fix(simulation): align vertical box drawing

.changeset/calm-sessions-header.md

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

.changeset/canonical-tool-results.md

@@ -1,8 +0,0 @@
----
-"@opencode-ai/plugin": minor
-"@opencode-ai/sdk": minor
-"@opencode-ai/client": minor
-"@opencode-ai/protocol": minor
----
-
-Replace the V2 tool result model with one canonical representation per fact. Tools lose `structured`, projection callbacks, the `Structured` generic, and the exported `Tool.settle` interpreter; tool responses carry schema-validated `output`, model-visible `content`, and optional compact JSON `metadata`. Code Mode receives the validated encoded output. Durable tool success stores non-empty model content plus optional metadata; failure stores one error plus the final bounded partial snapshot. Progress carries metadata only, while `execute.after` hooks receive the canonical terminal outcome and managed `outputPaths`. A one-time migration rewrites existing projected tool rows and moves provider-hosted result payloads into provider-owned result state.

.changeset/clean-sessions-generate.md

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

.changeset/fresh-composers-slot.md

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

.gitattributes

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

.github/workflows/publish.yml

@@ -90,18 +90,11 @@ jobs:
           opencode-app-id: ${{ vars.OPENCODE_APP_ID }}
           opencode-app-secret: ${{ secrets.OPENCODE_APP_SECRET }}
 
-      - name: Build legacy CLI
-        if: github.ref_name != 'v2'
-        run: ./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
-        env:
-          OPENCODE_VERSION: ${{ needs.version.outputs.version }}
-          OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
-          GH_REPO: ${{ needs.version.outputs.repo }}
-          GH_TOKEN: ${{ steps.committer.outputs.token }}
-
-      - name: Build preview CLI
+      - name: Build
         id: build
-        run: ./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
+        run: |
+          ./packages/opencode/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
+          ./packages/cli/script/build.ts ${{ (github.ref_name == 'beta' && '--sourcemaps') || '' }}
         env:
           OPENCODE_VERSION: ${{ needs.version.outputs.version }}
           OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
@@ -109,7 +102,6 @@ jobs:
           GH_TOKEN: ${{ steps.committer.outputs.token }}
 
       - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
-        if: github.ref_name != 'v2'
         with:
           name: opencode-cli
           path: |
@@ -117,7 +109,6 @@ jobs:
             packages/opencode/dist/opencode-linux*
 
       - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
-        if: github.ref_name != 'v2'
         with:
           name: opencode-cli-windows
           path: packages/opencode/dist/opencode-windows*
@@ -130,55 +121,6 @@ jobs:
     outputs:
       version: ${{ needs.version.outputs.version }}
 
-  build-node-cli:
-    needs: version
-    if: github.repository == 'anomalyco/opencode'
-    strategy:
-      fail-fast: false
-      matrix:
-        settings:
-          - target: linux-arm64
-            host: blacksmith-4vcpu-ubuntu-2404-arm
-          - target: linux-x64
-            host: blacksmith-4vcpu-ubuntu-2404
-          - target: darwin-arm64
-            host: macos-26
-          - target: windows-arm64
-            host: blacksmith-4vcpu-windows-2025
-          - target: windows-x64
-            host: blacksmith-4vcpu-windows-2025
-    runs-on: ${{ matrix.settings.host }}
-    defaults:
-      run:
-        shell: bash
-    steps:
-      - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # v3.6.0
-
-      - uses: ./.github/actions/setup-bun
-        with:
-          install-flags: --os=* --cpu=*
-
-      - uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
-        with:
-          node-version: "26.4.0"
-
-      - name: Build
-        run: bun packages/cli/script/build-node.ts --target=${{ matrix.settings.target }} --skip-install --outdir=dist/node
-        env:
-          OPENCODE_VERSION: ${{ needs.version.outputs.version }}
-          OPENCODE_RELEASE: ${{ needs.version.outputs.release }}
-
-      - name: Verify service lifecycle
-        if: matrix.settings.target != 'windows-arm64'
-        working-directory: packages/cli
-        run: bun run script/service-smoke.ts --node
-
-      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
-        with:
-          name: opencode-node-cli-${{ matrix.settings.target }}
-          path: packages/cli/dist/node/cli-node-*
-          if-no-files-found: error
-
   sign-cli-windows:
     needs:
       - build-cli
@@ -471,7 +413,6 @@ jobs:
     needs:
       - version
       - build-cli
-      - build-node-cli
       - sign-cli-windows
       - build-electron
     if: always() && !failure() && !cancelled()
@@ -500,13 +441,11 @@ jobs:
           registry-url: "https://registry.npmjs.org"
 
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
-        if: github.ref_name != 'v2'
         with:
           name: opencode-cli
           path: packages/opencode/dist
 
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
-        if: github.ref_name != 'v2'
         with:
           name: opencode-cli-windows
           path: packages/opencode/dist
@@ -522,12 +461,6 @@ jobs:
           name: opencode-preview-cli
           path: packages/cli/dist
 
-      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
-        with:
-          pattern: opencode-node-cli-*
-          path: packages/cli/dist/node
-          merge-multiple: true
-
       - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
         if: needs.version.outputs.release
         with:

.github/workflows/test.yml

@@ -78,30 +78,11 @@ jobs:
           bun run script/build.ts --single --skip-install
           bun run script/service-smoke.ts
 
-      - name: Setup Node build runtime
-        if: always()
-        uses: actions/setup-node@49933ea5288caeca8642d1e84afbd3f7d6820020 # v4.4.0
-        with:
-          node-version: "26.4.0"
-
-      - name: Verify Node build
-        if: always()
-        timeout-minutes: 15
-        working-directory: packages/cli
-        run: |
-          bun run script/build-node.ts --single --skip-install --outdir=dist/node
-          bun run script/service-smoke.ts --node
-
       - name: Check generated client
         if: runner.os == 'Linux'
         working-directory: packages/client
         run: bun run check:generated
 
-      - name: Check generated documentation
-        if: runner.os == 'Linux'
-        working-directory: packages/docs
-        run: bun run check:generated
-
   e2e:
     name: e2e (${{ matrix.settings.name }})
     if: github.ref_name != 'v2' && github.head_ref != 'v2'

.gitignore

@@ -11,7 +11,6 @@ node_modules
 playground
 tmp
 dist
-dist-node
 ts-dist
 .turbo
 .typecheck-profiles
@@ -26,7 +25,6 @@ Session.vim
 a.out
 target
 .scripts
-.cache
 .direnv/
 
 # Local dev files

.opencode/command/translate.md

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

AGENTS.md

@@ -19,6 +19,8 @@ Valid types are `feat`, `fix`, `docs`, `chore`, `refactor`, and `test`. Scopes a
 
 Examples: `fix(tui): simplify thinking toggle styling`, `docs: update contributing guide`, `chore(sdk): regenerate types`.
 
+Never bypass Git hooks. Do not use `--no-verify` or otherwise disable, skip, or circumvent commit or push hooks. If a hook fails, fix the failure or stop and report it to the user.
+
 ## Style Guide
 
 ### General Principles

docs/design/service-lifecycle.md

@@ -30,50 +30,6 @@ This proposal does not introduce a supervisor process, warm candidate server,
 protocol negotiation, idle background restart, or general execution-recovery
 framework.
 
-## Architecture at a Glance
-
-```text
-                       ╭───────────────────╮
-                       │ CLI ServiceConfig │
-                       ╰─────────┬─────────╯
-                                 │
-                                 ▼
-                     ╭──────────────────────╮
-                     │ CLI ServerConnection │
-                     ╰───────────┬──────────╯
-              ╭──────────────────╰───────────────────╮
-              ▼                                      ▼
-╭──────────────────────────╮            ╭─────────────────────────╮
-│ Client Service lifecycle │            │ CLI runPromiseWith seam │
-╰─────────────┬────────────╯            ╰─────────────┬───────────╯
-              ╰─────╮                                 │
-                    ▼                                 ▼
-     ╭────────────────────────────╮            ╭─────────────╮
-     │ Background service process │            │ TUI / Solid │
-     ╰──────────────┬─────────────╯            ╰──────┬──────╯
-                    │                                 │
-                    ╰────────────◀────────────────────╯
-                     ╭───────────────────────╮
-                     │ Server HTTP transport │
-                     ╰───────────┬───────────╯
-                                 │
-                                 ▼
-                       ╭──────────────────╮
-                       │ Core application │
-                       ╰──────────────────╯
-```
-
-| Owner                                            | Responsibility                                                                                      |
-| ------------------------------------------------ | --------------------------------------------------------------------------------------------------- |
-| `packages/client/src/effect/service.ts`          | Effect-native discovery, start, and stop lifecycle operations                                       |
-| `packages/cli/src/services/service-config.ts`    | CLI registration path, installed version, and daemon command                                        |
-| `packages/cli/src/services/server-connection.ts` | Resolve an endpoint and, only for the shared service, grouped reconnect and restart Effects         |
-| `packages/cli/src/server-process.ts`             | Daemon election, registration, and server process boot                                              |
-| `packages/server/src/process.ts`                 | HTTP lifecycle shell and application transport                                                      |
-| `packages/core`                                  | Application behavior behind the transport                                                           |
-| CLI default handler                              | Convert lifecycle Effects with the outer `FileSystem` context and pass grouped Promise capabilities |
-| `packages/tui` Solid client context              | Own event-stream reconnect, endpoint replacement, status, and user-triggered restart UI             |
-
 ## Implementation Status
 
 | Area                      | State                                                                 |
@@ -208,22 +164,19 @@ This design gives each concept one authority.
 
 ## System Model
 
-```text
-╭───────────────────────╮                              ╭──────────────────────────────╮
-│ Fresh or existing TUI │                              │ Process-held OS service lock │
-╰───────────┬───────────╯                              ╰───────────────┬──────────────╯
-            ╰─────┬ normal requests  observe ───────────────────────╮  │
-                  │ discover               │                        ├──╯ authorizes one owner
-                  ▼                        │                        ▼
-        ╭───────────────────╮              │               ╭─────────────────╮
-        │ Registration file │              │               │ Lifecycle shell │
-        ╰───────────────────╯              │               ╰────────┬────────╯
-                                           │                        │
-                                           ├────────────────────────╯
-                                           ▼
-                               ╭──────────────────────╮
-                               │ OpenCode application │
-                               ╰──────────────────────╯
+```mermaid
+flowchart LR
+  TUI[Fresh or existing TUI]
+  REG[Registration file]
+  LOCK[Process-held OS service lock]
+  SHELL[Lifecycle shell]
+  APP[OpenCode application]
+
+  TUI -->|discover| REG
+  TUI -->|observe| SHELL
+  TUI -->|normal requests| APP
+  SHELL --> APP
+  LOCK -->|authorizes one owner| SHELL
 ```
 
 The lifecycle shell and application run in the same process. The distinction is
@@ -358,39 +311,24 @@ Windows, where Bun FFI is not available on every shipped architecture. It lives
 the foundation of the design, so the delivery sequence spikes it first.
 
 ```mermaid
-Contender           Lock            Lifecycle              Application
-    │                 │                 │                       │
-    ├─ try acquire ───▶                 │                       │
-    │                 │                 │                       │
- ╭─ alt: lock held ────────────────────────────────────────────────╮
- │  │                 │                 │                       │  │
- │  ◀─ busy ──────────┤                 │                       │  │
- │  │                 │                 │                       │  │
- │  ├─────────╮       │                 │                       │  │
- │  │ exit    │       │                 │                       │  │
- │  ◀─────────╯       │                 │                       │  │
- │  │                 │                 │                       │  │
- ├─ else: lock acquired ───────────────────────────────────────────┤
- │  │                 │                 │                       │  │
- │  ◀─ owner ─────────┤                 │                       │  │
- │  │                 │                 │                       │  │
- │  ├─ bind, register, starting ────────▶                       │  │
- │  │                 │                 │                       │  │
- │  ├─ initialize ──────────────────────────────────────────────▶  │
- │  │                 │                 │                       │  │
- │╭─ alt: boot succeeds ──────────────────────────────────────────╮│
- ││ │                 │                 │                       │ ││
- ││ │                 │                 ◀─ ready ───────────────┤ ││
- ││ │                 │                 │                       │ ││
- │├─ else: boot fails ────────────────────────────────────────────┤│
- ││ │                 │                 │                       │ ││
- ││ │                 │                 ◀─ failed, stay bound ──┤ ││
- ││ │                 │                 │                       │ ││
- │╰───────────────────────────────────────────────────────────────╯│
- │  │                 │                 │                       │  │
- ╰─────────────────────────────────────────────────────────────────╯
-    │                 │                 │                       │
-```
+flowchart TD
+  A[Contender process starts]
+  B{Acquire service lock?}
+  C[Exit successfully]
+  D[Bind lifecycle shell]
+  E[Write registration]
+  F[Report starting]
+  G[Initialize application]
+  H[Report ready]
+  I[Serve until shutdown]
+
+  A --> B
+  B -->|No| C
+  B -->|Yes| D
+  D --> E --> F --> G
+  G -->|Success| H --> I
+  G -->|Failure| J[Report failed and stay bound]
+```
 
 Lock acquisition by a contender is nonblocking or tightly bounded. A loser
 must exit before constructing application routes or importing startup-heavy

infra/stage.ts

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

nix/desktop.nix

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

nix/hashes.json

@@ -1,8 +1,8 @@
 {
   "nodeModules": {
-    "x86_64-linux": "sha256-0kcwV34P2C3yKg2eG9W2nW+OedrSBb+1TdpuUeYtauY=",
-    "aarch64-linux": "sha256-yHVygApQchAB34wrtFR4GU0CkmZOlLsl3wsp15u0xzs=",
-    "aarch64-darwin": "sha256-DyalcwyK2Wn5R6249keFcNVECbgtjYNjscOFqTi88FI=",
-    "x86_64-darwin": "sha256-BkGw0GWN9W9q+/g4FYR0MqxUuFP80BPoERO+ypz/arQ="
+    "x86_64-linux": "sha256-F1luclnqCPQk9yxfmeSYGaM/nScf28yBu9K3Fv+Xd24=",
+    "aarch64-linux": "sha256-XW0XZnsCRkU3MFJH9TjMRYZHffzVy3cQyiNCkec2gl4=",
+    "aarch64-darwin": "sha256-bf8kvORs3Fs2UYLp3PekF+AJR7NKOcHb+fIQA79RtMk=",
+    "x86_64-darwin": "sha256-sBdQPkzd7JXNW6Lbi9JHiAsfHwdLwTKWY+uPeXAv2Nw="
   }
 }

package.json

@@ -15,7 +15,7 @@
     "dev:www": "bun run --cwd packages/www dev",
     "dev:storybook": "bun --cwd packages/storybook storybook",
     "lint": "oxlint",
-    "lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/util/src packages/core/src packages/server/src packages/protocol/src packages/cli/src",
+    "lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/core/src packages/server/src packages/protocol/src packages/cli/src",
     "test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
     "typecheck": "bun turbo typecheck --concurrency=3",
     "typecheck:profile": "bun script/profile-typecheck.ts",
@@ -37,18 +37,18 @@
       "packages/slack"
     ],
     "catalog": {
-      "@effect/opentelemetry": "4.0.0-beta.98",
-      "@effect/platform-node": "4.0.0-beta.98",
-      "@effect/sql-sqlite-bun": "4.0.0-beta.98",
+      "@effect/opentelemetry": "4.0.0-beta.83",
+      "@effect/platform-node": "4.0.0-beta.83",
+      "@effect/sql-sqlite-bun": "4.0.0-beta.83",
       "@npmcli/arborist": "9.4.0",
       "@types/bun": "1.3.13",
       "@types/cross-spawn": "6.0.6",
       "@octokit/rest": "22.0.0",
       "@hono/standard-validator": "0.2.0",
       "@hono/zod-validator": "0.4.2",
-      "@opentui/core": "0.4.5",
-      "@opentui/keymap": "0.4.5",
-      "@opentui/solid": "0.4.5",
+      "@opentui/core": "0.4.3",
+      "@opentui/keymap": "0.4.3",
+      "@opentui/solid": "0.4.3",
       "@tanstack/solid-virtual": "3.13.32",
       "@shikijs/stream": "4.2.0",
       "ulid": "3.0.1",
@@ -69,13 +69,12 @@
       "dompurify": "3.3.1",
       "drizzle-kit": "1.0.0-rc.2",
       "drizzle-orm": "1.0.0-rc.2",
-      "effect": "4.0.0-beta.98",
+      "effect": "4.0.0-beta.83",
       "ai": "6.0.168",
       "cross-spawn": "7.0.6",
       "hono": "4.10.7",
       "hono-openapi": "1.1.2",
       "fuzzysort": "3.1.0",
-      "get-east-asian-width": "1.6.0",
       "luxon": "3.6.1",
       "marked": "17.0.6",
       "marked-shiki": "1.2.1",
@@ -86,11 +85,9 @@
       "@typescript/native-preview": "7.0.0-dev.20251207.1",
       "zod": "4.1.8",
       "remeda": "2.26.0",
-      "resolve.exports": "2.0.3",
       "sst": "4.13.1",
       "shiki": "4.2.0",
       "solid-list": "0.3.0",
-      "string-width": "7.2.0",
       "tailwindcss": "4.1.11",
       "vite": "7.1.4",
       "@solidjs/meta": "0.29.4",
@@ -155,18 +152,18 @@
     "@types/node": "catalog:"
   },
   "patchedDependencies": {
+    "@ff-labs/fff-bun@0.9.3": "patches/@ff-labs%2Ffff-bun@0.9.3.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",
     "@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
     "solid-js@1.9.10": "patches/solid-js@1.9.10.patch",
     "@ai-sdk/xai@3.0.102": "patches/@ai-sdk%2Fxai@3.0.102.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@21.5.0": "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",
     "@modelcontextprotocol/sdk@1.29.0": "patches/@modelcontextprotocol%2Fsdk@1.29.0.patch",
-    "effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
+    "effect@4.0.0-beta.83": "patches/effect@4.0.0-beta.83.patch",
     "@tanstack/virtual-core@3.17.3": "patches/@tanstack%2Fvirtual-core@3.17.3.patch"
   }
 }

packages/ai/README.md

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

packages/ai/package.json

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

packages/ai/script/publish.ts

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

packages/ai/src/image-client.ts

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

packages/ai/src/image.ts

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

packages/ai/src/protocols.ts

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

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

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

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

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

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

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

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

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

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

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

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

@@ -1,132 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
-import { GeneratedImage, ImageModel, ImageResponse, type ImageRequestFor, type ImageRoute } from "../image"
-import { Auth, type Definition as AuthDefinition } from "../route/auth"
-import { InvalidProviderOutputReason, LLMError, mergeHttpOptions, mergeJsonRecords, type HttpOptions } from "../schema"
-import { ProviderShared } from "./shared"
-import { ImageInputs } from "./utils/image-input"
-
-const ADAPTER = "zai-images"
-export const DEFAULT_BASE_URL = "https://api.z.ai/api/paas/v4"
-export const PATH = "/images/generations"
-
-export type ZAIImageString<Known extends string> = Known | (string & {})
-
-export type ZAIImageOptions = {
-  readonly size?: ZAIImageString<
-    "1024x1024" | "768x1344" | "864x1152" | "1344x768" | "1152x864" | "1440x720" | "720x1440"
-  >
-  readonly quality?: ZAIImageString<"hd" | "standard">
-  readonly userID?: string
-} & Record<string, unknown>
-
-type ZAIImageBody = Record<string, unknown> & {
-  readonly model: string
-  readonly prompt: string
-}
-
-const ZAIImageResponse = Schema.Struct({
-  created: Schema.optional(Schema.Int),
-  id: Schema.optional(Schema.String),
-  request_id: Schema.optional(Schema.String),
-  data: Schema.Array(Schema.Struct({ url: Schema.String })),
-  content_filter: Schema.optional(
-    Schema.Array(
-      Schema.Struct({
-        role: Schema.optional(Schema.String),
-        level: Schema.optional(Schema.Number),
-      }),
-    ),
-  ),
-})
-
-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,
-  }
-}
-
-const invalidOutput = (message: string) =>
-  new LLMError({
-    module: ADAPTER,
-    method: "generate",
-    reason: new InvalidProviderOutputReason({ message, route: ADAPTER }),
-  })
-
-const applyQuery = (url: string, query: Record<string, string> | undefined) => {
-  if (!query) return url
-  const next = new URL(url)
-  Object.entries(query).forEach(([key, value]) => next.searchParams.set(key, value))
-  return next.toString()
-}
-
-export const model = (input: ModelInput) => {
-  const route: ImageRoute<ZAIImageOptions> = {
-    id: ADAPTER,
-    generate: Effect.fn("ZAIImages.generate")(function* (request: ImageRequestFor<ZAIImageOptions>, execute) {
-      if ((request.images?.length ?? 0) > 0)
-        return yield* ImageInputs.invalid(ADAPTER, "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 payload = yield* response.json.pipe(
-        Effect.mapError(() => invalidOutput("Failed to read the Z.ai Images response")),
-      )
-      const decoded = yield* Schema.decodeUnknownEffect(ZAIImageResponse)(payload).pipe(
-        Effect.mapError(() => invalidOutput("Z.ai Images returned an invalid response")),
-      )
-      if (decoded.data.length === 0) return yield* invalidOutput("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 = {
-  model,
-} as const

packages/ai/src/providers.ts

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

packages/ai/src/providers/anthropic-compatible.ts

@@ -1,67 +0,0 @@
-import type { ProviderPackage } from "../provider-package"
-import { AnthropicMessages } from "../protocols/anthropic-messages"
-import { Auth } from "../route/auth"
-import type { ProviderAuthOption } from "../route/auth-options"
-import type { RouteDefaultsInput } from "../route/client"
-import { ProviderID, type ModelID } from "../schema"
-
-export const id = ProviderID.make("anthropic-compatible")
-
-export type Config = RouteDefaultsInput &
-  ProviderAuthOption<"optional"> & {
-    readonly provider?: string
-    readonly baseURL: string
-  }
-
-export type Settings = ProviderPackage.Settings &
-  (
-    | { readonly apiKey?: string; readonly authToken?: never }
-    | { readonly apiKey?: never; readonly authToken?: string }
-  ) & {
-    readonly baseURL: string
-    readonly provider?: string
-  }
-
-export const routes = [AnthropicMessages.route]
-
-const auth = (input: ProviderAuthOption<"optional">) => {
-  if ("auth" in input && input.auth) return input.auth
-  return Auth.optional("apiKey" in input ? input.apiKey : undefined, "apiKey").pipe(Auth.header("x-api-key"))
-}
-
-export const configure = (input: Config) => {
-  if (!input.baseURL) throw new Error("Anthropic-compatible providers require a baseURL")
-  const provider = input.provider ?? "anthropic-compatible"
-  const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input
-  const route = AnthropicMessages.route.with({
-    ...rest,
-    provider,
-    endpoint: { baseURL },
-    auth: auth(input),
-  })
-  return {
-    id: ProviderID.make(provider),
-    model: (modelID: string | ModelID) => route.model({ id: modelID }),
-    configure,
-  }
-}
-
-export const provider = {
-  id,
-  configure,
-}
-
-export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
-  if (settings.apiKey !== undefined && settings.authToken !== undefined)
-    throw new Error("Anthropic-compatible apiKey cannot be combined with authToken")
-  return configure({
-    ...(settings.authToken === undefined ? { apiKey: settings.apiKey } : { auth: Auth.bearer(settings.authToken) }),
-    baseURL: settings.baseURL,
-    headers: settings.headers === undefined ? undefined : { ...settings.headers },
-    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
-    limits: settings.limits,
-    provider: settings.provider,
-  }).model(modelID)
-}
-
-export * as AnthropicCompatible from "./anthropic-compatible"

packages/ai/src/providers/google-vertex-chat.ts

@@ -1,81 +0,0 @@
-import type { ProviderPackage } from "../provider-package"
-import { OpenAICompatibleChat } from "../protocols/openai-compatible-chat"
-import type { RouteDefaultsInput } from "../route/client"
-import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
-import { GoogleVertexShared } from "./google-vertex-shared"
-
-export const id = ProviderID.make("google-vertex")
-
-export type Config = RouteDefaultsInput &
-  GoogleVertexShared.OAuthOptions & {
-    readonly baseURL?: string
-    readonly location?: string
-    readonly project?: string
-  }
-
-export interface Settings extends ProviderPackage.Settings {
-  readonly accessToken?: string
-  readonly apiKey?: never
-  readonly baseURL?: string
-  readonly location?: string
-  readonly project?: string
-  readonly providerOptions?: ProviderOptions
-}
-
-const route = OpenAICompatibleChat.route.with({
-  id: "google-vertex-chat",
-  provider: id,
-})
-
-export const routes = [route]
-
-const configuredRoute = (input: Config) => {
-  if ("apiKey" in input && input.apiKey !== undefined) throw new Error("Google Vertex Chat does not support API keys")
-  const {
-    accessToken: _accessToken,
-    auth: _auth,
-    baseURL,
-    location: inputLocation,
-    project: inputProject,
-    ...rest
-  } = input
-  const location = GoogleVertexShared.location(inputLocation, "global")
-  const project = GoogleVertexShared.project(inputProject)
-  return route.with({
-    ...rest,
-    endpoint: {
-      baseURL:
-        baseURL ??
-        `https://aiplatform.googleapis.com/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/endpoints/openapi`,
-    },
-    auth: GoogleVertexShared.oauth(input, project),
-  })
-}
-
-export const configure = (input: Config = {}) => {
-  const route = configuredRoute(input)
-  return {
-    id,
-    model: (modelID: string | ModelID) => route.model({ id: modelID }),
-    configure,
-  }
-}
-
-export const provider = {
-  id,
-  configure,
-}
-
-export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
-  if (settings.apiKey !== undefined) throw new Error("Google Vertex Chat does not support API keys")
-  return configure({
-    accessToken: settings.accessToken,
-    baseURL: settings.baseURL,
-    headers: settings.headers === undefined ? undefined : { ...settings.headers },
-    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
-    limits: settings.limits,
-    location: settings.location,
-    project: settings.project,
-    providerOptions: settings.providerOptions,
-  }).model(modelID)
-}

packages/ai/src/providers/google-vertex-messages.ts

@@ -1,111 +0,0 @@
-import { Effect, Schema, Struct } from "effect"
-import type { ProviderPackage } from "../provider-package"
-import { AnthropicMessages } from "../protocols/anthropic-messages"
-import { Auth } from "../route/auth"
-import { Route, type RouteDefaultsInput } from "../route/client"
-import { Endpoint } from "../route/endpoint"
-import { Framing } from "../route/framing"
-import { Protocol } from "../route/protocol"
-import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
-import { GoogleVertexShared } from "./google-vertex-shared"
-
-const VERSION = "vertex-2023-10-16" as const
-
-// models.dev uses this provider id even though the API contract is Anthropic Messages.
-export const id = ProviderID.make("google-vertex-anthropic")
-
-export type Config = RouteDefaultsInput &
-  GoogleVertexShared.OAuthOptions & {
-    readonly baseURL?: string
-    readonly location?: string
-    readonly project?: string
-  }
-
-export interface Settings extends ProviderPackage.Settings {
-  readonly accessToken?: string
-  readonly apiKey?: never
-  readonly baseURL?: string
-  readonly location?: string
-  readonly project?: string
-  readonly providerOptions?: ProviderOptions
-}
-
-const route = Route.make({
-  id: "google-vertex-messages",
-  provider: id,
-  providerMetadataKey: "anthropic",
-  protocol: Protocol.make({
-    id: AnthropicMessages.protocol.id,
-    body: {
-      schema: Schema.Struct({
-        ...Struct.omit(AnthropicMessages.AnthropicMessagesBody.fields, ["model"]),
-        anthropic_version: Schema.Literal(VERSION),
-      }),
-      from: (request) =>
-        AnthropicMessages.protocol.body.from(request).pipe(
-          Effect.map((body) => ({
-            ...Struct.omit(body, ["model"]),
-            anthropic_version: VERSION,
-          })),
-        ),
-    },
-    stream: AnthropicMessages.protocol.stream,
-  }),
-  endpoint: Endpoint.path(({ request }) => `/${request.model.id}:streamRawPredict`),
-  auth: Auth.none,
-  framing: Framing.sse,
-})
-
-export const routes = [route]
-
-const configuredRoute = (input: Config) => {
-  if ("apiKey" in input && input.apiKey !== undefined)
-    throw new Error("Google Vertex Messages does not support API keys")
-  const {
-    accessToken: _accessToken,
-    auth: _auth,
-    baseURL,
-    location: inputLocation,
-    project: inputProject,
-    ...rest
-  } = input
-  const location = GoogleVertexShared.location(inputLocation, "global")
-  const project = GoogleVertexShared.project(inputProject)
-  return route.with({
-    ...rest,
-    endpoint: {
-      baseURL:
-        baseURL ??
-        `https://${GoogleVertexShared.host(location)}/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/publishers/anthropic/models`,
-    },
-    auth: GoogleVertexShared.oauth(input, project),
-  })
-}
-
-export const configure = (input: Config = {}) => {
-  const route = configuredRoute(input)
-  return {
-    id,
-    model: (modelID: string | ModelID) => route.model({ id: modelID }),
-    configure,
-  }
-}
-
-export const provider = {
-  id,
-  configure,
-}
-
-export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
-  if (settings.apiKey !== undefined) throw new Error("Google Vertex Messages does not support API keys")
-  return configure({
-    accessToken: settings.accessToken,
-    baseURL: settings.baseURL,
-    headers: settings.headers === undefined ? undefined : { ...settings.headers },
-    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
-    limits: settings.limits,
-    location: settings.location,
-    project: settings.project,
-    providerOptions: settings.providerOptions,
-  }).model(modelID)
-}

packages/ai/src/providers/google-vertex-responses.ts

@@ -1,82 +0,0 @@
-import type { ProviderPackage } from "../provider-package"
-import { OpenAICompatibleResponses } from "../protocols/openai-compatible-responses"
-import type { RouteDefaultsInput } from "../route/client"
-import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
-import { GoogleVertexShared } from "./google-vertex-shared"
-
-export const id = ProviderID.make("google-vertex")
-
-export type Config = RouteDefaultsInput &
-  GoogleVertexShared.OAuthOptions & {
-    readonly baseURL?: string
-    readonly location?: string
-    readonly project?: string
-  }
-
-export interface Settings extends ProviderPackage.Settings {
-  readonly accessToken?: string
-  readonly apiKey?: never
-  readonly baseURL?: string
-  readonly location?: string
-  readonly project?: string
-  readonly providerOptions?: ProviderOptions
-}
-
-const route = OpenAICompatibleResponses.route.with({
-  id: "google-vertex-responses",
-  provider: id,
-})
-
-export const routes = [route]
-
-const configuredRoute = (input: Config) => {
-  if ("apiKey" in input && input.apiKey !== undefined)
-    throw new Error("Google Vertex Responses does not support API keys")
-  const {
-    accessToken: _accessToken,
-    auth: _auth,
-    baseURL,
-    location: inputLocation,
-    project: inputProject,
-    ...rest
-  } = input
-  const location = GoogleVertexShared.location(inputLocation, "global")
-  const project = GoogleVertexShared.project(inputProject)
-  return route.with({
-    ...rest,
-    endpoint: {
-      baseURL:
-        baseURL ??
-        `https://aiplatform.googleapis.com/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/endpoints/openapi`,
-    },
-    auth: GoogleVertexShared.oauth(input, project),
-  })
-}
-
-export const configure = (input: Config = {}) => {
-  const route = configuredRoute(input)
-  return {
-    id,
-    model: (modelID: string | ModelID) => route.model({ id: modelID }),
-    configure,
-  }
-}
-
-export const provider = {
-  id,
-  configure,
-}
-
-export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
-  if (settings.apiKey !== undefined) throw new Error("Google Vertex Responses does not support API keys")
-  return configure({
-    accessToken: settings.accessToken,
-    baseURL: settings.baseURL,
-    headers: settings.headers === undefined ? undefined : { ...settings.headers },
-    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
-    limits: settings.limits,
-    location: settings.location,
-    project: settings.project,
-    providerOptions: settings.providerOptions,
-  }).model(modelID)
-}

packages/ai/src/providers/google-vertex-shared.ts

@@ -1,77 +0,0 @@
-import type { AnyAuthClient } from "google-auth-library"
-import { Effect, Redacted } from "effect"
-import { Auth, MissingCredentialError } from "../route/auth"
-
-const SCOPE = "https://www.googleapis.com/auth/cloud-platform"
-
-export type OAuthOptions =
-  | { readonly accessToken?: string; readonly auth?: never }
-  | { readonly accessToken?: never; readonly auth?: Auth.Definition }
-
-export type ApiKeyOptions =
-  | (OAuthOptions & { readonly apiKey?: never })
-  | { readonly accessToken?: never; readonly apiKey?: string; readonly auth?: never }
-
-export const project = (value?: string) =>
-  value ??
-  process.env.GOOGLE_VERTEX_PROJECT ??
-  process.env.GOOGLE_CLOUD_PROJECT ??
-  process.env.GCP_PROJECT ??
-  process.env.GCLOUD_PROJECT
-
-export const location = (value: string | undefined, fallback: string) =>
-  value ??
-  process.env.GOOGLE_VERTEX_LOCATION ??
-  process.env.GOOGLE_CLOUD_LOCATION ??
-  process.env.VERTEX_LOCATION ??
-  fallback
-
-export const host = (location: string) => {
-  if (location === "global") return "aiplatform.googleapis.com"
-  // Jurisdictional multi-regions use Regional Endpoint Platform domains.
-  if (location === "eu" || location === "us") return `aiplatform.${location}.rep.googleapis.com`
-  return `${location}-aiplatform.googleapis.com`
-}
-
-export const requireProject = (value: string | undefined) => {
-  if (value) return value
-  throw new Error("Google Vertex requires a project when baseURL is not configured")
-}
-
-export const apiKey = (input: ApiKeyOptions) => {
-  if (input.apiKey !== undefined && (input.accessToken !== undefined || input.auth !== undefined))
-    throw new Error("Google Vertex apiKey cannot be combined with accessToken or auth")
-  if (input.accessToken !== undefined || input.auth !== undefined) return undefined
-  return input.apiKey ?? process.env.GOOGLE_VERTEX_API_KEY
-}
-
-const adc = (project?: string) => {
-  let client: Promise<AnyAuthClient> | undefined
-  const loadClient = () => {
-    if (client) return client
-    client = import("google-auth-library").then(({ GoogleAuth }) =>
-      new GoogleAuth({ projectId: project, scopes: [SCOPE] }).getClient(),
-    )
-    return client
-  }
-  return Auth.effect(
-    Effect.tryPromise({
-      try: async () => {
-        const token = await (await loadClient()).getAccessToken()
-        if (!token.token) throw new Error("Google ADC returned an empty access token")
-        return Redacted.make(token.token)
-      },
-      catch: () => new MissingCredentialError("Google Application Default Credentials"),
-    }),
-  ).bearer()
-}
-
-export const oauth = (input: OAuthOptions, project?: string) => {
-  if (input.accessToken !== undefined && input.auth !== undefined)
-    throw new Error("Google Vertex accessToken cannot be combined with auth")
-  if (input.auth) return input.auth
-  if (input.accessToken !== undefined) return Auth.bearer(input.accessToken)
-  return adc(project)
-}
-
-export * as GoogleVertexShared from "./google-vertex-shared"

packages/ai/src/providers/google-vertex.ts

@@ -1,98 +0,0 @@
-import type { ProviderPackage } from "../provider-package"
-import { Gemini } from "../protocols/gemini"
-import { Auth } from "../route/auth"
-import { Route, type RouteDefaultsInput } from "../route/client"
-import { Endpoint } from "../route/endpoint"
-import { Framing } from "../route/framing"
-import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
-import { GoogleVertexShared } from "./google-vertex-shared"
-
-export const id = ProviderID.make("google-vertex")
-
-export type Config = RouteDefaultsInput &
-  GoogleVertexShared.ApiKeyOptions & {
-    readonly baseURL?: string
-    readonly location?: string
-    readonly project?: string
-  }
-
-export type Settings = ProviderPackage.Settings &
-  (
-    | { readonly accessToken?: string; readonly apiKey?: never }
-    | { readonly accessToken?: never; readonly apiKey?: string }
-  ) & {
-    readonly baseURL?: string
-    readonly location?: string
-    readonly project?: string
-    readonly providerOptions?: ProviderOptions
-  }
-
-const route = Route.make({
-  id: "google-vertex-gemini",
-  provider: id,
-  providerMetadataKey: "google",
-  protocol: Gemini.protocol,
-  endpoint: Endpoint.path(({ request }) => {
-    const model = String(request.model.id)
-    return `/${model.startsWith("endpoints/") ? model : `models/${model}`}:streamGenerateContent?alt=sse`
-  }),
-  auth: Auth.none,
-  framing: Framing.sse,
-})
-
-export const routes = [route]
-
-const configuredRoute = (input: Config, modelID: string | ModelID) => {
-  const {
-    accessToken: _accessToken,
-    apiKey: _apiKey,
-    auth: _auth,
-    baseURL,
-    location: inputLocation,
-    project: inputProject,
-    ...rest
-  } = input
-  const apiKey = GoogleVertexShared.apiKey(input)
-  const endpointModel = String(modelID).startsWith("endpoints/")
-  if (apiKey !== undefined && endpointModel)
-    throw new Error("Google Vertex tuned models do not support Express Mode API keys")
-  const location = GoogleVertexShared.location(inputLocation, "us-central1")
-  const project = GoogleVertexShared.project(inputProject)
-  const endpoint =
-    baseURL ??
-    (apiKey
-      ? "https://aiplatform.googleapis.com/v1/publishers/google"
-      : `https://${GoogleVertexShared.host(location)}/v1beta1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}${endpointModel ? "" : "/publishers/google"}`)
-  return route.with({
-    ...rest,
-    endpoint: { baseURL: endpoint },
-    auth: apiKey === undefined ? GoogleVertexShared.oauth(input, project) : Auth.header("x-goog-api-key", apiKey),
-  })
-}
-
-export const configure = (input: Config = {}) => {
-  return {
-    id,
-    model: (modelID: string | ModelID) => configuredRoute(input, modelID).model({ id: modelID }),
-    configure,
-  }
-}
-
-export const provider = {
-  id,
-  configure,
-}
-export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
-  if (settings.apiKey !== undefined && settings.accessToken !== undefined)
-    throw new Error("Google Vertex apiKey cannot be combined with accessToken or auth")
-  return configure({
-    ...(settings.apiKey === undefined ? { accessToken: settings.accessToken } : { apiKey: settings.apiKey }),
-    baseURL: settings.baseURL,
-    headers: settings.headers === undefined ? undefined : { ...settings.headers },
-    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
-    limits: settings.limits,
-    location: settings.location,
-    project: settings.project,
-    providerOptions: settings.providerOptions,
-  }).model(modelID)
-}

packages/ai/src/providers/google-vertex/chat.ts

@@ -1,2 +0,0 @@
-export { model } from "../google-vertex-chat"
-export type { Settings } from "../google-vertex-chat"

packages/ai/src/providers/google-vertex/gemini.ts

@@ -1,2 +0,0 @@
-export { model } from "../google-vertex"
-export type { Settings } from "../google-vertex"

packages/ai/src/providers/google-vertex/messages.ts

@@ -1,2 +0,0 @@
-export { model } from "../google-vertex-messages"
-export type { Settings } from "../google-vertex-messages"

packages/ai/src/providers/google-vertex/responses.ts

@@ -1,2 +0,0 @@
-export { model } from "../google-vertex-responses"
-export type { Settings } from "../google-vertex-responses"

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

@@ -1 +0,0 @@
-export * from "../openai-compatible-responses"

packages/ai/src/providers/zai.ts

@@ -1,35 +0,0 @@
-import { ZAIImages } from "../protocols/zai-images"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options"
-import { HttpOptions, ProviderID, type ModelID } from "../schema"
-
-export const id = ProviderID.make("zai")
-
-export type Config = ProviderAuthOption<"optional"> & {
-  readonly baseURL?: string
-  readonly headers?: Record<string, string>
-  readonly http?: HttpOptions.Input
-}
-
-export type { ZAIImageOptions } from "../protocols/zai-images"
-
-const auth = (options: ProviderAuthOption<"optional">) => AuthOptions.bearer(options, "ZAI_API_KEY")
-
-export const configure = (input: Config = {}) => {
-  const image = (modelID: string | ModelID) =>
-    ZAIImages.model({
-      id: modelID,
-      auth: auth(input),
-      baseURL: input.baseURL,
-      headers: input.headers,
-      http: input.http === undefined ? undefined : HttpOptions.make(input.http),
-    })
-
-  return {
-    id,
-    image,
-    configure,
-  }
-}
-
-export const provider = configure()
-export const image = provider.image

packages/ai/src/route.ts

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

packages/ai/test/fixtures/recordings/anthropic-compatible-messages/minimax-m3-anthropic-compatible-text.json

@@ -1,40 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "provider": "minimax",
-    "protocol": "anthropic-messages",
-    "route": "anthropic-messages",
-    "transport": "http",
-    "model": "MiniMax-M3",
-    "tags": [
-      "prefix:anthropic-compatible-messages",
-      "provider:minimax",
-      "protocol:anthropic-messages",
-      "text",
-      "golden"
-    ],
-    "name": "anthropic-compatible-messages/minimax-m3-anthropic-compatible-text",
-    "recordedAt": "2026-07-18T03:42:22.893Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.minimax.io/anthropic/v1/messages",
-        "headers": {
-          "anthropic-version": "2023-06-01",
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"You are concise.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply exactly with: Hello!\"}]}],\"stream\":true,\"max_tokens\":40,\"temperature\":0}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"1a0b363d0882af316faebcec4d4855a8\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":53,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Hello\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"!\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\"},\"usage\":{\"input_tokens\":53,\"output_tokens\":2,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/anthropic-compatible-messages/minimax-m3-anthropic-compatible-tool-call.json

@@ -1,41 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "provider": "minimax",
-    "protocol": "anthropic-messages",
-    "route": "anthropic-messages",
-    "transport": "http",
-    "model": "MiniMax-M3",
-    "tags": [
-      "prefix:anthropic-compatible-messages",
-      "provider:minimax",
-      "protocol:anthropic-messages",
-      "tool",
-      "tool-call",
-      "golden"
-    ],
-    "name": "anthropic-compatible-messages/minimax-m3-anthropic-compatible-tool-call",
-    "recordedAt": "2026-07-18T03:42:23.876Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.minimax.io/anthropic/v1/messages",
-        "headers": {
-          "anthropic-version": "2023-06-01",
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"Call tools exactly as requested.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Call get_weather with city exactly Paris.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"tool_choice\":{\"type\":\"tool\",\"name\":\"get_weather\"},\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"6731ecc323233459d1792df9a733dd98\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":0,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":404,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"call_function_vkxtif4epmvm_1\",\"name\":\"get_weather\",\"input\":{}}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \\\"Paris\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"}\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\"},\"usage\":{\"input_tokens\":290,\"output_tokens\":27,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/anthropic-compatible-messages/minimax-m3-anthropic-compatible-tool-loop.json

@@ -1,60 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "provider": "minimax",
-    "protocol": "anthropic-messages",
-    "route": "anthropic-messages",
-    "transport": "http",
-    "model": "MiniMax-M3",
-    "tags": [
-      "prefix:anthropic-compatible-messages",
-      "provider:minimax",
-      "protocol:anthropic-messages",
-      "tool",
-      "tool-loop",
-      "golden"
-    ],
-    "name": "anthropic-compatible-messages/minimax-m3-anthropic-compatible-tool-loop",
-    "recordedAt": "2026-07-18T03:42:25.248Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.minimax.io/anthropic/v1/messages",
-        "headers": {
-          "anthropic-version": "2023-06-01",
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"3807fa12f9ecb9357df511e099da6da0\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":0,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":417,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"call_function_yr64rwmre4gr_1\",\"name\":\"get_weather\",\"input\":{}}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \\\"Paris\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"}\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\"},\"usage\":{\"input_tokens\":303,\"output_tokens\":27,\"cache_read_input_tokens\":114,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.minimax.io/anthropic/v1/messages",
-        "headers": {
-          "anthropic-version": "2023-06-01",
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"MiniMax-M3\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_function_yr64rwmre4gr_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_function_yr64rwmre4gr_1\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"id\":\"92f8a1e86f29946eb2699d40a088fc08\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"model\":\"MiniMax-M3\",\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":41,\"output_tokens\":0,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":430,\"service_tier\":\"standard\"},\"service_tier\":\"standard\"}}\n\nevent: ping\ndata: {\"type\":\"ping\"}\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Paris\"}}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\" is sunny.\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\"},\"usage\":{\"input_tokens\":41,\"output_tokens\":4,\"cache_read_input_tokens\":430,\"service_tier\":\"standard\"}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/openrouter-reasoning.json

@@ -1,34 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "anthropic/claude-sonnet-4.6",
-    "tags": [
-      "prefix:openai-compatible-chat",
-      "provider:openrouter",
-      "protocol:openai-chat",
-      "reasoning"
-    ],
-    "name": "openrouter-reasoning",
-    "recordedAt": "2026-07-18T11:28:39.267Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://openrouter.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"anthropic/claude-sonnet-4.6\",\"messages\":[{\"role\":\"system\",\"content\":\"Think through the arithmetic, then reply with only the final integer.\"},{\"role\":\"user\",\"content\":\"What is 173 multiplied by 219?\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_tokens\":1536,\"temperature\":0,\"reasoning\":{\"max_tokens\":1024}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": ": OPENROUTER PROCESSING\n\n: OPENROUTER PROCESSING\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\",\"reasoning\":\"173\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\"173\",\"format\":\"anthropic-claude-v1\",\"index\":0}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\n: OPENROUTER PROCESSING\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\",\"reasoning\":\" × 219\\n\\n173 × 200 = 34,600\\n173 × 19 = 173 × 20 - 173 = 3,460 - 173 = 3,287\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\" × 219\\n\\n173 × 200 = 34,600\\n173 × 19 = 173 × 20 - 173 = 3,460 - 173 = 3,287\",\"format\":\"anthropic-claude-v1\",\"index\":0}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\",\"reasoning\":\"\\n\\n34,600 + 3,287 = 37,887\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\"\\n\\n34,600 + 3,287 = 37,887\",\"format\":\"anthropic-claude-v1\",\"index\":0}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\",\"reasoning_details\":[{\"type\":\"reasoning.text\",\"signature\":\"EtgCCosBCA8YAipA0W4viH3kgBs43Cl5ewwVBPXTQElvzfbA2TLF4iSbKy9ZZDCSDjjAlF3Bs4ELEnP3vrrTuTioC6OB380lXQdyIDIRY2xhdWRlLXNvbm5ldC00LTY4AEIIdGhpbmtpbmdaJDRjMGYwNDZmLTI1ZmQtNDVmYi1iZmIzLWEwOGE4ZTI0OWNhNxIMMiUlJC3x/5p5PuTwGgwlc8eipZyoM94BHwMiMO45uQx/ymeOjbugi7RDVPZ4jZXSIiEbVi2CD7zPjAK5fFQoVGP1HD55v9CER823JCp6Dg5Xb7Lrk6NUd1XN2KTKrttK7mATE+IBrDTFmor/1cNeg+9gjIbxM/jn/6L5HPmh3/esEVu24Q0IGLZVoE7cTgGgxsrceKMD71Jp2XQgIWD8ltsPfWw3gSc4p+z18UuPN6LuR0mHHENTnClHrAPnOrxbDIl4ZwZgMX8YAQ==\",\"format\":\"anthropic-claude-v1\",\"index\":0}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"37887\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\",\"reasoning\":null},\"finish_reason\":\"stop\",\"native_finish_reason\":\"end_turn\"}]}\n\ndata: {\"id\":\"gen-1784374117-AXXPsQRoclZeQGx2uHeK\",\"object\":\"chat.completion.chunk\",\"created\":1784374117,\"model\":\"anthropic/claude-sonnet-4.6\",\"provider\":\"Anthropic\",\"service_tier\":\"default\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"stop\",\"native_finish_reason\":\"end_turn\"}],\"usage\":{\"prompt_tokens\":61,\"completion_tokens\":80,\"total_tokens\":141,\"cost\":0.001383,\"is_byok\":false,\"prompt_tokens_details\":{\"cached_tokens\":0,\"cache_write_tokens\":0,\"audio_tokens\":0,\"video_tokens\":0},\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"cost_details\":{\"upstream_inference_cost\":0.001383,\"upstream_inference_prompt_cost\":0.000183,\"upstream_inference_completions_cost\":0.0012},\"completion_tokens_details\":{\"reasoning_tokens\":29,\"image_tokens\":0,\"audio_tokens\":0}}}\n\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/pdf/anthropic-tool-result.json

@@ -1,35 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:pdf",
-      "pdf",
-      "provider:anthropic",
-      "protocol:anthropic-messages",
-      "tool",
-      "tool-result"
-    ],
-    "name": "pdf/anthropic-tool-result",
-    "recordedAt": "2026-07-22T18:15:39.002Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.anthropic.com/v1/messages",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"Read the PDF returned by the tool and follow the user's response format exactly.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Return only the verification code from the PDF.\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_pdf_1\",\"name\":\"read_pdf\",\"input\":{}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_pdf_1\",\"content\":[{\"type\":\"text\",\"text\":\"PDF read successfully\"},{\"type\":\"document\",\"source\":{\"type\":\"base64\",\"media_type\":\"application/pdf\",\"data\":\"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\"}}]}]}],\"tools\":[{\"name\":\"read_pdf\",\"description\":\"Read the attached PDF.\",\"input_schema\":{\"type\":\"object\",\"properties\":{},\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":40,\"temperature\":0}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_011CdHYzxyRpSVFgwTm6ccUr\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":2229,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":2,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}        }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}              }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ORCH\"}  }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ID-7391\"}           }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0               }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":2229,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":9}       }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\" }\n\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/pdf/anthropic-user-input.json

@@ -1,34 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:pdf",
-      "pdf",
-      "provider:anthropic",
-      "protocol:anthropic-messages",
-      "user-input"
-    ],
-    "name": "pdf/anthropic-user-input",
-    "recordedAt": "2026-07-22T18:15:37.979Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.anthropic.com/v1/messages",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"document\",\"source\":{\"type\":\"base64\",\"media_type\":\"application/pdf\",\"data\":\"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\"}},{\"type\":\"text\",\"text\":\"Return only the verification code from the PDF.\"}]}],\"stream\":true,\"max_tokens\":40,\"temperature\":0}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_011CdHYzsayb45rgfamcjFt3\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":1602,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":2,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}           }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}         }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ORCH\"}              }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ID-7391\"}}\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0      }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":1602,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":9}    }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"              }\n\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/pdf/bedrock-tool-result.json

@@ -1,36 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:pdf",
-      "pdf",
-      "provider:amazon-bedrock",
-      "protocol:bedrock-converse",
-      "tool",
-      "tool-result"
-    ],
-    "name": "pdf/bedrock-tool-result",
-    "recordedAt": "2026-07-22T18:15:52.400Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-haiku-4-5-20251001-v1%3A0/converse-stream",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"modelId\":\"us.anthropic.claude-haiku-4-5-20251001-v1:0\",\"messages\":[{\"role\":\"user\",\"content\":[{\"text\":\"Return only the verification code from the PDF.\"}]},{\"role\":\"assistant\",\"content\":[{\"toolUse\":{\"toolUseId\":\"call_pdf_1\",\"name\":\"read_pdf\",\"input\":{}}}]},{\"role\":\"user\",\"content\":[{\"toolResult\":{\"toolUseId\":\"call_pdf_1\",\"content\":[{\"text\":\"PDF read successfully\"},{\"document\":{\"format\":\"pdf\",\"name\":\"verification\",\"source\":{\"bytes\":\"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\"}}}],\"status\":\"success\"}}]}],\"system\":[{\"text\":\"Read the PDF returned by the tool and follow the user's response format exactly.\"}],\"inferenceConfig\":{\"maxTokens\":40,\"temperature\":0},\"toolConfig\":{\"tools\":[{\"toolSpec\":{\"name\":\"read_pdf\",\"description\":\"Read the attached PDF.\",\"inputSchema\":{\"json\":{\"type\":\"object\",\"properties\":{},\"additionalProperties\":false}}}}]}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/vnd.amazon.eventstream"
-        },
-        "body": "AAAAqgAAAFLa0GiGCzpldmVudC10eXBlBwAMbWVzc2FnZVN0YXJ0DTpjb250ZW50LXR5cGUHABBhcHBsaWNhdGlvbi9qc29uDTptZXNzYWdlLXR5cGUHAAVldmVudHsicCI6ImFiY2RlZmdoaWprbG1ub3BxcnN0dXZ3eHl6QUJDREVGR0hJSktMTU5PUFFSUyIsInJvbGUiOiJhc3Npc3RhbnQifXIDPnsAAADIAAAAV0lIuCQLOmV2ZW50LXR5cGUHABFjb250ZW50QmxvY2tEZWx0YQ06Y29udGVudC10eXBlBwAQYXBwbGljYXRpb24vanNvbg06bWVzc2FnZS10eXBlBwAFZXZlbnR7ImNvbnRlbnRCbG9ja0luZGV4IjowLCJkZWx0YSI6eyJ0ZXh0IjoiT1JDSCJ9LCJwIjoiYWJjZGVmZ2hpamtsbW5vcHFyc3R1dnd4eXpBQkNERUZHSElKS0xNTk9QUSJ9z2HHHgAAAMUAAABXsdh8lQs6ZXZlbnQtdHlwZQcAEWNvbnRlbnRCbG9ja0RlbHRhDTpjb250ZW50LXR5cGUHABBhcHBsaWNhdGlvbi9qc29uDTptZXNzYWdlLXR5cGUHAAVldmVudHsiY29udGVudEJsb2NrSW5kZXgiOjAsImRlbHRhIjp7InRleHQiOiJJRC0ifSwicCI6ImFiY2RlZmdoaWprbG1ub3BxcnN0dXZ3eHl6QUJDREVGR0hJSktMTU5PIn2+8d8RAAAAywAAAFcO6ML0CzpldmVudC10eXBlBwARY29udGVudEJsb2NrRGVsdGENOmNvbnRlbnQtdHlwZQcAEGFwcGxpY2F0aW9uL2pzb24NOm1lc3NhZ2UtdHlwZQcABWV2ZW50eyJjb250ZW50QmxvY2tJbmRleCI6MCwiZGVsdGEiOnsidGV4dCI6IjcifSwicCI6ImFiY2RlZmdoaWprbG1ub3BxcnN0dXZ3eHl6QUJDREVGR0hJSktMTU5PUFFSU1RVVlcifSIeZ+kAAACzAAAAV8dKafoLOmV2ZW50LXR5cGUHABFjb250ZW50QmxvY2tEZWx0YQ06Y29udGVudC10eXBlBwAQYXBwbGljYXRpb24vanNvbg06bWVzc2FnZS10eXBlBwAFZXZlbnR7ImNvbnRlbnRCbG9ja0luZGV4IjowLCJkZWx0YSI6eyJ0ZXh0IjoiMzkxIn0sInAiOiJhYmNkZWZnaGlqa2xtbm9wcXJzdHV2dyJ9HAStJQAAAMAAAABWDj/Dcws6ZXZlbnQtdHlwZQcAEGNvbnRlbnRCbG9ja1N0b3ANOmNvbnRlbnQtdHlwZQcAEGFwcGxpY2F0aW9uL2pzb24NOm1lc3NhZ2UtdHlwZQcABWV2ZW50eyJjb250ZW50QmxvY2tJbmRleCI6MCwicCI6ImFiY2RlZmdoaWprbG1ub3BxcnN0dXZ3eHl6QUJDREVGR0hJSktMTU5PUFFSU1RVVldYWVowMTIzNDU2NyJ9EPTSwQAAALAAAABRaYm2Hws6ZXZlbnQtdHlwZQcAC21lc3NhZ2VTdG9wDTpjb250ZW50LXR5cGUHABBhcHBsaWNhdGlvbi9qc29uDTptZXNzYWdlLXR5cGUHAAVldmVudHsicCI6ImFiY2RlZmdoaWprbG1ub3BxcnN0dXZ3eHl6QUJDREVGR0hJSktMTU5PUFFSU1RVIiwic3RvcFJlYXNvbiI6ImVuZF90dXJuIn0SuCAcAAAA+AAAAE6MAqhiCzpldmVudC10eXBlBwAIbWV0YWRhdGENOmNvbnRlbnQtdHlwZQcAEGFwcGxpY2F0aW9uL2pzb24NOm1lc3NhZ2UtdHlwZQcABWV2ZW50eyJtZXRyaWNzIjp7ImxhdGVuY3lNcyI6MzkyMn0sInAiOiJhYmNkZWZnaGlqa2xtbm9wcXJzdHV2d3h5ekFCQ0RFIiwidXNhZ2UiOnsiaW5wdXRUb2tlbnMiOjIyNDEsIm91dHB1dFRva2VucyI6Niwic2VydmVyVG9vbFVzYWdlIjp7fSwidG90YWxUb2tlbnMiOjIyNDd9fcd35Hw=",
-        "bodyEncoding": "base64"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/pdf/bedrock-user-input.json

@@ -1,35 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:pdf",
-      "pdf",
-      "provider:amazon-bedrock",
-      "protocol:bedrock-converse",
-      "user-input"
-    ],
-    "name": "pdf/bedrock-user-input",
-    "recordedAt": "2026-07-22T18:15:48.408Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-haiku-4-5-20251001-v1%3A0/converse-stream",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"modelId\":\"us.anthropic.claude-haiku-4-5-20251001-v1:0\",\"messages\":[{\"role\":\"user\",\"content\":[{\"document\":{\"format\":\"pdf\",\"name\":\"verification\",\"source\":{\"bytes\":\"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\"}}},{\"text\":\"Return only the verification code from the PDF.\"}]}],\"inferenceConfig\":{\"maxTokens\":40,\"temperature\":0}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/vnd.amazon.eventstream"
-        },
-        "body": "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",
-        "bodyEncoding": "base64"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/pdf/gemini-tool-result.json

@@ -1,53 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:pdf",
-      "pdf",
-      "provider:google",
-      "protocol:gemini",
-      "tool",
-      "tool-result"
-    ],
-    "name": "pdf/gemini-tool-result",
-    "recordedAt": "2026-07-22T18:21:59.606Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Use read_pdf with path verification.pdf and return the verification code.\"}]}],\"systemInstruction\":{\"parts\":[{\"text\":\"Call read_pdf exactly once with path verification.pdf, then reply only with the verification code from its PDF.\"}]},\"tools\":[{\"functionDeclarations\":[{\"name\":\"read_pdf\",\"description\":\"Read the attached PDF.\",\"parameters\":{\"required\":[\"path\"],\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\"}}}}]}],\"generationConfig\":{\"maxOutputTokens\":256,\"temperature\":0}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "data: {\"candidates\": [{\"content\": {\"parts\": [{\"functionCall\": {\"name\": \"read_pdf\",\"args\": {\"path\": \"verification.pdf\"},\"id\": \"58shgmez\"},\"thoughtSignature\": \"EqkCCqYCARFNMg/JrCTv5i3zYENFBVpZNFL3pbzJmi5Eu387ncF703xFMB4pwyaP7a1gi49EqBhCI2hWOpesU5nZQOLAhGgExKGa2GM+HzpEB5g62r0NFblm/BGkVZaImTuHR7bytfRC5jHQlHKo4OS27OLUVjvkMkBIYsvjhDErY7niERbXJVpyxTVqUf1GgZMSu8kC9/5WDlMs9xVKNT/6KMW4PhhSR9nXg4KZUa+bC03/ydhsWWgBa5aLCgvTq7WPj217xIsmUkSiRedIffPsUSNjYdMHUvWi8bOlvM1veEEP6GIfv5h9gXXzjnHbEHfQxV8PZuBAyY7iM6nqyfkJNdkZ1HdB7DXMBsMsRN6SgrIrFoXX2WaGrkoEI5tdZx1t/gdwF1jEVT6k\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 81,\"candidatesTokenCount\": 18,\"totalTokenCount\": 151,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 81}],\"thoughtsTokenCount\": 52,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RAphaui3OaSHz7IPy8Kb4Ak\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 81,\"candidatesTokenCount\": 18,\"totalTokenCount\": 151,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 81}],\"thoughtsTokenCount\": 52,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RAphaui3OaSHz7IPy8Kb4Ak\"}\r\n\r\n"
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Use read_pdf with path verification.pdf and return the verification code.\"}]},{\"role\":\"model\",\"parts\":[{\"functionCall\":{\"id\":\"58shgmez\",\"name\":\"read_pdf\",\"args\":{\"path\":\"verification.pdf\"}},\"thoughtSignature\":\"EqkCCqYCARFNMg/JrCTv5i3zYENFBVpZNFL3pbzJmi5Eu387ncF703xFMB4pwyaP7a1gi49EqBhCI2hWOpesU5nZQOLAhGgExKGa2GM+HzpEB5g62r0NFblm/BGkVZaImTuHR7bytfRC5jHQlHKo4OS27OLUVjvkMkBIYsvjhDErY7niERbXJVpyxTVqUf1GgZMSu8kC9/5WDlMs9xVKNT/6KMW4PhhSR9nXg4KZUa+bC03/ydhsWWgBa5aLCgvTq7WPj217xIsmUkSiRedIffPsUSNjYdMHUvWi8bOlvM1veEEP6GIfv5h9gXXzjnHbEHfQxV8PZuBAyY7iM6nqyfkJNdkZ1HdB7DXMBsMsRN6SgrIrFoXX2WaGrkoEI5tdZx1t/gdwF1jEVT6k\"}]},{\"role\":\"user\",\"parts\":[{\"functionResponse\":{\"id\":\"58shgmez\",\"name\":\"read_pdf\",\"response\":{\"name\":\"read_pdf\",\"content\":\"PDF read successfully\"},\"parts\":[{\"inlineData\":{\"mimeType\":\"application/pdf\",\"data\":\"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\"}}]}}]}],\"systemInstruction\":{\"parts\":[{\"text\":\"Call read_pdf exactly once with path verification.pdf, then reply only with the verification code from its PDF.\"}]},\"tools\":[{\"functionDeclarations\":[{\"name\":\"read_pdf\",\"description\":\"Read the attached PDF.\",\"parameters\":{\"required\":[\"path\"],\"type\":\"object\",\"properties\":{\"path\":{\"type\":\"string\"}}}}]}],\"generationConfig\":{\"maxOutputTokens\":256,\"temperature\":0}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"ORCHID-7391\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 123,\"candidatesTokenCount\": 8,\"totalTokenCount\": 184,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 123}],\"thoughtsTokenCount\": 53,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RgphaoL6CMjQz7IPjOnEmQI\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"EqECCp4CARFNMg9obBl8O6iU9lawUIWiE+1vztZm9NtaT9FuyJz343hd9ruz+xPco4Q1DY1GF81ZiSI2ElBkt8Wfwsqtix9LNGSMvbZhhk/ZnB54t05M/Dft1kujcMvEdZUWUI/jWaJ349tO1bKVH9MacG5+gl0n4y8DwyQZSV3xIcet547drSkcA/TM03RB+yj1/dcLHsvUjmv9EnO897vZgO2Dk4tbZ2NyCtOeQ3JKVhUTLg2pjkGk+POCNiOdESWiUzxdQKw9LiV6nnzi071tXNiMeVimq6d7xAzRVNapI2uXynvn9Uk3eyn85purOFa8cKriK9oD6vcyGMqgd9+gu2m3to0IHqd7o+2YSr1m5qV1xT1R2/WRQEtb1b1AuOAU6w==\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 1277,\"candidatesTokenCount\": 8,\"totalTokenCount\": 1338,\"promptTokensDetails\": [{\"modality\": \"IMAGE\",\"tokenCount\": 1102},{\"modality\": \"TEXT\",\"tokenCount\": 175}],\"thoughtsTokenCount\": 53,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"RgphaoL6CMjQz7IPjOnEmQI\"}\r\n\r\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/pdf/gemini-user-input.json

@@ -1,34 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:pdf",
-      "pdf",
-      "provider:google",
-      "protocol:gemini",
-      "user-input"
-    ],
-    "name": "pdf/gemini-user-input",
-    "recordedAt": "2026-07-22T18:20:55.140Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"inlineData\":{\"mimeType\":\"application/pdf\",\"data\":\"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\"}},{\"text\":\"Return only the verification code from the PDF.\"}]}],\"generationConfig\":{\"maxOutputTokens\":256,\"temperature\":0}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "data: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"ORCH\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 10,\"candidatesTokenCount\": 2,\"totalTokenCount\": 127,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 10}],\"thoughtsTokenCount\": 115,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"BQpharW2KaPgz7IP6uSLiAw\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"ID-7391\"}],\"role\": \"model\"},\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 10,\"candidatesTokenCount\": 8,\"totalTokenCount\": 133,\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 10}],\"thoughtsTokenCount\": 115,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"BQpharW2KaPgz7IP6uSLiAw\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"EokECoYEARFNMg8L4fpLqaX8tIQZcvw2vLt3WsFjGqpuJGgna0/AGczwuzndRcf3LGIEaliCf4ijVOb1AG4/VPBh1kMzfjeAyHhvWIe4yQVoBwI7BjpFyLie+SnGTXQXKKy5ygRqRLFsV6DcAixNXXBHJw2x/2Nhtriryqs4fhWrL/P7ppHC10sMnTwN6Mw5x20NKwgT+rrw6lvYmQe9rdQsBJ6Zmp0GpPlwZZiAgzvwPfVoNwHSGb54xe/T9wjISjwWNgpedhbsIBDRZFDwruS4x57KBKeMPO69GLfeMP8PJ7rpR0HgT7nRbrl/OdykG/jqSMTvoRSqxawsD+Yr/DukgGatyfB5Ic+X4RhD07URpkGTAu/cakBtzhSmM/hpzKU9m/cId1UCjopLTtonUqSAKkroPdp8kIYw0MI2OZCNVwbDrdClUPmjRKfcTkcC2jNj1rS+WDFbm+mo+SP3rDSvvCdyJuiXHGKiM2EhbYnu42aHVC6w7eAe4Gv3Fq/0faW47r0ihbiAohFB9XUA+fD07g83EjIuc9Q6BRVTTcBfoRkrR/yFZKt3qwPq02W6rPD13/1wAnMtabNcxePMMGk7Dlxwng9yPS0NEge2KD+miOj9SC4aTvOTq2451tfK1x3UZqqb205zGOPbjizhH/CA/PGkG84hdkAG4mrUK0rEHqeWwRXDsxpyfto=\"}],\"role\": \"model\"},\"finishReason\": \"STOP\",\"index\": 0}],\"usageMetadata\": {\"promptTokenCount\": 530,\"candidatesTokenCount\": 8,\"totalTokenCount\": 653,\"promptTokensDetails\": [{\"modality\": \"IMAGE\",\"tokenCount\": 520},{\"modality\": \"TEXT\",\"tokenCount\": 10}],\"thoughtsTokenCount\": 115,\"serviceTier\": \"standard\"},\"modelVersion\": \"gemini-3.5-flash\",\"responseId\": \"BQpharW2KaPgz7IP6uSLiAw\"}\r\n\r\n"
-      }
-    }
-  ]
-}

packages/ai/test/fixtures/recordings/zai-images/generates-an-image.json

@@ -1,28 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": ["prefix:zai-images", "provider:zai", "protocol:zai-images"],
-    "name": "zai-images/generates-an-image",
-    "recordedAt": "2026-07-19T16:03:55.761Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.z.ai/api/paas/v4/images/generations",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"cogview-4-250304\",\"prompt\":\"A simple flat red circle centered on a plain white background.\",\"size\":\"1024x1024\",\"quality\":\"standard\",\"user_id\":\"opencode-image-test\"}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/json; charset=UTF-8"
-        },
-        "body": "{\"created\":1784477028,\"data\":[{\"url\":\"https://mfile.z.ai/1784477035500-43574eab2b6e402da9063d6ac22dfefb.png?ufileattname=202607200003482062c3bba9b04f7d_watermark.png\"}],\"id\":\"202607200003482062c3bba9b04f7d\",\"request_id\":\"202607200003482062c3bba9b04f7d\"}"
-      }
-    }
-  ]
-}

packages/ai/test/image.test.ts

@@ -1,578 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { Image, ImageClient, ImageInput } from "../src"
-import { Google, OpenAI, XAI, ZAI } from "../src/providers"
-import { it } from "./lib/effect"
-import { dynamicResponse } from "./lib/http"
-
-describe("Image", () => {
-  it.effect("generates images through the OpenAI Images API", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model: OpenAI.configure({
-          apiKey: "test",
-          baseURL: "https://api.openai.test/v1",
-          queryParams: { "api-version": "v1" },
-          http: { body: { deployment: "test" }, headers: { "x-default": "yes" } },
-        }).image("gpt-image-2"),
-        prompt: "A robot tending a rooftop garden",
-        options: {
-          n: 2,
-          size: "2048x2048",
-          quality: "future-quality",
-          outputFormat: "jpeg",
-          output_format: "avif",
-          outputCompression: 30,
-          output_compression: 40,
-          background: "opaque",
-          native_default: true,
-          future_option: true,
-        },
-        http: {
-          body: { output_format: "webp", output_compression: 50, future_option: "http", request_metadata: "value" },
-          headers: { "x-request": "yes" },
-          query: { trace: "1" },
-        },
-      })
-
-      expect(response.images).toHaveLength(2)
-      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.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.url).toBe("https://api.openai.test/v1/images/generations?api-version=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({
-                  model: "gpt-image-2",
-                  prompt: "A robot tending a rooftop garden",
-                  n: 2,
-                  size: "2048x2048",
-                  quality: "future-quality",
-                  background: "opaque",
-                  output_format: "webp",
-                  output_compression: 50,
-                  native_default: true,
-                  future_option: "http",
-                  deployment: "test",
-                  request_metadata: "value",
-                })
-                return input.respond(
-                  JSON.stringify({
-                    data: [{ b64_json: "AQID", revised_prompt: "A precise robot" }, { b64_json: "BAUG" }],
-                    output_format: "webp",
-                    usage: { input_tokens: 4, output_tokens: 8, total_tokens: 12 },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                )
-              }),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("preserves native snake_case and unknown request options", () =>
-    Image.generate({
-      model: OpenAI.configure({
-        apiKey: "test",
-        baseURL: "https://api.openai.test/v1",
-      }).image("future-image-model"),
-      prompt: "A lighthouse in fog",
-      options: {
-        outputFormat: "jpeg",
-        output_format: "avif",
-        outputCompression: 30,
-        output_compression: 40,
-        provider_future_option: { enabled: true },
-      },
-    }).pipe(
-      Effect.tap((response) =>
-        Effect.sync(() => {
-          expect(response.image?.mediaType).toBe("image/avif")
-        }),
-      ),
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(JSON.parse(input.text)).toEqual({
-                model: "future-image-model",
-                prompt: "A lighthouse in fog",
-                output_format: "avif",
-                output_compression: 40,
-                provider_future_option: { enabled: true },
-              })
-              return Effect.succeed(
-                input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
-                  headers: { "content-type": "application/json" },
-                }),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("routes OpenAI byte inputs and masks through multipart edits", () =>
-    Image.generate({
-      model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("future-model"),
-      prompt: "Combine these images",
-      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,
-      },
-      http: {
-        body: { quality: "low", model: "corrupt", prompt: "corrupt", image: "corrupt", "image[]": "corrupt" },
-        headers: { "content-type": "application/json" },
-      },
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.url).toBe("https://api.openai.test/v1/images/edits")
-                expect(request.headers.get("content-type")).toStartWith("multipart/form-data; boundary=")
-                expect(input.text).toContain('name="model"\r\n\r\nfuture-model')
-                expect(input.text).toContain('name="prompt"\r\n\r\nCombine these images')
-                expect(input.text.match(/name="image\[\]"/g)).toHaveLength(2)
-                expect(input.text).toContain('name="mask"')
-                expect(input.text).toContain('name="quality"\r\n\r\nlow')
-                expect(input.text).not.toContain("corrupt")
-                return input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
-                  headers: { "content-type": "application/json" },
-                })
-              }),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("routes OpenAI URL and file inputs through JSON edits", () =>
-    Image.generate({
-      model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("future-model"),
-      prompt: "Combine these images",
-      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(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(JSON.parse(input.text)).toEqual({
-                model: "future-model",
-                prompt: "Combine these images",
-                images: [{ image_url: "https://example.test/source.png" }, { file_id: "file_123" }],
-                mask: { file_id: "file_mask" },
-                future_option: true,
-              })
-              return Effect.succeed(
-                input.respond(JSON.stringify({ data: [{ b64_json: "AQID" }] }), {
-                  headers: { "content-type": "application/json" },
-                }),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("routes ordered xAI image inputs through JSON edits", () =>
-    Image.generate({
-      model: XAI.configure({ apiKey: "test", baseURL: "https://api.xai.test/v1" }).image("future-model"),
-      prompt: "Combine these images",
-      images: [
-        ImageInput.bytes(Uint8Array.from([1, 2, 3]), "image/png"),
-        ImageInput.url("https://example.test/source.jpg"),
-        ImageInput.file("file_123"),
-      ],
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(JSON.parse(input.text)).toEqual({
-                model: "future-model",
-                prompt: "Combine these images",
-                images: [
-                  { url: "data:image/png;base64,AQID", type: "image_url" },
-                  { url: "https://example.test/source.jpg", type: "image_url" },
-                  { file_id: "file_123" },
-                ],
-              })
-              return Effect.succeed(
-                input.respond(JSON.stringify({ data: [{ b64_json: "AQID", mime_type: "image/png" }] }), {
-                  headers: { "content-type": "application/json" },
-                }),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("uses xAI's singular image field for one input", () =>
-    Image.generate({
-      model: XAI.configure({ apiKey: "test", baseURL: "https://api.xai.test/v1" }).image("future-model"),
-      prompt: "Edit this image",
-      images: [ImageInput.file("file_123")],
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(JSON.parse(input.text)).toEqual({
-                model: "future-model",
-                prompt: "Edit this image",
-                image: { file_id: "file_123" },
-              })
-              return Effect.succeed(
-                input.respond(JSON.stringify({ data: [{ b64_json: "AQID", mime_type: "image/png" }] }), {
-                  headers: { "content-type": "application/json" },
-                }),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("lowers ordered Google image inputs into generateContent parts", () =>
-    Image.generate({
-      model: Google.configure({ apiKey: "test", baseURL: "https://google.test/v1beta" }).image("future-model"),
-      prompt: "Combine these images",
-      images: [
-        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(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(JSON.parse(input.text).contents[0].parts).toEqual([
-                { text: "Combine these images" },
-                { inlineData: { mimeType: "image/png", data: "AQID" } },
-                { inlineData: { mimeType: "image/jpeg", data: "BAUG" } },
-                {
-                  fileData: {
-                    mimeType: "image/webp",
-                    fileUri: "https://generativelanguage.googleapis.com/v1beta/files/123",
-                  },
-                },
-              ])
-              return Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    candidates: [{ content: { parts: [{ inlineData: { mimeType: "image/png", data: "AQID" } }] } }],
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("rejects unsupported provider inputs before sending", () =>
-    Effect.gen(function* () {
-      const cases = [
-        Image.generate({
-          model: Google.configure({ apiKey: "test" }).image("model"),
-          prompt: "edit",
-          images: [ImageInput.url("https://example.test/image.png")],
-        }),
-        Image.generate({
-          model: ZAI.configure({ apiKey: "test" }).image("model"),
-          prompt: "edit",
-          images: [ImageInput.bytes(Uint8Array.from([1]), "image/png")],
-        }),
-      ]
-      yield* Effect.forEach(cases, (program) =>
-        program.pipe(
-          Effect.flip,
-          Effect.tap((error) => Effect.sync(() => expect(error.reason._tag).toBe("InvalidRequest"))),
-        ),
-      )
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(dynamicResponse(() => Effect.die("unsupported input reached the network"))),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("generates images through the Google generateContent API", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model: Google.configure({
-          apiKey: "test",
-          baseURL: "https://generativelanguage.test/v1beta/",
-          headers: { "x-default": "yes" },
-          http: { body: { labels: { deployment: "test" } }, query: { api: "v1" } },
-        }).image("any-model-id"),
-        prompt: "A robot tending a rooftop garden",
-        options: {
-          aspectRatio: "16:9",
-          imageSize: "2K",
-          seed: 42,
-          thinkingLevel: "HIGH",
-          includeThoughts: true,
-          futureOption: true,
-          imageConfig: { aspectRatio: "4:3", nativeImageOption: true },
-          thinkingConfig: { thinkingLevel: "LOW", nativeThinkingOption: true },
-        },
-        http: {
-          body: {
-            safetySettings: [],
-            generationConfig: {
-              imageConfig: { aspectRatio: "3:2", httpImageOption: true },
-              thinkingConfig: { includeThoughts: false, httpThinkingOption: true },
-              futureOption: "http",
-              httpOption: true,
-            },
-          },
-          headers: { "x-request": "yes" },
-          query: { trace: "1" },
-        },
-      })
-
-      expect(response.images).toHaveLength(3)
-      expect(response.images.map((image) => image.data)).toEqual([
-        Uint8Array.from([1, 2, 3]),
-        Uint8Array.from([4, 5, 6]),
-        Uint8Array.from([7, 8, 9]),
-      ])
-      expect(response.images.map((image) => image.mediaType)).toEqual(["image/png", "image/jpeg", "image/webp"])
-      expect(response.images[0].providerMetadata).toMatchObject({ google: { thoughtSignature: "signature-1" } })
-      expect(response.images[1].providerMetadata).toMatchObject({
-        google: { candidateIndex: 0, partIndex: 3, finishReason: "STOP" },
-      })
-      expect(response.images[2].providerMetadata).toMatchObject({ google: { candidateIndex: 7, partIndex: 0 } })
-      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",
-          responseId: "response-1",
-          promptFeedback: undefined,
-          candidates: [
-            {
-              index: 0,
-              finishReason: "STOP",
-              finishMessage: undefined,
-              safetyRatings: [{ category: "safe" }],
-              citationMetadata: undefined,
-              groundingMetadata: undefined,
-              parts: [
-                {
-                  type: "inlineData",
-                  mediaType: "image/png",
-                  thought: undefined,
-                  thoughtSignature: "signature-1",
-                },
-                { type: "text", text: "planning", thought: true, thoughtSignature: "text-signature" },
-                {
-                  type: "inlineData",
-                  mediaType: "image/png",
-                  thought: true,
-                  thoughtSignature: "draft-signature",
-                },
-                {
-                  type: "inlineData",
-                  mediaType: "image/jpeg",
-                  thought: undefined,
-                  thoughtSignature: undefined,
-                },
-              ],
-            },
-            {
-              index: 7,
-              finishReason: undefined,
-              finishMessage: undefined,
-              safetyRatings: undefined,
-              citationMetadata: undefined,
-              groundingMetadata: undefined,
-              parts: [
-                {
-                  type: "inlineData",
-                  mediaType: "image/webp",
-                  thought: undefined,
-                  thoughtSignature: undefined,
-                },
-              ],
-            },
-          ],
-        },
-      })
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.url).toBe(
-                  "https://generativelanguage.test/v1beta/models/any-model-id:generateContent?api=v1&trace=1",
-                )
-                expect(request.headers.get("x-goog-api-key")).toBe("test")
-                expect(request.headers.get("x-default")).toBe("yes")
-                expect(request.headers.get("x-request")).toBe("yes")
-                expect(JSON.parse(input.text)).toEqual({
-                  contents: [{ role: "user", parts: [{ text: "A robot tending a rooftop garden" }] }],
-                  generationConfig: {
-                    responseModalities: ["IMAGE"],
-                    imageConfig: {
-                      aspectRatio: "3:2",
-                      imageSize: "2K",
-                      nativeImageOption: true,
-                      httpImageOption: true,
-                    },
-                    seed: 42,
-                    thinkingConfig: {
-                      thinkingLevel: "LOW",
-                      includeThoughts: false,
-                      nativeThinkingOption: true,
-                      httpThinkingOption: true,
-                    },
-                    futureOption: "http",
-                    httpOption: true,
-                  },
-                  labels: { deployment: "test" },
-                  safetySettings: [],
-                })
-                return input.respond(
-                  JSON.stringify({
-                    candidates: [
-                      {
-                        content: {
-                          parts: [
-                            {
-                              inlineData: { mimeType: "image/png", data: "AQID" },
-                              thoughtSignature: "signature-1",
-                            },
-                            { text: "planning", thought: true, thoughtSignature: "text-signature" },
-                            {
-                              inlineData: { mimeType: "image/png", data: "CgsM" },
-                              thought: true,
-                              thoughtSignature: "draft-signature",
-                            },
-                            { inlineData: { mimeType: "image/jpeg", data: "BAUG" } },
-                          ],
-                        },
-                        finishReason: "STOP",
-                        safetyRatings: [{ category: "safe" }],
-                      },
-                      {
-                        index: 7,
-                        content: { parts: [{ inlineData: { mimeType: "image/webp", data: "BwgJ" } }] },
-                      },
-                    ],
-                    usageMetadata: {
-                      promptTokenCount: 5,
-                      candidatesTokenCount: 7,
-                      thoughtsTokenCount: 3,
-                      totalTokenCount: 15,
-                      serviceTier: "STANDARD",
-                    },
-                    modelVersion: "gemini-3.1-flash-image",
-                    responseId: "response-1",
-                  }),
-                  { 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(
-        "gemini-3.1-flash-image",
-      ),
-      prompt: "A robot tending a rooftop garden",
-    }).pipe(
-      Effect.flip,
-      Effect.tap((error) =>
-        Effect.sync(() => {
-          expect(error.reason._tag).toBe("InvalidProviderOutput")
-          if (error.reason._tag !== "InvalidProviderOutput") return
-          expect(error.reason.message).toContain("finish reasons: IMAGE_SAFETY")
-          expect(error.reason.providerMetadata).toEqual({
-            google: {
-              promptFeedback: { blockReason: "SAFETY" },
-              candidates: [
-                {
-                  index: 0,
-                  finishReason: "IMAGE_SAFETY",
-                  finishMessage: "The generated image was blocked by safety filters.",
-                  safetyRatings: [{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", blocked: true }],
-                  citationMetadata: undefined,
-                  groundingMetadata: undefined,
-                  parts: [{ type: "text", text: "blocked", thought: false, thoughtSignature: undefined }],
-                },
-              ],
-            },
-          })
-        }),
-      ),
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.succeed(
-                input.respond(
-                  JSON.stringify({
-                    candidates: [
-                      {
-                        content: { parts: [{ text: "blocked", thought: false }] },
-                        finishReason: "IMAGE_SAFETY",
-                        finishMessage: "The generated image was blocked by safety filters.",
-                        safetyRatings: [{ category: "HARM_CATEGORY_DANGEROUS_CONTENT", blocked: true }],
-                      },
-                    ],
-                    promptFeedback: { blockReason: "SAFETY" },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                ),
-              ),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-})

packages/ai/test/image.types.ts

@@ -1,161 +0,0 @@
-import {
-  Image,
-  ImageInput,
-  ImageModel,
-  type ImageModelOptions,
-  type ImageOptions,
-  type ImageRequestFor,
-  type ImageRoute,
-} from "../src"
-import { Google, OpenAI, XAI, ZAI } from "../src/providers"
-
-type GoogleLikeOptions = {
-  readonly aspectRatio?: "1:1" | "16:9"
-  readonly imageSize?: "1K" | "2K"
-} & 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> = { aspectRatio: "wide" }
-void invalidGoogleOptions
-
-Image.generate({
-  model: google,
-  prompt: "A lighthouse",
-  images: [
-    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"),
-  ],
-  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",
-  options: {
-    aspectRatio: "16:9",
-    imageSize: "2K",
-    seed: 42,
-    thinkingLevel: "HIGH",
-    includeThoughts: true,
-    futureOption: true,
-  },
-})
-Image.generate({
-  model: googleProvider,
-  prompt: "A lighthouse",
-  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", 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", 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: { options: { quality: "medium" } } })
-const futureOpenAIOptions: ImageModelOptions<typeof openai> = { quality: "future-quality" }
-void futureOpenAIOptions
-Image.generate({
-  model: openai,
-  prompt: "A lighthouse",
-  images: [ImageInput.url("https://example.com/source.png"), ImageInput.file("file_123")],
-  options: {
-    mask: ImageInput.bytes(Uint8Array.from([1]), "image/png"),
-    quality: "hd",
-    outputFormat: "webp",
-    size: "2048x2048",
-    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", options: { quality: 1 } })
-// @ts-expect-error Known OpenAI numeric options retain their value kind.
-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", 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: { options: { resolution: "1k" } } })
-Image.generate({
-  model: xai,
-  prompt: "A lighthouse",
-  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,
-  },
-})
-Image.generate({
-  model: xai,
-  prompt: "A lighthouse",
-  options: { aspect_ratio: "16:9", response_format: "b64_json", native_future_option: true },
-})
-// @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", 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: { options: { quality: "hd" } } })
-Image.generate({
-  model: zai,
-  prompt: "A lighthouse",
-  options: { quality: "future-quality", userID: "user-123", future_option: true },
-})
-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", options: { quality: 1 } })
-// @ts-expect-error Known Z.ai user IDs retain their value kind.
-Image.generate({ model: zai, prompt: "A lighthouse", options: { userID: 1 } })
-
-declare const generic: ImageModel<ImageOptions>
-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 image inputs.
-Image.generate({ model: openai, prompt: "A lighthouse", images: ["AQID"] })
-// @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 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",
-  options: { aspectRatio: "1:1", futureOption: true },
-})
-const typedRequest: ImageRequestFor<GoogleLikeOptions> = request
-void typedRequest
-
-// @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 requests no longer expose a common size option.
-Image.generate({ model: openai, prompt: "A lighthouse", size: { width: 1024, height: 1024 } })
-// @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 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") })

packages/ai/test/lib/image.ts

@@ -1,29 +0,0 @@
-export const dimensions = (data: Uint8Array) => {
-  if (data[0] === 0x89 && data[1] === 0x50 && data[2] === 0x4e && data[3] === 0x47)
-    return {
-      width: readUint32(data, 16),
-      height: readUint32(data, 20),
-    }
-  if (data[0] === 0xff && data[1] === 0xd8) {
-    for (let offset = 2; offset + 8 < data.length; ) {
-      if (data[offset] !== 0xff) {
-        offset++
-        continue
-      }
-      const marker = data[offset + 1]
-      if (
-        marker !== undefined &&
-        [0xc0, 0xc1, 0xc2, 0xc3, 0xc5, 0xc6, 0xc7, 0xc9, 0xca, 0xcb, 0xcd, 0xce, 0xcf].includes(marker)
-      )
-        return {
-          width: (data[offset + 7] << 8) | data[offset + 8],
-          height: (data[offset + 5] << 8) | data[offset + 6],
-        }
-      offset += 2 + ((data[offset + 2] << 8) | data[offset + 3])
-    }
-  }
-  throw new Error("Unsupported image fixture format")
-}
-
-const readUint32 = (data: Uint8Array, offset: number) =>
-  ((data[offset] << 24) | (data[offset + 1] << 16) | (data[offset + 2] << 8) | data[offset + 3]) >>> 0

packages/ai/test/provider-package.test.ts

@@ -1,296 +0,0 @@
-import { describe, expect, test } from "bun:test"
-import { model } from "@opencode-ai/ai/providers/openai"
-
-describe("provider package entrypoints", () => {
-  test("semantic API aliases expose the same contract", async () => {
-    const modules = await Promise.all([
-      import("@opencode-ai/ai/providers/openai"),
-      import("@opencode-ai/ai/providers/openai/responses"),
-      import("@opencode-ai/ai/providers/openai/chat"),
-      import("@opencode-ai/ai/providers/anthropic"),
-      import("@opencode-ai/ai/providers/anthropic-compatible"),
-      import("@opencode-ai/ai/providers/openai-compatible"),
-      import("@opencode-ai/ai/providers/openai-compatible/responses"),
-      import("@opencode-ai/ai/providers/amazon-bedrock"),
-      import("@opencode-ai/ai/providers/azure"),
-      import("@opencode-ai/ai/providers/azure/responses"),
-      import("@opencode-ai/ai/providers/azure/chat"),
-      import("@opencode-ai/ai/providers/google"),
-      import("@opencode-ai/ai/providers/google-vertex"),
-      import("@opencode-ai/ai/providers/google-vertex/gemini"),
-      import("@opencode-ai/ai/providers/google-vertex/chat"),
-      import("@opencode-ai/ai/providers/google-vertex/responses"),
-      import("@opencode-ai/ai/providers/google-vertex/messages"),
-    ])
-
-    for (const module of modules) expect(module.model).toBeFunction()
-    expect(modules[0].model).toBe(modules[1].model)
-    expect(modules[8].model).toBe(modules[9].model)
-    expect(modules[12].model).toBe(modules[13].model)
-  })
-
-  test("maps package settings onto the executable model", () => {
-    const selected = model("gpt-5", {
-      apiKey: "fixture",
-      baseURL: "https://api.openai.test/v1",
-      headers: { "x-application": "opencode" },
-      body: { service_tier: "priority" },
-      limits: { context: 200_000, output: 64_000 },
-      unrelatedInheritedSetting: true,
-    })
-
-    expect(selected.route.id).toBe("openai-responses")
-    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
-    expect(selected.route.defaults.http?.body).toEqual({ service_tier: "priority" })
-    expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
-  })
-
-  test("selects transport without changing the semantic API", () => {
-    expect(model("gpt-5", { apiKey: "fixture" }).route.id).toBe("openai-responses")
-    expect(model("gpt-5", { apiKey: "fixture", transport: "websocket" }).route.id).toBe("openai-responses-websocket")
-  })
-
-  test("maps OpenAI-compatible Responses settings onto the executable model", async () => {
-    const OpenAICompatibleResponses = await import("@opencode-ai/ai/providers/openai-compatible/responses")
-    const selected = OpenAICompatibleResponses.model("custom-model", {
-      apiKey: "fixture",
-      baseURL: "https://responses.example.test/v1",
-      provider: "example",
-      headers: { "x-application": "opencode" },
-      body: { service_tier: "priority" },
-      limits: { context: 200_000, output: 64_000 },
-      providerOptions: { openai: { reasoningEffort: "low", store: true } },
-    })
-
-    expect(String(selected.provider)).toBe("example")
-    expect(selected.route.id).toBe("openai-compatible-responses")
-    expect(selected.route.endpoint).toMatchObject({
-      baseURL: "https://responses.example.test/v1",
-      path: "/responses",
-    })
-    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
-    expect(selected.route.defaults.http?.body).toEqual({ service_tier: "priority" })
-    expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
-    expect(selected.route.defaults.providerOptions).toEqual({
-      openai: { reasoningEffort: "low", store: true },
-    })
-  })
-
-  test("maps Anthropic-compatible settings onto the executable model", async () => {
-    const AnthropicCompatible = await import("@opencode-ai/ai/providers/anthropic-compatible")
-    const selected = AnthropicCompatible.model("compatible-model", {
-      apiKey: "fixture",
-      baseURL: "https://messages.example.test/v1",
-      provider: "example",
-      headers: { "x-application": "opencode" },
-      body: { metadata: { user_id: "user_1" } },
-      limits: { context: 200_000, output: 64_000 },
-    })
-
-    expect(String(selected.provider)).toBe("example")
-    expect(selected.route.id).toBe("anthropic-messages")
-    expect(selected.route.endpoint).toMatchObject({
-      baseURL: "https://messages.example.test/v1",
-      path: "/messages",
-    })
-    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
-    expect(selected.route.defaults.http?.body).toEqual({ metadata: { user_id: "user_1" } })
-    expect(selected.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
-  })
-
-  test("requires an Anthropic-compatible base URL at runtime", async () => {
-    const AnthropicCompatible = await import("@opencode-ai/ai/providers/anthropic-compatible")
-    expect(() =>
-      Reflect.apply(AnthropicCompatible.model, undefined, ["compatible-model", { apiKey: "fixture" }]),
-    ).toThrow("Anthropic-compatible providers require a baseURL")
-  })
-
-  test("rejects conflicting Anthropic-compatible auth settings at runtime", async () => {
-    const Anthropic = await import("@opencode-ai/ai/providers/anthropic")
-    const AnthropicCompatible = await import("@opencode-ai/ai/providers/anthropic-compatible")
-    expect(() =>
-      Reflect.apply(AnthropicCompatible.model, undefined, [
-        "compatible-model",
-        {
-          apiKey: "fixture",
-          authToken: "token",
-          baseURL: "https://messages.example.test/v1",
-        },
-      ]),
-    ).toThrow("Anthropic-compatible apiKey cannot be combined with authToken")
-    expect(() =>
-      Reflect.apply(Anthropic.model, undefined, ["claude-sonnet-4-6", { apiKey: "fixture", authToken: "token" }]),
-    ).toThrow("Anthropic apiKey cannot be combined with authToken")
-  })
-
-  test("maps legacy OpenAI organization and project settings to headers", () => {
-    const selected = model("gpt-5", {
-      apiKey: "fixture",
-      organization: "org_123",
-      project: "proj_123",
-    })
-
-    expect(selected.route.defaults.headers).toMatchObject({
-      "OpenAI-Organization": "org_123",
-      "OpenAI-Project": "proj_123",
-    })
-  })
-
-  test("selects Azure API entrypoints with the same model contract", async () => {
-    const Azure = await import("@opencode-ai/ai/providers/azure")
-    const AzureChat = await import("@opencode-ai/ai/providers/azure/chat")
-    const AzureResponses = await import("@opencode-ai/ai/providers/azure/responses")
-    const settings = {
-      apiKey: "fixture",
-      resourceName: "opencode-test",
-      headers: { "x-application": "opencode" },
-      body: { service_tier: "priority" },
-      limits: { context: 200_000, output: 64_000 },
-    }
-
-    const responses = AzureResponses.model("deployment", settings)
-    const chat = AzureChat.model("deployment", settings)
-
-    expect(Azure.model("deployment", settings).route.id).toBe("azure-openai-responses")
-    expect(responses.route.id).toBe("azure-openai-responses")
-    expect(responses.route.endpoint.baseURL).toBe("https://opencode-test.openai.azure.com/openai/v1")
-    expect(responses.route.defaults.headers).toEqual({ "x-application": "opencode" })
-    expect(responses.route.defaults.http?.body).toEqual({ service_tier: "priority" })
-    expect(responses.route.defaults.limits).toEqual({ context: 200_000, output: 64_000 })
-    expect(chat.route.id).toBe("azure-openai-chat")
-  })
-
-  test("maps Google package settings onto the Gemini model", async () => {
-    const Google = await import("@opencode-ai/ai/providers/google")
-    const selected = Google.model("gemini-2.5-flash", {
-      apiKey: "fixture",
-      baseURL: "https://generativelanguage.test/v1beta",
-      headers: { "x-application": "opencode" },
-      body: { safetySettings: [] },
-      limits: { context: 1_000_000, output: 65_536 },
-      providerOptions: { gemini: { thinkingConfig: { thinkingBudget: 1_024 } } },
-    })
-
-    expect(selected.route.id).toBe("gemini")
-    expect(selected.route.endpoint.baseURL).toBe("https://generativelanguage.test/v1beta")
-    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
-    expect(selected.route.defaults.http?.body).toEqual({ safetySettings: [] })
-    expect(selected.route.defaults.limits).toEqual({ context: 1_000_000, output: 65_536 })
-    expect(selected.route.defaults.providerOptions).toEqual({
-      gemini: { thinkingConfig: { thinkingBudget: 1_024 } },
-    })
-  })
-
-  test("selects Vertex entrypoints with the same model contract", async () => {
-    const GoogleVertex = await import("@opencode-ai/ai/providers/google-vertex")
-    const GoogleVertexGemini = await import("@opencode-ai/ai/providers/google-vertex/gemini")
-    const GoogleVertexChat = await import("@opencode-ai/ai/providers/google-vertex/chat")
-    const GoogleVertexResponses = await import("@opencode-ai/ai/providers/google-vertex/responses")
-    const GoogleVertexMessages = await import("@opencode-ai/ai/providers/google-vertex/messages")
-    const gemini = GoogleVertex.model("gemini-3.5-flash", {
-      apiKey: "fixture",
-      headers: { "x-application": "opencode" },
-      body: { safetySettings: [] },
-      limits: { context: 1_000_000, output: 65_536 },
-    })
-    const messages = GoogleVertexMessages.model("claude-sonnet-4-6", {
-      accessToken: "fixture",
-      location: "global",
-      project: "vertex-project",
-    })
-    const chat = GoogleVertexChat.model("deepseek-ai/deepseek-v3.2-maas", {
-      accessToken: "fixture",
-      location: "global",
-      project: "vertex-project",
-    })
-    const responses = GoogleVertexResponses.model("xai/grok-4.20-reasoning", {
-      accessToken: "fixture",
-      location: "global",
-      project: "vertex-project",
-    })
-
-    expect(GoogleVertexGemini.model).toBe(GoogleVertex.model)
-    expect(gemini.route.id).toBe("google-vertex-gemini")
-    expect(gemini.route.protocol).toBe("gemini")
-    expect(gemini.route.endpoint.baseURL).toBe("https://aiplatform.googleapis.com/v1/publishers/google")
-    expect(gemini.route.defaults.headers).toEqual({ "x-application": "opencode" })
-    expect(gemini.route.defaults.http?.body).toEqual({ safetySettings: [] })
-    expect(gemini.route.defaults.limits).toEqual({ context: 1_000_000, output: 65_536 })
-    expect(
-      GoogleVertex.model("gemini-3.5-flash", {
-        accessToken: "fixture",
-        location: "eu",
-        project: "vertex-project",
-      }).route.endpoint.baseURL,
-    ).toBe("https://aiplatform.eu.rep.googleapis.com/v1beta1/projects/vertex-project/locations/eu/publishers/google")
-    expect(messages.route.id).toBe("google-vertex-messages")
-    expect(messages.route.protocol).toBe("anthropic-messages")
-    expect(messages.route.endpoint.baseURL).toBe(
-      "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/publishers/anthropic/models",
-    )
-    expect(chat.route.id).toBe("google-vertex-chat")
-    expect(chat.route.protocol).toBe("openai-chat")
-    expect(chat.route.endpoint).toMatchObject({
-      baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
-      path: "/chat/completions",
-    })
-    expect(responses.route.id).toBe("google-vertex-responses")
-    expect(responses.route.protocol).toBe("openai-responses")
-    expect(responses.route.endpoint).toMatchObject({
-      baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
-      path: "/responses",
-    })
-    expect(responses.route.defaults.providerOptions).toEqual({ openai: { store: false } })
-  })
-
-  test("rejects conflicting Vertex auth settings at runtime", async () => {
-    const GoogleVertex = await import("@opencode-ai/ai/providers/google-vertex")
-    const GoogleVertexChat = await import("@opencode-ai/ai/providers/google-vertex/chat")
-    const GoogleVertexMessages = await import("@opencode-ai/ai/providers/google-vertex/messages")
-    const GoogleVertexResponses = await import("@opencode-ai/ai/providers/google-vertex/responses")
-    const Providers = await import("@opencode-ai/ai/providers")
-    expect(() =>
-      Reflect.apply(GoogleVertex.model, undefined, [
-        "gemini-3.5-flash",
-        { accessToken: "token", apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex apiKey cannot be combined with accessToken or auth")
-    const configured = Reflect.apply(GoogleVertex.configure, undefined, [
-      { accessToken: "token", auth: {}, project: "vertex-project" },
-    ])
-    expect(() => configured.model("gemini-3.5-flash")).toThrow("Google Vertex accessToken cannot be combined with auth")
-    expect(() =>
-      Reflect.apply(GoogleVertexMessages.model, undefined, [
-        "claude-sonnet-4-6",
-        { apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex Messages does not support API keys")
-    expect(() =>
-      Reflect.apply(Providers.GoogleVertexMessages.configure, undefined, [
-        { apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex Messages does not support API keys")
-    expect(() =>
-      Reflect.apply(GoogleVertexChat.model, undefined, [
-        "deepseek-ai/deepseek-v3.2-maas",
-        { apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex Chat does not support API keys")
-    expect(() =>
-      Reflect.apply(Providers.GoogleVertexChat.configure, undefined, [
-        { apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex Chat does not support API keys")
-    expect(() =>
-      Reflect.apply(GoogleVertexResponses.model, undefined, [
-        "xai/grok-4.20-reasoning",
-        { apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex Responses does not support API keys")
-    expect(() =>
-      Reflect.apply(Providers.GoogleVertexResponses.configure, undefined, [
-        { apiKey: "fixture", project: "vertex-project" },
-      ]),
-    ).toThrow("Google Vertex Responses does not support API keys")
-  })
-})

packages/ai/test/provider/google-images.recorded.test.ts

@@ -1,56 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { Image, ImageInput } from "../../src"
-import { Google } from "../../src/providers"
-import { dimensions } from "../lib/image"
-import { recordedTests } from "../recorded-test"
-
-const model = Google.configure({
-  apiKey: process.env.GOOGLE_GENERATIVE_AI_API_KEY ?? "fixture",
-}).image("gemini-3.1-flash-image")
-
-const recorded = recordedTests({
-  prefix: "google-images",
-  provider: "google",
-  protocol: "google-images",
-  requires: ["GOOGLE_GENERATIVE_AI_API_KEY"],
-})
-
-describe("Google Images recorded", () => {
-  recorded.effect("generates an image", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model,
-        prompt: "A simple flat blue circle centered on a plain white background.",
-        options: { aspectRatio: "1:1" },
-      })
-
-      expect(response.images).toHaveLength(1)
-      expect(response.image?.mediaType).toMatch(/^image\//)
-      expect(response.image?.data).toBeInstanceOf(Uint8Array)
-      expect(response.image?.data.length).toBeGreaterThan(0)
-    }),
-  )
-
-  recorded.effect("edits an image", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model,
-        prompt:
-          "Transform this minimal source into a bright orange sun icon with eight rounded rays on a pale blue background.",
-        images: [
-          ImageInput.bytes(
-            yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
-            "image/jpeg",
-          ),
-        ],
-        options: { aspectRatio: "1:1" },
-      })
-
-      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 })
-    }),
-  )
-})

packages/ai/test/provider/google-vertex.test.ts

@@ -1,246 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { LLM } from "../../src"
-import { GoogleVertex, GoogleVertexChat, GoogleVertexMessages, GoogleVertexResponses } from "../../src/providers"
-import { LLMClient } from "../../src/route"
-import { it } from "../lib/effect"
-import { dynamicResponse } from "../lib/http"
-import { deltaChunk, finishChunk } from "../lib/openai-chunks"
-import { sseEvents } from "../lib/sse"
-
-describe("Google Vertex providers", () => {
-  it.effect("sends Gemini requests to the global Vertex endpoint", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: GoogleVertex.configure({
-            accessToken: "vertex-token",
-            location: "global",
-            project: "vertex-project",
-          }).model("gemini-3.5-flash"),
-          prompt: "Say hello.",
-        }),
-      ).pipe(
-        Effect.provide(
-          dynamicResponse((input) =>
-            Effect.gen(function* () {
-              const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-              expect(request.url).toBe(
-                "https://aiplatform.googleapis.com/v1beta1/projects/vertex-project/locations/global/publishers/google/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
-              )
-              expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
-              expect(yield* Effect.promise(() => request.json())).toMatchObject({
-                contents: [{ role: "user", parts: [{ text: "Say hello." }] }],
-              })
-              return input.respond(
-                sseEvents({
-                  candidates: [
-                    {
-                      content: { role: "model", parts: [{ text: "Hello." }] },
-                      finishReason: "STOP",
-                    },
-                  ],
-                }),
-                { headers: { "content-type": "text/event-stream" } },
-              )
-            }),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello.")
-    }),
-  )
-
-  it.effect("projects Anthropic Messages onto the Vertex raw-predict API", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: GoogleVertexMessages.configure({
-            accessToken: "vertex-token",
-            location: "eu",
-            project: "vertex-project",
-          }).model("claude-sonnet-4-6"),
-          prompt: "Say hello.",
-        }),
-      ).pipe(
-        Effect.provide(
-          dynamicResponse((input) =>
-            Effect.gen(function* () {
-              const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-              expect(request.url).toBe(
-                "https://aiplatform.eu.rep.googleapis.com/v1/projects/vertex-project/locations/eu/publishers/anthropic/models/claude-sonnet-4-6:streamRawPredict",
-              )
-              expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
-              expect(request.headers.get("anthropic-version")).toBeNull()
-              const body = yield* Effect.promise(() => request.json())
-              expect(body).toMatchObject({
-                anthropic_version: "vertex-2023-10-16",
-                messages: [{ role: "user", content: [{ type: "text", text: "Say hello." }] }],
-                stream: true,
-              })
-              expect(body).not.toHaveProperty("model")
-              return input.respond(
-                sseEvents(
-                  { type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
-                  { type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "Hello." } },
-                  { type: "content_block_stop", index: 0 },
-                  { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 2 } },
-                  { type: "message_stop" },
-                ),
-                { headers: { "content-type": "text/event-stream" } },
-              )
-            }),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello.")
-    }),
-  )
-
-  it.effect("sends MaaS requests through Vertex Chat Completions", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: GoogleVertexChat.configure({
-            accessToken: "vertex-token",
-            location: "global",
-            project: "vertex-project",
-          }).model("deepseek-ai/deepseek-v3.2-maas"),
-          prompt: "Say hello.",
-        }),
-      ).pipe(
-        Effect.provide(
-          dynamicResponse((input) =>
-            Effect.gen(function* () {
-              const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-              expect(request.url).toBe(
-                "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi/chat/completions",
-              )
-              expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
-              expect(yield* Effect.promise(() => request.json())).toMatchObject({
-                model: "deepseek-ai/deepseek-v3.2-maas",
-                messages: [{ role: "user", content: "Say hello." }],
-                stream: true,
-                stream_options: { include_usage: true },
-              })
-              return input.respond(sseEvents(deltaChunk({ content: "Hello." }), finishChunk("stop")), {
-                headers: { "content-type": "text/event-stream" },
-              })
-            }),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello.")
-    }),
-  )
-
-  it.effect("sends Grok requests through Vertex Responses", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: GoogleVertexResponses.configure({
-            accessToken: "vertex-token",
-            location: "global",
-            project: "vertex-project",
-          }).model("xai/grok-4.20-reasoning"),
-          prompt: "Say hello.",
-        }),
-      ).pipe(
-        Effect.provide(
-          dynamicResponse((input) =>
-            Effect.gen(function* () {
-              const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-              expect(request.url).toBe(
-                "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi/responses",
-              )
-              expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
-              expect(yield* Effect.promise(() => request.json())).toMatchObject({
-                model: "xai/grok-4.20-reasoning",
-                input: [{ role: "user", content: [{ type: "input_text", text: "Say hello." }] }],
-                store: false,
-                stream: true,
-              })
-              return input.respond(
-                sseEvents(
-                  { type: "response.output_text.delta", item_id: "msg_1", delta: "Hello." },
-                  { type: "response.completed", response: { id: "resp_1" } },
-                ),
-                { headers: { "content-type": "text/event-stream" } },
-              )
-            }),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello.")
-    }),
-  )
-
-  it.effect("protects the Vertex Messages API version from body overlays", () =>
-    Effect.gen(function* () {
-      const error = yield* LLMClient.prepare(
-        LLM.request({
-          model: GoogleVertexMessages.configure({
-            accessToken: "vertex-token",
-            http: { body: { anthropic_version: "wrong" } },
-            project: "vertex-project",
-          }).model("claude-sonnet-4-6"),
-          prompt: "Say hello.",
-        }),
-      ).pipe(Effect.flip)
-
-      expect(error.message).toContain("http.body cannot overlay protocol-owned field(s): anthropic_version")
-    }),
-  )
-
-  it.effect("routes tuned Gemini models through their deployed endpoint", () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: GoogleVertex.configure({
-            accessToken: "vertex-token",
-            location: "us-central1",
-            project: "vertex-project",
-          }).model("endpoints/1234567890"),
-          prompt: "Say hello.",
-        }),
-      ).pipe(
-        Effect.provide(
-          dynamicResponse((input) =>
-            Effect.gen(function* () {
-              const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-              expect(request.url).toBe(
-                "https://us-central1-aiplatform.googleapis.com/v1beta1/projects/vertex-project/locations/us-central1/endpoints/1234567890:streamGenerateContent?alt=sse",
-              )
-              return input.respond(
-                sseEvents({
-                  candidates: [
-                    {
-                      content: { role: "model", parts: [{ text: "Hello." }] },
-                      finishReason: "STOP",
-                    },
-                  ],
-                }),
-                { headers: { "content-type": "text/event-stream" } },
-              )
-            }),
-          ),
-        ),
-      )
-
-      expect(response.text).toBe("Hello.")
-    }),
-  )
-
-  it.effect("rejects tuned Gemini models in express mode", () =>
-    Effect.sync(() => {
-      expect(() => GoogleVertex.configure({ apiKey: "fixture" }).model("endpoints/1234567890")).toThrow(
-        "Google Vertex tuned models do not support Express Mode API keys",
-      )
-    }),
-  )
-})

packages/ai/test/provider/openai-chat-reasoning.recorded.test.ts

@@ -1,148 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { LLM, LLMEvent, LLMResponse, Model } from "../../src"
-import { OpenAIChat } from "../../src/protocols/openai-chat"
-import * as OpenAICompatible from "../../src/providers/openai-compatible"
-import * as OpenRouter from "../../src/providers/openrouter"
-import { LLMClient } from "../../src/route"
-import { recordedTests } from "../recorded-test"
-import { expectWeatherToolLoop, goldenWeatherToolLoopRequest, runWeatherToolLoop } from "../recorded-scenarios"
-
-const cases = [
-  {
-    name: "OpenRouter",
-    model: Model.update(
-      OpenRouter.configure({
-        apiKey: process.env.OPENROUTER_API_KEY ?? "fixture",
-        providerOptions: { openrouter: { reasoning: { max_tokens: 1024 } } },
-      }).model("anthropic/claude-sonnet-4.6"),
-      { compatibility: { reasoningField: "reasoning" } },
-    ),
-    requires: ["OPENROUTER_API_KEY"],
-    cassette: "openrouter-reasoning",
-    structured: true,
-  },
-  {
-    name: "Vercel AI Gateway",
-    model: Model.update(
-      OpenAICompatible.configure({
-        provider: "vercel-ai-gateway",
-        baseURL: "https://ai-gateway.vercel.sh/v1",
-        apiKey: process.env.AI_GATEWAY_API_KEY ?? "fixture",
-        http: { body: { reasoning: { enabled: true, max_tokens: 1024 } } },
-      }).model("anthropic/claude-sonnet-4.6"),
-      { compatibility: { reasoningField: "reasoning" } },
-    ),
-    requires: ["AI_GATEWAY_API_KEY"],
-    cassette: "vercel-ai-gateway-reasoning",
-    structured: true,
-  },
-] as const
-
-for (const item of cases) {
-  const recorded = recordedTests({
-    prefix: "openai-compatible-chat",
-    provider: item.model.provider,
-    protocol: "openai-chat",
-    requires: item.requires,
-    tags: ["reasoning"],
-    metadata: { model: item.model.id },
-  })
-
-  describe(`${item.name} reasoning recorded`, () => {
-    recorded.effect.with(
-      "streams scalar reasoning",
-      { cassette: item.cassette },
-      () =>
-        Effect.gen(function* () {
-          const response = yield* LLMClient.generate(
-            LLM.request({
-              model: item.model,
-              system: "Think through the arithmetic, then reply with only the final integer.",
-              prompt: "What is 173 multiplied by 219?",
-              generation: { maxTokens: 1536, temperature: 0 },
-            }),
-          )
-
-          expect(response.text.replaceAll(",", "").trim()).toBe("37887")
-          expect(response.reasoning.length).toBeGreaterThan(0)
-          expect(response.events.some(LLMEvent.is.reasoningDelta)).toBe(true)
-          const metadata = response.message.content.find((part) => part.type === "reasoning")?.providerMetadata
-          expect(metadata?.openai?.reasoningField).toBe(item.structured ? "reasoning" : "reasoning_content")
-          expect(Array.isArray(metadata?.openai?.reasoningDetails)).toBe(item.structured)
-          if (!item.structured) return
-          const details = metadata?.openai?.reasoningDetails
-          if (!Array.isArray(details)) return
-          expect(
-            details.some(
-              (detail) =>
-                typeof detail === "object" &&
-                detail !== null &&
-                "signature" in detail &&
-                typeof detail.signature === "string" &&
-                detail.signature.length > 0,
-            ),
-          ).toBe(true)
-
-          const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
-            LLM.request({ model: item.model, messages: [response.message] }),
-          )
-          expect(replay.body.messages).toMatchObject([
-            { role: "assistant", content: response.text, reasoning: response.reasoning },
-          ])
-          const replayDetails =
-            replay.body.messages[0]?.role === "assistant" ? replay.body.messages[0].reasoning_details : undefined
-          expect(Array.isArray(replayDetails)).toBe(true)
-          if (!Array.isArray(replayDetails)) return
-          expect(replayDetails).toEqual(details)
-          expect(replayDetails).toHaveLength(1)
-          expect(replayDetails[0]).toMatchObject({
-            type: "reasoning.text",
-            text: response.reasoning,
-            signature: expect.any(String),
-          })
-        }),
-      30_000,
-    )
-
-    recorded.effect.with(
-      "continues signed reasoning through a tool loop",
-      { cassette: `${item.cassette}-tool-loop`, tags: ["continuation", "tool", "tool-loop"] },
-      () =>
-        Effect.gen(function* () {
-          const events = yield* runWeatherToolLoop(
-            goldenWeatherToolLoopRequest({
-              id: `${item.cassette}-tool-loop`,
-              model: item.model,
-              maxTokens: 1536,
-              temperature: false,
-            }),
-          )
-
-          expectWeatherToolLoop(events)
-          expect(
-            LLMResponse.text({
-              events: events.slice(events.findIndex(LLMEvent.is.stepFinish) + 1),
-            }).trim(),
-          ).toMatch(/^Paris is sunny\.?$/)
-          const details = events
-            .filter(LLMEvent.is.reasoningEnd)
-            .map((event) => event.providerMetadata?.openai?.reasoningDetails)
-            .find(Array.isArray)
-          expect(Array.isArray(details)).toBe(item.structured)
-          if (!item.structured || !Array.isArray(details)) return
-          expect(
-            details.some(
-              (detail) =>
-                typeof detail === "object" &&
-                detail !== null &&
-                "signature" in detail &&
-                typeof detail.signature === "string" &&
-                detail.signature.length > 0,
-            ),
-          ).toBe(true)
-        }),
-      60_000,
-    )
-  })
-}

packages/ai/test/provider/openai-images.recorded.test.ts

@@ -1,62 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { Image, ImageInput } from "../../src"
-import { OpenAI } from "../../src/providers"
-import { dimensions } from "../lib/image"
-import { recordedTests } from "../recorded-test"
-
-const model = OpenAI.configure({
-  apiKey: process.env.OPENAI_API_KEY ?? "fixture",
-}).image("gpt-image-1-mini")
-
-const recorded = recordedTests({
-  prefix: "openai-images",
-  provider: "openai",
-  protocol: "openai-images",
-  requires: ["OPENAI_API_KEY"],
-})
-
-describe("OpenAI Images recorded", () => {
-  recorded.effect("generates an image", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model,
-        prompt: "A simple flat black circle centered on a plain white background.",
-        options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
-      })
-
-      expect(response.images).toHaveLength(1)
-      expect(response.image?.mediaType).toBe("image/jpeg")
-      expect(response.image?.data).toBeInstanceOf(Uint8Array)
-      expect(response.image?.data.length).toBeGreaterThan(0)
-    }),
-  )
-
-  recorded.effect.with(
-    "edits an image",
-    {
-      options: {
-        match: (incoming, recorded) => incoming.method === recorded.method && incoming.url === recorded.url,
-      },
-    },
-    () =>
-      Effect.gen(function* () {
-        const response = yield* Image.generate({
-          model,
-          prompt: "Keep the simple shape and change it from black to bright green.",
-          images: [
-            ImageInput.bytes(
-              yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
-              "image/jpeg",
-            ),
-          ],
-          options: { quality: "low", outputFormat: "jpeg", outputCompression: 10, size: "1024x1024" },
-        })
-
-        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 })
-      }),
-  )
-})

packages/ai/test/provider/openai-responses-images.recorded.test.ts

@@ -1,66 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { LLM, LLMEvent, Message } from "../../src"
-import { OpenAI } from "../../src/providers"
-import { recordedTests } from "../recorded-test"
-
-const openai = OpenAI.configure({
-  apiKey: process.env.OPENAI_API_KEY ?? "fixture",
-})
-
-const recorded = recordedTests({
-  prefix: "openai-responses-images",
-  provider: "openai",
-  protocol: "openai-responses",
-  requires: ["OPENAI_API_KEY"],
-})
-
-describe("OpenAI Responses image generation recorded", () => {
-  recorded.effect("generates and edits an image with the hosted tool", () =>
-    Effect.gen(function* () {
-      const initial = Message.user("Generate a simple flat black triangle centered on a plain white background.")
-      const tools = [
-        OpenAI.imageGeneration({
-          action: "auto",
-          quality: "low",
-          size: "1024x1024",
-          outputFormat: "jpeg",
-          outputCompression: 10,
-          partialImages: 0,
-        }),
-      ]
-      const response = yield* LLM.generate(
-        LLM.request({
-          model: openai.responses("gpt-5-mini"),
-          messages: [initial],
-          tools,
-          toolChoice: "image_generation",
-        }),
-      )
-
-      const result = response.events.find(LLMEvent.is.toolResult)
-      expect(result).toBeDefined()
-      expect(result?.providerExecuted).toBe(true)
-      expect(result?.result.type).toBe("content")
-      if (result?.result.type !== "content") return
-      expect(result.result.value).toHaveLength(1)
-      expect(result.result.value[0]?.type).toBe("file")
-      if (result.result.value[0]?.type !== "file") return
-      expect(result.result.value[0].mime).toBe("image/jpeg")
-      expect(result.result.value[0].uri.startsWith("data:image/jpeg;base64,")).toBe(true)
-
-      const edited = yield* LLM.generate(
-        LLM.request({
-          model: openai.responses("gpt-5-mini"),
-          messages: [initial, response.message, Message.user("Now make the triangle blue.")],
-          tools,
-          toolChoice: "image_generation",
-        }),
-      )
-      const editedResult = edited.events.find(LLMEvent.is.toolResult)
-      expect(editedResult?.result.type).toBe("content")
-      if (editedResult?.result.type !== "content") return
-      expect(editedResult.result.value[0]?.type).toBe("file")
-    }),
-  )
-})

packages/ai/test/provider/openrouter.test.ts

@@ -1,192 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { LLM, Message } from "../../src"
-import { LLMClient } from "../../src/route"
-import * as OpenRouter from "../../src/providers/openrouter"
-import { it } from "../lib/effect"
-import { fixedResponse } from "../lib/http"
-import { sseEvents } from "../lib/sse"
-
-describe("OpenRouter", () => {
-  it.effect("prepares OpenRouter models through the OpenAI-compatible Chat route", () =>
-    Effect.gen(function* () {
-      const model = OpenRouter.configure({ apiKey: "test-key" }).model("openai/gpt-4o-mini")
-
-      expect(model).toMatchObject({
-        id: "openai/gpt-4o-mini",
-        provider: "openrouter",
-        route: { id: "openrouter" },
-      })
-      expect(model.route.endpoint.baseURL).toBe("https://openrouter.ai/api/v1")
-
-      const prepared = yield* LLMClient.prepare(LLM.request({ model, prompt: "Say hello." }))
-
-      expect(prepared.route).toBe("openrouter")
-      expect(prepared.body).toMatchObject({
-        model: "openai/gpt-4o-mini",
-        messages: [{ role: "user", content: "Say hello." }],
-        stream: true,
-      })
-    }),
-  )
-
-  it.effect("applies OpenRouter payload options from the model helper", () =>
-    Effect.gen(function* () {
-      const prepared = yield* LLMClient.prepare(
-        LLM.request({
-          model: OpenRouter.configure({
-            apiKey: "test-key",
-            providerOptions: {
-              openrouter: {
-                usage: true,
-                reasoning: { effort: "high" },
-                promptCacheKey: "session_123",
-              },
-            },
-          }).model("anthropic/claude-3.7-sonnet:thinking"),
-          prompt: "Think briefly.",
-        }),
-      )
-
-      expect(prepared.body).toMatchObject({
-        usage: { include: true },
-        reasoning: { effort: "high" },
-        prompt_cache_key: "session_123",
-      })
-    }),
-  )
-
-  it.effect("preserves the upstream provider finish reason", () =>
-    Effect.gen(function* () {
-      const model = OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6")
-      const response = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents({
-              choices: [{ delta: { content: "Hello" }, finish_reason: "stop", native_finish_reason: "end_turn" }],
-            }),
-          ),
-        ),
-      )
-
-      expect(response.finishReason).toEqual({ normalized: "stop", raw: "end_turn" })
-    }),
-  )
-
-  it.effect("fails on a mid-stream provider error", () =>
-    Effect.gen(function* () {
-      const model = OpenRouter.configure({ apiKey: "test-key" }).model("openai/gpt-4o-mini")
-      const error = yield* LLMClient.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
-        Effect.provide(
-          fixedResponse(
-            sseEvents({
-              error: { code: 502, message: "Provider disconnected" },
-            }),
-          ),
-        ),
-        Effect.flip,
-      )
-
-      expect(error.reason).toMatchObject({ _tag: "ProviderInternal" })
-      expect(error.message).toContain("Provider disconnected")
-    }),
-  )
-
-  it.effect("preserves manually supplied reasoning details", () =>
-    Effect.gen(function* () {
-      const details = [
-        { type: "reasoning.text", text: "Think", format: "anthropic-claude-v1", index: 0 },
-        { type: "reasoning.text", text: "ing", format: "anthropic-claude-v1", index: 0 },
-        { type: "reasoning.text", signature: "signed", format: "anthropic-claude-v1", index: 0 },
-        { type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 1 },
-      ]
-      const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
-        LLM.request({
-          model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
-          messages: [
-            Message.assistant([
-              {
-                type: "reasoning",
-                text: "Thinking",
-                providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: details } },
-              },
-            ]),
-          ],
-        }),
-      )
-
-      expect(prepared.body.messages).toEqual([
-        {
-          role: "assistant",
-          content: null,
-          reasoning: "Thinking",
-          reasoning_details: 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" },
-      ]
-      const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
-        LLM.request({
-          model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
-          messages: [
-            Message.assistant({
-              type: "reasoning",
-              text: "Thinking",
-              providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: details } },
-            }),
-          ],
-        }),
-      )
-
-      expect(prepared.body.messages).toEqual([
-        { role: "assistant", content: null, reasoning: "Thinking", reasoning_details: details },
-      ])
-    }),
-  )
-
-  it.effect("does not merge distinct adjacent reasoning text blocks", () =>
-    Effect.gen(function* () {
-      const details = [
-        { type: "reasoning.text", id: "first", index: 0, text: "A", opaque: "first" },
-        { type: "reasoning.text", id: "second", index: 1, text: "B", opaque: "second" },
-      ]
-      const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
-        LLM.request({
-          model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
-          messages: [
-            Message.assistant({
-              type: "reasoning",
-              text: "AB",
-              providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: details } },
-            }),
-          ],
-        }),
-      )
-
-      expect(prepared.body.messages).toEqual([
-        { role: "assistant", content: null, reasoning: "AB", reasoning_details: details },
-      ])
-    }),
-  )
-
-  it.effect("omits scalar reasoning without continuation details", () =>
-    Effect.gen(function* () {
-      const prepared = yield* LLMClient.prepare<OpenRouter.OpenRouterBody>(
-        LLM.request({
-          model: OpenRouter.configure({ apiKey: "test-key" }).model("anthropic/claude-sonnet-4.6"),
-          messages: [Message.assistant({ type: "reasoning", text: "Thinking" })],
-        }),
-      )
-
-      expect(prepared.body.messages).toEqual([{ role: "assistant", content: null }])
-    }),
-  )
-})

packages/ai/test/provider/pdf.recorded.test.ts

@@ -1,207 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Schema, Stream } from "effect"
-import { LLM, LLMResponse, Message, ToolDefinition, type Model } from "../../src"
-import { AmazonBedrock, Anthropic, Google, OpenAI, XAI } from "../../src/providers"
-import { LLMClient } from "../../src/route"
-import { Tool } from "../../src/tool"
-import { runTools } from "../lib/tool-runtime"
-import { recordedTests } from "../recorded-test"
-
-const CODE = "ORCHID-7391"
-const PDF =
-  "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"
-
-const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY ?? "fixture" })
-const anthropic = Anthropic.configure({ apiKey: process.env.ANTHROPIC_API_KEY ?? "fixture" })
-const google = Google.configure({ apiKey: process.env.GOOGLE_API_KEY ?? "fixture" })
-const xai = XAI.configure({ apiKey: process.env.XAI_API_KEY ?? "fixture" })
-const bedrock = AmazonBedrock.configure({
-  apiKey: process.env.AWS_BEDROCK_API_KEY ?? "fixture",
-  region: process.env.AWS_REGION ?? "us-east-1",
-})
-
-const targets: ReadonlyArray<{
-  readonly id: string
-  readonly name: string
-  readonly provider: string
-  readonly protocol: string
-  readonly requires: string
-  readonly filename: string
-  readonly maxTokens: number
-  readonly model: Model
-}> = [
-  {
-    id: "openai",
-    name: "OpenAI Responses gpt-4o-mini",
-    provider: "openai",
-    protocol: "openai-responses",
-    requires: "OPENAI_API_KEY",
-    filename: "verification.pdf",
-    maxTokens: 40,
-    model: openai.responses("gpt-4o-mini"),
-  },
-  {
-    id: "anthropic",
-    name: "Anthropic Haiku 4.5",
-    provider: "anthropic",
-    protocol: "anthropic-messages",
-    requires: "ANTHROPIC_API_KEY",
-    filename: "verification.pdf",
-    maxTokens: 40,
-    model: anthropic.model("claude-haiku-4-5-20251001"),
-  },
-  {
-    id: "gemini",
-    name: "Gemini 3.5 Flash",
-    provider: "google",
-    protocol: "gemini",
-    requires: "GOOGLE_API_KEY",
-    filename: "verification.pdf",
-    maxTokens: 256,
-    model: google.model("gemini-3.5-flash"),
-  },
-  {
-    id: "xai",
-    name: "xAI Grok 4.5",
-    provider: "xai",
-    protocol: "openai-responses",
-    requires: "XAI_API_KEY",
-    filename: "verification.pdf",
-    maxTokens: 40,
-    model: xai.responses("grok-4.5"),
-  },
-  {
-    id: "bedrock",
-    name: "Bedrock Claude Haiku 4.5",
-    provider: "amazon-bedrock",
-    protocol: "bedrock-converse",
-    requires: "AWS_BEDROCK_API_KEY",
-    filename: "verification",
-    maxTokens: 40,
-    model: bedrock.model("us.anthropic.claude-haiku-4-5-20251001-v1:0"),
-  },
-]
-
-const recorded = recordedTests({ prefix: "pdf", tags: ["pdf"] })
-const prompt = "Return only the verification code from the PDF."
-const readPdf = ToolDefinition.make({
-  name: "read_pdf",
-  description: "Read the attached PDF.",
-  inputSchema: { type: "object", properties: {}, additionalProperties: false },
-})
-const readPdfRuntime = Tool.make({
-  description: readPdf.description,
-  parameters: Schema.Struct({ path: Schema.String }),
-  success: Schema.String,
-  execute: () => Effect.succeed("PDF read successfully"),
-  toModelOutput: () => [
-    { type: "text", text: "PDF read successfully" },
-    {
-      type: "file",
-      uri: `data:application/pdf;base64,${PDF}`,
-      mime: "application/pdf",
-      name: "verification.pdf",
-    },
-  ],
-})
-
-const expectCode = (response: LLMResponse) => {
-  expect(response.finishReason.normalized).toBe("stop")
-  expect(response.text.toUpperCase()).toContain(CODE)
-}
-
-describe("PDF recorded", () => {
-  for (const target of targets) {
-    recorded.effect.with(
-      `reads a user PDF with ${target.name}`,
-      {
-        id: `${target.id}-user-input`,
-        provider: target.provider,
-        protocol: target.protocol,
-        requires: [target.requires],
-        tags: ["user-input"],
-      },
-      Effect.gen(function* () {
-        expectCode(
-          yield* LLMClient.generate(
-            LLM.request({
-              id: `recorded_pdf_${target.id}_user_input`,
-              model: target.model,
-              cache: "none",
-              generation: { maxTokens: target.maxTokens, temperature: 0 },
-              messages: [
-                Message.user([
-                  { type: "media", mediaType: "application/pdf", data: PDF, filename: target.filename },
-                  { type: "text", text: prompt },
-                ]),
-              ],
-            }),
-          ),
-        )
-      }),
-    )
-
-    recorded.effect.with(
-      `reads a PDF tool result with ${target.name}`,
-      {
-        id: `${target.id}-tool-result`,
-        provider: target.provider,
-        protocol: target.protocol,
-        requires: [target.requires],
-        tags: ["tool", "tool-result"],
-      },
-      Effect.gen(function* () {
-        if (target.id === "gemini") {
-          const events = Array.from(
-            yield* runTools({
-              request: LLM.request({
-                id: "recorded_pdf_gemini_tool_result",
-                model: target.model,
-                system:
-                  "Call read_pdf exactly once with path verification.pdf, then reply only with the verification code from its PDF.",
-                prompt: "Use read_pdf with path verification.pdf and return the verification code.",
-                cache: "none",
-                generation: { maxTokens: target.maxTokens, temperature: 0 },
-              }),
-              tools: { read_pdf: readPdfRuntime },
-            }).pipe(Stream.runCollect),
-          )
-          expect(events.at(-1)).toMatchObject({ type: "finish", reason: { normalized: "stop" } })
-          expect(LLMResponse.text({ events }).toUpperCase()).toContain(CODE)
-          return
-        }
-
-        expectCode(
-          yield* LLMClient.generate(
-            LLM.request({
-              id: `recorded_pdf_${target.id}_tool_result`,
-              model: target.model,
-              system: "Read the PDF returned by the tool and follow the user's response format exactly.",
-              cache: "none",
-              generation: { maxTokens: target.maxTokens, temperature: 0 },
-              messages: [
-                Message.user(prompt),
-                Message.assistant([{ type: "tool-call", id: "call_pdf_1", name: readPdf.name, input: {} }]),
-                Message.tool({
-                  id: "call_pdf_1",
-                  name: readPdf.name,
-                  resultType: "content",
-                  result: [
-                    { type: "text", text: "PDF read successfully" },
-                    {
-                      type: "file",
-                      uri: `data:application/pdf;base64,${PDF}`,
-                      mime: "application/pdf",
-                      name: target.filename,
-                    },
-                  ],
-                }),
-              ],
-              tools: [readPdf],
-            }),
-          ),
-        )
-      }),
-    )
-  }
-})

packages/ai/test/provider/xai-images.recorded.test.ts

@@ -1,55 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { Image, ImageInput } from "../../src"
-import { XAI } from "../../src/providers"
-import { dimensions } from "../lib/image"
-import { recordedTests } from "../recorded-test"
-
-const model = XAI.configure({
-  apiKey: process.env.XAI_API_KEY ?? "fixture",
-}).image("grok-imagine-image")
-
-const recorded = recordedTests({
-  prefix: "xai-images",
-  provider: "xai",
-  protocol: "xai-images",
-  requires: ["XAI_API_KEY"],
-})
-
-describe("xAI Images recorded", () => {
-  recorded.effect("generates an image", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model,
-        prompt: "A simple flat black diamond centered on a plain white background.",
-        options: { aspectRatio: "1:1", resolution: "1k", responseFormat: "b64_json" },
-      })
-
-      expect(response.images).toHaveLength(1)
-      expect(response.image?.mediaType.startsWith("image/")).toBe(true)
-      expect(response.image?.data).toBeInstanceOf(Uint8Array)
-      expect(response.image?.data.length).toBeGreaterThan(0)
-    }),
-  )
-
-  recorded.effect("edits an image", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model,
-        prompt: "Keep the simple shape and change it from black to bright purple.",
-        images: [
-          ImageInput.bytes(
-            yield* Effect.promise(() => Bun.file("test/fixtures/images/edit-source.jpg").bytes()),
-            "image/jpeg",
-          ),
-        ],
-        options: { aspectRatio: "1:1", resolution: "1k", responseFormat: "b64_json" },
-      })
-
-      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 })
-    }),
-  )
-})

packages/ai/test/provider/xai-images.test.ts

@@ -1,109 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Layer } from "effect"
-import { Headers, HttpClientRequest } from "effect/unstable/http"
-import { Image, ImageClient } from "../../src"
-import { XAI } from "../../src/providers"
-import { Auth } from "../../src/route"
-import { it } from "../lib/effect"
-import { dynamicResponse } from "../lib/http"
-
-describe("xAI Images", () => {
-  it.effect("generates through the OpenAI-compatible Images API", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model: XAI.configure({
-          apiKey: "test",
-          baseURL: "https://api.xai.test/v1",
-          http: { body: { configured: true }, headers: { "x-default": "yes" } },
-        }).image("grok-imagine-image"),
-        prompt: "A robot tending a rooftop garden",
-        options: {
-          n: 2,
-          aspectRatio: "16:9",
-          aspect_ratio: "4:3",
-          resolution: "1k",
-          responseFormat: "url",
-          response_format: "b64_json",
-          future_option: true,
-        },
-        http: {
-          body: { resolution: "2k", future_option: "http" },
-          headers: { "x-request": "yes" },
-          query: { trace: "1" },
-        },
-      })
-
-      expect(response.images).toHaveLength(2)
-      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.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.url).toBe("https://api.xai.test/v1/images/generations?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({
-                  model: "grok-imagine-image",
-                  prompt: "A robot tending a rooftop garden",
-                  n: 2,
-                  aspect_ratio: "4:3",
-                  resolution: "2k",
-                  response_format: "b64_json",
-                  future_option: "http",
-                  configured: true,
-                })
-                return input.respond(
-                  JSON.stringify({
-                    data: [
-                      { b64_json: "AQID", url: null, mime_type: "image/jpeg" },
-                      { b64_json: null, url: "https://api.xai.test/image.jpg", mime_type: null },
-                    ],
-                    usage: { num_images: 2 },
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                )
-              }),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("supports request-level custom auth", () =>
-    Image.generate({
-      model: XAI.configure({
-        baseURL: "https://api.xai.test/v1",
-        auth: Auth.custom((input) =>
-          Effect.succeed(Headers.set(input.headers, "x-custom-auth", new URL(input.url).hostname)),
-        ),
-      }).image("grok-imagine-image"),
-      prompt: "A robot tending a rooftop garden",
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.headers.get("x-custom-auth")).toBe("api.xai.test")
-                return input.respond(JSON.stringify({ data: [{ b64_json: "AQID", mime_type: "image/png" }] }), {
-                  headers: { "content-type": "application/json" },
-                })
-              }),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-})

packages/ai/test/provider/zai-images.recorded.test.ts

@@ -1,32 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect } from "effect"
-import { Image } from "../../src"
-import { ZAI } from "../../src/providers"
-import { recordedTests } from "../recorded-test"
-
-const model = ZAI.configure({ apiKey: process.env.ZAI_API_KEY ?? "fixture" }).image("cogview-4-250304")
-
-const recorded = recordedTests({
-  prefix: "zai-images",
-  provider: "zai",
-  protocol: "zai-images",
-  requires: ["ZAI_API_KEY"],
-})
-
-describe("Z.ai Images recorded", () => {
-  recorded.effect("generates an image", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model,
-        prompt: "A simple flat red circle centered on a plain white background.",
-        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?.data).toBeString()
-      expect(response.image?.data).toStartWith("https://")
-      expect(response.providerMetadata?.zai).toBeDefined()
-    }),
-  )
-})

packages/ai/test/provider/zai-images.test.ts

@@ -1,130 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Effect, Layer } from "effect"
-import { HttpClientRequest } from "effect/unstable/http"
-import { Image, ImageClient } from "../../src"
-import { ZAI } from "../../src/providers"
-import { it } from "../lib/effect"
-import { dynamicResponse, fixedResponse } from "../lib/http"
-
-describe("Z.ai Images", () => {
-  it.effect("generates through the Z.ai Images API", () =>
-    Effect.gen(function* () {
-      const response = yield* Image.generate({
-        model: ZAI.configure({
-          apiKey: "test",
-          baseURL: "https://api.z.ai.test/api/paas/v4",
-          headers: { "x-default": "yes" },
-          http: { body: { configured: true, quality: "configured" }, query: { trace: "default" } },
-        }).image("glm-image"),
-        prompt: "A red circle on a white background",
-        options: {
-          quality: "hd",
-          userID: "alias-user",
-          user_id: "raw-user",
-          future_option: true,
-        },
-        http: {
-          headers: { "x-request": "yes" },
-          query: { trace: "request" },
-          body: { quality: "final", user_id: "final-user" },
-        },
-      })
-
-      expect(response.images).toHaveLength(1)
-      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,
-          id: "generation-1",
-          requestID: "request-1",
-          contentFilter: [{ role: "future-role", level: 4.5 }],
-        },
-      })
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) =>
-              Effect.gen(function* () {
-                const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
-                expect(request.url).toBe("https://api.z.ai.test/api/paas/v4/images/generations?trace=request")
-                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({
-                  model: "glm-image",
-                  prompt: "A red circle on a white background",
-                  quality: "final",
-                  user_id: "final-user",
-                  future_option: true,
-                  configured: true,
-                })
-                return input.respond(
-                  JSON.stringify({
-                    created: 1_760_335_349,
-                    id: "generation-1",
-                    request_id: "request-1",
-                    data: [{ url: "https://cdn.z.ai/generated.png" }],
-                    content_filter: [{ role: "future-role", level: 4.5 }],
-                  }),
-                  { headers: { "content-type": "application/json" } },
-                )
-              }),
-            ),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("lets raw native options override aliases", () =>
-    Image.generate({
-      model: ZAI.configure({ apiKey: "test" }).image("model"),
-      prompt: "test",
-      options: { quality: "future-quality", userID: "x", user_id: "raw-user" },
-    }).pipe(
-      Effect.provide(
-        ImageClient.layer.pipe(
-          Layer.provide(
-            dynamicResponse((input) => {
-              expect(JSON.parse(input.text)).toMatchObject({ quality: "future-quality", user_id: "raw-user" })
-              return Effect.succeed(
-                input.respond(JSON.stringify({ data: [{ url: "https://example.test/image.jpg" }] }), {
-                  headers: { "content-type": "application/json" },
-                }),
-              )
-            }),
-          ),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("rejects invalid response structures", () =>
-    Effect.gen(function* () {
-      const model = ZAI.configure({ apiKey: "test" }).image("model")
-      const payloads = [
-        {},
-        { data: [] },
-        { data: [{ b64_json: "image" }] },
-        { data: [{ url: 1 }] },
-        { data: [{ url: "https://example.test/image.jpg" }], content_filter: [{ role: 1, level: "high" }] },
-      ]
-
-      yield* Effect.forEach(payloads, (payload) =>
-        Image.generate({ model, prompt: "test" }).pipe(
-          Effect.provide(
-            ImageClient.layer.pipe(
-              Layer.provide(
-                fixedResponse(JSON.stringify(payload), { headers: { "content-type": "application/json" } }),
-              ),
-            ),
-          ),
-          Effect.flip,
-          Effect.tap((error) => Effect.sync(() => expect(error.reason._tag).toBe("InvalidProviderOutput"))),
-        ),
-      )
-    }),
-  )
-})

packages/ai/tsconfig.build.json

@@ -1,8 +0,0 @@
-{
-  "$schema": "https://json.schemastore.org/tsconfig",
-  "extends": "./tsconfig.json",
-  "compilerOptions": {
-    "allowImportingTsExtensions": false,
-    "noEmit": false
-  }
-}

packages/ai/tsconfig.json

@@ -1,12 +0,0 @@
-{
-  "$schema": "https://json.schemastore.org/tsconfig.json",
-  "extends": "@tsconfig/bun/tsconfig.json",
-  "compilerOptions": {
-    "rootDir": "src",
-    "outDir": "dist",
-    "declaration": true,
-    "lib": ["ESNext", "DOM", "DOM.Iterable"],
-    "noUncheckedIndexedAccess": false
-  },
-  "include": ["src"]
-}

packages/ai/tsconfig.types.json

@@ -1,9 +0,0 @@
-{
-  "$schema": "https://json.schemastore.org/tsconfig",
-  "extends": "./tsconfig.json",
-  "compilerOptions": {
-    "noEmit": true,
-    "rootDir": "."
-  },
-  "include": ["test/**/*.types.ts"]
-}

packages/app/e2e/performance/timeline-stability/fixture.ts

@@ -97,7 +97,6 @@ export async function setupTimeline(
     locale?: string
     deviceScaleFactor?: number
     seedHistory?: boolean
-    protocol?: "v1" | "v2"
   } = {},
 ) {
   const sessions = input.sessions ?? [session()]
@@ -115,7 +114,6 @@ export async function setupTimeline(
     retry: input.eventRetry ?? 20,
   })
   await mockOpenCodeServer(page, {
-    protocol: input.protocol,
     directory,
     project: project(),
     provider: provider(),

packages/app/e2e/regression/prompt-input-v2-command-draft.spec.ts

@@ -1,50 +0,0 @@
-import { expect, test } from "@playwright/test"
-import { base64Encode } from "@opencode-ai/core/util/encode"
-import { mockOpenCodeServer } from "../utils/mock-server"
-import { expectAppVisible } from "../utils/waits"
-
-const directory = "C:/OpenCode/PromptInputV2Editing"
-const projectID = "proj_prompt_input_v2_editing"
-const sessionID = "ses_prompt_input_v2_editing"
-
-test("preserves the draft when a populated command menu triggers a built-in", async ({ page }) => {
-  await mockOpenCodeServer(page, {
-    directory,
-    project: {
-      id: projectID,
-      worktree: directory,
-      vcs: "git",
-      name: "prompt-input-v2-editing",
-      time: { created: 1700000000000, updated: 1700000000000 },
-      sandboxes: [],
-    },
-    provider: { all: [], connected: [], default: {} },
-    sessions: [
-      {
-        id: sessionID,
-        slug: "prompt-input-v2-editing",
-        projectID,
-        directory,
-        title: "Prompt input V2 editing",
-        version: "dev",
-        time: { created: 1700000000000, updated: 1700000000000 },
-      },
-    ],
-    pageMessages: () => ({ items: [] }),
-  })
-  await page.addInitScript(() => {
-    localStorage.setItem("settings.v3", JSON.stringify({ general: { newLayoutDesigns: true } }))
-  })
-
-  await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
-  const composer = page.locator('[data-component="prompt-input-v2"]')
-  const input = composer.locator('[data-component="prompt-input"]')
-  await expectAppVisible(composer)
-
-  await input.fill("keep me")
-  await composer.getByRole("button", { name: "Add images and files" }).click()
-  await page.getByRole("menuitem", { name: "Commands" }).click()
-  await page.locator('[data-suggestion-id="model.choose"]').click()
-
-  await expect(input).toHaveText("keep me")
-})

packages/app/e2e/regression/prompt-thinking-level.spec.ts

@@ -54,15 +54,18 @@ test("shows the V2 thinking level control while relevant", async ({ page }) => {
   })
 
   await page.goto(`/${base64Encode(directory)}/session/${sessionID}`)
-  const composer = page.locator('[data-component="prompt-input-v2"]')
+  const composer = page.locator('[data-component="session-composer"]')
   const input = composer.locator('[data-component="prompt-input"]')
-  const control = composer.getByRole("button", { name: "Choose model variant" })
+  const control = composer.locator('[data-component="prompt-variant-control"]')
   await expectAppVisible(composer)
 
   await idleComposer(page)
+  await expect(control).toBeHidden()
+
+  await composer.hover()
   await expect(control).toBeVisible()
 
-  await control.click()
+  await control.locator('[data-action="prompt-model-variant"]').click()
   const high = page.getByRole("menuitemradio", { name: "high" })
   await expect(high).toBeVisible()
   await page.mouse.move(0, 0)

packages/app/e2e/regression/session-timeline-lifecycle-state.spec.ts

@@ -32,23 +32,6 @@ for (const expanded of [false, true]) {
   })
 }
 
-test("shows and expands a running shell command without shimmering it", async ({ page }) => {
-  const id = "prt_shell_running_command"
-  const command = "sleep 10 && echo done"
-  await setupTimeline(page, {
-    messages: [userMessage(), assistantMessage([shell(id, "running", "still running", command)], { completed: false })],
-    settings: { shellToolPartsExpanded: false },
-  })
-
-  const tool = page.locator(`[data-timeline-part-id="${id}"]`)
-  await expect(tool.locator('[data-component="text-shimmer"]')).toHaveAttribute("data-active", "true")
-  await expect(tool.locator('[data-component="shell-submessage"]')).toHaveText(command)
-  await expect(tool.locator('[data-component="shell-submessage"] [data-component="text-shimmer"]')).toHaveCount(0)
-  await tool.locator('[data-slot="collapsible-trigger"]').click()
-  await expect(tool.locator('[data-slot="collapsible-trigger"]')).toHaveAttribute("aria-expanded", "true")
-  await expect(tool.locator('[data-slot="bash-pre"]')).toContainText("still running")
-})
-
 test("transitions thinking and hidden reasoning through busy to idle", async ({ page }) => {
   const reasoningID = "prt_reasoning_hidden"
   const assistant = assistantMessage([reasoningPart(reasoningID, "## Inspecting stability")], { completed: false })

packages/app/e2e/regression/session-timeline-transport.spec.ts

@@ -89,8 +89,8 @@ test("reconnects after a stream error", async ({ page }) => {
   expect((await timeline.transport.connections())[0]?.endedBy).toBe("error")
 })
 
-test("does not request replay when reconnecting the volatile V2 event stream", async ({ page }) => {
-  const timeline = await setupTimeline(page, { eventRetry: 10, protocol: "v2" })
+test("records event IDs and reconnect Last-Event-ID headers", async ({ page }) => {
+  const timeline = await setupTimeline(page, { eventRetry: 10 })
   const first = await timeline.transport.send(partUpdated(textPart("prt_transport_id", "event with id")), {
     id: "timeline-event-7",
   })
@@ -100,7 +100,7 @@ test("does not request replay when reconnecting the volatile V2 event stream", a
   const connection = await timeline.transport.waitForConnection({ after: first.connectionID })
 
   expect(first.eventID).toBe("timeline-event-7")
-  expect(connection.headers["last-event-id"]).toBeUndefined()
+  expect(connection.headers["last-event-id"]).toBe("timeline-event-7")
 })
 
 test("passes through non-event fetches", async ({ page }) => {

packages/app/e2e/smoke/session-timeline.spec.ts

@@ -736,5 +736,5 @@ async function switchTitlebarSession(page: Page, sessionID: string, title: strin
 }
 
 async function expectSessionReady(page: Page) {
-  await expectAppVisible(page.getByRole("textbox", { name: "Prompt" }))
+  await expectAppVisible(page.getByRole("textbox", { name: /Ask anything/i }))
 }

packages/app/e2e/utils/mock-server.ts

@@ -4,7 +4,6 @@ const emptyList = new Set(["/skill", "/command", "/lsp", "/formatter", "/vcs/sta
 const emptyObject = new Set(["/global/config", "/config", "/provider/auth", "/mcp", "/experimental/resource"])
 
 export interface MockServerConfig {
-  protocol?: "v1" | "v2"
   provider: unknown
   directory: string
   project: unknown
@@ -54,20 +53,8 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
     if (url.port !== targetPort && url.port !== appPort) return route.fallback()
 
     const path = url.pathname
-    if (path === "/global/event" || path === "/event" || path === "/api/event") {
-      const events = config.events?.()
-      return sse(
-        route,
-        path === "/api/event"
-          ? [{ id: "evt_mock_connected", type: "server.connected", data: {} }, ...(events?.map(currentEvent) ?? [])]
-          : events,
-        config.eventRetry,
-      )
-    }
-    if (path === "/global/health")
-      return config.protocol === "v2" ? json(route, {}, undefined, 404) : json(route, { healthy: true })
-    if (path === "/api/health" && config.protocol === "v2")
-      return json(route, { healthy: true, version: "2.0.0", pid: 1 })
+    if (path === "/global/event" || path === "/event") return sse(route, config.events?.(), config.eventRetry)
+    if (path === "/global/health") return json(route, { healthy: true })
     if (path === "/experimental/capabilities") return json(route, { backgroundSubagents: true })
     if (path === "/permission")
       return json(route, typeof config.permissions === "function" ? config.permissions() : (config.permissions ?? []))
@@ -96,129 +83,10 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
         },
         data: [],
       })
-    if (path === "/api/agent")
-      return json(route, {
-        location: location(config),
-        data: [
-          {
-            id: "build",
-            name: "Build",
-            mode: "primary",
-            hidden: false,
-            request: { settings: {}, headers: {}, body: {} },
-            permissions: [],
-          },
-        ],
-      })
-    if (path === "/api/command") return json(route, { location: location(config), data: [] })
-    if (path === "/api/mcp") return json(route, { location: location(config), data: [] })
-    if (path === "/api/mcp/resource")
-      return json(route, { location: location(config), data: { resources: [], templates: [] } })
-    const integration = path.match(/^\/api\/integration\/([^/]+)$/)?.[1]
-    if (integration && route.request().method() === "GET")
-      return json(route, {
-        location: location(config),
-        data: { id: integration, name: integration, methods: [{ type: "key", label: "API key" }], connections: [] },
-      })
-    if (/^\/api\/integration\/[^/]+\/connect\/key$/.test(path) && route.request().method() === "POST")
-      return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
-    if (path === "/api/project") return json(route, [config.project])
-    if (path === "/api/project/current")
-      return json(route, { id: (config.project as { id?: string }).id, directory: config.directory })
-    if (path.startsWith("/api/project/") && route.request().method() === "PATCH") return json(route, config.project)
-    if (path === "/api/path")
-      return json(route, {
-        state: config.directory,
-        config: config.directory,
-        worktree: config.directory,
-        directory: config.directory,
-        home: "C:/OpenCode",
-      })
-    if (path === "/api/permission/request")
-      return json(route, {
-        location: location(config),
-        data: (typeof config.permissions === "function" ? config.permissions() : (config.permissions ?? [])).map(
-          currentPermission,
-        ),
-      })
-    if (path === "/api/question/request")
-      return json(route, {
-        location: location(config),
-        data: typeof config.questions === "function" ? config.questions() : (config.questions ?? []),
-      })
-    if (path === "/api/vcs")
-      return json(route, { location: location(config), data: { branch: "main", defaultBranch: "main" } })
-    if (path === "/api/vcs/status") return json(route, { location: location(config), data: [] })
-    if (path === "/api/vcs/diff") return json(route, { location: location(config), data: config.vcsDiff ?? [] })
-    if (path === "/api/pty/shells") return json(route, { location: location(config), data: [] })
-    if (/^\/api\/pty\/[^/]+\/connect-token$/.test(path))
-      return json(route, { location: location(config), data: { ticket: "e2e-ticket", expires_in: 60 } })
     if (emptyObject.has(path)) return json(route, {})
     if (emptyList.has(path)) return json(route, [])
-    if (path === "/api/session") {
-      const directory = url.searchParams.get("directory")
-      const parentID = url.searchParams.get("parentID")
-      const limit = Number(url.searchParams.get("limit") ?? 50)
-      const offset = Number(url.searchParams.get("cursor") ?? 0)
-      const sessions = config.sessions
-        .filter((session) => !directory || session.directory === directory)
-        .filter((session) => parentID !== "null" || session.parentID === undefined)
-        .filter((session) => {
-          const search = url.searchParams.get("search")?.toLowerCase()
-          return (
-            !search ||
-            String(session.title ?? "")
-              .toLowerCase()
-              .includes(search)
-          )
-        })
-      const ordered = url.searchParams.get("order") === "asc" ? sessions.toReversed() : sessions
-      const data = ordered.slice(offset, offset + limit)
-      const next = offset + limit < ordered.length ? String(offset + limit) : undefined
-      return json(route, {
-        data: data.map((session) => currentSession(session, config.directory)),
-        cursor: { next },
-      })
-    }
-    if (path === "/api/session/active") {
-      const statuses = (config.sessionStatus ?? {}) as Record<string, { type?: string }>
-      return json(route, {
-        data: Object.fromEntries(
-          Object.entries(statuses).flatMap(([id, status]) =>
-            status.type === "idle" ? [] : [[id, { type: "running" }]],
-          ),
-        ),
-      })
-    }
-    if (/^\/api\/session\/[^/]+\/shell$/.test(path) && route.request().method() === "POST") {
-      return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
-    }
-    if (/^\/api\/session\/[^/]+\/question\/[^/]+\/(reply|reject)$/.test(path) && route.request().method() === "POST") {
-      return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
-    }
-    if (/^\/api\/session\/[^/]+\/permission\/[^/]+\/reply$/.test(path) && route.request().method() === "POST") {
-      return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
-    }
-    if (
-      /^\/api\/session\/[^/]+\/(archive|rename|interrupt|revert\/clear|revert\/commit)$/.test(path) &&
-      route.request().method() === "POST"
-    ) {
-      return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
-    }
-    if (/^\/api\/session\/[^/]+$/.test(path) && route.request().method() === "DELETE") {
-      return route.fulfill({ status: 204, headers: { "access-control-allow-origin": "*" } })
-    }
     if (path in staticRoutes) return json(route, staticRoutes[path])
 
-    const currentSessionMatch = path.match(/^\/api\/session\/([^/]+)$/)
-    if (currentSessionMatch) {
-      const session = config.sessions.find((item) => item.id === currentSessionMatch[1])
-      if (!session) return json(route, { error: "Session not found" }, undefined, 404)
-      return json(route, {
-        data: currentSession(session, config.directory),
-      })
-    }
-
     const sessionMatch = path.match(/^\/session\/([^/]+)$/)
     if (sessionMatch) {
       const session = config.sessions.find((s) => s.id === sessionMatch[1])
@@ -239,24 +107,6 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
 
     if (/^\/session\/[^/]+\/(children|diff)$/.test(path)) return json(route, [])
 
-    const currentMessagesMatch = path.match(/^\/api\/session\/([^/]+)\/message$/)
-    if (currentMessagesMatch) {
-      const token = url.searchParams.get("cursor") ?? undefined
-      const before = token ? cursors.get(token) : undefined
-      if (token && !before) return json(route, { error: "Invalid cursor" }, undefined, 400)
-      config.onMessages?.({ sessionID: currentMessagesMatch[1], before, phase: "start" })
-      await config.beforeMessagesResponse?.({ sessionID: currentMessagesMatch[1]!, before })
-      if (config.messageDelay !== undefined) await new Promise((resolve) => setTimeout(resolve, config.messageDelay))
-      const pageData = config.pageMessages(currentMessagesMatch[1], Number(url.searchParams.get("limit") ?? 50), before)
-      config.onMessages?.({ sessionID: currentMessagesMatch[1], before, phase: "end" })
-      const cursor = pageData.cursor ? `cursor_${++nextCursor}` : undefined
-      if (cursor) cursors.set(cursor, pageData.cursor!)
-      return json(route, {
-        data: pageData.items.map(currentMessage).reverse(),
-        cursor: { next: cursor },
-      })
-    }
-
     const messagesMatch = path.match(/^\/session\/([^/]+)\/message$/)
     if (messagesMatch) {
       const token = url.searchParams.get("before") ?? undefined
@@ -279,115 +129,6 @@ export async function mockOpenCodeServer(page: Page, config: MockServerConfig) {
   })
 }
 
-function location(config: MockServerConfig) {
-  return {
-    directory: config.directory,
-    project: { id: (config.project as { id?: string }).id, directory: config.directory },
-  }
-}
-
-function currentPermission(value: unknown) {
-  const permission = value as Record<string, unknown>
-  if (permission.action) return permission
-  const tool = permission.tool as { messageID?: string; callID?: string } | undefined
-  return {
-    id: permission.id,
-    sessionID: permission.sessionID,
-    action: permission.permission,
-    resources: permission.patterns ?? [],
-    save: permission.always,
-    metadata: permission.metadata,
-    source:
-      tool?.messageID && tool.callID ? { type: "tool", messageID: tool.messageID, callID: tool.callID } : undefined,
-  }
-}
-
-export function currentSession(session: { id: string } & Record<string, unknown>, fallbackDirectory?: string) {
-  const time = session.time && typeof session.time === "object" ? session.time : {}
-  return {
-    id: session.id,
-    parentID: session.parentID,
-    projectID: session.projectID ?? "project",
-    agent: session.agent ?? "build",
-    model: session.model ?? { id: "mock-model", providerID: "mock-provider" },
-    cost: session.cost ?? 0,
-    tokens: session.tokens ?? { input: 0, output: 0, reasoning: 0, cache: { read: 0, write: 0 } },
-    time: {
-      created: "created" in time && typeof time.created === "number" ? time.created : 0,
-      updated: "updated" in time && typeof time.updated === "number" ? time.updated : 0,
-      ...(session.time && typeof session.time === "object" && "archived" in session.time
-        ? { archived: session.time.archived }
-        : {}),
-    },
-    title: session.title ?? session.id,
-    location: {
-      directory: typeof session.directory === "string" ? session.directory : fallbackDirectory,
-      ...(typeof session.workspaceID === "string" ? { workspaceID: session.workspaceID } : {}),
-    },
-    subpath: session.path,
-    revert: session.revert,
-  }
-}
-
-function currentMessage(value: unknown) {
-  const item = value as {
-    info: Record<string, unknown> & { id: string; role: "user" | "assistant"; time: { created: number } }
-    parts: Array<Record<string, unknown> & { type: string }>
-  }
-  if (item.info.role === "user") {
-    return {
-      id: item.info.id,
-      type: "user",
-      time: item.info.time,
-      text: item.parts
-        .flatMap((part) => (part.type === "text" && typeof part.text === "string" ? [part.text] : []))
-        .join("\n"),
-    }
-  }
-  return {
-    id: item.info.id,
-    type: "assistant",
-    time: item.info.time,
-    agent: item.info.agent ?? "build",
-    model: { id: item.info.modelID ?? "model", providerID: item.info.providerID ?? "provider" },
-    cost: item.info.cost,
-    tokens: item.info.tokens,
-    error: item.info.error,
-    content: item.parts.flatMap<unknown>((part) => {
-      if (part.type === "text" || part.type === "reasoning") return [{ type: part.type, text: part.text ?? "" }]
-      if (part.type !== "tool") return []
-      const state = part.state as Record<string, unknown>
-      return [
-        {
-          type: "tool",
-          id: part.id,
-          name: part.tool,
-          time: state.time ?? { created: item.info.time.created },
-          state:
-            state.status === "pending"
-              ? { status: "streaming", input: state.raw ?? JSON.stringify(state.input ?? {}) }
-              : state.status === "completed"
-                ? {
-                    status: "completed",
-                    input: state.input ?? {},
-                    structured: state.metadata ?? {},
-                    content: [{ type: "text", text: state.output ?? "" }],
-                  }
-                : state.status === "error"
-                  ? {
-                      status: "error",
-                      input: state.input ?? {},
-                      structured: state.metadata ?? {},
-                      content: [],
-                      error: { type: "ToolError", message: state.error ?? "Tool failed" },
-                    }
-                  : { status: "running", input: state.input ?? {}, structured: state.metadata ?? {}, content: [] },
-        },
-      ]
-    }),
-  }
-}
-
 function json(route: Route, body: unknown, headers?: Record<string, string>, status = 200) {
   return route.fulfill({
     status,
@@ -408,18 +149,3 @@ function sse(route: Route, events?: unknown[], retry?: number) {
     body: `${retry === undefined ? "" : `retry: ${retry}\n\n`}${events?.map((event) => `data: ${JSON.stringify(event)}\n\n`).join("") || ": ok\n\n"}`,
   })
 }
-
-function currentEvent(input: unknown) {
-  if (!input || typeof input !== "object" || !("payload" in input)) return input
-  const envelope = input as { directory?: string; payload?: unknown }
-  if (!envelope.payload || typeof envelope.payload !== "object") return input
-  const payload = envelope.payload as { id?: string; type?: string; properties?: unknown }
-  if (!payload.type) return input
-  return {
-    id: payload.id ?? `evt_mock_${Date.now()}`,
-    created: Date.now(),
-    type: payload.type,
-    data: payload.properties ?? {},
-    location: envelope.directory && envelope.directory !== "global" ? { directory: envelope.directory } : undefined,
-  }
-}

packages/app/e2e/utils/sse-transport.ts

@@ -3,7 +3,7 @@ import type { Page } from "@playwright/test"
 export type SseConnectionRecord = {
   id: number
   url: string
-  path: "/global/event" | "/event" | "/api/event"
+  path: "/global/event" | "/event"
   headers: Record<string, string>
   openedAt: number
   endedAt?: number
@@ -93,21 +93,6 @@ export async function installSseTransport<T>(
           eventOptions.retry === undefined ? "" : `retry: ${eventOptions.retry}\n`,
           `data: ${JSON.stringify(payload)}\n\n`,
         ].join("")
-      const currentEvent = (input: unknown) => {
-        if (!input || typeof input !== "object" || !("payload" in input)) return input
-        const envelope = input as { directory?: string; payload?: unknown }
-        if (!envelope.payload || typeof envelope.payload !== "object") return input
-        const payload = envelope.payload as { id?: string; type?: string; properties?: unknown }
-        if (!payload.type) return input
-        return {
-          id: payload.id ?? `evt_mock_${Date.now()}`,
-          created: Date.now(),
-          type: payload.type,
-          data: payload.properties ?? {},
-          location:
-            envelope.directory && envelope.directory !== "global" ? { directory: envelope.directory } : undefined,
-        }
-      }
       const acknowledge = (
         connection: Connection,
         bytes: number,
@@ -155,13 +140,15 @@ export async function installSseTransport<T>(
           output.forEach((chunk) => connection.controller.enqueue(chunk))
           return acknowledge(connection, input.bytes.length, output.length)
         }
-        const encoded = input.deliveries.map((delivery) => {
-          const payload = connection.path === "/api/event" ? currentEvent(delivery.payload) : delivery.payload
-          return { delivery, payload, bytes: encoder.encode(frame(payload, delivery.options)) }
-        })
+        const encoded = input.deliveries.map((delivery) => ({
+          delivery,
+          bytes: encoder.encode(frame(delivery.payload, delivery.options)),
+        }))
         encoded.forEach((item) => marker(item.delivery.options?.marker))
         if (input.burst) {
-          const bytes = encoder.encode(encoded.map((item) => frame(item.payload, item.delivery.options)).join(""))
+          const bytes = encoder.encode(
+            encoded.map((item) => frame(item.delivery.payload, item.delivery.options)).join(""),
+          )
           connection.controller.enqueue(bytes)
           return encoded.map((item) => acknowledge(connection, item.bytes.byteLength, 1, item.delivery.options?.id))
         }
@@ -174,10 +161,7 @@ export async function installSseTransport<T>(
       const fetch = (input: RequestInfo | URL, init?: RequestInit) => {
         const request = new Request(input, init)
         const url = new URL(request.url)
-        if (
-          url.origin !== server ||
-          (url.pathname !== "/global/event" && url.pathname !== "/event" && url.pathname !== "/api/event")
-        )
+        if (url.origin !== server || (url.pathname !== "/global/event" && url.pathname !== "/event"))
           return originalFetch(request)
 
         const id = ++nextConnectionID
@@ -193,10 +177,6 @@ export async function installSseTransport<T>(
             record.controller = controller
             connections.push(record)
             if (retry !== undefined) controller.enqueue(encoder.encode(`retry: ${retry}\n\n`))
-            if (url.pathname === "/api/event")
-              controller.enqueue(
-                encoder.encode(frame({ id: `evt_mock_connected_${id}`, type: "server.connected", data: {} })),
-              )
             request.signal.addEventListener(
               "abort",
               () => {

packages/app/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@opencode-ai/app",
-  "version": "1.18.4",
+  "version": "1.17.20",
   "description": "",
   "type": "module",
   "exports": {
@@ -53,7 +53,6 @@
     "@dnd-kit/helpers": "0.5.0",
     "@dnd-kit/solid": "0.5.0",
     "@kobalte/core": "catalog:",
-    "@opencode-ai/client": "file:vendor/opencode-ai-client-1.17.13.tgz",
     "@opencode-ai/core": "workspace:*",
     "@opencode-ai/schema": "workspace:*",
     "@opencode-ai/sdk": "workspace:*",
@@ -82,7 +81,7 @@
     "diff": "catalog:",
     "effect": "catalog:",
     "fuzzysort": "catalog:",
-    "ghostty-web": "github:anomalyco/ghostty-web#83c0a07b8628b748aed073b232cb4b52a6ca11c1",
+    "ghostty-web": "github:anomalyco/ghostty-web#513463a6f1190253057e8a3f0dac8f6ee8393553",
     "luxon": "catalog:",
     "marked": "catalog:",
     "marked-shiki": "catalog:",

packages/app/src/addons/serialize.test.ts

@@ -37,14 +37,6 @@ function writeAndWait(term: Terminal, data: string): Promise<void> {
 }
 
 describe("SerializeAddon", () => {
-  test("preserves color scheme reporting mode", async () => {
-    const { term, addon } = createTerminal()
-    await writeAndWait(term, "\x1b[?2031h")
-
-    expect(addon.serialize().startsWith("\x1b[?2031h")).toBe(true)
-    expect(addon.serialize({ excludeModes: true }).startsWith("\x1b[?2031h")).toBe(false)
-  })
-
   describe("ANSI color preservation", () => {
     test("should preserve text attributes (bold, italic, underline)", async () => {
       const { term, addon } = createTerminal()

packages/app/src/addons/serialize.ts

@@ -89,13 +89,6 @@ const getTerminalBuffers = (value: ITerminalCore): TerminalBuffers | undefined =
   return { active, normal, alternate }
 }
 
-const getTerminalMode = (value: ITerminalCore, mode: number) => {
-  if (!isRecord(value)) return false
-  const terminal = value.wasmTerm
-  if (!isRecord(terminal) || typeof terminal.getMode !== "function") return false
-  return terminal.getMode(mode) === true
-}
-
 // ============================================================================
 // Types
 // ============================================================================
@@ -551,8 +544,7 @@ export class SerializeAddon implements ITerminalAddon {
       return ""
     }
 
-    let content = !options?.excludeModes && getTerminalMode(this._terminal, 2031) ? "\u001b[?2031h" : ""
-    content += options?.range
+    let content = options?.range
       ? this._serializeBufferByRange(normalBuffer, options.range, true)
       : this._serializeBufferByScrollback(normalBuffer, options?.scrollback)
 

packages/app/src/app.tsx

@@ -9,16 +9,7 @@ import { Font } from "@opencode-ai/ui/font"
 import { Splash } from "@opencode-ai/ui/logo"
 import { ThemeProvider } from "@opencode-ai/ui/theme/context"
 import { MetaProvider } from "@solidjs/meta"
-import {
-  type BaseRouterProps,
-  Navigate,
-  Route,
-  Router,
-  useLocation,
-  useNavigate,
-  useParams,
-  useSearchParams,
-} from "@solidjs/router"
+import { type BaseRouterProps, Navigate, Route, Router, useNavigate, useParams, useSearchParams } from "@solidjs/router"
 import { QueryClient, QueryClientProvider } from "@tanstack/solid-query"
 import { Effect } from "effect"
 import { base64Encode } from "@opencode-ai/core/util/encode"
@@ -38,7 +29,6 @@ import {
   Show,
 } from "solid-js"
 import { Dynamic } from "solid-js/web"
-import { makeEventListener } from "@solid-primitives/event-listener"
 import { CommandProvider, useCommand, type CommandOption } from "@/context/command"
 import { CommentsProvider } from "@/context/comments"
 import { FileProvider } from "@/context/file"

packages/app/src/components/command-palette.ts

@@ -1,18 +1,17 @@
+import { base64Encode } from "@opencode-ai/core/util/encode"
 import { getFilename } from "@opencode-ai/core/util/path"
-import type { GlobalSession, Project } from "@opencode-ai/sdk/v2/client"
 import { useDialog } from "@opencode-ai/ui/context/dialog"
+import { useNavigate } from "@solidjs/router"
 import { createMemo, onCleanup } from "solid-js"
-import { commandPaletteOptions, useCommand, type CommandOption } from "@/context/command"
+import { useCommand, type CommandOption } from "@/context/command"
 import { useFile } from "@/context/file"
-import { useGlobal } from "@/context/global"
 import { useLanguage } from "@/context/language"
-import { useLayout, type LocalProject } from "@/context/layout"
-import { ServerConnection } from "@/context/server"
-import { useServerSDK } from "@/context/server-sdk"
-import { useTabs } from "@/context/tabs"
-import { displayName, projectForSession } from "@/pages/layout/helpers"
+import { useLayout } from "@/context/layout"
+import { useServerSDK, type ServerSDK } from "@/context/server-sdk"
+import { useServerSync } from "@/context/server-sync"
 import { createSessionTabs } from "@/pages/session/helpers"
 import { useSessionLayout } from "@/pages/session/session-layout"
+import { decode64 } from "@/utils/base64"
 
 export type CommandPaletteEntry = {
   id: string
@@ -25,8 +24,6 @@ export type CommandPaletteEntry = {
   path?: string
   directory?: string
   sessionID?: string
-  server?: ServerConnection.Key
-  project?: LocalProject
   archived?: number
   updated?: number
 }
@@ -78,25 +75,28 @@ export function createCommandPaletteFileOpener(onOpenFile?: (path: string) => vo
 
 export function createCommandPaletteModel(props: { filesOnly?: () => boolean; onOpenFile?: (path: string) => void }) {
   const command = useCommand()
-  const global = useGlobal()
   const language = useLanguage()
+  const layout = useLayout()
   const file = useFile()
   const dialog = useDialog()
+  const navigate = useNavigate()
   const serverSDK = useServerSDK()()
-  const serverCtx = global.ensureServerCtx(serverSDK.server)
-  const appTabs = useTabs()
-  const { tabs: sessionTabs } = useSessionLayout()
+  const serverSync = useServerSync()
+  const { params, tabs } = useSessionLayout()
   const openFile = createCommandPaletteFileOpener(props.onOpenFile)
   const state = { cleanup: undefined as (() => void) | void, committed: false }
   const filesOnly = () => props.filesOnly?.() ?? false
 
   const allowedCommands = createMemo(() => {
     if (filesOnly()) return []
-    return commandPaletteOptions(command.options)
+    return command.options.filter(
+      (option) =>
+        !option.disabled && !option.hidden && !option.id.startsWith("suggested.") && option.id !== "file.open",
+    )
   })
   const commandEntries = createMemo(() => {
     const category = language.t("palette.group.commands")
-    return allowedCommands().map((option) => createCommandPaletteCommandEntry(option, category))
+    return allowedCommands().map((option) => createCommandEntry(option, category))
   })
   const preferredCommandEntries = createMemo(() => {
     const all = allowedCommands()
@@ -105,11 +105,11 @@ export function createCommandPaletteModel(props: { filesOnly?: () => boolean; on
     const base = picked.length ? picked : all.slice(0, ENTRY_LIMIT)
     const sorted = picked.length ? [...base].sort((a, b) => (order.get(a.id) ?? 0) - (order.get(b.id) ?? 0)) : base
     const category = language.t("palette.group.commands")
-    return sorted.map((option) => createCommandPaletteCommandEntry(option, category))
+    return sorted.map((option) => createCommandEntry(option, category))
   })
 
   const tabState = createSessionTabs({
-    tabs: sessionTabs,
+    tabs,
     pathFromTab: file.pathFromTab,
     normalizeTab: (tab) => (tab.startsWith("file://") ? file.tab(tab) : tab),
   })
@@ -140,12 +140,36 @@ export function createCommandPaletteModel(props: { filesOnly?: () => boolean; on
       .map((path) => createCommandPaletteFileEntry(path, category))
   })
 
-  const sessions = createServerSessionEntries({
-    server: ServerConnection.key(serverSDK.server),
-    opened: serverCtx.projects.list,
-    stored: () => serverCtx.sync.data.project,
-    load: (search, signal) =>
-      serverSDK.client.experimental.session.list({ roots: true, search, limit: 50 }, { signal }),
+  const projectDirectory = createMemo(() => decode64(params.dir) ?? "")
+  const project = createMemo(() => {
+    const directory = projectDirectory()
+    if (!directory) return undefined
+    return layout.projects.list().find((item) => item.worktree === directory || item.sandboxes?.includes(directory))
+  })
+  const workspaces = createMemo(() => {
+    const directory = projectDirectory()
+    const current = project()
+    if (!current) return directory ? [directory] : []
+    const dirs = [current.worktree, ...(current.sandboxes ?? [])]
+    if (directory && !dirs.includes(directory)) return [...dirs, directory]
+    return dirs
+  })
+  const homedir = createMemo(() => serverSync().data.path.home)
+  const sessions = createSessionEntries({
+    workspaces,
+    label: (directory) => {
+      const current = project()
+      const kind =
+        current && directory === current.worktree
+          ? language.t("workspace.type.local")
+          : language.t("workspace.type.sandbox")
+      const [store] = serverSync().child(directory, { bootstrap: false })
+      const home = homedir()
+      const path = home ? directory.replace(home, "~") : directory
+      const name = store.vcs?.branch ?? getFilename(directory)
+      return `${kind} : ${name || path}`
+    },
+    load: (directory) => serverSDK.client.session.list({ directory, roots: true }),
     untitled: () => language.t("command.session.new"),
     category: () => language.t("command.category.session"),
   })
@@ -167,17 +191,8 @@ export function createCommandPaletteModel(props: { filesOnly?: () => boolean; on
       return
     }
     if (item.type === "session") {
-      if (!item.sessionID || !item.server) return
-      const directory = item.project?.worktree ?? item.directory
-      if (directory) {
-        serverCtx.projects.open(directory)
-        serverCtx.projects.touch(directory)
-      }
-      const tab = appTabs.addSessionTab({
-        server: item.server,
-        sessionId: item.sessionID,
-      })
-      appTabs.select(tab)
+      if (!item.directory || !item.sessionID) return
+      navigate(`/${base64Encode(item.directory)}/session/${item.sessionID}`)
       return
     }
     if (!item.path) return
@@ -203,7 +218,7 @@ export function createCommandPaletteModel(props: { filesOnly?: () => boolean; on
   }
 }
 
-export function createCommandPaletteCommandEntry(option: CommandOption, category: string): CommandPaletteEntry {
+function createCommandEntry(option: CommandOption, category: string): CommandPaletteEntry {
   return {
     id: "command:" + option.id,
     type: "command",
@@ -215,65 +230,96 @@ export function createCommandPaletteCommandEntry(option: CommandOption, category
   }
 }
 
-export function createServerSessionEntries(props: {
-  server: ServerConnection.Key
-  opened: () => LocalProject[]
-  stored: () => Project[]
-  load: (search: string, signal: AbortSignal) => Promise<{ data?: GlobalSession[] }>
+function createSessionEntries(props: {
+  workspaces: () => string[]
+  label: (directory: string) => string
+  load: (directory: string) => ReturnType<ServerSDK["client"]["session"]["list"]>
   untitled: () => string
   category: () => string
 }) {
-  let abort: AbortController | undefined
+  const state: {
+    token: number
+    inflight: Promise<CommandPaletteEntry[]> | undefined
+    cached: CommandPaletteEntry[] | undefined
+  } = { token: 0, inflight: undefined, cached: undefined }
 
-  onCleanup(() => abort?.abort())
-
-  return async (text: string): Promise<CommandPaletteEntry[]> => {
-    const search = text.trim()
-    if (!search) {
-      abort?.abort()
-      return []
+  return (text: string) => {
+    if (!text.trim()) {
+      state.token += 1
+      state.inflight = undefined
+      state.cached = undefined
+      return [] as CommandPaletteEntry[]
     }
-    abort?.abort()
-    const current = new AbortController()
-    abort = current
-    await new Promise<void>((resolve) => {
-      const timer = setTimeout(resolve, 100)
-      current.signal.addEventListener(
-        "abort",
-        () => {
-          clearTimeout(timer)
-          resolve()
-        },
-        { once: true },
-      )
-    })
-    if (current.signal.aborted) return []
-    const opened = props.opened()
-    const openedByID = new Map(opened.flatMap((project) => (project.id ? [[project.id, project] as const] : [])))
-    const stored = props.stored().map((project) => ({ ...project, expanded: false }))
-    const storedByID = new Map(stored.map((project) => [project.id, project] as const))
-    return props
-      .load(search, current.signal)
-      .then((result) =>
-        (result.data ?? [])
-          .filter((session) => !session.time.archived)
-          .map((session) => {
-            const project =
-              projectForSession(session, opened, openedByID) ?? projectForSession(session, stored, storedByID)
-            return {
-              id: `session:${props.server}:${session.id}`,
-              type: "session" as const,
-              title: session.title || props.untitled(),
-              description: project ? displayName(project) : session.project?.name || getFilename(session.directory),
-              category: props.category(),
-              directory: session.directory,
-              sessionID: session.id,
-              server: props.server,
-              project,
-              updated: session.time.updated,
-            }
-          }),
-      )
+    if (state.cached) return state.cached
+    if (state.inflight) return state.inflight
+
+    const current = state.token
+    const dirs = props.workspaces()
+    if (dirs.length === 0) return [] as CommandPaletteEntry[]
+
+    state.inflight = Promise.all(
+      dirs.map((directory) => {
+        const description = props.label(directory)
+        return props
+          .load(directory)
+          .then((result) =>
+            (result.data ?? [])
+              .filter((session) => !!session?.id)
+              .map((session) => ({
+                id: session.id,
+                title: session.title ?? props.untitled(),
+                description,
+                directory,
+                archived: session.time?.archived,
+                updated: session.time?.updated,
+              })),
+          )
+          .catch(() => [] as SessionEntryInput[])
+      }),
+    )
+      .then((results) => {
+        if (state.token !== current) return [] as CommandPaletteEntry[]
+        const seen = new Set<string>()
+        const next = results
+          .flat()
+          .filter((item) => {
+            const key = `${item.directory}:${item.id}`
+            if (seen.has(key)) return false
+            seen.add(key)
+            return true
+          })
+          .map((item) => createSessionEntry(item, props.category()))
+        state.cached = next
+        return next
+      })
       .catch(() => [] as CommandPaletteEntry[])
+      .finally(() => {
+        state.inflight = undefined
+      })
+
+    return state.inflight
+  }
+}
+
+type SessionEntryInput = {
+  directory: string
+  id: string
+  title: string
+  description: string
+  archived?: number
+  updated?: number
+}
+
+function createSessionEntry(input: SessionEntryInput, category: string): CommandPaletteEntry {
+  return {
+    id: `session:${input.directory}:${input.id}`,
+    type: "session",
+    title: input.title,
+    description: input.description,
+    category,
+    directory: input.directory,
+    sessionID: input.id,
+    archived: input.archived,
+    updated: input.updated,
   }
 }