tui: await renderer before terminal handoff

Ensure terminal ownership changes complete before suspending or launching an external editor, preventing stale renders during resume.
bump snapshot
2026-10-05 23:16:19 +00:00 · 2026-10-02 21:09:44 +02:00 · 2026-10-02 12:52:48 +02:00 · 2026-10-02 12:52:48 +02:00 · 2026-10-02 12:52:47 +02:00
1171 changed files with 19902 additions and 43535 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:
@@ -252,13 +252,6 @@ jobs:
          CI: true
        timeout-minutes: 15

-      - name: Run app component tests
-        if: ${{ !cancelled() && env.E2E_ENABLED == 'true' }}
-        run: bun --cwd packages/app test:components
-        env:
-          CI: true
-        timeout-minutes: 15
-
      - name: Upload Playwright artifacts
        if: always() && env.E2E_ENABLED == 'true'
        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
@@ -271,5 +264,3 @@ jobs:
            packages/app/e2e/playwright-report
            packages/session-ui/component-tests/test-results
            packages/session-ui/component-tests/playwright-report
-            packages/app/component-tests/test-results
-            packages/app/component-tests/playwright-report
@@ -63,60 +63,8 @@
        "anti-slop-effect/prefer-effect-match": "warn"
      }
    },
-    {
-      "files": ["packages/gui-extensions/src/*.ts", "packages/gui-extensions/src/*.tsx"],
-      "rules": {
-        "no-restricted-imports": [
-          "error",
-          {
-            "paths": [
-              {
-                "name": "solid-js",
-                "importNames": ["createEffect", "createRenderEffect", "createComputed"],
-                "message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
-              }
-            ]
-          }
-        ]
-      }
-    },
    {
      "files": ["packages/gui-extensions/src/*/**"],
-      "rules": {
-        "no-restricted-imports": [
-          "error",
-          {
-            "paths": [
-              {
-                "name": "solid-js",
-                "importNames": ["createEffect", "createRenderEffect", "createComputed"],
-                "message": "Extension code runs side effects through the SDK: createKeyed(source, fn, { otherwise }) per provider generation or value, createMemo or a plain function for derived values, createLatest for async data, createVisitState for per-visit state, and the handler for logic a user action causes. An escape hatch needs an oxlint-disable comment with a reason."
-              }
-            ],
-            "patterns": [
-              {
-                "regex": "^@opencode/(app|desktop)(/|$)",
-                "message": "GUI extensions never import the app or desktop packages. Use the SDK."
-              },
-              {
-                "regex": "^@/",
-                "message": "GUI extensions never import app internals. Use the SDK."
-              },
-              {
-                "group": ["../*/*", "!../*/contract", "!../sdk/*"],
-                "message": "Import another extension only through its contract.ts."
-              },
-              {
-                "regex": "\\.css$",
-                "message": "Import CSS with ?inline and contribute it with ctx.add(Style, css)."
-              }
-            ]
-          }
-        ]
-      }
-    },
-    {
-      "files": ["packages/gui-extensions/src/sdk/**"],
      "rules": {
        "no-restricted-imports": [
          "error",
@@ -33,7 +33,7 @@
    },
    "packages/ai": {
      "name": "@opencode/ai",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/credential-providers": "3.1057.0",
        "@opencode/schema": "workspace:*",
@@ -55,7 +55,7 @@
    },
    "packages/app": {
      "name": "@opencode/app",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@corvu/drawer": "catalog:",
        "@dnd-kit/abstract": "0.5.0",
@@ -112,7 +112,7 @@
    },
    "packages/cli": {
      "name": "@opencode/cli",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "bin": {
        "opencode": "./bin/opencode.cjs",
        "opencode2": "./bin/opencode2.cjs",
@@ -122,7 +122,7 @@
        "@clack/core": "1.0.0-alpha.1",
        "@clack/prompts": "1.0.0-alpha.1",
        "@effect/platform-node": "catalog:",
-        "@opencode-ai/pty": "0.2.0",
+        "@opencode-ai/pty": "0.1.13",
        "@opencode/client": "workspace:*",
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -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": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/protocol": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -205,7 +204,7 @@
    },
    "packages/codemode": {
      "name": "@opencode/codemode",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "acorn": "8.15.0",
        "effect": "catalog:",
@@ -218,7 +217,7 @@
    },
    "packages/console/app": {
      "name": "@opencode/console-app",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@ibm/plex": "6.4.1",
@@ -254,7 +253,7 @@
    },
    "packages/console/core": {
      "name": "@opencode/console-core",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/client-sts": "3.782.0",
        "@jsx-email/render": "1.1.1",
@@ -281,7 +280,7 @@
    },
    "packages/console/function": {
      "name": "@opencode/console-function",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@openauthjs/openauth": "0.0.0-20250322224806",
        "@opencode/console-core": "workspace:*",
@@ -298,7 +297,7 @@
    },
    "packages/console/mail": {
      "name": "@opencode/console-mail",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@jsx-email/all": "2.2.3",
        "@jsx-email/cli": "1.4.3",
@@ -322,7 +321,7 @@
    },
    "packages/console/support": {
      "name": "@opencode/console-support",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@opencode/console-core": "workspace:*",
@@ -342,7 +341,7 @@
    },
    "packages/core": {
      "name": "@opencode/core",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@ai-sdk/cohere": "3.0.27",
        "@ai-sdk/gateway": "3.0.104",
@@ -355,7 +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:",
@@ -383,6 +382,7 @@
        "mime-types": "3.0.2",
        "tree-sitter-bash": "0.25.0",
        "tree-sitter-powershell": "0.25.10",
+        "venice-ai-sdk-provider": "2.1.1",
        "web-tree-sitter": "0.25.10",
        "which": "6.0.1",
        "zod": "catalog:",
@@ -410,7 +410,7 @@
    },
    "packages/desktop": {
      "name": "@opencode/desktop",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@zip.js/zip.js": "2.7.62",
        "electron-context-menu": "5.0.0",
@@ -455,7 +455,7 @@
    },
    "packages/enterprise": {
      "name": "@opencode/enterprise",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@hono/standard-validator": "catalog:",
        "@opencode-ai/sdk": "1.18.21",
@@ -492,7 +492,7 @@
    },
    "packages/function": {
      "name": "@opencode/function",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@octokit/auth-app": "8.0.1",
        "@octokit/rest": "catalog:",
@@ -508,7 +508,7 @@
    },
    "packages/gui-extensions": {
      "name": "@opencode/gui-extensions",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@dnd-kit/abstract": "0.5.0",
        "@dnd-kit/dom": "0.5.0",
@@ -553,7 +553,7 @@
    },
    "packages/http-recorder": {
      "name": "@opencode/http-recorder",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@effect/platform-node-shared": "4.0.0-rc.112",
      },
@@ -572,7 +572,7 @@
    },
    "packages/httpapi-codegen": {
      "name": "@opencode/httpapi-codegen",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "effect": "catalog:",
        "prettier": "3.6.2",
@@ -585,7 +585,7 @@
    },
    "packages/latex": {
      "name": "@opencode/latex",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -599,7 +599,7 @@
    },
    "packages/merman": {
      "name": "@opencode/merman",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -614,7 +614,7 @@
    },
    "packages/plugin": {
      "name": "@opencode/plugin",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@ai-sdk/provider": "3.0.8",
        "@opencode/ai": "workspace:*",
@@ -640,8 +640,8 @@
      },
      "peerDependencies": {
        "@opencode/theme": "workspace:*",
-        "@opentui/core": ">=0.5.14",
-        "@opentui/solid": ">=0.5.14",
+        "@opentui/core": "0.0.0-20261002-f9ace790",
+        "@opentui/solid": "0.0.0-20261002-f9ace790",
        "solid-js": ">=1.9.0",
      },
      "optionalPeers": [
@@ -653,7 +653,7 @@
    },
    "packages/plugin-browser": {
      "name": "@opencode/plugin-browser",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -683,7 +683,7 @@
    },
    "packages/protocol": {
      "name": "@opencode/protocol",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/schema": "workspace:*",
        "effect": "catalog:",
@@ -698,7 +698,7 @@
    },
    "packages/schema": {
      "name": "@opencode/schema",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@standard-schema/spec": "catalog:",
        "effect": "catalog:",
@@ -722,7 +722,7 @@
    },
    "packages/sdk": {
      "name": "@opencode/sdk",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -743,7 +743,7 @@
    },
    "packages/server": {
      "name": "@opencode/server",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@effect/platform-node": "catalog:",
        "@effect/platform-node-shared": "catalog:",
@@ -765,7 +765,7 @@
    },
    "packages/session-ui": {
      "name": "@opencode/session-ui",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode/client": "workspace:*",
@@ -800,7 +800,7 @@
    },
    "packages/simulation": {
      "name": "@opencode/simulation",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/ai": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -820,7 +820,7 @@
    },
    "packages/stats/app": {
      "name": "@opencode/stats-app",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@ibm/plex": "6.4.1",
        "@kobalte/core": "catalog:",
@@ -854,7 +854,7 @@
    },
    "packages/stats/core": {
      "name": "@opencode/stats-core",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/client-athena": "3.933.0",
        "@planetscale/database": "1.19.0",
@@ -873,7 +873,7 @@
    },
    "packages/stats/server": {
      "name": "@opencode/stats-server",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@aws-sdk/client-firehose": "3.933.0",
        "@effect/platform-node": "catalog:",
@@ -919,7 +919,7 @@
    },
    "packages/theme": {
      "name": "@opencode/theme",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opentui/core": "catalog:",
        "effect": "catalog:",
@@ -933,7 +933,7 @@
    },
    "packages/tui": {
      "name": "@opencode/tui",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -967,7 +967,7 @@
    },
    "packages/ui": {
      "name": "@opencode/ui",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@pierre/diffs": "catalog:",
@@ -1002,7 +1002,7 @@
    },
    "packages/util": {
      "name": "@opencode/util",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@effect/opentelemetry": "catalog:",
        "@effect/platform-node": "catalog:",
@@ -1040,7 +1040,7 @@
    },
    "packages/web": {
      "name": "@opencode/web",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "@astrojs/cloudflare": "12.6.3",
        "@astrojs/markdown-remark": "6.3.1",
@@ -1081,7 +1081,7 @@
    },
    "services/update": {
      "name": "@opencode/update",
-      "version": "2.0.23",
+      "version": "2.0.22",
      "dependencies": {
        "jose": "6.0.11",
        "semver": "catalog:",
@@ -1134,9 +1134,9 @@
  },
  "overrides": {
    "@effect/platform-node-shared": "catalog:",
-    "@opentui/core": "catalog:",
-    "@opentui/keymap": "catalog:",
-    "@opentui/solid": "catalog:",
+    "@opentui/core": "0.0.0-20261002-f9ace790",
+    "@opentui/keymap": "0.0.0-20261002-f9ace790",
+    "@opentui/solid": "0.0.0-20261002-f9ace790",
    "@types/bun": "catalog:",
    "@types/node": "catalog:",
    "bun-types": "1.4.2",
@@ -1158,9 +1158,9 @@
    "@npmcli/arborist": "9.4.0",
    "@octokit/rest": "22.0.0",
    "@openauthjs/openauth": "0.0.0-20250322224806",
-    "@opentui/core": "0.5.14",
-    "@opentui/keymap": "0.5.14",
-    "@opentui/solid": "0.5.14",
+    "@opentui/core": "0.0.0-20261002-f9ace790",
+    "@opentui/keymap": "0.0.0-20261002-f9ace790",
+    "@opentui/solid": "0.0.0-20261002-f9ace790",
    "@pierre/diffs": "1.5.1",
    "@playwright/test": "1.59.1",
    "@sentry/solid": "10.71.0",
@@ -2166,19 +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=="],
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    "anymatch/picomatch": ["picomatch@2.3.2", "", {}, "sha512-V7+vQEJ06Z+c5tSye8S+nHUfI51xoXIXjHQ99cQtKUkQqqO1kO/KCJUfZXuB47h/YBlDhah2H3hdUGXn8ie0oA=="],
@@ -6690,6 +6702,12 @@

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

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

    "vite-plugin-icons-spritesheet/chalk": ["chalk@5.6.2", "", {}, "sha512-7NzBL0rN6fMUW+f7A6Io4h40qQlG+xGmtMxfbnH/K7TAtt8JQWVQK+6g0UXKMeVJoyV5EkkNsErQ8pVD3bLHbA=="],
@@ -7238,6 +7256,8 @@

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

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

    "ansi-align/string-width/strip-ansi": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
@@ -7536,6 +7556,10 @@

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

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

    "vscode-languageserver/vscode-languageserver-protocol/vscode-jsonrpc": ["vscode-jsonrpc@8.2.0", "", {}, "sha512-C+r0eKJUIfiDIfwJhria30+TYWPtuHJXHtI7J0YlOmKAo7ogxP20T0zxB7HZQIFhIyvoBPwWskjxrvAtfjyZfA=="],
@@ -8414,6 +8438,8 @@

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

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

    "@astrojs/cloudflare/@cloudflare/vite-plugin/miniflare/sharp/@img/sharp-darwin-arm64": ["@img/sharp-darwin-arm64@0.35.2", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.3.1" }, "os": "darwin", "cpu": "arm64" }, "sha512-eEieHsMksAW4IiO5NzauESRl2D2qz3J/kwUxUrSfV06A93eEaRfMpHXyUb1mAqrR7i8U9A0GRqE9pjn6u1Jjpg=="],
@@ -40,8 +40,6 @@ stdenv.mkDerivation (finalAttrs: {
    copyDesktopItems
  ]
  ++ lib.optionals stdenv.hostPlatform.isDarwin [
-    darwin.cctools
-    darwin.sigtool
    # Ad-hoc sign the .app: --config.mac.identity=null below skips signing.
    darwin.autoSignDarwinBinariesHook
  ];
@@ -1,7 +1,7 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-4AqU8dPEwo0ukoyEX1SuDVzsXQ7G/fIPnxoL400zH4M=",
-    "aarch64-linux": "sha256-p75sJYtR8a4oVKb1+Dgp8Kl+1onSmUw5NRv95bbV1+E=",
-    "aarch64-darwin": "sha256-Psyvbw/lGulysQlhK/MqcHVIwx2aCDTr+Pfr+gRWsG4="
+    "x86_64-linux": "sha256-g3k0cAFGqzmRYlcIkg1NDvlx1WxHYhnYPL0/a8E+qTg=",
+    "aarch64-linux": "sha256-a+3ymqdxOONGe2Tpq4GUccl1b+Dwzxlb9LFXgE1gZ+0=",
+    "aarch64-darwin": "sha256-h8xIzuMmaWfJqjHCO74xUDCWNKQLFrIGoKYZ+2TauYc="
  }
 }
@@ -2,7 +2,7 @@
  "$schema": "https://json.schemastore.org/package.json",
  "name": "opencode",
  "description": "AI-powered development tool",
-  "version": "2.0.23",
+  "version": "2.0.22",
  "private": true,
  "type": "module",
  "packageManager": "bun@1.4.2",
@@ -18,8 +18,7 @@
    "dev:www": "bun run --cwd services/www dev",
    "dev:storybook": "bun --cwd packages/storybook storybook",
    "bench:devex": "bun run --cwd packages/app test:bench:devex",
-    "lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml && bun script/sdk-docs.ts",
-    "lint:changed": "bun script/lint-changed.ts",
+    "lint": "oxlint && ast-grep scan -c script/ast-grep/gui-extensions/sgconfig.yml",
    "lint:effect-patterns": "ast-grep scan -c script/ast-grep/sgconfig.yml packages/util/src packages/core/src packages/server/src packages/protocol/src packages/cli/src",
    "lint:effect-simplifications": "ast-grep scan -c script/ast-grep/effect-simplifications/sgconfig.yml --off=unused-suppression packages",
    "test:lint-rules": "ast-grep test -c script/ast-grep/sgconfig.yml",
@@ -53,9 +52,9 @@
      "@octokit/rest": "22.0.0",
      "@hono/standard-validator": "0.2.0",
      "@hono/zod-validator": "0.4.2",
-      "@opentui/core": "0.5.14",
-      "@opentui/keymap": "0.5.14",
-      "@opentui/solid": "0.5.14",
+      "@opentui/core": "0.0.0-20261002-f9ace790",
+      "@opentui/keymap": "0.0.0-20261002-f9ace790",
+      "@opentui/solid": "0.0.0-20261002-f9ace790",
      "@tanstack/solid-virtual": "3.13.37",
      "@shikijs/stream": "4.4.3",
      "@standard-schema/spec": "1.1.0",
@@ -156,9 +155,9 @@
    "electron"
  ],
  "overrides": {
-    "@opentui/core": "catalog:",
-    "@opentui/keymap": "catalog:",
-    "@opentui/solid": "catalog:",
+    "@opentui/core": "0.0.0-20261002-f9ace790",
+    "@opentui/keymap": "0.0.0-20261002-f9ace790",
+    "@opentui/solid": "0.0.0-20261002-f9ace790",
    "@effect/platform-node-shared": "catalog:",
    "@types/bun": "catalog:",
    "@types/node": "catalog:",
@@ -27,31 +27,6 @@ Run `LLM.stream(...)` instead of `generate` when you want incremental `LLMEvent`
 `LLM.request(...)`. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses,
 Anthropic Messages, Gemini, Bedrock Converse, and any OpenAI-compatible deployment.

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

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

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

 Evaluation models compare shared state with typed choice, score, and boolean questions. The API is
@@ -1283,7 +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": "2.0.23",
+  "version": "2.0.22",
  "name": "@opencode/ai",
  "type": "module",
  "license": "MIT",
@@ -42,7 +42,6 @@ const RESPECTS_INLINE_HINTS = new Set([
  "alibaba-messages",
  "anthropic-messages",
  "anthropic-compatible-messages",
-  "bedrock-mantle-messages",
  "cloudflare-ai-gateway-messages",
  "google-vertex-messages",
  "meta-messages",
@@ -1,7 +1,7 @@
 import { Effect, Schema } from "effect"
 import { Protocol } from "../route/protocol.js"
 import { OpenResponses } from "./open-responses.js"
-import { JsonObject, ProviderShared } from "./shared.js"
+import { JsonObject, optionalArray, ProviderShared } from "./shared.js"
 import { OpenResponsesOptions } from "./utils/open-responses-options.js"
 import { ResponsesHostedTools } from "./utils/responses-hosted-tools.js"

@@ -25,6 +25,8 @@ const WebExtractorItem = Schema.StructWithRest(
 )
 const Body = Schema.Struct({
  ...OpenResponses.coreFields,
+  input: Schema.Array(Schema.Union([OpenResponses.InputItem, WebExtractorItem])),
+  tools: optionalArray(Schema.Union([OpenResponses.Tool, NativeTool])),
  enable_thinking: Options.fields.enableThinking,
  previous_response_id: Options.fields.previousResponseId,
  conversation: Options.fields.conversation,
@@ -50,7 +52,7 @@ export const protocol = Protocol.make({
      const opts = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(req.providerOptions ?? {})
      const body = yield* OpenResponses.fromRequestWithAdapter(req, adapter)
      const choice = body.tool_choice
-      return {
+      return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))({
        ...body,
        enable_thinking: opts.enableThinking,
        previous_response_id: opts.previousResponseId,
@@ -60,7 +62,7 @@ export const protocol = Protocol.make({
          typeof choice === "object" && choice.type === "function"
            ? { type: "allowed_tools" as const, mode: "required" as const, tools: [choice] }
            : choice,
-      }
+      })
    }),
  },
  stream: {
@@ -422,74 +422,57 @@ const AnthropicUsage = Schema.StructWithRest(
 )
 type AnthropicUsage = Schema.Schema.Type<typeof AnthropicUsage>

-const AnthropicStreamBlock = Schema.StructWithRest(
-  Schema.Struct({
-    type: Schema.String,
-    id: Schema.optional(Schema.String),
-    name: Schema.optional(Schema.String),
-    text: Schema.optional(Schema.String),
-    thinking: Schema.optional(Schema.String),
-    signature: Schema.optional(Schema.String),
-    // redacted_thinking blocks arrive whole in content_block_start with the
-    // encrypted payload in `data`; there is no streaming delta sequence.
-    data: Schema.optional(Schema.String),
-    input: Schema.optional(Schema.Unknown),
-    // *_tool_result blocks arrive whole as content_block_start (no streaming
-    // delta) with the structured payload in `content` and the originating
-    // server_tool_use id in `tool_use_id`.
-    tool_use_id: Schema.optional(Schema.String),
-    content: Schema.optional(Schema.Unknown),
-  }),
-  [JsonObject],
-)
+const AnthropicStreamBlock = Schema.Struct({
+  type: Schema.String,
+  id: Schema.optional(Schema.String),
+  name: Schema.optional(Schema.String),
+  text: Schema.optional(Schema.String),
+  thinking: Schema.optional(Schema.String),
+  signature: Schema.optional(Schema.String),
+  // redacted_thinking blocks arrive whole in content_block_start with the
+  // encrypted payload in `data`; there is no streaming delta sequence.
+  data: Schema.optional(Schema.String),
+  input: Schema.optional(Schema.Unknown),
+  // *_tool_result blocks arrive whole as content_block_start (no streaming
+  // delta) with the structured payload in `content` and the originating
+  // server_tool_use id in `tool_use_id`.
+  tool_use_id: Schema.optional(Schema.String),
+  content: Schema.optional(Schema.Unknown),
+})
 type AnthropicStreamBlock = Schema.Schema.Type<typeof AnthropicStreamBlock>
 const decodeAnthropicStreamBlock = Schema.decodeUnknownOption(AnthropicStreamBlock)

-const AnthropicStreamDelta = Schema.StructWithRest(
-  Schema.Struct({
-    content: optionalNull(Schema.String),
-    type: Schema.optional(Schema.String),
-    text: Schema.optional(Schema.String),
-    thinking: Schema.optional(Schema.String),
-    partial_json: Schema.optional(Schema.String),
-    signature: Schema.optional(Schema.String),
-    stop_reason: optionalNull(Schema.String),
-    stop_sequence: optionalNull(Schema.String),
-    stop_details: optionalNull(
-      Schema.StructWithRest(
-        Schema.Struct({ category: optionalNull(Schema.String), explanation: optionalNull(Schema.String) }),
-        [JsonObject],
-      ),
-    ),
-  }),
-  [JsonObject],
-)
+const AnthropicStreamDelta = Schema.Struct({
+  content: optionalNull(Schema.String),
+  type: Schema.optional(Schema.String),
+  text: Schema.optional(Schema.String),
+  thinking: Schema.optional(Schema.String),
+  partial_json: Schema.optional(Schema.String),
+  signature: Schema.optional(Schema.String),
+  stop_reason: optionalNull(Schema.String),
+  stop_sequence: optionalNull(Schema.String),
+  stop_details: optionalNull(
+    Schema.Struct({ category: optionalNull(Schema.String), explanation: optionalNull(Schema.String) }),
+  ),
+})
 type AnthropicStreamDelta = Schema.Schema.Type<typeof AnthropicStreamDelta>
 const decodeAnthropicStreamDelta = Schema.decodeUnknownOption(AnthropicStreamDelta)

-const AnthropicEvent = Schema.StructWithRest(
-  Schema.Struct({
-    type: Schema.String,
-    index: Schema.optional(Schema.Number),
-    message: Schema.optional(
-      Schema.StructWithRest(Schema.Struct({ usage: Schema.optional(AnthropicUsage) }), [JsonObject]),
-    ),
-    content_block: Schema.optional(Schema.Unknown),
-    delta: Schema.optional(Schema.Unknown),
-    usage: Schema.optional(AnthropicUsage),
-    // `type` and `message` are both required per Anthropic's spec, but
-    // OpenAI-compatible proxies and gateway translations occasionally drop one
-    // or the other; mark them optional so a partial payload still parses and
-    // the parser can fall back to whichever field is populated.
-    error: Schema.optional(
-      Schema.StructWithRest(
-        Schema.Struct({ type: Schema.optional(Schema.String), message: Schema.optional(Schema.String) }),
-        [JsonObject],
-      ),
-    ),
-  }),
-  [JsonObject],
-)
+const AnthropicEvent = Schema.Struct({
+  type: Schema.String,
+  index: Schema.optional(Schema.Number),
+  message: Schema.optional(Schema.Struct({ usage: Schema.optional(AnthropicUsage) })),
+  content_block: Schema.optional(Schema.Unknown),
+  delta: Schema.optional(Schema.Unknown),
+  usage: Schema.optional(AnthropicUsage),
+  // `type` and `message` are both required per Anthropic's spec, but
+  // OpenAI-compatible proxies and gateway translations occasionally drop one
+  // or the other; mark them optional so a partial payload still parses and
+  // the parser can fall back to whichever field is populated.
+  error: Schema.optional(
+    Schema.Struct({ type: Schema.optional(Schema.String), message: Schema.optional(Schema.String) }),
+  ),
+})
 type AnthropicEvent = Schema.Schema.Type<typeof AnthropicEvent>

 interface ParserState {
@@ -601,7 +584,10 @@ const serverToolResultType = (name: string): AnthropicServerToolResultType | und
  return undefined
 }

-const lowerServerToolResult = Effect.fnUntraced(function* (part: ToolResultPart, providerMetadataKey: string) {
+const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult")(function* (
+  part: ToolResultPart,
+  providerMetadataKey: string,
+) {
  const wireType = serverToolResultType(part.name)
  if (!wireType)
    return yield* invalid(`Anthropic Messages does not know how to round-trip server tool result for ${part.name}`)
@@ -671,7 +657,10 @@ const citationsFromMetadata = (metadata: MediaPart["metadata"]): AnthropicDocume

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

-const lowerMedia = Effect.fnUntraced(function* (part: MediaPart, breakpoints?: Cache.Breakpoints) {
+const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (
+  part: MediaPart,
+  breakpoints?: Cache.Breakpoints,
+) {
  const mime = part.media.mediaType.toLowerCase()
  const cacheControlValue = breakpoints ? cacheControl(breakpoints, part.cache) : undefined
  const fileId = fileIdFromMetadata(part.metadata)
@@ -815,6 +804,9 @@ const requireThinkingSignature = (request: LLMRequest) => {
  return true
 }

+// Mid-conversation system messages became available with Opus 4.8 and version
+// 5 of the other supported Claude families. Treat later family versions as
+// compatible without assuming that every Anthropic Messages model is Claude.
 // Opus 4.8 and every Claude 5 model accept mid-conversation system messages; later versions inherit support.
 const supportsNativeSystemUpdates = (request: LLMRequest) => {
  const version = claudeVersion(String(request.model.id))
@@ -823,9 +815,25 @@ const supportsNativeSystemUpdates = (request: LLMRequest) => {
  return version.major >= 5
 }

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

 const splitsLocalToolResults = (messages: LLMRequest["messages"], index: number) => {
  const pending = new Set<string>()
@@ -839,7 +847,7 @@ const splitsLocalToolResults = (messages: LLMRequest["messages"], index: number)
  return pending.size > 0
 }

-const lowerNativeSystemUpdate = Effect.fnUntraced(function* (
+const lowerNativeSystemUpdate = Effect.fn("AnthropicMessages.lowerNativeSystemUpdate")(function* (
  message: LLMRequest["messages"][number],
  breakpoints: Cache.Breakpoints,
 ) {
@@ -854,34 +862,12 @@ const lowerNativeSystemUpdate = Effect.fnUntraced(function* (
  }
 })

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

  for (const [index, message] of request.messages.entries()) {
    if (message.role === "system") {
@@ -893,8 +879,16 @@ const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoi
      }
      if (splitsLocalToolResults(request.messages, index))
        return yield* invalid("Anthropic Messages system updates cannot split a local tool call from its tool result")
-      if (holdUpdates) held.push(message)
-      else appendToUserTurn(messages, yield* lowerWrappedSystemUpdate(message, breakpoints))
+      if (supportsNativeSystemUpdates(request) && canUseNativeSystemUpdate(request, index)) {
+        messages.push(yield* lowerNativeSystemUpdate(message, breakpoints))
+        continue
+      }
+      const part = yield* ProviderShared.wrappedSystemUpdate("Anthropic Messages", message)
+      const block = { type: "text" as const, text: part.text, cache_control: cacheControl(breakpoints, part.cache) }
+      const previous = messages.at(-1)
+      if (previous?.role === "user")
+        messages[messages.length - 1] = { role: "user", content: [...previous.content, block] }
+      else messages.push({ role: "user", content: [block] })
      continue
    }

@@ -970,9 +964,7 @@ const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoi
          `Anthropic Messages assistant messages only support text, reasoning, and tool-call content for now`,
        )
      }
-      if (content.length === 0) continue
-      yield* releaseHeld()
-      messages.push({ role: "assistant", content })
+      if (content.length > 0) messages.push({ role: "assistant", content })
      continue
    }

@@ -993,14 +985,10 @@ const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, breakpoi
      messages[messages.length - 1] = { role: "user", content: [...previous.content, ...content] }
    else messages.push({ role: "user", content })
  }
-  yield* releaseHeld()

  return messages
 })

-// TODO: Move per-model capability heuristics (`supportsEffortUpdates`, `supportsNativeSystemUpdates`,
-// `supportsThinkingBlockBinding`) into explicit model/provider `compatibility` metadata so the protocol
-// only reads `request.model.compatibility`.
 // Per-turn effort started with Claude Opus 5 and every Claude 5.1 model; later versions of any family inherit it.
 const supportsEffortUpdates = (model: LLMRequest["model"]) => {
  const override = model.compatibility?.supportsEffortUpdates
@@ -1312,7 +1300,7 @@ const onContentBlockStart = (
  return [{ ...state, lifecycle: Lifecycle.stepStart(state.lifecycle, events) }, [...events, result]]
 }

-const onContentBlockDelta = Effect.fnUntraced(function* (
+const onContentBlockDelta = Effect.fn("AnthropicMessages.onContentBlockDelta")(function* (
  state: ParserState,
  event: AnthropicEvent & { readonly delta: AnthropicStreamDelta },
 ) {
@@ -1380,7 +1368,7 @@ const onContentBlockDelta = Effect.fnUntraced(function* (
  return [state, NO_EVENTS] satisfies StepResult
 })

-const onContentBlockStop = Effect.fnUntraced(function* (
+const onContentBlockStop = Effect.fn("AnthropicMessages.onContentBlockStop")(function* (
  state: ParserState,
  event: AnthropicEvent,
 ) {
@@ -1451,7 +1439,7 @@ const onMessageDelta = (
  ]
 }

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

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

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

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

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

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

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

-const finish = Effect.fnUntraced(function* (
+const finish = Effect.fn("CartesiaSpeech.finish")(function* (
  state: State,
  context: MediaProtocol.ResponseContext<Request>,
 ) {
@@ -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.fnUntraced(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"
@@ -95,7 +95,7 @@ const OUTPUT_FORMATS: Readonly<Record<string, string>> = {
 }

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

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

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

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

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

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

-const step = Effect.fnUntraced(function* (state: State, frame: string) {
+const step = Effect.fn("GoogleTranscription.step")(function* (state: State, frame: string) {
  const chunk = yield* decodeChunk(frame)
  const blocked = GeminiGenerateContent.blocked(route.name, chunk, frame)
  if (blocked !== undefined) return yield* blocked
@@ -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 = {
@@ -95,7 +117,7 @@ const HOSTED_TOOLS = {
  image_generation_call: {
    name: "image_generation",
    input: () => ({}),
-    result: Effect.fnUntraced(function* (raw: ResponsesHostedTools.Item) {
+    result: Effect.fn("MetaResponses.imageResult")(function* (raw: ResponsesHostedTools.Item) {
      const item = yield* Schema.decodeUnknownEffect(ImageItem)(raw).pipe(
        Effect.mapError((cause) =>
          ProviderShared.eventError(
@@ -136,7 +158,7 @@ const HOSTED_TOOLS = {
  },
 } satisfies ResponsesHostedTools.Definitions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

-export const HostedTool = Schema.StructWithRest(
-  Schema.Struct({
-    type: Schema.String,
-  }),
-  [JsonObject],
-)
-export type HostedTool = Schema.Schema.Type<typeof HostedTool>
-
 export const ToolChoice = Schema.Union([
  Schema.Literals(["auto", "none", "required"]),
  Schema.Struct({ type: Schema.tag("function"), name: Schema.String }),
@@ -260,7 +257,7 @@ export const coreFields = {
  model: Schema.String,
  input: Schema.Array(InputItem),
  instructions: Schema.optional(Schema.String),
-  tools: optionalArray(Schema.Union([Tool, HostedTool])),
+  tools: optionalArray(Tool),
  tool_choice: Schema.optional(ToolChoice),
  store: Schema.optional(Schema.Boolean),
  metadata: Schema.optional(Schema.Record(Schema.String, Schema.String)),
@@ -295,32 +292,24 @@ export const coreFields = {
  frequency_penalty: Schema.optional(Schema.Number),
 }

-export const OpenResponsesBody = Schema.Struct({
+const OpenResponsesBody = Schema.Struct({
  ...coreFields,
  stream: Schema.Literal(true),
 })
 export type OpenResponsesBody = Schema.Schema.Type<typeof OpenResponsesBody>

-export const OpenResponsesUsage = Schema.StructWithRest(
-  Schema.Struct({
-    input_tokens: Schema.optional(Schema.Number),
-    input_tokens_details: optionalNull(
-      Schema.StructWithRest(
-        Schema.Struct({
-          cached_tokens: Schema.optional(Schema.Number),
-          cache_write_tokens: Schema.optional(Schema.Number),
-        }),
-        [JsonObject],
-      ),
-    ),
-    output_tokens: Schema.optional(Schema.Number),
-    output_tokens_details: optionalNull(
-      Schema.StructWithRest(Schema.Struct({ reasoning_tokens: Schema.optional(Schema.Number) }), [JsonObject]),
-    ),
-    total_tokens: Schema.optional(Schema.Number),
-  }),
-  [JsonObject],
-)
+export const OpenResponsesUsage = Schema.Struct({
+  input_tokens: Schema.optional(Schema.Number),
+  input_tokens_details: optionalNull(
+    Schema.Struct({
+      cached_tokens: Schema.optional(Schema.Number),
+      cache_write_tokens: Schema.optional(Schema.Number),
+    }),
+  ),
+  output_tokens: Schema.optional(Schema.Number),
+  output_tokens_details: optionalNull(Schema.Struct({ reasoning_tokens: Schema.optional(Schema.Number) })),
+  total_tokens: Schema.optional(Schema.Number),
+})
 type OpenResponsesUsage = Schema.Schema.Type<typeof OpenResponsesUsage>

 // The spec requires `id` on every output item, but some gateways drop it from
@@ -408,7 +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
@@ -450,7 +441,7 @@ interface ReasoningStreamItem {
 // =============================================================================
 // Request Lowering
 // =============================================================================
-export const lowerTool = Effect.fnUntraced(function* (protocolName: string, tool: ToolDefinition) {
+export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (protocolName: string, tool: ToolDefinition) {
  if (tool.native !== undefined)
    return yield* ProviderShared.invalidRequest(`${protocolName} does not support provider-native tool ${tool.name}`)
  return {
@@ -464,10 +455,8 @@ export const lowerTool = Effect.fnUntraced(function* (protocolName: string, tool
 })

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

 export const lowerToolChoice = (protocolName: string, toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -515,10 +504,7 @@ const lowerReasoning = (part: ReasoningPart, providerMetadataKey: string): OpenR
  }
 }

-const decodeImageDetail = ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesInputImage.fields.detail))
-const decodeMessageMetadata = ProviderShared.validateWith(Schema.decodeUnknownEffect(MessageMetadata))
-
-const lowerMedia = Effect.fnUntraced(function* (
+const lowerMedia = Effect.fn("OpenResponses.lowerMedia")(function* (
  part: MediaPart,
  request: LLMRequest,
  adapter: ProviderAdapter,
@@ -527,8 +513,9 @@ const lowerMedia = Effect.fnUntraced(function* (
  const media = part.media.inline()
  const providerMedia = adapter.lowerMedia?.({ part, media, request })
  if (providerMedia) return providerMedia
-  const rawDetail = part.providerMetadata?.[metadataKey(request.model)]?.detail
-  const detail = rawDetail === undefined ? undefined : yield* decodeImageDetail(rawDetail)
+  const detail = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(OpenResponsesInputImage.fields.detail))(
+    part.providerMetadata?.[metadataKey(request.model)]?.detail,
+  )
  const mime = part.media.mediaType.toLowerCase()
  const url = ProviderShared.mediaUrl(part.media)
  const location = url ?? (yield* ProviderShared.requireInlineMedia(adapter.name, part.media)).dataUrl
@@ -601,16 +588,17 @@ const lowerToolResultOutput = Effect.fnUntraced(function* (

 const DEFAULT_EFFORT = "medium"

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

  for (const message of request.messages) {
-    const rawMetadata = message.providerMetadata?.[providerMetadataKey]
-    const metadata = rawMetadata === undefined ? undefined : yield* decodeMessageMetadata(rawMetadata)
+    const metadata = yield* ProviderShared.validateWith(
+      Schema.decodeUnknownEffect(Schema.UndefinedOr(MessageMetadata)),
+    )(message.providerMetadata?.[providerMetadataKey])
    if (message.role === "system") {
      const update = effortUpdate(message)
      if (update) {
@@ -764,7 +752,7 @@ const lowerMessages = Effect.fnUntraced(function* (
  return input
 })

-export const lowerConversation = Effect.fnUntraced(function* (
+export const lowerConversation = Effect.fn("OpenResponses.lowerConversation")(function* (
  request: LLMRequest,
  adapter: ProviderAdapter,
 ) {
@@ -839,7 +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
@@ -1151,7 +1143,7 @@ const onReasoningSummaryPartDone = (state: ParserState, event: Event): StepResul
  ]
 }

-const onFunctionCallArgumentsDelta = Effect.fnUntraced(function* (
+const onFunctionCallArgumentsDelta = Effect.fn("OpenResponses.onFunctionCallArgumentsDelta")(function* (
  state: ParserState,
  event: Event,
 ) {
@@ -1182,7 +1174,7 @@ const onFunctionCallArgumentsDelta = Effect.fnUntraced(function* (
  return [{ ...state, lifecycle, tools: result.tools }, events] satisfies StepResult
 })

-const onOutputItemDone = Effect.fnUntraced(function* (
+const onOutputItemDone = Effect.fn("OpenResponses.onOutputItemDone")(function* (
  state: ParserState,
  item: NormalizedEvent["item"],
 ) {
@@ -1318,7 +1310,7 @@ const onOutputItemDone = Effect.fnUntraced(function* (
  return [state, NO_EVENTS] satisfies StepResult
 })

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

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

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

-export const OpenAIChatMessage = Schema.Union([
+const OpenAIChatMessage = Schema.Union([
  Schema.Struct({
    role: Schema.Literal("system"),
    content: Schema.Union([Schema.String, Schema.Array(OpenAIChatUserContent)]),
@@ -200,7 +207,7 @@ export type OpenAIChatBody = Schema.Schema.Type<typeof OpenAIChatBody>
 // The event schema is one decoded SSE `data:` payload. `Framing.sse` splits the
 // byte stream into strings, then `Protocol.jsonEvent` decodes each string into
 // this provider-native event shape.
-export const OpenAIChatUsage = Schema.StructWithRest(
+const OpenAIChatUsage = Schema.StructWithRest(
  Schema.Struct({
    prompt_tokens: optionalNull(Schema.Number),
    completion_tokens: optionalNull(Schema.Number),
@@ -238,7 +245,7 @@ const OpenAIChatToolCallDeltaFunction = Schema.Struct({
  arguments: optionalNull(Schema.String),
 })

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

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

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

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

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

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

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

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

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

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

-const lowerMessages = Effect.fnUntraced(function* (request: LLMRequest, options: LoweringOptions) {
+const lowerMessages = Effect.fn("OpenAIChat.lowerMessages")(function* (request: LLMRequest, options: LoweringOptions) {
  const system: OpenAIChatMessage[] =
    request.system.length === 0
      ? []
@@ -859,7 +862,7 @@ export const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (
 // Streaming parsers are small state machines: every event returns a new state
 // plus the common `LLMEvent`s produced by that event. Tool calls are accumulated
 // because OpenAI streams JSON arguments across multiple deltas.
-const mapFinishReason = Effect.fnUntraced(function* (event: OpenAIChatEvent, reason: string) {
+const mapFinishReason = Effect.fn("OpenAIChat.mapFinishReason")(function* (event: OpenAIChatEvent, reason: string) {
  switch (reason) {
    case "error":
      return yield* new AIError({
@@ -1218,7 +1221,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
    ] as const
  })

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 const HOSTED_TOOLS = {
@@ -76,7 +83,7 @@ const step = (state: OpenResponses.ParserState, input: OpenResponses.Event) => {
 export const protocol = Protocol.make({
  id: ADAPTER,
  body: {
-    schema: OpenResponses.OpenResponsesBody,
+    schema: XAIResponsesBody,
    from: fromRequest,
  },
  stream: {
@@ -55,13 +55,7 @@ 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)) &&
@@ -1,20 +1,15 @@
 import { Route, type RouteDefaultsInput } from "../route/client.js"
 import { Endpoint } from "../route/endpoint.js"
 import type { ProviderPackage } from "../provider-package.js"
-import { AnthropicMessages } from "../protocols/anthropic-messages.js"
 import { OpenAIChat } from "../protocols/openai-chat.js"
 import { OpenResponses } from "../protocols/open-responses.js"
 import { BedrockAuth, type Credentials } from "../protocols/utils/bedrock-auth.js"
-import { claudeVersion } from "../protocols/utils/claude-model.js"
 import { ProviderConfigurationError, ProviderID, type ModelID } from "../schema/index.js"
 import { withOpenAIOptions, type OpenAIProviderOptionsInput } from "./openai-options.js"

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

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

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

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

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

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

  return {
    id,
    model: responses,
    chat,
-    messages,
    responses,
    configure,
  }
@@ -157,7 +119,7 @@ const fromSettings = ({
  region,
  topP,
  ...providerOptions
-}: Settings<Config["providerOptions"]>) =>
+}: Settings) =>
  configure({
    apiKey,
    auth,
@@ -175,10 +137,6 @@ export const chatModel: ProviderPackage.Definition<Settings, OpenAIProviderOptio
  modelID,
  settings,
 ) => fromSettings(settings).chat(modelID)
-export const messagesModel: ProviderPackage.Definition<
-  MessagesSettings,
-  AnthropicMessages.ProviderOptionsInput
->["model"] = (modelID, settings) => fromSettings(settings).messages(modelID)
 export const responsesModel: ProviderPackage.Definition<Settings, OpenAIProviderOptionsInput>["model"] = (
  modelID,
  settings,
@@ -1,2 +0,0 @@
-export { messagesModel as model } from "../../amazon-bedrock-mantle.js"
-export type { MessagesSettings as Settings } from "../../amazon-bedrock-mantle.js"
@@ -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)
@@ -54,7 +54,6 @@ const route = Route.make({
        ),
    },
    stream: AnthropicMessages.protocol.stream,
-    supportsEffortUpdates: AnthropicMessages.protocol.supportsEffortUpdates,
  }),
  endpoint: Endpoint.path(({ request }) => `/${request.model.id}:streamRawPredict`),
  auth: Auth.none,
@@ -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)
@@ -9,7 +9,6 @@ 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"
@@ -40,7 +39,6 @@ export * as Stability from "./stability.js"
 export * as TogetherAI from "./togetherai.js"
 export * as TypeSafeAI from "./typesafe-ai.js"
 export * as VercelAIGateway from "./vercel-ai-gateway.js"
-export * as Venice from "./venice.js"
 export * as XAI from "./xai.js"
 export * as ZAI from "./zai.js"
 export * as ZAICodingPlan from "./zai-coding-plan.js"
@@ -50,7 +50,7 @@ export const gpt5DefaultOptions = (modelID: string): ProviderOptions | undefined
 export const openAIDefaultOptions = (modelID: string): ProviderOptions | undefined =>
  mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID))

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

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

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

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

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

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

-  it.effect("releases a held system update next to an effort marker as one valid section", () =>
-    Effect.gen(function* () {
-      const prepared = yield* compileRequest(
-        LLM.request({
-          model: opus5,
-          messages: [
-            Message.user("Fix it."),
-            Message.assistant("Done."),
-            lowFromHigh,
-            Message.system("Update."),
-            Message.user("Next."),
-          ],
-          providerOptions: { effort: "low" },
-          cache: "none",
-        }),
-      )
-
-      expect(prepared.body.messages).toEqual([
-        { role: "user", content: [{ type: "text", text: "Fix it." }] },
-        { role: "assistant", content: [{ type: "text", text: "Done." }] },
-        { role: "system", content: [], output_config: { effort: "low" } },
-        { role: "user", content: [{ type: "text", text: "Next." }] },
-        { role: "system", content: [{ type: "text", text: "Update.", cache_control: undefined }] },
-      ])
-    }),
-  )
-
  it.effect("falls back to a plain top-level effort when history drifted from the current effort", () =>
    Effect.gen(function* () {
      const drifted = yield* compileRequest(
@@ -268,53 +242,20 @@ describe("Anthropic Messages effort updates", () => {
    }),
  )

-  it.effect("strips markers for Opus 5.0 on Bedrock Mantle Messages while lowering Opus 5.5", () =>
+  it.effect("strips markers on the Vertex Anthropic route, whose protocol wrapper does not forward support", () =>
    Effect.gen(function* () {
-      const mantle = AmazonBedrockMantle.configure({ apiKey: "test", region: "us-east-1" })
-      const opus50 = yield* compileRequest(
+      const prepared = yield* compileRequest(
        LLM.request({
-          model: mantle.messages("anthropic.claude-opus-5"),
-          messages: conversation,
-          providerOptions: { effort: "low" },
-        }),
-      )
-      const opus55 = yield* compileRequest(
-        LLM.request({
-          model: mantle.messages("anthropic.claude-opus-5-5"),
+          model: GoogleVertexMessages.configure({ accessToken: "test", location: "global", project: "test" }).model(
+            "claude-opus-5",
+          ),
          messages: conversation,
          providerOptions: { effort: "low" },
        }),
      )

-      expect(systemMessages(opus50.body)).toHaveLength(0)
-      expect(opus50.body.output_config).toEqual({ effort: "low" })
-      expect(systemMessages(opus55.body)).toEqual([{ role: "system", content: [], output_config: { effort: "low" } }])
-      expect(opus55.body.output_config).toEqual({ effort: "high" })
-    }),
-  )
-
-  it.effect("lowers markers on the Vertex Anthropic route for models that support them", () =>
-    Effect.gen(function* () {
-      const vertex = GoogleVertexMessages.configure({ accessToken: "test", location: "global", project: "test" })
-      const opus5 = yield* compileRequest(
-        LLM.request({
-          model: vertex.model("claude-opus-5"),
-          messages: conversation,
-          providerOptions: { effort: "low" },
-        }),
-      )
-      const opus48 = yield* compileRequest(
-        LLM.request({
-          model: vertex.model("claude-opus-4-8"),
-          messages: conversation,
-          providerOptions: { effort: "low" },
-        }),
-      )
-
-      expect(systemMessages(opus5.body)).toEqual([{ role: "system", content: [], output_config: { effort: "low" } }])
-      expect(opus5.body.output_config).toEqual({ effort: "high" })
-      expect(systemMessages(opus48.body)).toHaveLength(0)
-      expect(opus48.body.output_config).toEqual({ effort: "low" })
+      expect(systemMessages(prepared.body)).toHaveLength(0)
+      expect(prepared.body.output_config).toEqual({ effort: "low" })
    }),
  )
 })
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/accepts-malformed-assistant-tool-order-with-default-patch",
+    "recordedAt": "2026-05-05T20:09:16.245Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\",\"cache_control\":{\"type\":\"ephemeral\"}}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01SikJVFaMR1XLMtavUhvuog\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":638,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":1,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}               }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}          }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"The\"}     }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\" weather in Paris is currently 72°F.\"}        }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0}\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":638,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":14}              }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"             }\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,56 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/claude-opus-4-7-drives-a-tool-loop",
+    "recordedAt": "2026-05-03T19:59:44.186Z",
+    "tags": [
+      "prefix:anthropic-messages",
+      "provider:anthropic",
+      "protocol:anthropic-messages",
+      "tool",
+      "tool-loop",
+      "golden",
+      "flagship"
+    ]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-opus-4-7\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool, then answer in one short sentence.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-opus-4-7\",\"id\":\"msg_01DgAEgLgB1ZhavZon4qGE1t\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":798,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":0,\"service_tier\":\"standard\",\"inference_geo\":\"global\"}}    }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}}              }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"} }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\": \"}              }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\\\"Pa\"}    }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"ris\\\"}\"}  }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0           }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":798,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":66}             }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"            }\n\n"
+      }
+    },
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-opus-4-7\",\"system\":[{\"type\":\"text\",\"text\":\"Use the get_weather tool, then answer in one short sentence.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"toolu_01M8nJQQMxqpv1VaPYuJKT4j\",\"content\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"stream\":true,\"max_tokens\":80}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-opus-4-7\",\"id\":\"msg_011KJqj32QjkrUAiBFxhmEoG\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":895,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":5,\"service_tier\":\"standard\",\"inference_geo\":\"global\"}}       }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}            }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Paris is curr\"}   }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"ently sunny at 22°C.\"}           }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0        }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":895,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":19}}\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"}\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/rejects-malformed-assistant-tool-order-without-patch",
+    "recordedAt": "2026-05-05T20:08:42.597Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool", "sad-path"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"messages\":[{\"role\":\"assistant\",\"content\":[{\"type\":\"tool_use\",\"id\":\"call_1\",\"name\":\"get_weather\",\"input\":{\"city\":\"Paris\"}},{\"type\":\"text\",\"text\":\"I will check the weather.\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"tool_result\",\"tool_use_id\":\"call_1\",\"content\":\"{\\\"temperature\\\":\\\"72F\\\"}\"}]},{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Use that result to answer briefly.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get weather\",\"input_schema\":{\"type\":\"object\",\"properties\":{}}}],\"stream\":true,\"max_tokens\":4096}"
+      },
+      "response": {
+        "status": 400,
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"type\":\"error\",\"error\":{\"type\":\"invalid_request_error\",\"message\":\"messages.1: `tool_use` ids were found without `tool_result` blocks immediately after: call_1. Each `tool_use` block must have a corresponding `tool_result` block in the next message.\"},\"request_id\":\"req_011Cak2XdJgnzxKCY2BC2Beh\"}"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/streams-text",
+    "recordedAt": "2026-04-28T21:18:45.535Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"You are concise.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply with exactly: Hello!\"}]}],\"stream\":true,\"max_tokens\":20,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01UodR8c3ezAK8rAfi8HAs8g\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":18,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":2,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}          }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"text\",\"text\":\"\"}    }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"text_delta\",\"text\":\"Hello!\"}    }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0   }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":18,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":5}             }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"         }\n\n"
+      }
+    }
+  ]
+}
@@ -0,0 +1,29 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "anthropic-messages/streams-tool-call",
+    "recordedAt": "2026-04-28T21:18:46.878Z",
+    "tags": ["prefix:anthropic-messages", "provider:anthropic", "protocol:anthropic-messages", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.anthropic.com/v1/messages",
+        "headers": {
+          "anthropic-version": "2023-06-01",
+          "content-type": "application/json"
+        },
+        "body": "{\"model\":\"claude-haiku-4-5-20251001\",\"system\":[{\"type\":\"text\",\"text\":\"Call tools exactly as requested.\"}],\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Call get_weather with city exactly Paris.\"}]}],\"tools\":[{\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"input_schema\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false}}],\"tool_choice\":{\"type\":\"tool\",\"name\":\"get_weather\"},\"stream\":true,\"max_tokens\":80,\"temperature\":0}"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "text/event-stream; charset=utf-8"
+        },
+        "body": "event: message_start\ndata: {\"type\":\"message_start\",\"message\":{\"model\":\"claude-haiku-4-5-20251001\",\"id\":\"msg_01RYgU7NUPMK4B9v8S7gVpCS\",\"type\":\"message\",\"role\":\"assistant\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"stop_details\":null,\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"cache_creation\":{\"ephemeral_5m_input_tokens\":0,\"ephemeral_1h_input_tokens\":0},\"output_tokens\":16,\"service_tier\":\"standard\",\"inference_geo\":\"not_available\"}}             }\n\nevent: content_block_start\ndata: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"tool_use\",\"id\":\"toolu_012rmAruviySvUXSjgCPWVRu\",\"name\":\"get_weather\",\"input\":{},\"caller\":{\"type\":\"direct\"}}      }\n\nevent: ping\ndata: {\"type\": \"ping\"}\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"\"}             }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\"{\\\"city\\\":\"}    }\n\nevent: content_block_delta\ndata: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"input_json_delta\",\"partial_json\":\" \\\"Paris\\\"}\"}     }\n\nevent: content_block_stop\ndata: {\"type\":\"content_block_stop\",\"index\":0     }\n\nevent: message_delta\ndata: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"tool_use\",\"stop_sequence\":null,\"stop_details\":null},\"usage\":{\"input_tokens\":677,\"cache_creation_input_tokens\":0,\"cache_read_input_tokens\":0,\"output_tokens\":33}              }\n\nevent: message_stop\ndata: {\"type\":\"message_stop\"     }\n\n"
+      }
+    }
+  ]
+}
@@ -1,57 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "anthropic.claude-opus-5-5",
-    "tags": [
-      "prefix:bedrock-mantle-messages",
-      "provider:amazon-bedrock",
-      "protocol:anthropic-messages",
-      "reasoning",
-      "effort-update"
-    ],
-    "name": "bedrock-mantle-messages/applies-mid-conversation-effort-updates-and-thinking-block-binding-on-opus-5-5",
-    "recordedAt": "2026-10-04T03:56:23.139Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://bedrock-mantle.us-east-1.api.aws/anthropic/v1/messages",
-        "headers": {
-          "anthropic-beta": "interleaved-thinking-2025-05-14,thinking-binding-controls-2026-08-01",
-          "anthropic-version": "2023-06-01",
-          "content-type": "application/json"
-        },
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-{
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@@ -1,31 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:cohere",
-      "provider:cohere"
-    ],
-    "name": "cohere/streams-compatible-chat-reasoning",
-    "recordedAt": "2026-10-02T02:39:47.406Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.cohere.ai/compatibility/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"command-a-reasoning-08-2025\",\"messages\":[{\"role\":\"user\",\"content\":\"What is 17 times 23? Answer briefly.\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"reasoning_effort\":\"high\",\"max_tokens\":2048}"
-      },
-      "response": {
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-      }
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-}
@@ -1,31 +0,0 @@
-{
-  "version": 1,
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-      "provider:cohere"
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-    "name": "cohere/streams-native-text-and-usage",
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-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.cohere.com/v2/chat",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"command-a-03-2025\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"Reply exactly: OK\"}]}],\"stream\":true,\"max_tokens\":64}"
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-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: message-start\ndata: {\"id\":\"a171b3a5-db11-4445-a645-5221fb466ab8\",\"type\":\"message-start\",\"delta\":{\"message\":{\"role\":\"assistant\",\"content\":[],\"tool_plan\":\"\",\"tool_calls\":[],\"citations\":[]}}}\n\nevent: content-start\ndata: {\"type\":\"content-start\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"type\":\"text\",\"text\":\"\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"text\":\"OK\"}}}}\n\nevent: content-end\ndata: {\"type\":\"content-end\",\"index\":0}\n\nevent: message-end\ndata: {\"type\":\"message-end\",\"delta\":{\"finish_reason\":\"COMPLETE\",\"usage\":{\"billed_units\":{\"input_tokens\":4,\"output_tokens\":1},\"tokens\":{\"input_tokens\":499,\"output_tokens\":4},\"cached_tokens\":464}}}\n\ndata: [DONE]\n\n"
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-  ]
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@@ -1,31 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
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-      "prefix:cohere",
-      "provider:cohere"
-    ],
-    "name": "cohere/streams-native-thinking-with-a-budget",
-    "recordedAt": "2026-10-02T02:36:14.669Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
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-        "url": "https://api.cohere.com/v2/chat",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"command-a-reasoning-08-2025\",\"messages\":[{\"role\":\"user\",\"content\":[{\"type\":\"text\",\"text\":\"What is 17 times 23? Answer briefly.\"}]}],\"stream\":true,\"thinking\":{\"type\":\"enabled\",\"token_budget\":128},\"max_tokens\":2048}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream"
-        },
-        "body": "event: message-start\ndata: {\"id\":\"305edbbe-9f86-4bc0-9490-7766b168a453\",\"type\":\"message-start\",\"delta\":{\"message\":{\"role\":\"assistant\",\"content\":[],\"tool_plan\":\"\",\"tool_calls\":[],\"citations\":[]}}}\n\nevent: content-start\ndata: {\"type\":\"content-start\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"type\":\"thinking\",\"thinking\":\"\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\"Okay\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\",\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\" let\"}}}}\n\nevent: content-delta\ndata: {\"type\":\"content-delta\",\"index\":0,\"delta\":{\"message\":{\"content\":{\"thinking\":\"'s\"}}}}\n\nevent: content-delta\ndata: 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-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
-    ],
-    "name": "google-interactions/continues-tool-results-with-previous-interaction-id",
-    "recordedAt": "2026-10-03T18:10:17.900Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://generativelanguage.googleapis.com/v1beta/interactions",
-        "headers": {
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-      },
-      "response": {
-        "status": 200,
-        "headers": {
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-{
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-  "metadata": {
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-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
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-      "response": {
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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\":\"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"
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@@ -1,32 +0,0 @@
-{
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-  "metadata": {
-    "tags": [
-      "prefix:google-interactions",
-      "provider:google",
-      "protocol:google-interactions"
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-    "name": "google-interactions/streams-reasoning-and-retains-thought-signatures",
-    "recordedAt": "2026-10-03T18:08:37.674Z"
-  },
-  "interactions": [
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-      "transport": "http",
-      "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\":\"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 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": {
          "content-type": "text/event-stream; charset=utf-8"
        },
-        "body": "data: {\"id\":\"81417fdbfbeb4714ae737aab701cbee4\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"81417fdbfbeb4714ae737aab701cbee4\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"tool_calls\":[{\"id\":\"EwgHkPRLW\",\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\",\"arguments\":\"{\\\"city\\\": \\\"Paris\\\"}\"},\"index\":0}]},\"finish_reason\":\"tool_calls\"}],\"usage\":{\"prompt_tokens\":120,\"total_tokens\":132,\"completion_tokens\":12,\"prompt_tokens_details\":{\"cached_tokens\":0},\"service_tier\":\"standard\"},\"p\":\"abcdefghij\"}\n\ndata: [DONE]\n\n"
+        "body": "data: {\"id\":\"07491e37a5ed48f9987f1583753a466b\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"07491e37a5ed48f9987f1583753a466b\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"tool_calls\":[{\"id\":\"ffJovBNqY\",\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\",\"arguments\":\"{\\\"city\\\": \\\"Paris\\\"}\"},\"index\":0}]},\"finish_reason\":\"tool_calls\"}],\"usage\":{\"prompt_tokens\":110,\"total_tokens\":122,\"completion_tokens\":12,\"prompt_tokens_details\":{\"cached_tokens\":0},\"service_tier\":\"standard\"},\"p\":\"abcdefghijklm\"}\n\ndata: [DONE]\n\n"
      }
    },
    {
@@ -40,14 +33,14 @@
        "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?\"},{\"role\":\"assistant\",\"content\":\"\",\"tool_calls\":[{\"id\":\"EwgHkPRLW\",\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"}}]},{\"role\":\"tool\",\"tool_call_id\":\"EwgHkPRLW\",\"name\":\"lookup_weather\",\"content\":\"{\\\"condition\\\":\\\"sunny\\\",\\\"temperature\\\":\\\"18C\\\"}\"}],\"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\":\"none\",\"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?\"},{\"role\":\"assistant\",\"content\":\"\",\"tool_calls\":[{\"id\":\"ffJovBNqY\",\"type\":\"function\",\"function\":{\"name\":\"lookup_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"}}]},{\"role\":\"tool\",\"tool_call_id\":\"ffJovBNqY\",\"name\":\"lookup_weather\",\"content\":\"{\\\"condition\\\":\\\"sunny\\\",\\\"temperature\\\":\\\"18C\\\"}\"}],\"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\":\"none\",\"stream\":true,\"max_tokens\":160,\"temperature\":0,\"reasoning_effort\":\"none\"}"
      },
      "response": {
        "status": 200,
        "headers": {
          "content-type": "text/event-stream; charset=utf-8"
        },
-        "body": "data: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"The\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmnopqrstuvwxyz01234\"}\n\ndata: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" weather in Paris is\"},\"finish_reason\":null}],\"p\":\"abcdefghijkl\"}\n\ndata: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" currently sunny with a\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmn\"}\n\ndata: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" temperature of 1\"},\"finish_reason\":null}],\"p\":\"abcdefghi\"}\n\ndata: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"8°C\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmnopqrstuvwx\"}\n\ndata: {\"id\":\"a46eb8ccd1b947ca9d360c3446b295a5\",\"object\":\"chat.completion.chunk\",\"created\":1791000589,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\".\"},\"finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":67,\"total_tokens\":84,\"completion_tokens\":17,\"prompt_tokens_details\":{\"cached_tokens\":0},\"service_tier\":\"standard\"},\"p\":\"abcdefghijklmnopqrs\"}\n\ndata: [DONE]\n\n"
+        "body": "data: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"The\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmn\"}\n\ndata: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" weather in Paris is\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmn\"}\n\ndata: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" currently sunny with\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmnopqrstu\"}\n\ndata: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" a temperature of \"},\"finish_reason\":null}],\"p\":\"abcdef\"}\n\ndata: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"18°C\"},\"finish_reason\":null}],\"p\":\"abcdefghijklmnopqr\"}\n\ndata: {\"id\":\"8fcd293093b849139fc0893a48bbc7ce\",\"object\":\"chat.completion.chunk\",\"created\":1788110328,\"model\":\"mistral-small-latest\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\".\"},\"finish_reason\":\"stop\"}],\"usage\":{\"prompt_tokens\":57,\"total_tokens\":74,\"completion_tokens\":17,\"prompt_tokens_details\":{\"cached_tokens\":0},\"service_tier\":\"standard\"},\"p\":\"abcdefghijklmnopqrstuvwxyz\"}\n\ndata: [DONE]\n\n"
      }
    }
  ]
@@ -0,0 +1,28 @@
+{
+  "version": 1,
+  "metadata": {
+    "name": "openai-chat/continues-after-tool-result",
+    "recordedAt": "2026-05-06T01:33:31.878Z",
+    "tags": ["prefix:openai-chat", "provider:openai", "protocol:openai-chat", "tool"]
+  },
+  "interactions": [
+    {
+      "transport": "http",
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+      }
+    }
+  ]
+}
@@ -1,75 +0,0 @@
-{
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-      }
-    }
-  ]
-}
@@ -1,75 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "deepseek-v4-flash",
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "reasoning",
-      "tool",
-      "tool-loop",
-      "continuation",
-      "usage",
-      "scalar"
-    ],
-    "name": "venice-chat/deepseek-v4-flash-preserves-reasoning-through-a-tool-loop-and-follow-up",
-    "recordedAt": "2026-10-05T02:59:53.799Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"deepseek-v4-flash\",\"messages\":[{\"role\":\"system\",\"content\":\"Use the provided tool for private data. After receiving the result, give only the requested number; do not call the tool again.\"},{\"role\":\"user\",\"content\":\"Look up conversion rate for code ZEBRA. Then multiply that rate by 17 and add 9. You must use lookup_rate before answering.\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"description\":\"Retrieve the private conversion rate for a code. Only this tool knows the rate.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"string\",\"enum\":[\"ZEBRA\",\"MOOSE\"]}},\"required\":[\"code\"],\"additionalProperties\":false},\"strict\":false}}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
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-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"deepseek-v4-flash\",\"messages\":[{\"role\":\"system\",\"content\":\"Use the provided tool for private data. After receiving the result, give only the requested number; do not call the tool again.\"},{\"role\":\"user\",\"content\":\"Look up conversion rate for code ZEBRA. Then multiply that rate by 17 and add 9. You must use lookup_rate before answering.\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"chatcmpl-tool-ab656a8b683341f2\",\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"arguments\":\"{\\\"code\\\":\\\"ZEBRA\\\"}\"}}],\"reasoning_content\":\"The user wants me to look up the conversion rate for code ZEBRA, then multiply by 17 and add 9. Let me start by looking up the rate.\"},{\"role\":\"tool\",\"tool_call_id\":\"chatcmpl-tool-ab656a8b683341f2\",\"content\":\"{\\\"code\\\":\\\"ZEBRA\\\",\\\"rate\\\":23}\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"description\":\"Retrieve the private conversion rate for a code. Only this tool knows the rate.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"string\",\"enum\":[\"ZEBRA\",\"MOOSE\"]}},\"required\":[\"code\"],\"additionalProperties\":false},\"strict\":false}}],\"tool_choice\":\"none\",\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"service_tier\":null,\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"We have the\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" rate: 2\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"3. Mul\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"tiply by\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" 17: 2\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"3 * 17\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" = 391.\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" Then ad\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"d 9:\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" 391 + 9 = 400.\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"400\",\"reasoning_content\":\" So the answer is 400.\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":\"stop\"}]}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RtwpMZBraGwqJiKRKQFrmmIq\",\"object\":\"chat.completion.chunk\",\"created\":1791169191,\"model\":\"deepseek-v4-flash\",\"choices\":[],\"usage\":{\"prompt_tokens\":128,\"completion_tokens\":46,\"total_tokens\":174,\"prompt_tokens_details\":{\"cached_tokens\":0}}Line truncated
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"deepseek-v4-flash\",\"messages\":[{\"role\":\"system\",\"content\":\"Use the provided tool for private data. After receiving the result, give only the requested number; do not call the tool again.\"},{\"role\":\"user\",\"content\":\"Look up conversion rate for code ZEBRA. Then multiply that rate by 17 and add 9. You must use lookup_rate before answering.\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"chatcmpl-tool-ab656a8b683341f2\",\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"arguments\":\"{\\\"code\\\":\\\"ZEBRA\\\"}\"}}],\"reasoning_content\":\"The user wants me to look up the conversion rate for code ZEBRA, then multiply by 17 and add 9. Let me start by looking up the rate.\"},{\"role\":\"tool\",\"tool_call_id\":\"chatcmpl-tool-ab656a8b683341f2\",\"content\":\"{\\\"code\\\":\\\"ZEBRA\\\",\\\"rate\\\":23}\"},{\"role\":\"assistant\",\"content\":\"400\",\"reasoning_content\":\"We have the rate: 23. Multiply by 17: 23 * 17 = 391. Then add 9: 391 + 9 = 400. So the answer is 400.\"},{\"role\":\"user\",\"content\":\"Add 7 to your previous final answer. Reply with just the number.\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"description\":\"Retrieve the private conversion rate for a code. Only this tool knows the rate.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"string\",\"enum\":[\"ZEBRA\",\"MOOSE\"]}},\"required\":[\"code\"],\"additionalProperties\":false},\"strict\":false}}],\"tool_choice\":\"none\",\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"service_tier\":null,\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"We need to add\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" 7 to t\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"h\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"e previous ans\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"wer,\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" which\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\" was 400. S\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":\"o 400+7=407. Reply wi\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"407\",\"reasoning_content\":\"th just the number.\",\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":\"stop\"}]}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-R0MMWxoRA5NidBHTttxrMoVe\",\"object\":\"chat.completion.chunk\",\"created\":1791169192,\"model\":\"deepseek-v4-flash\",\"choices\":[],\"usage\":{\"prompt_tokens\":148,\"completion_tokens\":33,\"total_tokens\":181,\"prompt_tokens_details\":{\"cached_tokens\":0}},\"cost\":{\"usd\":0.000029499,\"diem\":0}}\n\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -1,75 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "gemini-3-1-pro-preview",
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "reasoning",
-      "tool",
-      "tool-loop",
-      "continuation",
-      "usage",
-      "details"
-    ],
-    "name": "venice-chat/gemini-3-1-pro-preview-preserves-reasoning-through-a-tool-loop-and-follow-up",
-    "recordedAt": "2026-10-05T03:00:58.104Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
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-    }
-  ]
-}
@@ -1,71 +0,0 @@
-{
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-      "provider:venice",
-      "protocol:venice-chat",
-      "tool",
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-      "signature"
-    ],
-    "name": "venice-chat/gemini-preserves-per-call-signatures-through-parallel-tools",
-    "recordedAt": "2026-10-05T03:21:54.383Z"
-  },
-  "interactions": [
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-        "url": "https://api.venice.ai/api/v1/chat/completions",
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-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"The retrieved rates are:\\n- **\"}}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"ZEBRA:** 23\\n- **MOOSE:** 31\\n\\n### Calculation:\\n1. **Add\"}}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\" the rates:**  \\n   $$23 + 31 = 54$$\\n\\n2. **Multiply by 7:**  \"}}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"\\n   $$54 \\\\times 7 = 378$$\\n\\nThe final result is **378\"}}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"**.\"}}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"thought_signature\":\"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\"}}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{},\"finish_reason\":\"stop\"}]}\n\ndata: {\"id\":\"gcp-1791170512529-w6lmsz\",\"object\":\"chat.completion.chunk\",\"created\":1791170512,\"model\":\"gemini-3-8-flash\",\"choices\":[],\"usage\":{\"prompt_tokens\":206,\"completion_tokens\":208,\"total_tokens\":414},\"cost\":{\"usd\":0.001168125,\"diem\":0}}\n\ndata: [DONE]\n\n"
-      }
-    },
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"gemini-3-8-flash\",\"messages\":[{\"role\":\"user\",\"content\":\"Look up private rates for both ZEBRA and MOOSE using two calls to lookup_rate. Then add the rates and multiply by 7. Use parallel calls if possible.\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"call_0\",\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"arguments\":\"{\\\"code\\\":\\\"ZEBRA\\\"}\"},\"thought_signature\":\"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\"},{\"id\":\"call_1\",\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"arguments\":\"{\\\"code\\\":\\\"MOOSE\\\"}\"}}]},{\"role\":\"tool\",\"tool_call_id\":\"call_0\",\"content\":\"{\\\"rate\\\":23}\"},{\"role\":\"tool\",\"tool_call_id\":\"call_1\",\"content\":\"{\\\"rate\\\":31}\"},{\"role\":\"assistant\",\"content\":\"The retrieved rates are:\\n- **ZEBRA:** 23\\n- **MOOSE:** 31\\n\\n### Calculation:\\n1. **Add the rates:**  \\n   $$23 + 31 = 54$$\\n\\n2. **Multiply by 7:**  \\n   $$54 \\\\times 7 = 378$$\\n\\nThe final result is **378**.\",\"thought_signature\":\"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\"},{\"role\":\"user\",\"content\":\"Add 7 to your previous final answer. Reply with just the number.\"}],\"tools\":[{\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"description\":\"Retrieve the private conversion rate for a code. Only this tool knows the rate.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"code\":{\"type\":\"string\",\"enum\":[\"ZEBRA\",\"MOOSE\"]}},\"required\":[\"code\"],\"additionalProperties\":false},\"strict\":false}}],\"tool_choice\":\"none\",\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"reasoning\":{\"effort\":\"high\"},\"venice_parameters\":{\"include_venice_system_prompt\":false},\"parallel_tool_calls\":true}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
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-        },
-        "body": "data: {\"id\":\"gcp-1791170514341-j5gh1h\",\"object\":\"chat.completion.chunk\",\"created\":1791170514,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"385\"}}]}\n\ndata: {\"id\":\"gcp-1791170514341-j5gh1h\",\"object\":\"chat.completion.chunk\",\"created\":1791170514,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{\"thought_signature\":\"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\"}}]}\n\ndata: {\"id\":\"gcp-1791170514341-j5gh1h\",\"object\":\"chat.completion.chunk\",\"created\":1791170514,\"model\":\"gemini-3-8-flash\",\"choices\":[{\"index\":0,\"delta\":{},\"finish_reason\":\"stop\"}]}\n\ndata: {\"id\":\"gcp-1791170514341-j5gh1h\",\"object\":\"chat.completion.chunk\",\"created\":1791170514,\"model\":\"gemini-3-8-flash\",\"choices\":[],\"usage\":{\"prompt_tokens\":429,\"completion_tokens\":83,\"total_tokens\":512},\"cost\":{\"usd\":0.00079125,\"diem\":0}}\n\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -1,75 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "model": "openai-gpt-54-mini",
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "reasoning",
-      "tool",
-      "tool-loop",
-      "continuation",
-      "usage",
-      "encrypted"
-    ],
-    "name": "venice-chat/openai-gpt-54-mini-preserves-reasoning-through-a-tool-loop-and-follow-up",
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You must use lookup_rate before answering.\"},{\"role\":\"assistant\",\"content\":null,\"tool_calls\":[{\"id\":\"call_onp7EArhOgXu0hGRF6Y5WHLu\",\"type\":\"function\",\"function\":{\"name\":\"lookup_rate\",\"arguments\":\"{\\\"code\\\":\\\"ZEBRA\\\"}\"}}],\"reasoning_details\":[{\"type\":\"reasoning.encrypted\",\"data\":\"gAAAAABqwxLxEN4vtmI2WcZ_aDDttdmPwAHgnV2gLZBo_f_mmTdGm4oZzE2JVzcj72AeXHyABmmo2VQN4nXaZK9GSSUZRlYL8mECMxKTj9AMgL8zlnuN5WDexxU-e9SduGP36RN9nH56-go4dz8eu5DEMvMf_TMoTnxz5AnC_UWbty63Vp8jEgkD-DoRjd0cg9LjthP_FLyMvP2Wj9qMJxEuO7Mw2_Pu4I3YeChnygLvmRfRR2QkamL5vjb9yHkl0Lb502vEGB2DW_czNEpHxisifvwRBjA7vk0mbn2dlhiR80aNHO71hC-QqrtUfPXx2HIbVLfbPdJf0saI0wD7ZuCJSQCBfB7fMCnj2ZLQeXa67lgXwsZDLBg4HmSJFvsMinx1IHIjUk7iebsKvmYx40cjqpXL3wj7htZWk2hO9OyGGUwlRsn5THdhTsgwg2SPbuHxb-sLPQnEFZ7bRp5lsVm31X2dlHDa1uZ7KLJZyy9g2CLIKsBwFFoCK7jY3HBXfL21ac5TAkOzVmz-XKl6OMPSl-PSdByOO15uHHpyOcJvJvuaea5Tj1nihtuDlhUP5EQPi7MiWpJMFo9AhDCafAbaQOEF5W8AQPeb_GXvPTzhySRAC8PxrhraEcZ4fjpjLqkv6mi_A1YHwbHEHHWjcK5VEKc3dadlIM_s6djclFBocVXrvnQQElVhWBDM-RtK9sgR07BFj5LVk6fYvg0b6gQnbDuQH18jhtPoj0SX0lN921XEQ1ebMCWGLANND2ew_wyNShYouJohefLULicWG57xh_yV1KEG1ufBedq2CPvCHA9Hm5UssbeJx5yBriyUA2Yh4D7j2UBT_KDWEHydDLQ4mWEyLTfQn0ZB3ZOqkU79z3HpK2w_VHUnkl5nEYEU2bmF5lsG33B4gtbQIBtZT76-fizXsvVZx__taOWXg96VMi3CD3DY0TS76B4U92KFmAFJ4aeiM8bkPuzf1Qd202EWE39CotUDoxAM6mzQu0NObTDnGQE776P6kzUoIKUmP8sDwYG5xot8ZTuXcBYysvj4-pFC_fvqMhsdfgonbke78SIjHtmePsOkfHBnCjSSUFKEbaM0nm8jJ6nYVwiYFuXBKD31QD462TAC7ORVIn32sWSgV2t3Sd7vq4ws2Yy7nUoILRAt_NYQUEXt7_R8J5YWj1L6Ruagk7Vtt-CAWxT6FhVyU4JhMb6-tJrYHgdmtunYrjpHBiOVdQR25aOmLbc_WlDvpO4azcRazpgkASAjPaaDycYceKcheiyUDBgFrvcSYrS1fJb6YZrTzOKw1Ztd0YsklS4nc3jffLNLrBQVvnkajj0OHjGcW8wkP93TCMJyt8tfIH0Rd5hIZLY5EqUWj9yZgXO7CuDKQZIEI0oZXef3mjfQqH8Q9rZsSgS3DI3mCF3CN003R_ZKKLGWkG8VzwlvdocNxaV_Z-ujp_O0YMyOcmEoTJI-j3JP3nefNboyP7EWND6VWDjJbqg64dvu0PK0EW5L0lnAu0l-WVb2qmXLYao_7bOlD8JLFZOyUgHAWmetmnm0NuxzevJEVBkNUu1jQatPzf2Jzf9SGKM_3bM_z0TM5McCZ2Pikzwp96QlaiEEWV_j2g02PT5Y3td-lfpoKxoFD5tltGNY9TlPzK-4a9Iz0hloiCprxWMLGKw2JzctrPF1xr42PKGNgPE84xAQ3sQ4mQ==\",\"id\":\"rs_014406f0f45e19c6016ac312f01d2487d2a5f2bdb7fbc42f76\",\"format\":\"openai-responses-v1\",\"index\":0}],\"reasoning_content\":\"**Calculating private data**\\n\\nI need to follow the developer's instructions and use the provided tool to handle private data. First, I should look up the rate for \\\"ZEBRA\\\" before I answer. After that, I’ll multiply the rate by 17 and then add 9 to get the required number. It’s important to give only the requested number and avoid making another tool call. I’ll likely use the commentary channel for this tool call.\\n\\n__ENCRYPTED_REASONING__id=rs_014406f0f45e19c6016ac312f01d2487d2a5f2bdb7fbc42f76\\ngAAAAABqwxLxEN4vtmI2WcZ_aDDttdmPwAHgnV2gLZBo_f_mmTdGm4oZzE2JVzcj72AeXHyABmmo2VQN4nXaZK9GSSUZRlYL8mECMxKTj9AMgL8zlnuN5WDexxU-e9SduGP36RN9nH56-go4dz8eu5DEMvMf_TMoTnxz5AnC_UWbty63Vp8jEgkD-DoRjd0cg9LjthP_FLyMvP2Wj9qMJxEuO7Mw2_Pu4I3YeChnygLvmRfRR2QkamL5vjb9yHkl0Lb502vEGB2DW_czNEpHxisifvwRBjA7vk0mbn2dlhiR80aNHO71hC-QqrtUfPXx2HIbVLfbPdJf0saI0wD7ZuCJSQCBfB7fMCnj2ZLQeXa67lgXwsZDLBg4HmSJFvsMinx1IHIjUk7iebsKvmYx40cjqpXL3wj7htZWk2hO9OyGGUwlRsn5THdhTsgwg2SPbuHxb-sLPQnEFZ7bRp5lsVm31X2dlHDa1uZ7KLJZyy9g2CLIKsBwFFoCK7jY3HBXfL21ac5TAkOzVmz-XKl6OMPSl-PSdByOO15uHHpyOcJvJvuaea5Tj1nihtuDlhUP5EQPi7MiWpJMFo9AhDCafAbaQOEF5W8AQPeb_GXvPTzhySRAC8PxrhraEcZ4fjpjLqkv6mi_A1YHwbHEHHWjcK5VEKc3dadlIM_s6djclFBocVXrvnQQElVhWBDM-RtK9sgR07BFj5LVk6fYvg0b6gQnbDuQH18jhtPoj0SX0lN921XEQ1ebMCWGLANND2ew_wyNShYouJohefLULicWG57xh_yV1KEG1ufBedq2CPvCHA9Hm5UssbeJx5yBriyUA2Yh4D7j2UBT_KDWEHydDLQ4mWEyLTfQn0ZB3ZOqkU79z3HpK2w_VHUnkl5nEYEU2bmF5lsG33B4gtbQIBtZT76-fizXsvVZx__taOWXg96VMi3CD3DY0TS76B4U92KFmAFJ4aeiM8bkPuzf1Qd202EWE39CotUDoxAM6mzQu0NObTDnGQE776P6kzUoIKUmP8sDwYG5xot8ZTuXcBYysvj4-pFC_fvqMhsdfgonbke78SIjHtmePsOkfHBnCjSSUFKEbaM0nm8jJ6nYVwiYFuXBKD31QD462TAC7ORVIn32sWSgV2t3Sd7vq4ws2Yy7nUoILRAt_NYQUEXt7_R8J5YWj1L6Ruagk7Vtt-CAWxT6FhVyU4JhMb6-tJrYHgdmtunYrjpHBiOVdQR25aOmLbc_WlDvpO4azcRazpgkASAjPaaDycYceKcheiyUDBgFrvcSYrS1fJb6YZrTzOKw1Ztd0YsklS4nc3jffLNLrBQVvnkajj0OHjGcW8wkP93TCMJyt8tfIH0Rd5hIZLY5EqUWj9yZgXO7CuDKQZIEI0oZXef3mjfQqH8Q9rZsSgS3DI3mCF3CN003R_ZKKLGWkG8VzwlvdocNxaV_Z-ujp_O0YMyOcmEoTJI-j3JP3nefNboyP7EWND6VWDjJbqg64dvu0PK0EW5L0lnAu0l-WVb2qmXLYao_7bOlD8JLFZOyUgHAWmetmnm0NuxzevJEVBkNUu1jQatPzf2Jzf9SGKM_3bM_z0TM5McCZ2Pikzwp96QlaiEEWV_j2g02PT5Y3td-lfpoKxoFD5tltGNY9TlPzK-4a9Iz0hloiCprxWMLGKw2JzctrPF1xr42PKGNgPE84xAQ3sQ4mQ==\"},{\"role\":\"tool\",\"tool_call_id\":\"call_onp7EArhOgXu0hGRF6Y5WHLu\",\"content\":\"{\\\"code\\\":\\\"ZEBRA\\\",\\\"rate\\\":23}\"},{\"role\":\"assistant\",\"content\":\"400\",\"reasoning_details\":[{\"type\":\"reasoning.encrypted\",\"data\":\"gAAAAABqwxL0Nl6Jl5EZuOLine truncated
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\"**Calculating a simple addition**\\n\\nThe\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" user\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" wants\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" me\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" to\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" add\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" 7\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" to\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" the\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" previous\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" final\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" answer\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\",\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" which\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" was\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" 400\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\".\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"choices\":[{\"index\":0,\"delta\":{\"reasoning_content\":\" This\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"resp_014406f0f45e19c6016ac312f49b9c87d2afc60121b8910612\",\"object\":\"chat.completion.chunk\",\"created\":1791169269,\"model\":\"openai-gpt-54-mini\",\"Line truncated
-      }
-    }
-  ]
-}
@@ -1,35 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "text",
-      "reasoning",
-      "toggle"
-    ],
-    "name": "venice-chat/qwen-disables-reasoning",
-    "recordedAt": "2026-10-05T02:59:04.614Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"qwen3-6-27b\",\"messages\":[{\"role\":\"user\",\"content\":\"What is 23 multiplied by 17 plus 9? Reply with just the number.\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"max_completion_tokens\":4096,\"reasoning\":{\"enabled\":false},\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 200,
-        "headers": {
-          "content-type": "text/event-stream; charset=utf-8"
-        },
-        "body": "data: {\"service_tier\":null,\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":\"assistant\",\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"4\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"0\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"0\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":null}],\"usage\":null}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[{\"index\":0,\"delta\":{\"role\":null,\"content\":\"\",\"reasoning_content\":null,\"tool_calls\":null},\"logprobs\":null,\"finish_reason\":\"stop\"}]}\n\ndata: {\"service_tier\":\"default\",\"id\":\"chatcmpl-RxYUpStKYw7YgEZcXjsb2dOt\",\"object\":\"chat.completion.chunk\",\"created\":1791169144,\"model\":\"qwen3-6-27b\",\"choices\":[],\"usage\":{\"prompt_tokens\":32,\"completion_tokens\":4,\"total_tokens\":36},\"cost\":{\"usd\":0.0000234,\"diem\":0}}\n\ndata: [DONE]\n\n"
-      }
-    }
-  ]
-}
@@ -1,33 +0,0 @@
-{
-  "version": 1,
-  "metadata": {
-    "tags": [
-      "prefix:venice-chat",
-      "provider:venice",
-      "protocol:venice-chat",
-      "error"
-    ],
-    "name": "venice-chat/surfaces-venice-model-errors",
-    "recordedAt": "2026-10-05T02:59:11.768Z"
-  },
-  "interactions": [
-    {
-      "transport": "http",
-      "request": {
-        "method": "POST",
-        "url": "https://api.venice.ai/api/v1/chat/completions",
-        "headers": {
-          "content-type": "application/json"
-        },
-        "body": "{\"model\":\"no-such-model-xyz\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"venice_parameters\":{\"include_venice_system_prompt\":false}}"
-      },
-      "response": {
-        "status": 404,
-        "headers": {
-          "content-type": "application/json; charset=utf-8"
-        },
-        "body": "{\"error\":\"Specified model not found: no-such-model-xyz. Did you mean: z-ai-glm-5-3, z-ai-glm-5-3-flash, z-ai-glm-5-turbo?\"}"
-      }
-    }
-  ]
-}
@@ -8,6 +8,7 @@ import {
  type ProviderMetadata,
  type ToolCallPart,
  ToolResultPart,
+  type ToolResultValue,
  type Usage,
 } from "../../src/schema/index.js"
 import { type Tools, toDefinitions } from "../../src/tool.js"
@@ -39,7 +39,9 @@ describe("provider error classification", () => {
    ]

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

@@ -460,27 +462,6 @@ 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: {
@@ -1,26 +0,0 @@
-import { LLM } from "../../src/index.js"
-import { Venice } from "../../src/providers.js"
-
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  providerOptions: { reasoningEffort: "high", reasoning: { summary: "concise" }, veniceParameters: { includeVeniceSystemPrompt: false } },
-})
-LLM.request({
-  model: Venice.configure({ providerOptions: { reasoningEffort: "future-effort" } }).model("future-model"),
-  providerOptions: { reasoning: { enabled: false }, promptCacheRetention: "future-retention", parallelToolCalls: false },
-})
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  // @ts-expect-error Thinking toggles are boolean.
-  providerOptions: { reasoning: { enabled: "false" } },
-})
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  // @ts-expect-error Venice uses nested reasoning, not Anthropic thinking controls.
-  providerOptions: { thinking: { type: "disabled" } },
-})
-LLM.request({
-  model: Venice.chat("qwen3-6-27b"),
-  // @ts-expect-error Venice's system-prompt toggle is boolean.
-  providerOptions: { veniceParameters: { includeVeniceSystemPrompt: "false" } },
-})
@@ -7,6 +7,67 @@ const configuration = (provider: string, message: string) =>
  expect.objectContaining({ _tag: "ProviderConfiguration", provider, message })

 describe("provider package entrypoints", () => {
+  test("semantic API aliases expose the same contract", async () => {
+    const modules = await Promise.all([
+      import("@opencode/ai/providers/openai"),
+      import("@opencode/ai/providers/openai/responses"),
+      import("@opencode/ai/providers/openai/chat"),
+      import("@opencode/ai/providers/anthropic"),
+      import("@opencode/ai/providers/anthropic-compatible"),
+      import("@opencode/ai/providers/openai-compatible"),
+      import("@opencode/ai/providers/openai-compatible/responses"),
+      import("@opencode/ai/providers/amazon-bedrock"),
+      import("@opencode/ai/providers/azure"),
+      import("@opencode/ai/providers/azure/responses"),
+      import("@opencode/ai/providers/azure/chat"),
+      import("@opencode/ai/providers/google"),
+      import("@opencode/ai/providers/google-vertex"),
+      import("@opencode/ai/providers/google-vertex/gemini"),
+      import("@opencode/ai/providers/google-vertex/chat"),
+      import("@opencode/ai/providers/google-vertex/responses"),
+      import("@opencode/ai/providers/google-vertex/messages"),
+      import("@opencode/ai/providers/openrouter"),
+      import("@opencode/ai/providers/xai"),
+      import("@opencode/ai/providers/amazon-bedrock/mantle"),
+      import("@opencode/ai/providers/amazon-bedrock/mantle/chat"),
+      import("@opencode/ai/providers/amazon-bedrock/mantle/responses"),
+      import("@opencode/ai/providers/togetherai"),
+      import("@opencode/ai/providers/cerebras"),
+      import("@opencode/ai/providers/deepinfra"),
+      import("@opencode/ai/providers/groq"),
+      import("@opencode/ai/providers/baseten"),
+      import("@opencode/ai/providers/deepseek"),
+      import("@opencode/ai/providers/fireworks"),
+      import("@opencode/ai/providers/cloudflare-ai-gateway"),
+      import("@opencode/ai/providers/cloudflare-workers-ai"),
+      import("@opencode/ai/providers/minimax"),
+      import("@opencode/ai/providers/minimax/messages"),
+      import("@opencode/ai/providers/minimax/chat"),
+      import("@opencode/ai/providers/minimax/responses"),
+      import("@opencode/ai/providers/moonshot"),
+      import("@opencode/ai/providers/moonshot/chat"),
+      import("@opencode/ai/providers/moonshot/messages"),
+      import("@opencode/ai/providers/moonshot/responses"),
+      import("@opencode/ai/providers/zai"),
+      import("@opencode/ai/providers/zai/chat"),
+      import("@opencode/ai/providers/zai-coding-plan"),
+      import("@opencode/ai/providers/zai-coding-plan/chat"),
+      import("@opencode/ai/providers/zai-coding-plan/messages"),
+      import("@opencode/ai/providers/zai-coding-plan/responses"),
+      import("@opencode/ai/providers/alibaba"),
+      import("@opencode/ai/providers/alibaba/chat"),
+      import("@opencode/ai/providers/alibaba/messages"),
+      import("@opencode/ai/providers/alibaba/responses"),
+    ])
+
+    for (const module of modules) expect(module.model).toBeFunction()
+    expect(modules[0].model).toBe(modules[1].model)
+    expect(modules[8].model).toBe(modules[9].model)
+    expect(modules[12].model).toBe(modules[13].model)
+    expect(modules[19].model).toBe(modules[21].model)
+    expect(modules[19].model).not.toBe(modules[20].model)
+  })
+
  test("maps Alibaba API entrypoints onto explicit regional routes", async () => {
    const modules = await Promise.all([
      import("@opencode/ai/providers/alibaba"),
@@ -14,6 +75,7 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/alibaba/messages"),
      import("@opencode/ai/providers/alibaba/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
    const settings = {
      region: "eu-central-1",
      workspaceID: "llm-fixture",
@@ -41,6 +103,7 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/moonshot/messages"),
      import("@opencode/ai/providers/moonshot/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
    const settings = {
      apiKey: "fixture",
      baseURL: "https://gateway.example/v1",
@@ -58,25 +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"),
@@ -84,6 +128,7 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/minimax/chat"),
      import("@opencode/ai/providers/minimax/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
    const settings = {
      apiKey: "fixture",
      baseURL: "https://gateway.example/v1",
@@ -110,6 +155,8 @@ describe("provider package entrypoints", () => {
      import("@opencode/ai/providers/zai-coding-plan/messages"),
      import("@opencode/ai/providers/zai-coding-plan/responses"),
    ])
+    expect(modules[0].model).toBe(modules[1].model)
+    expect(modules[2].model).toBe(modules[3].model)
    const routes = [
      "zai-chat",
      "zai-chat",
@@ -364,7 +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",
@@ -378,20 +424,11 @@ describe("provider package entrypoints", () => {
    expect(selected.route.defaults.headers).toEqual({ "x-application": "opencode" })
    expect(selected.route.defaults.http?.body).toEqual({ safetySettings: [] })
    expect(selected.route.defaults.providerOptions).toEqual({ thinkingConfig: { thinkingBudget: 1_024 } })
-    const interactions = GoogleInteractions.model("gemini-3.8-flash", {
-      apiKey: "fixture",
-      baseURL: "https://generativelanguage.test/v1beta",
-      thinkingLevel: "low",
-      store: true,
-    })
-    expect(interactions.route.id).toBe("google-interactions")
-    expect(interactions.route.endpoint.baseURL).toBe("https://generativelanguage.test/v1beta")
-    expect(interactions.route.defaults.providerOptions).toEqual({ thinkingLevel: "low", store: true })
-    expect(Google.configure().interactions("gemini-3.8-flash").route.protocol).toBe("google-interactions")
  })

  test("selects Vertex entrypoints with the same model contract", async () => {
    const GoogleVertex = await import("@opencode/ai/providers/google-vertex")
+    const GoogleVertexGemini = await import("@opencode/ai/providers/google-vertex/gemini")
    const GoogleVertexChat = await import("@opencode/ai/providers/google-vertex/chat")
    const GoogleVertexResponses = await import("@opencode/ai/providers/google-vertex/responses")
    const GoogleVertexMessages = await import("@opencode/ai/providers/google-vertex/messages")
@@ -416,6 +453,7 @@ describe("provider package entrypoints", () => {
      project: "vertex-project",
    })

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

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

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

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

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

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

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

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

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

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

@@ -239,198 +201,3 @@ describe("Amazon Bedrock Mantle recorded", () => {
    }),
  )
 })
-
-const recordedMessages = recordedTests({
-  prefix: "bedrock-mantle-messages",
-  provider: "amazon-bedrock",
-  protocol: "anthropic-messages",
-  requires: ["AWS_BEARER_TOKEN_BEDROCK"],
-  options: { redact: { allowRequestHeaders: ["anthropic-version", "anthropic-beta"] } },
-})
-
-const mantleMessages = (modelID: string) =>
-  AmazonBedrockMantle.configure({
-    apiKey: process.env.AWS_BEARER_TOKEN_BEDROCK ?? "fixture",
-    region: "us-east-1",
-  }).messages(modelID)
-
-const weatherTool = ToolDefinition.make({
-  name: "get_weather",
-  description: "Get the current weather in a city",
-  inputSchema: {
-    type: "object",
-    properties: { city: { type: "string", enum: ["Paris"] } },
-    required: ["city"],
-    additionalProperties: false,
-  },
-})
-
-describe("Amazon Bedrock Mantle Messages recorded", () => {
-  recordedMessages.effect.with(
-    "replays signed thinking through a tool loop and native system update",
-    { tags: ["tool", "tool-loop", "reasoning", "system-update"], metadata: { model: "anthropic.claude-opus-4-8" } },
-    () =>
-      Effect.gen(function* () {
-        const model = mantleMessages("anthropic.claude-opus-4-8")
-        const initial = LLM.request({
-          model,
-          system: "You are a concise assistant.",
-          prompt:
-            "First calculate 37 * 43. Then call get_weather for Paris. After receiving the tool result, state both the product and the weather.",
-          tools: [weatherTool],
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "medium",
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const first = yield* LLMClient.generate(initial)
-        expect(first.finishReason.normalized).toBe("tool-calls")
-        expect(first.toolCalls).toMatchObject([{ name: "get_weather", input: { city: "Paris" } }])
-        expect(first.reasoning.length).toBeGreaterThan(0)
-        expect(first.events.some(LLMEvent.is.toolInputDelta)).toBe(true)
-        const reasoningPart = first.message.content.find((part) => part.type === "reasoning")
-        const signature = (reasoningPart?.providerMetadata?.mantle as { readonly signature?: unknown } | undefined)
-          ?.signature
-        expect(typeof signature).toBe("string")
-
-        const followUp = LLMRequest.update(initial, {
-          messages: [
-            ...initial.messages,
-            first.message,
-            ...first.toolCalls.map((call) =>
-              Message.tool({ id: call.id, name: call.name, result: { condition: "sunny", temperatureC: 18 } }),
-            ),
-            Message.system("Reply in French in one short sentence."),
-          ],
-        })
-        const compiled = yield* compileRequest(followUp)
-        expect(compiled.body.messages[1]?.content[0]).toEqual({
-          type: "thinking",
-          thinking: first.reasoning,
-          signature: signature as string,
-        })
-        expect(compiled.body.messages.at(-1)).toEqual({
-          role: "system",
-          content: [
-            { type: "text", text: "Reply in French in one short sentence.", cache_control: { type: "ephemeral" } },
-          ],
-        })
-
-        const second = yield* LLMClient.generate(followUp)
-        expect(second.finishReason.normalized).toBe("stop")
-        expect(second.text).toContain("1591")
-        expect(second.text).toContain("18")
-      }),
-    120_000,
-  )
-
-  recordedMessages.effect.with(
-    "lowers system updates to wrapped user text on Haiku 4.5 with budget thinking",
-    { tags: ["reasoning", "system-update"], metadata: { model: "anthropic.claude-haiku-4-5" } },
-    () =>
-      Effect.gen(function* () {
-        const request = LLM.request({
-          model: mantleMessages("anthropic.claude-haiku-4-5"),
-          messages: [Message.user("What is 19 multiplied by 23?"), Message.system("Reply with only the integer.")],
-          providerOptions: {
-            thinking: { type: "enabled", budgetTokens: 1024 },
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const compiled = yield* compileRequest(request)
-        expect(compiled.body.thinking).toEqual({ type: "enabled", budget_tokens: 1024 })
-        expect(compiled.body.messages.some((message) => message.role === "system")).toBe(false)
-
-        const response = yield* LLMClient.generate(request)
-        expect(response.finishReason.normalized).toBe("stop")
-        expect(response.reasoning.length).toBeGreaterThan(0)
-        expect(response.text.trim()).toContain("437")
-      }),
-    120_000,
-  )
-
-  recordedMessages.effect.with(
-    "applies mid-conversation effort updates and thinking block binding on Opus 5.5",
-    { tags: ["reasoning", "effort-update"], metadata: { model: "anthropic.claude-opus-5-5" } },
-    () =>
-      Effect.gen(function* () {
-        const model = mantleMessages("anthropic.claude-opus-5-5")
-        const firstRequest = LLM.request({
-          model,
-          prompt: "Compute 37 * 43 step by step, then reply with only the integer.",
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "high",
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const firstCompiled = yield* compileRequest(firstRequest)
-        expect(firstCompiled.body.thinking).toEqual({
-          type: "adaptive",
-          display: "summarized",
-          block_binding: { prefix_mismatch_behavior: "drop_block" },
-        })
-
-        const first = yield* LLMClient.generate(firstRequest)
-        expect(first.finishReason.normalized).toBe("stop")
-        expect(first.reasoning.length).toBeGreaterThan(0)
-        expect(first.text.replaceAll(",", "")).toContain("1591")
-
-        const secondRequest = LLM.request({
-          model,
-          messages: [
-            ...firstRequest.messages,
-            first.message,
-            Message.effort({ effort: "low", previous: "high" }),
-            Message.user("Add 9 to that result. Reply with only the integer."),
-          ],
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "low",
-          },
-          generation: { maxTokens: 2048 },
-        })
-        const secondCompiled = yield* compileRequest(secondRequest)
-        expect(secondCompiled.body.output_config).toEqual({ effort: "high" })
-        expect(secondCompiled.body.messages.filter((message) => message.role === "system")).toEqual([
-          { role: "system", content: [], output_config: { effort: "low" } },
-        ])
-
-        const second = yield* LLMClient.generate(secondRequest)
-        expect(second.finishReason.normalized).toBe("stop")
-        expect(second.text.replaceAll(",", "")).toContain("1600")
-      }),
-    120_000,
-  )
-
-  recordedMessages.effect.with(
-    "strips unsupported mid-conversation effort updates on Opus 5.0",
-    { tags: ["reasoning", "effort-update"], metadata: { model: "anthropic.claude-opus-5" } },
-    () =>
-      Effect.gen(function* () {
-        const request = LLM.request({
-          model: mantleMessages("anthropic.claude-opus-5"),
-          messages: [
-            Message.user("What is 12 + 30?"),
-            Message.assistant("42"),
-            Message.effort({ effort: "low", previous: "high" }),
-            Message.user("Add 8 to that result. Reply with only the integer."),
-          ],
-          providerOptions: {
-            thinking: { type: "adaptive", display: "summarized" },
-            effort: "low",
-          },
-          generation: { maxTokens: 1024 },
-        })
-        const compiled = yield* compileRequest(request)
-        expect(compiled.body.output_config).toEqual({ effort: "low" })
-        expect(compiled.body.messages.some((message) => message.role === "system")).toBe(false)
-
-        const response = yield* LLMClient.generate(request)
-        expect(response.finishReason.normalized).toBe("stop")
-        expect(response.text.trim()).toContain("50")
-      }),
-    120_000,
-  )
-})
@@ -1,4 +1,4 @@
-import { describe, expect } from "bun:test"
+import { describe, expect, test } from "bun:test"
 import { ConfigProvider, Effect, Schema } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
 import { LLM, LLMEvent } from "../../src/index.js"
@@ -1,98 +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,
-)
Author	SHA1	Message	Date
Simon Klee	ff941aecf5	tui: await renderer before terminal handoff Ensure terminal ownership changes complete before suspending or launching an external editor, preventing stale renders during resume.	2026-10-02 21:09:44 +02:00
Simon Klee	8e392aef69	bump snapshot	2026-10-02 12:52:48 +02:00
Simon Klee	efec0a2cf5	tui: pin OpenTUI native snapshot Ensure OpenCode and plugins resolve the same native renderer build across supported platforms.	2026-10-02 12:52:48 +02:00
Simon Klee	7f5d17eb02	wip oc-ot-native	2026-10-02 12:52:47 +02:00