chore: remove updated screenshot asset

docs: add updated desktop screenshot
fix(desktop): use requested default background
2026-08-15 17:08:21 -04:00 · 2026-07-21 20:52:58 +00:00 · 2026-07-21 20:52:33 +00:00 · 2026-07-21 20:50:56 +00:00 · 2026-07-21 20:32:41 +00:00 · 2026-07-21 20:31:53 +00:00
503 changed files with 25207 additions and 11910 deletions
@@ -0,0 +1,5 @@
+---
+"@opencode-ai/cli": patch
+---
+
+Expose a TUI plugin slot at the top of the session view.
@@ -0,0 +1,7 @@
+---
+"@opencode-ai/client": patch
+"@opencode-ai/plugin": patch
+"@opencode-ai/protocol": patch
+---
+
+Expose transient, read-only session generation through the HTTP API, generated clients, and V2 plugin session context.
@@ -0,0 +1,5 @@
+---
+"@opencode-ai/cli": patch
+---
+
+Expose a TUI plugin slot above the session composer.
@@ -121,6 +121,55 @@ 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
@@ -413,6 +462,7 @@ jobs:
    needs:
      - version
      - build-cli
+      - build-node-cli
      - sign-cli-windows
      - build-electron
    if: always() && !failure() && !cancelled()
@@ -461,6 +511,12 @@ jobs:
          name: opencode-preview-cli
          path: packages/cli/dist

+      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
+        with:
+          pattern: opencode-node-cli-*
+          path: packages/cli/dist/node
+          merge-multiple: true
+
      - uses: actions/download-artifact@d3f86a106a0bac45b974a628896c90dbdf5c8093 # v4.3.0
        if: needs.version.outputs.release
        with:
@@ -78,6 +78,20 @@ 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
@@ -11,6 +11,7 @@ node_modules
 playground
 tmp
 dist
+dist-node
 ts-dist
 .turbo
 .typecheck-profiles
@@ -25,6 +26,7 @@ Session.vim
 a.out
 target
 .scripts
+.cache
 .direnv/

 # Local dev files
@@ -132,27 +132,37 @@
        "@opencode-ai/server": "workspace:*",
        "@opencode-ai/tui": "workspace:*",
        "@opentui/core": "catalog:",
-        "@opentui/keymap": "catalog:",
        "@opentui/solid": "catalog:",
        "@parcel/watcher": "2.5.1",
        "effect": "catalog:",
-        "fuzzysort": "catalog:",
        "immer": "11.1.4",
        "jsonc-parser": "3.3.1",
        "open": "10.1.2",
-        "opentui-spinner": "catalog:",
        "semver": "catalog:",
        "solid-js": "catalog:",
-        "strip-ansi": "7.1.2",
        "uqr": "0.1.3",
+        "ws": "8.21.0",
      },
      "devDependencies": {
+        "@lydell/node-pty-darwin-arm64": "1.2.0-beta.12",
+        "@lydell/node-pty-darwin-x64": "1.2.0-beta.12",
+        "@lydell/node-pty-linux-arm64": "1.2.0-beta.12",
+        "@lydell/node-pty-linux-x64": "1.2.0-beta.12",
+        "@lydell/node-pty-win32-arm64": "1.2.0-beta.12",
+        "@lydell/node-pty-win32-x64": "1.2.0-beta.12",
        "@opencode-ai/protocol": "workspace:*",
        "@opencode-ai/script": "workspace:*",
+        "@parcel/watcher-darwin-arm64": "2.5.1",
+        "@parcel/watcher-linux-arm64-glibc": "2.5.1",
+        "@parcel/watcher-linux-x64-glibc": "2.5.1",
+        "@parcel/watcher-win32-arm64": "2.5.1",
+        "@parcel/watcher-win32-x64": "2.5.1",
        "@tsconfig/bun": "catalog:",
        "@types/bun": "catalog:",
        "@types/semver": "catalog:",
        "@typescript/native-preview": "catalog:",
+        "vite": "catalog:",
+        "vite-plugin-solid": "catalog:",
      },
    },
    "packages/client": {
@@ -171,7 +181,7 @@
        "effect": "catalog:",
      },
      "peerDependencies": {
-        "effect": "4.0.0-beta.83",
+        "effect": "4.0.0-beta.98",
      },
      "optionalPeers": [
        "effect",
@@ -387,6 +397,7 @@
        "mime-types": "3.0.2",
        "minimatch": "10.2.5",
        "npm-package-arg": "13.0.2",
+        "resolve.exports": "catalog:",
        "semver": "^7.6.3",
        "turndown": "7.2.0",
        "venice-ai-sdk-provider": "2.1.1",
@@ -554,7 +565,7 @@
      "name": "@opencode-ai/http-recorder",
      "version": "1.18.3",
      "dependencies": {
-        "@effect/platform-node-shared": "4.0.0-beta.83",
+        "@effect/platform-node-shared": "4.0.0-beta.98",
      },
      "devDependencies": {
        "@effect/platform-node": "catalog:",
@@ -739,9 +750,9 @@
        "typescript": "catalog:",
      },
      "peerDependencies": {
-        "@opentui/core": ">=0.4.3",
-        "@opentui/keymap": ">=0.4.3",
-        "@opentui/solid": ">=0.4.3",
+        "@opentui/core": ">=0.4.5",
+        "@opentui/keymap": ">=0.4.5",
+        "@opentui/solid": ">=0.4.5",
      },
      "optionalPeers": [
        "@opentui/core",
@@ -885,9 +896,13 @@
      "version": "1.17.13",
      "dependencies": {
        "@fontsource/commit-mono": "5.2.5",
+        "@fontsource/noto-sans-math": "5.2.5",
+        "@fontsource/noto-sans-symbols": "5.2.5",
+        "@fontsource/noto-sans-symbols-2": "5.2.5",
        "@napi-rs/canvas": "1.0.2",
        "@opencode-ai/ai": "workspace:*",
        "@opencode-ai/core": "workspace:*",
+        "@opencode-ai/plugin": "workspace:*",
        "@opentui/core": "catalog:",
        "effect": "catalog:",
      },
@@ -1011,6 +1026,7 @@
        "@opencode-ai/client": "workspace:*",
        "@opencode-ai/core": "workspace:*",
        "@opencode-ai/plugin": "workspace:*",
+        "@opencode-ai/schema": "workspace:*",
        "@opencode-ai/simulation": "workspace:*",
        "@opencode-ai/ui": "workspace:*",
        "@opentui/core": "catalog:",
@@ -1021,10 +1037,12 @@
        "diff": "catalog:",
        "effect": "catalog:",
        "fuzzysort": "catalog:",
+        "get-east-asian-width": "catalog:",
        "open": "10.1.2",
        "opentui-spinner": "catalog:",
        "remeda": "catalog:",
        "solid-js": "catalog:",
+        "string-width": "catalog:",
        "strip-ansi": "7.1.2",
        "uqr": "0.1.3",
      },
@@ -1163,12 +1181,12 @@
    "@modelcontextprotocol/sdk@1.29.0": "patches/@modelcontextprotocol%2Fsdk@1.29.0.patch",
    "gcp-metadata@8.1.2": "patches/gcp-metadata@8.1.2.patch",
    "@standard-community/standard-openapi@0.2.9": "patches/@standard-community%2Fstandard-openapi@0.2.9.patch",
-    "effect@4.0.0-beta.83": "patches/effect@4.0.0-beta.83.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",
    "solid-js@1.9.10": "patches/solid-js@1.9.10.patch",
    "@ai-sdk/google@3.0.73": "patches/@ai-sdk%2Fgoogle@3.0.73.patch",
    "pacote@21.5.0": "patches/pacote@21.5.0.patch",
+    "effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
  },
  "overrides": {
    "@opentui/core": "catalog:",
@@ -1180,9 +1198,9 @@
  "catalog": {
    "@cloudflare/workers-types": "4.20251008.0",
    "@corvu/drawer": "0.2.4",
-    "@effect/opentelemetry": "4.0.0-beta.83",
-    "@effect/platform-node": "4.0.0-beta.83",
-    "@effect/sql-sqlite-bun": "4.0.0-beta.83",
+    "@effect/opentelemetry": "4.0.0-beta.98",
+    "@effect/platform-node": "4.0.0-beta.98",
+    "@effect/sql-sqlite-bun": "4.0.0-beta.98",
    "@hono/standard-validator": "0.2.0",
    "@hono/zod-validator": "0.4.2",
    "@kobalte/core": "0.13.11",
@@ -1190,9 +1208,9 @@
    "@npmcli/arborist": "9.4.0",
    "@octokit/rest": "22.0.0",
    "@openauthjs/openauth": "0.0.0-20250322224806",
-    "@opentui/core": "0.4.3",
-    "@opentui/keymap": "0.4.3",
-    "@opentui/solid": "0.4.3",
+    "@opentui/core": "0.4.5",
+    "@opentui/keymap": "0.4.5",
+    "@opentui/solid": "0.4.5",
    "@pierre/diffs": "1.2.10",
    "@playwright/test": "1.59.1",
    "@sentry/solid": "10.36.0",
@@ -1218,8 +1236,9 @@
    "dompurify": "3.3.1",
    "drizzle-kit": "1.0.0-rc.2",
    "drizzle-orm": "1.0.0-rc.2",
-    "effect": "4.0.0-beta.83",
+    "effect": "4.0.0-beta.98",
    "fuzzysort": "3.1.0",
+    "get-east-asian-width": "1.6.0",
    "hono": "4.10.7",
    "hono-openapi": "1.1.2",
    "luxon": "3.6.1",
@@ -1228,11 +1247,13 @@
    "opentui-spinner": "0.0.7",
    "remeda": "2.26.0",
    "remend": "1.3.0",
+    "resolve.exports": "2.0.3",
    "semver": "7.7.4",
    "shiki": "4.2.0",
    "solid-js": "1.9.10",
    "solid-list": "0.3.0",
    "sst": "4.13.1",
+    "string-width": "7.2.0",
    "tailwindcss": "4.1.11",
    "typescript": "5.8.2",
    "ulid": "3.0.1",
@@ -1619,13 +1640,13 @@

    "@drizzle-team/brocli": ["@drizzle-team/brocli@0.11.0", "", {}, "sha512-hD3pekGiPg0WPCCGAZmusBBJsDqGUR66Y452YgQsZOnkdQ7ViEPKuyP4huUGEZQefp8g34RRodXYmJ2TbCH+tg=="],

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+    "@effect/opentelemetry": ["@effect/opentelemetry@4.0.0-beta.98", "", { "peerDependencies": { "@opentelemetry/api": "^1.9", "@opentelemetry/api-logs": ">=0.203.0 <0.300.0", "@opentelemetry/resources": "^2.0.0", "@opentelemetry/sdk-logs": ">=0.203.0 <0.300.0", "@opentelemetry/sdk-metrics": "^2.0.0", "@opentelemetry/sdk-trace-base": "^2.0.0", "@opentelemetry/sdk-trace-node": "^2.0.0", "@opentelemetry/sdk-trace-web": "^2.0.0", "@opentelemetry/semantic-conventions": "^1.33.0", "effect": "^4.0.0-beta.98" }, "optionalPeers": ["@opentelemetry/api", "@opentelemetry/api-logs", "@opentelemetry/resources", "@opentelemetry/sdk-logs", "@opentelemetry/sdk-metrics", "@opentelemetry/sdk-trace-base", "@opentelemetry/sdk-trace-node", "@opentelemetry/sdk-trace-web"] }, "sha512-ITfK8xhcl+9GXOvPwzADWkOQ+dgUGZrJNefT3r2+uLFmzjyKRLtHzhLOl6lZaLSsf5io13+nmt8adfMRQPq+oA=="],

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+    "@effect/platform-node-shared": ["@effect/platform-node-shared@4.0.0-beta.98", "", { "dependencies": { "@types/ws": "^8.18.1", "ws": "^8.21.0" }, "peerDependencies": { "effect": "^4.0.0-beta.98" } }, "sha512-iySXaffnCJX1sNAIp79ghhIeui9E5qwUQyqd1VLPkB9UNO4vdpd9B5fTEXwe7S/GusL4jsk9vSvX38XJgRFG1w=="],

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+    "@effect/sql-sqlite-bun": ["@effect/sql-sqlite-bun@4.0.0-beta.98", "", { "peerDependencies": { "effect": "^4.0.0-beta.98" } }, "sha512-cc41uLhYBqexdbTNu4dlui+31E8hcVLEapLySa0C8d60FmBY8IEAV/RD3oF+6pqPslKEZ9p1+XVLdDm0iflw5Q=="],

    "@electron/asar": ["@electron/asar@3.4.1", "", { "dependencies": { "commander": "^5.0.0", "glob": "^7.1.6", "minimatch": "^3.0.4" }, "bin": { "asar": "bin/asar.js" } }, "sha512-i4/rNPRS84t0vSRa2HorerGRXWyF4vThfHesw0dmcWHp+cspK743UanA0suA5Q5y8kzY2y6YKrvbIUn69BCAiA=="],

@@ -1775,6 +1796,12 @@

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+    "@fontsource/noto-sans-math": ["@fontsource/noto-sans-math@5.2.5", "", {}, "sha512-1bxEvVlF51Vfgpju32mRZzI/CHvsfqjXjI2+sAuEyHYvXABUAIyj+93sCO3QZIoMG5drWyrzgoCqRQRaL6wQ8Q=="],
+
+    "@fontsource/noto-sans-symbols": ["@fontsource/noto-sans-symbols@5.2.5", "", {}, "sha512-mxoIRstsmZpZFzd/SRWiD+l6T7TGhpgCrGs7TEnnuGSQIfjVMrQT9Zej2enh9pkfmPNAFyeaGJkHkszJ1hH++w=="],
+
+    "@fontsource/noto-sans-symbols-2": ["@fontsource/noto-sans-symbols-2@5.2.5", "", {}, "sha512-F4O9WLifwoZS1quNzY1ebjMNo2cQPe/UP68Dmud0ONi2lOxaR6xp6fFPO2gG17MI7DwAnfMyQFl64A2tAd28hg=="],
+
    "@fuma-translate/react": ["@fuma-translate/react@1.0.2", "", { "peerDependencies": { "@types/react": "*", "react": "^19.2.0", "react-dom": "^19.2.0" }, "optionalPeers": ["@types/react"] }, "sha512-uOiOtBx3nRXR8Nu1GzBf1tApgF1FErDBTHxRIAQeyQdyOoZbrNRN6H4kDCWObY4qyGeGbHydG0DHzgeUgFDMIw=="],

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@@ -2273,27 +2300,27 @@

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@@ -5963,7 +5992,7 @@

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@@ -8341,6 +8370,26 @@

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+
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+
+    "@standard-community/standard-json/effect/multipasta": ["multipasta@0.2.7", "", {}, "sha512-KPA58d68KgGil15oDqXjkUBEBYc00XvbPj5/X+dyzeo/lWm9Nc25pQRlf1D+gv4OpK7NM0J1odrbu9JNNGvynA=="],
+
+    "@standard-community/standard-json/effect/toml": ["toml@4.1.1", "", {}, "sha512-EBJnVBr3dTXdA89WVFoAIPUqkBjxPMwRqsfuo1r240tKFHXv3zgca4+NJib/h6TyvGF7vOawz0jGuryJCdNHrw=="],
+
+    "@standard-community/standard-json/effect/uuid": ["uuid@14.0.0", "", { "bin": { "uuid": "dist-node/bin/uuid" } }, "sha512-Qo+uWgilfSmAhXCMav1uYFynlQO7fMFiMVZsQqZRMIXp0O7rR7qjkj+cPvBHLgBqi960QCoo/PH2/6ZtVqKvrg=="],
+
+    "@standard-community/standard-openapi/effect/fast-check": ["fast-check@4.8.0", "", { "dependencies": { "pure-rand": "^8.0.0" } }, "sha512-GOJ158CUMnN6cSahsv4+ExARvIDuzzinFjkp0E9WtiBa5zcVeLozVkWaE4IzFcc+Y48Wp1EDlUZsXRyAztQcSg=="],
+
+    "@standard-community/standard-openapi/effect/msgpackr": ["msgpackr@2.0.2", "", { "optionalDependencies": { "msgpackr-extract": "^3.0.4" } }, "sha512-c5hYOXFbP79Slh6Dzd2wzk+jnV7mX1UxfMYtilnY1NmalXPqG8DGb5cYCMBrW4AsH3zekBBZd4QrKz9NhtvYLQ=="],
+
+    "@standard-community/standard-openapi/effect/multipasta": ["multipasta@0.2.7", "", {}, "sha512-KPA58d68KgGil15oDqXjkUBEBYc00XvbPj5/X+dyzeo/lWm9Nc25pQRlf1D+gv4OpK7NM0J1odrbu9JNNGvynA=="],
+
+    "@standard-community/standard-openapi/effect/toml": ["toml@4.1.1", "", {}, "sha512-EBJnVBr3dTXdA89WVFoAIPUqkBjxPMwRqsfuo1r240tKFHXv3zgca4+NJib/h6TyvGF7vOawz0jGuryJCdNHrw=="],
+
+    "@standard-community/standard-openapi/effect/uuid": ["uuid@14.0.0", "", { "bin": { "uuid": "dist-node/bin/uuid" } }, "sha512-Qo+uWgilfSmAhXCMav1uYFynlQO7fMFiMVZsQqZRMIXp0O7rR7qjkj+cPvBHLgBqi960QCoo/PH2/6ZtVqKvrg=="],
+
    "@stoplight/spectral-core/minimatch/brace-expansion": ["brace-expansion@1.1.15", "", { "dependencies": { "balanced-match": "^1.0.0", "concat-map": "0.0.1" } }, "sha512-EwOCDEex4quD37XhqM3omwtMoJjr//isUZz1JopUNWms+4Z2ViyM/k1YIRePpoVNnQhENnxtFjLaxNHrT7xIUg=="],

    "@storybook/addon-docs/react-dom/scheduler": ["scheduler@0.23.2", "", { "dependencies": { "loose-envify": "^1.1.0" } }, "sha512-UOShsPwz7NrMUqhR6t0hWjFduvOzbtv7toDH1/hIrfRNIDBnnBWd0CwJTGvTpngVlmwGCdP9/Zl/tVrDqcuYzQ=="],
@@ -37,18 +37,18 @@
      "packages/slack"
    ],
    "catalog": {
-      "@effect/opentelemetry": "4.0.0-beta.83",
-      "@effect/platform-node": "4.0.0-beta.83",
-      "@effect/sql-sqlite-bun": "4.0.0-beta.83",
+      "@effect/opentelemetry": "4.0.0-beta.98",
+      "@effect/platform-node": "4.0.0-beta.98",
+      "@effect/sql-sqlite-bun": "4.0.0-beta.98",
      "@npmcli/arborist": "9.4.0",
      "@types/bun": "1.3.13",
      "@types/cross-spawn": "6.0.6",
      "@octokit/rest": "22.0.0",
      "@hono/standard-validator": "0.2.0",
      "@hono/zod-validator": "0.4.2",
-      "@opentui/core": "0.4.3",
-      "@opentui/keymap": "0.4.3",
-      "@opentui/solid": "0.4.3",
+      "@opentui/core": "0.4.5",
+      "@opentui/keymap": "0.4.5",
+      "@opentui/solid": "0.4.5",
      "@tanstack/solid-virtual": "3.13.32",
      "@shikijs/stream": "4.2.0",
      "ulid": "3.0.1",
@@ -69,12 +69,13 @@
      "dompurify": "3.3.1",
      "drizzle-kit": "1.0.0-rc.2",
      "drizzle-orm": "1.0.0-rc.2",
-      "effect": "4.0.0-beta.83",
+      "effect": "4.0.0-beta.98",
      "ai": "6.0.168",
      "cross-spawn": "7.0.6",
      "hono": "4.10.7",
      "hono-openapi": "1.1.2",
      "fuzzysort": "3.1.0",
+      "get-east-asian-width": "1.6.0",
      "luxon": "3.6.1",
      "marked": "17.0.6",
      "marked-shiki": "1.2.1",
@@ -85,9 +86,11 @@
      "@typescript/native-preview": "7.0.0-dev.20251207.1",
      "zod": "4.1.8",
      "remeda": "2.26.0",
+      "resolve.exports": "2.0.3",
      "sst": "4.13.1",
      "shiki": "4.2.0",
      "solid-list": "0.3.0",
+      "string-width": "7.2.0",
      "tailwindcss": "4.1.11",
      "vite": "7.1.4",
      "@solidjs/meta": "0.29.4",
@@ -163,7 +166,7 @@
    "@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.83": "patches/effect@4.0.0-beta.83.patch",
+    "effect@4.0.0-beta.98": "patches/effect@4.0.0-beta.98.patch",
    "@tanstack/virtual-core@3.17.3": "patches/@tanstack%2Fvirtual-core@3.17.3.patch"
  }
 }
@@ -1,6 +1,6 @@
 # @opencode-ai/ai

-Schema-first LLM core for opencode. One typed request, response, event, and tool language; provider quirks live in adapters, not in calling code.
+Schema-first AI primitives for opencode. Provider quirks live in adapters, not in calling code.

 ```ts
 import { Effect } from "effect"
@@ -24,6 +24,45 @@ const program = Effect.gen(function* () {

 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 } 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",
+    count: 2,
+    size: { width: 1024, height: 1024 },
+    providerOptions: { openai: { quality: "high", outputFormat: "webp" } },
+  })
+
+  return response.images // GeneratedImage[] with owned bytes or a provider URL
+})
+```
+
+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.
@@ -32,6 +71,8 @@ Run `LLMClient.stream(request)` instead of `generate` when you want incremental
 - **`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

@@ -182,7 +223,7 @@ Adding a new model or deployment is usually 5-15 lines using `Route.make({ proto

 ## Effect

-This package is built on Effect. Public methods return `Effect` or `Stream`; provide `LLMClient.layer` for runtime dispatch and import the provider/protocol modules for the routes you use. The example at `example/tutorial.ts` is a runnable walkthrough.
+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

@@ -1,6 +1,6 @@
 # LLM Provider Parity Status

-Last reviewed: 2026-07-16
+Last reviewed: 2026-07-17

 This file tracks the gap between the native `@opencode-ai/ai` package and the AI SDK provider packages that opencode still depends on for many catalog/runtime paths.

@@ -20,7 +20,7 @@ This file tracks the gap between the native `@opencode-ai/ai` package and the AI
 | OpenAI Responses WebSocket         | `src/protocols/openai-responses.ts`, `src/route/transport/websocket.ts`                        | Present as `OpenAI.responsesWebSocket(...)`.                                                                                                                             | Runner/catalog support explicitly must not downgrade WebSocket routes; broader runtime selection is not complete.                                                                                                                                         |
 | OpenAI-compatible Chat             | `src/protocols/openai-compatible-chat.ts`, `src/providers/openai-compatible.ts`                | Usable for generic Chat and several profiles: Baseten, Cerebras, DeepInfra, DeepSeek, Fireworks, Groq, TogetherAI.                                                       | Family quirks are mostly endpoint defaults, not full typed behavior.                                                                                                                                                                                      |
 | OpenAI-compatible Responses        | `src/protocols/openai-compatible-responses.ts`, `src/providers/openai-compatible-responses.ts` | Usable for deployments that implement the OpenAI Responses wire protocol.                                                                                                | No named family profiles or recorded deployment coverage yet.                                                                                                                                                                                             |
-| Anthropic-compatible Messages      | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts`                 | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base.                                                          | No named compatible family profiles or recorded deployment coverage yet.                                                                                                                                                                                  |
+| Anthropic-compatible Messages      | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic-compatible.ts`                 | Usable for deployments that implement the Anthropic Messages wire protocol. Named Anthropic composes this base; MiniMax M3 has recorded text and tool-loop coverage.       | No named compatible family profiles yet.                                                                                                                                                                                                                  |
 | Anthropic Messages                 | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts`                            | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage.                                                                           | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass.                                                                                                                                     |
 | Gemini Developer API               | `src/protocols/gemini.ts`, `src/providers/google.ts`                                           | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage.                                                                      | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays.                                                                                                                             |
 | Vertex Gemini                      | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts`                                    | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments.               | Core runner/catalog mapping and recorded provider coverage are missing.                                                                                                                                                                                   |
@@ -161,6 +161,18 @@ const PROVIDERS: ReadonlyArray<Provider> = [
    vars: [{ name: "TOGETHER_AI_API_KEY" }],
    validate: (env) => validateBearer("https://api.together.xyz/v1/models", Redacted.make(env.TOGETHER_AI_API_KEY)),
  },
+  {
+    id: "minimax",
+    label: "MiniMax",
+    tier: "compatible",
+    note: "Anthropic-compatible Messages text/tool recorded tests",
+    vars: [{ name: "MINIMAX_API_KEY" }],
+    validate: (env) =>
+      HttpClientRequest.get("https://api.minimax.io/anthropic/v1/models").pipe(
+        HttpClientRequest.setHeader("x-api-key", Redacted.value(Redacted.make(env.MINIMAX_API_KEY))),
+        executeRequest,
+      ),
+  },
  {
    id: "mistral",
    label: "Mistral",
@@ -0,0 +1,34 @@
+import { Context, Effect, Layer } from "effect"
+import { RequestExecutor } from "./route/executor"
+import type { ImageRequest, ImageResponse } from "./image"
+import type { LLMError } from "./schema"
+
+export type Execute = RequestExecutor.Interface["execute"]
+
+export interface Interface {
+  readonly generate: (request: ImageRequest) => Effect.Effect<ImageResponse, LLMError>
+}
+
+export class Service extends Context.Service<Service, Interface>()("@opencode/ImageClient") {}
+
+export const generate = (request: ImageRequest): 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
@@ -0,0 +1,116 @@
+import { Effect, Schema } from "effect"
+import { HttpOptions, InvalidRequestReason, LLMError, ModelID, ProviderID, ProviderMetadata, Usage } from "./schema"
+import { ImageClient, type Execute as ImageExecute } from "./image-client"
+
+export interface ImageRoute {
+  readonly id: string
+  readonly generate: (request: ImageRequest, execute: ImageExecute) => Effect.Effect<ImageResponse, LLMError>
+}
+
+export class ImageModel {
+  readonly id: ModelID
+  readonly provider: ProviderID
+  readonly route: ImageRoute
+  readonly defaults?: ImageModelDefaults
+
+  constructor(input: ImageModel.Input) {
+    this.id = input.id
+    this.provider = input.provider
+    this.route = input.route
+    this.defaults = input.defaults
+  }
+
+  static make(input: ImageModel.MakeInput) {
+    return new ImageModel({
+      id: ModelID.make(input.id),
+      provider: ProviderID.make(input.provider),
+      route: input.route,
+      defaults: input.defaults,
+    })
+  }
+}
+
+export namespace ImageModel {
+  export interface Input {
+    readonly id: ModelID
+    readonly provider: ProviderID
+    readonly route: ImageRoute
+    readonly defaults?: ImageModelDefaults
+  }
+
+  export interface MakeInput extends Omit<Input, "id" | "provider"> {
+    readonly id: string | ModelID
+    readonly provider: string | ProviderID
+  }
+}
+
+export interface ImageModelDefaults {
+  readonly providerOptions?: Record<string, Record<string, unknown>>
+  readonly http?: HttpOptions
+}
+
+export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
+  expected: "Image.Model",
+})
+
+export const ImageSize = Schema.Struct({
+  width: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),
+  height: Schema.Int.check(Schema.isGreaterThanOrEqualTo(1)),
+}).annotate({ identifier: "Image.Size" })
+export type ImageSize = Schema.Schema.Type<typeof ImageSize>
+
+export class ImageRequest extends Schema.Class<ImageRequest>("Image.Request")({
+  model: ImageModelSchema,
+  prompt: Schema.String,
+  count: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),
+  size: Schema.optional(ImageSize),
+  aspectRatio: Schema.optional(Schema.String),
+  seed: Schema.optional(Schema.Number),
+  providerOptions: Schema.optional(Schema.Record(Schema.String, Schema.Record(Schema.String, Schema.Unknown))),
+  http: Schema.optional(HttpOptions),
+  metadata: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
+}) {}
+
+export type ImageRequestInput = Omit<ConstructorParameters<typeof ImageRequest>[0], "http"> & {
+  readonly http?: HttpOptions.Input
+}
+
+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 const request = (input: ImageRequest | ImageRequestInput) => {
+  if (input instanceof ImageRequest) return input
+  return new ImageRequest({
+    ...input,
+    http: input.http === undefined ? undefined : HttpOptions.make(input.http),
+  })
+}
+
+export const generate = (input: ImageRequest | ImageRequestInput) =>
+  Effect.try({
+    try: () => request(input),
+    catch: (error) =>
+      new LLMError({
+        module: "Image",
+        method: "generate",
+        reason: new InvalidRequestReason({ message: error instanceof Error ? error.message : String(error) }),
+      }),
+  }).pipe(Effect.flatMap(ImageClient.generate))
+
+export const Image = {
+  request,
+  generate,
+} as const
@@ -1,4 +1,5 @@
 export { LLMClient } from "./route/client"
+export { ImageClient } from "./image-client"
 export { Auth } from "./route/auth"
 export { Provider } from "./provider"
 export { ProviderPackage } from "./provider-package"
@@ -10,6 +11,9 @@ export type {
  Service as LLMClientService,
 } from "./route/client"
 export * from "./schema"
+export { GeneratedImage, ImageModel, ImageRequest, ImageResponse, ImageSize } from "./image"
+export type { ImageModelDefaults, ImageRequestInput, ImageRoute } from "./image"
+export { Image } from "./image"
 export { Tool, ToolFailure, toDefinitions } from "./tool"
 export { ToolRuntime } from "./tool-runtime"
 export type { DispatchResult as ToolDispatchResult, ToolSettlement } from "./tool-runtime"
@@ -703,7 +703,14 @@ const onContentBlockStart = (state: ParserState, event: AnthropicEvent): StepRes
          providerExecuted: block.type === "server_tool_use",
        }),
      },
-      [...events, LLMEvent.toolInputStart({ id: block.id ?? String(event.index), name: block.name ?? "" })],
+      [
+        ...events,
+        LLMEvent.toolInputStart({
+          id: block.id ?? String(event.index),
+          name: block.name ?? "",
+          providerExecuted: block.type === "server_tool_use" ? true : undefined,
+        }),
+      ],
    ]
  }

@@ -561,7 +561,9 @@ const step = (state: ParserState, event: BedrockEvent) =>
      return [
        {
          ...state,
-          hasToolCalls: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasToolCalls,
+          hasToolCalls:
+            resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
+            state.hasToolCalls,
          lifecycle,
          tools: result.tools,
          reasoningSignatures: Object.fromEntries(
@@ -2,6 +2,7 @@ export * as AnthropicMessages from "./anthropic-messages"
 export * as BedrockConverse from "./bedrock-converse"
 export * as Gemini from "./gemini"
 export * as OpenAIChat from "./openai-chat"
+export * as OpenAIImages from "./openai-images"
 export * as OpenAICompatibleChat from "./openai-compatible-chat"
 export * as OpenAICompatibleResponses from "./openai-compatible-responses"
 export * as OpenAIResponses from "./openai-responses"
@@ -75,6 +75,9 @@ const OpenAIChatMessage = Schema.Union([
    content: Schema.NullOr(Schema.String),
    tool_calls: optionalArray(OpenAIChatAssistantToolCall),
    reasoning_content: Schema.optional(Schema.String),
+    reasoning: Schema.optional(Schema.String),
+    reasoning_text: Schema.optional(Schema.String),
+    reasoning_details: optionalArray(Schema.Unknown),
  }),
  Schema.Struct({ role: Schema.Literal("tool"), tool_call_id: Schema.String, content: Schema.String }),
 ]).pipe(Schema.toTaggedUnion("role"))
@@ -145,6 +148,9 @@ type OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta
 const OpenAIChatDelta = Schema.Struct({
  content: optionalNull(Schema.String),
  reasoning_content: optionalNull(Schema.String),
+  reasoning: optionalNull(Schema.String),
+  reasoning_text: optionalNull(Schema.String),
+  reasoning_details: optionalNull(Schema.Array(Schema.Unknown)),
  tool_calls: optionalNull(Schema.Array(OpenAIChatToolCallDelta)),
 })

@@ -160,12 +166,23 @@ export const OpenAIChatEvent = Schema.Struct({
 export type OpenAIChatEvent = Schema.Schema.Type<typeof OpenAIChatEvent>
 type OpenAIChatRequestMessage = LLMRequest["messages"][number]

+interface PendingToolDelta {
+  readonly id?: string
+  readonly name?: string
+  readonly input: string
+}
+
 export interface ParserState {
  readonly tools: ToolStream.State<number>
+  readonly pendingTools: Partial<Record<number, PendingToolDelta>>
  readonly toolCallEvents: ReadonlyArray<LLMEvent>
  readonly usage?: Usage
  readonly finishReason?: FinishReason
  readonly lifecycle: Lifecycle.State
+  readonly reasoningField?: "reasoning" | "reasoning_content" | "reasoning_text"
+  readonly reasoningDetails: Array<unknown>
+  readonly reasoningDetailsObserved: boolean
+  readonly reasoningEmitted: boolean
 }

 // =============================================================================
@@ -208,6 +225,20 @@ const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart
 const openAICompatibleReasoningContent = (native: unknown) =>
  isRecord(native) && typeof native.reasoning_content === "string" ? native.reasoning_content : undefined

+const reasoningField = (part: ReasoningPart) => {
+  const field = part.providerMetadata?.openai?.reasoningField
+  if (field === "reasoning" || field === "reasoning_content" || field === "reasoning_text") return field
+}
+
+const reasoningDetails = (parts: ReadonlyArray<ReasoningPart>, native: unknown) => {
+  const observed = parts.flatMap((part) => {
+    const details = part.providerMetadata?.openai?.reasoningDetails
+    return Array.isArray(details) ? details : []
+  })
+  if (parts.some((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))) return observed
+  if (isRecord(native) && Array.isArray(native.reasoning_details)) return native.reasoning_details
+}
+
 const lowerUserMessage = Effect.fn("OpenAIChat.lowerUserMessage")(function* (message: OpenAIChatRequestMessage) {
  const content: Array<Schema.Schema.Type<typeof OpenAIChatUserContent>> = []
  for (const part of message.content) {
@@ -248,14 +279,29 @@ const lowerAssistantMessage = Effect.fn("OpenAIChat.lowerAssistantMessage")(func
      continue
    }
  }
+  const text = reasoning.map((part) => part.text).join("")
+  const details = reasoningDetails(reasoning, message.native?.openaiCompatible)
+  const observedField = reasoning.map(reasoningField).find((value) => value !== undefined)
+  const nativeReasoning = openAICompatibleReasoningContent(message.native?.openaiCompatible)
+  const fullyStructured = reasoning.every((part) => Array.isArray(part.providerMetadata?.openai?.reasoningDetails))
+  const field = (() => {
+    if (reasoning.length === 0) return
+    if (observedField !== undefined) return observedField
+    if (nativeReasoning !== undefined) return "reasoning_content"
+    if (!fullyStructured) return "reasoning_content"
+  })()
+  const reasoningContent = (() => {
+    if (reasoning.length === 0) return nativeReasoning
+    if (field === "reasoning_content") return text
+  })()
  return {
    role: "assistant" as const,
    content: content.length === 0 ? null : ProviderShared.joinText(content),
    tool_calls: toolCalls.length === 0 ? undefined : toolCalls,
-    reasoning_content:
-      reasoning.length > 0
-        ? reasoning.map((part) => part.text).join("")
-        : openAICompatibleReasoningContent(message.native?.openaiCompatible),
+    reasoning_content: reasoningContent,
+    reasoning: reasoning.length > 0 && field === "reasoning" ? text : undefined,
+    reasoning_text: reasoning.length > 0 && field === "reasoning_text" ? text : undefined,
+    reasoning_details: details,
  }
 })

@@ -400,6 +446,65 @@ const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
  })
 }

+const reasoningDelta = (delta: Schema.Schema.Type<typeof OpenAIChatDelta> | null | undefined) => {
+  if (delta?.reasoning_content) return { field: "reasoning_content", text: delta.reasoning_content } as const
+  if (delta?.reasoning) return { field: "reasoning", text: delta.reasoning } as const
+  if (delta?.reasoning_text) return { field: "reasoning_text", text: delta.reasoning_text } as const
+}
+
+const detailText = (details: ReadonlyArray<unknown>) => {
+  const text = details.flatMap((detail) => {
+    if (!isRecord(detail)) return []
+    if (detail.type === "reasoning.text" && typeof detail.text === "string" && detail.text) return [detail.text]
+    if (detail.type === "reasoning.summary" && typeof detail.summary === "string" && detail.summary)
+      return [detail.summary]
+    return []
+  })
+  if (text.length > 0) return text.join("")
+}
+
+const appendReasoningDetails = (result: Array<unknown>, details: ReadonlyArray<unknown>) => {
+  for (const detail of details) {
+    const previous = result.at(-1)
+    if (
+      !isRecord(previous) ||
+      previous.type !== "reasoning.text" ||
+      !isRecord(detail) ||
+      detail.type !== "reasoning.text" ||
+      conflictingReasoningTextDetails(previous, detail)
+    ) {
+      result.push(detail)
+      continue
+    }
+    result[result.length - 1] = {
+      ...previous,
+      ...Object.fromEntries(Object.entries(detail).filter((entry) => entry[1] !== undefined)),
+      text: `${typeof previous.text === "string" ? previous.text : ""}${typeof detail.text === "string" ? detail.text : ""}`,
+      signature: mergeDetailValue(previous.signature, detail.signature),
+      format: mergeDetailValue(previous.format, detail.format),
+    }
+  }
+}
+
+const mergeDetailValue = (previous: unknown, current: unknown) =>
+  previous || current || (previous !== undefined ? previous : current)
+
+const conflictingReasoningTextDetails = (previous: Record<string, unknown>, current: Record<string, unknown>) =>
+  conflictingDetailValue(previous.id, current.id) ||
+  conflictingDetailValue(previous.index, current.index) ||
+  conflictingDetailValue(previous.format, current.format) ||
+  (Boolean(previous.signature) && Boolean(current.signature) && previous.signature !== current.signature)
+
+const conflictingDetailValue = (previous: unknown, current: unknown) =>
+  previous !== undefined && previous !== null && current !== undefined && current !== null && previous !== current
+
+const reasoningMetadata = (field: ParserState["reasoningField"], details?: ReadonlyArray<unknown>) => ({
+  openai: {
+    ...(field ? { reasoningField: field } : {}),
+    ...(details ? { reasoningDetails: details } : {}),
+  },
+})
+
 const step = (state: ParserState, event: OpenAIChatEvent) =>
  Effect.gen(function* () {
    const events: LLMEvent[] = []
@@ -409,25 +514,56 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
    const delta = choice?.delta
    const toolDeltas = delta?.tool_calls ?? []
    let tools = state.tools
+    let pendingTools = state.pendingTools

    let lifecycle = state.lifecycle

-    if (delta?.reasoning_content)
-      lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", delta.reasoning_content)
+    const reasoning = reasoningDelta(delta)
+    const reasoningField = state.reasoningField ?? (!state.lifecycle.text.has("text-0") ? reasoning?.field : undefined)
+    const detailDelta = Array.isArray(delta?.reasoning_details) ? delta.reasoning_details : undefined
+    if (detailDelta !== undefined) appendReasoningDetails(state.reasoningDetails, detailDelta)
+    const reasoningDetailsObserved = state.reasoningDetailsObserved || detailDelta !== undefined
+    const deltaMetadata = reasoningMetadata(reasoningField)
+    const text = detailDelta?.length ? (detailText(detailDelta) ?? reasoning?.text) : reasoning?.text
+    if (!state.lifecycle.text.has("text-0") && text !== undefined)
+      lifecycle = Lifecycle.reasoningDelta(lifecycle, events, "reasoning-0", text, deltaMetadata)
+    else if (
+      reasoningDetailsObserved &&
+      !lifecycle.reasoning.has("reasoning-0") &&
+      (Boolean(delta?.content) || toolDeltas.length > 0)
+    )
+      lifecycle = Lifecycle.reasoningStart(lifecycle, events, "reasoning-0", deltaMetadata)
+    const reasoningEmitted = state.reasoningEmitted || lifecycle.reasoning.has("reasoning-0")

    if (delta?.content) {
-      lifecycle = Lifecycle.reasoningEnd(lifecycle, events, "reasoning-0")
+      lifecycle = Lifecycle.reasoningEnd(
+        lifecycle,
+        events,
+        "reasoning-0",
+        reasoningMetadata(reasoningField, reasoningDetailsObserved ? state.reasoningDetails : undefined),
+      )
      lifecycle = Lifecycle.textDelta(lifecycle, events, "text-0", delta.content)
    }

-    if (toolDeltas.length) lifecycle = Lifecycle.reasoningEnd(lifecycle, events, "reasoning-0")
-
    for (const tool of toolDeltas) {
+      const current = tools[tool.index]
+      const pending = pendingTools[tool.index]
+      const id = current?.id ?? pending?.id ?? (tool.id || undefined)
+      const name = current?.name ?? pending?.name ?? (tool.function?.name || undefined)
+      const text = `${pending?.input ?? ""}${tool.function?.arguments ?? ""}`
+      if (!current && (!id || !name)) {
+        pendingTools = { ...pendingTools, [tool.index]: { id: id || undefined, name: name || undefined, input: text } }
+        continue
+      }
+      if (pending) {
+        pendingTools = { ...pendingTools }
+        delete pendingTools[tool.index]
+      }
      const result = ToolStream.appendOrStart(
        ADAPTER,
        tools,
        tool.index,
-        { id: tool.id ?? undefined, name: tool.function?.name ?? undefined, text: tool.function?.arguments ?? "" },
+        { id: id || undefined, name: name || undefined, text },
        "OpenAI Chat tool call delta is missing id or name",
      )
      if (ToolStream.isError(result)) return yield* result
@@ -436,8 +572,11 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
      events.push(...result.events)
    }

+    if (finishReason !== undefined && state.finishReason === undefined && Object.keys(pendingTools).length > 0)
+      return yield* ProviderShared.eventError(ADAPTER, "OpenAI Chat tool call delta is missing id or name")
+
    // Finalize accumulated tool inputs eagerly when finish_reason arrives so
-    // JSON parse failures fail the stream at the boundary rather than at halt.
+    // valid calls and malformed local calls settle independently.
    const finished =
      finishReason !== undefined && state.finishReason === undefined && Object.keys(tools).length > 0
        ? yield* ToolStream.finishAll(ADAPTER, tools)
@@ -446,10 +585,15 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
    return [
      {
        tools: finished?.tools ?? tools,
+        pendingTools,
        toolCallEvents: finished?.events ?? state.toolCallEvents,
        usage,
        finishReason,
        lifecycle,
+        reasoningField,
+        reasoningDetails: state.reasoningDetails,
+        reasoningDetailsObserved,
+        reasoningEmitted,
      },
      events,
    ] as const
@@ -459,7 +603,16 @@ const finishEvents = (state: ParserState): ReadonlyArray<LLMEvent> => {
  const events: LLMEvent[] = []
  const hasToolCalls = state.toolCallEvents.length > 0
  const reason = state.finishReason === "stop" && hasToolCalls ? "tool-calls" : state.finishReason
-  const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(state.lifecycle, events) : state.lifecycle
+  const metadata = reasoningMetadata(
+    state.reasoningField,
+    state.reasoningDetailsObserved ? state.reasoningDetails : undefined,
+  )
+  const started =
+    state.reasoningDetailsObserved && !state.reasoningEmitted
+      ? Lifecycle.reasoningStart(state.lifecycle, events, "reasoning-0", reasoningMetadata(state.reasoningField))
+      : state.lifecycle
+  const ended = Lifecycle.reasoningEnd(started, events, "reasoning-0", metadata)
+  const lifecycle = state.toolCallEvents.length ? Lifecycle.stepStart(ended, events) : ended
  events.push(...state.toolCallEvents)
  if (reason) Lifecycle.finish(lifecycle, events, { reason, usage: state.usage })
  return events
@@ -482,7 +635,16 @@ export const protocol = Protocol.make({
  },
  stream: {
    event: Protocol.jsonEvent(OpenAIChatEvent),
-    initial: () => ({ tools: ToolStream.empty<number>(), toolCallEvents: [], lifecycle: Lifecycle.initial() }),
+    initial: () => ({
+      tools: ToolStream.empty<number>(),
+      pendingTools: {},
+      toolCallEvents: [],
+      lifecycle: Lifecycle.initial(),
+      reasoningField: undefined,
+      reasoningDetails: [],
+      reasoningDetailsObserved: false,
+      reasoningEmitted: false,
+    }),
    step,
    onHalt: finishEvents,
  },
@@ -0,0 +1,208 @@
+import { Effect, Encoding, Schema } from "effect"
+import { Headers, HttpClientRequest } from "effect/unstable/http"
+import {
+  ImageModel,
+  GeneratedImage,
+  ImageResponse,
+  type ImageRequest,
+  type ImageModelDefaults,
+  type ImageRoute,
+} from "../image"
+import { Auth, type Definition as AuthDefinition } from "../route/auth"
+import { InvalidProviderOutputReason, LLMError, Usage, mergeHttpOptions, mergeJsonRecords } from "../schema"
+import { ProviderShared } from "./shared"
+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 interface OpenAIImageOptions {
+  readonly quality?: "auto" | "low" | "medium" | "high"
+  readonly background?: "auto" | "opaque" | "transparent"
+  readonly moderation?: "auto" | "low"
+  readonly outputFormat?: "png" | "jpeg" | "webp"
+  readonly outputCompression?: number
+}
+
+const OpenAIImageBody = Schema.Struct({
+  model: Schema.String,
+  prompt: Schema.String,
+  n: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(1))),
+  size: Schema.optional(Schema.String),
+  quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
+  background: Schema.optional(Schema.Literals(["auto", "opaque", "transparent"])),
+  moderation: Schema.optional(Schema.Literals(["auto", "low"])),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
+  output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),
+})
+export type OpenAIImageBody = Schema.Schema.Type<typeof OpenAIImageBody>
+
+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 defaults?: ImageModelDefaults
+}
+
+const providerOptions = (request: ImageRequest): OpenAIImageOptions => ({
+  ...request.model.defaults?.providerOptions?.openai,
+  ...request.providerOptions?.openai,
+})
+
+const body = (request: ImageRequest): OpenAIImageBody => {
+  const options = providerOptions(request)
+  return {
+    model: request.model.id,
+    prompt: request.prompt,
+    n: request.count,
+    size: request.size === undefined ? undefined : `${request.size.width}x${request.size.height}`,
+    quality: options.quality,
+    background: options.background,
+    moderation: options.moderation,
+    output_format: options.outputFormat,
+    output_compression: options.outputCompression,
+  }
+}
+
+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()
+}
+
+const PROTOCOL_BODY_FIELDS = new Set([
+  "model",
+  "prompt",
+  "n",
+  "size",
+  "quality",
+  "background",
+  "moderation",
+  "output_format",
+  "output_compression",
+])
+
+const bodyWithOverlay = Effect.fn("OpenAIImages.bodyWithOverlay")(function* (
+  imageBody: OpenAIImageBody,
+  overlay: Record<string, unknown> | undefined,
+) {
+  if (!overlay) return imageBody
+  const reserved = Object.keys(overlay).filter((key) => PROTOCOL_BODY_FIELDS.has(key))
+  if (reserved.length > 0)
+    return yield* ProviderShared.invalidRequest(
+      `http.body cannot overlay protocol-owned field(s): ${reserved.join(", ")}`,
+    )
+  return mergeJsonRecords(imageBody, overlay) ?? imageBody
+})
+
+export const model = (input: ModelInput) => {
+  const route: ImageRoute = {
+    id: ADAPTER,
+    generate: Effect.fn("OpenAIImages.generate")(function* (request: ImageRequest, execute) {
+      if (request.aspectRatio !== undefined)
+        return yield* ProviderShared.invalidRequest("OpenAI Images does not support the common aspectRatio option")
+      if (request.seed !== undefined)
+        return yield* ProviderShared.invalidRequest("OpenAI Images does not support the common seed option")
+
+      const requestBody = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenAIImageBody))(body(request))
+      const http = mergeHttpOptions(request.model.defaults?.http, request.http)
+      const overlaidBody = yield* bodyWithOverlay(requestBody, http?.body)
+      const text = ProviderShared.encodeJson(overlaidBody)
+      const url = applyQuery(`${(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 OpenAI Images response")),
+      )
+      const decoded = yield* Schema.decodeUnknownEffect(OpenAIImageResponse)(payload).pipe(
+        Effect.mapError(() => invalidOutput("OpenAI Images returned an invalid response")),
+      )
+      const format = decoded.output_format ?? providerOptions(request).outputFormat ?? "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 } },
+      })
+    }),
+  }
+  return ImageModel.make({ id: input.id, provider: "openai", route, defaults: input.defaults })
+}
+
+export const OpenAIImages = {
+  model,
+} as const
@@ -1,4 +1,4 @@
-import { Effect, Schema } from "effect"
+import { Effect, Encoding, Schema } from "effect"
 import { Route } from "../route/client"
 import { Auth } from "../route/auth"
 import { Endpoint } from "../route/endpoint"
@@ -25,6 +25,7 @@ import { OpenAIOptions } from "./utils/openai-options"
 import { Lifecycle } from "./utils/lifecycle"
 import { ToolSchemaProjection } from "./utils/tool-schema"
 import { ToolStream } from "./utils/tool-stream"
+import { OpenAIImage } from "./utils/openai-image"

 const ADAPTER = "openai-responses"
 export const DEFAULT_BASE_URL = "https://api.openai.com/v1"
@@ -113,11 +114,24 @@ const OpenAIResponsesTool = Schema.Struct({
  parameters: JsonObject,
  strict: Schema.optional(Schema.Boolean),
 })
-type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTool>
+const OpenAIResponsesImageGenerationTool = Schema.Struct({
+  type: Schema.tag("image_generation"),
+  action: Schema.optional(Schema.Literals(["auto", "generate", "edit"])),
+  background: Schema.optional(Schema.Literals(["auto", "opaque", "transparent"])),
+  input_fidelity: Schema.optional(Schema.Literals(["low", "high"])),
+  output_compression: Schema.optional(Schema.Int.check(Schema.isBetween({ minimum: 0, maximum: 100 }))),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
+  partial_images: Schema.optional(Schema.Int.check(Schema.isGreaterThanOrEqualTo(0))),
+  quality: Schema.optional(Schema.Literals(["auto", "low", "medium", "high"])),
+  size: Schema.optional(OpenAIImage.Size),
+})
+const OpenAIResponsesTools = Schema.Union([OpenAIResponsesTool, OpenAIResponsesImageGenerationTool])
+type OpenAIResponsesTool = Schema.Schema.Type<typeof OpenAIResponsesTools>

 const OpenAIResponsesToolChoice = Schema.Union([
  Schema.Literals(["auto", "none", "required"]),
  Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
+  Schema.Struct({ type: Schema.tag("image_generation") }),
 ])

 // Fields shared between the HTTP body and the WebSocket `response.create`
@@ -128,7 +142,7 @@ const OpenAIResponsesCoreFields = {
  model: Schema.String,
  input: Schema.Array(OpenAIResponsesInputItem),
  instructions: Schema.optional(Schema.String),
-  tools: optionalArray(OpenAIResponsesTool),
+  tools: optionalArray(OpenAIResponsesTools),
  tool_choice: Schema.optional(OpenAIResponsesToolChoice),
  store: Schema.optional(Schema.Boolean),
  service_tier: Schema.optional(OpenAIOptions.OpenAIServiceTier),
@@ -194,6 +208,8 @@ const OpenAIResponsesStreamItem = Schema.Struct({
  outputs: Schema.optional(Schema.Unknown),
  server_label: Schema.optional(Schema.String),
  output: Schema.optional(Schema.Unknown),
+  result: Schema.optional(Schema.String),
+  output_format: Schema.optional(Schema.Literals(["png", "jpeg", "webp"])),
  error: Schema.optional(Schema.Unknown),
  encrypted_content: optionalNull(Schema.String),
 })
@@ -258,21 +274,41 @@ const invalid = ProviderShared.invalidRequest
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): OpenAIResponsesTool => ({
-  type: "function",
-  name: tool.name,
-  description: tool.description,
-  parameters: ToolSchemaProjection.openAI(inputSchema),
-  // TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.
-  strict: false,
+const nativeImageToolInput = (tool: ToolDefinition) => {
+  const native = tool.native?.openai
+  return ProviderShared.isRecord(native) && native.type === "image_generation" ? native : undefined
+}
+
+const nativeImageTool = (tool: ToolDefinition) => {
+  const native = nativeImageToolInput(tool)
+  return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
+}
+
+const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition, inputSchema: JsonSchema) {
+  const native = nativeImageToolInput(tool)
+  if (native !== undefined) {
+    if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
+    return yield* invalid("OpenAI Responses image generation tool options are invalid")
+  }
+  return {
+    type: "function" as const,
+    name: tool.name,
+    description: tool.description,
+    parameters: ToolSchemaProjection.openAI(inputSchema),
+    // TODO: Read this from OpenAI-specific tool options so direct LLM callers can opt into strict schemas.
+    strict: false,
+  }
 })

-const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
+const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tools: ReadonlyArray<ToolDefinition>) =>
  ProviderShared.matchToolChoice("OpenAI Responses", toolChoice, {
    auto: () => "auto" as const,
    none: () => "none" as const,
    required: () => "required" as const,
-    tool: (name) => ({ type: "function" as const, name }),
+    tool: (name) =>
+      tools.some((tool) => tool.name === name && nativeImageTool(tool) !== undefined)
+        ? ({ type: "image_generation" } as const)
+        : { type: "function" as const, name },
  })

 const lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({
@@ -420,6 +456,13 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
          const itemID = hostedToolItemID(part)
          if (store !== false && itemID && !hostedToolReferences.has(itemID))
            input.push({ type: "item_reference", id: itemID })
+          if (store === false && part.name === "image_generation" && part.result.type === "content") {
+            const content: ReadonlyArray<ToolContent> = part.result.value
+            input.push({
+              role: "user",
+              content: yield* Effect.forEach(content, lowerToolResultContentItem),
+            })
+          }
          if (itemID) hostedToolReferences.add(itemID)
          continue
        }
@@ -485,10 +528,10 @@ const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request:
    tools:
      request.tools.length === 0
        ? undefined
-        : request.tools.map((tool) =>
+        : yield* Effect.forEach(request.tools, (tool) =>
            lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, toolSchemaCompatibility)),
          ),
-    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
+    tool_choice: request.toolChoice ? yield* lowerToolChoice(request.toolChoice, request.tools) : undefined,
    stream: true as const,
    max_output_tokens: generation?.maxTokens,
    temperature: generation?.temperature,
@@ -574,14 +617,29 @@ const isReasoningItem = (

 // Round-trip the full item as the structured result so consumers can extract
 // outputs / sources / status without re-decoding.
-const hostedToolResult = (item: OpenAIResponsesStreamItem) => {
+const hostedToolResult = Effect.fn("OpenAIResponses.hostedToolResult")(function* (item: OpenAIResponsesStreamItem) {
  const isError = typeof item.error !== "undefined" && item.error !== null
+  if (item.type === "image_generation_call" && item.result) {
+    yield* Effect.fromResult(Encoding.decodeBase64(item.result)).pipe(
+      Effect.mapError(() => ProviderShared.eventError(ADAPTER, "OpenAI Responses returned invalid image base64")),
+    )
+    return {
+      type: "content" as const,
+      value: [
+        {
+          type: "file" as const,
+          uri: `data:image/${item.output_format ?? "png"};base64,${item.result}`,
+          mime: `image/${item.output_format ?? "png"}`,
+        },
+      ],
+    }
+  }
  return isError ? { type: "error" as const, value: item.error } : { type: "json" as const, value: item }
-}
+})

-const hostedToolEvents = (
+const hostedToolEvents = Effect.fn("OpenAIResponses.hostedToolEvents")(function* (
  item: OpenAIResponsesStreamItem & { type: HostedToolType; id: string },
-): ReadonlyArray<LLMEvent> => {
+) {
  const tool = HOSTED_TOOLS[item.type]
  const providerMetadata = openaiMetadata({ itemId: item.id })
  return [
@@ -595,12 +653,12 @@ const hostedToolEvents = (
    LLMEvent.toolResult({
      id: item.id,
      name: tool.name,
-      result: hostedToolResult(item),
+      result: yield* hostedToolResult(item),
      providerExecuted: true,
      providerMetadata,
    }),
  ]
-}
+})

 type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]

@@ -835,7 +893,9 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
      {
        ...state,
        lifecycle,
-        hasFunctionCall: resultEvents.some(LLMEvent.is.toolCall) ? true : state.hasFunctionCall,
+        hasFunctionCall:
+          resultEvents.some((event) => LLMEvent.is.toolCall(event) || LLMEvent.is.toolInputError(event)) ||
+          state.hasFunctionCall,
        tools: result.tools,
      },
      events,
@@ -845,7 +905,7 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
  if (isHostedToolItem(item)) {
    const events: LLMEvent[] = []
    const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
-    events.push(...hostedToolEvents(item))
+    events.push(...(yield* hostedToolEvents(item)))
    return [{ ...state, lifecycle }, events] satisfies StepResult
  }

@@ -44,7 +44,7 @@ export const reasoningDelta = (
  providerMetadata?: ProviderMetadata,
 ): State => {
  const started = reasoningStart(state, events, id, providerMetadata)
-  events.push(LLMEvent.reasoningDelta({ id, text }))
+  events.push(LLMEvent.reasoningDelta({ id, text, providerMetadata }))
  return started
 }

@@ -0,0 +1,20 @@
+import { Schema } from "effect"
+
+const dimensions = (value: string) => {
+  const match = /^(\d+)x(\d+)$/.exec(value)
+  if (!match) return undefined
+  return { width: Number(match[1]), height: Number(match[2]) }
+}
+
+export const Size = Schema.String.check(
+  Schema.makeFilter((value) => {
+    if (value === "auto") return undefined
+    const parsed = dimensions(value)
+    if (!parsed) return "image size must be `auto` or `{width}x{height}`"
+    return parsed.width > 0 && parsed.height > 0 ? undefined : "image dimensions must be positive integers"
+  }),
+)
+
+export const OpenAIImage = {
+  Size,
+} as const
@@ -1,5 +1,5 @@
 import { Effect } from "effect"
-import { LLMError, LLMEvent, type ProviderMetadata, type ToolCall } from "../../schema"
+import { LLMError, LLMEvent, type ProviderMetadata, type ToolCall, type ToolInputError } from "../../schema"
 import { eventError, parseToolInput, type ToolAccumulator } from "../shared"

 type StreamKey = string | number
@@ -53,6 +53,7 @@ const inputStart = (tool: PendingTool) =>
  LLMEvent.toolInputStart({
    id: tool.id,
    name: tool.name,
+    providerExecuted: tool.providerExecuted ? true : undefined,
    providerMetadata: tool.providerMetadata,
  })

@@ -63,19 +64,36 @@ const inputDelta = (tool: PendingTool, text: string) =>
    text,
  })

-const toolCall = (route: string, tool: PendingTool, inputOverride?: string) =>
-  parseToolInput(route, tool.name, inputOverride ?? tool.input).pipe(
-    Effect.map(
-      (input): ToolCall =>
-        LLMEvent.toolCall({
-          id: tool.id,
-          name: tool.name,
-          input,
-          providerExecuted: tool.providerExecuted ? true : undefined,
-          providerMetadata: tool.providerMetadata,
-        }),
+const toolCall = (route: string, tool: PendingTool, inputOverride?: string) => {
+  const raw = inputOverride ?? tool.input
+  return parseToolInput(route, tool.name, raw).pipe(
+    Effect.map((input): ToolCall | ToolInputError =>
+      LLMEvent.toolCall({
+        id: tool.id,
+        name: tool.name,
+        input,
+        providerExecuted: tool.providerExecuted ? true : undefined,
+        providerMetadata: tool.providerMetadata,
+      }),
+    ),
+    Effect.catch((error) =>
+      tool.providerExecuted
+        ? Effect.fail(error)
+        : Effect.succeed(
+            LLMEvent.toolInputError({
+              id: tool.id,
+              name: tool.name,
+              raw,
+            }),
+          ),
    ),
  )
+}
+
+const finishEvents = (tool: PendingTool, event: ToolCall | ToolInputError): ReadonlyArray<LLMEvent> =>
+  event.type === "tool-input-error"
+    ? [event]
+    : [LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }), event]

 /** Store the updated tool and produce the optional public delta event. */
 const appendTool = <K extends StreamKey>(
@@ -122,8 +140,8 @@ export const appendOrStart = <K extends StreamKey>(
  missingToolMessage: string,
 ): AppendOutcome<K> | LLMError => {
  const current = tools[key]
-  const id = delta.id ?? current?.id
-  const name = delta.name ?? current?.name
+  const id = current?.id ?? delta.id
+  const name = current?.name ?? delta.name
  if (!id || !name) return eventError(route, missingToolMessage)

  const tool = {
@@ -158,8 +176,9 @@ export const appendExisting = <K extends StreamKey>(

 /**
 * Finalize one pending tool call: parse the accumulated raw JSON, remove it
- * from state, and return the optional public `tool-call` event. Missing keys are
- * a no-op because some providers emit stop events for non-tool content blocks.
+ * from state, and return either a call or a non-executable local input error.
+ * Missing keys are a no-op because some providers emit stop events for
+ * non-tool content blocks.
 */
 export const finish = <K extends StreamKey>(route: string, tools: State<K>, key: K) =>
  Effect.gen(function* () {
@@ -167,10 +186,7 @@ export const finish = <K extends StreamKey>(route: string, tools: State<K>, key:
    if (!tool) return { tools }
    return {
      tools: withoutTool(tools, key),
-      events: [
-        LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-        yield* toolCall(route, tool),
-      ],
+      events: finishEvents(tool, yield* toolCall(route, tool)),
    }
  })

@@ -185,17 +201,14 @@ export const finishWithInput = <K extends StreamKey>(route: string, tools: State
    if (!tool) return { tools }
    return {
      tools: withoutTool(tools, key),
-      events: [
-        LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-        yield* toolCall(route, tool, input),
-      ],
+      events: finishEvents(tool, yield* toolCall(route, tool, input)),
    }
  })

 /**
 * Finalize every pending tool call at once. OpenAI Chat has this shape: it does
- * not emit per-tool stop events, so all accumulated calls finish when the choice
- * receives a terminal `finish_reason`.
+ * not emit per-tool stop events, so all accumulated calls finish independently
+ * when the choice receives a terminal `finish_reason`.
 */
 export const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =>
  Effect.gen(function* () {
@@ -205,12 +218,7 @@ export const finishAll = <K extends StreamKey>(route: string, tools: State<K>) =
    return {
      tools: empty<K>(),
      events: yield* Effect.forEach(pending, (tool) =>
-        toolCall(route, tool).pipe(
-          Effect.map((call) => [
-            LLMEvent.toolInputEnd({ id: tool.id, name: tool.name, providerMetadata: tool.providerMetadata }),
-            call,
-          ]),
-        ),
+        toolCall(route, tool).pipe(Effect.map((event) => finishEvents(tool, event))),
      ).pipe(Effect.map((events) => events.flat())),
    }
  })
@@ -16,13 +16,17 @@ import {

 const patterns = [
  /prompt is too long/i,
+  /request_too_large/i,
  /input is too long for requested model/i,
  /exceeds the context window/i,
+  /exceeds (?:the )?(?:model'?s )?maximum context length(?: of [\d,]+ tokens?|\s*\([\d,]+\))/i,
  /input token count.*exceeds the maximum/i,
  /tokens in request more than max tokens allowed/i,
  /maximum prompt length is \d+/i,
  /reduce the length of the messages/i,
  /maximum context length is \d+ tokens/i,
+  /exceeds (?:the )?maximum allowed input length of [\d,]+ tokens?/i,
+  /input \(\d+ tokens\) is longer than the model'?s context length \(\d+ tokens\)/i,
  /exceeds the limit of \d+/i,
  /exceeds the available context size/i,
  /greater than the context length/i,
@@ -34,11 +38,17 @@ const patterns = [
  /input length.*exceeds.*context length/i,
  /prompt too long; exceeded (?:max )?context length/i,
  /too large for model with \d+ maximum context length/i,
+  /prompt has [\d,]+ tokens?, but the configured context size is [\d,]+ tokens?/i,
  /model_context_window_exceeded/i,
+  /too many tokens/i,
+  /token limit exceeded/i,
 ]

+const exclusions = [/^(throttling error|service unavailable):/i, /rate limit/i, /too many requests/i]
+
 export const isContextOverflow = (message: string) =>
-  patterns.some((pattern) => pattern.test(message)) || /^4(00|13)\s*(status code)?\s*\(no body\)/i.test(message)
+  !exclusions.some((pattern) => pattern.test(message)) &&
+  (patterns.some((pattern) => pattern.test(message)) || /^4(00|13)\s*(status code)?\s*\(no body\)/i.test(message))

 export const isContextOverflowFailure = (failure: unknown) =>
  failure instanceof LLMError
@@ -1,12 +1,14 @@
 import { AuthOptions, type ProviderAuthOption } from "../route/auth-options"
 import type { Route, RouteDefaultsInput } from "../route/client"
 import type { ProviderPackage } from "../provider-package"
-import { ProviderID, type ModelID } from "../schema"
+import { HttpOptions, ProviderID, ToolDefinition, mergeHttpOptions, type ModelID } from "../schema"
 import * as OpenAIChat from "../protocols/openai-chat"
 import * as OpenAIResponses from "../protocols/openai-responses"
 import { withOpenAIOptions, type OpenAIProviderOptionsInput } from "./openai-options"
+import { OpenAIImages, type OpenAIImageOptions } from "../protocols/openai-images"

 export type { OpenAIOptionsInput, OpenAIResponseIncludable } from "./openai-options"
+export type { OpenAIImageOptions } from "../protocols/openai-images"

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

@@ -20,8 +22,44 @@ export type Config = RouteDefaultsInput &
    readonly baseURL?: string
    readonly queryParams?: Record<string, string>
    readonly providerOptions?: OpenAIProviderOptionsInput
+    readonly image?: ImageConfig
  }

+export interface ImageConfig {
+  readonly providerOptions?: OpenAIImageOptions
+}
+
+export interface ImageGenerationOptions {
+  readonly action?: "auto" | "generate" | "edit"
+  readonly background?: "auto" | "opaque" | "transparent"
+  readonly inputFidelity?: "low" | "high"
+  readonly outputCompression?: number
+  readonly outputFormat?: "png" | "jpeg" | "webp"
+  readonly partialImages?: number
+  readonly quality?: "auto" | "low" | "medium" | "high"
+  readonly size?: string
+}
+
+export const imageGeneration = (options: ImageGenerationOptions = {}) =>
+  ToolDefinition.make({
+    name: "image_generation",
+    description: "Generate or edit an image using OpenAI's hosted image generation tool.",
+    inputSchema: { type: "object", properties: {}, additionalProperties: false },
+    native: {
+      openai: {
+        type: "image_generation",
+        action: options.action,
+        background: options.background,
+        input_fidelity: options.inputFidelity,
+        output_compression: options.outputCompression,
+        output_format: options.outputFormat,
+        partial_images: options.partialImages,
+        quality: options.quality,
+        size: options.size,
+      },
+    },
+  })
+
 export interface Settings extends ProviderPackage.Settings {
  readonly apiKey?: string
  readonly baseURL?: string
@@ -35,7 +73,7 @@ export interface Settings extends ProviderPackage.Settings {
 const auth = (options: ProviderAuthOption<"optional">) => AuthOptions.bearer(options, "OPENAI_API_KEY")

 const defaults = (input: Config) => {
-  const { apiKey: _, auth: _auth, baseURL: _baseURL, queryParams: _queryParams, ...rest } = input
+  const { apiKey: _, auth: _auth, baseURL: _baseURL, queryParams: _queryParams, image: _image, ...rest } = input
  return rest
 }

@@ -55,6 +93,21 @@ export const configure = (input: Config = {}) => {
  const responsesWebSocket = (id: string | ModelID) =>
    responsesWebSocketRoute.with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true })).model({ id })
  const chat = (id: string | ModelID) => chatRoute.with(withOpenAIOptions(id, modelDefaults)).model({ id })
+  const image = (modelID: string | ModelID) =>
+    OpenAIImages.model({
+      id: modelID,
+      auth: auth(input),
+      baseURL: input.baseURL,
+      headers: input.headers,
+      defaults: {
+        providerOptions:
+          input.image?.providerOptions === undefined ? undefined : { openai: { ...input.image.providerOptions } },
+        http: mergeHttpOptions(
+          input.http === undefined ? undefined : HttpOptions.make(input.http),
+          input.queryParams === undefined ? undefined : new HttpOptions({ query: input.queryParams }),
+        ),
+      },
+    })

  return {
    id,
@@ -62,6 +115,7 @@ export const configure = (input: Config = {}) => {
    responses,
    responsesWebSocket,
    chat,
+    image,
    configure,
  }
 }
@@ -97,3 +151,4 @@ export const chatModel: ProviderPackage.Definition<Settings>["model"] = (modelID
 export const responses = provider.responses
 export const responsesWebSocket = provider.responsesWebSocket
 export const chat = provider.chat
+export const image = provider.image
@@ -41,13 +41,31 @@ export const protocol = Protocol.make({
    schema: OpenRouterBody,
    from: (request) =>
      OpenAIChat.protocol.body.from(request).pipe(
-        Effect.map(
-          (body) =>
-            ({
-              ...body,
-              ...bodyOptions(request.providerOptions?.openrouter),
-            }) as OpenRouterBody,
-        ),
+        Effect.map((body) => {
+          const sourceAssistants = request.messages.filter((message) => message.role === "assistant")
+          let assistantIndex = 0
+          const messages = body.messages.map((message) => {
+            if (message.role !== "assistant") return message
+            const source = sourceAssistants[assistantIndex++]
+            const reasoning = source?.content
+              .filter((part) => part.type === "reasoning")
+              .map((part) => part.text)
+              .join("")
+            const reasoningDetails = Array.isArray(message.reasoning_details) ? message.reasoning_details : undefined
+            return {
+              ...message,
+              reasoning_content: undefined,
+              reasoning_text: undefined,
+              reasoning: reasoning && reasoningDetails && reasoningDetails.length > 0 ? reasoning : undefined,
+              reasoning_details: reasoningDetails,
+            }
+          })
+          return {
+            ...body,
+            messages,
+            ...bodyOptions(request.providerOptions?.openrouter),
+          } as OpenRouterBody
+        }),
      ),
  },
  stream: OpenAIChat.protocol.stream,
@@ -1,6 +1,6 @@
 import { Config, Effect, Redacted } from "effect"
 import { Headers } from "effect/unstable/http"
-import { AuthenticationReason, InvalidRequestReason, LLMError, type LLMRequest } from "../schema"
+import { AuthenticationReason, InvalidRequestReason, LLMError, type HttpOptions } from "../schema"

 export class MissingCredentialError extends Error {
  readonly _tag = "MissingCredentialError"
@@ -15,7 +15,7 @@ export type AuthError = CredentialError | LLMError
 type Secret = string | Redacted.Redacted | Config.Config<string | Redacted.Redacted>

 export interface AuthInput {
-  readonly request: LLMRequest
+  readonly request: { readonly http?: HttpOptions }
  readonly method: "POST" | "GET"
  readonly url: string
  readonly body: string
@@ -129,6 +129,7 @@ export const ToolInputStart = Schema.Struct({
  type: Schema.tag("tool-input-start"),
  id: ToolCallID,
  name: Schema.String,
+  providerExecuted: Schema.optional(Schema.Boolean),
  providerMetadata: Schema.optional(ProviderMetadata),
 }).annotate({ identifier: "LLM.Event.ToolInputStart" })
 export type ToolInputStart = Schema.Schema.Type<typeof ToolInputStart>
@@ -149,6 +150,15 @@ export const ToolInputEnd = Schema.Struct({
 }).annotate({ identifier: "LLM.Event.ToolInputEnd" })
 export type ToolInputEnd = Schema.Schema.Type<typeof ToolInputEnd>

+/** A local tool call whose final input could not be decoded. */
+export const ToolInputError = Schema.Struct({
+  type: Schema.tag("tool-input-error"),
+  id: ToolCallID,
+  name: Schema.String,
+  raw: Schema.String,
+}).annotate({ identifier: "LLM.Event.ToolInputError" })
+export type ToolInputError = Schema.Schema.Type<typeof ToolInputError>
+
 export const ToolCall = Schema.Struct({
  type: Schema.tag("tool-call"),
  id: ToolCallID,
@@ -216,6 +226,7 @@ const llmEventTagged = Schema.Union([
  ToolInputStart,
  ToolInputDelta,
  ToolInputEnd,
+  ToolInputError,
  ToolCall,
  ToolResult,
  ToolError,
@@ -253,6 +264,8 @@ export const LLMEvent = Object.assign(llmEventTagged, {
  toolInputDelta: (input: WithID<ToolInputDelta, ToolCallID>) =>
    ToolInputDelta.make({ ...input, id: toolCallID(input.id) }),
  toolInputEnd: (input: WithID<ToolInputEnd, ToolCallID>) => ToolInputEnd.make({ ...input, id: toolCallID(input.id) }),
+  toolInputError: (input: WithID<ToolInputError, ToolCallID>) =>
+    ToolInputError.make({ ...input, id: toolCallID(input.id) }),
  toolCall: (input: WithID<ToolCall, ToolCallID>) => ToolCall.make({ ...input, id: toolCallID(input.id) }),
  toolResult: (input: WithID<ToolResult, ToolCallID>) =>
    ToolResult.make({
@@ -283,6 +296,7 @@ export const LLMEvent = Object.assign(llmEventTagged, {
    toolInputStart: llmEventTagged.guards["tool-input-start"],
    toolInputDelta: llmEventTagged.guards["tool-input-delta"],
    toolInputEnd: llmEventTagged.guards["tool-input-end"],
+    toolInputError: llmEventTagged.guards["tool-input-error"],
    toolCall: llmEventTagged.guards["tool-call"],
    toolResult: llmEventTagged.guards["tool-result"],
    toolError: llmEventTagged.guards["tool-error"],
@@ -548,6 +562,10 @@ const reduceResponseState = (state: ResponseState, event: LLMEvent): ResponseSta
      return reduceToolInputDelta(next, event)
    case "tool-input-end":
      return reduceToolInputEnd(next, event)
+    case "tool-input-error": {
+      const { [event.id]: _finished, ...toolInputs } = next.toolInputs
+      return { ...next, toolInputs }
+    }
    case "tool-call":
      return reduceToolCall(next, event)
    case "tool-result":
@@ -0,0 +1,40 @@
+{
+  "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"
+      }
+    }
+  ]
+}
@@ -0,0 +1,41 @@
+{
+  "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"
+      }
+    }
+  ]
+}
@@ -0,0 +1,60 @@
+{
+  "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"
+      }
+    }
+  ]
+}
@@ -0,0 +1,34 @@
+{
+  "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"
+      }
+    }
+  ]
+}
@@ -0,0 +1,95 @@
+import { describe, expect } from "bun:test"
+import { Effect, Layer } from "effect"
+import { HttpClientRequest } from "effect/unstable/http"
+import { Image, ImageClient } from "../src"
+import { OpenAI } 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",
+        count: 2,
+        size: { width: 1024, height: 1024 },
+        providerOptions: {
+          openai: { quality: "high", outputFormat: "webp" },
+        },
+        http: {
+          body: { 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: "1024x1024",
+                  quality: "high",
+                  output_format: "webp",
+                  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("rejects invalid common and OpenAI image options locally", () =>
+    Image.generate({
+      model: OpenAI.configure({ apiKey: "test", baseURL: "https://api.openai.test/v1" }).image("gpt-image-2"),
+      prompt: "A robot tending a rooftop garden",
+      count: -1,
+      size: { width: -1, height: 0.5 },
+      providerOptions: { openai: { outputCompression: 101 } },
+    }).pipe(
+      Effect.flip,
+      Effect.tap((error) =>
+        Effect.sync(() => {
+          expect(error.reason._tag).toBe("InvalidRequest")
+        }),
+      ),
+      Effect.provide(
+        ImageClient.layer.pipe(
+          Layer.provide(dynamicResponse(() => Effect.die("invalid request should not reach the provider"))),
+        ),
+      ),
+    ),
+  )
+})
@@ -3,8 +3,30 @@ import { isContextOverflow } from "../src"
 import { classifyProviderFailure } from "../src/provider-error"

 describe("provider error classification", () => {
-  test("classifies Z.AI GLM token limit messages as context overflow", () => {
-    expect(isContextOverflow("tokens in request more than max tokens allowed")).toBe(true)
+  test("classifies provider token limit messages as context overflow", () => {
+    const messages = [
+      "tokens in request more than max tokens allowed",
+      '{"error":{"type":"request_too_large","message":"Request exceeds the maximum size"}}',
+      "Requested token count exceeds the model's maximum context length of 131072 tokens.",
+      "Input length (265330) exceeds model's maximum context length (262144).",
+      "Input length 131393 exceeds the maximum allowed input length of 131040 tokens.",
+      "The input (516368 tokens) is longer than the model's context length (262144 tokens).",
+      "Prompt has 5,958,968 tokens, but the configured context size is 256,000 tokens",
+      "Too many tokens",
+      "Token limit exceeded",
+    ]
+
+    expect(messages.every(isContextOverflow)).toBe(true)
+  })
+
+  test("does not classify rate limits as context overflow", () => {
+    const messages = [
+      "Throttling error: Too many tokens, please wait before trying again.",
+      "Rate limit exceeded, please retry after 30 seconds.",
+      "Too many requests. Please slow down.",
+    ]
+
+    expect(messages.some(isContextOverflow)).toBe(false)
  })

  test("classifies V1 plain-text rate limit fallbacks", () => {
@@ -484,6 +484,30 @@ describe("Anthropic Messages route", () => {
    }),
  )

+  it.effect("keeps malformed server tool input terminal", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        { type: "message_start", message: { usage: { input_tokens: 5 } } },
+        {
+          type: "content_block_start",
+          index: 0,
+          content_block: { type: "server_tool_use", id: "call_1", name: "web_search" },
+        },
+        {
+          type: "content_block_delta",
+          index: 0,
+          delta: { type: "input_json_delta", partial_json: '{"query":"partial' },
+        },
+        { type: "content_block_stop", index: 0 },
+      )
+
+      const error = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
+
+      expect(error).toBeInstanceOf(LLMError)
+      expect(error.message).toContain("Invalid JSON input for anthropic-messages tool call web_search")
+    }),
+  )
+
  it.effect("fails with a typed provider error for stream error frames", () =>
    Effect.gen(function* () {
      const error = yield* LLMClient.generate(request).pipe(
@@ -303,6 +303,32 @@ describe("Bedrock Converse route", () => {
    }),
  )

+  it.effect("emits malformed tool input as an unexecuted tool error", () =>
+    Effect.gen(function* () {
+      const body = eventStreamBody(
+        ["messageStart", { role: "assistant" }],
+        [
+          "contentBlockStart",
+          {
+            contentBlockIndex: 0,
+            start: { toolUse: { toolUseId: "tool_1", name: "lookup" } },
+          },
+        ],
+        ["contentBlockDelta", { contentBlockIndex: 0, delta: { toolUse: { input: '{"query":"partial' } } }],
+        ["contentBlockStop", { contentBlockIndex: 0 }],
+        ["messageStop", { stopReason: "end_turn" }],
+      )
+      const response = yield* LLMClient.generate(baseRequest).pipe(Effect.provide(fixedBytes(body)))
+
+      expect(response.events.find((event) => event.type === "tool-input-error")).toMatchObject({
+        id: "tool_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+      })
+      expect(response.finishReason).toBe("tool-calls")
+    }),
+  )
+
  it.effect("decodes reasoning deltas", () =>
    Effect.gen(function* () {
      const body = eventStreamBody(
@@ -1,7 +1,7 @@
 import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect, Schema } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { LLM } from "../../src"
+import { LLM, LLMEvent } from "../../src"
 import { CloudflareAIGateway, CloudflareWorkersAI } from "../../src/providers/cloudflare"
 import { LLMClient } from "../../src/route"
 import { it } from "../lib/effect"
@@ -83,6 +83,59 @@ describe("Cloudflare", () => {
    }),
  )

+  it.effect("preserves reasoning details for AI Gateway continuation", () =>
+    Effect.gen(function* () {
+      const model = CloudflareAIGateway.configure({
+        accountId: "test-account",
+        gatewayId: "test-gateway",
+        apiKey: "test-token",
+      }).model("anthropic/claude-sonnet-4.6")
+      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 },
+      ]
+      const merged = [
+        {
+          type: "reasoning.text",
+          text: "Thinking",
+          signature: "signed",
+          format: "anthropic-claude-v1",
+          index: 0,
+        },
+      ]
+      const response = yield* LLM.generate(LLM.request({ model, prompt: "Say hello." })).pipe(
+        Effect.provide(
+          dynamicResponse((input) =>
+            Effect.succeed(
+              input.respond(
+                sseEvents(
+                  deltaChunk({ reasoning: "Think", reasoning_details: [details[0]] }),
+                  deltaChunk({ reasoning: "ing", reasoning_details: [details[1]] }),
+                  deltaChunk({ reasoning_details: [details[2]] }),
+                  deltaChunk({ content: "Hello" }),
+                  deltaChunk({}, "stop"),
+                ),
+                { headers: { "content-type": "text/event-stream" } },
+              ),
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("Thinking")
+      expect(response.events.filter(LLMEvent.is.reasoningDelta)).toHaveLength(2)
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningField: "reasoning", reasoningDetails: merged },
+      })
+
+      const replay = yield* LLMClient.prepare(LLM.request({ model, messages: [response.message] }))
+      expect(replay.body.messages).toEqual([
+        { role: "assistant", content: "Hello", reasoning: "Thinking", reasoning_details: merged },
+      ])
+    }),
+  )
+
  it.effect("defaults AI Gateway id to default when omitted or blank", () =>
    Effect.gen(function* () {
      expect(
@@ -1,4 +1,5 @@
 import * as Anthropic from "../../src/providers/anthropic"
+import * as AnthropicCompatible from "../../src/providers/anthropic-compatible"
 import { CloudflareAIGateway, CloudflareWorkersAI } from "../../src/providers/cloudflare"
 import * as Google from "../../src/providers/google"
 import * as OpenAI from "../../src/providers/openai"
@@ -17,6 +18,11 @@ const anthropic = Anthropic.configure({
 })
 const anthropicHaiku = anthropic.model("claude-haiku-4-5-20251001")
 const anthropicOpus = anthropic.model("claude-opus-4-7")
+const minimax = AnthropicCompatible.configure({
+  apiKey: process.env.MINIMAX_API_KEY ?? "fixture",
+  baseURL: "https://api.minimax.io/anthropic/v1",
+  provider: "minimax",
+}).model("MiniMax-M3")
 const google = Google.configure({ apiKey: process.env.GOOGLE_GENERATIVE_AI_API_KEY ?? "fixture" })
 const gemini = google.model("gemini-2.5-flash")
 const xai = XAI.configure({ apiKey: process.env.XAI_API_KEY ?? "fixture" })
@@ -108,6 +114,15 @@ describeRecordedGoldenScenarios([
      { id: "image-tool-result", temperature: false, maxTokens: 40 },
    ],
  },
+  {
+    name: "MiniMax M3 Anthropic-compatible",
+    prefix: "anthropic-compatible-messages",
+    protocol: "anthropic-messages",
+    model: minimax,
+    requires: ["MINIMAX_API_KEY"],
+    options: { redact: { allowRequestHeaders: ["anthropic-version"] } },
+    scenarios: ["text", "tool-call", "tool-loop"],
+  },
  {
    name: "Gemini 2.5 Flash",
    prefix: "gemini",
@@ -0,0 +1,142 @@
+import { describe, expect } from "bun:test"
+import { Effect } from "effect"
+import { LLM, LLMEvent, LLMResponse } 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: OpenRouter.configure({
+      apiKey: process.env.OPENROUTER_API_KEY ?? "fixture",
+      providerOptions: { openrouter: { reasoning: { max_tokens: 1024 } } },
+    }).model("anthropic/claude-sonnet-4.6"),
+    requires: ["OPENROUTER_API_KEY"],
+    cassette: "openrouter-reasoning",
+    structured: true,
+  },
+  {
+    name: "Vercel AI Gateway",
+    model: 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"),
+    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,
+    )
+  })
+}
@@ -540,28 +540,401 @@ describe("OpenAI Chat route", () => {
    }),
  )

-  it.effect("parses OpenAI-compatible reasoning content deltas", () =>
+  it.effect("parses and replays OpenAI-compatible reasoning fields", () =>
    Effect.gen(function* () {
-      const body = sseEvents(
-        { choices: [{ delta: { reasoning_content: "thinking" } }] },
-        { choices: [{ delta: { content: "Hello" } }] },
-        { choices: [{ delta: {}, finish_reason: "stop" }] },
+      const fields = ["reasoning_content", "reasoning", "reasoning_text"] as const
+      for (const field of fields) {
+        const response = yield* LLMClient.generate(request).pipe(
+          Effect.provide(
+            fixedResponse(
+              sseEvents(
+                { choices: [{ delta: { [field]: "thinking" } }] },
+                { choices: [{ delta: { content: "Hello" } }] },
+                { choices: [{ delta: {}, finish_reason: "stop" }] },
+              ),
+            ),
+          ),
+        )
+
+        expect(response.reasoning).toBe("thinking")
+        expect(response.text).toBe("Hello")
+        expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+          openai: { reasoningField: field },
+        })
+
+        const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+          LLM.request({ model, messages: [response.message] }),
+        )
+        expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", [field]: "thinking" }])
+      }
+    }),
+  )
+
+  it.effect("preserves and replays reasoning details alongside scalar reasoning", () =>
+    Effect.gen(function* () {
+      const details = [
+        { type: "reasoning.text", text: "thinking", format: "anthropic-claude-v1", index: 0 },
+        { type: "reasoning.encrypted", data: "opaque", format: "anthropic-claude-v1", index: 1 },
+      ]
+      const response = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning: "thinking", reasoning_details: [details[0]] } }] },
+              { choices: [{ delta: { reasoning_details: [details[1]] } }] },
+              {
+                choices: [
+                  {
+                    delta: {
+                      tool_calls: [
+                        { index: 0, id: "call_1", function: { name: "lookup", arguments: '{"query":"weather"}' } },
+                      ],
+                    },
+                    finish_reason: "tool_calls",
+                  },
+                ],
+              },
+            ),
+          ),
+        ),
      )

-      const response = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)))
+      expect(response.reasoning).toBe("thinking")
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningField: "reasoning", reasoningDetails: details },
+      })
+
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({ model, messages: [response.message] }),
+      )
+      expect(replay.body.messages).toEqual([
+        {
+          role: "assistant",
+          content: null,
+          reasoning: "thinking",
+          reasoning_details: details,
+          tool_calls: [
+            {
+              id: "call_1",
+              type: "function",
+              function: { name: "lookup", arguments: '{"query":"weather"}' },
+            },
+          ],
+        },
+      ])
+    }),
+  )
+
+  it.effect("uses reasoning details as display fallback without inventing a scalar replay field", () =>
+    Effect.gen(function* () {
+      const details = [
+        { type: "reasoning.summary", summary: "thinking", format: "openai-responses-v1", index: 0 },
+        { type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 1 },
+      ]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning_details: [details[0]] } }] },
+              { choices: [{ delta: { reasoning_details: [details[1]] } }] },
+              { choices: [{ delta: { content: "Hello" } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )

      expect(response.reasoning).toBe("thinking")
-      expect(response.text).toBe("Hello")
-      expect(response.events).toMatchObject([
-        { type: "step-start", index: 0 },
-        { type: "reasoning-start", id: "reasoning-0" },
-        { type: "reasoning-delta", id: "reasoning-0", text: "thinking" },
-        { type: "reasoning-end", id: "reasoning-0" },
-        { type: "text-start", id: "text-0" },
-        { type: "text-delta", id: "text-0", text: "Hello" },
-        { type: "text-end", id: "text-0" },
-        { type: "step-finish", index: 0, reason: "stop" },
-        { type: "finish", reason: "stop" },
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningDetails: details },
+      })
+
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({ model, messages: [response.message] }),
+      )
+      expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", reasoning_details: details }])
+    }),
+  )
+
+  it.effect("preserves unknown reasoning details while using scalar display text", () =>
+    Effect.gen(function* () {
+      const details = [{ type: "reasoning.future", format: "provider-v2", state: { opaque: true } }]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning: "thinking", reasoning_details: details } }] },
+              { choices: [{ delta: { content: "Hello" } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("thinking")
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningField: "reasoning", reasoningDetails: details },
+      })
+
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({ model, messages: [response.message] }),
+      )
+      expect(replay.body.messages).toEqual([
+        { role: "assistant", content: "Hello", reasoning: "thinking", reasoning_details: details },
+      ])
+    }),
+  )
+
+  it.effect("uses scalar display text for signature-only reasoning details", () =>
+    Effect.gen(function* () {
+      const details = [{ type: "reasoning.text", signature: "signed", format: "provider-v2", index: 0 }]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning: "thinking", reasoning_details: details } }] },
+              { choices: [{ delta: { content: "Hello" } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("thinking")
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningField: "reasoning", reasoningDetails: details },
+      })
+    }),
+  )
+
+  it.effect("ignores scalar reasoning after content starts", () =>
+    Effect.gen(function* () {
+      const details = [{ type: "reasoning.text", text: "detail", format: "unknown", index: 0 }]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning_details: details } }] },
+              { choices: [{ delta: { content: "Hello" } }] },
+              { choices: [{ delta: { reasoning: "scalar" } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("detail")
+      expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
+      expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningDetails: details },
+      })
+    }),
+  )
+
+  it.effect("preserves an explicitly empty reasoning details array", () =>
+    Effect.gen(function* () {
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning_details: [] } }] },
+              { choices: [{ delta: { content: "Hello" } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("")
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningDetails: [] },
+      })
+
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({ model, messages: [response.message] }),
+      )
+      expect(replay.body.messages).toEqual([{ role: "assistant", content: "Hello", reasoning_details: [] }])
+    }),
+  )
+
+  it.effect("attaches signature-only details that arrive after content", () =>
+    Effect.gen(function* () {
+      const details = [
+        { type: "reasoning.text", text: "thinking", format: "anthropic-claude-v1", index: 0 },
+        { type: "reasoning.text", signature: "signed", format: "anthropic-claude-v1", index: 0 },
+      ]
+      const merged = [
+        {
+          type: "reasoning.text",
+          text: "thinking",
+          signature: "signed",
+          format: "anthropic-claude-v1",
+          index: 0,
+        },
+      ]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning: "thinking", reasoning_details: [details[0]] } }] },
+              { choices: [{ delta: { content: "Hello" } }] },
+              { choices: [{ delta: { reasoning_details: [details[1]] } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("thinking")
+      expect(response.message.content.filter((part) => part.type === "reasoning")).toHaveLength(1)
+      expect(response.message.content.find((part) => part.type === "reasoning")?.providerMetadata).toEqual({
+        openai: { reasoningField: "reasoning", reasoningDetails: merged },
+      })
+      expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
+      expect(response.events.filter(LLMEvent.is.reasoningDelta)).toHaveLength(1)
+      expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
+      expect(response.events.filter(LLMEvent.is.reasoningEnd).at(-1)?.providerMetadata).toEqual({
+        openai: { reasoningField: "reasoning", reasoningDetails: merged },
+      })
+      expect(response.events.findIndex(LLMEvent.is.reasoningEnd)).toBeLessThan(
+        response.events.findIndex(LLMEvent.is.textStart),
+      )
+
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({ model, messages: [response.message] }),
+      )
+      expect(replay.body.messages).toEqual([
+        { role: "assistant", content: "Hello", reasoning: "thinking", reasoning_details: merged },
+      ])
+    }),
+  )
+
+  it.effect("preserves metadata-only reasoning when the stream ends", () =>
+    Effect.gen(function* () {
+      const details = [{ type: "reasoning.encrypted", data: "opaque", format: "openai-responses-v1", index: 0 }]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning_details: details } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.message.content).toEqual([
+        { type: "reasoning", text: "", providerMetadata: { openai: { reasoningDetails: details } } },
+      ])
+      expect(response.events.filter(LLMEvent.is.reasoningStart)).toHaveLength(1)
+      expect(response.events.filter(LLMEvent.is.reasoningEnd)).toHaveLength(1)
+
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({ model, messages: [response.message] }),
+      )
+      expect(replay.body.messages).toEqual([{ role: "assistant", content: null, reasoning_details: details }])
+    }),
+  )
+
+  it.effect("flushes details-only display reasoning when the stream ends", () =>
+    Effect.gen(function* () {
+      const details = [{ type: "reasoning.summary", summary: "summary", format: "openai-responses-v1", index: 0 }]
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { choices: [{ delta: { reasoning_details: details } }] },
+              { choices: [{ delta: {}, finish_reason: "stop" }] },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.reasoning).toBe("summary")
+      expect(response.message.content).toEqual([
+        { type: "reasoning", text: "summary", providerMetadata: { openai: { reasoningDetails: details } } },
+      ])
+    }),
+  )
+
+  it.effect("replays details from multiple reasoning parts in order", () =>
+    Effect.gen(function* () {
+      const first = { type: "reasoning.text", text: "first", signature: "signed-0", index: 0 }
+      const second = { type: "reasoning.text", text: "second", signature: "signed-1", index: 1 }
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({
+          model,
+          messages: [
+            Message.assistant([
+              {
+                type: "reasoning",
+                text: "first",
+                providerMetadata: { openai: { reasoningDetails: [first] } },
+              },
+              {
+                type: "reasoning",
+                text: "second",
+                providerMetadata: { openai: { reasoningField: "reasoning", reasoningDetails: [second] } },
+              },
+            ]),
+          ],
+        }),
+      )
+
+      expect(replay.body.messages).toEqual([
+        { role: "assistant", content: null, reasoning: "firstsecond", reasoning_details: [first, second] },
+      ])
+    }),
+  )
+
+  it.effect("retains scalar replay for mixed structured reasoning parts", () =>
+    Effect.gen(function* () {
+      const detail = { type: "reasoning.encrypted", data: "opaque", index: 0 }
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({
+          model,
+          messages: [
+            Message.assistant([
+              {
+                type: "reasoning",
+                text: "A",
+                providerMetadata: { openai: { reasoningDetails: [detail] } },
+              },
+              { type: "reasoning", text: "B" },
+            ]),
+          ],
+        }),
+      )
+
+      expect(replay.body.messages).toEqual([
+        { role: "assistant", content: null, reasoning_content: "AB", reasoning_details: [detail] },
+      ])
+    }),
+  )
+
+  it.effect("replays native scalar reasoning alongside native details", () =>
+    Effect.gen(function* () {
+      const details = [{ type: "reasoning.encrypted", data: "opaque", index: 0 }]
+      const replay = yield* LLMClient.prepare<OpenAIChat.OpenAIChatBody>(
+        LLM.request({
+          model,
+          messages: [
+            Message.make({
+              role: "assistant",
+              content: [{ type: "reasoning", text: "thinking" }],
+              native: { openaiCompatible: { reasoning_content: "thinking", reasoning_details: details } },
+            }),
+          ],
+        }),
+      )
+
+      expect(replay.body.messages).toEqual([
+        { role: "assistant", content: null, reasoning_content: "thinking", reasoning_details: details },
      ])
    }),
  )
@@ -602,6 +975,67 @@ describe("OpenAI Chat route", () => {
    }),
  )

+  it.effect("ignores empty identity fields on later tool call deltas", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        deltaChunk({
+          tool_calls: [{ index: 0, id: "call_1", function: { name: "lookup", arguments: "{" } }],
+        }),
+        deltaChunk({
+          tool_calls: [{ index: 0, id: "", function: { name: "", arguments: '\"query\":\"weather\"}' } }],
+        }),
+        deltaChunk({}, "tool_calls"),
+      )
+      const response = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.toolCalls).toMatchObject([{ id: "call_1", name: "lookup", input: { query: "weather" } }])
+    }),
+  )
+
+  it.effect("buffers tool call deltas until the function name arrives", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        deltaChunk({
+          tool_calls: [{ index: 0, id: "call_1", function: { arguments: "{" } }],
+        }),
+        deltaChunk({
+          tool_calls: [{ index: 0, function: { name: "lookup", arguments: '\"query\":' } }],
+        }),
+        deltaChunk({ tool_calls: [{ index: 0, function: { arguments: '\"weather\"}' } }] }),
+        deltaChunk({}, "tool_calls"),
+      )
+      const response = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.toolCalls).toMatchObject([{ id: "call_1", name: "lookup", input: { query: "weather" } }])
+    }),
+  )
+
+  it.effect("fails when a buffered tool call never receives a function name", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        deltaChunk({
+          tool_calls: [{ index: 0, id: "call_1", function: { arguments: "{}" } }],
+        }),
+        deltaChunk({}, "tool_calls"),
+      )
+      const error = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(Effect.provide(fixedResponse(body)), Effect.flip)
+
+      expect(error.message).toContain("OpenAI Chat tool call delta is missing id or name")
+    }),
+  )
+
  it.effect("fails a streamed tool call when the provider ends without a finish reason", () =>
    Effect.gen(function* () {
      const body = sseEvents(
@@ -0,0 +1,40 @@
+import { describe, expect } from "bun:test"
+import { Effect } from "effect"
+import { Image } from "../../src"
+import { OpenAI } from "../../src/providers"
+import { recordedTests } from "../recorded-test"
+
+const model = OpenAI.configure({
+  apiKey: process.env.OPENAI_API_KEY ?? "fixture",
+  image: {
+    providerOptions: {
+      quality: "low",
+      outputFormat: "jpeg",
+      outputCompression: 10,
+    },
+  },
+}).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.",
+        size: { width: 1024, height: 1024 },
+      })
+
+      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)
+    }),
+  )
+})
@@ -0,0 +1,66 @@
+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")
+    }),
+  )
+})
@@ -1,7 +1,7 @@
 import { describe, expect } from "bun:test"
 import { ConfigProvider, Effect, Layer, Stream } from "effect"
 import { Headers, HttpClientRequest } from "effect/unstable/http"
-import { LLM, LLMError, Message, Model, ToolCallPart, Usage } from "../../src"
+import { LLM, LLMError, LLMEvent, Message, Model, ToolCallPart, ToolResultPart, Usage } from "../../src"
 import { Auth, LLMClient, RequestExecutor, WebSocketExecutor } from "../../src/route"
 import * as Azure from "../../src/providers/azure"
 import * as OpenAI from "../../src/providers/openai"
@@ -58,6 +58,39 @@ describe("OpenAI Responses route", () => {
    }),
  )

+  it.effect("lowers the hosted OpenAI image generation tool", () =>
+    Effect.gen(function* () {
+      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
+        LLM.request({
+          model,
+          prompt: "Show me a rooftop garden.",
+          tools: [OpenAI.imageGeneration({ action: "generate", quality: "high", size: "1024x1024" })],
+          toolChoice: "image_generation",
+        }),
+      )
+
+      expect(prepared.body.tools).toEqual([
+        { type: "image_generation", action: "generate", quality: "high", size: "1024x1024" },
+      ])
+      expect(prepared.body.tool_choice).toEqual({ type: "image_generation" })
+    }),
+  )
+
+  it.effect("rejects invalid hosted image generation options locally", () =>
+    Effect.gen(function* () {
+      const error = yield* LLMClient.prepare(
+        LLM.request({
+          model,
+          prompt: "Show me a rooftop garden.",
+          tools: [OpenAI.imageGeneration({ outputCompression: -1, partialImages: 4, size: "bogus" })],
+        }),
+      ).pipe(Effect.flip)
+
+      expect(error.reason._tag).toBe("InvalidRequest")
+      expect(error.message).toContain("image generation tool options are invalid")
+    }),
+  )
+
  it.effect("lowers semantic service tier options", () =>
    Effect.gen(function* () {
      const input = LLM.updateRequest(request, { providerOptions: { openai: { serviceTier: "priority" } } })
@@ -1103,6 +1136,48 @@ describe("OpenAI Responses route", () => {
    }),
  )

+  it.effect("continues stateless hosted image generation with the generated image", () =>
+    Effect.gen(function* () {
+      const imageTool = OpenAI.imageGeneration({ action: "edit" })
+      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
+        LLM.request({
+          model,
+          messages: [
+            Message.user("Generate a black triangle."),
+            Message.assistant([
+              ToolCallPart.make({
+                id: "ig_1",
+                name: "image_generation",
+                input: {},
+                providerExecuted: true,
+                providerMetadata: { openai: { itemId: "ig_1" } },
+              }),
+              ToolResultPart.make({
+                id: "ig_1",
+                name: "image_generation",
+                result: {
+                  type: "content",
+                  value: [{ type: "file", uri: "data:image/png;base64,AQID", mime: "image/png" }],
+                },
+                providerExecuted: true,
+                providerMetadata: { openai: { itemId: "ig_1" } },
+              }),
+            ]),
+            Message.user("Make it blue."),
+          ],
+          tools: [imageTool],
+        }),
+      )
+
+      expect(prepared.body.store).toBe(false)
+      expect(prepared.body.input).toEqual([
+        { role: "user", content: [{ type: "input_text", text: "Generate a black triangle." }] },
+        { role: "user", content: [{ type: "input_image", image_url: "data:image/png;base64,AQID" }] },
+        { role: "user", content: [{ type: "input_text", text: "Make it blue." }] },
+      ])
+    }),
+  )
+
  it.effect("joins streamed summary blocks into one continuation reasoning item", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
@@ -1259,6 +1334,69 @@ describe("OpenAI Responses route", () => {
    }),
  )

+  it.effect("emits malformed final function arguments as an unexecuted tool error", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        {
+          type: "response.output_item.added",
+          item: { type: "function_call", id: "item_1", call_id: "call_1", name: "lookup", arguments: "" },
+        },
+        { type: "response.function_call_arguments.delta", item_id: "item_1", delta: '{"query":"streamed"}' },
+        {
+          type: "response.output_item.done",
+          item: {
+            type: "function_call",
+            id: "item_1",
+            call_id: "call_1",
+            name: "lookup",
+            arguments: '{"query":"partial',
+          },
+        },
+        { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
+      )
+      const response = yield* LLMClient.generate(
+        LLM.updateRequest(request, {
+          tools: [{ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } }],
+        }),
+      ).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.events.find(LLMEvent.is.toolInputError)).toEqual({
+        type: "tool-input-error",
+        id: "call_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+      })
+      expect(response.finishReason).toBe("tool-calls")
+      expect(response.events.some(LLMEvent.is.toolCall)).toBeFalse()
+    }),
+  )
+
+  it.effect("settles malformed function arguments when output_item.added is absent", () =>
+    Effect.gen(function* () {
+      const body = sseEvents(
+        {
+          type: "response.output_item.done",
+          item: {
+            type: "function_call",
+            id: "item_1",
+            call_id: "call_1",
+            name: "lookup",
+            arguments: '{"query":"partial',
+          },
+        },
+        { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
+      )
+      const response = yield* LLMClient.generate(request).pipe(Effect.provide(fixedResponse(body)))
+
+      expect(response.events.find(LLMEvent.is.toolInputError)).toMatchObject({
+        id: "call_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+      })
+      expect(response.finishReason).toBe("tool-calls")
+    }),
+  )
+
  it.effect("decodes web_search_call as provider-executed tool-call + tool-result", () =>
    Effect.gen(function* () {
      const item = {
@@ -1298,6 +1436,59 @@ describe("OpenAI Responses route", () => {
    }),
  )

+  it.effect("decodes image generation output as image content", () =>
+    Effect.gen(function* () {
+      const item = {
+        type: "image_generation_call",
+        id: "ig_1",
+        status: "completed",
+        result: "AQID",
+      }
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { type: "response.output_item.done", item },
+              { type: "response.completed", response: { usage: { input_tokens: 5, output_tokens: 1 } } },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.events.find(LLMEvent.is.toolResult)).toMatchObject({
+        id: "ig_1",
+        name: "image_generation",
+        providerExecuted: true,
+        result: {
+          type: "content",
+          value: [{ type: "file", uri: "data:image/png;base64,AQID", mime: "image/png" }],
+        },
+      })
+    }),
+  )
+
+  it.effect("rejects malformed image generation base64", () =>
+    Effect.gen(function* () {
+      const error = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              {
+                type: "response.output_item.done",
+                item: { type: "image_generation_call", id: "ig_bad", status: "completed", result: "%%%" },
+              },
+              { type: "response.completed", response: {} },
+            ),
+          ),
+        ),
+        Effect.flip,
+      )
+
+      expect(error.reason._tag).toBe("InvalidProviderOutput")
+      expect(error.message).toContain("invalid image base64")
+    }),
+  )
+
  it.effect("decodes code_interpreter_call as provider-executed events with code input", () =>
    Effect.gen(function* () {
      const item = {
@@ -1,6 +1,6 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
-import { LLM } from "../../src"
+import { LLM, Message } from "../../src"
 import { LLMClient } from "../../src/route"
 import * as OpenRouter from "../../src/providers/openrouter"
 import { it } from "../lib/effect"
@@ -53,4 +53,102 @@ describe("OpenRouter", () => {
      })
    }),
  )
+
+  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 }])
+    }),
+  )
 })
@@ -120,29 +120,8 @@ export const runWeatherToolLoop = (request: LLMRequest) =>
    throw new Error("Weather tool loop exceeded 10 steps")
  })

-const assistantContent = (events: ReadonlyArray<LLMEvent>) => {
-  const content: ContentPart[] = []
-  for (const event of events) {
-    if (event.type === "text-delta" || event.type === "reasoning-delta") {
-      const type = event.type === "text-delta" ? "text" : "reasoning"
-      const last = content.at(-1)
-      if (last?.type === type) {
-        content[content.length - 1] = { ...last, text: `${last.text}${event.text}` }
-      } else {
-        content.push({ type, text: event.text })
-      }
-      continue
-    }
-    if (event.type === "text-end" || event.type === "reasoning-end") {
-      const type = event.type === "text-end" ? "text" : "reasoning"
-      const last = content.at(-1)
-      if (last?.type === type) content[content.length - 1] = { ...last, providerMetadata: event.providerMetadata }
-      continue
-    }
-    if (event.type === "tool-call") content.push(event)
-  }
-  return content
-}
+const assistantContent = (events: ReadonlyArray<LLMEvent>) =>
+  events.reduce(LLMResponse.reduce, LLMResponse.empty()).message.content

 export const expectFinish = (
  events: ReadonlyArray<LLMEvent>,
@@ -3,6 +3,8 @@ import { Layer } from "effect"
 import * as path from "node:path"
 import { fileURLToPath } from "node:url"
 import { LLMClient, RequestExecutor, WebSocketExecutor } from "../src/route"
+import { ImageClient } from "../src/image-client"
+import type { Service as ImageClientService } from "../src/image-client"
 import type { Service as LLMClientService } from "../src/route/client"
 import type { Service as RequestExecutorService } from "../src/route/executor"
 import type { Service as WebSocketExecutorService } from "../src/route/transport/websocket"
@@ -15,7 +17,7 @@ import {
 const __dirname = path.dirname(fileURLToPath(import.meta.url))
 const FIXTURES_DIR = path.resolve(__dirname, "fixtures", "recordings")

-type RecordedEnv = RequestExecutorService | WebSocketExecutorService | LLMClientService
+type RecordedEnv = RequestExecutorService | WebSocketExecutorService | LLMClientService | ImageClientService

 type RecordedTestsOptions = RecordedGroupOptions & {
  readonly options?: HttpRecorder.RecorderOptions
@@ -81,6 +83,10 @@ export const recordedTests = (options: RecordedTestsOptions) =>
        ),
      )
      const deps = Layer.mergeAll(requestExecutor, WebSocketExecutor.layer)
-      return Layer.mergeAll(deps, LLMClient.layer.pipe(Layer.provide(deps)))
+      return Layer.mergeAll(
+        deps,
+        LLMClient.layer.pipe(Layer.provide(deps)),
+        ImageClient.layer.pipe(Layer.provide(deps)),
+      )
    },
  })
@@ -95,4 +95,19 @@ describe("LLMResponse reducer", () => {
      { type: "tool-call", id: "call_1", name: "lookup", input: { query: "weather" } },
    ])
  })
+
+  test("clears malformed tool input without appending an executable call", () => {
+    const state = reduce([
+      LLMEvent.toolInputStart({ id: "call_1", name: "lookup" }),
+      LLMEvent.toolInputDelta({ id: "call_1", name: "lookup", text: '{"query":"partial' }),
+      LLMEvent.toolInputError({
+        id: "call_1",
+        name: "lookup",
+        raw: '{"query":"partial',
+      }),
+    ])
+
+    expect(state.toolInputs).toEqual({})
+    expect(state.message.content).toEqual([])
+  })
 })
@@ -36,6 +36,33 @@ describe("ToolStream", () => {
    }),
  )

+  it.effect("keeps accumulated identity when later deltas contain empty strings", () =>
+    Effect.gen(function* () {
+      const first = ToolStream.appendOrStart(
+        ADAPTER,
+        ToolStream.empty<number>(),
+        0,
+        { id: "call_1", name: "lookup", text: '{"query"' },
+        "missing tool",
+      )
+      if (ToolStream.isError(first)) return yield* first
+      const second = ToolStream.appendOrStart(
+        ADAPTER,
+        first.tools,
+        0,
+        { id: "", name: "", text: ':"weather"}' },
+        "missing tool",
+      )
+      if (ToolStream.isError(second)) return yield* second
+      const finished = yield* ToolStream.finish(ADAPTER, second.tools, 0)
+
+      expect(finished.events).toEqual([
+        { type: "tool-input-end", id: "call_1", name: "lookup" },
+        { type: "tool-call", id: "call_1", name: "lookup", input: { query: "weather" } },
+      ])
+    }),
+  )
+
  it.effect("fails appendExisting when the provider skipped the tool start", () =>
    Effect.gen(function* () {
      const error = ToolStream.appendExisting(ADAPTER, ToolStream.empty<number>(), 0, "{}", "missing tool")
@@ -64,6 +91,73 @@ describe("ToolStream", () => {
    }),
  )

+  it.effect("finalizes malformed local input as a non-executable tool error", () =>
+    Effect.gen(function* () {
+      const tools = ToolStream.start(ToolStream.empty<string>(), "item_1", {
+        id: "call_1",
+        name: "lookup",
+        input: '{"query":"partial',
+      })
+      const finished = yield* ToolStream.finish(ADAPTER, tools, "item_1")
+
+      expect(finished).toEqual({
+        tools: {},
+        events: [
+          {
+            type: "tool-input-error",
+            id: "call_1",
+            name: "lookup",
+            raw: '{"query":"partial',
+          },
+        ],
+      })
+    }),
+  )
+
+  it.effect("preserves valid siblings when one parallel input is malformed", () =>
+    Effect.gen(function* () {
+      const valid = ToolStream.start(ToolStream.empty<number>(), 0, {
+        id: "call_valid",
+        name: "lookup",
+        input: '{"query":"weather"}',
+      })
+      const tools = ToolStream.start(valid, 1, {
+        id: "call_invalid",
+        name: "lookup",
+        input: '{"query":"partial',
+      })
+      const finished = yield* ToolStream.finishAll(ADAPTER, tools)
+
+      expect(finished).toEqual({
+        tools: {},
+        events: [
+          { type: "tool-input-end", id: "call_valid", name: "lookup" },
+          { type: "tool-call", id: "call_valid", name: "lookup", input: { query: "weather" } },
+          {
+            type: "tool-input-error",
+            id: "call_invalid",
+            name: "lookup",
+            raw: '{"query":"partial',
+          },
+        ],
+      })
+    }),
+  )
+
+  it.effect("keeps malformed provider-executed input terminal", () =>
+    Effect.gen(function* () {
+      const tools = ToolStream.start(ToolStream.empty<string>(), "item_1", {
+        id: "call_1",
+        name: "web_search",
+        input: '{"query":"partial',
+        providerExecuted: true,
+      })
+      const result = yield* Effect.exit(ToolStream.finish(ADAPTER, tools, "item_1"))
+
+      expect(result._tag).toBe("Failure")
+    }),
+  )
+
  it.effect("preserves providerExecuted and clears all tools", () =>
    Effect.gen(function* () {
      const first: ToolStream.State<number> = ToolStream.start(ToolStream.empty<number>(), 0, {
@@ -1615,6 +1615,7 @@ export const PromptInput: Component<PromptInputProps> = (props) => {
          <div class="flex flex-col gap-3">
            <DockShellForm
              data-component={newSession() ? "session-new-composer" : "session-composer"}
+              data-background-surface="prompt"
              onSubmit={handleSubmit}
              classList={{
                "group/prompt-input min-h-[96px] w-full rounded-xl bg-v2-background-bg-base shadow-[var(--v2-elevation-raised)]": true,
@@ -446,6 +446,7 @@ export function PromptProjectAddButton(props: { controller: PromptProjectControl
  return (
    <button
      data-action="prompt-project"
+      data-background-surface="project-selector"
      type="button"
      class="flex h-7 min-w-0 max-w-[160px] items-center gap-1.5 rounded-sm px-2 text-[13px] font-[440] leading-5 tracking-[-0.04px] text-v2-text-text-faint transition-colors hover:bg-v2-overlay-simple-overlay-hover focus-visible:bg-v2-overlay-simple-overlay-hover focus-visible:outline-none"
      onClick={() => props.controller.add()}
@@ -464,6 +465,7 @@ function ProjectTrigger(props: ComponentProps<"button"> & { controller: PromptPr
    <button
      {...rest}
      data-action="prompt-project"
+      data-background-surface="project-selector"
      type="button"
      class="flex h-7 min-w-0 max-w-[203px] items-center gap-1.5 rounded-sm px-1.5 transition-colors focus-visible:bg-v2-overlay-simple-overlay-hover focus-visible:outline-none"
      classList={{
@@ -4,10 +4,14 @@ import { NEW_SESSION_CONTENT_WIDTH } from "@/pages/session/new-session-layout"

 export function NewSessionDesignView(props: { children: JSX.Element }) {
  return (
-    <div data-component="session-new-design" class="relative size-full overflow-hidden bg-v2-background-bg-deep ">
+    <div
+      data-component="session-new-design"
+      data-background-surface="shell"
+      class="relative size-full overflow-hidden bg-v2-background-bg-deep "
+    >
      <div class="absolute inset-x-0 top-[25.375%] flex justify-center px-6">
        <div class={NEW_SESSION_CONTENT_WIDTH}>
-          <WordmarkV2 class="h-auto w-full text-v2-background-bg-inverse" />
+          <WordmarkV2 class="h-auto w-full text-v2-background-bg-inverse [&>g>g>g]:!opacity-[0.45]" />
          <div class="mt-8">{props.children}</div>
        </div>
      </div>
@@ -0,0 +1,36 @@
+import { createStore } from "solid-js/store"
+import { useLanguage } from "@/context/language"
+import { usePlatform } from "@/context/platform"
+import { showToast } from "@/utils/toast"
+
+export function useSettingsBackgroundImage() {
+  const platform = usePlatform()
+  const language = useLanguage()
+  const [state, setState] = createStore({ busy: false })
+
+  const run = async (action: (() => Promise<unknown>) | undefined) => {
+    if (!action || state.busy) return
+    setState("busy", true)
+    try {
+      await action()
+    } catch (error) {
+      showToast({
+        variant: "error",
+        title: language.t("common.requestFailed"),
+        description: error instanceof Error ? error.message : String(error),
+      })
+    } finally {
+      setState("busy", false)
+    }
+  }
+
+  return {
+    available: !!platform.selectBackgroundImage,
+    active: () => platform.backgroundImage?.() ?? false,
+    get busy() {
+      return state.busy
+    },
+    select: () => run(platform.selectBackgroundImage),
+    clear: () => run(platform.clearBackgroundImage),
+  }
+}
@@ -31,6 +31,7 @@ import { decode64 } from "@/utils/base64"
 import { playSoundById, SOUND_OPTIONS } from "@/utils/sound"
 import { Link } from "./link"
 import { SettingsList } from "./settings-list"
+import { useSettingsBackgroundImage } from "./settings-background-image"

 let demoSoundState = {
  cleanup: undefined as (() => void) | undefined,
@@ -87,6 +88,7 @@ export const SettingsGeneral: Component = () => {
  const language = useLanguage()
  const permission = usePermission()
  const platform = usePlatform()
+  const backgroundImage = useSettingsBackgroundImage()
  const dialog = useDialog()
  const params = useParams()
  const settings = useSettings()
@@ -499,6 +501,24 @@ export const SettingsGeneral: Component = () => {
          />
        </SettingsRow>

+        <Show when={backgroundImage.available}>
+          <SettingsRow
+            title={language.t("settings.general.row.backgroundImage.title")}
+            description={language.t("settings.general.row.backgroundImage.description")}
+          >
+            <div class="flex items-center gap-2">
+              <Button size="small" variant="secondary" disabled={backgroundImage.busy} onClick={backgroundImage.select}>
+                {language.t("settings.general.row.backgroundImage.choose")}
+              </Button>
+              <Show when={backgroundImage.active()}>
+                <Button size="small" variant="ghost" disabled={backgroundImage.busy} onClick={backgroundImage.clear}>
+                  {language.t("settings.general.row.backgroundImage.remove")}
+                </Button>
+              </Show>
+            </div>
+          </SettingsRow>
+        </Show>
+
        <SettingsRow
          title={language.t("settings.general.row.uiFont.title")}
          description={language.t("settings.general.row.uiFont.description")}
@@ -29,6 +29,7 @@ import { Link } from "../link"
 import { SettingsListV2 } from "./parts/list"
 import { SettingsRowV2 } from "./parts/row"
 import { LayoutRetirementNotice, LayoutTransitionToggle } from "./interface-transition"
+import { useSettingsBackgroundImage } from "../settings-background-image"
 import "./settings-v2.css"

 let demoSoundState = {
@@ -88,6 +89,7 @@ export const SettingsGeneralV2: Component<{
  const language = useLanguage()
  const permission = usePermission()
  const platform = usePlatform()
+  const backgroundImage = useSettingsBackgroundImage()
  const dialog = useDialog()
  const settings = useSettings()
  const serverSync = useServerSync()
@@ -460,6 +462,29 @@ export const SettingsGeneralV2: Component<{
          />
        </SettingsRowV2>

+        <Show when={backgroundImage.available}>
+          <SettingsRowV2
+            title={language.t("settings.general.row.backgroundImage.title")}
+            description={language.t("settings.general.row.backgroundImage.description")}
+          >
+            <div class="flex items-center gap-2">
+              <ButtonV2
+                size="normal"
+                variant="neutral"
+                disabled={backgroundImage.busy}
+                onClick={backgroundImage.select}
+              >
+                {language.t("settings.general.row.backgroundImage.choose")}
+              </ButtonV2>
+              <Show when={backgroundImage.active()}>
+                <ButtonV2 size="normal" variant="ghost" disabled={backgroundImage.busy} onClick={backgroundImage.clear}>
+                  {language.t("settings.general.row.backgroundImage.remove")}
+                </ButtonV2>
+              </Show>
+            </div>
+          </SettingsRowV2>
+        </Show>
+
        <SettingsRowV2
          title={language.t("settings.general.row.uiFont.title")}
          description={language.t("settings.general.row.uiFont.description")}
@@ -227,6 +227,7 @@ export function Titlebar(props: { update?: TitlebarUpdate }) {

  return (
    <header
+      data-background-surface="shell"
      data-slot={useV2Titlebar() ? "titlebar-v2" : undefined}
      classList={{
        "shrink-0 relative flex flex-row": true,
@@ -112,6 +112,18 @@ type PlatformBase = {
  /** Read image from clipboard (desktop only) */
  readClipboardImage?(): Promise<File | null>

+  /** Load and apply the saved app background image. */
+  loadBackgroundImage?(): Promise<boolean>
+
+  /** Whether the app currently has a background image. */
+  backgroundImage?: Accessor<boolean>
+
+  /** Select and apply an app background image. */
+  selectBackgroundImage?(): Promise<boolean>
+
+  /** Clear the saved app background image. */
+  clearBackgroundImage?(): Promise<void>
+
  /** Export collected diagnostic logs (desktop only) */
  exportDebugLogs?(): Promise<string>

@@ -1,6 +1,7 @@
 // @refresh reload

 import * as Sentry from "@sentry/solid"
+import { createSignal } from "solid-js"
 import { render } from "solid-js/web"
 import { AppBaseProviders, AppInterface } from "@/app"
 import { type Platform, PlatformProvider } from "@/context/platform"
@@ -8,6 +9,12 @@ import { dict as en } from "@/i18n/en"
 import { dict as zh } from "@/i18n/zh"
 import { handleNotificationClick } from "@/utils/notification-click"
 import { authFromToken } from "@/utils/server"
+import {
+  clearWebBackgroundImage,
+  loadWebBackgroundImage,
+  saveWebBackgroundImage,
+  selectWebBackgroundImage,
+} from "@/utils/web-background-image"
 import pkg from "../package.json"
 import { ServerConnection } from "./context/server"

@@ -119,6 +126,21 @@ const clearAuthToken = () => {
  history.replaceState(null, "", location.pathname + (params.size ? `?${params}` : "") + location.hash)
 }

+const [backgroundImage, setBackgroundImage] = createSignal(false)
+let backgroundImageUrl: string | undefined
+const applyBackgroundImage = (image: Blob | null) => {
+  if (backgroundImageUrl) URL.revokeObjectURL(backgroundImageUrl)
+  backgroundImageUrl = image ? URL.createObjectURL(image) : undefined
+  setBackgroundImage(!!backgroundImageUrl)
+  document.documentElement.toggleAttribute("data-background-image", !!backgroundImageUrl)
+  if (backgroundImageUrl) {
+    document.documentElement.style.setProperty("--app-background-image", `url("${backgroundImageUrl}")`)
+    return true
+  }
+  document.documentElement.style.removeProperty("--app-background-image")
+  return false
+}
+
 const platform: Platform = {
  platform: "web",
  version: pkg.version,
@@ -132,8 +154,23 @@ const platform: Platform = {
    return stored ? ServerConnection.Key.make(stored) : null
  },
  setDefaultServer: writeDefaultServerUrl,
+  backgroundImage,
+  async loadBackgroundImage() {
+    return applyBackgroundImage(await loadWebBackgroundImage())
+  },
+  async selectBackgroundImage() {
+    const file = await selectWebBackgroundImage()
+    if (!file) return backgroundImage()
+    return applyBackgroundImage(await saveWebBackgroundImage(file))
+  },
+  async clearBackgroundImage() {
+    await clearWebBackgroundImage()
+    applyBackgroundImage(null)
+  },
 }

+void platform.loadBackgroundImage?.()
+
 if (import.meta.env.VITE_SENTRY_DSN) {
  Sentry.init({
    dsn: import.meta.env.VITE_SENTRY_DSN,
@@ -704,6 +704,10 @@ export const dict = {
  "settings.general.row.font.description": "خصّص الخط المستخدم في كتل التعليمات البرمجية",
  "settings.general.row.terminalFont.title": "خط الطرفية",
  "settings.general.row.terminalFont.description": "خصّص الخط المستخدم في الطرفية",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "خط الواجهة",
  "settings.general.row.uiFont.description": "خصّص الخط المستخدم في الواجهة بأكملها",
  "settings.general.row.followup.title": "سلوك المتابعة",
@@ -713,6 +713,10 @@ export const dict = {
  "settings.general.row.font.description": "Personalize a fonte usada em blocos de código",
  "settings.general.row.terminalFont.title": "Fonte do terminal",
  "settings.general.row.terminalFont.description": "Personalize a fonte usada no terminal",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Fonte da interface",
  "settings.general.row.uiFont.description": "Personalize a fonte usada em toda a interface",
  "settings.general.row.followup.title": "Comportamento de acompanhamento",
@@ -778,6 +778,10 @@ export const dict = {
  "settings.general.row.font.description": "Prilagodi font koji se koristi u blokovima koda",
  "settings.general.row.terminalFont.title": "Font terminala",
  "settings.general.row.terminalFont.description": "Prilagodite font koji se koristi u terminalu",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "UI font",
  "settings.general.row.uiFont.description": "Prilagodi font koji se koristi u cijelom interfejsu",
  "settings.general.row.followup.title": "Ponašanje nadovezivanja",
@@ -773,6 +773,10 @@ export const dict = {
  "settings.general.row.font.description": "Tilpas skrifttypen, der bruges i kodeblokke",
  "settings.general.row.terminalFont.title": "Terminalskrifttype",
  "settings.general.row.terminalFont.description": "Tilpas den skrifttype, der bruges i terminalen",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "UI-skrifttype",
  "settings.general.row.uiFont.description": "Tilpas skrifttypen, der bruges i hele brugerfladen",
  "settings.general.row.followup.title": "Opfølgningsadfærd",
@@ -724,6 +724,10 @@ export const dict = {
  "settings.general.row.font.description": "Die in Codeblöcken verwendete Schriftart anpassen",
  "settings.general.row.terminalFont.title": "Terminalschriftart",
  "settings.general.row.terminalFont.description": "Passe die im Terminal verwendete Schriftart an",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "UI-Schriftart",
  "settings.general.row.uiFont.description": "Die im gesamten Interface verwendete Schriftart anpassen",
  "settings.general.row.followup.title": "Verhalten bei Folgefragen",
@@ -862,6 +862,10 @@ export const dict = {
  "settings.general.row.colorScheme.description": "Choose whether OpenCode follows the system, light, or dark theme",
  "settings.general.row.theme.title": "Theme",
  "settings.general.row.theme.description": "Customise how OpenCode is themed.",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.font.title": "Code Font",
  "settings.general.row.font.description": "Customise the font used in code blocks",
  "settings.general.row.terminalFont.title": "Terminal Font",
@@ -781,6 +781,10 @@ export const dict = {
  "settings.general.row.font.description": "Personaliza la fuente usada en bloques de código",
  "settings.general.row.terminalFont.title": "Fuente del terminal",
  "settings.general.row.terminalFont.description": "Personaliza la fuente utilizada en el terminal",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Fuente de la interfaz",
  "settings.general.row.uiFont.description": "Personaliza la fuente usada en toda la interfaz",
  "settings.general.row.followup.title": "Comportamiento de seguimiento",
@@ -720,6 +720,10 @@ export const dict = {
  "settings.general.row.font.description": "Personnaliser la police utilisée dans les blocs de code",
  "settings.general.row.terminalFont.title": "Police du terminal",
  "settings.general.row.terminalFont.description": "Personnalisez la police utilisée dans le terminal",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Police de l'interface",
  "settings.general.row.uiFont.description": "Personnaliser la police utilisée dans toute l'interface",
  "settings.general.row.followup.title": "Comportement de suivi",
@@ -709,6 +709,10 @@ export const dict = {
  "settings.general.row.font.description": "コードブロックで使用するフォントをカスタマイズします",
  "settings.general.row.terminalFont.title": "ターミナルのフォント",
  "settings.general.row.terminalFont.description": "ターミナルで使用するフォントをカスタマイズ",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "UIフォント",
  "settings.general.row.uiFont.description": "インターフェース全体で使用するフォントをカスタマイズします",
  "settings.general.row.followup.title": "フォローアップの動作",
@@ -580,6 +580,10 @@ export const dict = {
  "settings.general.row.font.description": "코드 블록에 사용되는 글꼴을 사용자 지정",
  "settings.general.row.terminalFont.title": "터미널 글꼴",
  "settings.general.row.terminalFont.description": "터미널에서 사용할 글꼴을 설정합니다",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "UI 글꼴",
  "settings.general.row.uiFont.description": "인터페이스 전반에 사용되는 글꼴을 사용자 지정",
  "settings.general.row.followup.title": "후속 조치 동작",
@@ -654,6 +654,10 @@ export const dict = {
  "settings.general.row.font.description": "Tilpass skrifttypen som brukes i kodeblokker",
  "settings.general.row.terminalFont.title": "Terminalskrift",
  "settings.general.row.terminalFont.description": "Tilpass skrifttypen som brukes i terminalen",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "UI-skrift",
  "settings.general.row.uiFont.description": "Tilpass skrifttypen som brukes i hele grensesnittet",
  "settings.general.row.followup.title": "Oppfølgingsadferd",
@@ -714,6 +714,10 @@ export const dict = {
  "settings.general.row.font.description": "Dostosuj czcionkę używaną w blokach kodu",
  "settings.general.row.terminalFont.title": "Czcionka terminala",
  "settings.general.row.terminalFont.description": "Dostosuj czcionkę używaną w terminalu",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Czcionka interfejsu",
  "settings.general.row.uiFont.description": "Dostosuj czcionkę używaną w całym interfejsie",
  "settings.general.row.followup.title": "Zachowanie kontynuacji",
@@ -778,6 +778,10 @@ export const dict = {
  "settings.general.row.font.description": "Настройте шрифт, используемый в блоках кода",
  "settings.general.row.terminalFont.title": "Шрифт терминала",
  "settings.general.row.terminalFont.description": "Настройте шрифт, используемый в терминале",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Шрифт интерфейса",
  "settings.general.row.uiFont.description": "Настройте шрифт, используемый во всем интерфейсе",
  "settings.general.row.followup.title": "Поведение уточняющих вопросов",
@@ -771,6 +771,10 @@ export const dict = {
  "settings.general.row.font.description": "ปรับแต่งฟอนต์ที่ใช้ในบล็อกโค้ด",
  "settings.general.row.terminalFont.title": "ฟอนต์เทอร์มินัล",
  "settings.general.row.terminalFont.description": "ปรับแต่งฟอนต์ที่ใช้ในเทอร์มินัล",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "ฟอนต์ UI",
  "settings.general.row.uiFont.description": "ปรับแต่งฟอนต์ที่ใช้ทั่วทั้งอินเทอร์เฟซ",
  "settings.general.row.followup.title": "พฤติกรรมการติดตามผล",
@@ -784,6 +784,10 @@ export const dict = {
  "settings.general.row.font.description": "Kod bloklarında kullanılan yazı tipini özelleştirin",
  "settings.general.row.terminalFont.title": "Terminal yazı tipi",
  "settings.general.row.terminalFont.description": "Terminalde kullanılan yazı tipini özelleştirin",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Arayüz Yazı Tipi",
  "settings.general.row.uiFont.description": "Arayüz genelinde kullanılan yazı tipini özelleştirin",
  "settings.general.row.followup.title": "Takip davranışı",
@@ -870,6 +870,10 @@ export const dict = {
  "settings.general.row.font.description": "Налаштуйте шрифт, який використовується в блоках коду",
  "settings.general.row.terminalFont.title": "Шрифт термінала",
  "settings.general.row.terminalFont.description": "Налаштуйте шрифт, який використовується в терміналі",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "Шрифт інтерфейсу",
  "settings.general.row.uiFont.description": "Налаштуйте шрифт, який використовується в інтерфейсі",
  "settings.general.row.followup.title": "Поведінка продовження",
@@ -768,6 +768,10 @@ export const dict = {
  "settings.general.row.font.description": "自定义代码块使用的字体",
  "settings.general.row.terminalFont.title": "终端字体",
  "settings.general.row.terminalFont.description": "自定义终端使用的字体",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "界面字体",
  "settings.general.row.uiFont.description": "自定义整个界面使用的字体",
  "settings.general.row.followup.title": "跟进消息行为",
@@ -763,6 +763,10 @@ export const dict = {
  "settings.general.row.font.description": "自訂程式碼區塊使用的字型",
  "settings.general.row.terminalFont.title": "終端機字型",
  "settings.general.row.terminalFont.description": "自訂終端機使用的字型",
+  "settings.general.row.backgroundImage.title": "Background image",
+  "settings.general.row.backgroundImage.description": "Choose an image for the app background.",
+  "settings.general.row.backgroundImage.choose": "Choose image",
+  "settings.general.row.backgroundImage.remove": "Remove",
  "settings.general.row.uiFont.title": "介面字型",
  "settings.general.row.uiFont.description": "自訂整個介面使用的字型",
  "settings.general.row.followup.title": "後續追問行為",
@@ -3,6 +3,62 @@
@import "@opencode-ai/ui/v2/styles/tailwind.css";
@import "tw-animate-css";

+html[data-background-image] body {
+  background-image: linear-gradient(rgb(0 0 0 / 30%), rgb(0 0 0 / 30%)), var(--app-background-image);
+  background-color: transparent !important;
+  background-position: center;
+  background-repeat: no-repeat;
+  background-size: cover;
+}
+
+html[data-background-image] #root {
+  background-color: transparent !important;
+}
+
+html[data-background-image] [data-background-surface="shell"] {
+  background-color: transparent !important;
+}
+
+html[data-background-image] [data-background-surface="content"] {
+  background-color: color-mix(in srgb, var(--background-base) 68%, transparent) !important;
+}
+
+html[data-background-image] [data-background-surface="panel"] {
+  background-color: color-mix(in srgb, var(--v2-background-bg-base) 56%, transparent) !important;
+}
+
+html[data-background-image] [data-background-surface="prompt"] {
+  background-color: color-mix(in srgb, var(--v2-background-bg-base) 68%, transparent) !important;
+  backdrop-filter: blur(16px);
+}
+
+html[data-background-image] [data-background-surface="project-selector"] {
+  background-color: color-mix(in srgb, var(--v2-background-bg-base) 68%, transparent) !important;
+  box-shadow: inset 0 0 0 1px color-mix(in srgb, var(--v2-border-border-base) 70%, transparent);
+  backdrop-filter: blur(16px);
+}
+
+html[data-background-image] [data-background-surface="prompt"] [data-background-surface="project-selector"] {
+  background-color: transparent !important;
+  box-shadow: none;
+  backdrop-filter: none;
+}
+
+html[data-background-image] [data-background-surface="workspace-bar"] {
+  padding-inline: 6px;
+  padding-block: 2px;
+  border-radius: 6px;
+  background-color: color-mix(in srgb, var(--v2-background-bg-base) 68%, transparent) !important;
+  box-shadow: inset 0 0 0 1px color-mix(in srgb, var(--v2-border-border-base) 70%, transparent);
+  backdrop-filter: blur(16px);
+}
+
+html[data-background-image] [data-background-surface="workspace-bar"] [data-background-surface="project-selector"] {
+  background-color: transparent !important;
+  box-shadow: none;
+  backdrop-filter: none;
+}
+
@font-face {
  font-family: "JetBrainsMono Nerd Font Mono";
  src: url("/assets/JetBrainsMonoNerdFontMono-Regular.woff2") format("woff2");
@@ -598,7 +598,10 @@ export function NewHome() {
  }

  return (
-    <div class="rounded-[10px] shadow-[var(--v2-elevation-raised)] m-2 min-h-0 overflow-hidden bg-v2-background-bg-base self-stretch flex-1">
+    <div
+      data-background-surface="panel"
+      class="rounded-[10px] shadow-[var(--v2-elevation-raised)] m-2 min-h-0 overflow-hidden bg-v2-background-bg-base self-stretch flex-1"
+    >
      <ScrollView
        class="h-full [container-type:size]"
        thumbContainer={sessionThumbTrack}
@@ -26,6 +26,7 @@ export default function NewLayout(props: ParentProps) {

  return (
    <div
+      data-background-surface="shell"
      class="relative bg-v2-background-bg-deep flex-1 min-h-0 min-w-0 flex flex-col select-none [&_input]:select-text [&_textarea]:select-text [&_[contenteditable]]:select-text"
      style={{
        "padding-top": "env(safe-area-inset-top, 0px)",
@@ -2246,7 +2246,10 @@ export default function LegacyLayout(props: ParentProps) {
  )

  return (
-    <div class="relative bg-background-base flex-1 min-h-0 min-w-0 flex flex-col select-none [&_input]:select-text [&_textarea]:select-text [&_[contenteditable]]:select-text">
+    <div
+      data-background-surface="shell"
+      class="relative bg-background-base flex-1 min-h-0 min-w-0 flex flex-col select-none [&_input]:select-text [&_textarea]:select-text [&_[contenteditable]]:select-text"
+    >
      {autoselecting() ?? ""}
      <Titlebar update={titlebarUpdate} />
      <Show when={updateVersion() !== undefined}>
@@ -2344,6 +2347,7 @@ export default function LegacyLayout(props: ParentProps) {
              }}
            >
              <main
+                data-background-surface="content"
                classList={{
                  "size-full overflow-x-hidden flex flex-col items-start contain-strict border-t border-border-weak-base bg-background-base xl:border-l xl:rounded-tl-[12px]": true,
                }}
@@ -180,9 +180,11 @@ export default function NewSessionPage() {
                    />
                    <Show when={projectController.selected()}>
                      <div
+                        data-background-surface={showWorkspaceBar() ? "workspace-bar" : undefined}
                        class="flex min-h-7 min-w-0 items-center gap-0 text-v2-text-text-faint"
                        classList={{
                          "flex-col justify-center sm:flex-row": showWorkspaceBar(),
+                          "w-fit max-w-full self-center": showWorkspaceBar(),
                          "justify-start": !showWorkspaceBar(),
                        }}
                      >
@@ -335,6 +335,7 @@ function SessionRouteFrame(props: ParentProps<{ padded?: boolean }>) {
 function SessionPanelFrame(props: ParentProps<{ newLayout: boolean; raised?: boolean }>) {
  return (
    <div
+      data-background-surface={props.newLayout ? "panel" : undefined}
      classList={{
        "flex-1 min-h-0 flex flex-col": true,
        "bg-v2-background-bg-base": props.newLayout,
@@ -0,0 +1,33 @@
+const cacheName = "opencode-background-image-v1"
+const maxBytes = 20 * 1024 * 1024
+
+function key() {
+  return new URL("/__opencode/background-image", location.origin).toString()
+}
+
+export async function loadWebBackgroundImage() {
+  const response = await (await caches.open(cacheName)).match(key())
+  return response?.blob() ?? null
+}
+
+export async function saveWebBackgroundImage(file: File) {
+  if (!file.type.startsWith("image/")) throw new Error("Unsupported background image format")
+  if (file.size > maxBytes) throw new Error("Background images must be 20 MB or smaller")
+  await (await caches.open(cacheName)).put(key(), new Response(file, { headers: { "Content-Type": file.type } }))
+  return file
+}
+
+export async function clearWebBackgroundImage() {
+  await (await caches.open(cacheName)).delete(key())
+}
+
+export function selectWebBackgroundImage() {
+  return new Promise<File | null>((resolve) => {
+    const input = document.createElement("input")
+    input.type = "file"
+    input.accept = "image/avif,image/bmp,image/gif,image/jpeg,image/png,image/webp"
+    input.onchange = () => resolve(input.files?.[0] ?? null)
+    input.oncancel = () => resolve(null)
+    input.click()
+  })
+}
@@ -31,11 +31,13 @@ function run(target) {

 const envPath = process.env.OPENCODE_BIN_PATH
 const scriptDir = path.dirname(fs.realpathSync(__filename))
-const cached = path.join(scriptDir, ".opencode2")
+const command = path.basename(__filename).replace(/\.cjs$/, "")
+const nodeBuild = command === "opencode2-node"
+const cached = path.join(scriptDir, `.${command}`)
 const platform = { darwin: "darwin", linux: "linux", win32: "windows" }[os.platform()] || os.platform()
 const arch = { x64: "x64", arm64: "arm64", arm: "arm" }[os.arch()] || os.arch()
-const base = "@opencode-ai/cli-" + platform + "-" + arch
-const binary = platform === "windows" ? "opencode2.exe" : "opencode2"
+const base = `@opencode-ai/cli${nodeBuild ? "-node" : ""}-` + platform + "-" + arch
+const binary = platform === "windows" ? `${command}.exe` : command

 function supportsAvx2() {
  if (arch !== "x64") return false
@@ -77,6 +79,7 @@ function supportsAvx2() {
 }

 const names = (() => {
+  if (nodeBuild) return [base]
  const baseline = arch === "x64" && !supportsAvx2()
  if (platform === "linux") {
    const musl = (() => {
@@ -121,7 +124,7 @@ function findBinary(startDir) {
 const resolved = envPath || (fs.existsSync(cached) ? cached : findBinary(scriptDir))
 if (!resolved) {
  console.error(
-    "It seems that your package manager failed to install the right opencode2 CLI package. Try manually installing " +
+    `It seems that your package manager failed to install the right ${command} CLI package. Try manually installing ` +
      names.map((name) => `"${name}"`).join(" or ") +
      " package",
  )
@@ -12,20 +12,12 @@
  ],
  "exports": {
    "./daemon": "./src/daemon.ts",
-    "./mini": "./src/mini/index.ts",
-    "./mini/footer.command": "./src/mini/footer.command.tsx",
-    "./mini/footer.menu": "./src/mini/footer.menu.tsx",
-    "./mini/footer.permission": "./src/mini/footer.permission.tsx",
-    "./mini/footer.prompt": "./src/mini/footer.prompt.tsx",
-    "./mini/footer.question": "./src/mini/footer.question.tsx",
-    "./mini/footer.subagent": "./src/mini/footer.subagent.tsx",
-    "./mini/footer.view": "./src/mini/footer.view.tsx",
-    "./mini/scrollback.writer": "./src/mini/scrollback.writer.tsx",
-    "./mini/*": "./src/mini/*.ts",
+    "./run": "./src/run/index.ts",
    "./server-process": "./src/server-process.ts"
  },
  "scripts": {
    "build": "bun run script/build.ts",
+    "build:node": "bun run script/build-node.ts",
    "dev": "bun run src/index.ts",
    "test": "bun test --timeout 30000 --only-failures",
    "typecheck": "tsgo --noEmit"
@@ -39,19 +31,16 @@
    "@opencode-ai/server": "workspace:*",
    "@opencode-ai/tui": "workspace:*",
    "@opentui/core": "catalog:",
-    "@opentui/keymap": "catalog:",
    "@opentui/solid": "catalog:",
    "@parcel/watcher": "2.5.1",
    "effect": "catalog:",
-    "fuzzysort": "catalog:",
    "immer": "11.1.4",
    "jsonc-parser": "3.3.1",
    "open": "10.1.2",
-    "opentui-spinner": "catalog:",
    "semver": "catalog:",
    "solid-js": "catalog:",
-    "strip-ansi": "7.1.2",
-    "uqr": "0.1.3"
+    "uqr": "0.1.3",
+    "ws": "8.21.0"
  },
  "devDependencies": {
    "@opencode-ai/script": "workspace:*",
@@ -59,6 +48,19 @@
    "@tsconfig/bun": "catalog:",
    "@types/bun": "catalog:",
    "@types/semver": "catalog:",
-    "@typescript/native-preview": "catalog:"
+    "@typescript/native-preview": "catalog:",
+    "@lydell/node-pty-darwin-arm64": "1.2.0-beta.12",
+    "@lydell/node-pty-darwin-x64": "1.2.0-beta.12",
+    "@lydell/node-pty-linux-arm64": "1.2.0-beta.12",
+    "@lydell/node-pty-linux-x64": "1.2.0-beta.12",
+    "@lydell/node-pty-win32-arm64": "1.2.0-beta.12",
+    "@lydell/node-pty-win32-x64": "1.2.0-beta.12",
+    "@parcel/watcher-darwin-arm64": "2.5.1",
+    "@parcel/watcher-linux-arm64-glibc": "2.5.1",
+    "@parcel/watcher-linux-x64-glibc": "2.5.1",
+    "@parcel/watcher-win32-arm64": "2.5.1",
+    "@parcel/watcher-win32-x64": "2.5.1",
+    "vite": "catalog:",
+    "vite-plugin-solid": "catalog:"
  }
 }
@@ -0,0 +1,203 @@
+#!/usr/bin/env bun
+
+import { spawnSync } from "node:child_process"
+import { createHash } from "node:crypto"
+import { chmod, copyFile, mkdir, mkdtemp, realpath, rename, rm, stat, writeFile } from "node:fs/promises"
+import os from "node:os"
+import path from "node:path"
+import { build } from "vite"
+import { Script } from "@opencode-ai/script"
+import pkg from "../package.json"
+import { modelsData } from "./generate"
+import { collectNodeAssets, copyNodeAssets, hashNodeAssets, seaAssetMap } from "./node-assets"
+import { mainConfig } from "../vite.node.config"
+import { nodeExecArgv, nodeTarget, type NodeTarget } from "../src/node/target"
+
+const NODE_VERSION = "26.4.0"
+const dir = path.resolve(import.meta.dirname, "..")
+const outdir = path.resolve(
+  dir,
+  process.argv.find((arg) => arg.startsWith("--outdir="))?.slice("--outdir=".length) ?? "dist",
+)
+if (outdir === dir) throw new Error("--outdir must not be the package directory")
+if (outdir === path.join(dir, "dist-node")) {
+  throw new Error("--outdir must not be dist-node because it contains temporary files")
+}
+const bundleOnly = process.argv.includes("--bundle-only")
+const single = process.argv.includes("--single")
+const skipInstall = process.argv.includes("--skip-install")
+const requested = process.argv.find((arg) => arg.startsWith("--target="))?.slice("--target=".length)
+const allTargets = [
+  nodeTarget("linux", "arm64"),
+  nodeTarget("linux", "x64"),
+  nodeTarget("darwin", "arm64"),
+  nodeTarget("win32", "arm64"),
+  nodeTarget("win32", "x64"),
+]
+const targets = requested
+  ? allTargets.filter((target) => targetName(target) === requested)
+  : single || bundleOnly
+    ? [nodeTarget(process.platform, process.arch)]
+    : allTargets
+
+if (targets.length === 0) {
+  if (requested === "darwin-x64") throw new Error("Node 26.4 SEA does not support macOS x64")
+  throw new Error(`Unknown Node target: ${requested}`)
+}
+if (!bundleOnly && targets.some((target) => target.platform === "darwin" && target.arch === "x64")) {
+  throw new Error("Node 26.4 SEA does not support macOS x64")
+}
+
+process.chdir(dir)
+if (!skipInstall) run(process.execPath, ["install", "--os=*", "--cpu=*"])
+if (!bundleOnly) await rm(outdir, { recursive: true, force: true })
+const builder =
+  !bundleOnly || targets.some((target) => target.platform === process.platform && target.arch === process.arch)
+    ? await resolveHostNode()
+    : undefined
+
+for (const target of targets) {
+  console.log(`building cli-node-${targetName(target)}`)
+  const assets = await collectNodeAssets(target)
+  await rm("dist-node", { recursive: true, force: true })
+  const assetHash = await hashNodeAssets(assets)
+  const input = { version: Script.version, channel: Script.channel, models: modelsData, assetHash, target }
+  await build(mainConfig(input))
+  await copyNodeAssets(assets)
+
+  const host = target.platform === process.platform && target.arch === process.arch
+  if (host) {
+    if (!builder) throw new Error("Node SEA builder is unavailable")
+    run(builder, [...nodeExecArgv, "dist-node/opencode.mjs", "--version"])
+    run(builder, [...nodeExecArgv, "dist-node/opencode.mjs", "--help"])
+  }
+  if (bundleOnly) continue
+
+  const name = `cli-node-${targetName(target)}`
+  const binary = target.platform === "win32" ? "opencode2-node.exe" : "opencode2-node"
+  const output = path.join(outdir, name, "bin", binary)
+  if (!builder) throw new Error("Node SEA builder is unavailable")
+  await mkdir(path.dirname(output), { recursive: true })
+  const config = {
+    main: "dist-node/opencode.mjs",
+    mainFormat: "module",
+    executable: await resolveTargetNode(target, builder),
+    output: path.relative(dir, output),
+    disableExperimentalSEAWarning: true,
+    useSnapshot: false,
+    useCodeCache: false,
+    execArgv: nodeExecArgv,
+    execArgvExtension: "none",
+    assets: await seaAssetMap(),
+  }
+  await writeFile("dist-node/sea.json", `${JSON.stringify(config, null, 2)}\n`)
+  run(builder, ["--build-sea", "dist-node/sea.json"])
+  if (target.platform !== "win32") await chmod(output, 0o755)
+  if (target.platform === "darwin" && process.platform === "darwin") run("codesign", ["--sign", "-", output])
+  if (target.platform === "darwin" && process.platform !== "darwin") {
+    console.warn(`${output} must be signed on macOS before it can run`)
+  }
+  await writeFile(
+    path.join(outdir, name, "package.json"),
+    `${JSON.stringify(
+      {
+        name: `@opencode-ai/${name}`,
+        version: Script.version,
+        license: pkg.license,
+        repository: { type: "git", url: "git+https://github.com/anomalyco/opencode.git" },
+        os: [target.platform],
+        cpu: [target.arch],
+      },
+      null,
+      2,
+    )}\n`,
+  )
+  if (host) await smoke(output)
+}
+
+async function resolveHostNode() {
+  const candidates = [process.env.NODE_BIN, "node"].filter((item): item is string => Boolean(item))
+  for (const candidate of candidates) {
+    const result = spawnSync(
+      candidate,
+      ["-p", "JSON.stringify({version:process.versions.node,path:process.execPath})"],
+      {
+        encoding: "utf8",
+      },
+    )
+    if (result.status !== 0) continue
+    const info = JSON.parse(result.stdout) as { version: string; path: string }
+    if (info.version === NODE_VERSION) return realpath(info.path)
+  }
+  return resolveTargetNode(nodeTarget(process.platform, process.arch))
+}
+
+async function resolveTargetNode(target: NodeTarget, host?: string) {
+  if (host && target.platform === process.platform && target.arch === process.arch) return host
+  const cache = path.resolve(dir, ".cache", "node")
+  const platform = target.platform === "win32" ? "win" : target.platform
+  const archiveName = `node-v${NODE_VERSION}-${platform}-${target.arch}`
+  const targetDirectory = path.join(cache, archiveName)
+  const executable = path.join(targetDirectory, target.platform === "win32" ? "node.exe" : "bin/node")
+  if (
+    (await stat(executable).then(
+      () => true,
+      () => false,
+    )) &&
+    (await stat(path.join(targetDirectory, ".verified")).then(
+      () => true,
+      () => false,
+    ))
+  )
+    return realpath(executable)
+  await mkdir(cache, { recursive: true })
+  const extension = target.platform === "win32" ? "zip" : "tar.gz"
+  const filename = `${archiveName}.${extension}`
+  const archive = path.join(cache, filename)
+  const base = `https://nodejs.org/dist/v${NODE_VERSION}`
+  const [response, sums] = await Promise.all([fetch(`${base}/${filename}`), fetch(`${base}/SHASUMS256.txt`)])
+  if (!response.ok) throw new Error(`Failed to download Node ${NODE_VERSION}: ${response.status}`)
+  if (!sums.ok) throw new Error(`Failed to download Node ${NODE_VERSION} checksums: ${sums.status}`)
+  const data = new Uint8Array(await response.arrayBuffer())
+  const expected = (await sums.text())
+    .split("\n")
+    .find((line) => line.endsWith(`  ${filename}`))
+    ?.split(/\s+/)[0]
+  if (!expected) throw new Error(`Missing checksum for ${filename}`)
+  if (createHash("sha256").update(data).digest("hex") !== expected) throw new Error(`Checksum mismatch for ${filename}`)
+  await writeFile(archive, data)
+  const temporary = path.join(cache, `${archiveName}.${process.pid}.tmp`)
+  await rm(temporary, { recursive: true, force: true })
+  await mkdir(temporary)
+  if (target.platform !== "win32") run("tar", ["-xzf", archive, "-C", temporary])
+  if (target.platform === "win32" && process.platform === "win32") {
+    run(path.join(process.env.SystemRoot ?? "C:\\Windows", "System32", "tar.exe"), ["-xf", archive, "-C", temporary])
+  }
+  if (target.platform === "win32" && process.platform !== "win32") run("unzip", ["-q", archive, "-d", temporary])
+  await rm(targetDirectory, { recursive: true, force: true })
+  await rename(path.join(temporary, archiveName), targetDirectory)
+  await writeFile(path.join(targetDirectory, ".verified"), `${expected}\n`)
+  await rm(temporary, { recursive: true, force: true })
+  await rm(archive, { force: true })
+  return realpath(executable)
+}
+
+async function smoke(output: string) {
+  const root = await mkdtemp(path.join(os.tmpdir(), "opencode-node-smoke-"))
+  const executable = path.join(root, path.basename(output))
+  await copyFile(output, executable)
+  if (process.platform !== "win32") await chmod(executable, 0o755)
+  run(executable, ["--version"], root)
+  run(executable, ["--help"], root)
+  await rm(root, { recursive: true, force: true })
+}
+
+function targetName(target: NodeTarget) {
+  return `${target.platform === "win32" ? "windows" : target.platform}-${target.arch}`
+}
+
+function run(command: string, args: readonly string[], cwd = dir) {
+  const result = spawnSync(command, args, { cwd, stdio: "inherit", env: process.env })
+  if (result.error) throw result.error
+  if (result.status !== 0) throw new Error(`${command} exited with status ${result.status ?? "unknown"}`)
+}
@@ -1,7 +1,6 @@
 #!/usr/bin/env bun

 import { $ } from "bun"
-import fs from "fs"
 import { rm } from "fs/promises"
 import path from "path"
 import { Script } from "@opencode-ai/script"
@@ -11,9 +10,14 @@ import { modelsData } from "./generate"

 const dir = path.resolve(import.meta.dirname, "..")
 const binary = "opencode2"
+const outdir = path.resolve(
+  dir,
+  process.argv.find((arg) => arg.startsWith("--outdir="))?.slice("--outdir=".length) ?? "dist",
+)
+if (outdir === dir) throw new Error("--outdir must not be the package directory")
 process.chdir(dir)

-await rm("dist", { recursive: true, force: true })
+await rm(outdir, { recursive: true, force: true })

 const singleFlag = process.argv.includes("--single")
 const baselineFlag = process.argv.includes("--baseline")
@@ -50,10 +54,6 @@ const targets = singleFlag

 if (!skipInstall) await $`bun install --os="*" --cpu="*" @opentui/core@${pkg.dependencies["@opentui/core"]}`

-const localParserWorker = path.resolve(dir, "node_modules/@opentui/core/parser.worker.js")
-const rootParserWorker = path.resolve(dir, "../../node_modules/@opentui/core/parser.worker.js")
-const parserWorker = fs.realpathSync(fs.existsSync(localParserWorker) ? localParserWorker : rootParserWorker)
-
 for (const item of targets) {
  const target = [
    binary,
@@ -67,7 +67,7 @@ for (const item of targets) {
  const name = target.replace(binary, "cli")
  console.log(`building ${name}`)
  const result = await Bun.build({
-    entrypoints: ["./src/index.ts", parserWorker],
+    entrypoints: ["./src/index.ts"],
    tsconfig: "./tsconfig.json",
    plugins: [plugin],
    external: ["node-gyp"],
@@ -81,7 +81,7 @@ for (const item of targets) {
      autoloadTsconfig: true,
      autoloadPackageJson: true,
      target: target.replace(binary, "bun") as Bun.Build.CompileTarget,
-      outfile: `./dist/${name}/bin/${binary}`,
+      outfile: path.join(outdir, name, "bin", binary),
      execArgv: [`--user-agent=${binary}/${Script.version}`, "--use-system-ca", "--"],
      windows: {},
    },
@@ -93,10 +93,6 @@ for (const item of targets) {
      OPENCODE_LIBC: item.os === "linux" ? `'${item.abi ?? "glibc"}'` : "undefined",
      // FFF_LIBC selects the fff native lib variant: "musl" or "gnu".
      FFF_LIBC: item.os === "linux" ? `'${item.abi ?? "gnu"}'` : "undefined",
-      OTUI_TREE_SITTER_WORKER_PATH:
-        (item.os === "win32" ? '"B:/~BUN/root/' : '"/$bunfs/root/') +
-        path.relative(dir, parserWorker).replaceAll("\\", "/") +
-        '"',
      ...(item.os === "linux" ? { "process.env.OPENTUI_LIBC": JSON.stringify(item.abi ?? "glibc") } : {}),
    },
  })
@@ -107,7 +103,7 @@ for (const item of targets) {
  }

  await Bun.write(
-    `./dist/${name}/package.json`,
+    path.join(outdir, name, "package.json"),
    JSON.stringify(
      {
        name: `@opencode-ai/${name}`,
@@ -1,7 +1,9 @@
+import { readFile } from "node:fs/promises"
+
 const modelsUrl = process.env.OPENCODE_MODELS_URL || "https://models.dev"

 export const modelsData = process.env.MODELS_DEV_API_JSON
-  ? await Bun.file(process.env.MODELS_DEV_API_JSON).text()
+  ? await readFile(process.env.MODELS_DEV_API_JSON, "utf8")
  : await fetch(`${modelsUrl}/api.json`).then((response) => response.text())

 console.log("Loaded models.dev snapshot")
@@ -0,0 +1,83 @@
+import { createHash } from "node:crypto"
+import { copyFile, mkdir, readdir, readFile, stat } from "node:fs/promises"
+import { createRequire } from "node:module"
+import path from "node:path"
+import { fileURLToPath } from "node:url"
+import { getNodeAssets } from "@opentui/core/node-assets"
+import { attentionSoundAssets, type NodeTarget, photonWasmAsset } from "../src/node/target"
+
+const dir = path.resolve(import.meta.dirname, "..")
+
+// Bun's compiler discovers file imports and embeds them in its virtual filesystem. Vite only bundles the JavaScript
+// portion of the Node executable, while SEA embeds only the assets explicitly listed in its build configuration.
+// Collect and stage those files under stable keys so the SEA prelude can extract them to real paths at startup;
+// native addons, helper executables, and other path-based consumers cannot use assets directly from SEA memory.
+export type NodeAsset = {
+  readonly key: string
+  readonly source: string
+}
+
+async function files(root: string, current = root): Promise<string[]> {
+  return (
+    await Promise.all(
+      (await readdir(current, { withFileTypes: true })).map((entry) => {
+        const target = path.join(current, entry.name)
+        return entry.isDirectory() ? files(root, target) : [path.relative(root, target)]
+      }),
+    )
+  ).flat()
+}
+
+export async function collectNodeAssets(target: NodeTarget) {
+  const ptyEntry = fileURLToPath(import.meta.resolve(target.nodePtyPackage))
+  const ptyRoot = path.resolve(path.dirname(ptyEntry), "..")
+  const assets: NodeAsset[] = [
+    ...getNodeAssets({
+      platform: target.platform,
+      arch: target.arch,
+      ...(target.platform === "linux" ? { libc: "glibc" as const } : {}),
+    }),
+    { key: target.parcelWatcherAsset, source: fileURLToPath(import.meta.resolve(target.parcelWatcherPackage)) },
+    {
+      key: photonWasmAsset,
+      source: createRequire(path.resolve(dir, "../core/package.json")).resolve(photonWasmAsset),
+    },
+    ...attentionSoundAssets.map((key) => ({
+      key,
+      source: path.resolve(dir, "../ui/src/assets/audio", path.basename(key)),
+    })),
+    ...(await files(ptyRoot))
+      .filter((relative) => !relative.endsWith(".map") && !relative.endsWith(".pdb"))
+      .map((relative) => ({
+        key: `${target.nodePtyPackage}/${relative}`,
+        source: path.join(ptyRoot, relative),
+      })),
+  ]
+  await Promise.all(assets.map((asset) => stat(asset.source)))
+  return assets
+}
+
+export async function hashNodeAssets(assets: readonly NodeAsset[]) {
+  const hash = createHash("sha256")
+  for (const asset of assets.toSorted((left, right) => left.key.localeCompare(right.key))) {
+    hash.update(asset.key)
+    hash.update(await readFile(asset.source))
+  }
+  return hash.digest("hex").slice(0, 16)
+}
+
+export async function copyNodeAssets(assets: readonly NodeAsset[]) {
+  const root = path.join(dir, "dist-node", "assets")
+  await Promise.all(
+    assets.map(async (asset) => {
+      const target = path.join(root, asset.key)
+      await mkdir(path.dirname(target), { recursive: true })
+      await copyFile(asset.source, target)
+    }),
+  )
+}
+
+export async function seaAssetMap() {
+  const root = path.join(dir, "dist-node", "assets")
+  return Object.fromEntries((await files(root)).map((key) => [key.replaceAll(path.sep, "/"), path.join(root, key)]))
+}
@@ -0,0 +1,161 @@
+#!/usr/bin/env node
+
+import childProcess from "node:child_process"
+import fs from "node:fs"
+import os from "node:os"
+import path from "node:path"
+import { createRequire } from "node:module"
+import { fileURLToPath } from "node:url"
+
+const directory = path.dirname(fileURLToPath(import.meta.url))
+const require = createRequire(import.meta.url)
+const packageJson = JSON.parse(fs.readFileSync(path.join(directory, "package.json"), "utf8"))
+const command = Object.keys(packageJson.bin ?? {})[0]
+if (!command) throw new Error("OpenCode package does not declare a binary")
+
+const platform = { darwin: "darwin", linux: "linux", win32: "windows" }[os.platform()] ?? os.platform()
+const arch = { x64: "x64", arm64: "arm64", arm: "arm" }[os.arch()] ?? os.arch()
+const sourceBinary = platform === "windows" ? `${command}.exe` : command
+const targetBinary = path.resolve(directory, packageJson.bin[command])
+const dependencies = packageJson.optionalDependencies ?? {}
+const base = Object.keys(dependencies).find((name) => name.endsWith(`-${platform}-${arch}`))
+if (!base) throw new Error(`OpenCode does not provide a binary for ${platform}-${arch}`)
+
+function supportsAvx2() {
+  if (arch !== "x64") return false
+  if (platform === "linux") {
+    try {
+      return /(^|\s)avx2(\s|$)/i.test(fs.readFileSync("/proc/cpuinfo", "utf8"))
+    } catch {
+      return false
+    }
+  }
+  if (platform === "darwin") {
+    try {
+      const result = childProcess.spawnSync("sysctl", ["-n", "hw.optional.avx2_0"], {
+        encoding: "utf8",
+        timeout: 1500,
+      })
+      return result.status === 0 && (result.stdout || "").trim() === "1"
+    } catch {
+      return false
+    }
+  }
+  if (platform === "windows") {
+    const script =
+      '(Add-Type -MemberDefinition "[DllImport(""kernel32.dll"")] public static extern bool IsProcessorFeaturePresent(int ProcessorFeature);" -Name Kernel32 -Namespace Win32 -PassThru)::IsProcessorFeaturePresent(40)'
+    for (const executable of ["powershell.exe", "pwsh.exe", "pwsh", "powershell"]) {
+      try {
+        const result = childProcess.spawnSync(executable, ["-NoProfile", "-NonInteractive", "-Command", script], {
+          encoding: "utf8",
+          timeout: 3000,
+          windowsHide: true,
+        })
+        if (result.status !== 0) continue
+        const output = (result.stdout || "").trim().toLowerCase()
+        if (output === "true" || output === "1") return true
+        if (output === "false" || output === "0") return false
+      } catch {
+        continue
+      }
+    }
+  }
+  return false
+}
+
+function isMusl() {
+  if (platform !== "linux") return false
+  try {
+    if (fs.existsSync("/etc/alpine-release")) return true
+    const result = childProcess.spawnSync("ldd", ["--version"], { encoding: "utf8" })
+    return `${result.stdout || ""}${result.stderr || ""}`.toLowerCase().includes("musl")
+  } catch {
+    return false
+  }
+}
+
+function packageNames() {
+  const baseline = arch === "x64" && !supportsAvx2()
+  const names =
+    platform === "linux"
+      ? isMusl()
+        ? arch === "x64"
+          ? baseline
+            ? [`${base}-baseline-musl`, `${base}-musl`, `${base}-baseline`, base]
+            : [`${base}-musl`, `${base}-baseline-musl`, base, `${base}-baseline`]
+          : [`${base}-musl`, base]
+        : arch === "x64"
+          ? baseline
+            ? [`${base}-baseline`, base, `${base}-baseline-musl`, `${base}-musl`]
+            : [base, `${base}-baseline`, `${base}-musl`, `${base}-baseline-musl`]
+          : [base, `${base}-musl`]
+      : arch === "x64"
+        ? baseline
+          ? [`${base}-baseline`, base]
+          : [base, `${base}-baseline`]
+        : [base]
+  return names.filter((name) => dependencies[name])
+}
+
+function copyBinary(source) {
+  if (!fs.existsSync(source)) throw new Error(`Binary not found at ${source}`)
+  fs.mkdirSync(path.dirname(targetBinary), { recursive: true })
+  if (fs.existsSync(targetBinary)) fs.unlinkSync(targetBinary)
+  try {
+    fs.linkSync(source, targetBinary)
+  } catch {
+    fs.copyFileSync(source, targetBinary)
+  }
+  fs.chmodSync(targetBinary, 0o755)
+}
+
+function resolveBinary(name) {
+  const packagePath = require.resolve(`${name}/package.json`)
+  return path.join(path.dirname(packagePath), "bin", sourceBinary)
+}
+
+function installPackage(name) {
+  const temp = fs.mkdtempSync(path.join(os.tmpdir(), "opencode-install-"))
+  try {
+    const result = childProcess.spawnSync(
+      "npm",
+      ["install", "--ignore-scripts", "--no-save", "--loglevel=error", "--prefix", temp, `${name}@${dependencies[name]}`],
+      { stdio: "inherit", windowsHide: true },
+    )
+    if (result.status !== 0) return false
+    copyBinary(path.join(temp, "node_modules", name, "bin", sourceBinary))
+    return true
+  } finally {
+    fs.rmSync(temp, { recursive: true, force: true })
+  }
+}
+
+function verifyBinary() {
+  return (
+    childProcess.spawnSync(targetBinary, ["--version"], {
+      stdio: "ignore",
+      windowsHide: true,
+    }).status === 0
+  )
+}
+
+function main() {
+  const names = packageNames()
+  for (const name of names) {
+    try {
+      copyBinary(resolveBinary(name))
+      if (verifyBinary()) return
+    } catch {
+      if (installPackage(name) && verifyBinary()) return
+    }
+  }
+
+  throw new Error(`Failed to install OpenCode. Try manually installing ${names.map((name) => JSON.stringify(name)).join(" or ")}.`)
+}
+
+try {
+  main()
+} catch (error) {
+  console.error(error instanceof Error ? error.message : String(error))
+  process.exit(1)
+}
@@ -18,37 +18,66 @@ async function publish(dir: string, name: string, version: string) {
  await $`npm publish *.tgz --access public --tag ${Script.channel}`.cwd(dir)
 }

-const binaries: Record<string, string> = {}
-for (const filepath of new Bun.Glob("*/package.json").scanSync({ cwd: "./dist" })) {
-  const item = await Bun.file(`./dist/${filepath}`).json()
-  binaries[item.name] = item.version
+async function publishDistribution(input: { root: string; name: string; binary: string; packagePrefix: string }) {
+  const binaries: Record<string, string> = {}
+  for (const filepath of new Bun.Glob("*/package.json").scanSync({ cwd: input.root })) {
+    const item = await Bun.file(`${input.root}/${filepath}`).json()
+    if (!item.name.startsWith(input.packagePrefix)) continue
+    binaries[item.name] = item.version
+  }
+  console.log(input.name, "binaries", binaries)
+  const versions = new Set(Object.values(binaries))
+  if (versions.size > 1) throw new Error(`Binary package versions do not match for ${input.name}`)
+  const version = versions.values().next().value
+  if (!version) throw new Error(`No binary packages found for ${input.name}`)
+
+  await $`mkdir -p ${input.root}/${input.name}/bin`
+  await $`cp ./script/postinstall.mjs ${input.root}/${input.name}/postinstall.mjs`
+  await Bun.file(`${input.root}/${input.name}/bin/${input.binary}.exe`).write(
+    [
+      `echo "Error: ${input.name}'s postinstall script was not run." >&2`,
+      'echo "" >&2',
+      'echo "This occurs when installation scripts are disabled." >&2',
+      'echo "Run the package postinstall script or reinstall with scripts enabled." >&2',
+      "exit 1",
+      "",
+    ].join("\n"),
+  )
+  await Bun.file(`${input.root}/${input.name}/package.json`).write(
+    JSON.stringify(
+      {
+        name: input.name,
+        bin: { [input.binary]: `./bin/${input.binary}.exe` },
+        scripts: { postinstall: "node ./postinstall.mjs" },
+        version,
+        license: pkg.license,
+        repository: { type: "git", url: "git+https://github.com/anomalyco/opencode.git" },
+        os: ["darwin", "linux", "win32"],
+        cpu: ["arm64", "x64"],
+        optionalDependencies: binaries,
+      },
+      null,
+      2,
+    ),
+  )
+
+  await Promise.all(
+    Object.entries(binaries).map(([name, version]) =>
+      publish(`${input.root}/${name.replace("@opencode-ai/", "")}`, name, version),
+    ),
+  )
+  await publish(`${input.root}/${input.name}`, input.name, version)
 }
-console.log("binaries", binaries)
-const version = Object.values(binaries)[0]
-const name = pkg.name

-await $`mkdir -p ./dist/${name}/bin`
-await $`cp ./bin/opencode2.cjs ./dist/${name}/bin/opencode2`
-await Bun.file(`./dist/${name}/package.json`).write(
-  JSON.stringify(
-    {
-      name,
-      bin: { opencode2: "./bin/opencode2" },
-      version,
-      license: pkg.license,
-      repository: { type: "git", url: "git+https://github.com/anomalyco/opencode.git" },
-      os: ["darwin", "linux", "win32"],
-      cpu: ["arm64", "x64"],
-      optionalDependencies: binaries,
-    },
-    null,
-    2,
-  ),
-)
-
-await Promise.all(
-  Object.entries(binaries).map(([name, version]) =>
-    publish(`./dist/${name.replace("@opencode-ai/", "")}`, name, version),
-  ),
-)
-await publish(`./dist/${name}`, name, version)
+await publishDistribution({
+  root: "./dist",
+  name: pkg.name,
+  binary: "opencode2",
+  packagePrefix: "@opencode-ai/cli-",
+})
+await publishDistribution({
+  root: "./dist/node",
+  name: "opencode-node",
+  binary: "opencode2-node",
+  packagePrefix: "@opencode-ai/cli-node-",
+})
@@ -7,9 +7,10 @@ import fs from "node:fs/promises"
 import os from "node:os"
 import path from "node:path"

-const target = `cli-${process.platform === "win32" ? "windows" : process.platform}-${process.arch}`
-const directory = path.join(import.meta.dir, "..", "dist", target, "bin")
-const binary = path.join(directory, `opencode2${process.platform === "win32" ? ".exe" : ""}`)
+const nodeBuild = process.argv.includes("--node")
+const target = `cli${nodeBuild ? "-node" : ""}-${process.platform === "win32" ? "windows" : process.platform}-${process.arch}`
+const directory = path.join(import.meta.dir, "..", "dist", ...(nodeBuild ? ["node"] : []), target, "bin")
+const binary = path.join(directory, `opencode2${nodeBuild ? "-node" : ""}${process.platform === "win32" ? ".exe" : ""}`)
 if (!(await Bun.file(binary).exists())) throw new Error(`Missing compiled CLI in ${directory}`)

 const root = await fs.mkdtemp(path.join(os.tmpdir(), "opencode-service-smoke-"))
@@ -114,6 +114,10 @@ export const Commands = Spec.make(typeof OPENCODE_CLI_NAME === "string" ? OPENCO
        }),
      ],
    }),
+    Spec.make("plugin", {
+      description: "Manage plugins",
+      commands: [Spec.make("list", { description: "List active plugins" })],
+    }),
    Spec.make("migrate", { description: "Migrate v1 data to v2" }),
    Spec.make("mini", {
      description: "Start the minimal interactive interface",
@@ -1,4 +1,4 @@
-import { AppNodeBuilder } from "@opencode-ai/core/effect/app-node-builder"
+import { LayerNode } from "@opencode-ai/core/effect/layer-node"
 import { Global } from "@opencode-ai/core/global"
 import { run } from "@opencode-ai/tui"
 import { Commands } from "../commands"
@@ -75,6 +75,6 @@ export default Runtime.handler(Commands, (input) =>
                : Effect.logInfo(message, tags)
        runFork(effect)
      },
-    }).pipe(Effect.provide(AppNodeBuilder.build(Global.node)))
+    }).pipe(Effect.provide(LayerNode.compile(Global.node)))
  }),
 )
@@ -1,5 +1,6 @@
 import { EOL } from "node:os"
 import path from "node:path"
+import { readFile, stat, writeFile } from "node:fs/promises"
 import { Effect, Option } from "effect"
 import { applyEdits, modify } from "jsonc-parser"
 import { Global } from "@opencode-ai/core/global"
@@ -35,7 +36,7 @@ export default Runtime.handler(
  }),
 )

-async function resolveConfigPath(directory: string) {
+export async function resolveConfigPath(directory: string) {
  const candidates = [
    path.join(directory, "opencode.json"),
    path.join(directory, "opencode.jsonc"),
@@ -43,16 +44,24 @@ async function resolveConfigPath(directory: string) {
    path.join(directory, ".opencode", "opencode.jsonc"),
  ]
  for (const candidate of candidates) {
-    if (await Bun.file(candidate).exists()) return candidate
+    if (
+      await stat(candidate).then(
+        (info) => info.isFile(),
+        () => false,
+      )
+    )
+      return candidate
  }
  return candidates[0]
 }

 async function write(configPath: string, name: string, server: unknown) {
-  const file = Bun.file(configPath)
-  const text = (await file.exists()) ? await file.text() : "{}"
+  const text = await readFile(configPath, "utf8").catch((error) => {
+    if (typeof error === "object" && error !== null && "code" in error && error.code === "ENOENT") return "{}"
+    throw error
+  })
  const edits = modify(text, ["mcp", "servers", name], server, {
    formattingOptions: { tabSize: 2, insertSpaces: true },
  })
-  await Bun.write(configPath, applyEdits(text, edits))
+  await writeFile(configPath, applyEdits(text, edits))
 }
@@ -1,7 +1,9 @@
-import { Effect, Option } from "effect"
+import { Context, Effect, FileSystem, Option } from "effect"
 import { Commands } from "../commands"
 import { Runtime } from "../../framework/runtime"
 import { ServerConnection } from "../../services/server-connection"
+import { Config } from "../../config"
+import { resolve } from "@opencode-ai/tui/config"

 export default Runtime.handler(Commands.commands.mini, (input) =>
  Effect.gen(function* () {
@@ -9,9 +11,17 @@ export default Runtime.handler(Commands.commands.mini, (input) =>
    yield* Effect.promise(async () => validateMiniTerminal())
    const serverURL = Option.getOrUndefined(input.server)
    const server = yield* ServerConnection.resolve({ server: serverURL, standalone: input.standalone })
+    const config = yield* Config.Service
+    const resolved = resolve(yield* config.get(), { terminalSuspend: process.platform !== "win32" })
+    const fileSystem = yield* FileSystem.FileSystem
+    const runServicePromise = Effect.runPromiseWith(Context.make(FileSystem.FileSystem, fileSystem))
+    const service = server.service
    yield* Effect.promise(() =>
      runMini({
-        server,
+        server: {
+          endpoint: server.endpoint,
+          reconnect: service ? (signal) => runServicePromise(service.reconnect(), { signal }) : undefined,
+        },
        continue: input.continue,
        session: Option.getOrUndefined(input.session),
        fork: input.fork,
@@ -21,6 +31,7 @@ export default Runtime.handler(Commands.commands.mini, (input) =>
        replay: input.replay,
        replayLimit: Option.getOrUndefined(input.replayLimit),
        demo: input.demo,
+        tuiConfig: resolved,
      }),
    )
  }),
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Kit Langton	c34e505026	chore: remove updated screenshot asset	2026-07-21 20:52:58 +00:00
Kit Langton	16863ae97b	docs: add updated desktop screenshot	2026-07-21 20:52:33 +00:00
Kit Langton	314ca785df	fix(desktop): use requested default background	2026-07-21 20:50:56 +00:00
Kit Langton	a2697b9b08	chore: remove temporary screenshot asset	2026-07-21 20:32:41 +00:00
Kit Langton	5de3d73f24	docs: add desktop background screenshot	2026-07-21 20:31:53 +00:00
Kit Langton	4bf7210512	feat(desktop): add default background	2026-07-21 20:29:33 +00:00
Brendan Allan	4e4729535e	fix(app): pad the workspace bar	2026-07-21 00:04:58 +00:00
Brendan Allan	98bb5e3bb4	fix(app): center the workspace bar	2026-07-21 00:02:13 +00:00
Brendan Allan	8eec2c6d57	fix(app): glass the workspace bar	2026-07-20 23:59:10 +00:00
Brendan Allan	6fb632eeb6	fix(app): tune background presentation	2026-07-20 23:47:03 +00:00
Brendan Allan	5452a13e07	fix(app): refine background contrast	2026-07-20 23:43:41 +00:00
Brendan Allan	d881c1c476	fix(app): make background prompt translucent	2026-07-20 16:53:40 +00:00
Brendan Allan	364e2d9f03	feat(app): support web image backgrounds	2026-07-20 16:19:59 +00:00
Brendan Allan	35fcf1ed58	feat(desktop): add image backgrounds	2026-07-20 16:10:39 +00:00
James Long	e8b19afa8f	fix(tui): adapt file badge accent to theme mode (#37953 )	2026-07-20 11:45:29 -04:00
Aiden Cline	3da0dea8e7	feat(codemode): expand standard library parity (#37943 )	2026-07-20 09:59:37 -05:00
Dax Raad	c7aa47c144	feat(tui): implement session timeline	2026-07-20 09:53:07 -04:00
James Long	7be95bcd6a	feat(tui): support single-mode themes (#37930 )	2026-07-20 09:37:48 -04:00
opencode-agent[bot]	3f4fb3f9db	fix(tui): show opencode2 continuation command (#37933 ) Co-authored-by: Dax <mail@thdxr.com>	2026-07-20 13:36:02 +00:00
James Long	6702ce0d3f	fix(tui): soften theme scale extremes (#37555 )	2026-07-20 09:20:20 -04:00
Simon Klee	a9895a1e8a	fix(tui/mini): idle footer when session idles (#37910 )	2026-07-20 13:22:46 +02:00
Simon Klee	75c7ac6a2c	tui/mini: consolidate stream and panel internals (#37903 )	2026-07-20 12:45:48 +02:00
Simon Klee	0eb71d0fc7	refactor(tui): extract shared frontend helpers (#37868 )	2026-07-20 10:43:02 +02:00
Aiden Cline	deee40c572	fix(codemode): parse canonical index keys (#37851 )	2026-07-19 23:55:53 -05:00
Aiden Cline	8b5655ed53	fix(ai): preserve compatible reasoning details (#37708 )	2026-07-19 22:30:55 -05:00
opencode-agent[bot]	b9525b5878	fix(ai): expand context overflow patterns (#37848 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-19 22:22:56 -05:00
opencode-agent[bot]	2b8d1998d6	fix(ai): buffer partial tool call identity (#37847 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-19 22:12:49 -05:00
Aiden Cline	391cfbcfe7	fix(codemode): align string, array, and Date behavior (#37775 )	2026-07-19 21:41:06 -05:00
Dax Raad	fe0c74f4df	fix(cli): accept updated service on restart	2026-07-19 19:29:40 -04:00
Kit Langton	6d32bc9cb0	feat(simulation): control arbitrary tool lifecycles (#37816 )	2026-07-19 17:40:30 -04:00
Simon Klee	925c2423de	mini: add reconnect, forms, and shared targets (#37811 ) Centralize session target resolution for mini and noninteractive run paths. Recover from transport drops, replace questions with forms, and keep tool/catalog state location-scoped with live progress and theme discovery.	2026-07-19 22:45:10 +02:00
Kit Langton	71cb419570	fix(simulation): validate semantic click identity (#37808 )	2026-07-19 16:43:53 -04:00
Kit Langton	edc93ceff1	feat(simulation): expose semantic UI snapshots (#37802 )	2026-07-19 16:04:27 -04:00
opencode-agent[bot]	86a468c4d8	fix(tui): move agent cycling to shift-tab (#37706 ) Co-authored-by: Simon Klee <hello@simonklee.dk>	2026-07-19 21:45:03 +02:00
opencode-agent[bot]	f05d2ab551	fix(tui): load root sessions in switcher (#37784 ) Co-authored-by: Dax Raad <d@ironbay.co>	2026-07-19 16:32:32 +00:00
opencode-agent[bot]	bef6cfbffe	feat(client): support opaque payload schemas (#37773 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-19 16:08:26 +00:00
Aiden Cline	fe9a936867	feat(server): expose runtime MCP controls over HTTP (#37712 )	2026-07-19 10:28:25 -05:00
Aiden Cline	d5669ca934	docs(codemode): streamline README (#37769 )	2026-07-19 10:18:24 -05:00
opencode-agent[bot]	04f0a771a3	feat(ai): add OpenAI image generation (#37714 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-19 10:17:49 -05:00
Simon Klee	c50554d907	mini: move frontend into tui package (#37754 )	2026-07-19 14:12:22 +02:00
Simon Klee	3f5ad8441f	cli: extract run from mini package (#37737 )	2026-07-19 11:11:03 +02:00
Simon Klee	cf6e5b3604	mini: fix shell tool output display (#37711 )	2026-07-19 09:31:38 +02:00
Aiden Cline	cbcf191fdb	fix(core): detach disposed MCP registrations from root scope (#37660 )	2026-07-18 23:38:07 -05:00
Kit Langton	ba0bbdafaa	fix(core): preserve the first terminal failure (#37705 )	2026-07-19 00:00:23 -04:00
Kit Langton	a288cb5a0c	fix(core): continue after malformed tool input (#37701 )	2026-07-18 23:09:08 -04:00
Kit Langton	57ff57595a	fix(core): safely recover malformed tool input (#37698 )	2026-07-18 21:52:45 -04:00
Kit Langton	584fdefe6f	fix(simulation): render screenshot symbol glyphs (#37691 )	2026-07-18 21:36:21 -04:00
Kit Langton	c310ef82f4	fix(core): authorize relative external paths (#37689 )	2026-07-18 19:55:18 -04:00
Dax Raad	4e85a37590	fix(tui): auto-approve permissions in auto mode	2026-07-18 17:54:59 -04:00
opencode-agent[bot]	fe9b051d1a	feat(core): allow MCP Code Mode opt-out (#37681 ) Co-authored-by: Dax Raad <d@ironbay.co>	2026-07-18 17:17:56 -04:00
Aiden Cline	33f1b269e9	fix(codemode): stop leaking undefined into tool arguments (#37652 )	2026-07-18 13:42:16 -05:00
opencode-agent[bot]	0d68b0bb20	fix(tui): style interrupted compaction neutrally (#37655 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-18 13:41:01 -05:00
Kit Langton	4e56998d3c	fix(cli): harden managed service election (#37645 )	2026-07-18 14:16:55 -04:00
Aiden Cline	d625bc86fc	feat(core): publish pending MCP status during connect (#37605 )	2026-07-18 12:02:21 -05:00
Aiden Cline	5f437a09b0	feat(codemode): native coercion parity in interpreter (#37608 )	2026-07-18 12:01:10 -05:00
opencode-agent[bot]	7d4496eafc	test(core): stabilize shell progress test (#37643 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-18 11:59:24 -05:00
opencode-agent[bot]	1f2de535aa	fix(ai): parse compatible reasoning deltas (#37558 ) Co-authored-by: Aiden Cline <63023139+rekram1-node@users.noreply.github.com>	2026-07-18 10:57:10 -05:00
opencode-agent[bot]	529d55b1c3	fix(core): remove session import cycle (#37596 ) Co-authored-by: James Long <17031+jlongster@users.noreply.github.com>	2026-07-18 13:24:47 +00:00
Aiden Cline	deb5b144c3	test(ai): record MiniMax messages compatibility (#37604 )	2026-07-17 23:22:09 -05:00
opencode-agent[bot]	cd3cca0006	feat(core): add runtime MCP controls (#37308 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com> Co-authored-by: Aiden Cline <aidenpcline@gmail.com>	2026-07-17 22:56:52 -05:00
Aiden Cline	08a7080e11	fix(tui): exit composer picker with up arrow (#37601 )	2026-07-17 22:22:00 -05:00
Dax Raad	f2579c41b6	docs: allow trusted cli installation	2026-07-17 20:49:42 -04:00
Dax Raad	c4830c147d	fix(core): defer cyclic layer dependencies	2026-07-17 20:25:21 -04:00
Dax Raad	22c23cb44c	fix(cli): reduce startup overhead	2026-07-17 20:14:04 -04:00
opencode-agent[bot]	60ce33cde8	fix(cli): simplify service registration lease (#37576 ) Co-authored-by: Dax Raad <826656+thdxr@users.noreply.github.com>	2026-07-17 19:47:17 -04:00
opencode-agent[bot]	6ea8247e0f	fix(cli): elect managed service by port bind (#37572 ) Co-authored-by: Dax Raad <thdxr@users.noreply.github.com>	2026-07-17 23:12:36 +00:00
Aiden Cline	987242b3e8	fix(core): honor OAuth attempt expiration (#37557 )	2026-07-17 16:10:53 -05:00
James Long	fafb04ed59	feat(tui): track hue source identity (#37550 )	2026-07-17 15:38:22 -04:00
Aiden Cline	87d5b27668	feat(codemode): project OpenAPI schema directions (#37361 )	2026-07-17 14:24:50 -05:00
James Long	c7a7900ff2	refactor(tui): migrate workflow views to V2 themes (#37526 )	2026-07-17 15:18:58 -04:00
opencode-agent[bot]	f2a4011371	fix(cli): restore plugin list diagnostics (#37540 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-17 13:42:44 -05:00
Aiden Cline	4bc8faa01c	feat(core): add tool namespaces (#37529 )	2026-07-17 13:14:06 -05:00
Simon Klee	5d5b33f195	cli: rename node package to opencode-node (#37528 )	2026-07-17 19:04:40 +02:00
Kit Langton	3fc06accbd	fix(simulation): normalize named key presses (#37523 )	2026-07-17 12:24:54 -04:00
James Long	677526d72e	refactor(tui): migrate dialog views to V2 themes (#37516 )	2026-07-17 12:17:11 -04:00
Kit Langton	bce9c639d1	feat(tui): expose session composer top slot (#37518 )	2026-07-17 11:55:18 -04:00
Kit Langton	48adb9521c	feat(tui): expose session header slot (#37520 )	2026-07-17 11:55:06 -04:00
opencode-agent[bot]	9b3a4655f1	fix(core): clarify user-executed shell history (#37515 ) Co-authored-by: Aiden Cline <rekram1-node@users.noreply.github.com>	2026-07-17 10:49:02 -05:00
James Long	bd79e24842	fix(tui): raise neutral permission backgrounds (#37513 )	2026-07-17 11:35:02 -04:00
James Long	d67e035c18	refactor(tui): migrate leaf views to V2 themes (#37510 )	2026-07-17 11:19:03 -04:00
Simon Klee	f8470404e3	fix(cli): stabilize Windows ARM64 Node builds (#37503 )	2026-07-17 16:45:14 +02:00
opencode-agent[bot]	651751405d	test(tui): await diff tree context readiness (#37501 ) Co-authored-by: James Long <longster@gmail.com>	2026-07-17 10:41:00 -04:00
Kit Langton	44f7bb71c1	chore: upgrade Effect to beta.98 (#37498 )	2026-07-17 10:31:27 -04:00
James Long	b26d948b76	feat(tui): add hovered theme state (#37404 )	2026-07-17 10:19:42 -04:00
Simon Klee	2180fb8e7b	ci: fix node publish multi-arch install (#37497 )	2026-07-17 16:16:43 +02:00
Kit Langton	3db4458e6c	feat(session): expose transient generation API (#37433 )	2026-07-17 09:25:50 -04:00
Simon Klee	42e2dde739	fix(cli): prevent Node stdout EPIPE failures Keep draining standalone server stdout after reading its readiness message so later server output does not write into a closed pipe. Install the Node CLI broken-pipe handler before loading the main entrypoint. Ignore only EPIPE while preserving all unrelated stdout errors. This prevents Windows Node builds from failing when the TUI prints its exit epilogue after renderer teardown.	2026-07-17 14:46:46 +02:00
Simon Klee	a1b274e6f8	node v2 cli support (#36309 )	2026-07-17 14:45:06 +02:00