"),
+        ImageInput.file("file_123"),
      ],
    }).pipe(
      Effect.provide(
@@ -293,7 +269,7 @@ describe("Image", () => {
    Image.generate({
      model: XAI.configure({ apiKey: "test", baseURL: "https://api.xai.test/v1" }).image("future-model"),
      prompt: "Edit this image",
-      images: [Media.ref("xai", "file_123")],
+      images: [ImageInput.file("file_123")],
    }).pipe(
      Effect.provide(
        ImageClient.layer.pipe(
@@ -321,9 +297,9 @@ describe("Image", () => {
      model: Google.configure({ apiKey: "test", baseURL: "https://google.test/v1beta" }).image("future-model"),
      prompt: "Combine these images",
      images: [
-        Media.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
-        Media.fromDataUrl("data:image/jpeg;base64,BAUG"),
-        Media.ref("google", "https://generativelanguage.googleapis.com/v1beta/files/123", "image/webp"),
+        ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
+        ImageInput.url("data:image/jpeg;base64,BAUG"),
+        ImageInput.fileUri("https://generativelanguage.googleapis.com/v1beta/files/123", "image/webp"),
      ],
    }).pipe(
      Effect.provide(
@@ -362,20 +338,18 @@ describe("Image", () => {
        Image.generate({
          model: Google.configure({ apiKey: "test" }).image("model"),
          prompt: "edit",
-          images: [Media.url("https://example.test/image.png")],
+          images: [ImageInput.url("https://example.test/image.png")],
        }),
        Image.generate({
          model: ZAI.configure({ apiKey: "test" }).image("model"),
          prompt: "edit",
-          images: [Media.bytes(Uint8Array.from([1]), "image/png")],
+          images: [ImageInput.bytes(Uint8Array.from([1]), "image/png")],
        }),
      ]
      yield* Effect.forEach(cases, (program) =>
        program.pipe(
          Effect.flip,
-          Effect.tap((error) =>
-            Effect.sync(() => expect(["InvalidRequest", "UnsupportedOperation"]).toContain(error.reason._tag)),
-          ),
+          Effect.tap((error) => Effect.sync(() => expect(error.reason._tag).toBe("InvalidRequest"))),
        ),
      )
    }).pipe(
@@ -397,10 +371,10 @@ describe("Image", () => {
          http: { body: { labels: { deployment: "test" } }, query: { api: "v1" } },
        }).image("any-model-id"),
        prompt: "A robot tending a rooftop garden",
-        aspectRatio: "16:9",
-        seed: 42,
-        providerOptions: {
+        options: {
+          aspectRatio: "16:9",
          imageSize: "2K",
+          seed: 42,
          thinkingLevel: "HIGH",
          includeThoughts: true,
          futureOption: true,
@@ -423,7 +397,7 @@ describe("Image", () => {
      })

      expect(response.images).toHaveLength(3)
-      expect(yield* Effect.forEach(response.images, (image) => image.bytes())).toEqual([
+      expect(response.images.map((image) => image.data)).toEqual([
        Uint8Array.from([1, 2, 3]),
        Uint8Array.from([4, 5, 6]),
        Uint8Array.from([7, 8, 9]),
@@ -434,12 +408,10 @@ describe("Image", () => {
        google: { candidateIndex: 0, partIndex: 3, finishReason: "STOP" },
      })
      expect(response.images[2].providerMetadata).toMatchObject({ google: { candidateIndex: 7, partIndex: 0 } })
-      expect(response.usage).toMatchObject({
-        type: "tokens",
-        input: 5,
-        output: 10,
-        details: { reasoningTokens: 3, google: { serviceTier: "STANDARD" } },
-      })
+      expect(response.usage?.inputTokens).toBe(5)
+      expect(response.usage?.outputTokens).toBe(10)
+      expect(response.usage?.reasoningTokens).toBe(3)
+      expect(response.usage?.providerMetadata).toMatchObject({ google: { serviceTier: "STANDARD" } })
      expect(response.providerMetadata).toEqual({
        google: {
          modelVersion: "gemini-3.1-flash-image",
@@ -497,7 +469,7 @@ describe("Image", () => {
    }).pipe(
      Effect.provide(
        ImageClient.layer.pipe(
-          Layer.provideMerge(
+          Layer.provide(
            dynamicResponse((input) =>
              Effect.gen(function* () {
                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
@@ -577,69 +549,6 @@ describe("Image", () => {
    ),
  )

-  it.effect("surfaces filtered Google candidates as notices next to the returned image", () =>
-    Image.generate({
-      model: Google.configure({ apiKey: "test", baseURL: "https://generativelanguage.test/v1beta" }).image(
-        "gemini-3.1-flash-image",
-      ),
-      prompt: "A robot tending a rooftop garden",
-    }).pipe(
-      Effect.tap((response) =>
-        Effect.sync(() => {
-          expect(response.images).toHaveLength(1)
-          expect(response.notices).toEqual([
-            {
-              type: "filtered",
-              message: "Google Images reported prompt feedback",
-              providerMetadata: { google: { promptFeedback: { blockReason: "OTHER" } } },
-            },
-            {
-              type: "filtered",
-              message: "Google Images candidate 1 finished with IMAGE_SAFETY: Blocked.",
-              providerMetadata: {
-                google: {
-                  candidateIndex: 1,
-                  finishReason: "IMAGE_SAFETY",
-                  finishMessage: "Blocked.",
-                  safetyRatings: [{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", blocked: true }],
-                },
-              },
-            },
-          ])
-        }),
-      ),
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    promptFeedback: { blockReason: "OTHER" },
-                    candidates: [
-                      {
-                        content: { parts: [{ inlineData: { mimeType: "image/png", data: "AQID" } }] },
-                        finishReason: "STOP",
-                      },
-                      {
-                        index: 1,
-                        content: { parts: [{ text: "blocked" }] },
-                        finishReason: "IMAGE_SAFETY",
-                        finishMessage: "Blocked.",
-                        safetyRatings: [{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", blocked: true }],
-                      },
-                    ],
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              ),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
  it.effect("includes Google diagnostics when no final image is returned", () =>
    Image.generate({
      model: Google.configure({ apiKey: "test", baseURL: "https://generativelanguage.test/v1beta" }).image(
@@ -2,51 +2,50 @@ import { Effect } from "effect"
 import {
  Image,
  ImageClient,
+  ImageInput,
  ImageModel,
-  Media,
  type ImageModelOptions,
  type ImageOptions,
  type ImageRequestFor,
  type ImageRoute,
 } from "../src/index.js"
 import type { Service } from "../src/image-client.js"
-import { Anthropic, Google, OpenAI, XAI, ZAI } from "../src/providers.js"
+import { Google, OpenAI, XAI, ZAI } from "../src/providers.js"

 type Requirements<T> = T extends Effect.Effect<infer _A, infer _E, infer R> ? R : never
 type Equal<A, B> = [A, B] extends [B, A] ? true : false
 type Assert<T extends true> = T

 type GoogleLikeOptions = {
+  readonly aspectRatio?: "1:1" | "16:9"
  readonly imageSize?: "1K" | "2K"
-  readonly thinkingLevel?: "LOW" | "HIGH"
 } & Record<string, unknown>

 declare const route: ImageRoute<GoogleLikeOptions>
 const google = ImageModel.make<GoogleLikeOptions>({ id: "gemini-image", provider: "google", route })
 // @ts-expect-error Extracted model options retain known provider fields.
-const invalidGoogleOptions: ImageModelOptions<typeof google> = { imageSize: "8K" }
+const invalidGoogleOptions: ImageModelOptions<typeof google> = { aspectRatio: "wide" }
 void invalidGoogleOptions

 Image.generate({
  model: google,
  prompt: "A lighthouse",
  images: [
-    Media.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
-    Media.fromDataUrl("data:image/jpeg;base64,AQID"),
-    Media.ref("google", "https://generativelanguage.googleapis.com/v1beta/files/example", "image/webp"),
+    ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
+    ImageInput.url("data:image/jpeg;base64,AQID"),
+    ImageInput.fileUri("https://generativelanguage.googleapis.com/v1beta/files/example", "image/webp"),
  ],
-  aspectRatio: "16:9",
-  seed: 7,
-  providerOptions: { imageSize: "2K", thinkingLevel: "HIGH", futureOption: true },
+  options: { aspectRatio: "16:9", imageSize: "2K", futureOption: true },
 })

 const googleProvider = Google.configure({ apiKey: "test" }).image("any-model-id")
 Image.generate({
  model: googleProvider,
  prompt: "A lighthouse",
-  aspectRatio: "16:9",
-  providerOptions: {
+  options: {
+    aspectRatio: "16:9",
    imageSize: "2K",
+    seed: 42,
    thinkingLevel: "HIGH",
    includeThoughts: true,
    futureOption: true,
@@ -55,65 +54,57 @@ Image.generate({
 Image.generate({
  model: googleProvider,
  prompt: "A lighthouse",
-  providerOptions: { imageSize: "8K", thinkingLevel: "FUTURE" },
+  options: { aspectRatio: "future-ratio", imageSize: "8K", thinkingLevel: "FUTURE" },
 })
 // @ts-expect-error Image generation options are request-scoped, not provider configuration.
 Google.configure({ image: { providerOptions: { imageSize: "2K" } } })
 // @ts-expect-error Known Google string options retain their value kind.
-Image.generate({ model: googleProvider, prompt: "A lighthouse", providerOptions: { imageSize: 2 } })
+Image.generate({ model: googleProvider, prompt: "A lighthouse", options: { imageSize: 2 } })
+// @ts-expect-error Known Google numeric options retain their value kind.
+Image.generate({ model: googleProvider, prompt: "A lighthouse", options: { seed: "42" } })
 // @ts-expect-error Known Google boolean options retain their value kind.
-Image.generate({ model: googleProvider, prompt: "A lighthouse", providerOptions: { includeThoughts: "yes" } })
+Image.generate({ model: googleProvider, prompt: "A lighthouse", options: { includeThoughts: "yes" } })

 const openai = OpenAI.image("gpt-image-2")
 // @ts-expect-error Image generation options are request-scoped, not provider configuration.
-OpenAI.configure({ image: { providerOptions: { quality: "medium" } } })
+OpenAI.configure({ image: { options: { quality: "medium" } } })
 const futureOpenAIOptions: ImageModelOptions<typeof openai> = { quality: "future-quality" }
 void futureOpenAIOptions
 Image.generate({
  model: openai,
  prompt: "A lighthouse",
-  images: [Media.url("https://example.com/source.png"), Media.ref("openai", "file_123")],
-  mask: Media.bytes(Uint8Array.from([1]), "image/png"),
-  n: 2,
-  size: "2048x2048",
-  format: "webp",
-  providerOptions: {
+  images: [ImageInput.url("https://example.com/source.png"), ImageInput.file("file_123")],
+  options: {
+    mask: ImageInput.bytes(Uint8Array.from([1]), "image/png"),
    quality: "hd",
-    background: "transparent",
+    outputFormat: "webp",
+    size: "2048x2048",
    future_option: true,
  },
 })
-Image.generate({
-  model: openai,
-  prompt: "A lighthouse",
-  size: "256x256",
-  providerOptions: { quality: "future-quality" },
-})
-Image.generate({ model: openai, prompt: "A lighthouse", format: "future-format" })
-Image.generate({ model: openai, prompt: "A lighthouse", providerOptions: { native_future_option: true } })
+Image.generate({ model: openai, prompt: "A lighthouse", options: { quality: "future-quality", size: "256x256" } })
+Image.generate({ model: openai, prompt: "A lighthouse", options: { size: "1792x1024" } })
+Image.generate({ model: openai, prompt: "A lighthouse", options: { native_future_option: true } })
 // @ts-expect-error Known OpenAI string options retain their value kind.
-Image.generate({ model: openai, prompt: "A lighthouse", providerOptions: { quality: 1 } })
+Image.generate({ model: openai, prompt: "A lighthouse", options: { quality: 1 } })
 // @ts-expect-error Known OpenAI numeric options retain their value kind.
-Image.generate({ model: openai, prompt: "A lighthouse", providerOptions: { outputCompression: "80" } })
+Image.generate({ model: openai, prompt: "A lighthouse", options: { outputCompression: "80" } })
 OpenAI.imageGeneration({ action: "future-action", quality: "future-quality", size: "2048x2048" })
 // @ts-expect-error Hosted image generation numeric options retain their value kind.
 OpenAI.imageGeneration({ partialImages: "2" })
 // @ts-expect-error Known Google-like options are inferred from the selected model.
-Image.generate({ model: google, prompt: "A lighthouse", providerOptions: { imageSize: "8K" } })
-
-// @ts-expect-error Language models cannot be used for image requests.
-Image.generate({ model: Anthropic.configure({ apiKey: "test" }).model("claude-sonnet-4-5"), prompt: "A lighthouse" })
+Image.generate({ model: google, prompt: "A lighthouse", options: { aspectRatio: "wide" } })

 const xai = XAI.configure({ apiKey: "test" }).image("any-model-id")
 // @ts-expect-error Image generation options are request-scoped, not provider configuration.
-XAI.configure({ image: { providerOptions: { resolution: "1k" } } })
+XAI.configure({ image: { options: { resolution: "1k" } } })
 Image.generate({
  model: xai,
  prompt: "A lighthouse",
-  images: [Media.fromDataUrl("data:image/png;base64,AQID"), Media.ref("xai", "file_123")],
-  n: 2,
-  aspectRatio: "16:9",
-  providerOptions: {
+  images: [ImageInput.url("data:image/png;base64,AQID"), ImageInput.file("file_123")],
+  options: {
+    n: 2,
+    aspectRatio: "future-ratio",
    resolution: "future-resolution",
    responseFormat: "future-format",
    future_option: true,
@@ -122,43 +113,43 @@ Image.generate({
 Image.generate({
  model: xai,
  prompt: "A lighthouse",
-  providerOptions: { response_format: "b64_json", native_future_option: true },
+  options: { aspect_ratio: "16:9", response_format: "b64_json", native_future_option: true },
 })
-// @ts-expect-error Common count is numeric.
-Image.generate({ model: xai, prompt: "A lighthouse", n: "2" })
+// @ts-expect-error Known xAI numeric options retain their value kind.
+Image.generate({ model: xai, prompt: "A lighthouse", options: { n: "2" } })
 // @ts-expect-error Known xAI string options retain their value kind.
-Image.generate({ model: xai, prompt: "A lighthouse", providerOptions: { resolution: 2 } })
+Image.generate({ model: xai, prompt: "A lighthouse", options: { resolution: 2 } })

 const zai = ZAI.configure({ apiKey: "test" }).image("any-model-id")
 // @ts-expect-error Image generation options are request-scoped, not provider configuration.
-ZAI.configure({ image: { providerOptions: { quality: "hd" } } })
+ZAI.configure({ image: { options: { quality: "hd" } } })
 Image.generate({
  model: zai,
  prompt: "A lighthouse",
-  providerOptions: { quality: "future-quality", userID: "user-123", future_option: true },
+  options: { quality: "future-quality", userID: "user-123", future_option: true },
 })
-Image.generate({ model: zai, prompt: "A lighthouse", providerOptions: { user_id: "raw-user" } })
+Image.generate({ model: zai, prompt: "A lighthouse", options: { user_id: "raw-user" } })
 // @ts-expect-error Known Z.ai string options retain their value kind.
-Image.generate({ model: zai, prompt: "A lighthouse", providerOptions: { quality: 1 } })
+Image.generate({ model: zai, prompt: "A lighthouse", options: { quality: 1 } })
 // @ts-expect-error Known Z.ai user IDs retain their value kind.
-Image.generate({ model: zai, prompt: "A lighthouse", providerOptions: { userID: 1 } })
+Image.generate({ model: zai, prompt: "A lighthouse", options: { userID: 1 } })

 declare const generic: ImageModel<ImageOptions>
-Image.generate({ model: generic, prompt: "A lighthouse", providerOptions: { arbitrary: true } })
-const explicitAsset: Media.Asset = Media.url("https://example.com/image.png")
-void explicitAsset
+Image.generate({ model: generic, prompt: "A lighthouse", options: { arbitrary: true } })
+const explicitImageInput: ImageInput = ImageInput.url("https://example.com/image.png")
+void explicitImageInput

-// @ts-expect-error Raw strings are ambiguous and are not media assets.
+// @ts-expect-error Raw strings are ambiguous and are not image inputs.
 Image.generate({ model: openai, prompt: "A lighthouse", images: ["AQID"] })
-// @ts-expect-error Plain source objects must be lifted into `Media.Asset` first.
+// @ts-expect-error Byte image inputs require an explicit MIME type.
 Image.generate({ model: openai, prompt: "A lighthouse", images: [{ type: "bytes", data: new Uint8Array() }] })
-// @ts-expect-error Masks are media assets, not strings.
-Image.generate({ model: openai, prompt: "A lighthouse", mask: "https://example.com/mask.png" })
+// @ts-expect-error File URIs require an explicit MIME type for Gemini fileData.
+Image.generate({ model: google, prompt: "A lighthouse", images: [{ type: "file-uri", uri: "files/123" }] })

 const request = Image.request({
  model: google,
  prompt: "A lighthouse",
-  providerOptions: { imageSize: "1K", futureOption: true },
+  options: { aspectRatio: "1:1", futureOption: true },
 })
 const typedRequest: ImageRequestFor<GoogleLikeOptions> = request
 void typedRequest
@@ -166,13 +157,15 @@ const generated = ImageClient.generate(request)
 type GenerateRequirements = Assert<Equal<Requirements<typeof generated>, Service>>
 void (true satisfies GenerateRequirements)

-// @ts-expect-error Image requests use `n`, not `count`.
+// @ts-expect-error Image requests no longer expose a common count option.
 Image.generate({ model: openai, prompt: "A lighthouse", count: 2 })
-// @ts-expect-error Image sizes are `${width}x${height}` strings.
+// @ts-expect-error Image requests no longer expose a common size option.
 Image.generate({ model: openai, prompt: "A lighthouse", size: { width: 1024, height: 1024 } })
-// @ts-expect-error Aspect ratios are `${w}:${h}` strings.
-Image.generate({ model: openai, prompt: "A lighthouse", aspectRatio: "wide" })
+// @ts-expect-error Image requests no longer expose a common aspectRatio option.
+Image.generate({ model: openai, prompt: "A lighthouse", aspectRatio: "16:9" })
+// @ts-expect-error Image requests no longer expose a common seed option.
+Image.generate({ model: openai, prompt: "A lighthouse", seed: 1 })
 // @ts-expect-error Image requests do not expose metadata.
 Image.generate({ model: openai, prompt: "A lighthouse", metadata: { trace: true } })
-// @ts-expect-error `options` was renamed to `providerOptions`.
-Image.generate({ model: openai, prompt: "A lighthouse", options: { quality: "hd" } })
+// @ts-expect-error Masks are provider options, not a common image request field.
+Image.generate({ model: openai, prompt: "A lighthouse", mask: ImageInput.url("https://example.com/mask.png") })
@@ -17,7 +17,7 @@ export type Handler = (
  input: HandlerInput,
 ) => Effect.Effect<HttpClientResponse.HttpClientResponse, HttpClientError.HttpClientError>

-export const handlerLayer = (handler: Handler): Layer.Layer<HttpClient.HttpClient> =>
+const handlerLayer = (handler: Handler): Layer.Layer<HttpClient.HttpClient> =>
  Layer.succeed(
    HttpClient.HttpClient,
    HttpClient.make((request) =>
@@ -1,180 +0,0 @@
-import { describe, expect } from "bun:test"
-import { NodeFileSystem } from "@effect/platform-node"
-import { Effect, Ref, Schema } from "effect"
-import { FileSystem } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { Media, Message } from "../src/index.js"
-import { it } from "./lib/effect.js"
-import { dynamicResponse, scriptedResponses } from "./lib/http.js"
-
-const PNG = Uint8Array.from([0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a, 0, 0, 0, 0])
-const JPEG = Uint8Array.from([0xff, 0xd8, 0xff, 0xe0, 0, 0])
-const GIF = Uint8Array.from([0x47, 0x49, 0x46, 0x38, 0x39, 0x61])
-const WEBP = Uint8Array.from([0x52, 0x49, 0x46, 0x46, 0, 0, 0, 0, 0x57, 0x45, 0x42, 0x50])
-const PDF = Uint8Array.from([0x25, 0x50, 0x44, 0x46, 0x2d, 0x31])
-
-describe("Media", () => {
-  it.effect("round-trips every source through Media.from(asset.source)", () =>
-    Effect.sync(() => {
-      const assets = [
-        Media.bytes(PNG),
-        Media.base64("AQID", "image/png"),
-        Media.url("https://example.test/a.png", { mediaType: "image/png", expiresAt: 123, headers: { a: "b" } }),
-        Media.ref("openai", "file_123", "image/webp"),
-      ]
-      for (const asset of assets) {
-        const copy = Media.from(asset.source)
-        expect(copy.source).toEqual(asset.source)
-        expect(copy.mediaType).toBe(asset.mediaType)
-        expect(copy.kind).toBe(asset.kind)
-        expect(copy.expiresAt).toBe(asset.expiresAt)
-      }
-      expect(assets.map((asset) => asset.kind)).toEqual(["image", "image", "image", "image"])
-      expect(Media.url("https://example.test/unknown").mediaType).toBe("application/octet-stream")
-      expect(Media.url("https://example.test/unknown").kind).toBe("other")
-      expect(Media.base64("AQID", "application/pdf").kind).toBe("document")
-      expect(Media.base64("AQID", "video/mp4").kind).toBe("video")
-      expect(Media.base64("AQID", "audio/wav").kind).toBe("audio")
-    }),
-  )
-
-  it.effect("parses data URLs and rejects malformed ones", () =>
-    Effect.sync(() => {
-      const asset = Media.fromDataUrl("data:image/jpeg;base64,/9j/")
-      expect(asset.source).toEqual({ type: "base64", data: "/9j/", mediaType: "image/jpeg" })
-      expect(asset.mediaType).toBe("image/jpeg")
-      expect(Media.fromDataUrl("data:text/plain;charset=utf-8;base64,aGk=").source).toEqual({
-        type: "base64",
-        data: "aGk=",
-        mediaType: "text/plain",
-      })
-      expect(() => Media.fromDataUrl("https://example.test/a.png")).toThrow(
-        "Media data URLs must contain a MIME type and base64 data",
-      )
-      expect(() => Media.fromDataUrl("data:image/png,rawtext")).toThrow()
-    }),
-  )
-
-  it.effect("detects media types from magic bytes", () =>
-    Effect.sync(() => {
-      expect(Media.detectMediaType(PNG)).toBe("image/png")
-      expect(Media.detectMediaType(JPEG)).toBe("image/jpeg")
-      expect(Media.detectMediaType(GIF)).toBe("image/gif")
-      expect(Media.detectMediaType(WEBP)).toBe("image/webp")
-      expect(Media.detectMediaType(PDF)).toBe("application/pdf")
-      expect(Media.detectMediaType(Uint8Array.from([1, 2, 3]))).toBeUndefined()
-      expect(Media.bytes(PNG).mediaType).toBe("image/png")
-      expect(Media.bytes(Uint8Array.from([1, 2, 3])).mediaType).toBe("application/octet-stream")
-      expect(Media.bytes(Uint8Array.from([1, 2, 3]), "image/x-custom").mediaType).toBe("image/x-custom")
-    }),
-  )
-
-  it.effect("materializes url assets through the request executor once", () =>
-    Effect.gen(function* () {
-      const requests = yield* Ref.make<Array<HttpClientRequest.HttpClientRequest>>([])
-      const asset = Media.url("https://cdn.example.test/generated", {
-        expiresAt: 42,
-        headers: { authorization: "Bearer media" },
-        providerMetadata: { example: { id: "gen_1" } },
-      })
-      const program = Effect.gen(function* () {
-        const first = yield* asset.bytes()
-        const second = yield* asset.bytes()
-        expect(second).toBe(first)
-        expect(first).toEqual(PNG)
-        expect(yield* asset.base64()).toBe(Buffer.from(PNG).toString("base64"))
-        expect(yield* asset.dataUrl()).toBe(
-          `data:application/octet-stream;base64,${Buffer.from(PNG).toString("base64")}`,
-        )
-
-        const owned = yield* asset.materialize()
-        expect(owned.source).toEqual({ type: "bytes", data: PNG, mediaType: "image/png" })
-        expect(owned.mediaType).toBe("image/png")
-        expect(owned.kind).toBe("image")
-        expect(owned.expiresAt).toBeUndefined()
-        expect(owned.providerMetadata).toEqual({ example: { id: "gen_1" } })
-        expect(yield* owned.materialize()).toBe(owned)
-
-        const seen = yield* Ref.get(requests)
-        expect(seen).toHaveLength(1)
-        expect(seen[0].url).toBe("https://cdn.example.test/generated")
-        expect(seen[0].headers.authorization).toBe("Bearer media")
-      })
-      yield* program.pipe(
-        Effect.provide(
-          dynamicResponse((input) =>
-            Ref.update(requests, (all) => [...all, input.request]).pipe(
-              Effect.map(() => input.respond(PNG, { headers: { "content-type": "image/png" } })),
-            ),
-          ),
-        ),
-      )
-    }),
-  )
-
-  it.effect("caches decoded base64 bytes and encodes owned bytes lazily", () =>
-    Effect.gen(function* () {
-      const fromBase64 = Media.base64("AQID", "image/png")
-      const decoded = yield* fromBase64.bytes()
-      expect(decoded).toEqual(Uint8Array.from([1, 2, 3]))
-      expect(yield* fromBase64.bytes()).toBe(decoded)
-      expect(yield* fromBase64.base64()).toBe("AQID")
-
-      const fromBytes = Media.bytes(Uint8Array.from([1, 2, 3]), "image/png")
-      const encoded = yield* fromBytes.base64()
-      expect(encoded).toBe("AQID")
-      expect(yield* fromBytes.base64()).toBe(encoded)
-      expect(yield* fromBytes.dataUrl()).toBe("data:image/png;base64,AQID")
-
-      const invalid = yield* Media.base64("not base64!", "image/png").bytes().pipe(Effect.flip)
-      expect(invalid.reason._tag).toBe("InvalidRequest")
-      const ref = yield* Media.ref("openai", "file_1").bytes().pipe(Effect.flip)
-      expect(ref.reason._tag).toBe("InvalidRequest")
-    }).pipe(Effect.provide(scriptedResponses(["unused"]))),
-  )
-
-  it.effect("serializes assets inside messages and restores them as Media.Asset", () =>
-    Effect.sync(() => {
-      const codec = Schema.fromJsonString(Message)
-      const message = Message.user([
-        Message.media(Media.base64("AQID", "image/png", { info: { width: 1, height: 1 } }), { filename: "a.png" }),
-        Message.media(Media.url("https://example.test/b.pdf", { mediaType: "application/pdf", expiresAt: 7 })),
-      ])
-      const json = Schema.encodeSync(codec)(message)
-      expect(json).not.toContain("null")
-      const restored = Schema.decodeSync(codec)(json)
-      const parts = restored.content.filter((part) => part.type === "media")
-      expect(parts).toHaveLength(2)
-      expect(parts[0].media).toBeInstanceOf(Media.Asset)
-      expect(parts[0].media.source).toEqual({ type: "base64", data: "AQID", mediaType: "image/png" })
-      expect(parts[0].media.info).toEqual({ width: 1, height: 1 })
-      expect(parts[0].filename).toBe("a.png")
-      expect(parts[1].media.kind).toBe("document")
-      expect(parts[1].media.expiresAt).toBe(7)
-    }),
-  )
-
-  it.effect("reads files with sniffed media types and writes materialized assets", () =>
-    Effect.gen(function* () {
-      const fs = yield* FileSystem.FileSystem
-      const dir = yield* fs.makeTempDirectoryScoped()
-      const source = `${dir}/source.bin`
-      yield* fs.writeFile(source, PNG)
-
-      const asset = yield* Media.file(source)
-      expect(asset.mediaType).toBe("image/png")
-      expect(asset.source).toEqual({ type: "bytes", data: PNG, mediaType: "image/png" })
-
-      const plain = `${dir}/notes.md`
-      yield* fs.writeFile(plain, new TextEncoder().encode("# hi"))
-      expect((yield* Media.file(plain)).mediaType).toBe("text/markdown")
-
-      const target = `${dir}/copy.png`
-      yield* Media.write(Media.base64("AQID", "image/png"), target)
-      expect(yield* fs.readFile(target)).toEqual(Uint8Array.from([1, 2, 3]))
-
-      const missing = yield* Media.file(`${dir}/missing.png`).pipe(Effect.flip)
-      expect(missing.reason._tag).toBe("InvalidRequest")
-    }).pipe(Effect.provide(NodeFileSystem.layer), Effect.provide(scriptedResponses(["unused"]))),
-  )
-})
@@ -1,102 +0,0 @@
-import { describe, expect, test } from "bun:test"
-import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { AIError, LLMEvent, Media } from "../src/index.js"
-import { RequestExecutor } from "../src/route.js"
-import { AI } from "../src/promise.js"
-import { OpenAI } from "../src/providers.js"
-import { handlerLayer } from "./lib/http.js"
-import { sseEvents } from "./lib/sse.js"
-
-const openai = OpenAI.configure({ apiKey: "test", baseURL: "https://openai.test/v1" })
-
-const chatBody = sseEvents(
-  { choices: [{ delta: { content: "Hello" } }] },
-  { choices: [{ delta: { content: " world" } }] },
-  { choices: [{ delta: {}, finish_reason: "stop" }] },
-)
-
-/** Executor layer that answers chat completions with SSE text and image generations with one base64 PNG. */
-const executor = (seen: Array<string>) =>
-  RequestExecutor.layer.pipe(
-    Layer.provide(
-      handlerLayer((input) =>
-        Effect.gen(function* () {
-          const web = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-          seen.push(web.url)
-          if (web.url.endsWith("/images/generations"))
-            return input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }], output_format: "png" }), {
-              headers: { "content-type": "application/json" },
-            })
-          if (web.url.endsWith("/chat/completions"))
-            return input.respond(chatBody, { headers: { "content-type": "text/event-stream" } })
-          return input.respond(JSON.stringify({ error: { message: "not found" } }), {
-            status: 404,
-            headers: { "content-type": "application/json" },
-          })
-        }),
-      ),
-    ),
-  )
-
-describe("AI promise client", () => {
-  test("generates text, images, and streams over one managed runtime", async () => {
-    const seen: Array<string> = []
-    const ai = AI.make({ layer: executor(seen) })
-
-    const text = await ai.llm.generate({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })
-    expect(text.text).toBe("Hello world")
-
-    const image = await ai.image.generate({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" })
-    expect(image.image).toBeInstanceOf(Media.Asset)
-    expect(image.image.mediaType).toBe("image/png")
-    expect(await ai.run(image.image.bytes())).toEqual(Uint8Array.from([1, 2, 3]))
-
-    const deltas: Array<string> = []
-    for await (const event of ai.llm.stream({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })) {
-      if (LLMEvent.is.textDelta(event)) deltas.push(event.text)
-    }
-    expect(deltas).toEqual(["Hello", " world"])
-
-    const imageEvents: Array<string> = []
-    for await (const event of ai.image.stream({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" })) {
-      imageEvents.push(event.type)
-    }
-    expect(imageEvents).toEqual(["image", "finish"])
-
-    expect(seen).toEqual([
-      "https://openai.test/v1/chat/completions",
-      "https://openai.test/v1/images/generations",
-      "https://openai.test/v1/chat/completions",
-      "https://openai.test/v1/images/generations",
-    ])
-    await ai.dispose()
-  })
-
-  test("rethrows AIError unchanged and honors abort signals", async () => {
-    const ai = AI.make({ layer: executor([]) })
-
-    const failure = await ai.llm
-      .generate({ model: openai.responses("gpt-5"), prompt: "Hello" })
-      .then(() => undefined)
-      .catch((error: unknown) => error)
-    expect(failure).toBeInstanceOf(AIError)
-    expect(failure instanceof AIError && failure.reason.http?.status).toBe(404)
-
-    const controller = new AbortController()
-    controller.abort()
-    const aborted = await ai.llm
-      .generate({ model: openai.chat("gpt-4o-mini"), prompt: "Hello" }, { signal: controller.signal })
-      .then(() => "completed")
-      .catch(() => "aborted")
-    expect(aborted).toBe("aborted")
-
-    await ai.dispose()
-  })
-
-  test("the default client is created lazily and can be disposed", async () => {
-    expect(typeof AI.ai.llm.generate).toBe("function")
-    expect(typeof AI.ai.image.generate).toBe("function")
-    await AI.ai.dispose()
-  })
-})
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, LLMRequest, Message, ToolDefinition, Media } from "../../src/index.js"
+import { LLM, LLMEvent, LLMRequest, Message, ToolDefinition } from "../../src/index.js"
 import { Alibaba } from "../../src/providers.js"
 import { LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
@@ -65,7 +65,7 @@ for (const api of ["chat", "messages", "responses"] as const) {
              messages: [
                Message.user([
                  { type: "text", text: "Read the three words in this image. Reply with only the words in order." },
-                  { type: "media", media: Media.bytes(bytes, "image/png") },
+                  { type: "media", mediaType: "image/png", data: bytes },
                ]),
              ],
              generation: { maxTokens: 4096 },
@@ -1,17 +1,7 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import {
-  CacheHint,
-  LLM,
-  AIError,
-  LLMRequest,
-  Message,
-  ToolCallPart,
-  ToolDefinition,
-  Usage,
-  Media,
-} from "../../src/index.js"
+import { CacheHint, LLM, AIError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage } from "../../src/index.js"
 import { Auth, Endpoint, LLMClient, Route } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
 import * as AnthropicMessages from "../../src/protocols/anthropic-messages.js"
@@ -376,7 +366,7 @@ describe("Anthropic Messages route", () => {
          model: opus48,
          messages: [
            Message.user("Before."),
-            Message.make({ role: "system", content: { type: "media", media: Media.base64("AAECAw==", "image/png") } }),
+            Message.make({ role: "system", content: { type: "media", mediaType: "image/png", data: "AAECAw==" } }),
          ],
        }),
      ).pipe(Effect.flip)
@@ -2124,8 +2114,8 @@ describe("Anthropic Messages route", () => {
          messages: [
            Message.user([
              { type: "text", text: "What is in this image?" },
-              { type: "media", media: Media.base64("AAECAw==", "image/png") },
-              { type: "media", media: Media.base64("JVBERi0xLjQ=", "application/pdf"), filename: "report.pdf" },
+              { type: "media", mediaType: "image/png", data: "AAECAw==" },
+              { type: "media", mediaType: "application/pdf", data: "JVBERi0xLjQ=", filename: "report.pdf" },
            ]),
          ],
        }),
@@ -4,7 +4,6 @@ import { describe, expect } from "bun:test"
 import { Effect, Encoding, Ref, Schema, Stream } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
 import {
-  Media,
  CacheHint,
  GenerationOptions,
  type LanguageModel,
@@ -1679,10 +1678,10 @@ describe("Bedrock Converse route", () => {
          messages: [
            Message.user([
              { type: "text", text: "What is in this image?" },
-              { type: "media", media: Media.base64("AAAA", "image/png") },
-              { type: "media", media: Media.base64("BBBB", "image/jpeg") },
-              { type: "media", media: Media.base64("CCCC", "image/jpg") },
-              { type: "media", media: Media.base64("DDDD", "image/webp") },
+              { type: "media", mediaType: "image/png", data: "AAAA" },
+              { type: "media", mediaType: "image/jpeg", data: "BBBB" },
+              { type: "media", mediaType: "image/jpg", data: "CCCC" },
+              { type: "media", mediaType: "image/webp", data: "DDDD" },
            ]),
          ],
          cache: "none",
@@ -1713,9 +1712,7 @@ describe("Bedrock Converse route", () => {
        LLM.request({
          id: "req_image_bytes",
          model,
-          messages: [
-            Message.user([{ type: "media", media: Media.bytes(new Uint8Array([1, 2, 3, 4, 5]), "image/png") }]),
-          ],
+          messages: [Message.user([{ type: "media", mediaType: "image/png", data: new Uint8Array([1, 2, 3, 4, 5]) }])],
        }),
      )

@@ -1736,7 +1733,7 @@ describe("Bedrock Converse route", () => {
      const error = yield* compileRequest(
        LLM.request({
          model,
-          messages: [Message.user({ type: "media", media: Media.base64("not base64!", "image/png") })],
+          messages: [Message.user({ type: "media", mediaType: "image/png", data: "https://example.test/image.png" })],
        }),
      ).pipe(Effect.flip)

@@ -1745,25 +1742,6 @@ describe("Bedrock Converse route", () => {
    }),
  )

-  it.effect("rejects remote image URLs that were not materialized", () =>
-    Effect.gen(function* () {
-      const error = yield* compileRequest(
-        LLM.request({
-          model,
-          messages: [
-            Message.user({
-              type: "media",
-              media: Media.url("https://example.test/image.png", { mediaType: "image/png" }),
-            }),
-          ],
-        }),
-      ).pipe(Effect.flip)
-
-      expect(error).toMatchObject({ reason: { _tag: "InvalidRequest" } })
-      expect(error.message).toContain("requires inline media")
-    }),
-  )
-
  it.effect("lowers document media into Bedrock document blocks with format and name", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(
@@ -1774,8 +1752,8 @@ describe("Bedrock Converse route", () => {
          messages: [
            Message.user([
              { type: "text", text: "Summarize these documents." },
-              { type: "media", media: Media.base64("UERGREFUQQ==", "application/pdf"), filename: "report.pdf" },
-              { type: "media", media: Media.base64("Q1NWREFUQQ==", "text/csv"), filename: "data.csv" },
+              { type: "media", mediaType: "application/pdf", data: "UERGREFUQQ==", filename: "report.pdf" },
+              { type: "media", mediaType: "text/csv", data: "Q1NWREFUQQ==", filename: "data.csv" },
            ]),
          ],
        }),
@@ -1850,7 +1828,7 @@ describe("Bedrock Converse route", () => {
          messages: [
            Message.user([
              { type: "text", text: "Read this document" },
-              { type: "media", media: Media.base64("UERGREFUQQ==", "application/pdf"), filename: item.filename },
+              { type: "media", mediaType: "application/pdf", data: "UERGREFUQQ==", filename: item.filename },
            ]),
            Message.assistant([ToolCallPart.make({ id: "call_read", name: "read", input: {} })]),
            Message.tool({
@@ -1900,7 +1878,8 @@ describe("Bedrock Converse route", () => {
              { type: "text", text: "Read these documents" },
              ...["report_v1.txt", "report#v1.txt", "report v1 2.txt", "report v1.txt"].map((filename) => ({
                type: "media" as const,
-                media: Media.base64("SGVsbG8=", "text/plain"),
+                mediaType: "text/plain",
+                data: "SGVsbG8=",
                filename,
              })),
            ]),
@@ -1929,7 +1908,8 @@ describe("Bedrock Converse route", () => {
          messages: [
            Message.user({
              type: "media",
-              media: Media.base64("UERGREFUQQ==", "application/pdf"),
+              mediaType: "application/pdf",
+              data: "UERGREFUQQ==",
              filename: "report.pdf",
            }),
          ],
@@ -1959,7 +1939,8 @@ describe("Bedrock Converse route", () => {
              { type: "text", text: "Read these documents" },
              ...["report", undefined, 'report "final"\n.pdf'].map((filename) => ({
                type: "media" as const,
-                media: Media.base64("SGVsbG8=", "text/plain"),
+                mediaType: "text/plain",
+                data: "SGVsbG8=",
                filename,
              })),
            ]),
@@ -2056,7 +2037,7 @@ describe("Bedrock Converse route", () => {
      ).pipe(Effect.flip)

      expect(error).toMatchObject({ reason: { _tag: "InvalidRequest" } })
-      expect(error.message).toContain("requires inline media")
+      expect(error.message).toContain("Bedrock Converse media data must be valid base64")
    }),
  )

@@ -2066,7 +2047,7 @@ describe("Bedrock Converse route", () => {
        LLM.request({
          id: "req_bad_image",
          model,
-          messages: [Message.user([{ type: "media", media: Media.base64("x", "image/svg+xml") }])],
+          messages: [Message.user([{ type: "media", mediaType: "image/svg+xml", data: "x" }])],
        }),
      ).pipe(Effect.flip)

@@ -2080,9 +2061,7 @@ describe("Bedrock Converse route", () => {
        LLM.request({
          id: "req_bad_doc",
          model,
-          messages: [
-            Message.user([{ type: "media", media: Media.base64("x", "application/x-tar"), filename: "a.tar" }]),
-          ],
+          messages: [Message.user([{ type: "media", mediaType: "application/x-tar", data: "x", filename: "a.tar" }])],
        }),
      ).pipe(Effect.flip)

@@ -1,96 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { Evaluation, EvaluationModel, type EvaluationOptions } from "../../src/experimental.js"
-import { OpenCodeZen, OpenRouter, TypeSafeAI } from "../../src/providers.js"
-import { recordedTests } from "../recorded-test.js"
-
-const questions = {
-  department: {
-    type: "choice",
-    instructions: "Which team should handle this support request?",
-    criteria: {
-      billing: "Payments, invoices, refunds, or failed charges",
-      technical: "Bugs, outages, or integrations",
-      sales: "Pricing, upgrades, or new accounts",
-    },
-  },
-  urgency: {
-    type: "score",
-    instructions: "How urgent is this support request?",
-    criteria: ["Can wait for normal support", "Needs prompt attention", "Actively blocking revenue"],
-  },
-  refund: { type: "boolean", instructions: "Is the customer asking for a refund?" },
-} as const
-
-const state = "I was charged twice for the same invoice. Please refund the duplicate payment today."
-
-const typesafe = recordedTests({
-  prefix: "typesafe-evaluation",
-  provider: "typesafe-ai",
-  protocol: "system-one",
-  requires: ["TYPESAFE_API_KEY"],
-  metadata: { model: "jev-latest" },
-})
-
-const zen = recordedTests({
-  prefix: "opencode-zen-evaluation",
-  provider: "opencode",
-  protocol: "system-one",
-  requires: ["OPENCODE_API_KEY"],
-  metadata: { model: "jev-1.13-free" },
-})
-
-const openrouter = recordedTests({
-  prefix: "openrouter-evaluation",
-  provider: "openrouter",
-  protocol: "system-one",
-  requires: ["OPENROUTER_API_KEY"],
-  metadata: { model: "typesafe/jev-1.13" },
-})
-
-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",
-    ),
-  )
-
-  zen.effect("evaluates choice score and boolean questions", () =>
-    assertEvaluation(
-      OpenCodeZen.configure({ apiKey: process.env.OPENCODE_API_KEY ?? "fixture" }).experimental.evaluation(
-        "jev-1.13-free",
-      ),
-      "opencode",
-    ),
-  )
-
-  openrouter.effect("evaluates choice score and boolean questions", () =>
-    assertEvaluation(
-      OpenRouter.configure({ apiKey: process.env.OPENROUTER_API_KEY ?? "fixture" }).experimental.evaluation(
-        "typesafe/jev-1.13",
-      ),
-      "openrouter",
-    ),
-  )
-})
-
-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-")
-    expect(response.answers.department.type).toBe("choice")
-    expect(response.answers.department.choice).toBe("billing")
-    expect(response.answers.department.probabilities?.billing).toBeGreaterThan(0.5)
-    expect(response.answers.urgency.type).toBe("score")
-    expect(response.answers.urgency.score).toBeGreaterThanOrEqual(0)
-    expect(response.answers.urgency.score).toBeLessThanOrEqual(2)
-    expect(response.answers.refund.type).toBe("boolean")
-    expect(response.answers.refund.probability).toBeGreaterThan(0.5)
-    expect(response.usage?.inputTokens).toBeGreaterThan(0)
-    expect(response.usage?.outputTokens).toBeGreaterThan(0)
-    expect(response.providerMetadata?.[metadataKey]?.confidence).toBeDefined()
-  })
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, AIError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage, Media } from "../../src/index.js"
+import { LLM, AIError, LLMRequest, Message, ToolCallPart, ToolDefinition, Usage } from "../../src/index.js"
 import { Auth, LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
 import * as Gemini from "../../src/protocols/gemini.js"
@@ -340,8 +340,8 @@ describe("Gemini route", () => {
          messages: [
            Message.user([
              { type: "text", text: "What is in this image?" },
-              { type: "media", media: Media.base64("AAECAw==", "image/png") },
-              { type: "media", media: Media.base64("JVBERi0xLjQ=", "application/pdf") },
+              { type: "media", mediaType: "image/png", data: "AAECAw==" },
+              { type: "media", mediaType: "application/pdf", data: "JVBERi0xLjQ=" },
            ]),
            Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
            Message.tool({ id: "call_1", name: "lookup", result: { forecast: "sunny" } }),
@@ -446,7 +446,7 @@ describe("Gemini route", () => {
        LLM.request({
          model,
          messages: [
-            Message.user({ type: "media", media: Media.fromDataUrl("data:image/png;base64,AAEC") }),
+            Message.user({ type: "media", mediaType: "image/png", data: "data:image/png;base64,AAEC" }),
            Message.tool({
              id: "call_image",
              name: "read",
@@ -636,9 +636,9 @@ describe("Gemini route", () => {
          model,
          messages: [
            Message.user([
-              { type: "media", media: Media.base64("%%%=", "image/png") },
-              { type: "media", media: Media.fromDataUrl("data:image/jpeg;base64,/9j/") },
-              { type: "media", media: Media.base64("PHN2Zz4=", "image/svg+xml") },
+              { type: "media", mediaType: "image/png", data: "%%%=" },
+              { type: "media", mediaType: "image/png", data: "data:image/jpeg;base64,/9j/" },
+              { type: "media", mediaType: "image/svg+xml", data: "PHN2Zz4=" },
            ]),
          ],
        }),
@@ -648,7 +648,7 @@ describe("Gemini route", () => {
          role: "user",
          parts: [
            { inlineData: { mimeType: "image/png", data: "%%%=" } },
-            { inlineData: { mimeType: "image/jpeg", data: "/9j/" } },
+            { inlineData: { mimeType: "image/png", data: "/9j/" } },
            { inlineData: { mimeType: "image/svg+xml", data: "PHN2Zz4=" } },
          ],
        },
@@ -1773,34 +1773,19 @@ describe("Gemini route", () => {
    }),
  )

-  it.effect("replays generated assistant media as model inline data", () =>
+  it.effect("rejects unsupported assistant media content", () =>
    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
+      const error = yield* compileRequest(
        LLM.request({
          id: "req_media",
          model,
-          messages: [
-            Message.user("Draw a cat"),
-            Message.assistant([
-              { type: "text", text: "Here you go." },
-              {
-                type: "media",
-                media: Media.base64("AAECAw==", "image/png"),
-                providerMetadata: { google: { thoughtSignature: "sig_1" } },
-              },
-            ]),
-            Message.user("Now make it orange"),
-          ],
+          messages: [Message.assistant({ type: "media", mediaType: "image/png", data: "AAECAw==" })],
        }),
-      )
+      ).pipe(Effect.flip)

-      expect(prepared.body.contents[1]).toEqual({
-        role: "model",
-        parts: [
-          { text: "Here you go." },
-          { inlineData: { mimeType: "image/png", data: "AAECAw==" }, thoughtSignature: "sig_1" },
-        ],
-      })
+      expect(error.message).toContain(
+        "Gemini assistant messages only support text, reasoning, and tool-call content for now",
+      )
    }),
  )
 })
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { Image, Media } from "../../src/index.js"
+import { Image, ImageInput } from "../../src/index.js"
 import { Google } from "../../src/providers.js"
 import { dimensions } from "../lib/image.js"
 import { recordedTests } from "../recorded-test.js"
@@ -22,12 +22,13 @@ describe("Google Images recorded", () => {
      const response = yield* Image.generate({
        model,
        prompt: "A simple flat blue circle centered on a plain white background.",
-        aspectRatio: "1:1",
+        options: { aspectRatio: "1:1" },
      })

      expect(response.images).toHaveLength(1)
-      expect(response.image.mediaType).toMatch(/^image\//)
-      expect((yield* response.image.bytes()).length).toBeGreaterThan(0)
+      expect(response.image?.mediaType).toMatch(/^image\//)
+      expect(response.image?.data).toBeInstanceOf(Uint8Array)
+      expect(response.image?.data.length).toBeGreaterThan(0)
    }),
  )

@@ -38,16 +39,18 @@ describe("Google Images recorded", () => {
        prompt:
          "Transform this minimal source into a bright orange sun icon with eight rounded rays on a pale blue background.",
        images: [
-          Media.bytes(
+          ImageInput.bytes(
            yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
            "image/jpeg",
          ),
        ],
-        aspectRatio: "1:1",
+        options: { aspectRatio: "1:1" },
      })

-      expect(response.image.mediaType).toBe("image/jpeg")
-      expect(dimensions(yield* response.image.bytes())).toEqual({ width: 1024, height: 1024 })
+      expect(response.image?.mediaType).toBe("image/jpeg")
+      expect(response.image?.data).toBeInstanceOf(Uint8Array)
+      if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected owned Google image bytes")
+      expect(dimensions(response.image.data)).toEqual({ width: 1024, height: 1024 })
    }),
  )
 })
@@ -114,7 +114,7 @@ describe("Google Vertex providers", () => {
    }),
  )

-  it.effect("preserves function call ids in lowered Vertex bodies", () =>
+  it.effect("strips function call ids Vertex does not accept from lowered bodies", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(
        LLM.request({
@@ -142,14 +142,15 @@ describe("Google Vertex providers", () => {
        }),
      )

+      expect(JSON.stringify(prepared.body.contents)).not.toContain('"id"')
      expect(prepared.body.contents).toMatchObject([
-        { role: "model", parts: [{ functionCall: { id: "call_1", name: "lookup", args: { query: "weather" } } }] },
+        { role: "model", parts: [{ functionCall: { id: undefined, name: "lookup", args: { query: "weather" } } }] },
        {
          role: "user",
          parts: [
            {
              functionResponse: {
-                id: "call_1",
+                id: undefined,
                name: "lookup",
                response: { name: "lookup", content: "sunny" },
              },
@@ -234,23 +235,12 @@ describe("Google Vertex providers", () => {
          parts: [
            { text: "Thinking.", thought: true, thoughtSignature: "reasoning_sig" },
            { text: "Checking.", thoughtSignature: "text_sig" },
-            {
-              functionCall: { id: "provider_call_1", name: "lookup", args: { query: "weather" } },
-              thoughtSignature: "tool_sig",
-            },
+            { functionCall: { name: "lookup", args: { query: "weather" } }, thoughtSignature: "tool_sig" },
          ],
        },
        {
          role: "user",
-          parts: [
-            {
-              functionResponse: {
-                id: "provider_call_1",
-                name: "lookup",
-                response: { name: "lookup", content: "sunny" },
-              },
-            },
-          ],
+          parts: [{ functionResponse: { name: "lookup", response: { name: "lookup", content: "sunny" } } }],
        },
      ])
    }),
@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect, Schema } from "effect"
-import { LLM, Media, Message } from "../../src/index.js"
+import { LLM, Message } from "../../src/index.js"
 import { OpenAI, Azure, XAI } from "../../src/providers.js"
 import { compileRequest } from "../../src/route/client.js"
 import { it } from "../lib/effect.js"
@@ -16,7 +16,8 @@ for (const model of [
      const message = Message.user(
        details.map((detail) => ({
          type: "media",
-          media: Media.url("https://example.com/image.png", { mediaType: "image/png" }),
+          mediaType: "image/png",
+          data: "https://example.com/image.png",
          providerMetadata:
            detail === undefined ? undefined : { [model.route.providerMetadataKey ?? model.provider]: { detail } },
        })),
@@ -47,7 +48,8 @@ it.effect("rejects malformed image detail instead of silently discarding it", ()
        messages: [
          Message.user({
            type: "media",
-            media: Media.url("https://example.com/image.png", { mediaType: "image/png" }),
+            mediaType: "image/png",
+            data: "https://example.com/image.png",
            providerMetadata: { openai: { detail: 42 } },
          }),
        ],
@@ -1,7 +1,7 @@
 import { expect } from "bun:test"
 import { Effect, Layer } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { Image, ImageClient, LLM, LLMEvent, LLMRequest, Media, Message, ToolDefinition } from "../../src/index.js"
+import { Image, ImageClient, ImageInput, LLM, LLMEvent, LLMRequest, Message, ToolDefinition } from "../../src/index.js"
 import { Meta } from "../../src/providers/meta.js"
 import { MetaMessages } from "../../src/protocols/meta-messages.js"
 import { AnthropicMessages } from "../../src/protocols/anthropic-messages.js"
@@ -73,9 +73,9 @@ it.effect("Meta Images preserves request overlays, bearer auth, JSON edit inputs
        headers: { "x-client": "test" },
      }).image("muse-image-1.0"),
      prompt: "Edit",
-      images: [Media.bytes(Uint8Array.from([1, 2, 3]), "image/png")],
-      format: "webp",
-      providerOptions: {
+      images: [ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png")],
+      options: {
+        outputFormat: "webp",
        responseFormat: "url",
        reasoningStrength: "low",
        toolEnablement: { enable_web_search: false },
@@ -83,12 +83,8 @@ it.effect("Meta Images preserves request overlays, bearer auth, JSON edit inputs
      },
      http: { body: { output_format: "jpeg", future_option: true }, query: { trace: "1" } },
    })
-    expect(response.image.mediaType).toBe("image/jpeg")
-    expect(response.image.source).toEqual({
-      type: "url",
-      url: "https://images.example/result.jpg",
-      mediaType: "image/jpeg",
-    })
+    expect(response.image?.mediaType).toBe("image/jpeg")
+    expect(response.image?.data).toBe("https://images.example/result.jpg")
  }).pipe(
    Effect.provide(
      ImageClient.layer.pipe(
@@ -125,7 +121,7 @@ it.effect("Meta Images validates the final output format before sending the requ
    const error = yield* Image.generate({
      model: Meta.configure({ apiKey: "fixture" }).image("muse-image-1.0"),
      prompt: "Draw",
-      format: "png",
+      options: { outputFormat: "png" },
      http: { body: { output_format: 42 } },
    }).pipe(Effect.flip)
    expect(error.reason._tag).toBe("InvalidRequest")
@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect } from "effect"
-import { Image, LLM, LLMEvent, LLMRequest, Media, Message } from "../../src/index.js"
+import { Image, ImageInput, LLM, LLMEvent, LLMRequest, Message } from "../../src/index.js"
 import { Meta } from "../../src/providers/meta.js"
 import { LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
@@ -28,16 +28,15 @@ recorded.effect.with(
      const response = yield* Image.generate({
        model: meta.image(modelID),
        prompt: "A flat black square centered on a plain white background. No text.",
-        n: 1,
-        size: "256x256",
-        providerOptions: controls,
+        options: { ...controls, n: 1, size: "256x256" },
      })
      expect(response.images).toHaveLength(1)
-      expect(response.image.mediaType).toBe("image/webp")
-      const bytes = yield* response.image.bytes()
-      expect(new TextDecoder().decode(bytes.slice(0, 4))).toBe("RIFF")
-      expect(new TextDecoder().decode(bytes.slice(8, 12))).toBe("WEBP")
-      expect(response.usage?.type === "tokens" ? response.usage.output : undefined).toBeGreaterThan(0)
+      expect(response.image?.mediaType).toBe("image/webp")
+      expect(response.image?.data).toBeInstanceOf(Uint8Array)
+      if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected image bytes")
+      expect(new TextDecoder().decode(response.image.data.slice(0, 4))).toBe("RIFF")
+      expect(new TextDecoder().decode(response.image.data.slice(8, 12))).toBe("WEBP")
+      expect(response.usage?.outputTokens).toBeGreaterThan(0)
    }),
  180_000,
 )
@@ -51,18 +50,16 @@ recorded.effect.with(
        model: meta.image(modelID),
        prompt: "Change the shape to bright purple. Keep the plain white background.",
        images: [
-          Media.bytes(
+          ImageInput.bytes(
            yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
            "image/jpeg",
          ),
        ],
-        n: 1,
-        size: "256x256",
-        format: "png",
-        providerOptions: controls,
+        options: { ...controls, n: 1, outputFormat: "png", size: "256x256" },
      })
-      expect(response.image.mediaType).toBe("image/png")
-      expect(Array.from((yield* response.image.bytes()).slice(0, 8))).toEqual([137, 80, 78, 71, 13, 10, 26, 10])
+      expect(response.image?.mediaType).toBe("image/png")
+      if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected image bytes")
+      expect(Array.from(response.image.data.slice(0, 8))).toEqual([137, 80, 78, 71, 13, 10, 26, 10])
    }),
  180_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, ToolDefinition, Media } from "../../src/index.js"
+import { LLM, LLMEvent, Message, ToolDefinition } from "../../src/index.js"
 import { Mistral } from "../../src/providers/index.js"
 import { MistralChat } from "../../src/protocols/index.js"
 import { LLMClient } from "../../src/route.js"
@@ -46,8 +46,8 @@ describe("Mistral Chat", () => {
            Message.system("Updated"),
            Message.user([
              { type: "text", text: "Inspect" },
-              { type: "media", media: Media.base64("aW1hZ2U=", "image/png") },
-              { type: "media", media: Media.base64("cGRm", "application/pdf") },
+              { type: "media", mediaType: "image/png", data: "aW1hZ2U=" },
+              { type: "media", mediaType: "application/pdf", data: "cGRm" },
            ]),
            Message.assistant([
              { type: "reasoning", text: "Think" },
@@ -230,7 +230,8 @@ describe("Mistral Chat", () => {
          messages: [
            Message.user({
              type: "media",
-              media: Media.url("https://assets.example.test/input.png", { mediaType: "image/png" }),
+              mediaType: "image/png",
+              data: "https://assets.example.test/input.png",
            }),
            Message.tool({
              id: "Ab12Cd34E",
@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, Message, ToolDefinition, Media } from "../../src/index.js"
+import { LLM, LLMEvent, Message, ToolDefinition } from "../../src/index.js"
 import { Moonshot } from "../../src/providers.js"
 import { LLMClient } from "../../src/route.js"
 import { recordedTests } from "../recorded-test.js"
@@ -85,7 +85,7 @@ for (const api of ["chat", "messages", "responses"] as const) {
            messages: [
              Message.user([
                { type: "text", text: "Read the three words in this image. Reply only with those words in order." },
-                { type: "media", media: Media.bytes(image, "image/png") },
+                { type: "media", mediaType: "image/png", data: image },
              ]),
            ],
            generation: { maxTokens: 4096 },
@@ -2,7 +2,6 @@ import { describe, expect } from "bun:test"
 import { Effect, Ref, Schema, Stream } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
 import {
-  Media,
  HttpOptions,
  LLM,
  AIError,
@@ -687,7 +686,7 @@ describe("OpenAI Chat route", () => {
        LLM.request({
          model,
          messages: [
-            Message.user({ type: "media", media: Media.base64("AAEC", "image/png") }),
+            Message.user({ type: "media", mediaType: "image/png", data: "AAEC" }),
            Message.system("Keep the image."),
          ],
        }),
@@ -711,9 +710,9 @@ describe("OpenAI Chat route", () => {
          model,
          messages: [
            Message.user([
-              { type: "media", media: Media.base64("not-base64", "image/png") },
-              { type: "media", media: Media.fromDataUrl("data:image/jpeg;base64,/9j/") },
-              { type: "media", media: Media.base64("PHN2Zz4=", "image/svg+xml") },
+              { type: "media", mediaType: "image/png", data: "not-base64" },
+              { type: "media", mediaType: "image/png", data: "data:image/jpeg;base64,/9j/" },
+              { type: "media", mediaType: "image/svg+xml", data: "PHN2Zz4=" },
            ]),
          ],
        }),
@@ -737,7 +736,7 @@ describe("OpenAI Chat route", () => {
      const prepared = yield* compileRequest(
        LLM.request({
          model,
-          prompt: urls.map((url) => Message.media(Media.url(url, { mediaType: "image/png" }))),
+          prompt: urls.map((data) => ({ type: "media" as const, mediaType: "image/png", data })),
        }),
      )
      expect(prepared.body.messages).toEqual([
@@ -784,7 +783,7 @@ describe("OpenAI Chat route", () => {
      const error = yield* compileRequest(
        LLM.request({
          model,
-          messages: [Message.user({ type: "media", media: Media.base64("AAECAw==", "audio/mpeg") })],
+          messages: [Message.user({ type: "media", mediaType: "audio/mpeg", data: "AAECAw==" })],
        }),
      ).pipe(Effect.flip)
      expect(error.message).toContain("OpenAI Chat does not support media type audio/mpeg")
@@ -799,8 +798,8 @@ describe("OpenAI Chat route", () => {
          model,
          messages: [
            Message.user([
-              { type: "media", media: Media.base64("AAECAw==", "image/png") },
-              { type: "media", media: Media.fromDataUrl("data:image/jpeg;base64,/9j/") },
+              { type: "media", mediaType: "image/png", data: "AAECAw==" },
+              { type: "media", mediaType: "image/jpeg", data: "data:image/jpeg;base64,/9j/" },
            ]),
          ],
        }),
@@ -1182,9 +1181,7 @@ describe("OpenAI Chat route", () => {
    }),
  )

-  // Only recognized detail shapes are retained and replayed; echoing an
-  // undocumented provider payload is what breaks follow-up requests.
-  it.effect("drops unknown reasoning details while using scalar display text", () =>
+  it.effect("preserves unknown reasoning details while using scalar display text", () =>
    Effect.gen(function* () {
      const details = [{ type: "reasoning.future", format: "provider-v2", state: { opaque: true } }]
      const response = yield* LLMClient.generate(request).pipe(
@@ -1201,195 +1198,16 @@ describe("OpenAI Chat route", () => {

      expect(response.reasoning).toBe("thinking")
      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
-        openai: { reasoningField: "reasoning", reasoningDetails: [] },
+        openai: { reasoningField: "reasoning", reasoningDetails: details },
      })

      const replay = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
      expect(replay.body.messages).toEqual([
-        { role: "assistant", content: "Hello", reasoning: "thinking", reasoning_details: [] },
+        { role: "assistant", content: "Hello", reasoning: "thinking", reasoning_details: details },
      ])
    }),
  )

-  // Kimi's coding endpoint streams the full thinking through `reasoning_content`
-  // and a separate summary + encrypted blob through its own `reasoning_details`
-  // dialect. The stream-only `index` must not be echoed back.
-  it.effect("merges Kimi summary deltas by index and replays details without the streaming index", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(request).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents(
-              { choices: [{ delta: { reasoning_content: "Let me" } }] },
-              { choices: [{ delta: { reasoning_content: " think" } }] },
-              { choices: [{ delta: { reasoning_details: [{ index: 0, type: "summary", summary: "Plan" }] } }] },
-              { choices: [{ delta: { reasoning_details: [{ index: 0, type: "summary", summary: " tools" }] } }] },
-              { choices: [{ delta: { reasoning_details: [{ index: 1, type: "encrypted", encrypted: "opaque" }] } }] },
-              {
-                choices: [
-                  {
-                    delta: {
-                      tool_calls: [
-                        { index: 0, id: "call_1", type: "function", function: { name: "get_time", arguments: "{}" } },
-                      ],
-                    },
-                  },
-                ],
-              },
-              { choices: [{ delta: {}, finish_reason: "tool_calls" }] },
-            ),
-          ),
-        ),
-      )
-
-      const stored = [
-        { index: 0, type: "summary", summary: "Plan tools" },
-        { index: 1, type: "encrypted", encrypted: "opaque" },
-      ]
-      expect(response.reasoning).toBe("Let me think")
-      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
-        openai: { reasoningField: "reasoning_content", reasoningDetails: stored },
-      })
-
-      const replay = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
-      expect(replay.body.messages).toEqual([
-        {
-          role: "assistant",
-          content: null,
-          tool_calls: [{ id: "call_1", type: "function", function: { name: "get_time", arguments: "{}" } }],
-          reasoning_content: "Let me think",
-          reasoning_details: [
-            { type: "summary", summary: "Plan tools" },
-            { type: "encrypted", encrypted: "opaque" },
-          ],
-        },
-      ])
-    }),
-  )
-
-  it.effect("displays Kimi summaries and replays reasoning_content when no scalar reasoning streams", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(request).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents(
-              { choices: [{ delta: { reasoning_details: [{ index: 0, type: "summary", summary: "Plan" }] } }] },
-              { choices: [{ delta: { reasoning_details: [{ index: 0, type: "summary", summary: " tools" }] } }] },
-              { choices: [{ delta: { reasoning_details: [{ index: 1, type: "encrypted", encrypted: "opaque" }] } }] },
-              { choices: [{ delta: { content: "Hello" } }] },
-              { choices: [{ delta: {}, finish_reason: "stop" }] },
-            ),
-          ),
-        ),
-      )
-
-      expect(response.reasoning).toBe("Plan tools")
-
-      const replay = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
-      expect(replay.body.messages).toEqual([
-        {
-          role: "assistant",
-          content: "Hello",
-          reasoning_content: "Plan tools",
-          reasoning_details: [
-            { type: "summary", summary: "Plan tools" },
-            { type: "encrypted", encrypted: "opaque" },
-          ],
-        },
-      ])
-    }),
-  )
-
-  // Sessions persisted before the fix already hold Kimi details with `index`.
-  it.effect("strips the streaming index from previously stored Kimi details", () =>
-    Effect.gen(function* () {
-      const replay = yield* compileRequest(
-        LLM.request({
-          model,
-          messages: [
-            Message.assistant([
-              {
-                type: "reasoning",
-                text: "thinking",
-                providerMetadata: {
-                  openai: {
-                    reasoningField: "reasoning_content",
-                    reasoningDetails: [
-                      { index: 0, type: "summary", summary: "thinking" },
-                      { index: 1, type: "encrypted", encrypted: "opaque" },
-                    ],
-                  },
-                },
-              },
-            ]),
-          ],
-        }),
-      )
-
-      expect(replay.body.messages).toEqual([
-        {
-          role: "assistant",
-          content: "",
-          reasoning_content: "thinking",
-          reasoning_details: [
-            { type: "summary", summary: "thinking" },
-            { type: "encrypted", encrypted: "opaque" },
-          ],
-        },
-      ])
-    }),
-  )
-
-  it.effect("merges consecutive OpenRouter summary deltas and replays them unmodified", () =>
-    Effect.gen(function* () {
-      const merged = [
-        { type: "reasoning.summary", summary: "Plan tools", format: "openai-responses-v1", index: 0 },
-        { type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 0 },
-      ]
-      const response = yield* LLMClient.generate(request).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents(
-              {
-                choices: [
-                  {
-                    delta: {
-                      reasoning_details: [
-                        { type: "reasoning.summary", summary: "Plan", format: "openai-responses-v1", index: 0 },
-                      ],
-                    },
-                  },
-                ],
-              },
-              {
-                choices: [
-                  {
-                    delta: {
-                      reasoning_details: [
-                        { type: "reasoning.summary", summary: " tools", format: "openai-responses-v1", index: 0 },
-                      ],
-                    },
-                  },
-                ],
-              },
-              { choices: [{ delta: { reasoning_details: [merged[1]] } }] },
-              { choices: [{ delta: { content: "Hello" } }] },
-              { choices: [{ delta: {}, finish_reason: "stop" }] },
-            ),
-          ),
-        ),
-      )
-
-      expect(response.reasoning).toBe("Plan tools")
-      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
-        openai: { reasoningDetails: merged },
-      })
-
-      const replay = yield* compileRequest(LLM.request({ model, messages: [response.message] }))
-      expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", reasoning_details: merged }])
-    }),
-  )
-
  it.effect("uses scalar display text for signature-only reasoning details", () =>
    Effect.gen(function* () {
      const details = [{ type: "reasoning.text", signature: "signed", format: "provider-v2", index: 0 }]
@@ -375,27 +375,6 @@ describe("OpenAI-compatible Chat route", () => {
    }),
  )

-  it.effect("ignores bare null frames between deltas", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(request).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents(
-              deltaChunk({ role: "assistant", content: "Hello" }),
-              "null",
-              deltaChunk({ content: "!" }),
-              "null",
-              deltaChunk({}, "stop"),
-            ),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello!")
-      expect(response.finishReason).toEqual({ normalized: "stop", raw: "stop" })
-    }),
-  )
-
  it.effect("accepts nullable usage and preserves provider fields", () =>
    Effect.gen(function* () {
      const response = yield* LLMClient.generate(request).pipe(
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, Message, ToolDefinition, Media } from "../../src/index.js"
+import { LLM, LLMEvent, Message, ToolDefinition } from "../../src/index.js"
 import { configure } from "../../src/providers/openai-compatible-responses.js"
 import { OpenAI } from "../../src/providers.js"
 import { OpenResponses } from "../../src/protocols/open-responses.js"
@@ -129,7 +129,7 @@ describe("Open Responses-compatible route", () => {
        LLM.request({
          model,
          messages: [
-            Message.user([{ type: "media", media: Media.fromDataUrl(pdf), filename: "input.pdf" }]),
+            Message.user([{ type: "media", mediaType: "application/pdf", data: pdf, filename: "input.pdf" }]),
            Message.assistant({ type: "tool-call", id: "call_1", name: "read", input: {} }),
            Message.tool({
              id: "call_1",
@@ -393,33 +393,6 @@ describe("Open Responses-compatible route", () => {
    }),
  )

-  it.effect("ignores bare null frames between events", () =>
-    Effect.gen(function* () {
-      const model = configure({
-        apiKey: "test-key",
-        baseURL: "https://responses.example.test/v1",
-      }).model("example-model")
-      const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents(
-              { type: "response.output_item.added", output_index: 0, item: { type: "message", id: "msg_1" } },
-              "null",
-              { type: "response.output_text.delta", output_index: 0, item_id: "msg_1", delta: "Hello" },
-              "null",
-              { type: "response.output_item.done", output_index: 0, item: { type: "message", id: "msg_1" } },
-              { type: "response.completed", response: { id: "resp_1" } },
-              "null",
-            ),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello")
-      expect(response.events.at(-1)).toMatchObject({ type: "finish" })
-    }),
-  )
-
  describe("stream validation", () => {
    const request = LLM.request({
      model: configure({ apiKey: "test-key", baseURL: "https://responses.example.test/v1" }).model("example-model"),
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { Image, Media } from "../../src/index.js"
+import { Image, ImageInput } from "../../src/index.js"
 import { OpenAI } from "../../src/providers.js"
 import { dimensions } from "../lib/image.js"
 import { recordedTests } from "../recorded-test.js"
@@ -22,14 +22,13 @@ describe("OpenAI Images recorded", () => {
      const response = yield* Image.generate({
        model,
        prompt: "A simple flat black circle centered on a plain white background.",
-        size: "1024x1024",
-        format: "jpeg",
-        providerOptions: { quality: "low", outputCompression: 10 },
+        options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
      })

      expect(response.images).toHaveLength(1)
-      expect(response.image.mediaType).toBe("image/jpeg")
-      expect((yield* response.image.bytes()).length).toBeGreaterThan(0)
+      expect(response.image?.mediaType).toBe("image/jpeg")
+      expect(response.image?.data).toBeInstanceOf(Uint8Array)
+      expect(response.image?.data.length).toBeGreaterThan(0)
    }),
  )

@@ -46,18 +45,18 @@ describe("OpenAI Images recorded", () => {
          model,
          prompt: "Keep the simple shape and change it from black to bright green.",
          images: [
-            Media.bytes(
+            ImageInput.bytes(
              yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
              "image/jpeg",
            ),
          ],
-          size: "1024x1024",
-          format: "jpeg",
-          providerOptions: { quality: "low", outputCompression: 10 },
+          options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
        })

-        expect(response.image.mediaType).toBe("image/jpeg")
-        expect(dimensions(yield* response.image.bytes())).toEqual({ width: 1024, height: 1024 })
+        expect(response.image?.mediaType).toBe("image/jpeg")
+        expect(response.image?.data).toBeInstanceOf(Uint8Array)
+        if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected owned OpenAI image bytes")
+        expect(dimensions(response.image.data)).toEqual({ width: 1024, height: 1024 })
      }),
  )
 })
@@ -2,7 +2,6 @@ import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect, Layer, Logger, Ref, Schema, Stream } from "effect"
 import { Headers, HttpClientRequest } from "effect/unstable/http"
 import {
-  Media,
  LLM,
  AIError,
  HttpContext,
@@ -4617,30 +4616,6 @@ describe("OpenAI Responses route", () => {
    }),
  )

-  it.effect("replays assistant media parts as portable user image input", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model,
-          messages: [
-            Message.user("Draw a cat"),
-            Message.assistant([
-              { type: "text", text: "Here it is." },
-              { type: "media", media: Media.base64("AQID", "image/png") },
-            ]),
-            Message.user("Make it orange"),
-          ],
-        }),
-      )
-      expect(prepared.body.input).toMatchObject([
-        { type: "message", role: "user" },
-        { type: "message", role: "assistant", content: [{ type: "output_text", text: "Here it is." }] },
-        { type: "message", role: "user", content: [{ type: "input_image", image_url: "data:image/png;base64,AQID" }] },
-        { type: "message", role: "user" },
-      ])
-    }),
-  )
-
  it.effect("replays hosted image results as portable content regardless of storage", () =>
    Effect.gen(function* () {
      const item = {
@@ -4802,8 +4777,8 @@ describe("OpenAI Responses route", () => {
          model,
          messages: [
            Message.user([
-              { type: "media", media: Media.base64("AAECAw==", "image/png") },
-              { type: "media", media: Media.base64("JVBERi0xLjQ=", "application/pdf"), filename: "report.pdf" },
+              { type: "media", mediaType: "image/png", data: "AAECAw==" },
+              { type: "media", mediaType: "application/pdf", data: "JVBERi0xLjQ=", filename: "report.pdf" },
            ]),
          ],
        }),
@@ -4834,7 +4809,8 @@ describe("OpenAI Responses route", () => {
          messages: [
            Message.user({
              type: "media",
-              media: Media.fromDataUrl("data:application/pdf;base64,JVBERi0xLjQ="),
+              mediaType: "application/pdf",
+              data: "data:application/pdf;base64,JVBERi0xLjQ=",
              filename: "report.pdf",
            }),
          ],
@@ -4863,7 +4839,7 @@ describe("OpenAI Responses route", () => {
        LLM.request({
          id: "req_media",
          model,
-          messages: [Message.user({ type: "media", media: Media.base64("AAECAw==", "application/x-tar") })],
+          messages: [Message.user({ type: "media", mediaType: "application/x-tar", data: "AAECAw==" })],
        }),
      )

@@ -4890,10 +4866,11 @@ describe("OpenAI Responses route", () => {
          model,
          messages: [
            Message.user([
-              { type: "media", media: Media.url("https://example.com/image.png", { mediaType: "image/png" }) },
+              { type: "media", mediaType: "image/png", data: "https://example.com/image.png" },
              {
                type: "media",
-                media: Media.url("https://example.com/report.pdf", { mediaType: "application/pdf" }),
+                mediaType: "application/pdf",
+                data: "https://example.com/report.pdf",
                filename: "report.pdf",
              },
            ]),
@@ -315,9 +315,10 @@ describe("OpenRouter", () => {
    }),
  )

-  it.effect("drops unrecognized details and preserves duplicate continuation details", () =>
+  it.effect("preserves opaque and duplicate continuation details", () =>
    Effect.gen(function* () {
      const details = [
+        { type: "reasoning.future", format: "provider-v2", state: { opaque: true } },
        { type: "reasoning.encrypted", id: "state", data: "opaque" },
        { type: "reasoning.encrypted", id: "state", data: "opaque" },
      ]
@@ -329,15 +330,7 @@ describe("OpenRouter", () => {
            Message.assistant({
              type: "reasoning",
              text: "Thinking",
-              providerMetadata: {
-                openrouter: {
-                  reasoningField: "reasoning",
-                  reasoningDetails: [
-                    { type: "reasoning.future", format: "provider-v2", state: { opaque: true } },
-                    ...details,
-                  ],
-                },
-              },
+              providerMetadata: { openrouter: { reasoningField: "reasoning", reasoningDetails: details } },
            }),
          ],
        }),
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect, Schema, Stream } from "effect"
-import { LLM, LLMResponse, Message, ToolDefinition, type LanguageModel, Media } from "../../src/index.js"
+import { LLM, LLMResponse, Message, ToolDefinition, type LanguageModel } from "../../src/index.js"
 import { AmazonBedrock, Anthropic, Google, OpenAI, XAI } from "../../src/providers.js"
 import { LLMClient } from "../../src/route.js"
 import { Tool } from "../../src/tool.js"
@@ -131,7 +131,7 @@ describe("PDF recorded", () => {
              generation: { maxTokens: target.maxTokens, temperature: 0 },
              messages: [
                Message.user([
-                  { type: "media", media: Media.base64(PDF, "application/pdf"), filename: target.filename },
+                  { type: "media", mediaType: "application/pdf", data: PDF, filename: target.filename },
                  { type: "text", text: prompt },
                ]),
              ],
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { Image, Media } from "../../src/index.js"
+import { Image, ImageInput } from "../../src/index.js"
 import { XAI } from "../../src/providers.js"
 import { dimensions } from "../lib/image.js"
 import { recordedTests } from "../recorded-test.js"
@@ -22,13 +22,13 @@ describe("xAI Images recorded", () => {
      const response = yield* Image.generate({
        model,
        prompt: "A simple flat black diamond centered on a plain white background.",
-        aspectRatio: "1:1",
-        providerOptions: { resolution: "1k", responseFormat: "b64_json" },
+        options: { aspectRatio: "1:1", resolution: "1k", responseFormat: "b64_json" },
      })

      expect(response.images).toHaveLength(1)
-      expect(response.image.mediaType.startsWith("image/")).toBe(true)
-      expect((yield* response.image.bytes()).length).toBeGreaterThan(0)
+      expect(response.image?.mediaType.startsWith("image/")).toBe(true)
+      expect(response.image?.data).toBeInstanceOf(Uint8Array)
+      expect(response.image?.data.length).toBeGreaterThan(0)
    }),
  )

@@ -38,17 +38,18 @@ describe("xAI Images recorded", () => {
        model,
        prompt: "Keep the simple shape and change it from black to bright purple.",
        images: [
-          Media.bytes(
+          ImageInput.bytes(
            yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
            "image/jpeg",
          ),
        ],
-        aspectRatio: "1:1",
-        providerOptions: { resolution: "1k", responseFormat: "b64_json" },
+        options: { aspectRatio: "1:1", resolution: "1k", responseFormat: "b64_json" },
      })

-      expect(response.image.mediaType).toMatch(/^image\/(jpeg|png)$/)
-      expect(dimensions(yield* response.image.bytes())).toEqual({ width: 1024, height: 1024 })
+      expect(response.image?.mediaType).toMatch(/^image\/(jpeg|png)$/)
+      expect(response.image?.data).toBeInstanceOf(Uint8Array)
+      if (!(response.image?.data instanceof Uint8Array)) throw new Error("Expected owned xAI image bytes")
+      expect(dimensions(response.image.data)).toEqual({ width: 1024, height: 1024 })
    }),
  )
 })
@@ -17,9 +17,9 @@ describe("xAI Images", () => {
          http: { body: { configured: true }, headers: { "x-default": "yes" } },
        }).image("grok-imagine-image"),
        prompt: "A robot tending a rooftop garden",
-        n: 2,
-        aspectRatio: "16:9",
-        providerOptions: {
+        options: {
+          n: 2,
+          aspectRatio: "16:9",
          aspect_ratio: "4:3",
          resolution: "1k",
          responseFormat: "url",
@@ -34,16 +34,16 @@ describe("xAI Images", () => {
      })

      expect(response.images).toHaveLength(2)
-      expect(response.image.mediaType).toBe("image/jpeg")
-      expect(yield* response.image.bytes()).toEqual(Uint8Array.from([1, 2, 3]))
-      expect(response.images[1].mediaType).toBe("application/octet-stream")
-      expect(response.images[1].source).toEqual({ type: "url", url: "https://api.xai.test/image.jpg" })
-      expect(response.usage).toBeUndefined()
+      expect(response.image?.mediaType).toBe("image/jpeg")
+      expect(response.image?.data).toEqual(Uint8Array.from([1, 2, 3]))
+      expect(response.images[1]?.mediaType).toBe("application/octet-stream")
+      expect(response.images[1]?.data).toBe("https://api.xai.test/image.jpg")
+      expect(response.usage?.providerMetadata).toEqual({ xai: { num_images: 2 } })
      expect(response.providerMetadata).toEqual({ xai: { usage: { num_images: 2 } } })
    }).pipe(
      Effect.provide(
        ImageClient.layer.pipe(
-          Layer.provideMerge(
+          Layer.provide(
            dynamicResponse((input) =>
              Effect.gen(function* () {
                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
@@ -1,6 +1,6 @@
 import { expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM, LLMEvent, Message, ToolDefinition, Media } from "../../src/index.js"
+import { LLM, LLMEvent, Message, ToolDefinition } from "../../src/index.js"
 import { ZAI } from "../../src/providers.js"
 import { LLMClient } from "../../src/route.js"
 import { recordedTests } from "../recorded-test.js"
@@ -92,7 +92,7 @@ recorded.effect.with(
          messages: [
            Message.user([
              { type: "text", text: "Read the three words in this image. Reply with only the words in order." },
-              { type: "media", media: Media.bytes(bytes, "image/png") },
+              { type: "media", mediaType: "image/png", data: bytes },
            ]),
          ],
          generation: { maxTokens: 4096 },
@@ -19,14 +19,13 @@ describe("Z.ai Images recorded", () => {
      const response = yield* Image.generate({
        model,
        prompt: "A simple flat red circle centered on a plain white background.",
-        size: "1024x1024",
-        providerOptions: { quality: "standard", userID: "opencode-image-test" },
+        options: { size: "1024x1024", quality: "standard", userID: "opencode-image-test" },
      })

      expect(response.images).toHaveLength(1)
-      expect(response.image.mediaType).toBe("application/octet-stream")
-      expect(response.image.source.type).toBe("url")
-      expect(response.image.source.type === "url" && response.image.source.url).toStartWith("https://")
+      expect(response.image?.mediaType).toBe("application/octet-stream")
+      expect(response.image?.data).toBeString()
+      expect(response.image?.data).toStartWith("https://")
      expect(response.providerMetadata?.zai).toBeDefined()
    }),
  )
@@ -17,7 +17,7 @@ describe("Z.ai Images", () => {
          http: { body: { configured: true, quality: "configured" }, query: { trace: "default" } },
        }).image("glm-image"),
        prompt: "A red circle on a white background",
-        providerOptions: {
+        options: {
          quality: "hd",
          userID: "alias-user",
          user_id: "raw-user",
@@ -31,15 +31,8 @@ describe("Z.ai Images", () => {
      })

      expect(response.images).toHaveLength(1)
-      expect(response.image.mediaType).toBe("application/octet-stream")
-      expect(response.image.source).toEqual({ type: "url", url: "https://cdn.z.ai/generated.png" })
-      expect(response.notices).toEqual([
-        {
-          type: "moderated",
-          message: "Z.ai Images applied a content filter for future-role at level 4.5",
-          providerMetadata: { zai: { role: "future-role", level: 4.5 } },
-        },
-      ])
+      expect(response.image?.mediaType).toBe("application/octet-stream")
+      expect(response.image?.data).toBe("https://cdn.z.ai/generated.png")
      expect(response.providerMetadata).toEqual({
        zai: {
          created: 1_760_335_349,
@@ -116,7 +109,7 @@ describe("Z.ai Images", () => {
    Image.generate({
      model: ZAI.configure({ apiKey: "test" }).image("model"),
      prompt: "test",
-      providerOptions: { quality: "future-quality", userID: "x", user_id: "raw-user" },
+      options: { quality: "future-quality", userID: "x", user_id: "raw-user" },
    }).pipe(
      Effect.provide(
        ImageClient.layer.pipe(
@@ -1,7 +1,6 @@
 import { expect } from "bun:test"
 import { Effect, Schema } from "effect"
 import {
-  Media,
  LLM,
  LLMEvent,
  LLMRequest,
@@ -331,7 +330,7 @@ const runImageScenario = (context: GoldenScenarioContext) =>
          type: "text",
          text: "The image contains exactly three lowercase English words. Read them left to right and reply with only those words.",
        },
-        { type: "media", media: Media.base64(yield* restroomImage(), "image/png") },
+        { type: "media", mediaType: "image/png", data: yield* restroomImage() },
      ]),
      assistant.expectText(/.+/, {
        system: "Read images carefully. Reply only with the visible text.",
@@ -6,8 +6,6 @@ import * as path from "node:path"
 import { fileURLToPath } from "node:url"
 import { LLMClient, RequestExecutor } from "../src/route.js"
 import { ImageClient } from "../src/image-client.js"
-import { EvaluationClient } from "../src/experimental/evaluation-client.js"
-import type { Service as EvaluationClientService } from "../src/experimental/evaluation-client.js"
 import type { Service as ImageClientService } from "../src/image-client.js"
 import type { Service as LLMClientService } from "../src/route/client.js"
 import type { Service as RequestExecutorService } from "../src/route/executor.js"
@@ -20,12 +18,7 @@ import {
 const __dirname = path.dirname(fileURLToPath(import.meta.url))
 const FIXTURES_DIR = path.resolve(__dirname, "fixtures", "recordings")

-type RecordedEnv =
-  | RequestExecutorService
-  | LLMClientService
-  | ImageClientService
-  | EvaluationClientService
-  | Socket.WebSocketConstructor
+type RecordedEnv = RequestExecutorService | LLMClientService | ImageClientService | Socket.WebSocketConstructor

 type RecordedTestsOptions = RecordedGroupOptions & {
  readonly options?: HttpRecorder.RecorderOptions
@@ -99,7 +92,6 @@ export const recordedTests = (options: RecordedTestsOptions) =>
        requestExecutor,
        LLMClient.layer.pipe(Layer.provide(requestExecutor)),
        ImageClient.layer.pipe(Layer.provide(requestExecutor)),
-        EvaluationClient.layer.pipe(Layer.provide(requestExecutor)),
        webSocket,
      )
    },
@@ -178,20 +178,6 @@ describe("AI.Usage", () => {
    }),
  )

-  it.effect("sseFraming drops bare null frames and keeps other payloads", () =>
-    Effect.gen(function* () {
-      const frames = yield* ProviderShared.sseFraming(
-        Stream.make(
-          new TextEncoder().encode(
-            'data: {"first":true}\n\ndata: null\n\nevent: update\ndata: null\n\ndata: "null"\n\ndata: 0\n\ndata: {"second":true}\n\ndata: [DONE]\n\ndata: null\n\n',
-          ),
-        ),
-      ).pipe(Stream.runCollect)
-
-      expect(Array.from(frames)).toEqual(['{"first":true}', '"null"', "0", '{"second":true}'])
-    }),
-  )
-
  test("visibleOutputTokens clamps reasoning > output to zero", () => {
    expect(new Usage({ outputTokens: 10, reasoningTokens: 4 }).visibleOutputTokens).toBe(6)
    expect(new Usage({ outputTokens: 10 }).visibleOutputTokens).toBe(10)
--- a/Show More
+++ b/Show More