fix(stats): align chart dot grid with bars

2026-10-04 14:36:18 +00:00 · 2026-10-01 23:34:44 -06:00
1094 changed files with 16837 additions and 37859 deletions
@@ -18,20 +18,9 @@ jobs:
    steps:
      - name: Checkout repository
        uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4.3.1
-        with:
-          # A pull request checks out its merge into the current base; the first parent is that base.
-          fetch-depth: 2

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

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

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

 concurrency:
@@ -94,6 +94,12 @@ jobs:
          git config --global user.email "bot@opencode.ai"
          git config --global user.name "opencode"

+      - name: Install ffmpeg
+        if: runner.os == 'Linux'
+        run: |
+          sudo apt-get update
+          sudo apt-get install --yes ffmpeg
+
      - name: Cache Turbo
        uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
        with:
@@ -252,13 +258,6 @@ jobs:
          CI: true
        timeout-minutes: 15

-      - name: Run app component tests
-        if: ${{ !cancelled() && env.E2E_ENABLED == 'true' }}
-        run: bun --cwd packages/app test:components
-        env:
-          CI: true
-        timeout-minutes: 15
-
      - name: Upload Playwright artifacts
        if: always() && env.E2E_ENABLED == 'true'
        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
@@ -271,5 +270,3 @@ jobs:
            packages/app/e2e/playwright-report
            packages/session-ui/component-tests/test-results
            packages/session-ui/component-tests/playwright-report
-            packages/app/component-tests/test-results
-            packages/app/component-tests/playwright-report
@@ -63,60 +63,8 @@
        "anti-slop-effect/prefer-effect-match": "warn"
      }
    },
-    {
-      "files": ["packages/gui-extensions/src/*.ts", "packages/gui-extensions/src/*.tsx"],
-      "rules": {
-        "no-restricted-imports": [
-          "error",
-          {
-            "paths": [
-              {
-                "name": "solid-js",
-                "importNames": ["createEffect", "createRenderEffect", "createComputed"],
-                "message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
-              }
-            ]
-          }
-        ]
-      }
-    },
    {
      "files": ["packages/gui-extensions/src/*/**"],
-      "rules": {
-        "no-restricted-imports": [
-          "error",
-          {
-            "paths": [
-              {
-                "name": "solid-js",
-                "importNames": ["createEffect", "createRenderEffect", "createComputed"],
-                "message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
-              }
-            ],
-            "patterns": [
-              {
-                "regex": "^@opencode/(app|desktop)(/|$)",
-                "message": "GUI extensions never import the app or desktop packages. Use the SDK."
-              },
-              {
-                "regex": "^@/",
-                "message": "GUI extensions never import app internals. Use the SDK."
-              },
-              {
-                "group": ["../*/*", "!../*/contract", "!../sdk/*"],
-                "message": "Import another extension only through its contract.ts."
-              },
-              {
-                "regex": "\\.css$",
-                "message": "Import CSS with ?inline and contribute it with ctx.add(Style, css)."
-              }
-            ]
-          }
-        ]
-      }
-    },
-    {
-      "files": ["packages/gui-extensions/src/sdk/**"],
      "rules": {
        "no-restricted-imports": [
          "error",
@@ -33,7 +33,7 @@
    },
    "packages/ai": {
      "name": "@opencode/ai",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@aws-sdk/credential-providers": "3.1057.0",
        "@opencode/schema": "workspace:*",
@@ -55,7 +55,7 @@
    },
    "packages/app": {
      "name": "@opencode/app",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@corvu/drawer": "catalog:",
        "@dnd-kit/abstract": "0.5.0",
@@ -112,17 +112,17 @@
    },
    "packages/cli": {
      "name": "@opencode/cli",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "bin": {
        "opencode": "./bin/opencode.cjs",
        "opencode2": "./bin/opencode2.cjs",
      },
      "dependencies": {
-        "@agentclientprotocol/sdk": "1.6.0",
+        "@agentclientprotocol/sdk": "1.2.1",
        "@clack/core": "1.0.0-alpha.1",
        "@clack/prompts": "1.0.0-alpha.1",
        "@effect/platform-node": "catalog:",
-        "@opencode-ai/pty": "0.2.0",
+        "@opencode-ai/pty": "0.1.13",
        "@opencode/client": "workspace:*",
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -133,7 +133,6 @@
        "@opentui/solid": "catalog:",
        "@parcel/watcher": "2.5.1",
        "@silvia-odwyer/photon-node": "0.3.4",
-        "diff": "catalog:",
        "effect": "catalog:",
        "immer": "11.1.4",
        "jsonc-parser": "3.3.1",
@@ -179,7 +178,7 @@
    },
    "packages/client": {
      "name": "@opencode/client",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/protocol": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -205,7 +204,7 @@
    },
    "packages/codemode": {
      "name": "@opencode/codemode",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "acorn": "8.15.0",
        "effect": "catalog:",
@@ -218,7 +217,7 @@
    },
    "packages/console/app": {
      "name": "@opencode/console-app",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@ibm/plex": "6.4.1",
@@ -254,7 +253,7 @@
    },
    "packages/console/core": {
      "name": "@opencode/console-core",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@aws-sdk/client-sts": "3.782.0",
        "@jsx-email/render": "1.1.1",
@@ -281,7 +280,7 @@
    },
    "packages/console/function": {
      "name": "@opencode/console-function",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@openauthjs/openauth": "0.0.0-20250322224806",
        "@opencode/console-core": "workspace:*",
@@ -298,7 +297,7 @@
    },
    "packages/console/mail": {
      "name": "@opencode/console-mail",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@jsx-email/all": "2.2.3",
        "@jsx-email/cli": "1.4.3",
@@ -322,7 +321,7 @@
    },
    "packages/console/support": {
      "name": "@opencode/console-support",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@opencode/console-core": "workspace:*",
@@ -342,7 +341,7 @@
    },
    "packages/core": {
      "name": "@opencode/core",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@ai-sdk/cohere": "3.0.27",
        "@ai-sdk/gateway": "3.0.104",
@@ -355,7 +354,7 @@
        "@lydell/node-pty": "catalog:",
        "@modelcontextprotocol/client": "2.0.0",
        "@modelcontextprotocol/core": "2.0.0",
-        "@opencode-ai/pty": "0.2.0",
+        "@opencode-ai/pty": "0.1.13",
        "@opencode/ai": "workspace:*",
        "@opencode/codemode": "workspace:*",
        "@opencode/plugin": "workspace:*",
@@ -365,7 +364,7 @@
        "@parcel/watcher": "2.5.1",
        "@silvia-odwyer/photon-node": "0.3.4",
        "@standard-schema/spec": "catalog:",
-        "bun-pty": "0.4.9",
+        "bun-pty": "0.4.8",
        "diff": "catalog:",
        "drizzle-orm": "catalog:",
        "effect": "catalog:",
@@ -411,7 +410,7 @@
    },
    "packages/desktop": {
      "name": "@opencode/desktop",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@zip.js/zip.js": "2.7.62",
        "electron-context-menu": "5.0.0",
@@ -456,7 +455,7 @@
    },
    "packages/enterprise": {
      "name": "@opencode/enterprise",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@hono/standard-validator": "catalog:",
        "@opencode-ai/sdk": "1.18.21",
@@ -493,7 +492,7 @@
    },
    "packages/function": {
      "name": "@opencode/function",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@octokit/auth-app": "8.0.1",
        "@octokit/rest": "catalog:",
@@ -509,7 +508,7 @@
    },
    "packages/gui-extensions": {
      "name": "@opencode/gui-extensions",
-      "version": "2.0.22",
+      "version": "2.0.20",
      "dependencies": {
        "@dnd-kit/abstract": "0.5.0",
        "@dnd-kit/dom": "0.5.0",
@@ -554,7 +553,7 @@
    },
    "packages/http-recorder": {
      "name": "@opencode/http-recorder",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@effect/platform-node-shared": "4.0.0-rc.112",
      },
@@ -573,7 +572,7 @@
    },
    "packages/httpapi-codegen": {
      "name": "@opencode/httpapi-codegen",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "effect": "catalog:",
        "prettier": "3.6.2",
@@ -586,7 +585,7 @@
    },
    "packages/latex": {
      "name": "@opencode/latex",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -600,7 +599,7 @@
    },
    "packages/merman": {
      "name": "@opencode/merman",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -615,7 +614,7 @@
    },
    "packages/plugin": {
      "name": "@opencode/plugin",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@ai-sdk/provider": "3.0.8",
        "@opencode/ai": "workspace:*",
@@ -654,7 +653,7 @@
    },
    "packages/plugin-browser": {
      "name": "@opencode/plugin-browser",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -684,7 +683,7 @@
    },
    "packages/protocol": {
      "name": "@opencode/protocol",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/schema": "workspace:*",
        "effect": "catalog:",
@@ -699,7 +698,7 @@
    },
    "packages/schema": {
      "name": "@opencode/schema",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@standard-schema/spec": "catalog:",
        "effect": "catalog:",
@@ -723,7 +722,7 @@
    },
    "packages/sdk": {
      "name": "@opencode/sdk",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -744,7 +743,7 @@
    },
    "packages/server": {
      "name": "@opencode/server",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@effect/platform-node": "catalog:",
        "@effect/platform-node-shared": "catalog:",
@@ -766,7 +765,7 @@
    },
    "packages/session-ui": {
      "name": "@opencode/session-ui",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode/client": "workspace:*",
@@ -801,7 +800,7 @@
    },
    "packages/simulation": {
      "name": "@opencode/simulation",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/ai": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -821,7 +820,7 @@
    },
    "packages/stats/app": {
      "name": "@opencode/stats-app",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@ibm/plex": "6.4.1",
        "@kobalte/core": "catalog:",
@@ -855,7 +854,7 @@
    },
    "packages/stats/core": {
      "name": "@opencode/stats-core",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@aws-sdk/client-athena": "3.933.0",
        "@planetscale/database": "1.19.0",
@@ -874,7 +873,7 @@
    },
    "packages/stats/server": {
      "name": "@opencode/stats-server",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@aws-sdk/client-firehose": "3.933.0",
        "@effect/platform-node": "catalog:",
@@ -920,7 +919,7 @@
    },
    "packages/theme": {
      "name": "@opencode/theme",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opentui/core": "catalog:",
        "effect": "catalog:",
@@ -934,7 +933,7 @@
    },
    "packages/tui": {
      "name": "@opencode/tui",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -968,7 +967,7 @@
    },
    "packages/ui": {
      "name": "@opencode/ui",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@pierre/diffs": "catalog:",
@@ -1003,7 +1002,7 @@
    },
    "packages/util": {
      "name": "@opencode/util",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@effect/opentelemetry": "catalog:",
        "@effect/platform-node": "catalog:",
@@ -1041,7 +1040,7 @@
    },
    "packages/web": {
      "name": "@opencode/web",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "@astrojs/cloudflare": "12.6.3",
        "@astrojs/markdown-remark": "6.3.1",
@@ -1082,7 +1081,7 @@
    },
    "services/update": {
      "name": "@opencode/update",
-      "version": "2.0.22",
+      "version": "2.0.21",
      "dependencies": {
        "jose": "6.0.11",
        "semver": "catalog:",
@@ -1231,7 +1230,7 @@

    "@adobe/css-tools": ["@adobe/css-tools@4.5.0", "", {}, "sha512-6OzddxPio9UiWTCemp4N8cYLV2ZN1ncRnV1cVGtve7dhPOtRkleRyx32GQCYSwDYgaHU3USMm84tNsvKzRCa1Q=="],

-    "@agentclientprotocol/sdk": ["@agentclientprotocol/sdk@1.6.0", "", { "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" } }, "sha512-XxXrmX7aZkDgOB0Rg9cu+ZFyiUUc5lF2n9seO3Gc4OR+MTdfZOwIqF6m3LvsmmM8K3qgPmXkDH8/IFM2u9vdcQ=="],
+    "@agentclientprotocol/sdk": ["@agentclientprotocol/sdk@1.2.1", "", { "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" } }, "sha512-jwYUdOQR7tc+Zfch53VL4JJyUNK/46q03uUTYb+PjECsmnNl94XFXOfYLJ8RBpMNidXd1rpOAVgb0vqD98xImA=="],

    "@ai-sdk/cohere": ["@ai-sdk/cohere@3.0.27", "", { "dependencies": { "@ai-sdk/provider": "3.0.8", "@ai-sdk/provider-utils": "4.0.21" }, "peerDependencies": { "zod": "^3.25.76 || ^4.1.8" } }, "sha512-OqcCq2PiFY1dbK/0Ck45KuvE8jfdxRuuAE9Y5w46dAk6U+9vPOeg1CDcmR+ncqmrYrhRl3nmyDttyDahyjCzAw=="],

@@ -2167,19 +2166,19 @@

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

-    "@opencode-ai/pty": ["@opencode-ai/pty@0.2.0", "", { "optionalDependencies": { "@opencode-ai/pty-darwin-arm64": "0.2.0", "@opencode-ai/pty-darwin-x64": "0.2.0", "@opencode-ai/pty-linux-arm64-gnu": "0.2.0", "@opencode-ai/pty-linux-arm64-musl": "0.2.0", "@opencode-ai/pty-linux-x64-gnu": "0.2.0", "@opencode-ai/pty-linux-x64-musl": "0.2.0" }, "bin": { "opencode-pty": "bin/opencode-pty.js" } }, "sha512-pV86urAwinpwFXX8AJlOf8S9CVJhGsV+11I/J6TcxMW0c7u6LgeODzdj/BVBC6jUhsG2aKDxg8rACMcDCy3HiA=="],
+    "@opencode-ai/pty": ["@opencode-ai/pty@0.1.13", "", { "optionalDependencies": { "@opencode-ai/pty-darwin-arm64": "0.1.13", "@opencode-ai/pty-darwin-x64": "0.1.13", "@opencode-ai/pty-linux-arm64-gnu": "0.1.13", "@opencode-ai/pty-linux-arm64-musl": "0.1.13", "@opencode-ai/pty-linux-x64-gnu": "0.1.13", "@opencode-ai/pty-linux-x64-musl": "0.1.13" }, "bin": { "opencode-pty": "bin/opencode-pty.js" } }, "sha512-WPCN8h8HaZhhUcrMG0zu+4D9vco0EZiEg/gCF1K3JPRN6UsHMiXq1HVIy5IlyfcoyjfViRmQmXYE4AuU3laBjA=="],

-    "@opencode-ai/pty-darwin-arm64": ["@opencode-ai/pty-darwin-arm64@0.2.0", "", { "os": "darwin", "cpu": "arm64" }, "sha512-2y6xrktb2J7rRk+mzAJHA8cCbWhC4Lo2zJ66t9ad59qFhL5nzAPfpEOwnyvvFqhxebHNvL08Mp64M9IHnM0aiA=="],
+    "@opencode-ai/pty-darwin-arm64": ["@opencode-ai/pty-darwin-arm64@0.1.13", "", { "os": "darwin", "cpu": "arm64" }, "sha512-fVtQZqVLBuJx/aB+5ojfmQifS1KMc9gxlxpFQ6bxEFU8tn8xHQTiFPaNroZgOtaw7I4ceGyx/eXieK1wp68yAA=="],

-    "@opencode-ai/pty-darwin-x64": ["@opencode-ai/pty-darwin-x64@0.2.0", "", { "os": "darwin", "cpu": "x64" }, "sha512-XVQwK9+KgVGYunCYPCCBf1Or0z6zSkzjgfdJd7dEe/LOFg5vmMkOfSB9dCXnoRCWGviWYk7xd07iFIFOgyj5Ig=="],
+    "@opencode-ai/pty-darwin-x64": ["@opencode-ai/pty-darwin-x64@0.1.13", "", { "os": "darwin", "cpu": "x64" }, "sha512-b/tAEm0hCMXraPM9cxR8Rg7X1UBZInRTaxWAS4Ht9eH1nWj1rANOLvHWiWX/vVh5TB0Ubg8bWPu4B0nZkEHROQ=="],

-    "@opencode-ai/pty-linux-arm64-gnu": ["@opencode-ai/pty-linux-arm64-gnu@0.2.0", "", { "os": "linux", "cpu": "arm64" }, "sha512-TPVGCQk5E65IY3ipcpd17rwKehdvXcXEYRhhGzok/6Dske69ei2S+ERz7NXZ8cKFAvbiiT771HHM+XyVYAl+7A=="],
+    "@opencode-ai/pty-linux-arm64-gnu": ["@opencode-ai/pty-linux-arm64-gnu@0.1.13", "", { "os": "linux", "cpu": "arm64" }, "sha512-I124aSYBBjpGZnYExHfIajkvVK1FiK+//OJBGdqqFp5pas2Oruq4O8tv+pMoxomZIYh2ce/QhOOYLHRwXsthTg=="],

-    "@opencode-ai/pty-linux-arm64-musl": ["@opencode-ai/pty-linux-arm64-musl@0.2.0", "", { "os": "linux", "cpu": "arm64" }, "sha512-iH6/liY7xN1OXVD9eGzdH11BVGvnpPsH5Z1Unz0Pn9EzkPFf28oDNKNyeXV0xIAP53oiYp8gpRq2PADNwbVsTg=="],
+    "@opencode-ai/pty-linux-arm64-musl": ["@opencode-ai/pty-linux-arm64-musl@0.1.13", "", { "os": "linux", "cpu": "arm64" }, "sha512-feWsfKpaDytGJzutoK43GqQwVghG2vHZt6BE/ydPZNuqIrySQ/6JfliUAMwn5BWs/Ky7ouSwKHCyAVeukusSvg=="],

-    "@opencode-ai/pty-linux-x64-gnu": ["@opencode-ai/pty-linux-x64-gnu@0.2.0", "", { "os": "linux", "cpu": "x64" }, "sha512-GhdrmbUzxGHRfWvt1qutgVD4HLb7aSBsgWGjFsc6k8HjO5ZbdaC3ScRyd512YAAG5KAROLKZ6+0SEBsm5xFYlA=="],
+    "@opencode-ai/pty-linux-x64-gnu": ["@opencode-ai/pty-linux-x64-gnu@0.1.13", "", { "os": "linux", "cpu": "x64" }, "sha512-jliNgsevGuxfIeX7eyzjHhrJkF8uEUPnDLbF2v16uv69FhEHrraf7jyWkxazMP6rNvn2CGtwMMc4BXPS5pzjhg=="],

-    "@opencode-ai/pty-linux-x64-musl": ["@opencode-ai/pty-linux-x64-musl@0.2.0", "", { "os": "linux", "cpu": "x64" }, "sha512-EbHchDsMmL5aOReIoo8NvQkKnyhyKmoL2RleF2JYF76va3FKuksmwsOBgQJh54i+QA4Fd0+9x54Q+2fJOzPiRQ=="],
+    "@opencode-ai/pty-linux-x64-musl": ["@opencode-ai/pty-linux-x64-musl@0.1.13", "", { "os": "linux", "cpu": "x64" }, "sha512-rXDpidW66gz2b2M/NbUN8ZKmAxaJcASnuHATeXevlrFdiPUv8uJwvkRd6Pla1fp01Q65MkBmgRa7Q9c+H1PlzA=="],

    "@opencode-ai/schema": ["@opencode-ai/schema@0.0.0-beta-18050", "", { "dependencies": { "@standard-schema/spec": "1.1.0", "effect": "4.0.0-rc.111" } }, "sha512-/D6VXaWlytTXR3IOiMLIKuPcfp7FQNUzRPm9z3K7UBFd1Bw4q/WZksaf5RVcBGz+0YRxYMc1V4D7MFlceSgtyg=="],

@@ -3549,7 +3548,7 @@

    "bun-ffi-structs": ["bun-ffi-structs@0.3.1", "", { "peerDependencies": { "typescript": "^5" } }, "sha512-3gM7PpVWLyrwxWjcilSiGuhWanhZivvo6l0u573NziPH6f/gwk6McbaYgn7oJWov6pKGRTDbrg94W5DcJsKTtQ=="],

-    "bun-pty": ["bun-pty@0.4.9", "", {}, "sha512-IUF/B3FANo8vIQ775Zt7Er7lphMpYMhLkes45am2WE8FaVI7KRYtj1rQwliZ18b6GpNzBNWcl7sz9QT5wDFBeQ=="],
+    "bun-pty": ["bun-pty@0.4.8", "", {}, "sha512-rO70Mrbr13+jxHHHu2YBkk2pNqrJE5cJn29WE++PUr+GFA0hq/VgtQPZANJ8dJo6d7XImvBk37Innt8GM7O28w=="],

    "bun-types": ["bun-types@1.4.2", "", { "dependencies": { "@types/node": "*" } }, "sha512-bxV1FgK7yBIzjRe5zBozIM4Bem11ZJcCXSrjWRG3YWLt8yFDePu4cLjpebO8OvPeIE9trbyPF4fuj3Cia4Fj3w=="],

@@ -13,12 +13,7 @@
  opencode,
 }:
 let
-  electronPin =
-    (lib.pipe ../packages/desktop/package.json [
-      builtins.readFile
-      builtins.fromJSON
-    ]).devDependencies.electron;
-  electron = callPackage ./electron.nix { inherit electronPin; };
+  electron = callPackage ./electron.nix { };
 in
 stdenv.mkDerivation (finalAttrs: {
  pname = "opencode-desktop";
@@ -40,8 +35,6 @@ stdenv.mkDerivation (finalAttrs: {
    copyDesktopItems
  ]
  ++ lib.optionals stdenv.hostPlatform.isDarwin [
-    darwin.cctools
-    darwin.sigtool
    # Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
    darwin.autoSignDarwinBinariesHook
  ];
@@ -73,7 +66,7 @@ stdenv.mkDerivation (finalAttrs: {
    ''
    # https://github.com/electron/electron/issues/31121
    # mac builds use a .app bundle which doesnt have this issue
-    + lib.optionalString stdenv.hostPlatform.isLinux ''
+    + lib.optionalString stdenv.isLinux ''
      substituteInPlace \
        packages/desktop/src/main/windows/appearance.ts \
        packages/desktop/src/main/service/desktop-cli.ts \
@@ -81,7 +74,6 @@ stdenv.mkDerivation (finalAttrs: {
    '';

  preBuild = ''
-    echo "electron ${electron.version} from nixpkgs ${lib.version}, package.json pins ${electronPin}"
    cp -r "${electron.dist}" $HOME/.electron-dist
    chmod -R u+w $HOME/.electron-dist

@@ -97,15 +89,8 @@ stdenv.mkDerivation (finalAttrs: {

    export OPENCODE_CLI_DIST="$TMPDIR/desktop-cli"
    cli_package=$(bun -e 'import { getCurrentCli } from "./scripts/utils.ts"; console.log(getCurrentCli().package.replace("@opencode/", ""))')
-    # copyBuiltCliToResources joins this dist with the npm package name getCurrentCli()
-    # reports, not the Nix build's name. It reads only .version from the manifest and
-    # writes it as opencode-cli.version beside the binary.
    mkdir -p "$OPENCODE_CLI_DIST/$cli_package/bin"
    cp ${lib.getExe opencode} "$OPENCODE_CLI_DIST/$cli_package/bin/opencode"
-    # OPENCODE_VERSION is what the bundled CLI prints for --version, so the manifest
-    # and the executable cannot drift.
-    bun -e 'await Bun.write(process.argv[1], JSON.stringify({ version: process.env.OPENCODE_VERSION }) + "\n")' \
-      "$OPENCODE_CLI_DIST/$cli_package/package.json"

    bun run build
    npx electron-builder --dir \
@@ -153,13 +138,6 @@ stdenv.mkDerivation (finalAttrs: {
    "libc.musl-x86_64.so.1"
  ];

-  passthru = {
-    # electronVersion is what ships; electronPin is what packages/desktop/package.json
-    # asks for. They differ whenever nixpkgs carries no release of the pinned minor.
-    electronVersion = electron.version;
-    inherit electronPin;
-  };
-
  meta = {
    description = "OpenCode Desktop App";
    mainProgram = "opencode-desktop";
@@ -1,10 +1,12 @@
-{ lib, pkgs, electronPin }:
+{ callPackage, path }:
 let
-  # Nixpkgs owns the release hashes, so bumping the pin no longer means editing this repo. Only the
-  # major is delegated, so what gets built trails the pin whenever nixpkgs has not shipped it yet.
-  # That is safe: the bundle ships one native addon, node-pty's Node-API prebuild, and
-  # only the win32 WSL runtime loads it, so nothing in the main process binds the
-  # Electron ABI.
-  major = lib.versions.major electronPin;
+  version = (builtins.fromJSON (builtins.readFile ../packages/desktop/package.json)).devDependencies.electron;
 in
-pkgs."electron_${major}-bin" or (throw "nixpkgs ${lib.version} carries no prebuilt electron ${major}: run `nix flake update nixpkgs`, or pin a major nixpkgs still carries")
+(callPackage (path + "/pkgs/development/tools/electron/binary/generic.nix") { }) version {
+  # Electron 42.10.1 SHASUMS256.txt; update with the desktop package version.
+  aarch64-linux = "20e68d6c4e47f3ebf59de7c6b1f8b8bec6a6ebda6a451132f9b465f3f13ce467";
+  x86_64-linux = "2452b27112d92387471fa2488aafac85d79ea3f2ee1216c0abd5150d6c12362b";
+  aarch64-darwin = "ac7194a3dfd81930ba35355c01620262c1254752859b42dcb8f4b9e4d174a871";
+  # fetchzip hashes the unpacked headers, not the release tarball.
+  headers = "sha256-4eUy3BZVvxTl7KUOsxio7769lL6ag/ecbeK+qLURWMI=";
+}
@@ -1,7 +1,7 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-2RlbJRTEKSliuUbAE2lAktX63JFR/RKAuLkcCou8wb4=",
-    "aarch64-linux": "sha256-P7DAE018lTJNGmttg87U9oaTAuw/wHlnMStdnXYKCr0=",
-    "aarch64-darwin": "sha256-N+NfV1ObOTnW+ez7As+CS+6ci/iRGCQ6cslvyQFCp6E="
+    "x86_64-linux": "sha256-yCdtDQsXERjfL9bJg7YXNloMBOPwFkPMFVNAzXlarBM=",
+    "aarch64-linux": "sha256-iQ1bLIszETcFoD4CENpoaDZJZF/KBKZFeTp9r7ogJ9Y=",
+    "aarch64-darwin": "sha256-G7oIrTXEFQ5iEF8KSpA4xJPw9xwqRDpbIR472iIoqC4="
  }
 }
@@ -12,7 +12,7 @@
  installShellFiles,
  versionCheckHook,
  writableTmpDirAsHomeHook,
-  node_modules ? callPackage ./node_modules.nix { },
+  node_modules ? callPackage ./node-modules.nix { },
 }:
 stdenvNoCC.mkDerivation (finalAttrs: {
  pname = "opencode";
@@ -85,30 +85,14 @@ stdenvNoCC.mkDerivation (finalAttrs: {
  '';

  postInstall = lib.optionalString (stdenvNoCC.buildPlatform.canExecute stdenvNoCC.hostPlatform) ''
-    # v2 dropped the `completion` subcommand; --completions is the global flag.
-    # --completions also accepts sh, which emits the same script as bash.
-    # staged to files, substitute below rejects anything that is not a regular file
-    $out/bin/opencode --completions bash > opencode.bash
-    $out/bin/opencode --completions zsh > _opencode
-    $out/bin/opencode --completions fish > opencode.fish
-
+    # trick yargs into also generating zsh completions
    installShellCompletion --cmd opencode \
-      --bash opencode.bash \
-      --fish opencode.fish \
-      --zsh _opencode
-
-    # OPENCODE_CLI_NAME is a build-time define, so the opencode2 copies are
-    # renamed rather than regenerated. --replace-fail is a global literal
-    # substitution, so any lowercase opencode that later appears in a
-    # description or help text ships as opencode2 in the opencode2 copy.
-    substitute opencode.bash opencode2.bash --replace-fail opencode opencode2
-    substitute _opencode _opencode2 --replace-fail opencode opencode2
-    substitute opencode.fish opencode2.fish --replace-fail opencode opencode2
+      --bash <($out/bin/opencode completion) \
+      --zsh <(SHELL=/bin/zsh $out/bin/opencode completion)

    installShellCompletion --cmd opencode2 \
-      --bash opencode2.bash \
-      --fish opencode2.fish \
-      --zsh _opencode2
+      --bash <($out/bin/opencode2 completion) \
+      --zsh <(SHELL=/bin/zsh $out/bin/opencode2 completion)
  '';

  nativeInstallCheckInputs = [
@@ -2,7 +2,7 @@
  "$schema": "https://json.schemastore.org/package.json",
  "name": "opencode",
  "description": "AI-powered development tool",
-  "version": "2.0.22",
+  "version": "2.0.21",
  "private": true,
  "type": "module",
  "packageManager": "bun@1.4.2",
@@ -18,8 +18,7 @@
    "dev:www": "bun run --cwd services/www dev",
    "dev:storybook": "bun --cwd packages/storybook storybook",
    "bench:devex": "bun run --cwd packages/app test:bench:devex",
-    "lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml && bun script/sdk-docs.ts",
-    "lint:changed": "bun script/lint-changed.ts",
+    "lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml",
    "lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/util/src packages/core/src packages/server/src packages/protocol/src packages/cli/src",
    "lint:effect-simplifications": "ast-grep scan -c script/ast-grep/effect-simplifications/sgconfig.yml --off=unused-suppression packages",
    "test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
@@ -27,31 +27,6 @@ Run `LLM.stream(...)` instead of `generate` when you want incremental `LLMEvent`
 `LLM.request(...)`. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses,
 Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.

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

@@ -1248,7 +1223,7 @@ const gateway = CloudflareAIGateway.configure({
 }).model("workers-ai/@cf/meta/llama-3.1-8b-instruct")
 ```

-Included LLM providers: OpenAI, Anthropic, Google (Gemini), Google Vertex, Amazon Bedrock, Azure OpenAI, Baseten, Cerebras, Cohere, Cloudflare AI Gateway, Cloudflare Workers AI, DeepInfra, DeepSeek, Fireworks, Groq, Mistral, OpenRouter, TogetherAI, and xAI. Z.ai currently exposes image generation. Generic Chat Completions, Responses, and Anthropic Messages-compatible entrypoints support custom endpoints.
+Included LLM providers: OpenAI, Anthropic, Google (Gemini), Google Vertex, Amazon Bedrock, Azure OpenAI, Baseten, Cerebras, Cloudflare AI Gateway, Cloudflare Workers AI, DeepInfra, DeepSeek, Fireworks, Groq, Mistral, OpenRouter, TogetherAI, and xAI. Z.ai currently exposes image generation. Generic Chat Completions, Responses, and Anthropic Messages-compatible entrypoints support custom endpoints.

 Each named provider owns its module, endpoint, authentication, and route setup. Providers with the same wire format compose the shared protocol directly:

@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "2.0.22",
+  "version": "2.0.21",
  "name": "@opencode/ai",
  "type": "module",
  "license": "MIT",
@@ -38,7 +38,6 @@ const resolve = (policy: CachePolicy | undefined): CachePolicyObject => {
 // prefix caching, Gemini's implicit + out-of-band CachedContent). Skip the
 // whole policy pass for these — emitting hints would be harmless but pointless.
 const RESPECTS_INLINE_HINTS = new Set([
-  "alibaba-chat",
  "alibaba-messages",
  "anthropic-messages",
  "anthropic-compatible-messages",
@@ -50,18 +49,16 @@ const RESPECTS_INLINE_HINTS = new Set([
  "zai-coding-messages",
  "bedrock-converse",
  "openrouter",
-  "digitalocean",
 ])

 // OpenRouter upstreams other than Anthropic and Alibaba Qwen cache without breakpoints. Gemini uses only the last
 // breakpoint, so a conversation-tail breakpoint writes a new cache every step and costs more than none. Qwen ignores
 // breakpoints on tool definitions and caches tools with the system prompt.
-const QWEN: CachePolicyObject = { system: true, messages: { tail: 1 } }
 const openRouterPolicy = (modelID: string): CachePolicyObject => {
  // `~anthropic/claude-sonnet-latest` style IDs are OpenRouter aliases for the latest model in a family.
  const id = modelID.replace(/^~/, "")
  if (id.startsWith("anthropic/")) return AUTO
-  if (id.startsWith("qwen/")) return QWEN
+  if (id.startsWith("qwen/")) return { system: true, messages: { tail: 1 } }
  return NONE
 }

@@ -173,11 +170,7 @@ export const applyCachePolicy = (request: LLMRequest): LLMRequest => {
  const policy =
    request.model.route.id === "openrouter" && (request.cache === undefined || request.cache === "auto")
      ? openRouterPolicy(request.model.id)
-      : request.model.route.id === "alibaba-chat" && (request.cache === undefined || request.cache === "auto")
-        ? request.model.id.toLowerCase().startsWith("qwen")
-          ? QWEN
-          : NONE
-        : resolve(request.cache)
+      : resolve(request.cache)
  if (!policy.tools && !policy.system && !policy.messages) return request

  const hint = makeHint(policy.ttlSeconds)
@@ -3,7 +3,6 @@ import { Protocol } from "../route/protocol.js"
 import type { LanguageModelCompatibility } from "../schema/index.js"
 import { OpenAIChat } from "./openai-chat.js"
 import { JsonObject, ProviderShared } from "./shared.js"
-import { cacheControl } from "./utils/cache.js"
 import { OpenResponsesOptions } from "./utils/open-responses-options.js"

 export type ReasoningEffort = OpenResponsesOptions.ReasoningEffort
@@ -69,7 +68,7 @@ export const protocol = Protocol.make({
    from: Effect.fn("AlibabaChat.fromRequest")(function* (req) {
      const opts = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(req.providerOptions ?? {})
      return {
-        ...(yield* OpenAIChat.fromRequest(req, { cacheControl: cacheControl() })),
+        ...(yield* OpenAIChat.protocol.body.from(req)),
        enable_thinking: opts.enableThinking,
        // Alibaba also rejects an explicit budget that is not below `max_completion_tokens`.
        thinking_budget:
@@ -1,7 +1,7 @@
 import { Effect, Schema } from "effect"
 import { Protocol } from "../route/protocol.js"
 import { OpenResponses } from "./open-responses.js"
-import { JsonObject, ProviderShared } from "./shared.js"
+import { JsonObject, optionalArray, ProviderShared } from "./shared.js"
 import { OpenResponsesOptions } from "./utils/open-responses-options.js"
 import { ResponsesHostedTools } from "./utils/responses-hosted-tools.js"

@@ -25,6 +25,8 @@ const WebExtractorItem = Schema.StructWithRest(
 )
 const Body = Schema.Struct({
  ...OpenResponses.coreFields,
+  input: Schema.Array(Schema.Union([OpenResponses.InputItem, WebExtractorItem])),
+  tools: optionalArray(Schema.Union([OpenResponses.Tool, NativeTool])),
  enable_thinking: Options.fields.enableThinking,
  previous_response_id: Options.fields.previousResponseId,
  conversation: Options.fields.conversation,
@@ -50,7 +52,7 @@ export const protocol = Protocol.make({
      const opts = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(req.providerOptions ?? {})
      const body = yield* OpenResponses.fromRequestWithAdapter(req, adapter)
      const choice = body.tool_choice
-      return {
+      return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))({
        ...body,
        enable_thinking: opts.enableThinking,
        previous_response_id: opts.previousResponseId,
@@ -60,7 +62,7 @@ export const protocol = Protocol.make({
          typeof choice === "object" && choice.type === "function"
            ? { type: "allowed_tools" as const, mode: "required" as const, tools: [choice] }
            : choice,
-      }
+      })
    }),
  },
  stream: {
@@ -807,12 +807,15 @@ const requireThinkingSignature = (request: LLMRequest) => {
 // Mid-conversation system messages became available with Opus 4.8 and version
 // 5 of the other supported Claude families. Treat later family versions as
 // compatible without assuming that every Anthropic Messages model is Claude.
-// Opus 4.8 and every Claude 5 model accept mid-conversation system messages; later versions inherit support.
 const supportsNativeSystemUpdates = (request: LLMRequest) => {
-  const version = claudeVersion(String(request.model.id))
-  if (version === undefined) return false
-  if (version.family === "opus" && version.major === 4) return version.minor >= 8
-  return version.major >= 5
+  const match = /(?:^|[./])claude-(fable|haiku|mythos|opus|sonnet)-(\d+)(?:[.-](\d+))?/.exec(
+    String(request.model.id).toLowerCase(),
+  )
+  if (!match) return false
+  const major = Number(match[2])
+  if (match[1] !== "opus") return major >= 5
+  if (major !== 4) return major >= 5
+  return match[3] !== undefined && match[3].length <= 2 && Number(match[3]) >= 8
 }

 const endsInServerToolUse = (message: LLMRequest["messages"][number]) => {
@@ -989,13 +992,13 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
  return messages
 })

-// Per-turn effort started with Claude Opus 5 and every Claude 5.1 model; later versions of any family inherit it.
 const supportsEffortUpdates = (model: LLMRequest["model"]) => {
  const override = model.compatibility?.supportsEffortUpdates
  if (override !== undefined) return override
  const version = claudeVersion(model.id)
  if (version === undefined) return false
-  if (version.family === "opus" && version.major >= 5) return true
+  if (version.family === "opus") return version.major >= 5
+  if (version.family !== "fable" && version.family !== "mythos") return false
  return version.major > 5 || (version.major === 5 && version.minor >= 1)
 }

@@ -319,9 +319,6 @@ const lowerToolResult = Effect.fn("BedrockConverse.lowerToolResult")(function* (
  } satisfies BedrockToolResultBlock
 })

-// Keep Claude and Nova tool-result images inline; put other models' images beside the result.
-const keepToolImagesInline = (id: string) => id.includes("anthropic.claude-") || id.includes("amazon.nova-")
-
 const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
  request: LLMRequest,
  breakpoints: BedrockCache.Breakpoints,
@@ -331,19 +328,8 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
  // Mistral can reject replay IDs even when they satisfy Converse's broader ID syntax.
  const normalizeID = request.model.id.includes("mistral.") ? MistralToolID.normalizer(request) : (id: string) => id
  const providerMetadataKey = request.model.route.providerMetadataKey ?? String(request.model.provider)
-  const hoistImages = !keepToolImagesInline(request.model.id)
-  // Bedrock expects parallel tool results before any images hoisted beside them.
-  const pendingImages: BedrockMedia.ImageBlock[] = []
-  const flushImages = () => {
-    if (pendingImages.length === 0) return
-    const previous = messages.at(-1)
-    if (previous?.role === "user")
-      messages[messages.length - 1] = { role: "user", content: [...previous.content, ...pendingImages] }
-    pendingImages.length = 0
-  }

  for (const message of request.messages) {
-    if (message.role !== "tool") flushImages()
    if (message.role === "system") {
      const part = yield* ProviderShared.wrappedSystemUpdate("Bedrock Converse", message)
      const content = textWithCache(breakpoints, part.text, part.cache)
@@ -417,22 +403,7 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
    for (const part of message.content) {
      if (!ProviderShared.supportsContent(part, ["tool-result"]))
        return yield* ProviderShared.unsupportedContent("Bedrock Converse", "tool", ["tool-result"])
-      const result = yield* lowerToolResult(part, documentNames, normalizeID)
-      const images: BedrockMedia.ImageBlock[] = hoistImages
-        ? result.toolResult.content.filter((item) => "image" in item)
-        : []
-      const nonImageContent = result.toolResult.content.filter((item) => !("image" in item))
-      content.push(
-        images.length === 0
-          ? result
-          : {
-              toolResult: {
-                ...result.toolResult,
-                content: nonImageContent.length > 0 ? nonImageContent : [{ text: "See attached image." }],
-              },
-            },
-      )
-      pendingImages.push(...images)
+      content.push(yield* lowerToolResult(part, documentNames, normalizeID))
      const cachePoint = BedrockCache.block(breakpoints, part.cache)
      if (cachePoint) content.push(cachePoint)
    }
@@ -442,7 +413,6 @@ const lowerMessages = Effect.fn("BedrockConverse.lowerMessages")(function* (
    else messages.push({ role: "user", content })
  }

-  flushImages()
  return messages
 })

@@ -1,334 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Route } from "../route/client.js"
-import { Endpoint } from "../route/endpoint.js"
-import { Framing } from "../route/framing.js"
-import { Protocol } from "../route/protocol.js"
-import { LLMEvent, Usage, type FinishReasonDetails, type LLMRequest } from "../schema/index.js"
-import { ProviderShared } from "./shared.js"
-import { Lifecycle } from "./utils/lifecycle.js"
-import { ToolStream } from "./utils/tool-stream.js"
-
-const ADAPTER = "cohere-chat"
-export const DEFAULT_BASE_URL = "https://api.cohere.com/v2"
-
-const Options = Schema.Struct({
-  thinking: Schema.optional(
-    Schema.Struct({
-      type: Schema.optional(Schema.Literals(["enabled", "disabled"])),
-      tokenBudget: Schema.optional(Schema.Int.check(Schema.isGreaterThan(0))),
-    }),
-  ),
-})
-export type ProviderOptionsInput = Schema.Schema.Type<typeof Options>
-
-const Content = Schema.Union([
-  Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("thinking"), thinking: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("image_url"), image_url: Schema.Struct({ url: Schema.String }) }),
-])
-const ToolCall = Schema.Struct({
-  id: Schema.String,
-  type: Schema.Literal("function"),
-  function: Schema.Struct({ name: Schema.String, arguments: Schema.String }),
-})
-const Message = Schema.Struct({
-  role: Schema.Literals(["system", "user", "assistant", "tool"]),
-  content: Schema.optional(Schema.Union([Schema.String, Schema.Array(Content)])),
-  tool_calls: Schema.optional(Schema.Array(ToolCall)),
-  tool_call_id: Schema.optional(Schema.String),
-  tool_plan: Schema.optional(Schema.String),
-})
-const Body = Schema.Struct({
-  model: Schema.String,
-  messages: Schema.Array(Message),
-  stream: Schema.Literal(true),
-  tools: Schema.optional(
-    Schema.Array(
-      Schema.Struct({
-        type: Schema.Literal("function"),
-        function: Schema.Struct({
-          name: Schema.String,
-          description: Schema.optional(Schema.String),
-          parameters: Schema.Unknown,
-        }),
-      }),
-    ),
-  ),
-  tool_choice: Schema.optional(Schema.Literals(["NONE", "REQUIRED"])),
-  thinking: Schema.optional(Schema.Struct({ type: Schema.String, token_budget: Schema.optional(Schema.Number) })),
-  max_tokens: Schema.optional(Schema.Number),
-  temperature: Schema.optional(Schema.Number),
-  p: Schema.optional(Schema.Number),
-  k: Schema.optional(Schema.Number),
-  seed: Schema.optional(Schema.Number),
-  stop_sequences: Schema.optional(Schema.Array(Schema.String)),
-  frequency_penalty: Schema.optional(Schema.Number),
-  presence_penalty: Schema.optional(Schema.Number),
-})
-const TokenCounts = Schema.Struct({
-  input_tokens: Schema.optional(Schema.Number),
-  output_tokens: Schema.optional(Schema.Number),
-  reasoning_tokens: Schema.optional(Schema.Number),
-})
-const NativeUsage = Schema.Struct({
-  tokens: Schema.optional(TokenCounts),
-  billed_units: Schema.optional(TokenCounts),
-  cached_tokens: Schema.optional(Schema.Number),
-})
-const Event = Schema.Union([
-  Schema.Struct({ type: Schema.Literal("message-start") }),
-  Schema.Struct({
-    type: Schema.Literals(["content-start", "content-delta"]),
-    index: Schema.Number,
-    delta: Schema.Struct({
-      message: Schema.Struct({
-        content: Schema.Struct({ text: Schema.optional(Schema.String), thinking: Schema.optional(Schema.String) }),
-      }),
-    }),
-  }),
-  Schema.Struct({ type: Schema.Literal("content-end"), index: Schema.Number }),
-  Schema.Struct({
-    type: Schema.Literal("tool-plan-delta"),
-    delta: Schema.Struct({ message: Schema.Struct({ tool_plan: Schema.String }) }),
-  }),
-  Schema.Struct({
-    type: Schema.Literals(["tool-call-start", "tool-call-delta"]),
-    index: Schema.Number,
-    delta: Schema.Struct({
-      message: Schema.Struct({
-        tool_calls: Schema.Struct({
-          id: Schema.optional(Schema.String),
-          function: Schema.Struct({ name: Schema.optional(Schema.String), arguments: Schema.optional(Schema.String) }),
-        }),
-      }),
-    }),
-  }),
-  Schema.Struct({ type: Schema.Literal("tool-call-end"), index: Schema.Number }),
-  Schema.Struct({
-    type: Schema.Literal("message-end"),
-    delta: Schema.Struct({ finish_reason: Schema.String, usage: Schema.optional(NativeUsage) }),
-  }),
-  // Citation output is outside this basic chat surface.
-  Schema.Struct({ type: Schema.Literals(["citation-start", "citation-end"]) }),
-])
-type Event = typeof Event.Type
-type State = {
-  readonly lifecycle: Lifecycle.State
-  readonly tools: ToolStream.State<number>
-  readonly finished: boolean
-}
-
-const TOOL_CHOICE = { auto: undefined, none: "NONE", required: "REQUIRED", tool: "REQUIRED" } as const
-
-const fromRequest = Effect.fn("CohereChat.fromRequest")(function* (request: LLMRequest) {
-  const options = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(request.providerOptions ?? {})
-  const flattened = ProviderShared.flattenToolRequest(request)
-  const messages: (typeof Message.Type)[] = request.system.length
-    ? [
-        {
-          role: "system",
-          content:
-            request.system.length === 1
-              ? request.system[0].text
-              : request.system.map((part) => ({ type: "text", text: part.text })),
-        },
-      ]
-    : []
-  for (const message of flattened.request.messages) {
-    if (message.role === "system") {
-      messages.push({ role: "user", content: (yield* ProviderShared.wrappedSystemUpdate("Cohere Chat", message)).text })
-      continue
-    }
-    if (message.role === "tool") {
-      for (const part of message.content) {
-        if (part.type !== "tool-result")
-          return yield* ProviderShared.unsupportedContent("Cohere Chat", "tool", ["tool-result"])
-        if (part.result.type === "content" && part.result.value.some((item) => item.type === "file"))
-          return yield* ProviderShared.invalidRequest("Cohere Chat does not support file content in tool results")
-        messages.push({ role: "tool", tool_call_id: part.id, content: ProviderShared.toolResultText(part) })
-      }
-      continue
-    }
-    const content: (typeof Content.Type)[] = []
-    const calls: (typeof ToolCall.Type)[] = []
-    const plans: string[] = []
-    for (const part of message.content) {
-      if (part.type === "text") {
-        content.push({ type: "text", text: part.text })
-        continue
-      }
-      if (message.role === "assistant" && part.type === "reasoning") {
-        if (part.providerMetadata?.cohere?.toolPlan === true) plans.push(part.text)
-        else content.push({ type: "thinking", thinking: part.text })
-        continue
-      }
-      if (message.role === "assistant" && part.type === "tool-call") {
-        const args = ProviderShared.encodeJson(part.input)
-        calls.push({ id: part.id, type: "function", function: { name: part.name, arguments: args } })
-        continue
-      }
-      if (message.role === "user" && part.type === "media" && part.media.mediaType.startsWith("image/")) {
-        const url =
-          ProviderShared.mediaUrl(part.media) ??
-          (yield* ProviderShared.requireInlineMedia("Cohere Chat", part.media)).dataUrl
-        content.push({ type: "image_url", image_url: { url } })
-        continue
-      }
-      return yield* ProviderShared.unsupportedContent(
-        "Cohere Chat",
-        message.role,
-        message.role === "user" ? ["text", "media"] : ["text", "reasoning", "tool-call"],
-      )
-    }
-    messages.push({
-      role: message.role,
-      content: content.length ? content : undefined,
-      tool_calls: calls.length ? calls : undefined,
-      tool_plan: plans.length ? plans.join("") : undefined,
-    })
-  }
-  const selected = request.toolChoice?.type === "tool" ? request.toolChoice.name : undefined
-  const tools = selected === undefined ? flattened.tools : flattened.tools.filter((tool) => tool.name === selected)
-  if (selected !== undefined && tools.length === 0)
-    return yield* ProviderShared.invalidRequest("Cohere Chat tool choice must name an available tool")
-  if (tools.some((tool) => tool.native !== undefined))
-    return yield* ProviderShared.invalidRequest("Cohere Chat does not support provider-defined tools")
-  return {
-    model: request.model.id,
-    messages,
-    stream: true as const,
-    tools: tools.length
-      ? tools.map((tool) => ({
-          type: "function" as const,
-          function: { name: tool.name, description: tool.description, parameters: tool.inputSchema },
-        }))
-      : undefined,
-    tool_choice: TOOL_CHOICE[request.toolChoice?.type ?? "auto"],
-    thinking: options.thinking && {
-      type: options.thinking.type ?? "enabled",
-      // Cohere rejects budgets above max_tokens; fitting also leaves room for the answer.
-      token_budget:
-        options.thinking.tokenBudget === undefined
-          ? undefined
-          : ProviderShared.fitThinkingBudget(options.thinking.tokenBudget, request.generation?.maxTokens),
-    },
-    max_tokens: request.generation?.maxTokens,
-    temperature: request.generation?.temperature,
-    p: request.generation?.topP,
-    k: request.generation?.topK,
-    seed: request.generation?.seed,
-    stop_sequences: request.generation?.stop,
-    frequency_penalty: request.generation?.frequencyPenalty,
-    presence_penalty: request.generation?.presencePenalty,
-  }
-})
-
-const finishReason = (raw: string): FinishReasonDetails => {
-  switch (raw) {
-    case "COMPLETE":
-    case "STOP_SEQUENCE":
-      return { normalized: "stop", raw }
-    case "MAX_TOKENS":
-      return { normalized: "length", raw }
-    case "TOOL_CALL":
-      return { normalized: "tool-calls", raw }
-    case "ERROR":
-    case "TIMEOUT":
-      return { normalized: "error", raw }
-    default:
-      return { normalized: "unknown", raw }
-  }
-}
-
-const mapUsage = (usage: typeof NativeUsage.Type) =>
-  new Usage({
-    inputTokens: usage.tokens?.input_tokens,
-    outputTokens: usage.tokens?.output_tokens,
-    nonCachedInputTokens: ProviderShared.subtractTokens(usage.tokens?.input_tokens, usage.cached_tokens),
-    cacheReadInputTokens: usage.cached_tokens,
-    reasoningTokens: usage.tokens?.reasoning_tokens,
-    totalTokens: ProviderShared.totalTokens(usage.tokens?.input_tokens, usage.tokens?.output_tokens, undefined),
-    providerMetadata: { cohere: usage },
-  })
-
-// Lifecycle deltas open blocks on demand and ends are no-ops for closed blocks, so content-start needs no handling.
-const step = Effect.fn("CohereChat.step")(function* (state: State, event: Event) {
-  const events: LLMEvent[] = []
-  switch (event.type) {
-    case "message-start":
-      return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, events] as const
-    case "content-delta": {
-      const id = String(event.index)
-      const content = event.delta.message.content
-      const lifecycle =
-        content.thinking !== undefined
-          ? Lifecycle.reasoningDelta(state.lifecycle, events, id, content.thinking)
-          : Lifecycle.textDelta(state.lifecycle, events, id, content.text ?? "")
-      return [{ ...state, lifecycle }, events] as const
-    }
-    case "content-end": {
-      const id = String(event.index)
-      const lifecycle = Lifecycle.textEnd(Lifecycle.reasoningEnd(state.lifecycle, events, id), events, id)
-      return [{ ...state, lifecycle }, events] as const
-    }
-    case "tool-plan-delta": {
-      const plan = event.delta.message.tool_plan
-      const lifecycle = Lifecycle.reasoningDelta(state.lifecycle, events, "tool-plan", plan, {
-        cohere: { toolPlan: true },
-      })
-      return [{ ...state, lifecycle }, events] as const
-    }
-    case "tool-call-start":
-    case "tool-call-delta": {
-      const call = event.delta.message.tool_calls
-      const result = ToolStream.appendOrStart(
-        ADAPTER,
-        state.tools,
-        event.index,
-        { id: call.id, name: call.function.name, text: call.function.arguments ?? "" },
-        "Cohere tool call is missing id or name",
-      )
-      if (ToolStream.isError(result)) return yield* result
-      return [{ ...state, tools: result.tools }, result.events] as const
-    }
-    case "tool-call-end": {
-      const result = yield* ToolStream.finish(ADAPTER, state.tools, event.index)
-      return [{ ...state, tools: result.tools }, result.events ?? []] as const
-    }
-    case "message-end": {
-      const pending = yield* ToolStream.finishAll(ADAPTER, state.tools)
-      events.push(...pending.events)
-      const lifecycle = Lifecycle.finish(state.lifecycle, events, {
-        reason: finishReason(event.delta.finish_reason),
-        usage: event.delta.usage && mapUsage(event.delta.usage),
-      })
-      return [{ tools: pending.tools, lifecycle, finished: true }, events] as const
-    }
-    default:
-      return [state, events] as const
-  }
-})
-
-export const protocol = Protocol.make({
-  id: ADAPTER,
-  body: { schema: Body, from: fromRequest },
-  stream: {
-    event: Protocol.jsonEvent(Event),
-    initial: (): State => ({ lifecycle: Lifecycle.initial(), tools: ToolStream.empty(), finished: false }),
-    step,
-    terminal: (event) => event.type === "message-end",
-    onHalt: (state) =>
-      state.finished
-        ? Effect.succeed([])
-        : Effect.fail(ProviderShared.eventError(ADAPTER, "Cohere stream ended without message-end")),
-  },
-})
-export const route = Route.make({
-  id: ADAPTER,
-  provider: "cohere",
-  providerMetadataKey: "cohere",
-  protocol,
-  endpoint: Endpoint.path("/chat", { baseURL: DEFAULT_BASE_URL }),
-  framing: Framing.sse,
-})
-export * as CohereChat from "./cohere-chat.js"
@@ -475,7 +475,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
    safetySettings: options.safetySettings,
    serviceTier: options.serviceTier,
    systemInstruction:
-      request.system.length === 0 ? undefined : { parts: request.system.map((part) => ({ text: part.text })) },
+      request.system.length === 0 ? undefined : { parts: [{ text: ProviderShared.joinText(request.system) }] },
    tools: hasTools
      ? [
          {
@@ -1,561 +0,0 @@
-import { Effect, Schema } from "effect"
-import { Route } from "../route/client.js"
-import { Auth } from "../route/auth.js"
-import { Endpoint } from "../route/endpoint.js"
-import { Framing } from "../route/framing.js"
-import { Protocol } from "../route/protocol.js"
-import {
-  AIError,
-  LLMEvent,
-  ProviderID,
-  Usage,
-  type LLMRequest,
-  type ProviderMetadata,
-  type ToolResultPart,
-} from "../schema/index.js"
-import { Media } from "../media.js"
-import { classifyProviderFailure, providerErrorMessage } from "../provider-error.js"
-import { encodeJson } from "../utils/json.js"
-import { JsonObject, knownString, lenient, optionalNull, ProviderShared } from "./shared.js"
-import { Lifecycle } from "./utils/lifecycle.js"
-import { MediaInput } from "./utils/media-input.js"
-import { ToolStream } from "./utils/tool-stream.js"
-
-const ADAPTER = "google-interactions"
-export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"
-
-// =============================================================================
-// Public Model Input
-// =============================================================================
-const ThinkingLevel = knownString<"minimal" | "low" | "medium" | "high">()
-const Options = Schema.Struct({
-  previousInteractionId: lenient(Schema.String),
-  store: lenient(Schema.Boolean),
-  thinkingLevel: lenient(ThinkingLevel),
-  thinkingSummaries: lenient(knownString<"auto" | "none">()),
-  serviceTier: lenient(knownString<"standard" | "flex" | "priority">()),
-})
-export type OptionsInput = typeof Options.Encoded
-export type ProviderOptionsInput = OptionsInput
-const decodeOptions = ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))
-
-// =============================================================================
-// Request Body Schema
-// =============================================================================
-const Text = Schema.Struct({ type: Schema.Literal("text"), text: Schema.String })
-const MediaContent = Schema.Struct({
-  type: Schema.Literals(["image", "audio", "video", "document"]),
-  data: Schema.optional(Schema.String),
-  uri: Schema.optional(Schema.String),
-  mime_type: Schema.String,
-})
-const Content = Schema.Union([Text, MediaContent])
-const InputStep = Schema.Union([
-  Schema.Struct({ type: Schema.Literals(["user_input", "model_output"]), content: Schema.Array(Content) }),
-  Schema.Struct({
-    type: Schema.Literal("thought"),
-    signature: Schema.optional(Schema.String),
-    summary: Schema.optional(Schema.Array(Text)),
-  }),
-  Schema.Struct({
-    type: Schema.Literal("function_call"),
-    id: Schema.String,
-    name: Schema.String,
-    arguments: Schema.Unknown,
-    signature: Schema.optional(Schema.String),
-  }),
-  Schema.Struct({
-    type: Schema.Literal("function_result"),
-    call_id: Schema.String,
-    name: Schema.String,
-    result: Schema.Unknown,
-    is_error: Schema.optional(Schema.Boolean),
-  }),
-])
-type InputStep = typeof InputStep.Type
-const ToolChoice = Schema.Union([
-  Schema.Literals(["auto", "any", "none"]),
-  Schema.Struct({ allowed_tools: Schema.Struct({ mode: Schema.Literal("any"), tools: Schema.Array(Schema.String) }) }),
-])
-const Body = Schema.Struct({
-  model: Schema.String,
-  input: Schema.Array(InputStep),
-  stream: Schema.Literal(true),
-  store: Schema.Boolean,
-  previous_interaction_id: Schema.optional(Schema.String),
-  system_instruction: Schema.optional(Schema.String),
-  service_tier: Schema.optional(Schema.String),
-  tools: Schema.optional(
-    Schema.Array(
-      Schema.Struct({
-        type: Schema.Literal("function"),
-        name: Schema.String,
-        description: Schema.String,
-        parameters: JsonObject,
-      }),
-    ),
-  ),
-  generation_config: Schema.Struct({
-    max_output_tokens: Schema.optional(Schema.Number),
-    temperature: Schema.optional(Schema.Number),
-    top_p: Schema.optional(Schema.Number),
-    seed: Schema.optional(Schema.Number),
-    stop_sequences: Schema.optional(Schema.Array(Schema.String)),
-    thinking_level: Schema.optional(ThinkingLevel),
-    thinking_summaries: Schema.optional(Schema.String),
-    tool_choice: Schema.optional(ToolChoice),
-  }),
-})
-
-// =============================================================================
-// Streaming Event Schema
-// =============================================================================
-const RawUsage = Schema.StructWithRest(
-  Schema.Struct({
-    total_input_tokens: optionalNull(Schema.Number),
-    total_cached_tokens: optionalNull(Schema.Number),
-    total_output_tokens: optionalNull(Schema.Number),
-    total_thought_tokens: optionalNull(Schema.Number),
-    total_tokens: optionalNull(Schema.Number),
-    raw_prompt_token: optionalNull(Schema.Number),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-type RawUsage = typeof RawUsage.Type
-const OutputStep = Schema.Struct({
-  type: Schema.String,
-  id: Schema.optional(Schema.String),
-  name: Schema.optional(Schema.String),
-  arguments: Schema.optional(JsonObject),
-  signature: Schema.optional(Schema.String),
-  summary: Schema.optional(Schema.Array(Text)),
-  content: Schema.optional(Schema.Array(Schema.Struct({ type: Schema.String, text: Schema.optional(Schema.String) }))),
-})
-type OutputStep = typeof OutputStep.Type
-const Delta = Schema.Union([
-  Schema.Struct({ type: Schema.Literal("text"), text: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("arguments_delta"), arguments: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("thought_signature"), signature: Schema.String }),
-  Schema.Struct({ type: Schema.Literal("thought_summary"), content: Text }),
-  // Unknown output modalities must fail explicitly rather than disappearing from a successful response.
-  Schema.Struct({ type: Schema.String }),
-])
-const Interaction = Schema.StructWithRest(
-  Schema.Struct({
-    id: Schema.optional(Schema.String),
-    status: Schema.String,
-    usage: Schema.optional(RawUsage),
-  }),
-  [Schema.Record(Schema.String, Schema.Unknown)],
-)
-const Event = Schema.Union([
-  Schema.Struct({ event_type: Schema.Literal("step.start"), index: Schema.Number, step: OutputStep }),
-  Schema.Struct({ event_type: Schema.Literal("step.delta"), index: Schema.Number, delta: Delta }),
-  Schema.Struct({ event_type: Schema.Literal("step.stop"), index: Schema.Number }),
-  Schema.Struct({
-    event_type: Schema.Literal("interaction.created"),
-    interaction: Schema.Struct({ id: Schema.optional(Schema.String) }),
-  }),
-  Schema.Struct({
-    event_type: Schema.Literal("interaction.status_update"),
-    interaction_id: Schema.optional(Schema.String),
-    status: Schema.String,
-  }),
-  Schema.Struct({ event_type: Schema.Literal("interaction.completed"), interaction: Interaction }),
-  Schema.Struct({ event_type: Schema.Literal("error"), error: Schema.Unknown }),
-])
-type Event = typeof Event.Type
-
-// =============================================================================
-// Parser State
-// =============================================================================
-interface ParserState {
-  readonly route: string
-  readonly metadataKey: string
-  readonly lifecycle: Lifecycle.State
-  readonly steps: Partial<Record<number, OutputStep>>
-  readonly tools: ToolStream.State<number>
-  readonly completed: boolean
-}
-type StepResult = readonly [ParserState, ReadonlyArray<LLMEvent>]
-
-// =============================================================================
-// Request Body Construction
-// =============================================================================
-const mediaContent = Effect.fn("GoogleInteractions.mediaContent")(function* (asset: Media.Asset) {
-  if (
-    asset.kind !== "image" &&
-    asset.kind !== "audio" &&
-    asset.kind !== "video" &&
-    asset.mediaType !== "application/pdf" &&
-    asset.mediaType !== "text/csv"
-  )
-    return yield* ProviderShared.invalidRequest(
-      `Google Interactions does not support ${asset.mediaType} document input`,
-    )
-  const type: (typeof MediaContent.Type)["type"] =
-    asset.kind === "image" || asset.kind === "audio" || asset.kind === "video" ? asset.kind : "document"
-  const uri = MediaInput.refID(asset, ProviderID.make("google"))
-  if (uri !== undefined) return { type, uri, mime_type: asset.mediaType }
-  const inline = yield* ProviderShared.requireInlineMedia("Google Interactions", asset)
-  return { type, data: inline.base64, mime_type: inline.mime }
-})
-
-const signature = (metadata: ProviderMetadata | undefined, key: string) => {
-  const value = metadata?.[key]
-  return ProviderShared.isRecord(value) && typeof value.interactionSignature === "string"
-    ? value.interactionSignature
-    : undefined
-}
-
-const lowerMessages = Effect.fn("GoogleInteractions.lowerMessages")(function* (request: LLMRequest) {
-  const steps: InputStep[] = []
-  const key = request.model.route.providerMetadataKey ?? String(request.model.provider)
-  for (const message of request.messages) {
-    if (message.role === "system") {
-      const part = yield* ProviderShared.wrappedSystemUpdate("Google Interactions", message)
-      steps.push({ type: "user_input", content: [{ type: "text", text: part.text }] })
-      continue
-    }
-    const start = steps.length
-    // Consecutive ordinary content remains one native message; tools and thoughts retain their chronology.
-    const append = (content: typeof Content.Type) => {
-      const type = message.role === "assistant" ? "model_output" : "user_input"
-      const last = steps.at(-1)
-      if (steps.length > start && last?.type === type)
-        steps[steps.length - 1] = { type, content: [...last.content, content] }
-      else steps.push({ type, content: [content] })
-    }
-    for (const part of message.content) {
-      if (message.role === "tool") {
-        if (part.type !== "tool-result")
-          return yield* ProviderShared.unsupportedContent(ADAPTER, "tool", ["tool-result"])
-        steps.push({
-          type: "function_result",
-          call_id: part.id,
-          name: part.name,
-          result: yield* lowerToolResult(part),
-          is_error: part.result.type === "error" || undefined,
-        })
-        continue
-      }
-      if (part.type === "text") {
-        append({ type: "text", text: part.text })
-        continue
-      }
-      if (part.type === "media") {
-        append(yield* mediaContent(part.media))
-        continue
-      }
-      if (message.role === "assistant" && part.type === "reasoning") {
-        steps.push({
-          type: "thought",
-          signature: signature(part.providerMetadata, key),
-          summary: part.text ? [{ type: "text", text: part.text }] : undefined,
-        })
-        continue
-      }
-      if (message.role === "assistant" && part.type === "tool-call") {
-        steps.push({
-          type: "function_call",
-          id: part.id,
-          name: part.name,
-          arguments: part.input,
-          signature: signature(part.providerMetadata, key),
-        })
-        continue
-      }
-      return yield* ProviderShared.unsupportedContent(
-        ADAPTER,
-        message.role,
-        message.role === "user" ? ["text", "media"] : ["text", "media", "reasoning", "tool-call"],
-      )
-    }
-  }
-  return steps
-})
-
-const lowerToolResult = Effect.fn("GoogleInteractions.lowerToolResult")(function* (part: ToolResultPart) {
-  if (part.result.type === "json" && ProviderShared.isRecord(part.result.value)) return part.result.value
-  if (part.result.type !== "content") return ProviderShared.toolResultText(part)
-
-  return yield* Effect.forEach(part.result.value, (item): Effect.Effect<typeof Content.Type, AIError> => {
-    if (item.type === "text") return Effect.succeed({ type: "text", text: item.text })
-    return mediaContent(ProviderShared.toolFileMedia(item).media)
-  })
-})
-
-const fromRequest = Effect.fn("GoogleInteractions.fromRequest")(function* (request: LLMRequest) {
-  const options = yield* decodeOptions(request.providerOptions ?? {})
-  const flattened = ProviderShared.flattenToolRequest(request)
-  if (flattened.tools.some((tool) => tool.native !== undefined))
-    return yield* ProviderShared.invalidRequest("Google Interactions hosted tools are not supported")
-  if (
-    request.generation?.topK !== undefined ||
-    request.generation?.frequencyPenalty !== undefined ||
-    request.generation?.presencePenalty !== undefined
-  )
-    return yield* ProviderShared.invalidRequest(
-      "Google Interactions does not support topK, frequencyPenalty, or presencePenalty",
-    )
-  const choice =
-    request.toolChoice === undefined
-      ? undefined
-      : yield* ProviderShared.matchToolChoice(ADAPTER, request.toolChoice, {
-          auto: () => "auto" as const,
-          none: () => "none" as const,
-          required: () => "any" as const,
-          tool: (name) => ({ allowed_tools: { mode: "any" as const, tools: [name] } }),
-        })
-  return {
-    model: request.model.id,
-    input: yield* lowerMessages(flattened.request),
-    stream: true as const,
-    // Full-history replay need not create retained provider resources. Continuation callers opt in to storage.
-    store: options.store ?? false,
-    previous_interaction_id: options.previousInteractionId,
-    system_instruction: request.system.length ? ProviderShared.joinText(request.system) : undefined,
-    service_tier: options.serviceTier,
-    tools: flattened.tools.length
-      ? flattened.tools.map((tool) => ({
-          type: "function" as const,
-          name: tool.name,
-          description: tool.description,
-          parameters: tool.inputSchema,
-        }))
-      : undefined,
-    generation_config: {
-      max_output_tokens: request.generation?.maxTokens,
-      temperature: request.generation?.temperature,
-      top_p: request.generation?.topP,
-      seed: request.generation?.seed,
-      stop_sequences: request.generation?.stop,
-      thinking_level: options.thinkingLevel,
-      thinking_summaries: options.thinkingSummaries,
-      tool_choice: choice,
-    },
-  }
-})
-
-// =============================================================================
-// Stream Parsing
-// =============================================================================
-const metadata = (state: ParserState, step: OutputStep): ProviderMetadata => ({
-  [state.metadataKey]: { interactionSignature: step.signature },
-})
-const mapUsage = (usage: RawUsage | undefined, key: string) => {
-  if (!usage) return undefined
-  const input = usage.total_input_tokens ?? undefined
-  const cached = usage.total_cached_tokens ?? undefined
-  const reasoning = usage.total_thought_tokens ?? undefined
-  const output =
-    usage.total_output_tokens === undefined || usage.total_output_tokens === null
-      ? undefined
-      : usage.total_output_tokens + (reasoning ?? 0)
-  return new Usage({
-    contextTokens: usage.raw_prompt_token ?? input,
-    inputTokens: input,
-    outputTokens: output,
-    nonCachedInputTokens: ProviderShared.subtractTokens(input, cached),
-    cacheReadInputTokens: cached,
-    reasoningTokens: reasoning,
-    totalTokens: usage.total_tokens ?? undefined,
-    providerMetadata: { [key]: usage },
-  })
-}
-
-const onStart = Effect.fn("GoogleInteractions.onStart")(function* (
-  state: ParserState,
-  index: number,
-  step: OutputStep,
-) {
-  const events: LLMEvent[] = []
-  let lifecycle = Lifecycle.stepStart(state.lifecycle, events)
-  let tools = state.tools
-  const id = String(index)
-  if (step.type === "thought") {
-    lifecycle = Lifecycle.reasoningStart(lifecycle, events, id, metadata(state, step))
-    for (const part of step.summary ?? []) lifecycle = Lifecycle.reasoningDelta(lifecycle, events, id, part.text)
-  } else if (step.type === "model_output") {
-    lifecycle = Lifecycle.textStart(lifecycle, events, id)
-    for (const part of step.content ?? []) {
-      if (part.type !== "text")
-        return yield* ProviderShared.eventError(
-          ADAPTER,
-          `Unsupported Interactions output: ${part.type}`,
-          encodeJson(step),
-        )
-      if (part.text) lifecycle = Lifecycle.textDelta(lifecycle, events, id, part.text)
-    }
-  } else if (step.type === "function_call") {
-    if (!step.id || !step.name)
-      return yield* ProviderShared.eventError(ADAPTER, "Interactions function call lacks id or name", encodeJson(step))
-    tools = ToolStream.start(tools, index, {
-      id: step.id,
-      name: step.name,
-      providerMetadata: metadata(state, step),
-      input: step.arguments && Object.keys(step.arguments).length ? encodeJson(step.arguments) : "",
-    })
-    events.push(LLMEvent.toolInputStart({ id: step.id, name: step.name, providerMetadata: metadata(state, step) }))
-  } else
-    return yield* ProviderShared.eventError(ADAPTER, `Unsupported Interactions step: ${step.type}`, encodeJson(step))
-  return [{ ...state, lifecycle, tools, steps: { ...state.steps, [index]: step } }, events] satisfies StepResult
-})
-
-const onDelta = Effect.fn("GoogleInteractions.onDelta")(function* (
-  state: ParserState,
-  index: number,
-  delta: typeof Delta.Type,
-) {
-  const step = state.steps[index]
-  if (!step)
-    return yield* ProviderShared.eventError(ADAPTER, "Interactions delta without step.start", encodeJson(delta))
-  const events: LLMEvent[] = []
-  if (delta.type === "text" && "text" in delta && step.type === "model_output")
-    return [
-      { ...state, lifecycle: Lifecycle.textDelta(state.lifecycle, events, String(index), delta.text) },
-      events,
-    ] satisfies StepResult
-  if (delta.type === "thought_summary" && "content" in delta && step.type === "thought")
-    return [
-      { ...state, lifecycle: Lifecycle.reasoningDelta(state.lifecycle, events, String(index), delta.content.text) },
-      events,
-    ] satisfies StepResult
-  if (delta.type === "thought_signature" && "signature" in delta) {
-    const next = { ...step, signature: delta.signature }
-    const tool = state.tools[index]
-    return [
-      {
-        ...state,
-        steps: { ...state.steps, [index]: next },
-        tools: tool ? { ...state.tools, [index]: { ...tool, providerMetadata: metadata(state, next) } } : state.tools,
-      },
-      events,
-    ] satisfies StepResult
-  }
-  if (delta.type === "arguments_delta" && "arguments" in delta && step.type === "function_call") {
-    const result = ToolStream.appendExisting(
-      ADAPTER,
-      state.tools,
-      index,
-      delta.arguments,
-      "Interactions arguments without function call",
-    )
-    if (ToolStream.isError(result)) return yield* result
-    return [{ ...state, tools: result.tools }, result.events] satisfies StepResult
-  }
-  return yield* ProviderShared.eventError(ADAPTER, `Unsupported Interactions delta: ${delta.type}`, encodeJson(delta))
-})
-
-const onStop = Effect.fn("GoogleInteractions.onStop")(function* (state: ParserState, index: number) {
-  const step = state.steps[index]
-  if (!step) return yield* ProviderShared.eventError(ADAPTER, "Interactions step.stop without step.start")
-  const events: LLMEvent[] = []
-  if (step.type === "thought")
-    return [
-      { ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, String(index), metadata(state, step)) },
-      events,
-    ] satisfies StepResult
-  if (step.type === "model_output")
-    return [
-      { ...state, lifecycle: Lifecycle.textEnd(state.lifecycle, events, String(index)) },
-      events,
-    ] satisfies StepResult
-  const result = yield* ToolStream.finish(ADAPTER, state.tools, index)
-  return [{ ...state, tools: result.tools }, result.events ?? []] satisfies StepResult
-})
-
-const step = Effect.fn("GoogleInteractions.step")(function* (state: ParserState, event: Event) {
-  switch (event.event_type) {
-    case "step.start":
-      return yield* onStart(state, event.index, event.step)
-    case "step.delta":
-      return yield* onDelta(state, event.index, event.delta)
-    case "step.stop":
-      return yield* onStop(state, event.index)
-    case "interaction.created":
-    case "interaction.status_update":
-      return [state, []] satisfies StepResult
-    case "error":
-      return yield* new AIError({
-        reason: classifyProviderFailure({
-          message: providerErrorMessage(encodeJson(event)) ?? "Google Interactions stream error",
-          data: event.error,
-          rawBody: encodeJson(event),
-        }),
-      })
-    case "interaction.completed": {
-      const interaction = event.interaction
-      if (interaction.status === "failed" || interaction.status === "cancelled")
-        return yield* new AIError({
-          reason: classifyProviderFailure({
-            message: `Google Interactions ${interaction.status}`,
-            data: interaction,
-            rawBody: encodeJson(event),
-          }),
-        })
-      if (!["completed", "requires_action", "incomplete"].includes(interaction.status))
-        return yield* ProviderShared.eventError(
-          ADAPTER,
-          `Unexpected terminal Interactions status: ${interaction.status}`,
-          encodeJson(event),
-        )
-      const pending = yield* ToolStream.finishAll(ADAPTER, state.tools)
-      const events = [...pending.events]
-      const lifecycle = Lifecycle.finish(state.lifecycle, events, {
-        reason: {
-          normalized:
-            interaction.status === "requires_action"
-              ? "tool-calls"
-              : interaction.status === "incomplete"
-                ? "length"
-                : "stop",
-          raw: interaction.status,
-        },
-        usage: mapUsage(interaction.usage, state.metadataKey),
-        providerMetadata: { [state.metadataKey]: { interactionId: interaction.id } },
-      })
-      return [{ ...state, lifecycle, tools: pending.tools, completed: true }, events] satisfies StepResult
-    }
-  }
-})
-
-// =============================================================================
-// Protocol And Route
-// =============================================================================
-export const protocol = Protocol.make({
-  id: ADAPTER,
-  sanitizer: "gemini",
-  body: { schema: Body, from: fromRequest },
-  stream: {
-    event: Protocol.jsonEvent(Event),
-    initial: (request): ParserState => ({
-      route: `${request.model.provider}/${ADAPTER}`,
-      metadataKey: request.model.route.providerMetadataKey ?? String(request.model.provider),
-      lifecycle: Lifecycle.initial(),
-      steps: {},
-      tools: ToolStream.empty<number>(),
-      completed: false,
-    }),
-    step,
-    terminal: (event) => event.event_type === "interaction.completed",
-    onHalt: (state) =>
-      state.completed
-        ? Effect.succeed([])
-        : Effect.fail(
-            ProviderShared.eventError(ADAPTER, "Google Interactions stream ended before interaction.completed"),
-          ),
-  },
-})
-
-export const route = Route.make({
-  id: ADAPTER,
-  provider: "google",
-  providerMetadataKey: "google",
-  protocol,
-  endpoint: Endpoint.path("/interactions", { baseURL: DEFAULT_BASE_URL }),
-  auth: Auth.none,
-  framing: Framing.sse,
-})
-
-export * as GoogleInteractions from "./google-interactions.js"
@@ -1,8 +1,6 @@
 export * as AnthropicMessages from "./anthropic-messages.js"
 export * as BedrockConverse from "./bedrock-converse.js"
-export * as CohereChat from "./cohere-chat.js"
 export * as Gemini from "./gemini.js"
-export * as GoogleInteractions from "./google-interactions.js"
 export * as MistralChat from "./mistral-chat.js"
 export * as OpenAIChat from "./openai-chat.js"
 export * as OpenAIImages from "./openai-images.js"
@@ -1,5 +1,6 @@
 import { Effect, Encoding, Schema } from "effect"
 import { Protocol } from "../route/protocol.js"
+import { HttpTransport } from "../route/transport/index.js"
 import { LLMEvent, LLMRequest, Message, ToolResultPart } from "../schema/index.js"
 import { OpenResponses } from "./open-responses.js"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
@@ -43,6 +44,13 @@ const ImageItem = Schema.Struct({
  error: Schema.optional(Schema.Unknown),
 })

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

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

 const HOSTED_TOOLS = {
@@ -200,7 +222,7 @@ const step = Effect.fn("MetaResponses.step")(function* (state: ParserState, inpu

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

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

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

 const MistralMessage = Schema.Union([
-  Schema.Struct({
-    role: Schema.Literal("system"),
-    content: Schema.Union([Schema.String, Schema.Array(MistralTextContent)]),
-  }),
+  Schema.Struct({ role: Schema.Literal("system"), content: Schema.String }),
  Schema.Struct({
    role: Schema.Literal("user"),
    content: Schema.Union([Schema.String, Schema.Array(MistralUserContent)]),
@@ -338,17 +335,7 @@ const lowerToolResults = Effect.fn("MistralChat.lowerToolResults")(function* (
 const lowerMessages = Effect.fn("MistralChat.lowerMessages")(function* (request: LLMRequest) {
  const normalizeID = MistralToolID.normalizer(request)
  const messages: MistralMessage[] =
-    request.system.length === 0
-      ? []
-      : [
-          {
-            role: "system",
-            content:
-              request.system.length === 1
-                ? request.system[0].text
-                : request.system.map((part) => ({ type: "text", text: part.text })),
-          },
-        ]
+    request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
  for (const message of request.messages) {
    if (message.role === "system") {
      const update = yield* ProviderShared.wrappedSystemUpdate("Mistral Chat", message)
@@ -168,20 +168,10 @@ export const ConfigurationUpdate = Schema.Struct({
  type: Schema.Literal("configuration_update"),
  reasoning: Schema.Struct({ effort: OpenResponsesOptions.ReasoningEffort }),
 })
-export type ConfigurationUpdate = Schema.Schema.Type<typeof ConfigurationUpdate>
-
-export const HostedToolReplay = Schema.StructWithRest(
-  Schema.Struct({
-    type: Schema.String,
-    id: Schema.String,
-  }),
-  [JsonObject],
-)
-export type HostedToolReplayItem = Schema.Schema.Type<typeof HostedToolReplay>
+type ConfigurationUpdate = Schema.Schema.Type<typeof ConfigurationUpdate>

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

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

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

-export const OpenResponsesBody = Schema.Struct({
+const OpenResponsesBody = Schema.Struct({
  ...coreFields,
  stream: Schema.Literal(true),
 })
@@ -400,7 +397,9 @@ export const decodeChannelEvent = (frame: string) =>
 export interface ProviderAdapter {
  readonly id: string
  readonly name: string
-  readonly nativeTool?: (native: NonNullable<ToolDefinition["native"]>) => Effect.Effect<HostedTool, AIError>
+  readonly nativeTool?: (
+    native: NonNullable<ToolDefinition["native"]>,
+  ) => Effect.Effect<{ readonly type: string }, AIError>
  readonly lowerMedia?: (input: {
    readonly part: MediaPart
    readonly media: Media.Inline | undefined
@@ -456,10 +455,8 @@ export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (protoco
 })

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

 export const lowerToolChoice = (protocolName: string, toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -595,7 +592,7 @@ const lowerMessages = Effect.fn("OpenResponses.lowerMessages")(function* (
  request: LLMRequest,
  adapter: ProviderAdapter,
 ) {
-  const input: OpenResponsesInputItem[] = []
+  const input: LoweredInputItem[] = []
  const providerMetadataKey = metadataKey(request.model)

  for (const message of request.messages) {
@@ -830,7 +827,11 @@ export const fromRequestWithAdapter = Effect.fn("OpenResponses.fromRequestWithAd
  }
 })

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

 // =============================================================================
 // Stream Parsing
@@ -14,6 +14,7 @@ import {
  ProviderInternalError,
  UnknownProviderError,
  Usage,
+  type FinishReason,
  type FinishReasonDetails,
  type CacheHint,
  type LLMRequest,
@@ -45,6 +46,12 @@ const OpenAIChatCacheControl = Schema.Struct({
 })
 type OpenAIChatCacheControl = Schema.Schema.Type<typeof OpenAIChatCacheControl>

+const OpenAIChatFunction = Schema.Struct({
+  name: Schema.String,
+  description: Schema.String,
+  parameters: JsonObject,
+})
+
 const OpenAIChatTool = Schema.Struct({
  type: Schema.tag("function"),
  function: Schema.Struct({
@@ -205,11 +212,9 @@ const OpenAIChatUsage = Schema.StructWithRest(
    prompt_tokens: optionalNull(Schema.Number),
    completion_tokens: optionalNull(Schema.Number),
    total_tokens: optionalNull(Schema.Number),
-    // Provider-specific cache accounting fields.
+    // Zai reports cache hits as top-level `cached_tokens`; DeepSeek uses `prompt_cache_hit_tokens`.
    cached_tokens: optionalNull(Schema.Number),
    prompt_cache_hit_tokens: optionalNull(Schema.Number),
-    cache_read_input_tokens: optionalNull(Schema.Number),
-    cache_created_input_tokens: optionalNull(Schema.Number),
    prompt_tokens_details: optionalNull(
      Schema.StructWithRest(
        Schema.Struct({
@@ -898,19 +903,16 @@ const mapFinishReason = Effect.fn("OpenAIChat.mapFinishReason")(function* (event
 // satisfied on both sides.
 // Providers differ on cache-hit location: OpenAI uses
 // `prompt_tokens_details.cached_tokens`, DeepSeek uses
-// `prompt_cache_hit_tokens`, Zai uses top-level `cached_tokens`, and
-// DigitalOcean uses top-level `cache_read_input_tokens` / `cache_created_input_tokens`.
+// `prompt_cache_hit_tokens`, and Zai uses top-level `cached_tokens`.
 const mapUsage = (usage: OpenAIChatEvent["usage"], providerMetadataKey: string): Usage | undefined => {
  if (!usage) return undefined
  const input = usage.prompt_tokens ?? undefined
  const output = usage.completion_tokens ?? undefined
-  const cached =
-    usage.prompt_tokens_details?.cached_tokens ??
-    usage.prompt_cache_hit_tokens ??
-    usage.cached_tokens ??
-    usage.cache_read_input_tokens ??
-    undefined
-  const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens ?? usage.cache_created_input_tokens ?? undefined
+  const cached = (usage.prompt_tokens_details?.cached_tokens ??
+    (usage as { prompt_cache_hit_tokens?: number | null }).prompt_cache_hit_tokens ??
+    (usage as { cached_tokens?: number | null }).cached_tokens ??
+    undefined) as number | undefined
+  const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens ?? undefined
  const reasoning = usage.completion_tokens_details?.reasoning_tokens ?? undefined
  const nonCached = ProviderShared.subtractTokens(input, ProviderShared.sumTokens(cached, cacheWrite))
  return new Usage({
@@ -103,8 +103,15 @@ const OpenAIResponsesToolChoice = Schema.Union([
  Schema.Struct({ type: Schema.tag("image_generation") }),
 ])

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

 const adapter = {
@@ -195,13 +202,15 @@ const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tool
        : { type: "function" as const, name },
  })

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

 const checkpointBody = {
@@ -1,5 +1,4 @@
 // Shared counter and TTL mapping for provider cache-marker lowering.
-import type { CacheHint } from "../../schema/index.js"

 export interface Breakpoints {
  remaining: number
@@ -12,12 +11,3 @@ export const newBreakpoints = (cap: number): Breakpoints => ({ remaining: cap, d
 // requests omit the wire TTL and use the provider default.
 export const ttlBucket = (ttlSeconds: number | undefined): "1h" | undefined =>
  ttlSeconds !== undefined && ttlSeconds >= 3600 ? "1h" : undefined
-
-export const cacheControl = () => {
-  const breakpoints = newBreakpoints(4)
-  return (cache: CacheHint | undefined) => {
-    if (cache === undefined || breakpoints.remaining === 0) return undefined
-    breakpoints.remaining -= 1
-    return { type: "ephemeral" as const, ttl: ttlBucket(cache.ttlSeconds) }
-  }
-}
@@ -31,12 +31,19 @@ const XAIResponsesHostedToolItem = Schema.Union([
  ),
 ])

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

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

 const HOSTED_TOOLS = {
@@ -76,7 +83,7 @@ const step = (state: OpenResponses.ParserState, input: OpenResponses.Event) => {
 export const protocol = Protocol.make({
  id: ADAPTER,
  body: {
-    schema: OpenResponses.OpenResponsesBody,
+    schema: XAIResponsesBody,
    from: fromRequest,
  },
  stream: {
@@ -35,8 +35,6 @@ const patterns = [
  /exceeds the limit of \d+/i,
  /exceeds the available context size/i,
  /greater than the context length/i,
-  // Hugging Face Text Generation Inference, e.g. Together
-  /`inputs` tokens \+ `max_new_tokens` must be <= \d+/i,
  /context window exceeds limit/i,
  /exceeded model token limit/i,
  /context[_ ]length[_ ]exceeded/i,
@@ -55,13 +53,7 @@ const patterns = [

 const payloadPatterns = [/request entity too large/i, /payload too large/i, /request too large/i]

-const exclusions = [
-  /^(throttling error|service unavailable):/i,
-  /rate limit/i,
-  /too many requests/i,
-  // Cohere reports an output limit above the model maximum as "too many tokens"; compaction cannot fix it.
-  /max[_ ]tokens must be less than/i,
-]
+const exclusions = [/^(throttling error|service unavailable):/i, /rate limit/i, /too many requests/i]

 export const isContextOverflow = (message: string) =>
  !exclusions.some((pattern) => pattern.test(message)) &&
@@ -1,66 +0,0 @@
-import { CohereChat } from "../protocols/cohere-chat.js"
-import { OpenAIChat } from "../protocols/openai-chat.js"
-import { Route, type RouteDefaultsInput } from "../route/client.js"
-import { Endpoint } from "../route/endpoint.js"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { ProviderID, type ModelID, type OpenString } from "../schema/index.js"
-import type { ProviderPackage } from "../provider-package.js"
-
-export const id = ProviderID.make("cohere")
-const COMPATIBILITY_BASE_URL = "https://api.cohere.ai/compatibility/v1"
-export type ChatOptionsInput = { readonly reasoningEffort?: OpenString<"none" | "high"> }
-export type ProviderOptions = CohereChat.ProviderOptionsInput & ChatOptionsInput
-export type LanguageModelOptions = Omit<RouteDefaultsInput, "providerOptions"> &
-  ProviderAuthOption<"optional"> & {
-    readonly baseURL?: string
-    readonly providerOptions?: ProviderOptions
-  }
-export type Settings<Options = CohereChat.ProviderOptionsInput> = ProviderPackage.Settings &
-  Options & { readonly apiKey?: string; readonly baseURL?: string }
-
-export const route = CohereChat.route
-export const chatRoute = Route.make({
-  id: "cohere-chat-completions",
-  provider: id,
-  providerMetadataKey: "cohere",
-  protocol: OpenAIChat.protocol,
-  endpoint: Endpoint.path("/chat/completions", { baseURL: COMPATIBILITY_BASE_URL }),
-  framing: OpenAIChat.framing,
-})
-export const routes = [route, chatRoute]
-
-export const configure = (input: LanguageModelOptions = {}) => {
-  const { apiKey: _apiKey, auth: _auth, baseURL, ...defaults } = input
-  const auth = AuthOptions.bearer(input, "COHERE_API_KEY")
-  const native = route.with({ ...defaults, auth, endpoint: { baseURL: baseURL ?? CohereChat.DEFAULT_BASE_URL } })
-  const chat = chatRoute.with({ ...defaults, auth, endpoint: { baseURL: baseURL ?? COMPATIBILITY_BASE_URL } })
-  return {
-    id,
-    model: (modelID: string | ModelID) => native.model<CohereChat.ProviderOptionsInput>({ id: modelID }),
-    chat: (modelID: string | ModelID) =>
-      chat.model<ChatOptionsInput>({
-        id: modelID,
-        compatibility: {
-          maxTokensField: "max_tokens",
-          supportsStore: false,
-          supportsUsageInStreaming: true,
-          reasoningField: "reasoning_content",
-          supportsStrictMode: false,
-        },
-      }),
-    configure,
-  }
-}
-export const provider = configure()
-export const model: ProviderPackage.Definition<Settings, CohereChat.ProviderOptionsInput>["model"] = (
-  modelID,
-  { apiKey, baseURL, body, headers, ...providerOptions },
-) =>
-  configure({
-    apiKey,
-    baseURL,
-    headers,
-    http: body === undefined ? undefined : { body: { ...body } },
-    providerOptions,
-  }).model(modelID)
-export * as Cohere from "./cohere.js"
@@ -1,16 +0,0 @@
-import type { ProviderPackage } from "../../provider-package.js"
-import { Cohere } from "../cohere.js"
-
-export type Settings = Cohere.Settings<Cohere.ChatOptionsInput>
-
-export const model: ProviderPackage.Definition<Settings, Cohere.ChatOptionsInput>["model"] = (
-  modelID,
-  { apiKey, baseURL, body, headers, ...providerOptions },
-) =>
-  Cohere.configure({
-    apiKey,
-    baseURL,
-    headers,
-    http: body === undefined ? undefined : { body: { ...body } },
-    providerOptions,
-  }).chat(modelID)
@@ -1,76 +0,0 @@
-import type { ProviderPackage } from "../provider-package.js"
-import { OpenAIChat } from "../protocols/openai-chat.js"
-import { cacheControl } from "../protocols/utils/cache.js"
-import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { Route, type RouteDefaultsInput } from "../route/client.js"
-import { Endpoint } from "../route/endpoint.js"
-import { Protocol } from "../route/protocol.js"
-import { ProviderID, type ModelID } from "../schema/index.js"
-import type { OpenAIProviderOptionsInput } from "./openai-options.js"
-
-export const id = ProviderID.make("digitalocean")
-const baseURL = "https://inference.do-ai.run/v1"
-
-export type LanguageModelOptions = Omit<RouteDefaultsInput, "providerOptions"> &
-  ProviderAuthOption<"optional"> & {
-    readonly baseURL?: string
-    readonly providerOptions?: OpenAIProviderOptionsInput
-  }
-
-export type Settings = ProviderPackage.Settings & OpenAIProviderOptionsInput & { readonly apiKey?: string }
-
-export const protocol = Protocol.make({
-  id: "digitalocean-chat",
-  body: {
-    schema: OpenAIChat.protocol.body.schema,
-    from: (request) => OpenAIChat.fromRequest(request, { cacheControl: cacheControl() }),
-  },
-  stream: OpenAIChat.protocol.stream,
-})
-
-export const route = Route.make({
-  id: "digitalocean",
-  provider: id,
-  providerMetadataKey: "digitalocean",
-  protocol,
-  endpoint: Endpoint.path("/chat/completions", { baseURL }),
-  framing: OpenAIChat.framing,
-})
-
-export const routes = [route]
-
-export const configure = (input: LanguageModelOptions = {}) => {
-  const { apiKey: _apiKey, auth: _auth, baseURL: endpoint, ...defaults } = input
-  const configured = route.with({
-    ...defaults,
-    endpoint: { baseURL: endpoint ?? baseURL },
-    auth: AuthOptions.bearer(input, ["DIGITALOCEAN_ACCESS_TOKEN", "DIGITALOCEAN_API_KEY", "DO_INFERENCE_API_KEY"]),
-  })
-  return {
-    id,
-    model: (modelID: string | ModelID) =>
-      configured.model<OpenAIProviderOptionsInput>({
-        id: modelID,
-        compatibility: {
-          supportsPromptCacheKey: true,
-        },
-      }),
-    configure,
-  }
-}
-
-export const provider = configure()
-
-export const model: ProviderPackage.Definition<Settings, OpenAIProviderOptionsInput>["model"] = (
-  modelID,
-  { apiKey, baseURL, body, headers, ...providerOptions },
-) =>
-  configure({
-    apiKey,
-    baseURL,
-    headers,
-    http: { body },
-    providerOptions,
-  }).model(modelID)
-
-export * as DigitalOcean from "./digitalocean.js"
@@ -37,7 +37,7 @@ export type Settings = ProviderPackage.Settings &
 const route = Route.make({
  id: "google-vertex-messages",
  provider: id,
-  providerMetadataKey: "vertex",
+  providerMetadataKey: "anthropic",
  protocol: Protocol.make({
    id: AnthropicMessages.protocol.id,
    body: {
@@ -5,7 +5,6 @@ import { MediaRoute } from "../route/media.js"
 import type { ProviderPackage } from "../provider-package.js"
 import { ProviderID, type ModelID } from "../schema/index.js"
 import { Gemini } from "../protocols/gemini.js"
-import { GoogleInteractions } from "../protocols/google-interactions.js"
 import { GoogleImages } from "../protocols/google-images.js"
 import { GoogleSpeech } from "../protocols/google-speech.js"
 import { GoogleTranscription } from "../protocols/google-transcription.js"
@@ -17,16 +16,15 @@ export type { GoogleTranscriptionOptions } from "../protocols/google-transcripti
 export type { GoogleVideoOptions } from "../protocols/google-video.js"
 export type GeminiOptionsInput = Gemini.OptionsInput
 export type GeminiProviderOptionsInput = Gemini.ProviderOptionsInput
-export type GoogleInteractionsOptionsInput = GoogleInteractions.OptionsInput

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

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

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

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

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

 export const image = provider.image
-export const interactions = provider.interactions
 export const video = provider.video
 export const speech = provider.speech
 export const transcription = provider.transcription
@@ -1,21 +0,0 @@
-import { configure } from "../google.js"
-import type { ProviderPackage } from "../../provider-package.js"
-import type { GoogleInteractions } from "../../protocols/google-interactions.js"
-
-export type Settings = ProviderPackage.Settings &
-  GoogleInteractions.ProviderOptionsInput & {
-    readonly apiKey?: string
-    readonly baseURL?: string
-  }
-
-export const model: ProviderPackage.Definition<Settings, GoogleInteractions.ProviderOptionsInput>["model"] = (
-  modelID,
-  { apiKey, baseURL, body, headers, ...providerOptions },
-) =>
-  configure({
-    apiKey,
-    baseURL,
-    headers: headers === undefined ? undefined : { ...headers },
-    http: body === undefined ? undefined : { body: { ...body } },
-    providerOptions,
-  }).interactions(modelID)
@@ -71,7 +71,7 @@ export const protocol = Protocol.make({
 export const route = Route.make({
  id: "groq-chat",
  provider: id,
-  providerMetadataKey: "groq",
+  providerMetadataKey: "openai",
  protocol,
  endpoint: Endpoint.path("/chat/completions", { baseURL }),
  framing: OpenAIChat.framing,
@@ -9,13 +9,11 @@ export * as Baseten from "./baseten.js"
 export * as BlackForestLabs from "./black-forest-labs.js"
 export * as Cartesia from "./cartesia.js"
 export * as Cerebras from "./cerebras.js"
-export * as Cohere from "./cohere.js"
 export * as CloudflareAIGateway from "./cloudflare-ai-gateway.js"
 export * as CloudflareWorkersAI from "./cloudflare-workers-ai.js"
 export * as DeepInfra from "./deepinfra.js"
 export * as Deepgram from "./deepgram.js"
 export * as DeepSeek from "./deepseek.js"
-export * as DigitalOcean from "./digitalocean.js"
 export * as ElevenLabs from "./elevenlabs.js"
 export * as Fal from "./fal.js"
 export * as Fireworks from "./fireworks.js"
@@ -3,11 +3,11 @@ import { Route, type RouteDefaultsInput } from "../route/client.js"
 import { Endpoint } from "../route/endpoint.js"
 import { Protocol } from "../route/protocol.js"
 import { AuthOptions, type ProviderAuthOption } from "../route/auth-options.js"
-import { HttpOptions, ProviderID, type ModelID, type OpenString } from "../schema/index.js"
+import { HttpOptions, ProviderID, type CacheHint, type ModelID, type OpenString } from "../schema/index.js"
 import type { ProviderPackage } from "../provider-package.js"
 import { SystemOne } from "../experimental/system-one.js"
 import { OpenAIChat } from "../protocols/openai-chat.js"
-import { cacheControl } from "../protocols/utils/cache.js"
+import { newBreakpoints, ttlBucket } from "../protocols/utils/cache.js"
 import { isRecord, ProviderShared } from "../protocols/shared.js"

 export const id = ProviderID.make("openrouter")
@@ -131,6 +131,18 @@ export const protocol = Protocol.make({
  stream: OpenAIChat.protocol.stream,
 })

+const cacheControl = () => {
+  const breakpoints = newBreakpoints(4)
+  return (cache: CacheHint | undefined) => {
+    if (cache === undefined || breakpoints.remaining === 0) return undefined
+    breakpoints.remaining -= 1
+    return {
+      type: "ephemeral" as const,
+      ...(ttlBucket(cache.ttlSeconds) === "1h" ? { ttl: "1h" } : {}),
+    }
+  }
+}
+
 // OpenRouter forwards `reasoning.max_tokens` as the upstream thinking budget. Upstreams such as Anthropic and Alibaba
 // reject one that is not below the output limit; 1,024 is Anthropic's minimum budget.
 const fitReasoning = (reasoning: Record<string, unknown>, maxTokens: number | undefined) =>
@@ -358,6 +358,7 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
  input: MakeTransportInput<Body, Prepared, Frame, Event, State>,
 ): Route<Body, Prepared> {
  const protocol = input.protocol
+  const encodeBody = Schema.encodeSync(Schema.fromJsonString(protocol.body.schema))
  const decodeEventEffect = Schema.decodeUnknownEffect(protocol.stream.event)
  const decodeEvent = (route: string) => (frame: Frame) =>
    decodeEventEffect(frame).pipe(
@@ -416,7 +417,7 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
          request,
          endpoint: routeInput.endpoint,
          auth: routeInput.auth ?? Auth.none,
-          encodeBody: ProviderShared.encodeJson,
+          encodeBody,
          middleware: options?.http,
          webSocket: options?.webSocket,
        }),
@@ -575,7 +576,9 @@ const compile = Effect.fn("LLM.compile")(function* (request: LLMRequest, options
  const resolved = prepareRequest(request)
  const route = resolved.model.route

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

  return {
@@ -159,15 +159,6 @@ const nativeTransportFailure = (error: unknown) => {
  return failure
 }

-// HTTP hooks re-wrap response bodies, so a read failure can arrive as an HttpClientError caused by
-// another HttpClientError. The innermost cause carries the native failure.
-const rootCause = (error: unknown): unknown =>
-  HttpClientError.isHttpClientError(error) && "cause" in error.reason && error.reason.cause !== undefined
-    ? rootCause(error.reason.cause)
-    : error
-
-const CONNECTION_LOST = "Connection lost while reading the response"
-
 const httpError = (input: {
  readonly error: unknown
  readonly request: HttpClientRequest.HttpClientRequest
@@ -188,21 +179,20 @@ const httpError = (input: {
      }),
    })

-  const source = rootCause(input.error)
+  const source =
+    HttpClientError.isHttpClientError(input.error) && "cause" in input.error.reason
+      ? (input.error.reason.cause ?? input.error)
+      : input.error
  const native = nativeTransportFailure(source)
  const code = native?.code
-  const detail =
-    code && native?.message && !native.message.includes(code) ? `${code}: ${native.message}` : native?.message
-  const message = detail ?? (input.error instanceof Error ? input.error.message : undefined)
+  const raw = native?.message ?? (input.error instanceof Error ? input.error.message : undefined)
+  const detail = raw
+  const message = code && detail && !detail.includes(code) ? `${code}: ${detail}` : detail

  if (Cause.isTimeoutError(input.error) || Cause.isTimeoutError(source))
    return transportError({ message: message ?? "HTTP transport timed out", code: code ?? "Timeout" })
  if (!HttpClientError.isHttpClientError(input.error))
    return transportError({ message: message ?? "HTTP transport failed", code })
-  // Effect reports every response body read failure as a DecodeError, but the raw byte stream decodes
-  // nothing: provider output parsing happens later and fails as InvalidProviderOutput.
-  if (input.operation === "read" && input.error.reason._tag === "DecodeError")
-    return transportError({ message: detail ? `${CONNECTION_LOST}: ${detail}` : CONNECTION_LOST, code })
  if (input.error.reason._tag === "TransportError") {
    return transportError({
      message: message ?? input.error.reason.description ?? "HTTP transport failed",
@@ -1,19 +1,11 @@
-import { Clock, Duration, Effect, Stream } from "effect"
+import { Effect } from "effect"
 import { Headers, HttpClientRequest } from "effect/unstable/http"
 import { Auth } from "../auth.js"
 import { render as renderEndpoint } from "../endpoint.js"
 import { Framing } from "../framing.js"
 import type { HttpMiddleware, Transport, TransportPrepareInput } from "./index.js"
 import * as ProviderShared from "../../protocols/shared.js"
-import {
-  AIError,
-  DEFAULT_HTTP_TIMEOUT_MS,
-  mergeJsonRecords,
-  TransportError,
-  type HttpContext,
-  type HttpTimeout,
-  type LLMRequest,
-} from "../../schema/index.js"
+import { mergeJsonRecords, type LLMRequest } from "../../schema/index.js"
 import { RequestExecutor } from "../executor.js"

 export type JsonRequestInput<Body> = TransportPrepareInput<Body>
@@ -95,53 +87,17 @@ export const httpJson = <Body, Frame>(input: HttpJsonInput<Body, Frame>): HttpJs
        middleware: prepareInput.middleware,
      }
    }),
-  execute: (prepared, request, runtime) =>
+  execute: (prepared, _request, runtime) =>
    Effect.gen(function* () {
-      const timeout = (operation: "request" | "read", message: string, http?: HttpContext) =>
-        new AIError({
-          reason: new TransportError({
-            message,
-            transport: "http",
-            operation,
-            code: "Timeout",
-            url: prepared.request.url,
-            http,
-          }),
-        })
-      const started = yield* Clock.currentTimeMillis
-      // Unlike the header and chunk limits, the whole-request budget has no default.
-      const total = request.http?.timeout ? Duration.millis(request.http.timeout) : Duration.infinity
-      const response = yield* runtime.http.execute(prepared.request, prepared.middleware).pipe(
-        Effect.timeoutOrElse({
-          duration: Duration.min(timeoutDuration(request.http?.headerTimeout), total),
-          orElse: () => timeout("request", "Timed out waiting for response headers"),
-        }),
-      )
-      const http = RequestExecutor.responseHttp(response)
-      const remaining = Duration.subtract(total, Duration.millis((yield* Clock.currentTimeMillis) - started))
+      const response = yield* runtime.http.execute(prepared.request, prepared.middleware)
      return {
-        frames: prepared.framing.frame(
-          RequestExecutor.responseStream(response).pipe(
-            Stream.timeoutOrElse({
-              duration: timeoutDuration(request.http?.chunkTimeout),
-              orElse: () => Stream.fail(timeout("read", "Timed out waiting for response data", http)),
-            }),
-            Stream.interruptWhen(
-              Effect.sleep(remaining).pipe(
-                Effect.andThen(Effect.fail(timeout("read", "Timed out waiting for the response to complete", http))),
-              ),
-            ),
-          ),
-        ),
-        http,
+        frames: prepared.framing.frame(RequestExecutor.responseStream(response)),
+        http: RequestExecutor.responseHttp(response),
        body: prepared.framing.body,
      }
    }),
 })

-const timeoutDuration = (value: HttpTimeout | undefined) =>
-  value === false ? Duration.infinity : Duration.millis(value ?? DEFAULT_HTTP_TIMEOUT_MS)
-
 export const sseJson = {
  id: "http-json/sse",
  with: <Body>() => httpJson<Body, string>({ framing: Framing.sse }),
@@ -48,23 +48,10 @@ export const mergeProviderOptions = (
  ...items: ReadonlyArray<ProviderOptions | undefined>
 ): ProviderOptions | undefined => mergeJsonRecords(...items)

-/** Milliseconds for an HTTP timeout, or `false` to disable it. */
-export const HttpTimeout = Schema.Union([Schema.Number.check(Schema.isGreaterThan(0)), Schema.Literal(false)])
-export type HttpTimeout = Schema.Schema.Type<typeof HttpTimeout>
-
-/** Applied to `headerTimeout` and `chunkTimeout` when a request leaves them unset. */
-export const DEFAULT_HTTP_TIMEOUT_MS = 300_000
-
 export class HttpOptions extends Schema.Class<HttpOptions>("AI.HttpOptions")({
  body: Schema.optional(JsonSchema),
  headers: Schema.optional(Schema.Record(Schema.String, Schema.String)),
  query: Schema.optional(Schema.Record(Schema.String, Schema.String)),
-  /** Time allowed for the whole request, from send until the response completes. Unbounded when unset. */
-  timeout: Schema.optional(HttpTimeout),
-  /** Time allowed for response headers to arrive. */
-  headerTimeout: Schema.optional(HttpTimeout),
-  /** Time allowed between streamed response chunks once headers have arrived. */
-  chunkTimeout: Schema.optional(HttpTimeout),
 }) {}

 export namespace HttpOptions {
@@ -83,12 +70,8 @@ export const mergeHttpOptions = (...items: ReadonlyArray<HttpOptions | undefined
  const body = mergeJsonRecords(...items.map((item) => item?.body))
  const headers = mergeStringRecords(...items.map((item) => item?.headers))
  const query = mergeStringRecords(...items.map((item) => item?.query))
-  const timeout = items.findLast((item) => item?.timeout !== undefined)?.timeout
-  const headerTimeout = items.findLast((item) => item?.headerTimeout !== undefined)?.headerTimeout
-  const chunkTimeout = items.findLast((item) => item?.chunkTimeout !== undefined)?.chunkTimeout
-  if (!body && !headers && !query && timeout === undefined && headerTimeout === undefined && chunkTimeout === undefined)
-    return undefined
-  return new HttpOptions({ body, headers, query, timeout, headerTimeout, chunkTimeout })
+  if (!body && !headers && !query) return undefined
+  return new HttpOptions({ body, headers, query })
 }

 export class GenerationOptions extends Schema.Class<GenerationOptions>("LLM.GenerationOptions")({
@@ -14,6 +14,7 @@ import * as GoogleVertexChat from "../src/providers/google-vertex-chat.js"
 import * as GoogleVertexMessages from "../src/providers/google-vertex-messages.js"
 import * as GoogleVertexResponses from "../src/providers/google-vertex-responses.js"
 import * as OpenAI from "../src/providers/openai.js"
+import * as OpenAICompatible from "../src/providers/openai-compatible.js"
 import * as OpenRouter from "../src/providers/openrouter.js"
 import * as XAI from "../src/providers/xai.js"

@@ -8,7 +8,6 @@ import {
  AmazonBedrock,
  AnthropicCompatible,
  CloudflareAIGateway,
-  DigitalOcean,
  GoogleVertexMessages,
  Meta,
  MiniMax,
@@ -118,86 +117,6 @@ describe("applyCachePolicy", () => {
    }),
  )

-  it.effect("'auto' emits cache_control markers on DigitalOcean", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: DigitalOcean.configure({ apiKey: "test" }).model("anthropic-claude-fable-5.1"),
-          system: "You are concise.",
-          tools: [{ name: "lookup", description: "Look up a value", inputSchema: { type: "object", properties: {} } }],
-          prompt: "hi",
-        }),
-      )
-
-      expect(prepared.body).toMatchObject({
-        tools: [{ type: "function", function: { name: "lookup" }, cache_control: { type: "ephemeral" } }],
-        messages: [
-          {
-            role: "system",
-            content: [{ text: "You are concise.", cache_control: { type: "ephemeral" } }],
-          },
-          {
-            role: "user",
-            content: [{ text: "hi", cache_control: { type: "ephemeral" } }],
-          },
-        ],
-      })
-    }),
-  )
-
-  it.effect("Alibaba chat caches the system and conversation tail without marking tools", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: Alibaba.configure({ region: "ap-southeast-1", apiKey: "test" }).chat("qwen3.8-max"),
-          system: "You are concise.",
-          tools: [{ name: "lookup", description: "Look up a value", inputSchema: { type: "object", properties: {} } }],
-          prompt: "hi",
-        }),
-      )
-
-      expect(prepared.body).toMatchObject({
-        tools: [{ type: "function", function: { name: "lookup" } }],
-        messages: [
-          {
-            role: "system",
-            content: [{ text: "You are concise.", cache_control: { type: "ephemeral" } }],
-          },
-          { role: "user", content: [{ text: "hi", cache_control: { type: "ephemeral" } }] },
-        ],
-      })
-      expect(prepared.body.tools?.[0]?.cache_control).toBeUndefined()
-    }),
-  )
-
-  it.effect("Alibaba chat omits automatic cache markers when cache is none", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: Alibaba.configure({ region: "ap-southeast-1", apiKey: "test" }).chat("qwen3.8-max"),
-          system: "You are concise.",
-          prompt: "hi",
-          cache: "none",
-        }),
-      )
-
-      expect(JSON.stringify(prepared.body)).not.toContain("cache_control")
-    }),
-  )
-
-  it.effect("Alibaba chat does not assume non-Qwen models support cache markers", () =>
-    Effect.gen(function* () {
-      const alibaba = Alibaba.configure({ region: "ap-southeast-1", apiKey: "test" })
-      for (const modelID of ["kimi-k3", "glm-5.2", "deepseek-v4-flash-0731", "MiniMax-M2.5"]) {
-        const prepared = yield* compileRequest(
-          LLM.request({ model: alibaba.chat(modelID), system: "You are concise.", prompt: "hi" }),
-        )
-
-        expect(JSON.stringify(prepared.body)).not.toContain("cache_control")
-      }
-    }),
-  )
-
  it.effect("'auto' emits Anthropic cache markers on Anthropic-compatible routes", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(
@@ -1,12 +1,13 @@
 import { describe, expect, test } from "bun:test"
 import { Effect } from "effect"
-import { LLM, Message, ToolCallPart } from "../src/index.js"
+import { LLM, LLMRequest, Message, ToolCallPart } from "../src/index.js"
 import { Auth, LLMClient } from "../src/route.js"
 import { compileRequest } from "../src/route/client.js"
 import { AnthropicMessages } from "../src/protocols/anthropic-messages.js"
 import { OpenAIResponses } from "../src/protocols/openai-responses.js"
 import { Gemini } from "../src/protocols/gemini.js"
 import { GoogleVertexMessages, OpenAI } from "../src/providers.js"
+import { applyCachePolicy } from "../src/cache-policy.js"
 import { applyEffortUpdates } from "../src/effort-updates.js"
 import { it, testEffect } from "./lib/effect.js"
 import { dynamicResponse } from "./lib/http.js"
@@ -196,15 +197,9 @@ describe("Anthropic Messages effort updates", () => {
    ["anthropic/claude-opus-5", true],
    ["claude-fable-5-1", true],
    ["claude-mythos-5-1", true],
-    ["claude-opus-5-5", true],
-    ["claude-sonnet-5-5", true],
-    ["anthropic/claude-sonnet-5-5", true],
-    ["claude-sonnet-6", true],
-    ["claude-haiku-6", true],
    ["claude-fable-5", false],
    ["claude-opus-4-8", false],
    ["claude-sonnet-5", false],
-    ["claude-sonnet-5-20260801", false],
    ["kimi-k2.5", false],
  ] as const) {
    it.effect(`${supported ? "lowers" : "strips"} markers for ${id}`, () =>
@@ -1,17 +1,11 @@
 import { describe, expect } from "bun:test"
 import { Deferred, Effect, Fiber, Layer, Ref, Stream } from "effect"
-import { Headers, HttpClientError, HttpClientRequest, HttpClientResponse } from "effect/unstable/http"
-import { LLM, AIError, HttpContext, InvalidProviderOutputError, TransportError, isRetryable } from "../src/index.js"
-import {
-  LLMClient,
-  RequestExecutor,
-  WebSocketTransport,
-  type HttpMiddleware,
-  type WebSocketChannelExecutor,
-} from "../src/route.js"
+import { Headers, HttpClientError, HttpClientRequest } from "effect/unstable/http"
+import { LLM, AIError, HttpContext, InvalidProviderOutputError, TransportError } from "../src/index.js"
+import { LLMClient, RequestExecutor, WebSocketTransport, type WebSocketChannelExecutor } from "../src/route.js"
 import { route } from "../src/protocols/openai-chat.js"
 import { configure } from "../src/providers/openai.js"
-import { dynamicResponse, fixedResponse, handlerLayer, systemError, truncatedStream } from "./lib/http.js"
+import { dynamicResponse, fixedResponse, handlerLayer, systemError } from "./lib/http.js"
 import { deltaChunk } from "./lib/openai-chunks.js"
 import { sseEvents, sseRaw } from "./lib/sse.js"
 import { it } from "./lib/effect.js"
@@ -24,8 +18,6 @@ const secretRequest = HttpClientRequest.post("https://provider.test/v1/chat?api_
  HttpClientRequest.setHeaders(Headers.fromInput({ authorization: "Bearer header-secret-456" })),
 )

-const sseRequest = HttpClientRequest.post("https://provider.test/v1/messages")
-
 const expectAIError = (error: unknown) => {
  expect(error).toBeInstanceOf(AIError)
  if (!(error instanceof AIError)) throw new Error("expected AIError")
@@ -101,9 +93,7 @@ describe("RequestExecutor", () => {
      const error = yield* RequestExecutor.stream(executor, secretRequest).pipe(Stream.runDrain, Effect.flip)

      expectAIError(error)
-      expect(error.message).toBe(
-        "Connection lost while reading the response: ECONNRESET: disconnected query-secret-123 header-secret-456",
-      )
+      expect(error.message).toBe("ECONNRESET: disconnected query-secret-123 header-secret-456")
      expect(error.reason.http).toMatchObject({ status: 200, url: secretRequest.url })
      expect(error.reason.cause).toMatchObject({ code: "ECONNRESET" })
      expect(error.reason).toMatchObject({
@@ -133,7 +123,7 @@ describe("RequestExecutor", () => {
      const error = yield* RequestExecutor.stream(executor, secretRequest).pipe(Stream.runDrain, Effect.flip)

      expectAIError(error)
-      expect(error.message).toBe("Connection lost while reading the response: ECONNRESET: socket closed")
+      expect(error.message).toBe("ECONNRESET: socket closed")
      expect(error.reason.cause).toBeInstanceOf(TypeError)
      expect(error.reason).toMatchObject({
        _tag: "Transport",
@@ -154,54 +144,6 @@ describe("RequestExecutor", () => {
    ),
  )

-  it.effect("reports a connection lost mid-stream through middleware that re-wraps the body", () =>
-    Effect.gen(function* () {
-      const executor = yield* RequestExecutor.Service
-      const chunks: Array<Uint8Array> = []
-      // Session HTTP hooks hand plugins a web Response, so the body is re-wrapped around the original stream.
-      const rewrap: HttpMiddleware = (input, handler) =>
-        Effect.gen(function* () {
-          const response = yield* handler(input)
-          const body = yield* Stream.toReadableStreamEffect(response.stream)
-          return HttpClientResponse.fromWeb(
-            input,
-            new Response(body, { status: response.status, headers: response.headers }),
-          )
-        })
-      const error = yield* RequestExecutor.stream(executor, sseRequest, rewrap).pipe(
-        Stream.runForEach((chunk) => Effect.sync(() => chunks.push(chunk))),
-        Effect.flip,
-      )
-
-      expectAIError(error)
-      expect(new TextDecoder().decode(chunks[0])).toBe('data: {"type":"ping"}\n\n')
-      expect(error.message).toBe("Connection lost while reading the response: ECONNRESET: other side closed")
-      expect(error.reason.cause).toBeInstanceOf(TypeError)
-      expect(error.reason.http).toMatchObject({ status: 200 })
-      expect(error.reason).toMatchObject({ _tag: "Transport", operation: "read", code: "ECONNRESET" })
-      expect(isRetryable(error)).toBeTrue()
-    }).pipe(
-      Effect.provide(
-        truncatedStream(
-          ['data: {"type":"ping"}\n\n'],
-          new TypeError("terminated", { cause: systemError("ECONNRESET", "other side closed") }),
-        ),
-      ),
-    ),
-  )
-
-  it.effect("does not report a body read failure without a native cause as a decode error", () =>
-    Effect.gen(function* () {
-      const executor = yield* RequestExecutor.Service
-      const error = yield* RequestExecutor.stream(executor, sseRequest).pipe(Stream.runDrain, Effect.flip)
-
-      expectAIError(error)
-      expect(error.message).toBe("Connection lost while reading the response")
-      expect(error.reason).toMatchObject({ _tag: "Transport", operation: "read", code: undefined })
-      expect(isRetryable(error)).toBeTrue()
-    }).pipe(Effect.provide(truncatedStream(['data: {"type":"ping"}\n\n'], new DOMException("aborted", "AbortError")))),
-  )
-
  it.effect("preserves middleware error messages", () =>
    Effect.gen(function* () {
      const executor = yield* RequestExecutor.Service
@@ -10,7 +10,7 @@
      "usage"
    ],
    "name": "alibaba-chat/qwen-3-7-plus-streams-thinking-disabled",
-    "recordedAt": "2026-10-02T01:23:37.836Z"
+    "recordedAt": "2026-09-08T03:10:42.782Z"
  },
  "interactions": [
    {
@@ -21,14 +21,14 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"qwen3.7-plus\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is 173 multiplied by 219? Reply with only the final integer.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"enable_thinking\":false}"
+        "body": "{\"model\":\"qwen3.7-plus\",\"messages\":[{\"role\":\"user\",\"content\":\"What is 173 multiplied by 219? Reply with only the final integer.\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"enable_thinking\":false}"
      },
      "response": {
        "status": 200,
        "headers": {
          "content-type": "text/event-stream;charset=utf-8"
        },
-        "body": "data: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-e96a3356-bec9-98ad-bdbe-af00a15ee965\",\"created\":1790904216,\"object\":\"chat.completion.chunk\",\"usage\":null,\"choices\":[{\"logprobs\":null,\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null}]}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-e96a3356-bec9-98ad-bdbe-af00a15ee965\",\"choices\":[{\"delta\":{\"content\":\"3\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904216,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-e96a3356-bec9-98ad-bdbe-af00a15ee965\",\"choices\":[{\"delta\":{\"content\":\"7887\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904216,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-e96a3356-bec9-98ad-bdbe-af00a15ee965\",\"choices\":[{\"delta\":{\"content\":\"\"},\"index\":0,\"finish_reason\":\"stop\",\"logprobs\":null}],\"created\":1790904216,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"choices\":[],\"created\":1790904216,\"id\":\"chatcmpl-e96a3356-bec9-98ad-bdbe-af00a15ee965\",\"model\":\"qwen3.7-plus\",\"object\":\"chat.completion.chunk\",\"usage\":{\"completion_tokens\":5,\"prompt_tokens\":32,\"prompt_tokens_details\":{\"cache_creation\":{\"ephemeral_5m_input_tokens\":0},\"cache_creation_input_tokens\":0,\"cache_type\":\"ephemeral\",\"cache_write_tokens\":0,\"cached_tokens\":0,\"text_tokens\":32},\"total_tokens\":37}}\n\ndata: [DONE]\n\n"
+        "body": "data: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-047bcb67-b193-9a4f-9d77-ea0325be6d7c\",\"created\":1788837041,\"object\":\"chat.completion.chunk\",\"usage\":null,\"choices\":[{\"logprobs\":null,\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":null}]}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-047bcb67-b193-9a4f-9d77-ea0325be6d7c\",\"choices\":[{\"delta\":{\"content\":\"3\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788837041,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-047bcb67-b193-9a4f-9d77-ea0325be6d7c\",\"choices\":[{\"delta\":{\"content\":\"7887\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788837041,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-047bcb67-b193-9a4f-9d77-ea0325be6d7c\",\"choices\":[{\"delta\":{\"content\":\"\"},\"index\":0,\"finish_reason\":\"stop\",\"logprobs\":null}],\"created\":1788837041,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"choices\":[],\"created\":1788837041,\"id\":\"chatcmpl-047bcb67-b193-9a4f-9d77-ea0325be6d7c\",\"model\":\"qwen3.7-plus\",\"object\":\"chat.completion.chunk\",\"usage\":{\"completion_tokens\":5,\"prompt_tokens\":32,\"prompt_tokens_details\":{\"cached_tokens\":0,\"text_tokens\":32},\"total_tokens\":37}}\n\ndata: [DONE]\n\n"
      }
    }
  ]
@@ -10,7 +10,7 @@
      "usage"
    ],
    "name": "alibaba-chat/qwen-3-7-plus-streams-thinking-enabled",
-    "recordedAt": "2026-10-02T01:23:43.998Z"
+    "recordedAt": "2026-09-08T03:10:54.099Z"
  },
  "interactions": [
    {
@@ -21,14 +21,14 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"qwen3.7-plus\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is 173 multiplied by 219? Reply with only the final integer.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"enable_thinking\":true,\"thinking_budget\":1024}"
+        "body": "{\"model\":\"qwen3.7-plus\",\"messages\":[{\"role\":\"user\",\"content\":\"What is 173 multiplied by 219? Reply with only the final integer.\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"enable_thinking\":true,\"thinking_budget\":1024}"
      },
      "response": {
        "status": 200,
        "headers": {
          "content-type": "text/event-stream;charset=utf-8"
        },
-        "body": "data: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null,\"choices\":[{\"logprobs\":null,\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\",\"reasoning_content\":\"\"},\"finish_reason\":null}]}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\"Thinking\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" Process:\\n\\n1\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\".  Identify\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" the core\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" question: Calculate \"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\"173 *\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" 219\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\".\\n2.\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\"  Constraint: Reply\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" with *\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\"only* the final\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" integer.\\n3\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1790904218,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-70ed9ebc-62fe-9ee8-a442-7a3881697fdf\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\".  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{\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-ec928416-c99b-9f46-9805-cbb37bd7c499\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" the constraint:** The\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788837042,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-ec928416-c99b-9f46-9805-cbb37bd7c499\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\" response must contain *\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788837042,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.7-plus\",\"id\":\"chatcmpl-ec928416-c99b-9f46-9805-cbb37bd7c499\",\"choices\":[{\"delta\":{\"content\":\"\",\"reasoning_content\":\"only\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788837042,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: 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      }
    }
  ]
@@ -1,15 +1,9 @@
 {
  "version": 1,
  "metadata": {
-    "tags": [
-      "prefix:alibaba-chat",
-      "provider:alibaba",
-      "protocol:alibaba-chat",
-      "region:ap-southeast-1",
-      "image"
-    ],
+    "tags": ["prefix:alibaba-chat", "provider:alibaba", "protocol:alibaba-chat", "region:ap-southeast-1", "image"],
    "name": "alibaba-chat/qwen-3-8-flash-reads-image-bytes",
-    "recordedAt": "2026-10-02T01:23:45.179Z"
+    "recordedAt": "2026-09-08T03:10:55.585Z"
  },
  "interactions": [
    {
@@ -20,14 +14,14 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"qwen3.8-flash\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Read the three words in this image. Reply with only the words in order.\",\"cache_control\":{\"type\":\"ephemeral\"}},{\"type\":\"image_url\",\"image_url\":{\"url\":\"data:image/png;base64,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 truncated
+        "body": "{\"model\":\"qwen3.8-flash\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Read the three words in this image. Reply with only the words in order.\"},{\"type\":\"image_url\",\"image_url\":{\"url\":\"data:image/png;base64,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 truncated
      },
      "response": {
        "status": 200,
        "headers": {
          "content-type": "text/event-stream;charset=utf-8"
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@@ -12,7 +12,7 @@
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{\"model\":\"qwen3.8-max\",\"id\":\"chatcmpl-c075c2f7-07b5-975b-96bd-5ee12c72fb7c\",\"choices\":[{\"delta\":{\"content\":\" cost is \",\"reasoning_content\":\"\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788836991,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.8-max\",\"id\":\"chatcmpl-c075c2f7-07b5-975b-96bd-5ee12c72fb7c\",\"choices\":[{\"delta\":{\"content\":\"219 ×\",\"reasoning_content\":\"\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788836991,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.8-max\",\"id\":\"chatcmpl-c075c2f7-07b5-975b-96bd-5ee12c72fb7c\",\"choices\":[{\"delta\":{\"content\":\" $173\",\"reasoning_content\":\"\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788836991,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.8-max\",\"id\":\"chatcmpl-c075c2f7-07b5-975b-96bd-5ee12c72fb7c\",\"choices\":[{\"delta\":{\"content\":\" = $37\",\"reasoning_content\":\"\"},\"index\":0,\"finish_reason\":null,\"logprobs\":null}],\"created\":1788836991,\"object\":\"chat.completion.chunk\",\"usage\":null}\n\ndata: {\"model\":\"qwen3.8-max\",\"id\":\"chatcmpl-c075c2f7-07b5-975b-96bd-5ee12c72fb7c\",\"choices\":[{\"delta\":{\"content\":\",887\",\"reasoning_content\":\Line truncated
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@@ -11,7 +11,7 @@
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-    "recordedAt": "2026-10-02T01:23:30.455Z"
+    "recordedAt": "2026-09-08T03:09:49.033Z"
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@@ -22,14 +22,14 @@
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      }
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@@ -11,7 +11,7 @@
      "usage"
    ],
    "name": "alibaba-chat/qwen-3-8-max-streams-medium-effort",
-    "recordedAt": "2026-10-02T01:23:20.103Z"
+    "recordedAt": "2026-09-08T03:09:38.233Z"
  },
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@@ -11,7 +11,7 @@
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-    "recordedAt": "2026-10-02T01:23:26.218Z"
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      }
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  ]
@@ -0,0 +1,29 @@
+{
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+        "url": "https://api.anthropic.com/v1/messages",
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+}
@@ -0,0 +1,56 @@
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+      "flagship"
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+      },
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+      },
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+    }
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+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/rejects-malformed-assistant-tool-order-without-patch",
+    "recordedAt": "2026-05-05T20:08:42.597Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool", "sad-path"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
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+        "url": "https://api.anthropic.com/v1/messages",
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+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}},{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
+      },
+      "response": {
+        "status": 400,
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"type\":\"error\",\"error\":{\"type\":\"invalid_request_error\",\"message\":\"messages.1: `tool_use` ids were found without `tool_result` blocks immediately after: call_1. Each `tool_use` block must have a corresponding `tool_result` block in the next message.\"},\"request_id\":\"req_011Cak2XdJgnzxKCY2BC2Beh\"}"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/streams-text",
+    "recordedAt": "2026-04-28T21:18:45.535Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages"]
+  },
+  "interactions": [
+    {
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+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"You are concise.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply with exactly: Hello!\"}]}],\"stream\":true,\"max_tokens\":20,\"temperature\":0}"
+      },
+      "response": {
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+        "headers": {
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+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
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+    "name": "anthropic-messages/streams-tool-call",
+    "recordedAt": "2026-04-28T21:18:46.878Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
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+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
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+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"Call tools exactly as requested.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Call get_weather with city exactly Paris.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"tool_choice\":{\"type\":\"tool\",\"name\":\"get_weather\"},\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
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+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01RYgU7NUPMK4B9v8S7gVpCS\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":16,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}             }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_012rmAruviySvUXSjgCPWVRu\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}}      }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"}             }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\":\"}    }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\" \\\"Paris\\\"}\"}     }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0     }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":33}              }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"     }\n\n"
+      }
+    }
+  ]
+}
@@ -1,49 +0,0 @@
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-  },
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-      },
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-{
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-{
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-{
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-      "provider:cohere"
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-{
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@@ -1,54 +0,0 @@
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-        "url": "https://inference.do-ai.run/v1/chat/completions",
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-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "data: {\"choices\":[{\"delta\":{\"content\":\"Paris\",\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{\"content\":\" is sunny.\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[{\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\"}\n\ndata: {\"choices\":[],\"created\":1790840198,\"id\":\"chatcmpl-3914ee28-f256-4a49-994f-49365922a7a6\",\"model\":\"anthropic-claude-haiku-4.5\",\"object\":\"chat.completion.chunk\",\"usage\":{\"cache_created_input_tokens\":0,\"cache_creation\":{\"ephemeral_1h_input_tokens\":0,\"ephemeral_5m_input_tokens\":0},\"cache_read_input_tokens\":0,\"completion_tokens\":7,\"completion_tokens_details\":{\"reasoning_tokens\":0},\"prompt_tokens\":668,\"prompt_tokens_details\":{\"cached_tokens\":0},\"speed\":null,\"total_tokens\":675}}\n\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -1,53 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "anthropic-claude-haiku-4.5",
-    "tags": [
-      "prefix:digitalocean-chat",
-      "provider:digitalocean",
-      "protocol:digitalocean-chat",
-      "cache",
-      "usage"
-    ],
-    "name": "digitalocean-chat/haiku-reuses-a-cached-prompt",
-    "recordedAt": "2026-10-01T07:36:36.689Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://inference.do-ai.run/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
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-        "body": "{\"model\":\"anthropic-claude-haiku-4.5\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and aLine truncated
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-      "response": {
-        "status": 200,
-        "headers": {
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-      }
-    },
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-      "transport": "http",
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Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and avoid filler. Cite numbers when known. You are a concise, factual assistant. Answer precisely and aLine truncated
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
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-      }
-    }
-  ]
-}
@@ -1,66 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/continues-tool-results-with-previous-interaction-id",
-    "recordedAt": "2026-10-03T18:10:17.900Z"
-  },
-  "interactions": [
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-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
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-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]}],\"stream\":true,\"store\":true,\"system_instruction\":\"Use get_weather for weather questions. Answer concisely after receiving the result.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"generation_config\":{\"max_output_tokens\":2048,\"thinking_level\":\"low\",\"tool_choice\":\"any\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
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-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
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-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"function_result\",\"call_id\":\"call_326996\",\"name\":\"get_weather\",\"result\":{\"temperature\":22,\"condition\":\"sunny\"}}],\"stream\":true,\"store\":false,\"previous_interaction_id\":\"v1_ChdCMFhCYXRqeURhVDdxdHNQNWJLTXNBURIXQjBYQmF0anlEYVQ3cXRzUDViS01zQVE\",\"system_instruction\":\"Use get_weather for weather questions. Answer concisely after receiving the result.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"generation_config\":{\"max_output_tokens\":2048,\"thinking_level\":\"low\",\"tool_choice\":\"none\"}}"
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-      "response": {
-        "status": 200,
-        "headers": {
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-        "body": "event: interaction.created\ndata: {\"interaction\":{\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"EmkKZwFpFH0TchP60hnCGy9QgdyJKikXfeP9DBx/BVTE92JiMUcdYnAQ7vGOt2zL8v0GQMbCshndVE0+WeHt0QXyzeeMeNFH/UQ5bxo3Vs+T3H1e6Fq3LFIjDuvYvMYMRLk44oULO1EhoCg=\",\"type\":\"thought_signature\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":0,\"event_type\":\"step.stop\"}\n\nevent: step.start\ndata: {\"index\":1,\"step\":{\"type\":\"model_output\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"text\":\"The weather in Paris\",\"type\":\"text\"},\"event_type\":\"step.delta\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"text\":\" is sunny with a temperature of 22°C.\",\"type\":\"text\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":1,\"event_type\":\"step.stop\"}\n\nevent: interaction.completed\ndata: {\"interaction\":{\"status\":\"completed\",\"usage\":{\"total_tokens\":115,\"total_input_tokens\":99,\"input_tokens_by_modality\":[{\"modality\":\"text\",\"tokens\":99}],\"total_cached_tokens\":0,\"total_output_tokens\":16,\"total_tool_use_tokens\":0,\"total_thought_tokens\":0,\"raw_prompt_token\":134,\"model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":134}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":20}]}],\"non_grounding_model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":134}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":20}]}]},\"created\":\"2026-10-03T18:10:17Z\",\"updated\":\"2026-10-03T18:10:17Z\",\"service_tier\":\"standard\",\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.completed\"}\n\nevent: done\ndata: [DONE]\n\n"
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "DELETE",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions/v1_ChdCMFhCYXRqeURhVDdxdHNQNWJLTXNBURIXQjBYQmF0anlEYVQ3cXRzUDViS01zQVE",
-        "headers": {},
-        "body": ""
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{}"
-      }
-    }
-  ]
-}
@@ -1,50 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/replays-native-tool-results-and-signatures-statelessly",
-    "recordedAt": "2026-10-03T18:10:15.040Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
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-        },
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-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: interaction.created\ndata: {\"interaction\":{\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"EmkKZwFpFH0TU3VE2ypZTy8W0/W4ikeJNHd8J/UqUDCBIILV/U6sCJUEUat3oneLPVOSvuy+mLi2ByVh2ZlkcxEiY4DsOcsHKSF6q1WBk9YuCqE+W8BMNjZoRwBQeyDeq6cJpXDVkFtBYbg=\",\"type\":\"thought_signature\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":0,\"event_type\":\"step.stop\"}\n\nevent: step.start\ndata: {\"index\":1,\"step\":{\"id\":\"call_1850980\",\"signature\":\"AWkUfRNTdUTbKllPLxbT9biKR4k0d3wn9SpQMIEggtX9TqwIlQRRq3eid4s9U5K+7L6YuLYHJWHZmWRzESJjgOw5ywcpIXqrVYGT1i4KoT5bwEw2NmhHAFB7IN6rpwmlcNWQW0FhuA==\",\"type\":\"function_call\",\"name\":\"get_weather\",\"arguments\":{}},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\",\"type\":\"arguments_delta\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":1,\"event_type\":\"step.stop\"}\n\nevent: interaction.completed\ndata: {\"interaction\":{\"status\":\"requires_action\",\"usage\":{\"total_tokens\":84,\"total_input_tokens\":68,\"input_tokens_by_modality\":[{\"modality\":\"text\",\"tokens\":68}],\"total_cached_tokens\":0,\"total_output_tokens\":16,\"total_tool_use_tokens\":0,\"total_thought_tokens\":0,\"raw_prompt_token\":107,\"model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":107}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":22}]}],\"non_grounding_model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":107}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":22}]}]},\"created\":\"2026-10-03T18:10:14Z\",\"updated\":\"2026-10-03T18:10:14Z\",\"service_tier\":\"standard\",\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.completed\"}\n\nevent: done\ndata: [DONE]\n\n"
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"type\":\"thought\",\"signature\":\"EmkKZwFpFH0TU3VE2ypZTy8W0/W4ikeJNHd8J/UqUDCBIILV/U6sCJUEUat3oneLPVOSvuy+mLi2ByVh2ZlkcxEiY4DsOcsHKSF6q1WBk9YuCqE+W8BMNjZoRwBQeyDeq6cJpXDVkFtBYbg=\"},{\"type\":\"function_call\",\"id\":\"call_1850980\",\"name\":\"get_weather\",\"arguments\":{\"city\":\"Paris\"},\"signature\":\"AWkUfRNTdUTbKllPLxbT9biKR4k0d3wn9SpQMIEggtX9TqwIlQRRq3eid4s9U5K+7L6YuLYHJWHZmWRzESJjgOw5ywcpIXqrVYGT1i4KoT5bwEw2NmhHAFB7IN6rpwmlcNWQW0FhuA==\"},{\"type\":\"function_result\",\"call_id\":\"call_1850980\",\"name\":\"get_weather\",\"result\":{\"temperature\":22,\"condition\":\"sunny\"}}],\"stream\":true,\"store\":false,\"system_instruction\":\"Use get_weather for weather questions. Answer concisely after receiving the result.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"generation_config\":{\"max_output_tokens\":2048,\"thinking_level\":\"low\",\"thinking_summaries\":\"auto\",\"tool_choice\":\"none\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: interaction.created\ndata: {\"interaction\":{\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"EmkKZwFpFH0TRPN/gVeX86bn3+mP2Y1jv3jX464uSnSB+RuBqyig1Xfg52RBzk5GzUt98niutpbttYfMLkXURehjrP1AJUJzQbGLMqmqKD5iEp3bgLq46B3Ov+RcO539Fcz6+qCpPx+VaMQ=\",\"type\":\"thought_signature\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":0,\"event_type\":\"step.stop\"}\n\nevent: step.start\ndata: {\"index\":1,\"step\":{\"type\":\"model_output\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"text\":\"The weather in Paris\",\"type\":\"text\"},\"event_type\":\"step.delta\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"text\":\" is sunny with a temperature of 22°C.\",\"type\":\"text\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":1,\"event_type\":\"step.stop\"}\n\nevent: interaction.completed\ndata: {\"interaction\":{\"status\":\"completed\",\"usage\":{\"total_tokens\":108,\"total_input_tokens\":92,\"input_tokens_by_modality\":[{\"modality\":\"text\",\"tokens\":92}],\"total_cached_tokens\":0,\"total_output_tokens\":16,\"total_tool_use_tokens\":0,\"total_thought_tokens\":0,\"raw_prompt_token\":104,\"model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":104}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":20}]}],\"non_grounding_model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":104}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":20}]}]},\"created\":\"2026-10-03T18:10:15Z\",\"updated\":\"2026-10-03T18:10:15Z\",\"service_tier\":\"standard\",\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.completed\"}\n\nevent: done\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -1,32 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/streams-reasoning-and-retains-thought-signatures",
-    "recordedAt": "2026-10-03T18:08:37.674Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"Find the smallest positive integer that leaves remainder 1 modulo 7, 2 modulo 9, and 3 modulo 11. Explain briefly.\"}]}],\"stream\":true,\"store\":false,\"generation_config\":{\"max_output_tokens\":4096,\"thinking_level\":\"high\",\"thinking_summaries\":\"auto\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: interaction.created\ndata: {\"interaction\":{\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"content\":{\"text\":\"**Analyzing Congruences**\\n\\nI'm tackling a system of congruences to find the smallest positive integer x. Currently, I'm reviewing the Chinese Remainder Theorem as a potential solution, or considering a direct congruence-based approach. The congruences are as follows: $x \\\\equiv 1 \\\\pmod{7}$, $x \\\\equiv 2 \\\\pmod{9}$, $x \\\\equiv 3 \\\\pmod{11}$. I will use these congruences to find a solution.\\n\\n\\n\",\"type\":\"text\"},\"type\":\"thought_summary\"},\"event_type\":\"step.delta\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"content\":{\"text\":\"**Combining Congruences**\\n\\nI've made progress by combining the first two congruences. I determined that x is congruent to 29 modulo 63. Now, I am focused on the remaining congruence, attempting to solve for k in the expression 63k + 29 ≡ 3 (mod 11). I simplified the expression to 8k ≡ 7 (mod 11) and am looking to multiply both sides to eliminate the coefficient of k.\\n\\n\\n\",\"type\":\"text\"},\"type\":\"thought_summary\"},\"event_type\":\"step.delta\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"EskbCsYbAWkUfRM84T8fIy7KmpVRW3jt54Qo5USy0D9bJVmz6itgVBPMK3oD6Lx2AlpdFNnJ4oKCuDmIBs7ok77Tx10Ou1qfT0CsnJ391kx2pc1xAKdJJxvv2nBkHzVWb2/BORG0YNsdE96ulew1vC6x4mu/33XglL06m1hNhK8DPXGdn5lWMhKOqb9L9oBhMxazHUMlwStX67RdjURSVw/lodq/6Ao6PPTguHE9gEyh/iWwALZJCKkZw0LNgdWSRa/Ke4tfr8bncWcIGqz8bmxlaSUVB70m3o7TqvX6l4OyxEG4EwI8ixAKsxIicmxzzIqtGlWGqV/1ahnfIEktee0gF+cH/LcrBjUDblnOGUeKNCZlz7MBVIoRlWx5al5xcX1Vb63SekRlAuBqHqdEioYvMwm52QXzeXfNMDf+ixMhtpQ2fpAjG7PM+D0y+m2V9+3iUI/63e44RjWW2kZhgLrCQ9KSWrRoSsohGVS9zvGQBaVc6vb1QyX56A80eLKbqcGhWSHc+gp1L2lCM1MwBsvl9wM+Szzs8O61UBQJD4C/Pvyed1hxwt0Ebku70VyfTPJGLufWDisMOrruBmQ8MU+OyFk4N1Qm2ZkhOw2tE3yi9lf2ih0mfuj2a/nj81GIbvbSA+r+Oh3lhgOX7IlzidD6BJgSgWY4bG83a1twEVJyvBKZBIIDYKumDSz7tX9gWeKa5b90+RKGohyeM4Kp3yxuPGDPW6jxSHa6hch837OagyVjO/EVkB1LruWIAVAvFG9oAPYNesB2xFeeseXCnAQaNYbw6KMkH85kNBREvFZU1QpFHFWQ9gAxWfSTxCjnkqGao1In/b7wQVopgMVthrCr5VScf8HArkDdD8R9pnN9iD6he0mjmsFnw3mA80KxcWugmKiYkWrIfpEdbNB5FsyCffW+Wt9WmmFnH168qkhbkp5uXk3s8/bJFKmeijyNVWIG9LlLnZ6tpDkq8UqZSriapLq2byI1fk+Mu3UszAeen4qSDXQ32xGqKSr+SG/qpqVlFrvYr2PePjaZUljSqrH0CQSdqMvmlnM9E3XO4rQNtKcmg14BZ4FpVh7m/kCM0zfCfjSdX/BwWibEV4loM+eqLYyX7aul+chBDiQeO3iGkGWkfpycax2NDTYEMfimjuAJlWXsAuhJcdzLdeRucaZwJ0Fwpo0P153I8GIo7AQckiVaeBZRBY9fTEoz8khALMGRGSMrFDqqJ+1dDVdNxAh2txUeOneNi/D0rfM1W4yLJaB6Djl48VHoM1DguwSNDj4yE32Ku4XpXasoSd5/jRmmT8FKvk+FF4jxbJZcYHyTLcnyFCvDfrSBqdJAbdaLgkvRz9Gl1JAs3WPKR+CvIjbuf1cWxj8V8fyngf239aHVfePTXFXPi+M7uRo+923rjW7XxJortd68jHa7GpaLGUKVXgtKBXkAKCrRNRRwIJjODieyGYkj+GdUE0ikYCwbUPx8ZamGY3hjP8GjaVHK+9pUP7CddlUn3H3lIFbcXxQUtCOEFmwg9s9JcJSWLaoX0Vg0KIC1hYtamEkdiJSDbQWURPgzTD/llV86iDx/yaDgXWxaT4DkyNRfVcK2AFiDHQjHhRGd8KDizdpyCfAJZwTlF/nAPz4/FA1/bQ/cT5MHuebzbWbzkYDkDBzTXp2ND6VF50a3XUoKGV3LC6AEsUrUIDksKatHh0hLe+j/YMwOluyvI1WqfAHjCnAqjl/l29S/gFpAKMMjSS60OQzgp/hhORd+gDb8vj/9AS19B8uowIz8KnJkMHv57W3CKPROz2gBMl1VQYm5rRIayBn1fEtpwldDScyhFNtdx7G/ypjQLpgVqzdZTy1dZqHJwA1lOtoMfG1kz/SIDxF56kzUpUcc9Smz/hF3hhGn7TYsQZtcMRB1/W8JCq4qvUle0MIAOXn4XukmQXae6M25aHfHUad7H4BGrFP+P0398drrRQGaqSzos4Hpl1Ev6+3t4mlC81aeRi12asZoIuYTs+RxH4wSe/tbfX+579MuSm07iQGSSmbo8r9xcEREPjEJZ+hNl1YlZB3x/fpzMfVW9L0omiF+rPcTiiILmQh32LRkJ8ZDiAw4HXTZHYKR1sGe+NBqCjT5Y1ZGzQE+4RntZQ7L39qDN8N6VK1gSnL1pEsHui+kLBh8OF+VZWWw2625evbyZ4TPTOccgGf6oOnqNKNn1R6yu7ixK/eOVl1hWUbFZBaWcBvIw1IT4kjA63Q9C9cTqs2abxMzVdP4vdN1M5PC7vNoD9CYBS6GXqw+8B5ODgs6o7ktSNkeUas8XWFxb8xq+m/X112ujTuIcv7loDijzdmKwZq1YLhVEfPTtgGDxZLlGAwIbCvxK2WPjT7h9o+aDZpX3mf7Qwm6+mBMboz4i8b0QnSCIiSBsVx/tHbwA/bH8VwaIqqhZssQMhFCu3RoNlEQ5O9oV4qONmPDhuRNpt/ArBiCyCQ+N4LFvwVQr7t5y7ioW7JVCCoBSjBlQ3b2EEbH/4tbgt9VkCIXN5qSjcu/rmgMQvpYa4Mud6Hq4Z3GNe7jTgc084nD4E2pR5yqxkjgI7axtkHbDLcNKa2yNW7OwIrg0j+iK6AW6TMd/M3oXOH26FAUfdLi72tl6jcS3osbQZ+/8jed+frQdx2GGxT/NLvfLq002T+rgq4InFPcrzXHItfk6pNfAOnYPyB8zw8INSSpa5TOk11CKQ0eOv4SLDbuf8ffRNfOA4cl/dm4M6bANzx9R1RWdRt1bf05NPtzPN7lH32CtCzajFA1wmI6JpcXerG0QosKWjfltSdYTOE2+8SNW2xP3pTuQUpi7X5ewXeJZ06rtXcS09URjZCRd1Vob6zDavL1chuJOmK0eoZpCS0IlaLzIZsiaQXpQeAVVMA8+oUX/JHovkYD+iWy+Q12TtuIR6sOFR6upajX677lFRY+P8NjoharzWKBhZwkxII31I9aU/T59G5/qmWvi+HUiz7Ke/cbIceQeHejjbcyh4coq9K15SvthpAIkO9WohOXsJBIEGBUNA6bzree4nHOkPD9A34FXjjs6dFnbc9S9Edu8PlfKJ5E6I1z680J3UkoA749fHfK8wV5lIVqd81LLYQweT7U5ue2AQmAECxcXW0cBDsMv3mQL9wBcdKdxFOb9ZEKkako1REjm5RuIlJ9tcc9X5ZSE1vCh/enj3Lj1UrY2qNeTYCsSoSEoEmIyarDzG9q4Nd5K5fTW8IHKgDbwA3Al4Nu8fQLlc9OnHp8zUXXr6tfVrn/5LfqdjZANCJuIamnlg/kVBpp6364KbdapnI1B1FoEhKUZbqSx9IxgDpj1bY+0R9Apms4vV7bLFQQks8HsBFxZ80dlVxOt//YqOXy6x4oCmg8x5Gxb6z6oHybcO34LUIUHOHuC+Dcc0B+lAQjINHEn395KNcgZiO57Line truncated
-      }
-    }
-  ]
-}
@@ -1,32 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/streams-text-and-reports-usage",
-    "recordedAt": "2026-10-03T18:08:32.334Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"gemini-3.8-flash\",\"input\":[{\"type\":\"user_input\",\"content\":[{\"type\":\"text\",\"text\":\"Reply with exactly one word: hello\"}]}],\"stream\":true,\"store\":false,\"generation_config\":{\"max_output_tokens\":2048,\"thinking_level\":\"low\"}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: interaction.created\ndata: {\"interaction\":{\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.created\"}\n\nevent: interaction.status_update\ndata: {\"status\":\"in_progress\",\"event_type\":\"interaction.status_update\"}\n\nevent: step.start\ndata: {\"index\":0,\"step\":{\"type\":\"thought\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":0,\"delta\":{\"signature\":\"EmkKZwFpFH0TKZDuA7i8rhztLxjVI9+u+bpJI/x6/j60nie/dFgj5TyzAJCDDZQYfmeXEBrujJcdKT5FiKPuuMYWq1shTTILJ1JQpG2WkGAk6rAxxgxp7Ac0+rporJ7knHFF/jVWQD+AYGY=\",\"type\":\"thought_signature\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":0,\"event_type\":\"step.stop\"}\n\nevent: step.start\ndata: {\"index\":1,\"step\":{\"type\":\"model_output\"},\"event_type\":\"step.start\"}\n\nevent: step.delta\ndata: {\"index\":1,\"delta\":{\"text\":\"hello\",\"type\":\"text\"},\"event_type\":\"step.delta\"}\n\nevent: step.stop\ndata: {\"index\":1,\"event_type\":\"step.stop\"}\n\nevent: interaction.completed\ndata: {\"interaction\":{\"status\":\"completed\",\"usage\":{\"total_tokens\":9,\"total_input_tokens\":8,\"input_tokens_by_modality\":[{\"modality\":\"text\",\"tokens\":8}],\"total_cached_tokens\":0,\"total_output_tokens\":1,\"total_tool_use_tokens\":0,\"total_thought_tokens\":0,\"raw_prompt_token\":39,\"model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":39}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":5}]}],\"non_grounding_model_invocation_token_counts\":[{\"prompt_tokens_details\":[{\"modality\":\"text\",\"tokens\":39}],\"candidates_tokens_details\":[{\"modality\":\"text\",\"tokens\":5}]}]},\"created\":\"2026-10-03T18:08:32Z\",\"updated\":\"2026-10-03T18:08:32Z\",\"service_tier\":\"standard\",\"object\":\"interaction\",\"model\":\"gemini-3.8-flash\"},\"event_type\":\"interaction.completed\"}\n\nevent: done\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -2,16 +2,9 @@
  "version": 1,
  "metadata": {
    "model": "mistral-small-latest",
-    "tags": [
-      "prefix:mistral-chat",
-      "provider:mistral",
-      "protocol:mistral-chat",
-      "tool",
-      "tool-loop",
-      "usage"
-    ],
+    "tags": ["prefix:mistral-chat", "provider:mistral", "protocol:mistral-chat", "tool", "tool-loop", "usage"],
    "name": "mistral-chat/drives-a-tool-loop",
-    "recordedAt": "2026-10-03T04:09:49.878Z"
+    "recordedAt": "2026-08-30T17:18:49.552Z"
  },
  "interactions": [
    {
@@ -22,14 +15,14 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"mistral-small-latest\",\"messages\":[{\"role\":\"system\",\"content\":[{\"type\":\"text\",\"text\":\"Call lookup_weather exactly once with Paris.\"},{\"type\":\"text\",\"text\":\"After the tool result, describe the weather briefly.\"}]},{\"role\":\"user\",\"content\":\"What is the weather?\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\",\"description\":\"Look up the current weather for a city\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\",\"enum\":[\"Paris\"]}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}}],\"tool_choice\":{\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\"}},\"stream\":true,\"max_tokens\":160,\"temperature\":0,\"reasoning_effort\":\"none\"}"
+        "body": "{\"model\":\"mistral-small-latest\",\"messages\":[{\"role\":\"system\",\"content\":\"Call lookup_weather exactly once with Paris.\"},{\"role\":\"user\",\"content\":\"What is the weather?\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\",\"description\":\"Look up the current weather for a city\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\",\"enum\":[\"Paris\"]}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}}],\"tool_choice\":{\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\"}},\"stream\":true,\"max_tokens\":160,\"temperature\":0,\"reasoning_effort\":\"none\"}"
      },
      "response": {
        "status": 200,
        "headers": {
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+          "content-type": "text/event-stream"
+        },
+        "body": ": OPENROUTER PROCESSING\n\n: OPENROUTER PROCESSING\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"Paris\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" is\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" sunny\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" and\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" \",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"22\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"°C\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\".\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"service_tier\":\"default\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"stop\",\"native_finish_reason\":\"completed\"}]}\n\ndata: {\"id\":\"gen-1778031310-JUYfFzDbun699uUYoA4N\",\"object\":\"chat.completion.chunk\",\"created\":1778031310,\"model\":\"openai/gpt-5.5-20260423\",\"provider\":\"OpenAI\",\"service_tier\":\"default\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"stop\",\"native_finish_reason\":\"completed\"}],\"usage\":{\"prompt_tokens\":108,\"completion_tokens\":12,\"total_tokens\":120,\"cost\":0.0009,\"is_byok\":false,\"prompt_tokens_details\":{\"cached_tokens\":0,\"cache_write_tokens\":0,\"audio_tokens\":0,\"video_tokens\":0},\"cost_details\":{\"upstream_inference_cost\":0.0009,\"upstream_inference_prompt_cost\":0.00054,\"upstream_inference_completions_cost\":0.00036},\"completion_tokens_details\":{\"reasoning_tokens\":0,\"image_tokens\":0,\"audio_tokens\":0}}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,28 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "openai-compatible-chat/openrouter-streams-text",
+    "recordedAt": "2026-05-06T01:35:06.767Z",
+    "tags": ["prefix:openai-compatible-chat", "protocol:openai-compatible-chat", "provider:openrouter"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://openrouter.ai/api/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"openai/gpt-4o-mini\",\"messages\":[{\"role\":\"system\",\"content\":\"You are concise.\"},{\"role\":\"user\",\"content\":\"Reply with exactly: Hello!\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_tokens\":20,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": ": OPENROUTER PROCESSING\n\ndata: {\"id\":\"gen-1778031306-UD7bR0I1JNCsPvVzlXat\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"Azure\",\"system_fingerprint\":\"fp_eb37e061ec\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"Hello\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-UD7bR0I1JNCsPvVzlXat\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"Azure\",\"system_fingerprint\":\"fp_eb37e061ec\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"!\",\"role\":\"assistant\"},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-UD7bR0I1JNCsPvVzlXat\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"Azure\",\"system_fingerprint\":\"fp_eb37e061ec\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"stop\",\"native_finish_reason\":\"stop\"}]}\n\ndata: {\"id\":\"gen-1778031306-UD7bR0I1JNCsPvVzlXat\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"Azure\",\"system_fingerprint\":\"fp_eb37e061ec\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"stop\",\"native_finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":21,\"completion_tokens\":3,\"total_tokens\":24,\"cost\":0.00000495,\"is_byok\":false,\"prompt_tokens_details\":{\"cached_tokens\":0,\"cache_write_tokens\":0,\"audio_tokens\":0,\"video_tokens\":0},\"cost_details\":{\"upstream_inference_cost\":0.00000495,\"upstream_inference_prompt_cost\":0.00000315,\"upstream_inference_completions_cost\":0.0000018},\"completion_tokens_details\":{\"reasoning_tokens\":0,\"image_tokens\":0,\"audio_tokens\":0}}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,28 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "openai-compatible-chat/openrouter-streams-tool-call",
+    "recordedAt": "2026-05-06T01:35:07.466Z",
+    "tags": ["prefix:openai-compatible-chat", "protocol:openai-compatible-chat", "provider:openrouter", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://openrouter.ai/api/v1/chat/completions",
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"openai/gpt-4o-mini\",\"messages\":[{\"role\":\"system\",\"content\":\"Call tools exactly as requested.\"},{\"role\":\"user\",\"content\":\"Call get_weather with city exactly Paris.\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}}],\"tool_choice\":{\"type\":\"function\",\"function\":{\"name\":\"get_weather\"}},\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_tokens\":80,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream"
+        },
+        "body": ": OPENROUTER PROCESSING\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"id\":\"call_L7mHMq49ZSUTBHjLJfBIP2eT\",\"type\":\"function\",\"function\":{\"name\":\"get_weather\",\"arguments\":\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"{\\\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"city\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\\\":\\\"\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"Paris\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":null,\"role\":\"assistant\",\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\\\"}\"}}]},\"finish_reason\":null,\"native_finish_reason\":null}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"tool_calls\",\"native_finish_reason\":\"stop\"}]}\n\ndata: {\"id\":\"gen-1778031306-HYzOq04JIk1hZQ4iaNjD\",\"object\":\"chat.completion.chunk\",\"created\":1778031306,\"model\":\"openai/gpt-4o-mini\",\"provider\":\"OpenAI\",\"system_fingerprint\":\"fp_b6580bbee1\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\",\"role\":\"assistant\"},\"finish_reason\":\"tool_calls\",\"native_finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":67,\"completion_tokens\":5,\"total_tokens\":72,\"cost\":0.00001305,\"is_byok\":false,\"prompt_tokens_details\":{\"cached_tokens\":0,\"cache_write_tokens\":0,\"audio_tokens\":0,\"video_tokens\":0},\"cost_details\":{\"upstream_inference_cost\":0.00001305,\"upstream_inference_prompt_cost\":0.00001005,\"upstream_inference_completions_cost\":0.000003},\"completion_tokens_details\":{\"reasoning_tokens\":0,\"image_tokens\":0,\"audio_tokens\":0}}}\n\ndata: [DONE]\n\n"
+      }
+    }
+  ]
+}
@@ -1,169 +0,0 @@
-import { describe, expect } from "bun:test"
-import { Deferred, Effect, Fiber } from "effect"
-import * as TestClock from "effect/testing/TestClock"
-import { HttpOptions, LLM, mergeHttpOptions } from "../src/index.js"
-import { LLMClient } from "../src/route.js"
-import { configure } from "../src/providers/openai.js"
-import { dynamicResponse } from "./lib/http.js"
-import { deltaChunk, finishChunk } from "./lib/openai-chunks.js"
-import { sseEvents, sseRaw } from "./lib/sse.js"
-import { it } from "./lib/effect.js"
-
-const model = configure({ baseURL: "https://api.openai.test/v1/", apiKey: "test" }).chat("gpt-4.1-mini")
-const SSE = { headers: { "content-type": "text/event-stream" } }
-
-const silentServer = dynamicResponse(() => Effect.never)
-
-const slowHeadersServer = dynamicResponse((input) =>
-  Effect.sleep("10 minutes").pipe(
-    Effect.as(input.respond(sseEvents(deltaChunk({ role: "assistant", content: "Hi" }), finishChunk("stop")), SSE)),
-  ),
-)
-
-// Sends one chunk, then stalls until `resume` releases the rest of the body.
-const stalledServer = Effect.gen(function* () {
-  const stalled = yield* Deferred.make<void>()
-  let resume = () => {}
-  const released = new Promise<void>((resolve) => {
-    resume = resolve
-  })
-  const encoder = new TextEncoder()
-  const layer = dynamicResponse((input) =>
-    Effect.sync(() =>
-      input.respond(
-        new ReadableStream<Uint8Array>({
-          start(controller) {
-            controller.enqueue(encoder.encode(sseRaw(`data: ${JSON.stringify(deltaChunk({ content: "Hi" }))}`)))
-          },
-          async pull(controller) {
-            Deferred.doneUnsafe(stalled, Effect.void)
-            await released
-            controller.enqueue(encoder.encode(sseEvents(finishChunk("stop"))))
-            controller.close()
-          },
-        }),
-        SSE,
-      ),
-    ),
-  )
-  return { layer, stalled, resume: () => resume() }
-})
-
-describe("HTTP transport timeouts", () => {
-  it.effect("fails when response headers take longer than five minutes", () =>
-    Effect.gen(function* () {
-      const fiber = yield* LLMClient.generate(LLM.request({ model, prompt: "Hello" })).pipe(
-        Effect.provide(silentServer),
-        Effect.flip,
-        Effect.forkChild({ startImmediately: true }),
-      )
-      yield* TestClock.adjust("5 minutes")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error.reason).toMatchObject({
-        _tag: "Transport",
-        transport: "http",
-        operation: "request",
-        code: "Timeout",
-      })
-    }),
-  )
-
-  it.effect("fails when the response body stalls for five minutes", () =>
-    Effect.gen(function* () {
-      const server = yield* stalledServer
-      const fiber = yield* LLMClient.generate(LLM.request({ model, prompt: "Hello" })).pipe(
-        Effect.provide(server.layer),
-        Effect.flip,
-        Effect.forkChild({ startImmediately: true }),
-      )
-      yield* Deferred.await(server.stalled)
-      yield* Effect.yieldNow
-      yield* TestClock.adjust("5 minutes")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error.reason).toMatchObject({ _tag: "Transport", transport: "http", operation: "read", code: "Timeout" })
-      expect(error.reason.http).toMatchObject({ status: 200 })
-    }),
-  )
-
-  it.effect("applies a configured header timeout", () =>
-    Effect.gen(function* () {
-      const fiber = yield* LLMClient.generate(
-        LLM.request({ model, prompt: "Hello", http: { headerTimeout: 1_000 } }),
-      ).pipe(Effect.provide(silentServer), Effect.flip, Effect.forkChild({ startImmediately: true }))
-      yield* TestClock.adjust("1 second")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error.reason).toMatchObject({ _tag: "Transport", operation: "request", code: "Timeout" })
-    }),
-  )
-
-  it.effect("disables the header timeout with false", () =>
-    Effect.gen(function* () {
-      const fiber = yield* LLMClient.generate(
-        LLM.request({ model, prompt: "Hello", http: { headerTimeout: false } }),
-      ).pipe(Effect.provide(slowHeadersServer), Effect.forkChild({ startImmediately: true }))
-      yield* TestClock.adjust("10 minutes")
-      const response = yield* Fiber.join(fiber)
-
-      expect(response.text).toBe("Hi")
-    }),
-  )
-
-  it.effect("disables the chunk timeout with false", () =>
-    Effect.gen(function* () {
-      const server = yield* stalledServer
-      const fiber = yield* LLMClient.generate(
-        LLM.request({ model, prompt: "Hello", http: { chunkTimeout: false } }),
-      ).pipe(Effect.provide(server.layer), Effect.forkChild({ startImmediately: true }))
-      yield* Deferred.await(server.stalled)
-      yield* Effect.yieldNow
-      yield* TestClock.adjust("10 minutes")
-      server.resume()
-      const response = yield* Fiber.join(fiber)
-
-      expect(response.text).toBe("Hi")
-    }),
-  )
-
-  it.effect("applies a whole-request timeout while the body is still streaming", () =>
-    Effect.gen(function* () {
-      const server = yield* stalledServer
-      const fiber = yield* LLMClient.generate(
-        LLM.request({ model, prompt: "Hello", http: { timeout: 60_000, chunkTimeout: false } }),
-      ).pipe(Effect.provide(server.layer), Effect.flip, Effect.forkChild({ startImmediately: true }))
-      yield* Deferred.await(server.stalled)
-      yield* Effect.yieldNow
-      yield* TestClock.adjust("1 minute")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error.reason).toMatchObject({ _tag: "Transport", operation: "read", code: "Timeout" })
-    }),
-  )
-
-  it.effect("bounds the header wait by a shorter whole-request timeout", () =>
-    Effect.gen(function* () {
-      const fiber = yield* LLMClient.generate(
-        LLM.request({ model, prompt: "Hello", http: { timeout: 1_000, headerTimeout: false } }),
-      ).pipe(Effect.provide(silentServer), Effect.flip, Effect.forkChild({ startImmediately: true }))
-      yield* TestClock.adjust("1 second")
-      const error = yield* Fiber.join(fiber)
-
-      expect(error.reason).toMatchObject({ _tag: "Transport", operation: "request", code: "Timeout" })
-    }),
-  )
-
-  it.effect("merges timeouts with later values winning", () =>
-    Effect.sync(() => {
-      const merged = mergeHttpOptions(
-        new HttpOptions({ timeout: 5_000, headerTimeout: 1_000, chunkTimeout: 2_000 }),
-        new HttpOptions({ headers: { a: "b" } }),
-        new HttpOptions({ chunkTimeout: false }),
-      )
-
-      expect(merged).toMatchObject({ headers: { a: "b" }, timeout: 5_000, headerTimeout: 1_000, chunkTimeout: false })
-      expect(mergeHttpOptions(new HttpOptions({}), undefined)).toBeUndefined()
-    }),
-  )
-})
@@ -8,6 +8,7 @@ import {
  type ProviderMetadata,
  type ToolCallPart,
  ToolResultPart,
+  type ToolResultValue,
  type Usage,
 } from "../../src/schema/index.js"
 import { type Tools, toDefinitions } from "../../src/tool.js"
@@ -15,7 +15,6 @@ describe("provider error classification", () => {
      "Prompt has 5,958,968 tokens, but the configured context size is 256,000 tokens",
      "Range of input length should be [1, 129024]",
      "Too many tokens",
-      "Input validation error: `inputs` tokens + `max_new_tokens` must be <= 131073. Given: 600035 `inputs` tokens and 16 `max_new_tokens`",
      "Token limit exceeded",
    ]

@@ -39,7 +38,9 @@ describe("provider error classification", () => {
    ]

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

@@ -460,27 +461,6 @@ describe("provider error rawBody classification", () => {
    expect(reason._tag === "InvalidRequest" ? reason.classification : reason._tag).toBe("context-overflow")
  })

-  test("separates Cohere prompt overflow from output limit rejections", () => {
-    const classify = (message: string) => {
-      const reason = classifyProviderFailure({
-        message,
-        status: 400,
-        rawBody: JSON.stringify({ error_type: "TOO_MANY_TOKENS", message }),
-      })
-      return reason._tag === "InvalidRequest" ? reason.classification : reason._tag
-    }
-    expect(
-      classify(
-        "too many tokens: size limit exceeded by 168512 tokens. Try using shorter or fewer inputs. The limit for this model is 132000 tokens.",
-      ),
-    ).toBe("context-overflow")
-    expect(
-      classify(
-        "too many tokens: max tokens must be less than or equal to 4096, the maximum output length for this model - received 1000000.",
-      ),
-    ).toBeUndefined()
-  })
-
  test("classifies invalid API keys reported as HTTP 400 as authentication failures", () => {
    const rawBody = JSON.stringify({
      error: {
@@ -121,25 +121,6 @@ describe("provider package entrypoints", () => {
    })
  })

-  test("maps Cohere entrypoints onto native and compatibility routes", async () => {
-    const modules = await Promise.all([
-      import("@opencode/ai/providers/cohere"),
-      import("@opencode/ai/providers/cohere/chat"),
-    ])
-    const settings = { apiKey: "fixture", headers: { "x-test": "fixture" }, body: { future_option: true } }
-    const routes = [
-      ["cohere-chat", "https://api.cohere.com/v2"],
-      ["cohere-chat-completions", "https://api.cohere.ai/compatibility/v1"],
-    ]
-    modules.forEach((module, index) => {
-      const selected = module.model("command-a-03-2025", settings)
-      expect(selected.provider).toBe("cohere")
-      expect([selected.route.id, selected.route.endpoint.baseURL]).toEqual(routes[index])
-      expect(selected.route.defaults.headers).toEqual(settings.headers)
-      expect(selected.route.defaults.http?.body).toEqual(settings.body)
-    })
-  })
-
  test("maps MiniMax API entrypoints onto provider-owned routes", async () => {
    const modules = await Promise.all([
      import("@opencode/ai/providers/minimax"),
@@ -430,7 +411,6 @@ describe("provider package entrypoints", () => {

  test("maps Google package settings onto the Gemini model", async () => {
    const Google = await import("@opencode/ai/providers/google")
-    const GoogleInteractions = await import("@opencode/ai/providers/google/interactions")
    const selected = Google.model("gemini-2.5-flash", {
      apiKey: "fixture",
      baseURL: "https://generativelanguage.test/v1beta",
@@ -444,16 +424,6 @@ describe("provider package entrypoints", () => {
    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
    expect(selected.route.defaults.http?.body).toEqual({ safetySettings: [] })
    expect(selected.route.defaults.providerOptions).toEqual({ thinkingConfig: { thinkingBudget: 1_024 } })
-    const interactions = GoogleInteractions.model("gemini-3.8-flash", {
-      apiKey: "fixture",
-      baseURL: "https://generativelanguage.test/v1beta",
-      thinkingLevel: "low",
-      store: true,
-    })
-    expect(interactions.route.id).toBe("google-interactions")
-    expect(interactions.route.endpoint.baseURL).toBe("https://generativelanguage.test/v1beta")
-    expect(interactions.route.defaults.providerOptions).toEqual({ thinkingLevel: "low", store: true })
-    expect(Google.configure().interactions("gemini-3.8-flash").route.protocol).toBe("google-interactions")
  })

  test("selects Vertex entrypoints with the same model contract", async () => {
@@ -314,9 +314,6 @@ describe("Anthropic Messages route", () => {
        "claude-haiku-5-1",
        "claude-fable-6",
        "anthropic/claude-mythos-7.2",
-        "claude-sonnet-5-5",
-        "claude-opus-4-8@20260101",
-        "claude-nova-6",
      ]

      const prepared = yield* Effect.forEach(ids, (id) =>
@@ -21,6 +21,7 @@ import {
 import { LLMClient } from "../../src/route.js"
 import { compileRequest } from "../../src/route/client.js"
 import { AmazonBedrock } from "../../src/providers.js"
+import * as BedrockConverse from "../../src/protocols/bedrock-converse.js"
 import { it } from "../lib/effect.js"
 import { withProcessEnv } from "../lib/env.js"
 import { dynamicResponse, fixedResponse } from "../lib/http.js"
@@ -647,177 +648,6 @@ describe("Bedrock Converse route", () => {
    }),
  )

-  it.effect("hoists tool-result images beside the result for Bedrock GPT models", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
-            "global.openai.gpt-6-sol",
-          ),
-          messages: [
-            Message.user("What is in this image?"),
-            Message.assistant([ToolCallPart.make({ id: "tool_1", name: "read", input: {} })]),
-            Message.tool({
-              id: "tool_1",
-              name: "read",
-              result: {
-                type: "content",
-                value: [
-                  { type: "text", text: "Image loaded." },
-                  { type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" },
-                  { type: "file", uri: "data:application/pdf;base64,QkI=", mime: "application/pdf", name: "note.pdf" },
-                ],
-              },
-            }),
-          ],
-          cache: "none",
-        }),
-      )
-
-      expect(prepared.body.messages[2]).toEqual({
-        role: "user",
-        content: [
-          {
-            toolResult: {
-              toolUseId: "tool_1",
-              content: [
-                { text: "Image loaded." },
-                { text: 'Attached file "note.pdf" has document label "note".' },
-                { document: { format: "pdf", name: "note", source: { bytes: "QkI=" } } },
-              ],
-              status: "success",
-            },
-          },
-          { image: { format: "png", source: { bytes: "AAAA" } } },
-        ],
-      })
-    }),
-  )
-
-  it.effect("hoists tool-result images for other Bedrock model families", () =>
-    Effect.gen(function* () {
-      for (const id of [
-        "qwen.qwen3-vl-235b-a22b",
-        "global.xai.grok-4.7",
-        "global.moonshotai.kimi-k3",
-        "us.meta.llama4-scout-17b-instruct-v1:0",
-      ]) {
-        const prepared = yield* compileRequest(
-          LLM.request({
-            model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
-              id,
-            ),
-            messages: [
-              Message.assistant([ToolCallPart.make({ id: "tool_1", name: "read", input: {} })]),
-              Message.tool({
-                id: "tool_1",
-                name: "read",
-                result: {
-                  type: "content",
-                  value: [{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" }],
-                },
-              }),
-            ],
-            cache: "none",
-          }),
-        )
-        expect(prepared.body.messages[1]).toEqual({
-          role: "user",
-          content: [
-            { toolResult: { toolUseId: "tool_1", content: [{ text: "See attached image." }], status: "success" } },
-            { image: { format: "png", source: { bytes: "AAAA" } } },
-          ],
-        })
-      }
-    }),
-  )
-  ;["global.anthropic.claude-sonnet-4-5-20250929-v1:0", "us.amazon.nova-pro-v1:0"].forEach((id) => {
-    it.effect(`keeps ${id} tool images inside the result`, () =>
-      Effect.gen(function* () {
-        const prepared = yield* compileRequest(
-          LLM.request({
-            model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
-              id,
-            ),
-            messages: [
-              Message.assistant([ToolCallPart.make({ id: "tool_1", name: "read", input: {} })]),
-              Message.tool({
-                id: "tool_1",
-                name: "read",
-                result: {
-                  type: "content",
-                  value: [{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" }],
-                },
-              }),
-            ],
-            cache: "none",
-          }),
-        )
-
-        expect(prepared.body.messages[1]).toEqual({
-          role: "user",
-          content: [
-            {
-              toolResult: {
-                toolUseId: "tool_1",
-                content: [{ image: { format: "png", source: { bytes: "AAAA" } } }],
-                status: "success",
-              },
-            },
-          ],
-        })
-      }),
-    )
-  })
-
-  it.effect("keeps parallel tool results before hoisted images and gives image-only results text", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: AmazonBedrock.configure({ baseURL: "https://bedrock-runtime.test", apiKey: "test-bearer" }).model(
-            "global.openai.gpt-6-sol",
-          ),
-          messages: [
-            Message.assistant([
-              ToolCallPart.make({ id: "tool_1", name: "first", input: {} }),
-              ToolCallPart.make({ id: "tool_2", name: "second", input: {} }),
-            ]),
-            Message.tool({
-              id: "tool_1",
-              name: "first",
-              result: {
-                type: "content",
-                value: [{ type: "file", uri: "data:image/png;base64,AAAA", mime: "image/png" }],
-              },
-            }),
-            Message.tool({
-              id: "tool_2",
-              name: "second",
-              result: {
-                type: "content",
-                value: [
-                  { type: "text", text: "Second image." },
-                  { type: "file", uri: "data:image/jpeg;base64,BBBB", mime: "image/jpeg" },
-                ],
-              },
-            }),
-          ],
-          cache: "none",
-        }),
-      )
-
-      expect(prepared.body.messages[1]).toEqual({
-        role: "user",
-        content: [
-          { toolResult: { toolUseId: "tool_1", content: [{ text: "See attached image." }], status: "success" } },
-          { toolResult: { toolUseId: "tool_2", content: [{ text: "Second image." }], status: "success" } },
-          { image: { format: "png", source: { bytes: "AAAA" } } },
-          { image: { format: "jpeg", source: { bytes: "BBBB" } } },
-        ],
-      })
-    }),
-  )
-
  it.effect("decodes text-delta + messageStop + metadata usage from binary event stream", () =>
    Effect.gen(function* () {
      const body = eventStreamBody(
@@ -1,4 +1,4 @@
-import { describe, expect } from "bun:test"
+import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect, Schema } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
 import { LLM, LLMEvent } from "../../src/index.js"
@@ -1,98 +0,0 @@
-import { expect } from "bun:test"
-import { Effect } from "effect"
-import { LLM, LLMEvent, LLMRequest, SystemPart } from "../../src/index.js"
-import { Cohere } from "../../src/providers/cohere.js"
-import { LLMClient } from "../../src/route.js"
-import { expectWeatherToolLoop, goldenWeatherToolLoopRequest, runWeatherToolLoop } from "../recorded-scenarios.js"
-import { recordedTests } from "../recorded-test.js"
-
-const recorded = recordedTests({ prefix: "cohere", provider: "cohere", requires: ["COHERE_API_KEY"] })
-const cohere = Cohere.configure({ apiKey: process.env.COHERE_API_KEY ?? "fixture" })
-
-recorded.effect(
-  "streams native text and usage",
-  () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: cohere.model("command-a-03-2025"),
-          prompt: "Reply exactly: OK",
-          generation: { maxTokens: 64 },
-        }),
-      )
-      expect(response.text.trim()).toMatch(/^OK\.?$/)
-      expect(response.usage.inputTokens).toBeGreaterThan(0)
-      expect(response.usage.outputTokens).toBeGreaterThan(0)
-      expect(response.events.find(LLMEvent.is.finish)?.reason).toEqual({ normalized: "stop", raw: "COMPLETE" })
-      expect(response.usage.providerMetadata?.cohere?.billed_units).toBeDefined()
-    }),
-  60_000,
-)
-
-recorded.effect(
-  "streams native thinking with a budget",
-  () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: cohere.model("command-a-reasoning-08-2025"),
-          prompt: "What is 17 times 23? Answer briefly.",
-          providerOptions: { thinking: { type: "enabled", tokenBudget: 128 } },
-          generation: { maxTokens: 2048 },
-        }),
-      )
-      expect(response.reasoning.length).toBeGreaterThan(0)
-      expect(response.text).toContain("391")
-      expect(response.usage.reasoningTokens).toBeGreaterThan(0)
-      expect(response.usage.reasoningTokens).toBeLessThanOrEqual(128)
-      expect(response.events.filter(LLMEvent.is.finish)).toHaveLength(1)
-    }),
-  60_000,
-)
-
-recorded.effect(
-  "continues a native tool call",
-  () =>
-    Effect.gen(function* () {
-      const events = yield* runWeatherToolLoop(
-        LLMRequest.update(
-          goldenWeatherToolLoopRequest({
-            id: "cohere-tool-loop",
-            model: cohere.model("command-a-plus-05-2026"),
-            maxTokens: 2048,
-            temperature: false,
-          }),
-          {
-            system: [
-              SystemPart.make("Use the get_weather tool exactly once."),
-              SystemPart.make("After the tool result, reply exactly: Paris is sunny."),
-            ],
-          },
-        ),
-      )
-      expectWeatherToolLoop(events)
-      expect(events.some(LLMEvent.is.toolInputDelta)).toBe(true)
-    }),
-  60_000,
-)
-
-recorded.effect(
-  "streams compatible chat reasoning",
-  () =>
-    Effect.gen(function* () {
-      const response = yield* LLMClient.generate(
-        LLM.request({
-          model: cohere.chat("command-a-reasoning-08-2025"),
-          prompt: "What is 17 times 23? Answer briefly.",
-          providerOptions: { reasoningEffort: "high" },
-          generation: { maxTokens: 2048 },
-        }),
-      )
-      expect(response.reasoning.length).toBeGreaterThan(0)
-      expect(response.text).toContain("391")
-      expect(response.events.find(LLMEvent.is.finish)?.reason.normalized).toBe("stop")
-      expect(response.usage.inputTokens).toBeGreaterThan(0)
-      expect(response.usage.reasoningTokens).toBeGreaterThan(0)
-    }),
-  60_000,
-)
@@ -1,272 +0,0 @@
-import { expect, test } from "bun:test"
-import { Effect } from "effect"
-import { LLM, LLMClient, LLMEvent, Media, Message, SystemPart, isRetryable } from "../../src/index.js"
-import { Cohere } from "../../src/providers/cohere.js"
-import { compileRequest } from "../../src/route/client.js"
-import { it } from "../lib/effect.js"
-import { fixedResponse } from "../lib/http.js"
-import { sseEvents } from "../lib/sse.js"
-
-const cohere = Cohere.configure({ apiKey: "fixture" })
-
-test("Cohere exposes native and compatible endpoints without Core remapping", () => {
-  expect(cohere.model("command-a-03-2025").route.endpoint.baseURL).toBe("https://api.cohere.com/v2")
-  expect(cohere.chat("command-a-03-2025").route.endpoint.baseURL).toBe("https://api.cohere.ai/compatibility/v1")
-  expect(
-    Cohere.model("command-a-03-2025", { apiKey: "fixture", headers: { "X-Test": "yes" }, body: { temperature: 0 } })
-      .route.defaults?.http,
-  ).toMatchObject({ body: { temperature: 0 } })
-})
-
-it.effect("Cohere lowers native history, thinking, tools, and sampling", () =>
-  Effect.gen(function* () {
-    const prepared = yield* compileRequest(
-      LLM.request({
-        model: cohere.model("command-a-reasoning-08-2025"),
-        system: [SystemPart.make("Be concise.\nKeep this newline."), SystemPart.make("Second instructions.")],
-        messages: [
-          Message.user("Lookup Paris"),
-          Message.assistant([{ type: "tool-call", id: "lookup-1", name: "lookup", input: { city: "Paris" } }]),
-          Message.tool({ id: "lookup-1", name: "lookup", result: { sunny: true } }),
-        ],
-        tools: [{ name: "lookup", description: "Look up a city", inputSchema: { type: "object", properties: {} } }],
-        toolChoice: "required",
-        providerOptions: { thinking: { tokenBudget: 128 } },
-        generation: { maxTokens: 2048, topP: 0.9, topK: 10 },
-      }),
-    )
-    expect(prepared.body).toMatchObject({
-      model: "command-a-reasoning-08-2025",
-      stream: true,
-      p: 0.9,
-      k: 10,
-      max_tokens: 2048,
-      thinking: { type: "enabled", token_budget: 128 },
-      tool_choice: "REQUIRED",
-      messages: [
-        {
-          role: "system",
-          content: [
-            { type: "text", text: "Be concise.\nKeep this newline." },
-            { type: "text", text: "Second instructions." },
-          ],
-        },
-        { role: "user", content: [{ type: "text", text: "Lookup Paris" }] },
-        {
-          role: "assistant",
-          tool_calls: [{ id: "lookup-1", function: { name: "lookup", arguments: '{"city":"Paris"}' } }],
-        },
-        { role: "tool", tool_call_id: "lookup-1", content: '{"sunny":true}' },
-      ],
-    })
-  }),
-)
-
-it.effect("Cohere compatibility omits unsupported OpenAI fields", () =>
-  Effect.gen(function* () {
-    const prepared = yield* compileRequest(
-      LLM.request({
-        model: cohere.chat("command-a-reasoning-08-2025"),
-        prompt: "Hello",
-        providerOptions: { reasoningEffort: "high" },
-        generation: { maxTokens: 64 },
-      }),
-    )
-    expect(prepared.body).toMatchObject({ reasoning_effort: "high", max_tokens: 64, stream: true })
-    expect(prepared.body.stream_options).toEqual({ include_usage: true })
-    for (const key of ["store", "max_completion_tokens", "parallel_tool_calls", "prompt_cache_key"])
-      expect(prepared.body[key]).toBeUndefined()
-  }),
-)
-
-it.effect("Cohere maps inclusive usage while retaining distinct billed units", () =>
-  Effect.gen(function* () {
-    const response = yield* LLMClient.generate(
-      LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
-    ).pipe(
-      Effect.provide(
-        fixedResponse(
-          sseEvents(
-            { type: "message-start" },
-            { type: "content-start", index: 0, delta: { message: { content: { type: "thinking", thinking: "" } } } },
-            { type: "content-delta", index: 0, delta: { message: { content: { thinking: "Think" } } } },
-            { type: "content-end", index: 0 },
-            { type: "content-start", index: 1, delta: { message: { content: { type: "text", text: "" } } } },
-            { type: "content-delta", index: 1, delta: { message: { content: { text: "OK" } } } },
-            { type: "content-end", index: 1 },
-            {
-              type: "message-end",
-              delta: {
-                finish_reason: "COMPLETE",
-                usage: {
-                  tokens: { input_tokens: 100, output_tokens: 20, reasoning_tokens: 10 },
-                  billed_units: { input_tokens: 30, output_tokens: 15 },
-                  cached_tokens: 60,
-                },
-              },
-            },
-          ),
-        ),
-      ),
-    )
-    expect(response.text).toBe("OK")
-    expect(response.reasoning).toBe("Think")
-    expect(response.usage).toMatchObject({
-      inputTokens: 100,
-      nonCachedInputTokens: 40,
-      cacheReadInputTokens: 60,
-      outputTokens: 20,
-      reasoningTokens: 10,
-      totalTokens: 120,
-      providerMetadata: { cohere: { billed_units: { input_tokens: 30, output_tokens: 15 } } },
-    })
-    expect(response.events.filter(LLMEvent.is.finish)).toHaveLength(1)
-  }),
-)
-
-it.effect("Cohere rejects incomplete streams", () =>
-  Effect.gen(function* () {
-    const error = yield* LLMClient.generate(
-      LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
-    ).pipe(Effect.provide(fixedResponse(sseEvents({ type: "message-start" }))), Effect.flip)
-    expect(error.message).toContain("without message-end")
-  }),
-)
-
-it.effect("Cohere preserves native tool plans in continued history", () =>
-  Effect.gen(function* () {
-    const response = yield* LLMClient.generate(
-      LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
-    ).pipe(
-      Effect.provide(
-        fixedResponse(
-          sseEvents(
-            { type: "message-start" },
-            { type: "tool-plan-delta", delta: { message: { tool_plan: "Look up the weather." } } },
-            {
-              type: "tool-call-start",
-              index: 0,
-              delta: { message: { tool_calls: { id: "lookup-1", function: { name: "lookup", arguments: "" } } } },
-            },
-            {
-              type: "tool-call-delta",
-              index: 0,
-              delta: { message: { tool_calls: { function: { arguments: '{"city":"Paris"}' } } } },
-            },
-            { type: "tool-call-end", index: 0 },
-            { type: "message-end", delta: { finish_reason: "TOOL_CALL" } },
-          ),
-        ),
-      ),
-    )
-    expect(response.toolCalls[0]?.input).toEqual({ city: "Paris" })
-    const prepared = yield* compileRequest(
-      LLM.request({
-        model: cohere.model("command-a-03-2025"),
-        messages: [response.message, Message.tool({ id: "lookup-1", name: "lookup", result: { sunny: true } })],
-      }),
-    )
-    expect(prepared.body.messages).toMatchObject([
-      { role: "assistant", tool_plan: "Look up the weather.", tool_calls: [{ id: "lookup-1" }] },
-      { role: "tool", tool_call_id: "lookup-1" },
-    ])
-  }),
-)
-
-it.effect("Cohere rejects unsupported media instead of silently dropping it", () =>
-  Effect.gen(function* () {
-    const error = yield* compileRequest(
-      LLM.request({
-        model: cohere.model("command-a-03-2025"),
-        messages: [Message.user([{ type: "media", media: Media.base64("Zm9v", "audio/wav") }])],
-      }),
-    ).pipe(Effect.flip)
-    expect(error.reason._tag).toBe("InvalidRequest")
-  }),
-)
-
-it.effect("Cohere thinking budgets must be positive integers", () =>
-  Effect.gen(function* () {
-    const error = yield* compileRequest(
-      LLM.request({
-        model: cohere.model("command-a-reasoning-08-2025"),
-        providerOptions: { thinking: { tokenBudget: 0 } },
-      }),
-    ).pipe(Effect.flip)
-    expect(error.reason._tag).toBe("InvalidRequest")
-  }),
-)
-
-it.effect("Cohere fits thinking budgets under the output limit", () =>
-  Effect.gen(function* () {
-    const prepared = yield* compileRequest(
-      LLM.request({
-        model: cohere.model("command-a-reasoning-08-2025"),
-        prompt: "Hi",
-        providerOptions: { thinking: { tokenBudget: 31_999 } },
-        generation: { maxTokens: 4096 },
-      }),
-    )
-    expect(prepared.body.thinking).toEqual({ type: "enabled", token_budget: 2048 })
-  }),
-)
-
-// Bodies captured live on 2026-10-02, except 402 and 429, which are Cohere's documented messages.
-const errors = [
-  { status: 401, message: "Incorrect API key provided: ***-123.", tag: "Authentication", retry: false },
-  { status: 404, message: "model 'no-such-model-xyz' not found", tag: "InvalidRequest", retry: false },
-  {
-    status: 400,
-    message: "invalid request: temperature must be between 0 and 2.0 inclusive.",
-    tag: "InvalidRequest",
-    retry: false,
-  },
-  {
-    status: 400,
-    error_type: "TOO_MANY_TOKENS",
-    message: "too many tokens: size limit exceeded by 168512 tokens. The limit for this model is 132000 tokens.",
-    tag: "InvalidRequest",
-    classification: "context-overflow",
-    retry: false,
-  },
-  {
-    status: 400,
-    error_type: "TOO_MANY_TOKENS",
-    message:
-      "too many tokens: max tokens must be less than or equal to 4096, the maximum output length for this model - received 1000000.",
-    tag: "InvalidRequest",
-    retry: false,
-  },
-  { status: 402, message: "Please add or update your payment method to continue", tag: "QuotaExceeded", retry: false },
-  {
-    status: 429,
-    message: "You are using a Trial key, which is limited to 40 API calls / minute.",
-    tag: "RateLimit",
-    retry: true,
-  },
-  { status: 500, message: "internal server error", tag: "ProviderInternal", retry: true },
-]
-
-it.effect("Cohere HTTP errors map to AI error reasons", () =>
-  Effect.forEach(errors, (item) =>
-    Effect.gen(function* () {
-      const error = yield* LLMClient.generate(
-        LLM.request({ model: cohere.model("command-a-03-2025"), prompt: "Hi" }),
-      ).pipe(
-        Effect.provide(
-          fixedResponse(JSON.stringify({ id: "fixture", error_type: item.error_type, message: item.message }), {
-            status: item.status,
-            headers: { "content-type": "application/json" },
-          }),
-        ),
-        Effect.flip,
-      )
-      expect({
-        message: error.message,
-        tag: error.reason._tag,
-        classification: error.reason._tag === "InvalidRequest" ? error.reason.classification : undefined,
-        retry: isRetryable(error),
-      }).toEqual({ message: item.message, tag: item.tag, classification: item.classification, retry: item.retry })
-    }),
-  ),
-)