feat(core): record overflow as a compaction reason

chore(nix): update nixpkgs for Bun 1.4 (#50221 )
Co-authored-by: Test User <test@test.com>
2026-09-28 03:27:37 +00:00 · 2026-09-27 22:14:42 -05:00 · 2026-09-27 21:34:52 -05:00 · 2026-09-27 15:05:46 -07:00 · 2026-09-27 14:47:19 -07:00 · 2026-09-27 21:05:20 +02:00
352 changed files with 11161 additions and 4303 deletions
@@ -1,5 +0,0 @@
---
-"@opencode/core": patch
---
-
-Correct directory page headings when the read offset is zero.
@@ -184,7 +184,7 @@ const table = sqliteTable("session", {
 - Keep `SessionRunner`, model resolution, tool registry, permissions, and filesystem Location-scoped. Omitted `Location.workspaceID` means implicit-local placement; explicit workspace identity remains reserved for future placement semantics.
 - Preserve one explicit `llm.stream(request)` call per Physical Attempt and reload projected history before durable continuation. A logical Step may use generic pre-output retries, one full-context retry after continuation rejection, incomplete-stream continuation, or one overflow-compaction rebuild. Generic retries retain the logical step number and do not consume another agent-step allowance. Do not delegate orchestration to an in-memory tool loop.
 - Keep local Session drains process-local until clustering is implemented. `SessionRunCoordinator` joins explicit same-Session resumes, coalesces prompt wakeups, and allows different Sessions to run concurrently. A write-ahead execution claim marks a process-local busy period for restart recovery: terminal completion, failure, or user interruption releases it, while shutdown interruption and process death preserve it. Startup recovery resumes claimed top-level Sessions with durable per-execution attempt accounting. The claim is a recovery marker, not clustered ownership, fencing, or an exactly-once guarantee.
- Keep native compaction mechanisms out of `SessionCompaction`. Plugins register `native` strategies through the `SessionCompaction` editor that turn a prepared request into a replacement window (the built-in `NativeCompactionPlugin` handles `@opencode/ai` compaction operations); later registrations win. Core owns the provider-mode decision, route provenance, the retry policy, overflow recovery, interruption, usage accounting, and checkpoint persistence.
+- Keep provider-specific native compaction mechanisms in `@opencode/ai` behind `LLMClient.compact`. `SessionCompaction` chooses a summary or native compaction from the model's `compaction` setting and owns route provenance, request shrinking, the retry policy, interruption, usage accounting, and checkpoint persistence.
 - Keep delivery vocabulary explicit. Prompts steer by default. At safe step boundaries, steered compaction takes priority up to the first steered move control; other steers retain enqueue order. At an idle boundary, steers take priority; otherwise exactly one queued item delivers before the runner reevaluates continuation. Inbox items may be cancelled or changed between queue and steer before delivery. Promoting new user input resets the selected agent's step allowance; a batch of steers resets it once.
 - One step is one logical LLM call; its durable record covers only the model-visible span. Do not write "provider turn", and do not use bare "turn" for a single call: "turn" is reserved for the future assistant-turn unit containing all steps from prompt promotion until the session would go idle.
 - Keep event replay ownership separate from clustered Session execution ownership.
@@ -32,7 +32,7 @@
    },
    "packages/ai": {
      "name": "@opencode/ai",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@aws-sdk/credential-providers": "3.1057.0",
        "@opencode/schema": "workspace:*",
@@ -54,7 +54,7 @@
    },
    "packages/app": {
      "name": "@opencode/app",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@corvu/drawer": "catalog:",
        "@dnd-kit/abstract": "0.5.0",
@@ -112,13 +112,14 @@
    },
    "packages/cli": {
      "name": "@opencode/cli",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "bin": {
        "opencode": "./bin/opencode.cjs",
        "opencode2": "./bin/opencode2.cjs",
      },
      "dependencies": {
        "@agentclientprotocol/sdk": "1.2.1",
+        "@clack/core": "1.0.0-alpha.1",
        "@clack/prompts": "1.0.0-alpha.1",
        "@effect/platform-node": "catalog:",
        "@opencode-ai/pty": "0.1.13",
@@ -135,7 +136,7 @@
        "effect": "catalog:",
        "immer": "11.1.4",
        "jsonc-parser": "3.3.1",
-        "open": "10.1.2",
+        "picocolors": "1.1.1",
        "solid-js": "catalog:",
        "tree-sitter-bash": "0.25.0",
        "tree-sitter-powershell": "0.25.10",
@@ -177,7 +178,7 @@
    },
    "packages/client": {
      "name": "@opencode/client",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/protocol": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -203,7 +204,7 @@
    },
    "packages/codemode": {
      "name": "@opencode/codemode",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "acorn": "8.15.0",
        "effect": "catalog:",
@@ -216,7 +217,7 @@
    },
    "packages/console/app": {
      "name": "@opencode/console-app",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@ibm/plex": "6.4.1",
@@ -252,7 +253,7 @@
    },
    "packages/console/core": {
      "name": "@opencode/console-core",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@aws-sdk/client-sts": "3.782.0",
        "@jsx-email/render": "1.1.1",
@@ -279,7 +280,7 @@
    },
    "packages/console/function": {
      "name": "@opencode/console-function",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@openauthjs/openauth": "0.0.0-20250322224806",
        "@opencode/console-core": "workspace:*",
@@ -296,7 +297,7 @@
    },
    "packages/console/mail": {
      "name": "@opencode/console-mail",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@jsx-email/all": "2.2.3",
        "@jsx-email/cli": "1.4.3",
@@ -320,7 +321,7 @@
    },
    "packages/console/support": {
      "name": "@opencode/console-support",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@opencode/console-core": "workspace:*",
@@ -340,7 +341,7 @@
    },
    "packages/core": {
      "name": "@opencode/core",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@ai-sdk/cohere": "3.0.27",
        "@ai-sdk/gateway": "3.0.104",
@@ -408,7 +409,7 @@
    },
    "packages/desktop": {
      "name": "@opencode/desktop",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@zip.js/zip.js": "2.7.62",
        "electron-context-menu": "5.0.0",
@@ -457,7 +458,7 @@
    },
    "packages/enterprise": {
      "name": "@opencode/enterprise",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@hono/standard-validator": "catalog:",
        "@opencode-ai/sdk": "1.18.21",
@@ -494,7 +495,7 @@
    },
    "packages/function": {
      "name": "@opencode/function",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@octokit/auth-app": "8.0.1",
        "@octokit/rest": "catalog:",
@@ -510,7 +511,7 @@
    },
    "packages/http-recorder": {
      "name": "@opencode/http-recorder",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@effect/platform-node-shared": "4.0.0-rc.112",
      },
@@ -529,7 +530,7 @@
    },
    "packages/httpapi-codegen": {
      "name": "@opencode/httpapi-codegen",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "effect": "catalog:",
        "prettier": "3.6.2",
@@ -542,7 +543,7 @@
    },
    "packages/latex": {
      "name": "@opencode/latex",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -556,7 +557,7 @@
    },
    "packages/merman": {
      "name": "@opencode/merman",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opentui/core": "catalog:",
@@ -571,7 +572,7 @@
    },
    "packages/plugin": {
      "name": "@opencode/plugin",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@ai-sdk/provider": "3.0.8",
        "@opencode/ai": "workspace:*",
@@ -597,8 +598,8 @@
      },
      "peerDependencies": {
        "@opencode/theme": "workspace:*",
-        "@opentui/core": ">=0.5.10",
-        "@opentui/solid": ">=0.5.10",
+        "@opentui/core": ">=0.5.12",
+        "@opentui/solid": ">=0.5.12",
        "solid-js": ">=1.9.0",
      },
      "optionalPeers": [
@@ -610,7 +611,7 @@
    },
    "packages/plugin-browser": {
      "name": "@opencode/plugin-browser",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/plugin": "workspace:*",
        "@opencode/schema": "workspace:*",
@@ -640,7 +641,7 @@
    },
    "packages/protocol": {
      "name": "@opencode/protocol",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/schema": "workspace:*",
        "effect": "catalog:",
@@ -655,7 +656,7 @@
    },
    "packages/schema": {
      "name": "@opencode/schema",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@standard-schema/spec": "catalog:",
        "effect": "catalog:",
@@ -679,7 +680,7 @@
    },
    "packages/sdk": {
      "name": "@opencode/sdk",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -700,7 +701,7 @@
    },
    "packages/server": {
      "name": "@opencode/server",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@effect/platform-node": "catalog:",
        "@effect/platform-node-shared": "catalog:",
@@ -722,7 +723,7 @@
    },
    "packages/session-ui": {
      "name": "@opencode/session-ui",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode/client": "workspace:*",
@@ -757,7 +758,7 @@
    },
    "packages/simulation": {
      "name": "@opencode/simulation",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/ai": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -777,7 +778,7 @@
    },
    "packages/stats/app": {
      "name": "@opencode/stats-app",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@ibm/plex": "6.4.1",
        "@kobalte/core": "catalog:",
@@ -811,7 +812,7 @@
    },
    "packages/stats/core": {
      "name": "@opencode/stats-core",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@aws-sdk/client-athena": "3.933.0",
        "@planetscale/database": "1.19.0",
@@ -830,7 +831,7 @@
    },
    "packages/stats/server": {
      "name": "@opencode/stats-server",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@aws-sdk/client-firehose": "3.933.0",
        "@effect/platform-node": "catalog:",
@@ -876,7 +877,7 @@
    },
    "packages/theme": {
      "name": "@opencode/theme",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opentui/core": "catalog:",
        "effect": "catalog:",
@@ -890,7 +891,7 @@
    },
    "packages/tui": {
      "name": "@opencode/tui",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@opencode/client": "workspace:*",
        "@opencode/core": "workspace:*",
@@ -909,7 +910,6 @@
        "effect": "catalog:",
        "fuzzysort": "catalog:",
        "get-east-asian-width": "catalog:",
-        "open": "10.1.2",
        "opentui-spinner": "catalog:",
        "remeda": "catalog:",
        "solid-js": "catalog:",
@@ -925,7 +925,7 @@
    },
    "packages/ui": {
      "name": "@opencode/ui",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@pierre/diffs": "catalog:",
@@ -960,7 +960,7 @@
    },
    "packages/util": {
      "name": "@opencode/util",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@effect/opentelemetry": "catalog:",
        "@effect/platform-node": "catalog:",
@@ -982,6 +982,7 @@
        "mime-types": "3.0.2",
        "minimatch": "10.2.5",
        "npm-package-arg": "13.0.2",
+        "open": "11.0.4",
        "pacote": "21.5.1",
      },
      "devDependencies": {
@@ -997,7 +998,7 @@
    },
    "packages/web": {
      "name": "@opencode/web",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "@astrojs/cloudflare": "12.6.3",
        "@astrojs/markdown-remark": "6.3.1",
@@ -1038,7 +1039,7 @@
    },
    "services/update": {
      "name": "@opencode/update",
-      "version": "2.0.16",
+      "version": "2.0.18",
      "dependencies": {
        "jose": "6.0.11",
        "semver": "catalog:",
@@ -1098,6 +1099,7 @@
    "@types/node": "catalog:",
    "bun-types": "1.4.2",
    "effect": "catalog:",
+    "open": "11.0.4",
    "solid-js": "catalog:",
  },
  "catalog": {
@@ -1114,9 +1116,9 @@
    "@npmcli/arborist": "9.4.0",
    "@octokit/rest": "22.0.0",
    "@openauthjs/openauth": "0.0.0-20250322224806",
-    "@opentui/core": "0.5.10",
-    "@opentui/keymap": "0.5.10",
-    "@opentui/solid": "0.5.10",
+    "@opentui/core": "0.5.12",
+    "@opentui/keymap": "0.5.12",
+    "@opentui/solid": "0.5.12",
    "@pierre/diffs": "1.2.10",
    "@playwright/test": "1.59.1",
    "@sentry/solid": "10.71.0",
@@ -2252,27 +2254,27 @@

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@@ -4340,6 +4342,8 @@

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@@ -4386,7 +4390,7 @@

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@@ -4850,7 +4854,7 @@

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+    "open": ["open@11.0.4", "", { "dependencies": { "default-browser": "^5.5.1", "define-lazy-prop": "^3.0.0", "is-in-ssh": "^1.0.0", "is-inside-container": "^1.0.0", "powershell-utils": "^0.2.1", "wsl-utils": "^1.0.0" } }, "sha512-++Zlftm0kVLPmzC06t6epuWmcRMDbI4z5P3NNX979WA/k23+NtSOynEGzsVfZwguKw2mi5umVgnBlJQMwRz4Pg=="],

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@@ -4994,6 +4998,8 @@

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+    "powershell-utils": ["powershell-utils@0.2.1", "", {}, "sha512-C+y9x90UElAddDZmV4qOx9W53B61PO7cIqWz2dQsWlwswuq4mr8NEwytdGKboYbQlGZ3awrkTeNvcZiZNHnQ8A=="],
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@@ -5814,7 +5820,7 @@

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+    "wsl-utils": ["wsl-utils@1.0.0", "", { "dependencies": { "is-wsl": "^3.1.0", "powershell-utils": "^0.1.0" } }, "sha512-Hl0ZOAs672vg+06kfujwRhoS6/jehvULrlFkuF2dRu6pHgA8U06h3xqNIqNNU1LTXPcedxByAR4GS6pwQK0mgA=="],

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@@ -5910,8 +5916,6 @@

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-
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@@ -6394,8 +6398,6 @@

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-    "chrome-launcher/is-wsl": ["is-wsl@2.2.0", "", { "dependencies": { "is-docker": "^2.0.0" } }, "sha512-fKzAra0rGJUUBwGBgNkHZuToZcn+TtXHpeCgmkMJMMYx1sQDYaCSyjJBSCa2nH1DGm7s3n1oBnohoVTBaN7Lww=="],
-
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@@ -6500,6 +6502,10 @@

    "import-in-the-middle/es-module-lexer": ["es-module-lexer@2.3.2", "", {}, "sha512-poHGpORABojJJucnV9KbOavETW8lBVnphkW77ER5/BQ5Fz7oXSoCNek7IH3vR5nRjdsEz926ibFYX8KtLQmdyw=="],

+    "is-inside-container/is-docker": ["is-docker@3.0.0", "", { "bin": { "is-docker": "cli.js" } }, "sha512-eljcgEDlEns/7AXFosB5K/2nCM4P7FQPkGc/DWLy5rmFEWvZayGrik1d9/QIY5nJ4f9YsVvBkA6kJpHn9rISdQ=="],
+
+    "is-wsl/is-docker": ["is-docker@2.2.1", "", { "bin": { "is-docker": "cli.js" } }, "sha512-F+i2BKsFrH66iaUFc0woD8sLy8getkwTwtOBjvs56Cx4CgJDeKQeqfz8wAYiSb8JOprWhHH5p77PbmYCvvUuXQ=="],
+
    "js-beautify/glob": ["glob@10.5.0", "", { "dependencies": { "foreground-child": "^3.1.0", "jackspeak": "^3.1.2", "minimatch": "^9.0.4", "minipass": "^7.1.2", "package-json-from-dist": "^1.0.0", "path-scurry": "^1.11.1" }, "bin": { "glob": "dist/esm/bin.mjs" } }, "sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg=="],

    "js-beautify/nopt": ["nopt@7.2.1", "", { "dependencies": { "abbrev": "^2.0.0" }, "bin": { "nopt": "bin/nopt.js" } }, "sha512-taM24ViiimT/XntxbPyJQzCG+p4EKOpgD3mxFwW38mGjVUrfERQOeY4EDHjdnptttfHuHQXFx+lTP08Q+mLa/w=="],
@@ -6510,8 +6516,6 @@

    "lighthouse/devtools-protocol": ["devtools-protocol@0.0.1663043", "", {}, "sha512-33aOY3ZnBP1dgZsshgaL+/XlsQleiFZgyUaDtdZkEa1nbZhVY1MoDeWjk+wxg25fU924l1ZJfoGNmjjeA/5s1w=="],

-    "lighthouse/open": ["open@8.4.2", "", { "dependencies": { "define-lazy-prop": "^2.0.0", "is-docker": "^2.1.1", "is-wsl": "^2.2.0" } }, "sha512-7x81NCL719oNbsq/3mh+hVrAWmFuEYUqrq/Iw3kUzH8ReypT9QQ0BLoJS7/G9k6N81XjW4qHWtjWwe/9eLy1EQ=="],
-
    "lighthouse/ws": ["ws@7.5.13", "", { "peerDependencies": { "bufferutil": "^4.0.1", "utf-8-validate": "^5.0.2" }, "optionalPeers": ["bufferutil", "utf-8-validate"] }, "sha512-rsKI6xDBFVf4r/x8XyChGK04QR/XHroxs/jUcoWvtEZM8TPU/X/uIY9B1CsSzYws9ZJb/6bbBu7dPhFW00CAoA=="],

    "md-to-react-email/marked": ["marked@7.0.4", "", { "bin": { "marked": "bin/marked.js" } }, "sha512-t8eP0dXRJMtMvBojtkcsA7n48BkauktUKzfkPSCq85ZMTJ0v76Rke4DYz01omYpPTUh4p/f7HePgRo3ebG8+QQ=="],
@@ -6614,8 +6618,6 @@

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-    "storybook/open": ["open@10.2.0", "", { "dependencies": { "default-browser": "^5.2.1", "define-lazy-prop": "^3.0.0", "is-inside-container": "^1.0.0", "wsl-utils": "^0.1.0" } }, "sha512-YgBpdJHPyQ2UE5x+hlSXcnejzAvD0b22U2OuAP+8OnlJT+PjWPxtgmGqKKc+RgTM63U9gN0YzrYc71R2WT/hTA=="],
-
    "storybook-solidjs-vite/semver": ["semver@7.8.1", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-rkVq3IXh+4FDGch+KwzX3aV9W3kO54GyEgpvBzSyctDA6Xtd7RJQV1xmXbeQp5v7+VzLOfVqiutSE6GICgPFvg=="],

    "storybook-solidjs-vite/vite": ["vite@7.1.11", "", { "dependencies": { "esbuild": "^0.25.0", "fdir": "^6.5.0", "picomatch": "^4.0.3", "postcss": "^8.5.6", "rollup": "^4.43.0", "tinyglobby": "^0.2.15" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "peerDependencies": { "@types/node": "^20.19.0 || >=22.12.0", "jiti": ">=1.21.0", "less": "^4.0.0", "lightningcss": "^1.21.0", "sass": "^1.70.0", "sass-embedded": "^1.70.0", "stylus": ">=0.54.8", "sugarss": "^5.0.0", "terser": "^5.16.0", "tsx": "^4.8.1", "yaml": "^2.4.2" }, "optionalPeers": ["@types/node", "jiti", "less", "lightningcss", "sass", "sass-embedded", "stylus", "sugarss", "terser", "tsx", "yaml"], "bin": { "vite": "bin/vite.js" } }, "sha512-uzcxnSDVjAopEUjljkWh8EIrg6tlzrjFUfMcR1EVsRDGwf/ccef0qQPRyOrROwhrTDaApueq+ja+KLPlzR/zdg=="],
@@ -6702,6 +6704,10 @@

    "write-file-atomic/signal-exit": ["signal-exit@4.1.0", "", {}, "sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw=="],

+    "wsl-utils/is-wsl": ["is-wsl@3.1.1", "", { "dependencies": { "is-inside-container": "^1.0.0" } }, "sha512-e6rvdUCiQCAuumZslxRJWR/Doq4VpPR82kqclvcS0efgt430SlGIk05vdCN58+VrzgtIcfNODjozVielycD4Sw=="],
+
+    "wsl-utils/powershell-utils": ["powershell-utils@0.1.0", "", {}, "sha512-dM0jVuXJPsDN6DvRpea484tCUaMiXWjuCn++HGTqUWzGDjv5tZkEZldAJ/UMlqRYGFrD/etByo4/xOuC/snX2A=="],
+
    "yaml-language-server/prettier": ["prettier@3.9.6", "", { "bin": { "prettier": "bin/prettier.cjs" } }, "sha512-OpN0zzVdiaiAhxpuuj5efpIS4sY9j7bY6uR5mnj5yPzGkdkjNKSJeUThPb60Jw29QuAZgA4o+/iB49kFiaBX6g=="],

    "yaml-language-server/request-light": ["request-light@0.5.8", "", {}, "sha512-3Zjgh+8b5fhRJBQZoy+zbVKpAQGLyka0MPgW3zruTF4dFFJ8Fqcfu9YsAvi/rvdcaTeWG3MkbZv4WKxAn/84Lg=="],
@@ -7336,8 +7342,6 @@

    "builder-util/js-yaml/argparse": ["argparse@2.0.1", "", {}, "sha512-8+9WqebbFzpX9OR+Wa6O29asIogeRMzcGtAINdpMHHyAg10f05aSFVBbcEqGf/PXw1EjAZ+q2/bEBg3DvurK3Q=="],

-    "chrome-launcher/is-wsl/is-docker": ["is-docker@2.2.1", "", { "bin": { "is-docker": "cli.js" } }, "sha512-F+i2BKsFrH66iaUFc0woD8sLy8getkwTwtOBjvs56Cx4CgJDeKQeqfz8wAYiSb8JOprWhHH5p77PbmYCvvUuXQ=="],
-
    "cliui/string-width/emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],

    "cliui/strip-ansi/ansi-regex": ["ansi-regex@5.0.1", "", {}, "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ=="],
@@ -7398,12 +7402,6 @@

    "lazystream/readable-stream/string_decoder": ["string_decoder@1.1.1", "", { "dependencies": { "safe-buffer": "~5.1.0" } }, "sha512-n/ShnvDi6FHbbVfviro+WojiFzv+s8MPMHBczVePfUpDJLwoLT0ht1l4YwBCbi8pJAveEEdnkHyPyTP/mzRfwg=="],

-    "lighthouse/open/define-lazy-prop": ["define-lazy-prop@2.0.0", "", {}, "sha512-Ds09qNh8yw3khSjiJjiUInaGX9xlqZDY7JVryGxdxV7NPeuqQfplOpQ66yJFZut3jLa5zOwkXw1g9EI2uKh4Og=="],
-
-    "lighthouse/open/is-docker": ["is-docker@2.2.1", "", { "bin": { "is-docker": "cli.js" } }, "sha512-F+i2BKsFrH66iaUFc0woD8sLy8getkwTwtOBjvs56Cx4CgJDeKQeqfz8wAYiSb8JOprWhHH5p77PbmYCvvUuXQ=="],
-
-    "lighthouse/open/is-wsl": ["is-wsl@2.2.0", "", { "dependencies": { "is-docker": "^2.0.0" } }, "sha512-fKzAra0rGJUUBwGBgNkHZuToZcn+TtXHpeCgmkMJMMYx1sQDYaCSyjJBSCa2nH1DGm7s3n1oBnohoVTBaN7Lww=="],
-
    "miniflare/sharp/@img/sharp-darwin-arm64": ["@img/sharp-darwin-arm64@0.33.5", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.0.4" }, "os": "darwin", "cpu": "arm64" }, "sha512-UT4p+iz/2H4twwAoLCqfA9UH5pI6DggwKEGuaPy7nCVQ8ZsiY5PIcrRvD1DzuY3qYL07NtIQcWnBSY/heikIFQ=="],

    "miniflare/sharp/@img/sharp-darwin-x64": ["@img/sharp-darwin-x64@0.33.5", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-x64": "1.0.4" }, "os": "darwin", "cpu": "x64" }, "sha512-fyHac4jIc1ANYGRDxtiqelIbdWkIuQaI84Mv45KvGRRxSAa7o7d1ZKAOBaYbnepLC1WqxfpimdeWfvqqSGwR2Q=="],
@@ -7674,6 +7672,10 @@

    "@astrojs/starlight/@astrojs/mdx/@astrojs/markdown-remark/shiki": ["shiki@3.23.0", "", { "dependencies": { "@shikijs/core": "3.23.0", "@shikijs/engine-javascript": "3.23.0", "@shikijs/engine-oniguruma": "3.23.0", "@shikijs/langs": "3.23.0", "@shikijs/themes": "3.23.0", "@shikijs/types": "3.23.0", "@shikijs/vscode-textmate": "^10.0.2", "@types/hast": "^3.0.4" } }, "sha512-55Dj73uq9ZXL5zyeRPzHQsK7Nbyt6Y10k5s7OjuFZGMhpp4r/rsLBH0o/0fstIzX1Lep9VxefWljK/SKCzygIA=="],

+    "@astrojs/starlight/astro/@astrojs/telemetry/is-docker": ["is-docker@3.0.0", "", { "bin": { "is-docker": "cli.js" } }, "sha512-eljcgEDlEns/7AXFosB5K/2nCM4P7FQPkGc/DWLy5rmFEWvZayGrik1d9/QIY5nJ4f9YsVvBkA6kJpHn9rISdQ=="],
+
+    "@astrojs/starlight/astro/@astrojs/telemetry/is-wsl": ["is-wsl@3.1.1", "", { "dependencies": { "is-inside-container": "^1.0.0" } }, "sha512-e6rvdUCiQCAuumZslxRJWR/Doq4VpPR82kqclvcS0efgt430SlGIk05vdCN58+VrzgtIcfNODjozVielycD4Sw=="],
+
    "@astrojs/starlight/astro/p-queue/p-timeout": ["p-timeout@6.1.4", "", {}, "sha512-MyIV3ZA/PmyBN/ud8vV9XzwTrNtR4jFrObymZYnZqMmW0zA8Z17vnT0rBgFE/TlohB+YCHqXMgZzb3Csp49vqg=="],

    "@astrojs/starlight/astro/sharp/@img/sharp-darwin-arm64": ["@img/sharp-darwin-arm64@0.33.5", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.0.4" }, "os": "darwin", "cpu": "arm64" }, "sha512-UT4p+iz/2H4twwAoLCqfA9UH5pI6DggwKEGuaPy7nCVQ8ZsiY5PIcrRvD1DzuY3qYL07NtIQcWnBSY/heikIFQ=="],
@@ -8076,6 +8078,10 @@

    "@opencode/web/@astrojs/cloudflare/wrangler/workerd": ["workerd@1.20260708.1", "", { "optionalDependencies": { "@cloudflare/workerd-darwin-64": "1.20260708.1", "@cloudflare/workerd-darwin-arm64": "1.20260708.1", "@cloudflare/workerd-linux-64": "1.20260708.1", "@cloudflare/workerd-linux-arm64": "1.20260708.1", "@cloudflare/workerd-windows-64": "1.20260708.1" }, "bin": { "workerd": "bin/workerd" } }, "sha512-WAK+Kt/VVCSldH2qSr8lx46XCJ4Q+bdlHNaFqUtOHthBEIB8C1N8HVW+VOLrxDoTCk0NGNv0zajnBeQK4JOB9w=="],

+    "@opencode/web/astro/@astrojs/telemetry/is-docker": ["is-docker@3.0.0", "", { "bin": { "is-docker": "cli.js" } }, "sha512-eljcgEDlEns/7AXFosB5K/2nCM4P7FQPkGc/DWLy5rmFEWvZayGrik1d9/QIY5nJ4f9YsVvBkA6kJpHn9rISdQ=="],
+
+    "@opencode/web/astro/@astrojs/telemetry/is-wsl": ["is-wsl@3.1.1", "", { "dependencies": { "is-inside-container": "^1.0.0" } }, "sha512-e6rvdUCiQCAuumZslxRJWR/Doq4VpPR82kqclvcS0efgt430SlGIk05vdCN58+VrzgtIcfNODjozVielycD4Sw=="],
+
    "@opencode/web/astro/js-yaml/argparse": ["argparse@2.0.1", "", {}, "sha512-8+9WqebbFzpX9OR+Wa6O29asIogeRMzcGtAINdpMHHyAg10f05aSFVBbcEqGf/PXw1EjAZ+q2/bEBg3DvurK3Q=="],

    "@opencode/web/astro/p-queue/p-timeout": ["p-timeout@6.1.4", "", {}, "sha512-MyIV3ZA/PmyBN/ud8vV9XzwTrNtR4jFrObymZYnZqMmW0zA8Z17vnT0rBgFE/TlohB+YCHqXMgZzb3Csp49vqg=="],
@@ -8216,6 +8222,10 @@

    "archiver-utils/glob/path-scurry/lru-cache": ["lru-cache@10.4.3", "", {}, "sha512-JNAzZcXrCt42VGLuYz0zfAzDfAvJWW6AfYlDBQyDV5DClI2m5sAmK+OIO7s59XfsRsWHp02jAJrRadPRGTt6SQ=="],

+    "astro-expressive-code/astro/@astrojs/telemetry/is-docker": ["is-docker@3.0.0", "", { "bin": { "is-docker": "cli.js" } }, "sha512-eljcgEDlEns/7AXFosB5K/2nCM4P7FQPkGc/DWLy5rmFEWvZayGrik1d9/QIY5nJ4f9YsVvBkA6kJpHn9rISdQ=="],
+
+    "astro-expressive-code/astro/@astrojs/telemetry/is-wsl": ["is-wsl@3.1.1", "", { "dependencies": { "is-inside-container": "^1.0.0" } }, "sha512-e6rvdUCiQCAuumZslxRJWR/Doq4VpPR82kqclvcS0efgt430SlGIk05vdCN58+VrzgtIcfNODjozVielycD4Sw=="],
+
    "astro-expressive-code/astro/js-yaml/argparse": ["argparse@2.0.1", "", {}, "sha512-8+9WqebbFzpX9OR+Wa6O29asIogeRMzcGtAINdpMHHyAg10f05aSFVBbcEqGf/PXw1EjAZ+q2/bEBg3DvurK3Q=="],

    "astro-expressive-code/astro/p-queue/p-timeout": ["p-timeout@6.1.4", "", {}, "sha512-MyIV3ZA/PmyBN/ud8vV9XzwTrNtR4jFrObymZYnZqMmW0zA8Z17vnT0rBgFE/TlohB+YCHqXMgZzb3Csp49vqg=="],
@@ -8318,6 +8328,10 @@

    "temp/rimraf/glob/minimatch": ["minimatch@3.1.5", "", { "dependencies": { "brace-expansion": "^1.1.7" } }, "sha512-VgjWUsnnT6n+NUk6eZq77zeFdpW2LWDzP6zFGrCbHXiYNul5Dzqk2HHQ5uFH2DNW5Xbp8+jVzaeNt94ssEEl4w=="],

+    "toolbeam-docs-theme/astro/@astrojs/telemetry/is-docker": ["is-docker@3.0.0", "", { "bin": { "is-docker": "cli.js" } }, "sha512-eljcgEDlEns/7AXFosB5K/2nCM4P7FQPkGc/DWLy5rmFEWvZayGrik1d9/QIY5nJ4f9YsVvBkA6kJpHn9rISdQ=="],
+
+    "toolbeam-docs-theme/astro/@astrojs/telemetry/is-wsl": ["is-wsl@3.1.1", "", { "dependencies": { "is-inside-container": "^1.0.0" } }, "sha512-e6rvdUCiQCAuumZslxRJWR/Doq4VpPR82kqclvcS0efgt430SlGIk05vdCN58+VrzgtIcfNODjozVielycD4Sw=="],
+
    "toolbeam-docs-theme/astro/js-yaml/argparse": ["argparse@2.0.1", "", {}, "sha512-8+9WqebbFzpX9OR+Wa6O29asIogeRMzcGtAINdpMHHyAg10f05aSFVBbcEqGf/PXw1EjAZ+q2/bEBg3DvurK3Q=="],

    "toolbeam-docs-theme/astro/p-queue/p-timeout": ["p-timeout@6.1.4", "", {}, "sha512-MyIV3ZA/PmyBN/ud8vV9XzwTrNtR4jFrObymZYnZqMmW0zA8Z17vnT0rBgFE/TlohB+YCHqXMgZzb3Csp49vqg=="],
@@ -2,11 +2,11 @@
  "nodes": {
    "nixpkgs": {
      "locked": {
-        "lastModified": 1776683584,
-        "narHash": "sha256-NuTLMrr10Tng72hurYG8jYQ4XKK8wnpJmOGcPiis96g=",
+        "lastModified": 1790510107,
+        "narHash": "sha256-EVMNYv7hYDDD9TGVT/hIyTYgpiXA8y3m5xIEIxuGNU0=",
        "owner": "NixOS",
        "repo": "nixpkgs",
-        "rev": "9dd5558b06dbdacbf635a3dd36dce1b1a7ee3a89",
+        "rev": "3181085bfd08663b6b9e60bc7a8395c2aaa741bd",
        "type": "github"
      },
      "original": {
@@ -1,8 +1,8 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-+Clo0VPDdruHSoBNvV/wKAM8iR6HJPtB00oa8yl9ujU=",
-    "aarch64-linux": "sha256-4wU5v36GTXjwyt5ls4FH+5G43Ujd+dKVSJR21w3lhbA=",
-    "aarch64-darwin": "sha256-pThjoD6baddQ6biy7k1ByXwGwLAeWe/+w0tcYmt1uWs=",
-    "x86_64-darwin": "sha256-bCBl63CqBiqilb+YdaOLBYYZx/yf47c1aqgDOkgdegg="
+    "x86_64-linux": "sha256-7DgxTpKv6ITKTom0mhlJNPQfdEjtEHK5P8uyCr26HZw=",
+    "aarch64-linux": "sha256-PJxW1Ibfx6oS1neWPSHqzP1Pm1HT9my1TrrHmOb6/no=",
+    "aarch64-darwin": "sha256-VIme5VHfM8JxNiDSOykkr5FytghDLI0FxkhiOXUSyQw=",
+    "x86_64-darwin": "sha256-rQ/j0QkR1vxAq4jgUbr0nY4RDyiLTJqN8q1AfoiEqVQ="
  }
 }
@@ -2,7 +2,7 @@
  "$schema": "https://json.schemastore.org/package.json",
  "name": "opencode",
  "description": "AI-powered development tool",
-  "version": "2.0.16",
+  "version": "2.0.18",
  "private": true,
  "type": "module",
  "packageManager": "bun@1.4.2",
@@ -52,9 +52,9 @@
      "@octokit/rest": "22.0.0",
      "@hono/standard-validator": "0.2.0",
      "@hono/zod-validator": "0.4.2",
-      "@opentui/core": "0.5.10",
-      "@opentui/keymap": "0.5.10",
-      "@opentui/solid": "0.5.10",
+      "@opentui/core": "0.5.12",
+      "@opentui/keymap": "0.5.12",
+      "@opentui/solid": "0.5.12",
      "@tanstack/solid-virtual": "3.13.37",
      "@shikijs/stream": "4.4.3",
      "@standard-schema/spec": "1.1.0",
@@ -162,6 +162,7 @@
    "@types/node": "catalog:",
    "bun-types": "1.4.2",
    "effect": "catalog:",
+    "open": "11.0.4",
    "solid-js": "catalog:"
  },
  "patchedDependencies": {
@@ -10,11 +10,11 @@

 ## Conventions

-Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `Message.media(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, and `LLM.generateObject`. Use `LLMRequest.update(...)` when deriving canonical request data; do not add a duplicate `LLM.updateRequest(...)` path. Two ways to construct the same thing is one too many.
+Per-type constructors live on the type, not as top-level re-exports. Use `Message.system(...)`, `Message.user(...)`, `Message.assistant(...)`, `Message.tool(...)`, `Message.media(...)`, `LanguageModel.make(...)`, `ToolDefinition.make(...)`, `ToolCallPart.make(...)`, `ToolResultPart.make(...)`, `ToolChoice.make(...)`, `ToolChoice.named(...)`, `SystemPart.make(...)`, and `GenerationOptions.make(...)` directly. The top-level `LLM` namespace is reserved for request-shaped call APIs: `LLM.request`, `LLM.generate`, `LLM.stream`, and `LLM.generateObject`. `LLM.generate`/`LLM.stream` and Promise `ai.llm.generate`/`ai.llm.stream` accept ergonomic input or an `LLMRequest`; both paths use the same canonical request. Core still builds, logs, replays, and updates that durable `LLMRequest` boundary. Use `LLMRequest.update(...)` when deriving canonical request data; do not add a duplicate `LLM.updateRequest(...)` path.

-Modality namespaces mirror `LLM` exactly: `Image.request`, `Image.generate`, `Image.stream` (later `Video`, `Speech`, `Transcription`). Common request fields (`images`, `mask`, `n`, `size`, `aspectRatio`, `seed`, `format`) lower natively or fail with a typed `AIError`; provider-native controls always live under `providerOptions`, never under a modality-specific `options` key.
+Modality namespaces mirror `LLM` exactly: `Image.request`, `Image.generate`, `Image.stream`, and the same for `Video`, `Speech`, and `Transcription`. Common request fields (`images`, `mask`, `n`, `size`, `aspectRatio`, `seed`, `format`) lower natively or fail with a typed `AIError`; provider-native controls always live under `providerOptions`, never under a modality-specific `options` key.

-Media payloads are always `Media.Asset` (`src/media.ts`). Construct them with `Media.bytes`, `Media.base64`, `Media.url`, `Media.ref`, `Media.fromDataUrl`, or `Media.file`; never introduce a parallel `data: string | Uint8Array` shape. `MediaPart.media`, `ImageRequest.images`/`mask`, `ImageResponse.images`, and the `media` `LLMEvent` all share it. Protocols branch on `asset.source.type` and `asset.kind` and use `ProviderShared.inlineMedia` / `requireInlineMedia` / `mediaUrl` / `MediaInput.refID` rather than re-deriving base64 or URL handling.
+Media payloads are always `Media.Asset` (`src/media.ts`). Construct them with `Media.bytes`, `Media.base64`, `Media.url`, `Media.ref`, `Media.fromDataUrl`, or `Media.file`; never introduce a parallel `data: string | Uint8Array` shape. `MediaPart.media`, `ImageRequest.images`/`mask`, `ImageResponse.images`, and the `media` `LLMEvent` all share it. Protocols branch on `asset.source.type` and `asset.kind` and use `ProviderShared.requireInlineMedia` / `inlineRequired` / `mediaUrl` / `mediaReference` and `MediaInput.inlineBytes` / `refID` rather than re-deriving base64 or URL handling.

 `schema/messages.ts → media.ts → route/executor-service.ts` is an accepted runtime dependency from the schema layer on the executor service tag: `Media.Asset.bytes()` must be able to download `url` sources, and the tag lives in that leaf module precisely so the schema barrel never imports the executor implementation (which imports the schema barrel back). Do not move the tag into `route/executor.ts` or import `route/executor.ts` from `src/schema/*` or `src/media.ts`.

@@ -98,11 +98,11 @@ When a provider supports multiple physical transports, selection remains executi

 Media does not fit the SSE-frames-to-event-state-machine LLM route. `MediaRoute.inline(...)` / `queued(...)` / `stream(...)` (`src/route/media.ts`) compose a `MediaProtocol` kind with `Endpoint` and `Auth` and own the transport plumbing: `http` option merging, URL/query rendering, auth headers, JSON vs multipart encoding, and handing the response back to the protocol. `MediaProtocol.inline` (`src/route/media-protocol.ts`) is `body.from(request)` plus `response.decode(response, context)`; each protocol declares `const route = MediaProtocol.identity({ id, name, provider })` once and decodes through `route.decodeJson` / `route.text` / `route.decodeStarted` so decode failures retain the raw body and HTTP context, raising `route.unsupported(operation, message)` for requests it cannot lower, and passes `route` as the first argument to `MediaProtocol.inline` / `queued` / `stream`. `Generation` (`src/generation.ts`) is the provider-neutral handle for a queued generation over a `GenerationRoute` (`status`, `result`, `cancel`). Image protocol files follow the same section order as LLM protocols and declare unsupported common fields once through the protocol's `unsupported` list.

-`MediaProtocol.queued` is the submit-then-poll kind every video route uses: `start` (body + decode into `{ token, snapshot }`), `status`, `result`, and optional `cancel`, each addressed by a route-owned `token` whose `Schema.Codec` makes it serializable. `MediaRoute.inline` and `MediaRoute.queued` compose the two kinds with `Endpoint` and `Auth`; the queued route decodes the token once at the boundary (`start` output or `resume` input) and closes over it in a token-free `GenerationRoute` (`status`/`result`/`cancel` are plain Effects), so `Generation` never sees the token's shape and only carries the encoded JSON for persistence. Polls reuse the route's auth and deployment headers plus the request's `http` overlay after `start`, and resolve relative paths against the route base URL (provider-issued absolute URLs such as fal's `status_url` pass through). `result` is always its own GET even when the provider returns output inside the status document, so `Generation.await` behaves the same after `start` and after `resume`. `PollContext.auth` carries only what `Auth` added or changed so protocols can hand download credentials to output assets as transient `Media.Asset.headers` (Veo) — never part of `source` or JSON. Status strings map through a per-protocol `STATUS` table via `MediaProtocol.status`; terminal generations without output fail through `output.ended` / `output.contentPolicy` with the provider document on `reason.body`. `GenerationAwaitOptions` (`AwaitOptions` in `src/generation.ts`, `{ poll?: Poll }`) is the one options type for `await`, `events`, `Video.generate`, and `Video.stream`.
+`MediaProtocol.queued` is the submit-then-poll kind every video route uses: `start` (body + decode into `{ token, snapshot }`), `status`, `result`, and optional `cancel` (with `activeOnly` when the provider's cancel endpoint deletes finished work, as Runway's does: the route refreshes status first and skips terminal generations), each addressed by a route-owned `token` whose `Schema.Codec` makes it serializable. `MediaRoute.inline` and `MediaRoute.queued` compose the two kinds with `Endpoint` and `Auth`; the queued route decodes the token once at the boundary (`start` output or `resume` input) and closes over it in a token-free `GenerationRoute` (`status`/`result`/`cancel` are plain Effects), so `Generation` never sees the token's shape and only carries the encoded JSON for persistence. Polls reuse the route's auth and deployment headers plus the request's `http` overlay after `start`, and resolve relative paths against the route base URL (provider-issued absolute URLs such as fal's `status_url` pass through). `result` is always its own GET even when the provider returns output inside the status document, so `Generation.await` behaves the same after `start` and after `resume`. `PollContext.auth` carries only what `Auth` added or changed so protocols can hand download credentials to output assets as transient `Media.Asset.headers` (Veo) — never part of `source` or JSON. Status strings map through a per-protocol `STATUS` table via `MediaProtocol.status`; terminal generations without output fail through `output.ended` / `output.contentPolicy` with the provider document on `reason.body`; a `failed` generation maps the provider's error code through a per-protocol `FAILURE` table via `MediaProtocol.failure` so rejected inputs are not reported as retryable `ProviderInternal`. `GenerationAwaitOptions` (`AwaitOptions` in `src/generation.ts`, `{ poll?: Poll }`) is the one options type for `await`, `events`, `Video.generate`, and `Video.stream`.

 `MediaProtocol.stream` is the incremental kind every speech route uses, with the same discipline as LLM protocols. `MediaRoute.stream` submits the caller's request as `MediaProtocol.Addressed<Request>` (`{ ...request, mode }`, `mode: "generate" | "stream"`), so one provider stays one protocol: `body.from`, the endpoint path, and `frames` read `request.mode` to pick the body, path, and framing. `frames(bytes, context)` returns frames — `Framing.sse`, `Framing.lines`, `Framing.document` (a single-document response shaped like a streamed record), or the raw `bytes` for chunked audio. `initial()` is fresh per-response parser state; `step` folds each frame into it and emits modality events; `finish(state, context)` runs once after the last frame with the request, body, and observed `http` (header-only usage lives there) and emits exactly one terminal event or fails with `route.incomplete()`. Keep parser state to real accumulators and derive anything the request or body determines in `finish`. `generate` runs the same stream and folds it with the modality's `collect`. Request-derived URL parameters go on the body's `query` (array values repeat the parameter), applied before route and caller `http.query`. Decode frames with `route.decodeFrame` and raise stream-time failures with `route.frameError` (the frame stays on `reason.body`); protocols never thread HTTP context, because the route fills `reason.http` on stream errors that lack it. Speech protocols share `protocols/utils/speech-stream.ts` for deltas, timestamps, voice ids, PCM and container descriptions, and the terminal asset.

-Transcription uses all three kinds (OpenAI and Gemini stream, Deepgram is inline, AssemblyAI is queued): every route carries its `kind` and `TranscriptionClient` dispatches on it. `ImageRoute` is the same union; both clients dispatch through `MediaRoute.dispatch` and models compose through `composeAnyRoute`, and fal queue protocols come from `protocols/utils/fal-queue.ts`. Bodies are `json`, `multipart`, or `binary` (a raw upload), and a queued protocol that must upload media before submitting implements `start.prepare` (`MediaProtocol.Prepare`; AssemblyAI `/v2/upload`).
+Every modality route is the inline | stream | queued union (transcription uses all three: OpenAI and Gemini stream, Deepgram and ElevenLabs are inline, AssemblyAI is queued), every client is `MediaClient.make(Service, { modality, responseEvents })` (`src/media-client.ts`), which dispatches on the route's `kind`, and every model composes through `composeRoute`. fal queue protocols come from `protocols/utils/fal-queue.ts`, bodies are `json`, `multipart`, or `binary` (a raw upload), and a queued protocol that must upload media before submitting implements `start.prepare` (`MediaProtocol.Prepare`; AssemblyAI `/v2/upload`).

 ### URL Construction

@@ -112,7 +112,7 @@ For providers where the URL is derived from typed inputs (Azure resource name, B

 ### Provider Facades

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

 ```ts
 const openai = OpenAI.configure({ apiKey, baseURL })
@@ -275,6 +275,7 @@ Use this order for every protocol module:
 ### Rules

 - Keep protocol files focused on the protocol. Move provider-specific projection, signing, media normalization, or other bulky transformations into `src/protocols/utils/*`.
+- Send `tool.inputSchema` as given. `prepareRequest` applies the tool schema rules (`ToolSchemaProjection.tools`) once per request, including tools in namespaces. A protocol whose API needs a model family's rules for every model declares `sanitizer` instead of transforming schemas itself.
 - Use `Effect.fn("Provider.fromRequest")` for request body construction entrypoints. Use `Effect.fn(...)` for event handlers that yield effects; keep purely synchronous handlers as plain functions returning a `StepResult` that the dispatcher lifts via `Effect.succeed(...)`.
 - Parser state owns terminal information. The state machine records finish reason, usage, and pending tool calls; emit one terminal `finish` event (or `provider-error`) for each completed response. If a provider splits reason and usage across events, merge them in parser state before flushing.
 - Emit exactly one terminal `finish` event for a completed response, normally after a matching `step-finish`. Use `stream.terminal` to stop reading when the provider has a completion sentinel; use `stream.onHalt` when the final event must be flushed after the framed stream ends.
@@ -9,15 +9,13 @@ import { OpenAI } from "@opencode/ai/providers"

 const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY })

-const request = LLM.request({
-  model: openai.responses("gpt-4o-mini"), // `.chat(...)` selects the Chat Completions API instead
-  system: "You are concise.",
-  prompt: "Say hello in one short sentence.",
-  generation: { maxTokens: 40 },
-})
-
 const program = Effect.gen(function* () {
-  const response = yield* LLM.generate(request)
+  const response = yield* LLM.generate({
+    model: openai.responses("gpt-4o-mini"), // `.chat(...)` selects the Chat Completions API instead
+    system: "You are concise.",
+    prompt: "Say hello in one short sentence.",
+    generation: { maxTokens: 40 },
+  })
  console.log(response.text)
 })

@@ -25,7 +23,8 @@ const program = Effect.gen(function* () {
 await Effect.runPromise(program.pipe(Effect.provide(AIClient.layer)))
 ```

-Run `LLM.stream(request)` instead of `generate` when you want incremental `LLMEvent`s. The event stream is provider-neutral — same shape across OpenAI Chat, OpenAI Responses,
+Run `LLM.stream(...)` instead of `generate` when you want incremental `LLMEvent`s. Both accept input or a prebuilt
+`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.

 The same configured facade names image, video, speech, and transcription models. `Image.generate` resolves the
@@ -72,10 +71,11 @@ helpers; `ai.file` and `ai.write` load `node:fs/promises` on first use, so no Ef
 import { AI } from "@opencode/ai/promise"

 const ai = AI.make()
-const text = await ai.llm.generate({ model: openai.responses("gpt-4o-mini"), prompt: "Say hello." })
+const input = { model: openai.responses("gpt-4o-mini"), prompt: "Say hello." }
+const text = await ai.llm.generate(input)
 const generated = await ai.image.generate({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" })
 await ai.write(generated.image, "./lighthouse.png") // also ai.file(path), ai.bytes(asset), ai.base64(asset), ai.materialize(asset)
-for await (const event of ai.llm.stream({ model: openai.responses("gpt-4o-mini"), prompt: "Stream hello." })) {
+for await (const event of ai.llm.stream(ai.llm.request(input))) {
  // LLMEvent
 }
 await ai.dispose()
@@ -475,18 +475,18 @@ const program = Effect.gen(function* () {
 Common fields are portable in shape, not in support. Unsupported fields fail with a typed `AIError` before any network
 call rather than being dropped, so check this table before swapping only the `model`:

-| Provider              | `n` | `size`    | `aspectRatio` | `seed` | `format` | `images`                  | `mask`              |
-| --------------------- | --- | --------- | ------------- | ------ | -------- | ------------------------- | ------------------- |
-| OpenAI                | ✓¹  | ✓         | ✗             | ✗      | ✓        | ✓                         | ✓                   |
-| Google (Gemini)       | 1   | ✗         | ✓             | ✓      | ✗        | ✓ (no public URLs)        | ✗                   |
-| xAI                   | ✓   | ✗         | ✓             | ✗      | ✗        | ✓                         | ✗                   |
-| Z.ai                  | ✗   | ✓         | ✗             | ✗      | ✗        | ✗                         | ✗                   |
-| Meta                  | ✓   | ✓ (hint)  | ✗             | ✗      | ✓        | ✓                         | ✗                   |
-| Black Forest Labs     | 1   | per model | per model     | ✓      | ✓        | per model (1–8)           | `flux-pro-1.0-fill` |
-| fal                   | ✓   | per model | per model     | ✓      | ✓        | 1 (several on `/edit`)    | ✓                   |
-| Replicate             | ✗   | ✗         | ✗             | ✗      | ✗        | ✗ (use `providerOptions`) | ✗                   |
-| Stability `image`     | 1   | ✗         | ✓             | ✓      | ✓        | 1 (not on `core`)         | ✗                   |
-| Stability `upscale()` | ✗   | ✗         | ✗             | ✓      | ✓        | exactly 1 (required)      | ✗                   |
+| Provider              | `n` | `size`    | `aspectRatio` | `seed` | `format` | `images`                         | `mask`              |
+| --------------------- | --- | --------- | ------------- | ------ | -------- | -------------------------------- | ------------------- |
+| OpenAI                | ✓¹  | ✓         | ✗             | ✗      | ✓        | ✓                                | ✓                   |
+| Google (Gemini)       | 1   | ✗         | ✓             | ✓      | ✗        | ✓ (no public URLs)               | ✗                   |
+| xAI                   | ✓   | ✗         | ✓             | ✗      | ✗        | ✓                                | ✗                   |
+| Z.ai                  | ✗   | ✓         | ✗             | ✗      | ✗        | ✗                                | ✗                   |
+| Meta                  | ✓   | ✓ (hint)  | ✗             | ✗      | ✓        | ✓                                | ✗                   |
+| Black Forest Labs     | 1   | per model | per model     | ✓      | ✓        | per model (1–8)                  | `flux-pro-1.0-fill` |
+| fal                   | ✓   | per model | per model     | ✓      | ✓        | 1 (several on `/edit`, `/multi`) | ✓                   |
+| Replicate             | ✗   | ✗         | ✗             | ✗      | ✗        | ✗ (use `providerOptions`)        | ✗                   |
+| Stability `image`     | 1   | ✗         | ✓             | ✓      | ✓        | 1 (not on `core`)                | ✗                   |
+| Stability `upscale()` | ✗   | ✗         | ✗             | ✓      | ✓        | exactly 1 (required)             | ✗                   |

 ✓ lowers natively; ✗ fails whenever the field is set (including `n: 1`); `1` means `n > 1` fails. ¹ `Image.stream` on OpenAI generates one image. fal
 rejects `size` and `aspectRatio` together; which one a fal or BFL model takes depends on the model.
@@ -621,8 +621,7 @@ persist the bytes promptly if they must remain available.
 ### Partial images

 OpenAI's GPT image models stream previews. `Image.stream` sends `stream: true` with `partialImages` (0–3, default 2)
-and emits `image-partial` events before each final `image`; `Image.generate` keeps the plain JSON request.
-`dall-e-*` models do not stream and fail typed:
+and emits `image-partial` events before each final `image`; `Image.generate` keeps the plain JSON request:

 ```ts
 import { Stream } from "effect"
@@ -699,7 +698,7 @@ const program = Effect.gen(function* () {
 })
 ```

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

 ## Video generation

@@ -753,7 +752,10 @@ const events = Video.stream({ model: Runway.configure({ apiKey }).video("gen4.5"

 Status polls, result fetches, cancels, and asset downloads all run through the same request executor with the route's
 auth. `Generation.await` and `Generation.events` fail with a
-`Timeout` reason when `poll.timeout` (default 10 minutes) elapses. Failed,
+`Timeout` reason when `poll.timeout` (default 10 minutes) elapses. Status polls and result fetches retry transient
+failures (rate limits, provider 5xx, network errors) with backoff that honors `retry-after`, always within
+`poll.timeout`; submits and cancels never retry. Interrupting a wait (or aborting its `signal`) does not cancel the
+provider job, which keeps running and billing: call `cancel()` to stop it. Failed,
 cancelled, and expired generations fail typed with the provider's terminal document on `reason.body`; moderation
 outcomes (Veo `raiMediaFilteredReasons`, xAI `respect_moderation`, Runway `SAFETY.*` codes) surface as `notices` when
 a video is still returned and as a `ContentPolicy` reason when nothing is.
@@ -774,7 +776,9 @@ Provider notes:
 The promise client exposes the same surface: `ai.video.start(...)` resolves to a handle with `await`, `events`,
 `result`, `refresh`, `cancel`, and `token`; `ai.video.generate`, `ai.video.resume(model, token)`, and
 `ai.video.stream` mirror the Effect API. The handle's `status` and `progress` are a snapshot from when it was
-created; `refresh()` resolves to a new handle.
+created; `refresh()` resolves to a new handle. Every promise method and stream accepts `{ signal }`: like `fetch`,
+aborting rejects the Promise or throws from the `for await` loop with `signal.reason` (an `AbortError` `DOMException`
+unless `abort(reason)` passed one), while `break` stops a stream without throwing.

 ```ts
 import { ai } from "@opencode/ai/promise"
@@ -840,9 +844,10 @@ Provider notes:
 - **OpenAI** streams over SSE (`stream_format: "sse"`), which is also the only place it reports token usage; `tts-1`
  and `tts-1-hd` do not support SSE and stream the raw audio body instead. `pcm` is 24 kHz 16-bit mono. `language`
  and `timestamps` are not supported.
- **Gemini TTS** returns raw 16-bit PCM only (`audio/L16;codec=pcm;rate=24000`), so any `format` other than `pcm`
-  fails typed; wrap the samples yourself. Style is directed in the text, so `instructions` and `speed` fail typed.
-  Only `gemini-3.1-flash-tts-preview` and later support streaming. Two-speaker audio goes through
+- **Gemini TTS** returns the provider's default output: WAV for Gemini 3.8 TTS `generate`, raw 16-bit PCM
+  (`audio/L16;codec=pcm;rate=24000`) otherwise. `pcm` is the only explicit `format` it accepts, and it fails typed on
+  Gemini 3.8 `generate`; the route never wraps PCM as WAV. Style is directed in the text, so `instructions` and
+  `speed` fail typed. Only `gemini-3.1-flash-tts-preview` and later support streaming. Two-speaker audio goes through
  `providerOptions.speechConfig.multiSpeakerVoiceConfig`.
 - **ElevenLabs** requires `voice` (the path voice id) and authenticates with `xi-api-key`. `format` maps to the
  `output_format` query parameter (`mp3_44100_128`, `pcm_24000`, `wav_24000`, `opus_48000_64`);
@@ -871,11 +876,12 @@ for await (const event of ai.speech.stream({ model, text: "Hello from OpenCode."
 ## Transcription

 Transcription (speech-to-text) is the one modality whose providers use every route kind: OpenAI and Gemini stream,
-Deepgram answers inline, and AssemblyAI is queued. `Transcription.generate` and `Transcription.stream` work on all of
-them; `Transcription.start` / `resume` return a `Generation` on queued routes and fail with `UnsupportedOperation`
-elsewhere. Models come from `.transcription(...)` selectors on the `OpenAI`, `Google`, `Deepgram`, and `AssemblyAI`
-facades. Common fields (`language`, `prompt`, `timestamps: "none" | "segment" | "word"`, `diarize`, `speakers`) lower
-natively or fail with a typed `AIError` before any network call; a route may return more than asked.
+Deepgram and ElevenLabs answer inline, and AssemblyAI is queued. `Transcription.generate` and `Transcription.stream`
+work on all of them; `Transcription.start` / `resume` return a `Generation` on queued routes and fail with
+`UnsupportedOperation` elsewhere. Models come from `.transcription(...)` selectors on the `OpenAI`, `Google`,
+`Deepgram`, `ElevenLabs`, and `AssemblyAI` facades. Common fields (`language`, `prompt`,
+`timestamps: "none" | "segment" | "word"`, `diarize`, `speakers`) lower natively or fail with a typed `AIError` before
+any network call; a route may return more than asked.

 ```ts
 import { Console, Effect, Stream } from "effect"
@@ -887,7 +893,7 @@ const openai = OpenAI.configure({ apiKey: process.env.OPENAI_API_KEY })
 const program = Effect.gen(function* () {
  const audio = yield* Media.file("./call.mp3")

-  // Speaker-labelled segments; labels are provider-native strings ("A", "0", "spk:0").
+  // Speaker-labelled segments; labels are provider-native strings ("A", "0", "spk:0", "speaker_0").
  const response = yield* Transcription.generate({
    model: Deepgram.configure({ apiKey }).transcription("nova-3"),
    audio,
@@ -897,7 +903,7 @@ const program = Effect.gen(function* () {
  response.text // "Hello from OpenCode."
  response.segments // [{ text, startSeconds, endSeconds, speaker: "0" }]
  response.words // [{ text, startSeconds, endSeconds, speaker, confidence }]
-  response.language // the provider's own value, lowercased ("en", "english", "en_us")
+  response.language // the provider's own value, lowercased ("en", "eng", "english", "en_us")

  // Text deltas as the model transcribes, then one finish carrying the whole transcript.
  yield* Transcription.stream({ model: openai.transcription("gpt-4o-mini-transcribe"), audio }).pipe(
@@ -921,7 +927,12 @@ Provider notes:
 - **OpenAI** takes inline audio only; `diarize` needs `gpt-4o-transcribe-diarize`, timestamps need `whisper-1`, and `whisper-1` does not stream.
 - **Gemini** needs a transcribe model (`gemini-3.5-transcribe`); `prompt` and `speakers` fail typed.
 - **Deepgram** detects the language unless `language` is set; vocabulary goes in `providerOptions.keyterm`.
- **AssemblyAI** uploads inline audio before submitting and is the only route that accepts `speakers`.
+- **ElevenLabs** (`scribe_v2`) uploads inline audio as the multipart `file` and sends a URL as `source_url`. Words
+  always carry timestamps, and segments are speaker turns, so `diarize`, `timestamps: "segment"`, or `speakers` turns
+  on diarization. `speakers` is an upper bound (`num_speakers`); `prompt` fails typed (vocabulary goes in
+  `providerOptions.keyterms`), as do webhook delivery and per-channel output (`use_multi_channel` without
+  `multichannel_output_style: "combined"`).
+- **AssemblyAI** uploads inline audio before submitting and treats `speakers` as the exact speaker count.

 The promise client mirrors the Effect API:

@@ -936,7 +947,7 @@ const transcript = await generation.await({ poll: { interval: 3_000 } })
 ## Public API

 - **`LLM.request({...})`** — build a provider-neutral `LLMRequest`. Accepts ergonomic inputs (`system: string`, `prompt: string`) that normalize into the canonical Schema classes.
- **`LLM.generate` / `LLM.stream`** — re-exported from `LLMClient` for one-import use.
+- **`LLM.generate` / `LLM.stream`** — run direct input or an `LLMRequest` through `LLMClient` for one-import use.
 - **`Message.user(...)` / `Message.assistant(...)` / `Message.tool(...)`** — message constructors from the canonical schema model.
 - **`LanguageModel.make(...)` / `ToolCallPart.make(...)` / `ToolResultPart.make(...)` / `ToolDefinition.make(...)`** — model and tool-related constructors from the canonical schema model.
 - **`LLMEvent.is.*`** — typed guards (`is.textDelta`, `is.toolCall`, `is.finish`, …) for filtering streams.
@@ -944,6 +955,7 @@ const transcript = await generation.await({ poll: { interval: 3_000 } })
 - **`ImageClient`** — Effect service and layer for image execution, parallel to `LLMClient`.
 - **`Media`** — the shared asset type (`Media.Asset`, `Media.Source`) and constructors used by messages, tool results, and media requests.
 - **`Generation`** — provider-neutral handle for an in-flight media generation (`await`, `refresh`, `cancel`, `events`) used by queued media routes.
+- **`Video.request` / `generate` / `stream` / `start` / `resume`** — queued video generation through a provider-neutral request; `VideoClient` is its Effect service and layer.
 - **`Speech.request` / `Speech.generate` / `Speech.stream`** — text-to-speech through a provider-neutral request; `SpeechClient` is its Effect service and layer.
 - **`Transcription.request` / `generate` / `stream` / `start` / `resume`** — speech-to-text over inline, streaming, and queued routes; `TranscriptionClient` is its Effect service and layer.
 - **`AIClient.layer` / `AIClient.layerWith(executor)`** — every modality client plus the request executor in one layer.
@@ -40,7 +40,7 @@ The design below is derived from a survey of the raw provider APIs (OpenAI, Gemi

 ### Model selection

-A model value is built as `OpenAI.configure({ apiKey }).responses("gpt-5")` or `.image("gpt-image-2")`: `configure` fixes credentials, endpoint, and defaults; the selector fixes which of the provider's APIs to hit and binds the typed `providerOptions` generic. Media follows the same shape with one selector per modality — `openai.image(id)` today, `.video(id)` / `.speech(id)` / `.transcription(id)` as those modalities land — mirroring `openai.responses(id)`. `Image.request` accepts `ImageModel` only, exactly as `LLM.request` accepts `LanguageModel`.
+A model value is built as `OpenAI.configure({ apiKey }).responses("gpt-5")` or `.image("gpt-image-2")`: `configure` fixes credentials, endpoint, and defaults; the selector fixes which of the provider's APIs to hit and binds the typed `providerOptions` generic. Media follows the same shape with one selector per modality — `.image(id)`, `.video(id)`, `.speech(id)`, `.transcription(id)` on the facades that offer each — mirroring `openai.responses(id)`. `Image.request` accepts `ImageModel` only, exactly as `LLM.request` accepts `LanguageModel`.

 ```ts
 import { OpenAI, Google } from "@opencode/ai/providers"
@@ -135,12 +135,12 @@ Effect.gen(function* () {
 })
 ```

-`size` and `aspectRatio` are not interchangeable; each route rejects fields it cannot lower — see the README's Image
-portability matrix.
+`size` and `aspectRatio` are not interchangeable; each route rejects fields it cannot lower — see the portability table
+in the README's Image generation section.

 Editing is not a separate function; `images`/`mask` on the request select the edit path in the route (OpenAI `/images/edits`, Gemini multimodal parts, xAI `/images/edits`). Routes that cannot honor `mask` fail with `Unsupported`.

-`ImageRoute` is the inline | stream | queued union, dispatched on `route.kind`. `Image.stream` on a streaming route emits `image-partial` previews before each `image`; on a queued route it emits `generation-queued` / `generation-progress` observations, then the result's `image` and `finish` events.
+`ImageRoute` is the inline | stream | queued union, dispatched on `route.kind`, like every modality route. `Image.stream` on a streaming route emits `image-partial` previews before each `image`; on a queued route it emits `generation-queued` / `generation-progress` observations, then the result's `image` and `finish` events.

 #### Video

@@ -166,8 +166,8 @@ Effect.gen(function* () {

  // Simple: wait for it.
  const response = yield* Video.generate(request, { poll: { interval: "10 seconds", timeout: "10 minutes" } })
-  response.video                                     // Media.Asset: url with expiresAt (+ transient `headers` for Veo downloads)
-  response.usage                                     // credits on Runway; the other three report none
+  response.video                                     // Media.Asset: url (expiresAt on Veo and Runway; transient `headers` for Veo downloads)
+  response.usage                                     // credits on Runway; the other three report none (xAI's usage.cost_in_usd_ticks is not decoded)
  response.notices                                   // Veo raiMediaFilteredReasons → filtered, xAI respect_moderation → moderated
  yield* response.video.materialize()                // pull bytes before the URL expires

@@ -175,7 +175,7 @@ Effect.gen(function* () {
  const generation = yield* Video.start(request)     // Generation<VideoResponse>
  generation.id; generation.status; generation.progress; generation.position; generation.token
  yield* generation.await({ poll })                  // VideoResponse
-  yield* generation.cancel()                         // fal PUT cancel_url, Runway DELETE /tasks/{id}; no-op for Veo and xAI
+  yield* generation.cancel()                         // fal PUT cancel_url, Runway DELETE /tasks/{id}; Veo and xAI succeed without a request

  // Resume from another process. The token is validated against the route's codec and refreshed once. It carries no
  // route identity, so persist the provider and model ID alongside it: `resume` needs the model.
@@ -188,10 +188,11 @@ Effect.gen(function* () {

 Tokens are route-owned JSON: Veo `{ operation }`, xAI `{ requestID }`, Runway `{ taskID }`, fal
 `{ requestID, statusURL, responseURL, cancelURL }` (fal's follow-up URLs are authoritative and absolute). Common-field
-lowering per provider: Veo takes inline media only and rejects `audio: false` and `n > 1`; xAI rejects `seed` and
-`negativePrompt` and routes a `video` input to edits or (`providerOptions.mode: "extend"`) extensions; fal rejects
-`durationSeconds`, `references`, and `frames.last` because the field names and enums differ per model; Runway passes
-`aspectRatio` through as its pixel `ratio` and rejects `n`.
+lowering per provider: Veo takes inline media only, rejects `audio: false` and `n > 1`, and requires `frames.first`
+when `frames.last` is set; xAI rejects `n`, `seed`, and `negativePrompt` and routes a `video` input to edits or
+(`providerOptions.mode: "extend"`) extensions; fal rejects `n`, plus `durationSeconds`, `references`, and `frames.last`
+because the field names and enums differ per model; Runway passes `aspectRatio` through as its pixel `ratio` and
+rejects `n`.

 Deferred: `Video.complete(model, token, webhook)` (finish from a webhook payload without polling) and provider poll
 hints (none of the four providers emit one). Later providers: Luma, Kling, MiniMax, Replicate.
@@ -215,7 +216,7 @@ const request = Speech.request({
 })

 const response = yield* Speech.generate(request)   // SpeechResponse: audio: Media.Asset, timestamps?, usage?, providerMetadata?
-yield* Speech.stream(request)                      // Stream<SpeechEvent>: audio-delta { chunk } | timestamps { items } | finish { audio, usage? }
+yield* Speech.stream(request)                      // Stream<SpeechEvent>: generation-queued | generation-progress | audio-delta { chunk } | timestamps { items } | finish { audio, usage? }
 ```

 Execution is `MediaProtocol.stream` for every provider: one request whose body is framed and folded by a `step`
@@ -241,10 +242,12 @@ name→id resolution. Multi-speaker (Gemini `speechConfig.multiSpeakerVoiceConfi
 `opus_48000_64`, Cartesia `{ container, encoding, sample_rate }`, Deepgram `encoding`+`container`) and declares the
 asset's media type rather than sniffing, because headerless PCM can look like an MPEG frame sync. Headerless PCM
 always carries `info.encoding`, `info.sampleRate`, and `info.channels`; its media type is the provider's declaration
-(Gemini `audio/L16;codec=pcm;rate=24000`, Deepgram's `content-type`) or `audio/pcm`. Gemini returns PCM only, so any
-other `format` is rejected rather than wrapped as WAV by the route. Every `format` value a route cannot produce (unknown
-to it, a container on Cartesia SSE, WAV on an ElevenLabs stream, anything but PCM on Gemini) fails the same way as an
-unsupported field: `UnsupportedOperation` with `operation: "media.format"`.
+(Gemini `audio/L16;codec=pcm;rate=24000`, Deepgram's `content-type`) or `audio/pcm`. Gemini's asset follows the
+provider's declared type: WAV for Gemini 3.8 TTS `generate`, headerless PCM otherwise. The route never wraps PCM as WAV,
+so `pcm` is the only explicit `format` it accepts, and not on Gemini 3.8 `generate`. Every `format` value a route cannot
+produce (unknown to it, a container on Cartesia SSE, WAV on an ElevenLabs stream, anything but `pcm` on Gemini, `pcm` on
+Gemini 3.8 `generate`) fails the same way as an unsupported field: `UnsupportedOperation` with
+`operation: "media.format"`.

 **Timestamps.** `timestamps: true` on the request asks for alignment. ElevenLabs selects the `with-timestamps`
 endpoints (character-level, NDJSON when streaming); Cartesia sets `add_timestamps` on `/tts/sse` (word-level; a
@@ -267,8 +270,8 @@ Deferred: `Speech.session(...)` — input-streaming TTS where text arrives incre
 #### Transcription (STT)

 Shipped as the second half of phase 3 (`src/transcription.ts`, `src/transcription-client.ts`, protocols
-`openai-transcription`, `google-transcription`, `deepgram-transcription`, `assemblyai-transcription`; new `AssemblyAI`
-facade).
+`openai-transcription`, `google-transcription`, `deepgram-transcription`, `elevenlabs-transcription`,
+`assemblyai-transcription`; new `AssemblyAI` facade).

 ```ts
 const request = Transcription.request({
@@ -277,7 +280,7 @@ const request = Transcription.request({
  language: "en",                                  // provider-native passthrough
  timestamps: "segment",                           // none | segment | word
  diarize: true,
-  speakers: 2,                                     // expected count, hint only (AssemblyAI)
+  speakers: 2,                                     // speaker count (AssemblyAI exact, ElevenLabs maximum)
  providerOptions: { known_speaker_names: ["agent"] },
 })

@@ -291,10 +294,11 @@ yield* Transcription.resume(model, token)
 Transcription is the first modality whose providers span all three protocol kinds, and it needed no fourth kind.
 Every `MediaRoute` now carries its `kind`; `TranscriptionRoute` is the union of the inline, stream, and queued routes;
 `TranscriptionModel.fromRoute` is overloaded per protocol kind (arity picks the overload: `<Options>`,
-`<Options, Frame, State>`, `<Options, Token>`) and composes through `MediaRoute.inline` / `stream` / `queued`; and
-`TranscriptionClient` dispatches on `route.kind`. `generate` on a queued route is `start` then `await`; `stream` on an
-inline route is the response as a single `finish`, and on a queued route it is the status observations followed by
-`finish`. `start` / `resume` on a non-queued route fail with `UnsupportedOperation` (`transcription.start`). The
+`<Options, Frame, State>`, `<Options, Token>`) and composes through the shared `composeRoute` (`src/media-model.ts`),
+which picks `MediaRoute.inline` / `stream` / `queued`; and `TranscriptionClient`, like every modality client, is
+`MediaClient.make` (`src/media-client.ts`), which dispatches on `route.kind`. `generate` on a queued route is `start`
+then `await`; `stream` on an inline route is the response as a single `finish`, and on a queued route it is the status
+observations followed by `finish`. `start` / `resume` on a non-queued route fail with `UnsupportedOperation` (`transcription.start`). The
 `finish` event carries the whole transcript (text, segments, words, language, duration, usage), so the stream route's
 `collect` is just "take `finish`".

@@ -304,16 +308,23 @@ upload); `packages/ai/AGENTS.md` (Media Routes) describes both.
 Settled rules:

 - **Timestamps.** A granularity the selected route or model cannot produce fails as `UnsupportedOperation`
-  (`media.timestamps`), following Speech; a route that returns more than asked (Deepgram and AssemblyAI always return
-  words) is not stripped. Segments always carry start and end times: Gemini times each transcription part from its
+  (`media.timestamps`), following Speech; a route that returns more than asked (Deepgram, ElevenLabs, and AssemblyAI
+  always return words) is not stripped. Segments always carry start and end times: Gemini times each transcription part from its
  word offsets, so segment timestamps and diarization also request word offsets there.
 - **Diarization.** `diarize` means segments (and words, where the provider labels them) carry `speaker`. Labels are
-  provider-native strings — OpenAI `A` or a known speaker name, Deepgram `0`, Gemini `spk:0`, AssemblyAI `A` — with no
-  cross-provider speaker model. `speakers` is a hint; only AssemblyAI (`speakers_expected`) accepts it.
+  provider-native strings — OpenAI `A` or a known speaker name, Deepgram `0`, Gemini `spk:0`, AssemblyAI `A`,
+  ElevenLabs `speaker_0` — with no cross-provider speaker model. `speakers` is the number of speakers to label:
+  AssemblyAI (`speakers_expected`) treats it as an exact constraint rather than a hint, and ElevenLabs
+  (`num_speakers`) as the maximum. Both turn on diarization for it; the other routes reject it.
+- **Segments from words.** ElevenLabs returns only a token list (`word`, `spacing`, `audio_event`), so its segments
+  are speaker turns: consecutive words and spacing with one `speaker_id`, text joined from the provider's own spacing
+  tokens. `words` drops spacing and audio events. Segments therefore need diarization, which `timestamps: "segment"`
+  turns on, as AssemblyAI's utterances need speaker labels.
 - **Language** is passed through (`language`, OpenAI `gpt-transcribe` `languages[]`, Gemini `languageCodes`,
-  AssemblyAI `language_code`). `response.language` is the provider's own value, lowercased but not normalized: an
-  ISO code on most routes, `english` from whisper-1, `en_us` from AssemblyAI. Deepgram and AssemblyAI assume English
-  unless asked to detect, so a missing `language` enables their detection.
+  AssemblyAI and ElevenLabs `language_code`). `response.language` is the provider's own value, lowercased but not
+  normalized: an ISO code on most routes (AssemblyAI's detection returns `en`, ElevenLabs ISO 639-3 `eng`), `english`
+  from whisper-1. Deepgram and AssemblyAI assume English unless asked to detect, so a missing `language` enables their
+  detection.
 - **Gemini** requires a transcribe model; other model ids fail with `UnsupportedOperation` before the call, because
  general models ignore `audioTranscriptionConfig` and answer conversationally. Streamed chunks carry whole speaker
  turns (one part per turn), which join with a space.
@@ -323,14 +334,15 @@ Settled rules:

 | Provider | Kind | Audio input | `timestamps` | `diarize` | Unsupported | Usage |
 |---|---|---|---|---|---|---|
-| OpenAI | stream (`stream: true` in `stream` mode) | multipart `file` (inline only) | `whisper-1` (`verbose_json`); diarize model: `segment` | `gpt-4o-transcribe-diarize` (`diarized_json`) | `speakers`; `prompt` on the diarize model; streaming on `whisper-1` | `tokens` or `seconds` |
+| OpenAI | stream (`stream: true` in `stream` mode; `whisper-1` ignores `stream`, so it emits only `finish`) | multipart `file` (inline only) | `whisper-1` (`verbose_json`); diarize model: `segment` | `gpt-4o-transcribe-diarize` (`diarized_json`) | `speakers`; `prompt` on the diarize model | `tokens` or `seconds` |
 | Gemini | stream (`generateContent` / `streamGenerateContent`) | `inlineData` or Gemini Files `fileData` | `audioTranscriptionConfig.wordTimestamp` | `audioTranscriptionConfig.diarization` | `prompt`, `speakers` | `tokens` |
 | Deepgram | inline | raw body, or JSON `{ url }` | words always; `segment` → `utterances` | `diarize_model=latest` + `utterances` | `prompt`, `speakers` | `seconds` (`metadata.duration`) |
+| ElevenLabs | inline | multipart `file`, or `source_url` | words always; `segment` → `diarize` (speaker turns) | `diarize` | `prompt`; `webhook`, per-channel `use_multi_channel` | `seconds` (`audio_duration_secs`) |
 | AssemblyAI | queued (upload → submit → poll) | `/v2/upload` then `audio_url`, or a URL | words always; `segment` → `speaker_labels` | `speaker_labels` | — | `seconds` (`audio_duration`) |

 Deferred: `Transcription.session(...)` — realtime STT over WebSocket (Deepgram live, AssemblyAI streaming, ElevenLabs
 realtime, OpenAI realtime transcription) — is the same future scoped `session` shape as input-streaming TTS and ships
-with the realtime work in phase 5. ElevenLabs Scribe is not implemented yet.
+with the realtime work in phase 5.

 ### `Generation` — shared async execution

@@ -353,7 +365,11 @@ GenerationAwaitOptions = { poll?: Poll }
 Poll = { interval?: Duration; timeout?: Duration }
 ```

-`Generation` is not video-specific. Image routes on BFL, fal, and Replicate are queued; `Image.start` exists for them. A route declares itself `inline` or `queued`; `generate` on a queued route is `start` then `await`.
+`Generation` is not video-specific. Image routes on BFL, fal, Replicate, and Stability `upscale()` are queued; `Image.start` exists for them. A route declares itself `inline` or `queued`; `generate` on a queued route is `start` then `await`.
+
+Status polls and result reads retry transient failures (rate limits, provider 5xx, and transport errors, classified by the same `isRetryable` the Session runner uses) inside `MediaRoute.queued`. Only the HTTP exchange retries, never the decoded document: a terminal `failed` generation also surfaces as `ProviderInternal` and must not be re-read. Gaps grow exponentially from 1s with jitter, up to 30s each, honoring a provider `retry-after` up to that cap, for at most 8 retries. `await`, `events`, and `Video.stream` cut retries off at `poll.timeout` and fail with `Timeout`, so retries never extend the caller's deadline; a direct `result()` or `resume` read is bounded by the retry cap alone. `start` and `cancel` never retry: a repeated submit can start and bill a second job. The policy is internal; there is no option for it.
+
+Interrupting `await`, `events`, or `Video.stream` (or aborting the promise API's `signal`) stops waiting only. The provider job keeps running and billing; call `cancel()` explicitly to stop it.

 ### Usage

@@ -389,24 +405,26 @@ for await (const event of generation.events({ poll: { interval: 10_000 } })) {
 const video = await generation.await({ poll: { interval: 10_000 }, signal })
 const resumed = await ai.video.resume(model, JSON.parse(saved)) // persist provider + model ID with the token

-const text = await ai.llm.generate({ model, prompt })
+const request = ai.llm.request({ model, prompt })
+const text = await ai.llm.generate(request)
 for await (const event of ai.llm.stream(request)) { … }

 await ai.dispose()
 ```

-Streams become `AsyncIterable` via `Stream.toAsyncIterable`. `AIError` is thrown as-is. `AbortSignal` maps to interruption. Nothing in `src/*` except this entrypoint knows about promises.
+Streams become `AsyncIterable` via `Stream.toAsyncIterable`. `AIError` is thrown as-is. Aborting an `AbortSignal` interrupts the work and, like `fetch`, rejects the Promise or throws from the stream with `signal.reason` instead of ending the stream as if complete. Nothing in `src/*` except this entrypoint knows about promises.

 ### Providers

-Existing facades gain per-modality selectors; the modality routes each facade provides:
+Existing facades gain per-modality selectors; the modality routes each facade provides (*italics* are not
+implemented):

 | Facade | llm | image | video | speech | transcription | other |
 |---|---|---|---|---|---|---|
-| `OpenAI` | responses (default), chat | Images API (stream) | Sora (deprecated 2026-09-24) | ✓ | ✓ | |
+| `OpenAI` | responses (default), chat | Images API (stream) | *Sora skipped (decision 8)* | ✓ | ✓ | |
 | `Google` | Gemini | Gemini-native | Veo | Gemini TTS | `gemini-3.5-transcribe` | |
 | `XAI` | ✓ | ✓ | ✓ | | | |
-| `ElevenLabs` | | | | ✓ | Scribe | soundEffect, music |
+| `ElevenLabs` | | | | ✓ | Scribe | *soundEffect, music (phase 5)* |
 | `Cartesia` | | | | ✓ | | |
 | `Deepgram` | | | | Aura | ✓ | |
 | `Fal` | | ✓ (queued) | ✓ | | | |
@@ -415,11 +433,11 @@ Existing facades gain per-modality selectors; the modality routes each facade pr
 | `Replicate` | | ✓ (queued) | | | | |
 | `Stability` | | `image` (inline), `upscale()` (queued) | | | | |
 | `Runway` | | | ✓ | | | |
-| `Luma`, `Kling`, `MiniMax` | | per provider | | | | |
+| `Luma`, `Kling`, `MiniMax` | | *deferred* | *deferred* | | | |

 New facades follow the existing one-file-per-provider rule. The facade selector is the public path for media models; modality-specific package entrypoints (for example `@opencode/ai/providers/openai/images`) are deferred until Core has a modality-aware model resolver.

-`ImageModel<Options>` gives typed `providerOptions` per model; `VideoModel`, `SpeechModel`, and `TranscriptionModel` follow the same generic. They share an internal `MediaModel` base class (ids, route, `http` overlays) that is not part of the public exports; `Generation` and the promise client work with the concrete modality models.
+`ImageModel<Options>` gives typed `providerOptions` per model; `VideoModel`, `SpeechModel`, and `TranscriptionModel` follow the same generic. As with `LanguageModel`, the route type does not carry `Options`, so `ImageModel<OpenAIImageOptions>` is an `ImageModel` and client methods take plain `ImageRequestFor`. They share an internal `MediaModel` base class (ids, route, `http` overlays) that is not part of the public exports; `Generation` and the promise client work with the concrete modality models.

 ### Routes and protocols

@@ -459,7 +477,7 @@ Foundation + Image ship together as the reference implementation, serially. Vide

 1. **Foundation** — per-modality selectors, `Media`, `Generation`, `Poll`, `Usage` union, `MediaProtocol` kinds, `@opencode/ai/promise` with `llm` + `image`. Port the five existing image protocols onto it. Unify `MediaPart` and add the `media` LLM event (fixes Gemini image output being dropped).
 2. **Video** — ✅ Veo, xAI, fal, Runway shipped (`MediaProtocol.queued`, `Video.start/generate/resume/stream`, promise `ai.video`). Deferred: `Video.complete` (webhooks), Luma, Kling, MiniMax, Replicate.
-3. **Speech + Transcription** — ✅ Speech: OpenAI, Gemini TTS, ElevenLabs, Cartesia, Deepgram shipped (`MediaProtocol.stream`, `Speech.generate/stream`, promise `ai.speech`). ✅ Transcription: OpenAI, Gemini, Deepgram, AssemblyAI shipped across all three route kinds (`Transcription.generate/stream/start/resume`, promise `ai.transcription`). Pending: ElevenLabs Scribe. Deferred: `Speech.session` and `Transcription.session` (WebSocket streaming).
+3. **Speech + Transcription** — ✅ Speech: OpenAI, Gemini TTS, ElevenLabs, Cartesia, Deepgram shipped (`MediaProtocol.stream`, `Speech.generate/stream`, promise `ai.speech`). ✅ Transcription: OpenAI, Gemini, Deepgram, ElevenLabs Scribe, AssemblyAI shipped across all three route kinds (`Transcription.generate/stream/start/resume`, promise `ai.transcription`). Deferred: `Speech.session` and `Transcription.session` (WebSocket streaming).
 4. **Image queued routes and partials** — ✅ BFL, fal, Replicate, and Stability creative upscale queued; Stability generate inline; OpenAI `partial_images` streaming (`image-partial` restored). Imagen dropped: shut down on the Gemini API and discontinued on Vertex (2026-06-30). Deferred: Stability's synchronous edit and fast/conservative upscale endpoints.
 5. **Later** — ElevenLabs music/SFX, Lyria, `Speech.session` / `Transcription.session`, realtime.

@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "2.0.16",
+  "version": "2.0.18",
  "name": "@opencode/ai",
  "type": "module",
  "license": "MIT",
@@ -53,6 +53,8 @@ export type Event = Observation | { readonly type: "generation-finished"; readon

 const TERMINAL: ReadonlySet<Status> = new Set(["completed", "failed", "cancelled", "expired"])

+export const isTerminal = (status: Status) => TERMINAL.has(status)
+
 export class Generation<Response> {
  readonly id: string
  readonly status: Status
@@ -81,7 +83,7 @@ export class Generation<Response> {
  }

  get terminal() {
-    return TERMINAL.has(this.status)
+    return isTerminal(this.status)
  }

  refresh(): Effect.Effect<Generation<Response>, AIError> {
@@ -100,7 +102,7 @@ export class Generation<Response> {
    return settled.pipe(
      // Non-completed terminal states also go through `result` so the route can surface its provider failure body.
      Effect.flatMap((generation) => generation.result()),
-      Effect.timeoutOrElse({ duration: timeout, orElse: () => this.timeoutError(timeout) }),
+      Effect.timeoutOrElse({ duration: timeout, orElse: () => timeoutError(this.id, timeout) }),
    )
  }

@@ -109,9 +111,10 @@ export class Generation<Response> {
  }

  /**
-   * Status observations as a stream, ending after the first terminal observation. Each poll is bounded by the time
-   * remaining until `poll.timeout`, so a hung status request fails the stream instead of stalling it. (`Stream.interruptWhen`
-   * would express this directly but deadlocks under `TestClock` when the source completes while the timer sleeps.)
+   * Status observations as a stream, ending after the first terminal observation. Each poll and each sleep between polls
+   * is bounded by the time remaining until `poll.timeout`, so a hung status request or a long interval fails the stream at
+   * the deadline instead of stalling it. (`Stream.interruptWhen` would express this directly but deadlocks under
+   * `TestClock` when the source completes while the timer sleeps.)
   */
  events(options?: AwaitOptions): Stream.Stream<Event, AIError> {
    if (this.terminal) return Stream.make(this.event())
@@ -120,17 +123,13 @@ export class Generation<Response> {
      Clock.currentTimeMillis.pipe(
        Effect.map((start) => {
          const deadline = start + Duration.toMillis(timeout)
-          const refresh = Clock.currentTimeMillis.pipe(
-            Effect.flatMap((now) =>
-              this.refresh().pipe(
-                Effect.timeoutOrElse({
-                  duration: Duration.millis(Math.max(0, deadline - now)),
-                  orElse: () => this.timeoutError(timeout),
-                }),
-              ),
+          const refresh = within(this.refresh(), this.id, timeout, deadline)
+          const schedule = this.schedule(options?.poll).pipe(
+            Schedule.modifyDelay((meta) =>
+              Effect.succeed(Duration.min(meta.duration, Duration.millis(Math.max(0, deadline - meta.now)))),
            ),
          )
-          return Stream.fromEffectSchedule(refresh, this.schedule(options?.poll)).pipe(
+          return Stream.fromEffectSchedule(refresh, schedule).pipe(
            Stream.takeUntil((generation) => generation.terminal),
            Stream.map((generation) => generation.event()),
          )
@@ -145,15 +144,6 @@ export class Generation<Response> {
    return { type: "generation-progress", id: this.id, progress: this.progress }
  }

-  private timeoutError(timeout: Duration.Duration) {
-    return new AIError({
-      reason: new TimeoutError({
-        message: `Generation ${this.id} did not finish within ${Duration.format(timeout)}`,
-        timeoutMs: Duration.toMillis(timeout),
-      }),
-    })
-  }
-
  private poll(poll: Poll | undefined) {
    return this.refresh().pipe(
      Effect.repeat({ schedule: this.schedule(poll), until: (generation) => generation.terminal }),
@@ -165,12 +155,53 @@ export class Generation<Response> {
  }
 }

+/** `events` followed by the expanded result, with the result fetch bounded by the same `poll.timeout` deadline. */
 export const resultEvents = <Response, A>(
  generation: Generation<Response>,
  expand: (response: Response) => ReadonlyArray<A>,
  options?: AwaitOptions,
-): Stream.Stream<Observation | A, AIError> =>
-  generation.events(options).pipe(
-    Stream.filter((event): event is Observation => event.type !== "generation-finished"),
-    Stream.concat(Stream.fromIterableEffect(Effect.map(generation.result(), expand))),
+): Stream.Stream<Observation | A, AIError> => {
+  const timeout = Duration.fromInputUnsafe(options?.poll?.timeout ?? DEFAULT_POLL_TIMEOUT)
+  return Stream.unwrap(
+    Clock.currentTimeMillis.pipe(
+      Effect.map((start) =>
+        generation.events(options).pipe(
+          Stream.filter((event): event is Observation => event.type !== "generation-finished"),
+          Stream.concat(
+            Stream.fromIterableEffect(
+              within(generation.result(), generation.id, timeout, start + Duration.toMillis(timeout)).pipe(
+                Effect.map(expand),
+              ),
+            ),
+          ),
+        ),
+      ),
+    ),
  )
+}
+
+/**
+ * Run `effect` within the time left until `deadline`. Fails before starting once the deadline has passed: a fast
+ * request could otherwise win the zero-budget race and schedule another zero-delay poll.
+ */
+const within = <A>(effect: Effect.Effect<A, AIError>, id: string, timeout: Duration.Duration, deadline: number) =>
+  Clock.currentTimeMillis.pipe(
+    Effect.flatMap((now) =>
+      now >= deadline
+        ? Effect.fail(timeoutError(id, timeout))
+        : effect.pipe(
+            Effect.timeoutOrElse({
+              duration: Duration.millis(deadline - now),
+              orElse: () => Effect.fail(timeoutError(id, timeout)),
+            }),
+          ),
+    ),
+  )
+
+const timeoutError = (id: string, timeout: Duration.Duration) =>
+  new AIError({
+    reason: new TimeoutError({
+      message: `Generation ${id} did not finish within ${Duration.format(timeout)}`,
+      timeoutMs: Duration.toMillis(timeout),
+    }),
+  })
@@ -1,99 +1,30 @@
-import { Context, Effect, Layer, Stream } from "effect"
-import type { AwaitOptions, Generation } from "./generation.js"
-import { RequestExecutor } from "./route/executor.js"
-import { MediaRoute } from "./route/media.js"
-import type { AIError } from "./schema/index.js"
+import { Context } from "effect"
+import { MediaClient } from "./media-client.js"
 import {
-  responseEvents,
+  ImageOutputEvent,
+  ImageFinishEvent,
  type ImageEvent,
-  type ImageModel,
-  type ImageOptions,
  type ImageRequestFor,
  type ImageResponse,
 } from "./image.js"

-export interface Interface {
-  readonly generate: <Options extends ImageOptions>(
-    request: ImageRequestFor<Options>,
-    options?: AwaitOptions,
-  ) => Effect.Effect<ImageResponse, AIError>
-  readonly stream: <Options extends ImageOptions>(
-    request: ImageRequestFor<Options>,
-    options?: AwaitOptions,
-  ) => Stream.Stream<ImageEvent, AIError>
-  readonly start: <Options extends ImageOptions>(
-    request: ImageRequestFor<Options>,
-  ) => Effect.Effect<Generation<ImageResponse>, AIError>
-  readonly resume: <Options extends ImageOptions>(
-    model: ImageModel<Options>,
-    token: unknown,
-  ) => Effect.Effect<Generation<ImageResponse>, AIError>
-}
+export type Interface = MediaClient.Interface<ImageRequestFor, ImageEvent, ImageResponse>

 export class ImageClientService extends Context.Service<ImageClientService, Interface>()("@opencode/ImageClient") {}
 export const Service = ImageClientService
 export type Service = ImageClientService

-export const generate = <Options extends ImageOptions>(
-  request: ImageRequestFor<Options>,
-  options?: AwaitOptions,
-): Effect.Effect<ImageResponse, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.generate(request, options)
-  })
-
-export const stream = <Options extends ImageOptions>(
-  request: ImageRequestFor<Options>,
-  options?: AwaitOptions,
-): Stream.Stream<ImageEvent, AIError, Service> =>
-  Stream.unwrap(
-    Effect.gen(function* () {
-      const client = yield* Service
-      return client.stream(request, options)
-    }),
-  )
-
-export const start = <Options extends ImageOptions>(
-  request: ImageRequestFor<Options>,
-): Effect.Effect<Generation<ImageResponse>, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.start(request)
-  })
-
-export const resume = <Options extends ImageOptions>(
-  model: ImageModel<Options>,
-  token: unknown,
-): Effect.Effect<Generation<ImageResponse>, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.resume(model, token)
-  })
-
-export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
-  Service,
-  Effect.gen(function* () {
-    const executor = yield* RequestExecutor.Service
-    const dispatch = MediaRoute.dispatch<ImageEvent, ImageResponse>({
-      modality: "image",
-      execute: executor.execute,
-      responseEvents,
-    })
-    return Service.of({
-      start: (request) => dispatch.start(request.model.route, request),
-      resume: (model, token) => dispatch.resume(model.route, model, token),
-      generate: (request, options) => dispatch.generate(request.model.route, request, options),
-      stream: (request, options) => dispatch.stream(request.model.route, request, options),
-    })
-  }),
-)
-
 export const ImageClient = {
  Service,
-  layer,
-  generate,
-  stream,
-  start,
-  resume,
+  ...MediaClient.make(Service, {
+    modality: "image",
+    responseEvents: (response: ImageResponse) => [
+      ...response.images.map((image, index) => ImageOutputEvent.make({ index, image })),
+      ImageFinishEvent.make({
+        usage: response.usage,
+        notices: response.notices,
+        providerMetadata: response.providerMetadata,
+      }),
+    ],
+  }),
 } as const
@@ -1,9 +1,8 @@
 import { Effect, Schema, Stream } from "effect"
 import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
 import { Media } from "./media.js"
-import { MediaModel, composeAnyRoute, tryRequest } from "./media-model.js"
+import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
 import { MediaRoute } from "./route/media.js"
-import type { MediaProtocol } from "./route/media-protocol.js"
 import { AIError, HttpOptions, MediaUsage, ProviderMetadata, type OpenString } from "./schema/index.js"
 import { ImageClient, Service } from "./image-client.js"

@@ -11,75 +10,39 @@ import { ImageClient, Service } from "./image-client.js"
 // Model
 // ---------------------------------------------------------------------------

-export type ImageOptions = Record<string, unknown>
+export type ImageOptions = MediaModel.Options

-export type ImageRoute<Options extends ImageOptions = ImageOptions> = MediaRoute.AnyRoute<
-  ImageRequestFor<Options>,
-  ImageEvent,
-  ImageResponse
->
+export type ImageRoute = MediaRoute.AnyRoute<ImageRequestFor, ImageEvent, ImageResponse>

-export class ImageModel<Options extends ImageOptions = ImageOptions> extends MediaModel<ImageRoute<Options>, Options> {
+export class ImageModel<Options extends ImageOptions = ImageOptions> extends MediaModel<ImageRoute, Options> {
  declare protected readonly _ImageModel: void

-  static make<Options extends ImageOptions = ImageOptions>(input: MediaModel.Input<ImageRoute<Options>>) {
-    return new ImageModel<Options>(input)
-  }
-
  /** The number of type arguments selects the kind: `<Options>`, `<Options, Frame, State>`, or `<Options, Token>`. */
  static fromRoute<Options extends ImageOptions>(
-    route: ImageModel.InlineRouteInput<Options>,
+    route: MediaModel.InlineRouteInput<ImageRequestFor<Options>, ImageResponse>,
    input: MediaRoute.ModelInput,
  ): ImageModel<Options>
  static fromRoute<Options extends ImageOptions, Frame, State>(
-    route: ImageModel.StreamRouteInput<Options, Frame, State>,
+    route: MediaModel.StreamRouteInput<ImageRequestFor<Options>, ImageEvent, Frame, State>,
    input: MediaRoute.ModelInput,
  ): ImageModel<Options>
  static fromRoute<Options extends ImageOptions, Token>(
-    route: ImageModel.QueuedRouteInput<Options, Token>,
+    route: MediaModel.QueuedRouteInput<ImageRequestFor<Options>, ImageResponse, Token>,
    input: MediaRoute.ModelInput,
  ): ImageModel<Options>
  static fromRoute<Options extends ImageOptions, Frame, State, Token>(
-    route: ImageModel.RouteInput<Options, Frame, State, Token>,
+    route: MediaModel.AnyRouteInput<ImageRequestFor<Options>, ImageEvent, ImageResponse, Frame, State, Token>,
    input: MediaRoute.ModelInput,
  ) {
    return new ImageModel<Options>({
      id: input.id,
      provider: route.protocol.provider,
      http: input.http,
-      route: composeAnyRoute(route, input, collectResponse),
+      route: composeRoute(route, input, collectResponse) as ImageRoute,
    })
  }
 }

-export namespace ImageModel {
-  export type InlineRouteInput<Options extends ImageOptions = ImageOptions> = MediaModel.RouteInput<
-    ImageRequestFor<Options>,
-    MediaProtocol.Inline<ImageRequestFor<Options>, ImageResponse>
-  >
-
-  export type StreamRouteInput<
-    Options extends ImageOptions = ImageOptions,
-    Frame = unknown,
-    State = unknown,
-  > = MediaModel.RouteInput<
-    MediaProtocol.Addressed<ImageRequestFor<Options>>,
-    MediaProtocol.Streamed<ImageRequestFor<Options>, ImageEvent, Frame, State>
-  >
-
-  export type QueuedRouteInput<Options extends ImageOptions = ImageOptions, Token = unknown> = MediaModel.RouteInput<
-    ImageRequestFor<Options>,
-    MediaProtocol.Queued<ImageRequestFor<Options>, ImageResponse, Token>
-  >
-
-  export type RouteInput<
-    Options extends ImageOptions = ImageOptions,
-    Frame = unknown,
-    State = unknown,
-    Token = unknown,
-  > = MediaModel.AnyRouteInput<ImageRequestFor<Options>, ImageEvent, ImageResponse, Frame, State, Token>
-}
-
 export const ImageModelSchema = Schema.declare((value): value is ImageModel => value instanceof ImageModel, {
  expected: "Image.Model",
 })
@@ -190,15 +153,6 @@ export const ImageEvent = Object.assign(imageEventTagged, {
 })
 export type ImageEvent = Schema.Schema.Type<typeof imageEventTagged>

-export const responseEvents = (response: ImageResponse): ReadonlyArray<ImageEvent> => [
-  ...response.images.map((image, index) => ImageOutputEvent.make({ index, image })),
-  ImageFinishEvent.make({
-    usage: response.usage,
-    notices: response.notices,
-    providerMetadata: response.providerMetadata,
-  }),
-]
-
 const collectResponse = (events: ReadonlyArray<ImageEvent>): Effect.Effect<ImageResponse> => {
  const finish = events.find(ImageEvent.is.finish)
  // Every image protocol's `finish` emits the terminal event or fails, so a completed stream always has one.
@@ -232,36 +186,31 @@ export function request(input: ImageRequest | ImageRequestInput) {
 const requestEffect = (input: ImageRequest | ImageRequestInput) => tryRequest(() => request(input))

 export function generate<const Model extends ImageModel>(
-  input: ImageRequestInput<Model>,
+  input: ImageRequest | ImageRequestInput<Model>,
  options?: AwaitOptions,
 ): Effect.Effect<ImageResponse, AIError, Service>
-export function generate(input: ImageRequest, options?: AwaitOptions): Effect.Effect<ImageResponse, AIError, Service>
 export function generate(input: ImageRequest | ImageRequestInput, options?: AwaitOptions) {
  return requestEffect(input).pipe(Effect.flatMap((request) => ImageClient.generate(request, options)))
 }

 export function stream<const Model extends ImageModel>(
-  input: ImageRequestInput<Model>,
+  input: ImageRequest | ImageRequestInput<Model>,
  options?: AwaitOptions,
 ): Stream.Stream<ImageEvent, AIError, Service>
-export function stream(input: ImageRequest, options?: AwaitOptions): Stream.Stream<ImageEvent, AIError, Service>
 export function stream(input: ImageRequest | ImageRequestInput, options?: AwaitOptions) {
  return Stream.unwrap(requestEffect(input).pipe(Effect.map((request) => ImageClient.stream(request, options))))
 }

 /** Inline and streaming routes fail with `UnsupportedOperation`. */
 export function start<const Model extends ImageModel>(
-  input: ImageRequestInput<Model>,
+  input: ImageRequest | ImageRequestInput<Model>,
 ): Effect.Effect<Generation<ImageResponse>, AIError, Service>
-export function start(input: ImageRequest): Effect.Effect<Generation<ImageResponse>, AIError, Service>
 export function start(input: ImageRequest | ImageRequestInput) {
  return requestEffect(input).pipe(Effect.flatMap((request) => ImageClient.start(request)))
 }

-export const resume = <Options extends ImageOptions>(
-  model: ImageModel<Options>,
-  token: unknown,
-): Effect.Effect<Generation<ImageResponse>, AIError, Service> => ImageClient.resume(model, token)
+export const resume = (model: ImageModel, token: unknown): Effect.Effect<Generation<ImageResponse>, AIError, Service> =>
+  ImageClient.resume(model, token)

 export const Image = {
  request,
@@ -4,7 +4,7 @@ export { ImageClient } from "./image-client.js"
 export { Auth } from "./route/auth.js"
 export { Provider } from "./provider.js"
 export { ProviderPackage } from "./provider-package.js"
-export { isContextOverflow, isContextOverflowFailure } from "./provider-error.js"
+export { isContextOverflow, isContextOverflowFailure, isRetryable } from "./provider-error.js"
 export type {
  RouteLanguageModelInput,
  RouteRoutedLanguageModelInput,
@@ -1,5 +1,6 @@
-import { Effect, JsonSchema, Schema } from "effect"
-import { LLMClient, Service } from "./route/client.js"
+import { Effect, JsonSchema, Schema, Stream } from "effect"
+import { tryRequest } from "./media-model.js"
+import { LLMClient, Service, type StreamOptions } from "./route/client.js"
 import {
  GenerationOptions,
  HttpOptions,
@@ -35,9 +36,26 @@ export type RequestInput<SelectedLanguageModel extends LanguageModel = LanguageM
  readonly http?: HttpOptions.Input
 }

-export const generate = LLMClient.generate
+export function generate<const Model extends LanguageModel>(
+  input: RequestInput<Model>,
+  options?: StreamOptions,
+): Effect.Effect<LLMResponse, AIError, Service>
+export function generate(input: LLMRequest, options?: StreamOptions): Effect.Effect<LLMResponse, AIError, Service>
+export function generate(input: RequestInput | LLMRequest, options?: StreamOptions) {
+  return requestEffect(input).pipe(Effect.flatMap((request) => LLMClient.generate(request, options)))
+}

-export const stream = LLMClient.stream
+export function stream<const Model extends LanguageModel>(
+  input: RequestInput<Model>,
+  options?: StreamOptions,
+): Stream.Stream<LLMEvent, AIError, Service>
+export function stream(input: LLMRequest, options?: StreamOptions): Stream.Stream<LLMEvent, AIError, Service>
+export function stream(input: RequestInput | LLMRequest, options?: StreamOptions) {
+  return Stream.unwrap(requestEffect(input).pipe(Effect.map((request) => LLMClient.stream(request, options))))
+}
+
+const requestEffect = (input: RequestInput | LLMRequest) =>
+  input instanceof LLMRequest ? Effect.succeed(input) : tryRequest(() => request(input))

 export const request = <const SelectedLanguageModel extends LanguageModel>(
  input: RequestInput<SelectedLanguageModel>,
@@ -0,0 +1,77 @@
+import { type Context, Effect, Layer, Stream } from "effect"
+import { resultEvents, type AwaitOptions, type Generation, type Observation } from "./generation.js"
+import { RequestExecutor } from "./route/executor.js"
+import type { MediaRoute } from "./route/media.js"
+import { AIError, UnsupportedOperationError } from "./schema/index.js"
+
+/** A media request whose model carries the route that executes it. */
+export interface RoutedRequest<Self extends MediaRoute.MediaRequest, Event, Response> extends MediaRoute.MediaRequest {
+  readonly model: MediaRoute.MediaRequest["model"] & { readonly route: MediaRoute.AnyRoute<Self, Event, Response> }
+}
+
+/** `start` and `resume` fail with `UnsupportedOperation` on inline and stream routes. */
+export interface Interface<Req extends RoutedRequest<Req, Event, Response>, Event, Response> {
+  readonly generate: (request: Req, options?: AwaitOptions) => Effect.Effect<Response, AIError>
+  readonly stream: (request: Req, options?: AwaitOptions) => Stream.Stream<Event | Observation, AIError>
+  readonly start: (request: Req) => Effect.Effect<Generation<Response>, AIError>
+  readonly resume: (model: Req["model"], token: unknown) => Effect.Effect<Generation<Response>, AIError>
+}
+
+/** One modality's layer and service accessors, dispatching each request on its route's `kind`. */
+export const make = <Self, Req extends RoutedRequest<Req, Event, Response>, Event, Response>(
+  service: Context.Service<Self, Interface<Req, Event, Response>>,
+  input: {
+    readonly modality: string
+    /** A completed response expanded into the streaming event shape. */
+    readonly responseEvents: (response: Response) => ReadonlyArray<Event>
+  },
+) => ({
+  layer: Layer.effect(
+    service,
+    Effect.gen(function* () {
+      const executor = yield* RequestExecutor.Service
+      const notQueued = (route: MediaRoute.AnyRoute<Req, Event, Response>, operation: string) =>
+        new AIError({
+          reason: new UnsupportedOperationError({
+            operation: `${input.modality}.${operation}`,
+            provider: route.provider,
+            route: route.id,
+            message: `${route.provider}/${route.id} is not a queued route; use generate or stream`,
+          }),
+        })
+      const start = (request: Req) => {
+        const route = request.model.route
+        if (route.kind !== "queued") return Effect.fail(notQueued(route, "start"))
+        return route.start(request, executor.execute)
+      }
+      return service.of({
+        start,
+        resume: (model, token) => {
+          if (model.route.kind !== "queued") return Effect.fail(notQueued(model.route, "resume"))
+          return model.route.resume(model, token, executor.execute)
+        },
+        generate: (request, options) => {
+          const route = request.model.route
+          if (route.kind !== "queued") return route.generate(request, executor.execute)
+          return start(request).pipe(Effect.flatMap((generation) => generation.await(options)))
+        },
+        stream: (request, options) => {
+          const route = request.model.route
+          if (route.kind === "stream") return route.stream(request, executor.execute)
+          if (route.kind === "queued")
+            return Stream.unwrap(
+              start(request).pipe(Effect.map((generation) => resultEvents(generation, input.responseEvents, options))),
+            )
+          return Stream.fromIterableEffect(Effect.map(route.generate(request, executor.execute), input.responseEvents))
+        },
+      })
+    }),
+  ),
+  generate: (request: Req, options?: AwaitOptions) => service.use((client) => client.generate(request, options)),
+  stream: (request: Req, options?: AwaitOptions) =>
+    Stream.unwrap(service.useSync((client) => client.stream(request, options))),
+  start: (request: Req) => service.use((client) => client.start(request)),
+  resume: (model: Req["model"], token: unknown) => service.use((client) => client.resume(model, token)),
+})
+
+export * as MediaClient from "./media-client.js"
@@ -6,11 +6,13 @@ import { AIError, HttpOptions, InvalidRequestError, ModelID, ProviderID } from "

 /**
 * What every media model carries: ids, the configured route, and deployment `http` overlays. Modality classes
- * (`ImageModel`, `VideoModel`, `SpeechModel`) extend it with their route type and a nominal marker so one cannot stand
- * in for the other in requests.
+ * (`ImageModel`, `VideoModel`, `SpeechModel`, `TranscriptionModel`) extend it with their route type and a nominal
+ * marker so one cannot stand in for the other in requests.
 */
 export class MediaModel<Route, Options> {
-  declare protected readonly _Options: (options: Options) => Options
+  // As with `LanguageModel`, the route type is erased over `Options`; `fromRoute` and the constructor trust that the
+  // route accepts every request this model's `Options` admit.
+  declare protected readonly _Options: Options
  readonly id: ModelID
  readonly provider: ProviderID
  readonly route: Route
@@ -25,6 +27,8 @@ export class MediaModel<Route, Options> {
 }

 export namespace MediaModel {
+  export type Options = Record<string, unknown>
+
  export interface Input<Route> {
    readonly id: string | ModelID
    readonly provider: string | ProviderID
@@ -41,48 +45,56 @@ export namespace MediaModel {
    readonly headers?: Record<string, string>
  }

+  export type InlineRouteInput<Request extends MediaRoute.MediaRequest, Response> = RouteInput<
+    Request,
+    MediaProtocol.Inline<Request, Response>
+  >
+
+  export type StreamRouteInput<Request extends MediaRoute.MediaRequest, Event, Frame, State> = RouteInput<
+    MediaProtocol.Addressed<Request>,
+    MediaProtocol.Streamed<Request, Event, Frame, State>
+  >
+
+  export type QueuedRouteInput<Request extends MediaRoute.MediaRequest, Response, Token> = RouteInput<
+    Request,
+    MediaProtocol.Queued<Request, Response, Token>
+  >
+
  export type AnyRouteInput<Request extends MediaRoute.MediaRequest, Event, Response, Frame, State, Token> =
-    | RouteInput<Request, MediaProtocol.Inline<Request, Response>>
-    | RouteInput<MediaProtocol.Addressed<Request>, MediaProtocol.Streamed<Request, Event, Frame, State>>
-    | RouteInput<Request, MediaProtocol.Queued<Request, Response, Token>>
+    | InlineRouteInput<Request, Response>
+    | StreamRouteInput<Request, Event, Frame, State>
+    | QueuedRouteInput<Request, Response, Token>
 }

 /** Compose a protocol route input with one deployment through `MediaRoute.inline`, `queued`, or `stream`. */
-export const composeRoute = <Request extends MediaRoute.MediaRequest, Protocol, Route>(
-  compose: (input: MediaRoute.Composition<Request> & { readonly protocol: Protocol }) => Route,
-  route: MediaModel.RouteInput<Request, Protocol>,
-  input: MediaRoute.ModelInput,
-): Route =>
-  compose({
-    protocol: route.protocol,
-    endpoint: Endpoint.path(route.path, { baseURL: input.baseURL ?? route.baseURL }),
-    auth: input.auth,
-    headers:
-      route.headers === undefined && input.headers === undefined ? undefined : { ...route.headers, ...input.headers },
-  })
-
-export const composeAnyRoute = <Request extends MediaRoute.MediaRequest, Event, Response, Frame, State, Token>(
+export const composeRoute = <Request extends MediaRoute.MediaRequest, Event, Response, Frame, State, Token>(
  route: MediaModel.AnyRouteInput<Request, Event, Response, Frame, State, Token>,
  input: MediaRoute.ModelInput,
  collect: (events: ReadonlyArray<Event>) => Effect.Effect<Response, AIError>,
 ): MediaRoute.AnyRoute<Request, Event, Response> => {
-  if (isStreamInput(route))
-    return composeRoute((composition) => MediaRoute.stream({ ...composition, collect }), route, input)
-  if (isQueuedInput(route)) return composeRoute(MediaRoute.queued, route, input)
-  return composeRoute(MediaRoute.inline, route, input)
+  if (isStreamInput(route)) return MediaRoute.stream({ ...composition(route, input), collect })
+  if (isQueuedInput(route)) return MediaRoute.queued(composition(route, input))
+  return MediaRoute.inline(composition(route, input))
 }

+const composition = <Request extends MediaRoute.MediaRequest, Protocol>(
+  route: MediaModel.RouteInput<Request, Protocol>,
+  input: MediaRoute.ModelInput,
+): MediaRoute.Composition<Request> & { readonly protocol: Protocol } => ({
+  protocol: route.protocol,
+  endpoint: Endpoint.path(route.path, { baseURL: input.baseURL ?? route.baseURL }),
+  auth: input.auth,
+  headers:
+    route.headers === undefined && input.headers === undefined ? undefined : { ...route.headers, ...input.headers },
+})
+
 const isStreamInput = <Request extends MediaRoute.MediaRequest, Event, Response, Frame, State, Token>(
  route: MediaModel.AnyRouteInput<Request, Event, Response, Frame, State, Token>,
-): route is MediaModel.RouteInput<
-  MediaProtocol.Addressed<Request>,
-  MediaProtocol.Streamed<Request, Event, Frame, State>
-> => route.protocol.kind === "stream"
+): route is MediaModel.StreamRouteInput<Request, Event, Frame, State> => route.protocol.kind === "stream"

 const isQueuedInput = <Request extends MediaRoute.MediaRequest, Event, Response, Frame, State, Token>(
  route: MediaModel.AnyRouteInput<Request, Event, Response, Frame, State, Token>,
-): route is MediaModel.RouteInput<Request, MediaProtocol.Queued<Request, Response, Token>> =>
-  route.protocol.kind === "queued"
+): route is MediaModel.QueuedRouteInput<Request, Response, Token> => route.protocol.kind === "queued"

 /** Lift a synchronous Schema-class constructor into a typed `InvalidRequest` failure. */
 export const tryRequest = <A>(make: () => A): Effect.Effect<A, AIError> =>
@@ -1,23 +1,22 @@
 import { Effect, Layer, ManagedRuntime, Stream } from "effect"
 import { AIClient } from "./ai-client.js"
 import type { AwaitOptions, Event, Generation, Snapshot } from "./generation.js"
-import { Image, ImageModel, ImageRequest, type ImageOptions, type ImageRequestInput } from "./image.js"
+import { Image, type ImageModel, type ImageRequest, type ImageRequestInput } from "./image.js"
 import { LLM } from "./index.js"
 import { Media } from "./media.js"
 import { tryRequest } from "./media-model.js"
 import { RequestExecutor } from "./route/executor.js"
 import { AIError, InvalidRequestError, LanguageModel, LLMRequest } from "./schema/index.js"
 import type { RequestInput } from "./llm.js"
-import { Speech, SpeechModel, SpeechRequest, type SpeechRequestInput } from "./speech.js"
+import { Speech, type SpeechModel, type SpeechRequest, type SpeechRequestInput } from "./speech.js"
 import {
  Transcription,
-  TranscriptionModel,
-  TranscriptionRequest,
-  type TranscriptionOptions,
+  type TranscriptionModel,
+  type TranscriptionRequest,
  type TranscriptionRequestInput,
 } from "./transcription.js"
 import { fileMediaType } from "./utils/media-type.js"
-import { Video, VideoModel, VideoRequest, type VideoOptions, type VideoRequestInput } from "./video.js"
+import { Video, type VideoModel, type VideoRequest, type VideoRequestInput } from "./video.js"

 /**
 * Promise-first entrypoint for scripts and non-Effect callers. One `ManagedRuntime` hosts the LLM, image, video, speech,
@@ -43,7 +42,7 @@ export type GenerationHandle<Response> = Snapshot & {
  /** Serializable JSON; pass it back to `resume` from another process. */
  readonly token: unknown
  readonly await: (options?: AwaitOptions & RunOptions) => Promise<Response>
-  /** Status observations until the first terminal one, polling like `await`; abort ends iteration without throwing. */
+  /** Status observations until the first terminal one, polling like `await`; abort throws `signal.reason`. */
  readonly events: (options?: AwaitOptions & RunOptions) => AsyncIterable<Event>
  /** The result without polling; fails when the generation has not completed. */
  readonly result: (options?: RunOptions) => Promise<Response>
@@ -51,15 +50,16 @@ export type GenerationHandle<Response> = Snapshot & {
  readonly cancel: (options?: RunOptions) => Promise<void>
 }

+// Fails with `signal.reason` so aborted calls reject and aborted streams throw like `fetch`: an `AbortError` by default.
 const abortEffect = (signal: AbortSignal | undefined) =>
  signal === undefined
    ? Effect.never
-    : Effect.callback<void>((resume) => {
+    : Effect.callback<never, unknown>((resume) => {
        if (signal.aborted) {
-          resume(Effect.void)
+          resume(Effect.fail(signal.reason))
          return
        }
-        const onAbort = () => resume(Effect.void)
+        const onAbort = () => resume(Effect.fail(signal.reason))
        signal.addEventListener("abort", onAbort, { once: true })
        return Effect.sync(() => signal.removeEventListener("abort", onAbort))
      })
@@ -69,14 +69,14 @@ export const make = (options: Options = {}) => {

  /** Run any package Effect (for example `LLMClient.compact(...)`) inside this runtime. */
  const run = <A, E>(effect: Effect.Effect<A, E, Services>, options?: RunOptions) =>
-    runtime.runPromise(effect, { signal: options?.signal })
+    runtime.runPromise(Effect.raceFirst(effect, abortEffect(options?.signal)))

  const iterate = <A, E>(stream: Stream.Stream<A, E, Services>, options?: RunOptions): AsyncIterable<A> =>
    Stream.toAsyncIterable(
      Stream.unwrap(
        runtime.contextEffect.pipe(
          Effect.map(
-            (context): Stream.Stream<A, E> =>
+            (context): Stream.Stream<A, unknown> =>
              stream.pipe(Stream.interruptWhen(abortEffect(options?.signal)), Stream.provideContext(context)),
          ),
        ),
@@ -93,17 +93,8 @@ export const make = (options: Options = {}) => {
    cancel: (options) => run(generation.cancel(), options),
  })

-  // The typed `generate`/`stream` overloads take a concrete input or a request, not the union; normalize once here.
  const llmRequest = (input: RequestInput | LLMRequest) =>
    input instanceof LLMRequest ? Effect.succeed(input) : tryRequest(() => LLM.request(input))
-  const imageRequest = (input: ImageRequestInput | ImageRequest) =>
-    input instanceof ImageRequest ? input : Image.request(input)
-  const videoRequest = (input: VideoRequestInput | VideoRequest) =>
-    input instanceof VideoRequest ? input : Video.request(input)
-  const speechRequest = (input: SpeechRequestInput | SpeechRequest) =>
-    input instanceof SpeechRequest ? input : Speech.request(input)
-  const transcriptionRequest = (input: TranscriptionRequestInput | TranscriptionRequest) =>
-    input instanceof TranscriptionRequest ? input : Transcription.request(input)

  return {
    run,
@@ -155,61 +146,58 @@ export const make = (options: Options = {}) => {
      generate: <const Model extends ImageModel>(
        input: ImageRequestInput<Model> | ImageRequest,
        options?: AwaitOptions & RunOptions,
-      ) => run(Image.generate(imageRequest(input), { poll: options?.poll }), options),
+      ) => run(Image.generate(input, { poll: options?.poll }), options),
      stream: <const Model extends ImageModel>(
        input: ImageRequestInput<Model> | ImageRequest,
        options?: AwaitOptions & RunOptions,
-      ) => iterate(Image.stream(imageRequest(input), { poll: options?.poll }), options),
+      ) => iterate(Image.stream(input, { poll: options?.poll }), options),
      start: <const Model extends ImageModel>(input: ImageRequestInput<Model> | ImageRequest, options?: RunOptions) =>
-        run(Image.start(imageRequest(input)), options).then(handle),
-      resume: <Options extends ImageOptions>(model: ImageModel<Options>, token: unknown, options?: RunOptions) =>
+        run(Image.start(input), options).then(handle),
+      resume: (model: ImageModel, token: unknown, options?: RunOptions) =>
        run(Image.resume(model, token), options).then(handle),
    },
    video: {
      request: Video.request,
      start: <const Model extends VideoModel>(input: VideoRequestInput<Model> | VideoRequest, options?: RunOptions) =>
-        run(Video.start(videoRequest(input)), options).then(handle),
+        run(Video.start(input), options).then(handle),
      generate: <const Model extends VideoModel>(
        input: VideoRequestInput<Model> | VideoRequest,
        options?: AwaitOptions & RunOptions,
-      ) => run(Video.generate(videoRequest(input), { poll: options?.poll }), options),
-      resume: <Options extends VideoOptions>(model: VideoModel<Options>, token: unknown, options?: RunOptions) =>
+      ) => run(Video.generate(input, { poll: options?.poll }), options),
+      resume: (model: VideoModel, token: unknown, options?: RunOptions) =>
        run(Video.resume(model, token), options).then(handle),
      stream: <const Model extends VideoModel>(
        input: VideoRequestInput<Model> | VideoRequest,
        options?: AwaitOptions & RunOptions,
-      ) => iterate(Video.stream(videoRequest(input), { poll: options?.poll }), options),
+      ) => iterate(Video.stream(input, { poll: options?.poll }), options),
    },
    speech: {
      request: Speech.request,
      generate: <const Model extends SpeechModel>(
        input: SpeechRequestInput<Model> | SpeechRequest,
        options?: RunOptions,
-      ) => run(Speech.generate(speechRequest(input)), options),
+      ) => run(Speech.generate(input), options),
      stream: <const Model extends SpeechModel>(
        input: SpeechRequestInput<Model> | SpeechRequest,
        options?: RunOptions,
-      ) => iterate(Speech.stream(speechRequest(input)), options),
+      ) => iterate(Speech.stream(input), options),
    },
    transcription: {
      request: Transcription.request,
      generate: <const Model extends TranscriptionModel>(
        input: TranscriptionRequestInput<Model> | TranscriptionRequest,
        options?: AwaitOptions & RunOptions,
-      ) => run(Transcription.generate(transcriptionRequest(input), { poll: options?.poll }), options),
+      ) => run(Transcription.generate(input, { poll: options?.poll }), options),
      stream: <const Model extends TranscriptionModel>(
        input: TranscriptionRequestInput<Model> | TranscriptionRequest,
        options?: AwaitOptions & RunOptions,
-      ) => iterate(Transcription.stream(transcriptionRequest(input), { poll: options?.poll }), options),
+      ) => iterate(Transcription.stream(input, { poll: options?.poll }), options),
      start: <const Model extends TranscriptionModel>(
        input: TranscriptionRequestInput<Model> | TranscriptionRequest,
        options?: RunOptions,
-      ) => run(Transcription.start(transcriptionRequest(input)), options).then(handle),
-      resume: <Options extends TranscriptionOptions>(
-        model: TranscriptionModel<Options>,
-        token: unknown,
-        options?: RunOptions,
-      ) => run(Transcription.resume(model, token), options).then(handle),
+      ) => run(Transcription.start(input), options).then(handle),
+      resume: (model: TranscriptionModel, token: unknown, options?: RunOptions) =>
+        run(Transcription.resume(model, token), options).then(handle),
    },
    dispose: () => runtime.dispose(),
  }
@@ -70,7 +70,11 @@ export const protocol = Protocol.make({
      return {
        ...(yield* OpenAIChat.protocol.body.from(req)),
        enable_thinking: opts.enableThinking,
-        thinking_budget: opts.thinkingBudget,
+        // Alibaba also rejects an explicit budget that is not below `max_completion_tokens`.
+        thinking_budget:
+          opts.thinkingBudget === undefined
+            ? undefined
+            : ProviderShared.fitThinkingBudget(opts.thinkingBudget, req.generation?.maxTokens),
        preserve_thinking: opts.preserveThinking,
        clear_thinking: opts.clearThinking,
        thinking: opts.thinking,
@@ -26,18 +26,21 @@ export const protocol = Protocol.make({
    from: Effect.fn("AlibabaMessages.fromRequest")(function* (req) {
      const opts = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))(req.providerOptions ?? {})
      // Model Studio accepts enabled thinking without Anthropic's mandatory token budget.
+      const body = yield* AnthropicMessages.protocol.body.from(
+        LLMRequest.update(req, {
+          providerOptions: { ...req.providerOptions, thinking: undefined },
+        }),
+      )
+      const budget = opts.thinking?.budgetTokens ?? opts.thinking?.budget_tokens
      return {
-        ...(yield* AnthropicMessages.protocol.body.from(
-          LLMRequest.update(req, {
-            providerOptions: { ...req.providerOptions, thinking: undefined },
-          }),
-        )),
+        ...body,
        thinking:
          opts.thinking === undefined
            ? undefined
            : {
                type: opts.thinking.type,
-                budget_tokens: opts.thinking.budgetTokens ?? opts.thinking.budget_tokens,
+                budget_tokens:
+                  budget === undefined ? undefined : ProviderShared.fitThinkingBudget(budget, body.max_tokens),
              },
      }
    }),
@@ -18,7 +18,6 @@ import {
  type CacheHint,
  type FinishReasonDetails,
  type FinishReason,
-  type JsonSchema,
  type MediaPart,
  type ProviderMetadata,
  type ProviderOptions,
@@ -31,13 +30,13 @@ import { classifyProviderFailure } from "../provider-error.js"
 import { effortUpdate, resolveEffortUpdates } from "../effort-updates.js"
 import * as Cache from "./utils/cache.js"
 import { Lifecycle } from "./utils/lifecycle.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { ToolStream } from "./utils/tool-stream.js"

 const ADAPTER = "anthropic-messages"
 export const DEFAULT_BASE_URL = "https://api.anthropic.com/v1"
 export const PATH = "/messages"
 export const DEFAULT_MAX_TOKENS = 32_000
+const MIN_THINKING_BUDGET = 1_024
 const DEFAULT_EFFORT = "high"

 const SSE_EVENTS = new Set([
@@ -524,10 +523,10 @@ const redactedDataFromMetadata = (metadata: ProviderMetadata | undefined, key: s
  return typeof provider.redactedData === "string" ? provider.redactedData : undefined
 }

-const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
+const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition): AnthropicTool => ({
  name: tool.name,
  description: tool.description,
-  input_schema: inputSchema,
+  input_schema: tool.inputSchema,
  cache_control: cacheControl(breakpoints, tool.cache),
 })

@@ -1027,6 +1026,15 @@ const applyThinkingBindingDefault = (model: LLMRequest["model"], thinking: Anthr
  }
 }

+// Anthropic also requires an explicit thinking budget below `max_tokens` and at or above its minimum.
+const fitThinking = (thinking: AnthropicThinking | undefined, maxTokens: number) =>
+  thinking?.type === "enabled"
+    ? {
+        ...thinking,
+        budget_tokens: ProviderShared.fitThinkingBudget(thinking.budget_tokens, maxTokens, MIN_THINKING_BUDGET),
+      }
+    : thinking
+
 const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (request: LLMRequest) {
  const options = yield* decodeOptions(request.providerOptions ?? {})
  const management = options.contextManagement
@@ -1039,12 +1047,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
  // over-mark we keep their tool hints and shed the message-tail ones first.
  const breakpoints = Cache.newBreakpoints(ANTHROPIC_BREAKPOINT_CAP)
  const flattened = ProviderShared.flattenToolRequest(updates.request)
-  const tools =
-    flattened.tools.length === 0
-      ? undefined
-      : flattened.tools.map((tool) =>
-          lowerTool(breakpoints, tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model)),
-        )
+  const tools = flattened.tools.length === 0 ? undefined : flattened.tools.map((tool) => lowerTool(breakpoints, tool))
  // Anthropic rejects tool_choice when tools are absent; "none" is only meaningful with tools present.
  const toolChoice = tools === undefined || !request.toolChoice ? undefined : yield* lowerToolChoice(request.toolChoice)
  const systemParts = request.system.filter((part) => part.text.length > 0)
@@ -1064,6 +1067,7 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
  }
  const output_config =
    updates.effort === undefined && format === undefined ? undefined : { effort: updates.effort, format }
+  const maxTokens = generation?.maxTokens ?? DEFAULT_MAX_TOKENS
  const body = {
    model: request.model.id,
    system,
@@ -1071,12 +1075,12 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
    tools,
    tool_choice: toolChoice,
    stream: true as const,
-    max_tokens: generation?.maxTokens ?? DEFAULT_MAX_TOKENS,
+    max_tokens: maxTokens,
    temperature: generation?.temperature,
    top_p: generation?.topP,
    top_k: generation?.topK,
    stop_sequences: generation?.stop,
-    thinking: applyThinkingBindingDefault(request.model, options.thinking),
+    thinking: applyThinkingBindingDefault(request.model, fitThinking(options.thinking, maxTokens)),
    output_config,
    // top-level passthrough per SDK MessageCreateParamsBase:4638,4643,4649,4654,4670
    cache_control: options.cache_control ?? options.cacheControl,
@@ -110,8 +110,11 @@ const fromRequest = Effect.fn("AssemblyAITranscription.fromRequest")(function* (
        language_code: request.language,
        language_detection: request.language === undefined ? true : undefined,
        prompt: request.prompt,
-        // Turn-level `utterances`, the only segments AssemblyAI returns, require speaker labels.
-        speaker_labels: request.diarize === true || request.timestamps === "segment" ? true : undefined,
+        // Turn-level `utterances`, the only segments AssemblyAI returns, and `speakers_expected` require speaker labels.
+        speaker_labels:
+          request.diarize === true || request.timestamps === "segment" || request.speakers !== undefined
+            ? true
+            : undefined,
        speakers_expected: request.speakers,
      },
      request.providerOptions,
@@ -155,8 +158,7 @@ const decodeResult = Effect.fn("AssemblyAITranscription.decodeResult")(function*
  const error = transcript.error ?? undefined
  if (status === "failed")
    return yield* output.ended("failed", `${route.name} transcription failed${error === undefined ? "" : `: ${error}`}`)
-  if (status !== "completed")
-    return yield* output.invalid(`${route.name} transcript ${context.token.transcriptID} has not finished`)
+  if (status !== "completed") return yield* output.pending(context.token.transcriptID)
  const duration = transcript.audio_duration ?? undefined
  return new TranscriptionResponse({
    text: transcript.text ?? "",
@@ -9,7 +9,6 @@ import {
  type CacheHint,
  type FinishReason,
  type FinishReasonDetails,
-  type JsonSchema,
  type LLMRequest,
  type LanguageModel,
  type ProviderMetadata,
@@ -26,7 +25,6 @@ import { BedrockCache } from "./utils/bedrock-cache.js"
 import { BedrockMedia } from "./utils/bedrock-media.js"
 import { Lifecycle } from "./utils/lifecycle.js"
 import { MistralToolID } from "./utils/mistral-tool-id.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { ToolStream } from "./utils/tool-stream.js"
 import { concatBytes } from "../utils/bytes.js"

@@ -221,22 +219,18 @@ type BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>
 // =============================================================================
 // Request Lowering
 // =============================================================================
-const lowerToolSpec = (tool: ToolDefinition, inputSchema: JsonSchema): BedrockToolSpec => ({
+const lowerToolSpec = (tool: ToolDefinition): BedrockToolSpec => ({
  toolSpec: {
    name: tool.name,
    ...(tool.description.trim().length > 0 ? { description: tool.description } : {}),
-    inputSchema: { json: inputSchema },
+    inputSchema: { json: tool.inputSchema },
  },
 })

-const lowerTools = (
-  model: LanguageModel,
-  breakpoints: BedrockCache.Breakpoints,
-  tools: ReadonlyArray<ToolDefinition>,
-): BedrockTool[] => {
+const lowerTools = (breakpoints: BedrockCache.Breakpoints, tools: ReadonlyArray<ToolDefinition>): BedrockTool[] => {
  const result: BedrockTool[] = []
  for (const tool of tools) {
-    result.push(lowerToolSpec(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, model)))
+    result.push(lowerToolSpec(tool))
    const cachePoint = BedrockCache.block(breakpoints, tool.cache)
    if (cachePoint) result.push(cachePoint)
  }
@@ -441,19 +435,39 @@ const isHighReasoningEffort = Schema.is(
  }),
 )

+const Options = Schema.Struct({
+  thinking: Schema.optional(Schema.Struct({ type: Schema.Literal("enabled"), budgetTokens: Schema.Number })),
+})
+export type OptionsInput = typeof Options.Type
+const decodeOptions = ProviderShared.validateWith(Schema.decodeUnknownEffect(Options))
+// Claude on Bedrock requires the thinking budget below `maxTokens`, with a minimum of 1,024.
+const MIN_THINKING_BUDGET = 1_024
+
 const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request: LLMRequest) {
  const toolChoice = request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined
  const flattened = ProviderShared.flattenToolRequest(request)
  const generation = request.generation
+  const options = yield* decodeOptions(request.providerOptions ?? {})
  const maxTokens =
    isNova2(request.model) && isHighReasoningEffort(request.http?.body) ? undefined : generation?.maxTokens
+  const thinking =
+    options.thinking === undefined
+      ? undefined
+      : {
+          type: "enabled",
+          budget_tokens: ProviderShared.fitThinkingBudget(
+            options.thinking.budgetTokens,
+            maxTokens,
+            MIN_THINKING_BUDGET,
+          ),
+        }
  // Bedrock-Claude shares Anthropic's 4-breakpoint cap. Spend the budget in
  // tools → system → messages order to favour the highest-impact prefixes.
  const breakpoints = BedrockCache.breakpoints(request.model.id)
  const toolConfig = (() => {
    if (flattened.tools.length === 0) return undefined
    return {
-      tools: lowerTools(request.model, breakpoints, flattened.tools),
+      tools: lowerTools(breakpoints, flattened.tools),
      // Converse has no native "none". Keep definitions stable for prompt
      // caching and omit only the unsupported choice.
      toolChoice,
@@ -487,9 +501,15 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
    system,
    inferenceConfig,
    toolConfig,
-    // Converse's base inferenceConfig has no topK; Anthropic/Nova accept it
-    // as a model-specific field, so it goes through additionalModelRequestFields.
-    additionalModelRequestFields: generation?.topK === undefined ? undefined : { top_k: generation.topK },
+    // Converse's base inferenceConfig has no topK or thinking; Anthropic/Nova accept them
+    // as model-specific fields, so they go through additionalModelRequestFields.
+    additionalModelRequestFields:
+      generation?.topK === undefined && thinking === undefined
+        ? undefined
+        : {
+            ...(generation?.topK === undefined ? {} : { top_k: generation.topK }),
+            ...(thinking === undefined ? {} : { thinking }),
+          },
  }
 })

@@ -31,13 +31,21 @@ export type Request = ImageRequestFor<BlackForestLabsImageOptions>
 // 2. Token and response schemas
 // ---------------------------------------------------------------------------

-/** Regional clusters answer on different hosts, so the returned `polling_url` is followed verbatim. */
-export const Token = Schema.Struct({ id: Schema.String, pollingURL: Schema.String })
+/**
+ * Regional clusters answer on different hosts, so the returned `polling_url` is followed verbatim. BFL reports the
+ * credit cost on submit, so it rides on the token; it is optional so tokens persisted before it existed still decode.
+ */
+export const Token = Schema.Struct({
+  id: Schema.String,
+  pollingURL: Schema.String,
+  cost: Schema.optionalKey(Schema.Number),
+})
 export type Token = Schema.Schema.Type<typeof Token>

 const StartResponse = Schema.Struct({
  id: Schema.String,
  polling_url: Schema.String,
+  cost: optionalNull(Schema.Number),
 })

 const Result = Schema.Struct({
@@ -145,7 +153,11 @@ const fromRequest = Effect.fn("BlackForestLabsImages.fromRequest")(function* (re
 // ---------------------------------------------------------------------------

 const decodeStart = route.decodeStarted(StartResponse, (value) => ({
-  token: { id: value.id, pollingURL: value.polling_url },
+  token: {
+    id: value.id,
+    pollingURL: value.polling_url,
+    ...(value.cost === undefined || value.cost === null ? {} : { cost: value.cost }),
+  },
  snapshot: { id: value.id, status: "queued" },
 }))

@@ -169,14 +181,16 @@ const decodeResult = Effect.fn("BlackForestLabsImages.decodeResult")(function* (
  if (isModerated(document.status)) return yield* output.contentPolicy(`${route.name} moderated the generation`)
  if (status === "failed" || status === "expired")
    return yield* output.ended(status, `${route.name} generation ${context.token.id} ended with ${document.status}`)
-  if (status !== "completed" || document.result === undefined || document.result === null)
+  if (status !== "completed") return yield* output.pending(context.token.id)
+  if (document.result === undefined || document.result === null)
    return yield* output.invalid(`${route.name} generation ${context.token.id} has no result`)
  const { sample, seed, prompt, ...rest } = document.result
+  // A settled `cost` on the result supersedes the submit-time cost carried on the token.
+  const cost = document.cost ?? context.token.cost
  return new ImageResponse({
    // `sample` is a signed URL that expires 10 minutes after the result is ready, so it is downloaded now.
    images: [yield* context.materialize(Media.url(sample))],
-    usage:
-      document.cost === undefined || document.cost === null ? undefined : { type: "credits", credits: document.cost },
+    usage: cost === undefined ? undefined : { type: "credits", credits: cost },
    providerMetadata: {
      bfl: { id: context.token.id, seed: seed ?? undefined, prompt: prompt ?? undefined, ...rest },
    },
@@ -67,6 +67,9 @@ const queryParameters = (request: Request) => {
 }

 const fromRequest = Effect.fn("DeepgramSpeech.fromRequest")(function* (request: Request) {
+  // Not in `unsupported`: that list would also reject `timestamps: false`, which asks for nothing.
+  if (request.timestamps === true)
+    return yield* route.unsupported("media.timestamps", `${route.name} does not return timestamps`)
  if (
    request.format !== undefined &&
    FORMATS[request.format] === undefined &&
@@ -86,24 +89,32 @@ const fromRequest = Effect.fn("DeepgramSpeech.fromRequest")(function* (request:
 // 6. Stream parsing
 // ---------------------------------------------------------------------------

-const HEADERLESS_ENCODINGS: Readonly<Record<string, SpeechStream.PcmEncoding>> = {
-  linear16: "pcm_s16le",
-  mulaw: "pcm_mulaw",
-  alaw: "pcm_alaw",
+/** Deepgram wraps raw encodings in WAV unless `container` is `none`, and defaults their sample rate per encoding. */
+const HEADERLESS_ENCODINGS: Readonly<
+  Record<string, { readonly encoding: SpeechStream.PcmEncoding; readonly sampleRate: number }>
+> = {
+  linear16: { encoding: "pcm_s16le", sampleRate: 24000 },
+  mulaw: { encoding: "pcm_mulaw", sampleRate: 8000 },
+  alaw: { encoding: "pcm_alaw", sampleRate: 8000 },
 }

 const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) => {
  const headers = context.http.headers
  const mediaType = headers["content-type"]
  const format = audioFormat(context.request)
-  const encoding = HEADERLESS_ENCODINGS[format.encoding ?? ""]
+  const headerless = HEADERLESS_ENCODINGS[format.encoding ?? ""]
+  const container = format.container ?? (headerless === undefined ? undefined : "wav")
  const requestID = headers["dg-request-id"]
  const modelName = headers["dg-model-name"]
  return SpeechStream.finish(route, state, {
-    ...(format.container === "none" && encoding !== undefined
-      ? SpeechStream.pcm(encoding, SpeechStream.sampleRate(mediaType), mediaType)
+    ...(container === "none" && headerless !== undefined
+      ? SpeechStream.pcm(
+          headerless.encoding,
+          SpeechStream.sampleRate(mediaType) ?? context.request.providerOptions?.sampleRate ?? headerless.sampleRate,
+          mediaType,
+        )
      : // Deepgram's default encoding is MP3; WAV is a container around any encoding.
-        { mediaType, info: { format: format.container === "wav" ? "wav" : (format.encoding ?? "mp3") } }),
+        { mediaType, info: { format: container === "wav" ? "wav" : (format.encoding ?? "mp3") } }),
    usage: SpeechStream.headerUsage("characters", headers["dg-char-count"]),
    providerMetadata:
      requestID === undefined && modelName === undefined
@@ -117,7 +128,7 @@ const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) =
 // ---------------------------------------------------------------------------

 export const protocol = MediaProtocol.stream<Request, SpeechEvent, Uint8Array, State>(route, {
-  unsupported: ["voice", "language", "instructions", "timestamps"],
+  unsupported: ["voice", "language", "instructions"],
  body: { from: fromRequest },
  frames: (bytes) => bytes,
  initial: () => ({ chunks: [] }),
@@ -6,6 +6,7 @@ import { mergeJsonRecords, type OpenString } from "../schema/index.js"
 import { TranscriptionModel, TranscriptionResponse, type TranscriptionRequestFor } from "../transcription.js"
 import { ProviderShared } from "./shared.js"
 import { MediaInput } from "./utils/media-input.js"
+import { SpeakerTurns } from "./utils/speaker-turns.js"

 const route = MediaProtocol.identity({ id: "deepgram-transcription", name: "Deepgram", provider: "deepgram" })
 export const DEFAULT_BASE_URL = "https://api.deepgram.com"
@@ -115,16 +116,6 @@ const speaker = (value: number | undefined) => (value === undefined ? undefined

 const wordText = (word: typeof Word.Type) => word.punctuated_word ?? word.word

-// Utterances split on pauses, not speakers: the v2 diarizer labels a whole utterance with one speaker even when its
-// words change speaker, so segments split each utterance at speaker changes.
-const speakerTurns = (words: ReadonlyArray<typeof Word.Type>) =>
-  words.reduce<Array<Array<typeof Word.Type>>>((turns, word) => {
-    const last = turns.at(-1)
-    if (last === undefined || last[0].speaker !== word.speaker) return [...turns, [word]]
-    last.push(word)
-    return turns
-  }, [])
-
 const decodeResponse = Effect.fn("DeepgramTranscription.decodeResponse")(function* (
  response: HttpClientResponse.HttpClientResponse,
 ) {
@@ -136,6 +127,8 @@ const decodeResponse = Effect.fn("DeepgramTranscription.decodeResponse")(functio
  const requestID = output.value.metadata?.request_id
  return new TranscriptionResponse({
    text: alternative.transcript,
+    // Utterances split on pauses, not speakers: the v2 diarizer labels a whole utterance with one speaker even when
+    // its words change speaker, so segments split each utterance at speaker changes.
    segments: output.value.results.utterances?.flatMap((utterance) =>
      utterance.words === undefined || utterance.words.length === 0
        ? [
@@ -146,7 +139,7 @@ const decodeResponse = Effect.fn("DeepgramTranscription.decodeResponse")(functio
              speaker: speaker(utterance.speaker),
            },
          ]
-        : speakerTurns(utterance.words).map((turn) => ({
+        : SpeakerTurns.group(utterance.words, (word) => word.speaker).map((turn) => ({
            text: turn.map(wordText).join(" "),
            startSeconds: turn[0].start,
            endSeconds: turn[turn.length - 1].end,
@@ -0,0 +1,211 @@
+import { Effect, Schema } from "effect"
+import type { HttpClientResponse } from "effect/unstable/http"
+import { MediaProtocol } from "../route/media-protocol.js"
+import { MediaRoute } from "../route/media.js"
+import { mergeJsonRecords, type OpenString } from "../schema/index.js"
+import { TranscriptionModel, TranscriptionResponse, type TranscriptionRequestFor } from "../transcription.js"
+import { mediaTypeExtension } from "../utils/media-type.js"
+import { ProviderShared, optionalNull } from "./shared.js"
+import { MediaInput } from "./utils/media-input.js"
+import { SpeakerTurns } from "./utils/speaker-turns.js"
+
+const route = MediaProtocol.identity({
+  id: "elevenlabs-transcription",
+  name: "ElevenLabs Transcription",
+  provider: "elevenlabs",
+})
+export const DEFAULT_BASE_URL = "https://api.elevenlabs.io"
+export const PATH = "/v1/speech-to-text"
+
+// ---------------------------------------------------------------------------
+// 1. Public model input
+// ---------------------------------------------------------------------------
+
+export type ElevenLabsTranscriptionOptions = {
+  readonly tag_audio_events?: boolean
+  readonly timestamps_granularity?: OpenString<"none" | "word" | "character">
+  readonly diarization_threshold?: number
+  readonly file_format?: OpenString<"pcm_s16le_16" | "other">
+  readonly temperature?: number
+  readonly seed?: number
+  readonly keyterms?: ReadonlyArray<string>
+  readonly no_verbatim?: boolean
+  readonly detect_speaker_roles?: boolean
+  readonly use_speaker_library?: boolean
+  readonly entity_detection?: string | ReadonlyArray<string>
+  readonly entity_redaction?: string | ReadonlyArray<string>
+  readonly entity_redaction_mode?: OpenString<"redacted" | "entity_type" | "enumerated_entity_type">
+} & Record<string, unknown>
+
+export type Request = TranscriptionRequestFor<ElevenLabsTranscriptionOptions>
+
+// ---------------------------------------------------------------------------
+// 2. Response schema
+// ---------------------------------------------------------------------------
+
+/** `type` is `word`, `spacing` (the whitespace between words), or `audio_event` (`(laughter)`). */
+const Token = Schema.Struct({
+  text: Schema.String,
+  type: Schema.String,
+  start: optionalNull(Schema.Number),
+  end: optionalNull(Schema.Number),
+  speaker_id: optionalNull(Schema.String),
+  logprob: optionalNull(Schema.Number),
+})
+type Token = Schema.Schema.Type<typeof Token>
+
+const Transcript = Schema.Struct({
+  language_code: optionalNull(Schema.String),
+  text: Schema.String,
+  words: optionalNull(Schema.Array(Token)),
+  transcription_id: optionalNull(Schema.String),
+  audio_duration_secs: optionalNull(Schema.Number),
+})
+
+// ---------------------------------------------------------------------------
+// 5. Request body construction
+// ---------------------------------------------------------------------------
+
+/** Speaker turns are the only segments ElevenLabs can produce, and `num_speakers` only applies to diarization. */
+const diarizes = (request: Request) =>
+  request.diarize === true || request.timestamps === "segment" || request.speakers !== undefined
+
+const RESERVED_FORM_FIELDS = new Set([
+  "file",
+  "cloud_storage_url",
+  "source_url",
+  "model_id",
+  "language_code",
+  "diarize",
+  "num_speakers",
+])
+
+const validate = (request: Request, overlay: Record<string, unknown>) => {
+  // Webhook requests return 202 with no transcript; the result arrives at a configured webhook instead.
+  if (overlay.webhook === true)
+    return Effect.fail(route.unsupported("transcription.webhook", `${route.name} does not deliver to webhooks`))
+  // Separate multichannel output replaces the transcript with one transcript per channel.
+  if (overlay.use_multi_channel === true && overlay.multichannel_output_style !== "combined")
+    return Effect.fail(
+      route.unsupported(
+        "transcription.multichannel",
+        `${route.name} returns a single transcript; set multichannel_output_style: "combined" to merge channels`,
+      ),
+    )
+  if (overlay.timestamps_granularity === "none" && (request.timestamps === "word" || diarizes(request)))
+    return Effect.fail(
+      route.unsupported(
+        "media.timestamps",
+        `${route.name} cannot return word timestamps or speaker turns with timestamps_granularity: "none"`,
+      ),
+    )
+  return Effect.void
+}
+
+const fromRequest = Effect.fn("ElevenLabsTranscription.fromRequest")(function* (request: Request) {
+  const overlay = mergeJsonRecords(request.providerOptions, request.http?.body) ?? {}
+  yield* validate(request, overlay)
+  const form = new FormData()
+  const url = ProviderShared.mediaUrl(request.audio)
+  if (url === undefined) {
+    const extension = mediaTypeExtension(request.audio.mediaType)
+    const audio = yield* MediaInput.inlineBytes(route.id, request.audio)
+    form.append(
+      "file",
+      MediaInput.blob(audio, request.audio.mediaType),
+      extension === undefined ? "audio" : `audio.${extension}`,
+    )
+  }
+  MediaInput.appendFields(
+    form,
+    {
+      model_id: request.model.id,
+      // `cloud_storage_url` is deprecated in favor of `source_url`, which accepts any hosted audio or video URL.
+      source_url: url,
+      language_code: request.language,
+      diarize: diarizes(request) ? true : undefined,
+      num_speakers: request.speakers,
+    },
+    { overlay, reserved: RESERVED_FORM_FIELDS, repeatArrays: "key" },
+  )
+  return MediaProtocol.multipart(form)
+})
+
+// ---------------------------------------------------------------------------
+// 6. Response decoding
+// ---------------------------------------------------------------------------
+
+const decodeTranscript = route.decodeJson(Transcript)
+
+type TimedWord = Token & { readonly start: number; readonly end: number }
+
+const isTimedWord = (token: Token): token is TimedWord =>
+  token.type === "word" && typeof token.start === "number" && typeof token.end === "number"
+
+/** Turn text keeps the provider's own spacing tokens, so languages written without spaces are not re-spaced. */
+const speakerTurns = (tokens: ReadonlyArray<Token>) =>
+  SpeakerTurns.group(
+    tokens.filter((token) => token.type === "word" || token.type === "spacing"),
+    (token) => token.speaker_id,
+  ).flatMap((turn) => {
+    const words = turn.filter(isTimedWord)
+    if (words.length === 0) return []
+    return [
+      {
+        text: turn
+          .map((token) => token.text)
+          .join("")
+          .trim(),
+        startSeconds: words[0].start,
+        endSeconds: words[words.length - 1].end,
+        speaker: turn[0].speaker_id ?? undefined,
+      },
+    ]
+  })
+
+const decodeResponse = Effect.fn("ElevenLabsTranscription.decodeResponse")(function* (
+  response: HttpClientResponse.HttpClientResponse,
+  context: MediaProtocol.DecodeContext<Request>,
+) {
+  const output = yield* decodeTranscript(response)
+  const transcript = output.value
+  const tokens = transcript.words ?? []
+  const duration = transcript.audio_duration_secs ?? undefined
+  const transcriptionID = transcript.transcription_id ?? undefined
+  return new TranscriptionResponse({
+    text: transcript.text,
+    segments: diarizes(context.request) ? speakerTurns(tokens) : undefined,
+    words: tokens.filter(isTimedWord).map((word) => ({
+      text: word.text,
+      startSeconds: word.start,
+      endSeconds: word.end,
+      speaker: word.speaker_id ?? undefined,
+      confidence: typeof word.logprob === "number" ? Math.exp(word.logprob) : undefined,
+    })),
+    language: transcript.language_code?.toLowerCase(),
+    durationSeconds: duration,
+    usage: duration === undefined ? undefined : { type: "seconds", seconds: duration },
+    providerMetadata: transcriptionID === undefined ? undefined : { elevenlabs: { transcriptionId: transcriptionID } },
+  })
+})
+
+// ---------------------------------------------------------------------------
+// 7. Protocol and route
+// ---------------------------------------------------------------------------
+
+export const protocol = MediaProtocol.inline<Request, TranscriptionResponse>(route, {
+  unsupported: ["prompt"],
+  body: { from: fromRequest },
+  response: { decode: decodeResponse },
+})
+
+export const model = (input: MediaRoute.ModelInput) =>
+  TranscriptionModel.fromRoute<ElevenLabsTranscriptionOptions>(
+    { protocol, baseURL: DEFAULT_BASE_URL, path: PATH },
+    input,
+  )
+
+export const ElevenLabsTranscription = {
+  protocol,
+  model,
+} as const
@@ -49,7 +49,7 @@ const QueueResult = Schema.StructWithRest(
 // ---------------------------------------------------------------------------

 const sizing = (model: string) => {
-  if (/^fal-ai\/(nano-banana|flux-pro\/v1\.1-ultra)/.test(model)) return "aspect_ratio"
+  if (/^fal-ai\/(nano-banana|flux-pro\/(v1\.1-ultra|kontext))/.test(model)) return "aspect_ratio"
  if (model.startsWith("fal-ai/flux")) return "image_size"
  return undefined
 }
@@ -63,20 +63,24 @@ const validate = (request: Request) => {
    return Effect.fail(route.unsupported("media.size", `${id} sizes by aspectRatio`))
  if (request.aspectRatio !== undefined && field === "image_size")
    return Effect.fail(route.unsupported("media.aspectRatio", `${id} sizes by size (image_size)`))
-  if ((request.images?.length ?? 0) > 1 && !isEdit(id))
+  if ((request.images?.length ?? 0) > 1 && !takesImageList(id))
    return Effect.fail(
-      route.unsupported("media.images", `${id} takes one image_url; use an /edit endpoint for several images`),
+      route.unsupported(
+        "media.images",
+        `${id} takes one image_url; use an /edit or /multi endpoint for several images`,
+      ),
    )
  return Effect.void
 }

-// `/edit` endpoints take an `image_urls` list; image-to-image, fill, and Ultra take one `image_url` (beside `mask_url`).
-const isEdit = (model: string) => model.endsWith("/edit")
+// `/edit` and `/multi` (Kontext) endpoints take an `image_urls` list; image-to-image, fill, and Ultra take one
+// `image_url` (beside `mask_url`).
+const takesImageList = (model: string) => model.endsWith("/edit") || model.endsWith("/multi")

 const fromRequest = Effect.fn("FalImages.fromRequest")(function* (request: Request) {
  yield* validate(request)
  const images = yield* Effect.forEach(request.images ?? [], (image) => FalQueue.mediaUrl(image, route.name))
-  const edit = isEdit(request.model.id)
+  const list = takesImageList(request.model.id)
  return MediaProtocol.json(
    mergeJsonRecords(
      {
@@ -86,8 +90,8 @@ const fromRequest = Effect.fn("FalImages.fromRequest")(function* (request: Reque
        image_size: request.size === undefined ? undefined : MediaInput.dimensions(request.size),
        aspect_ratio: request.aspectRatio,
        output_format: request.format,
-        image_urls: edit && images.length > 0 ? images : undefined,
-        image_url: edit ? undefined : images[0],
+        image_urls: list && images.length > 0 ? images : undefined,
+        image_url: list ? undefined : images[0],
        mask_url: request.mask === undefined ? undefined : yield* FalQueue.mediaUrl(request.mask, route.name),
      },
      request.providerOptions,
@@ -112,12 +116,14 @@ const decodeResult = Effect.fn("FalImages.decodeResult")(function* (
  // With the safety checker on, flagged images come back blacked out rather than omitted.
  const flagged = (has_nsfw_concepts ?? []).flatMap((value, index) => (value ? [index] : []))
  return new ImageResponse({
-    images: images.map((image) =>
-      Media.url(image.url, {
-        mediaType: image.content_type ?? undefined,
-        info: { width: image.width ?? undefined, height: image.height ?? undefined },
-      }),
-    ),
+    images: images.map((image) => {
+      const info = { width: image.width ?? undefined, height: image.height ?? undefined }
+      // `sync_mode: true` returns data URIs instead of hosted URLs.
+      return (
+        Media.parseDataUrl(image.url, { info }) ??
+        Media.url(image.url, { mediaType: image.content_type ?? undefined, info })
+      )
+    }),
    notices:
      flagged.length === 0
        ? undefined
@@ -11,7 +11,6 @@ import {
  Usage,
  type FinishReason,
  type LLMRequest,
-  type LanguageModel,
  type MediaPart,
  type ProviderMetadata,
  type ProviderOptions,
@@ -24,11 +23,12 @@ import { Media } from "../media.js"
 import { JsonObject, knownString, lenient, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { GeminiGenerateContent } from "./utils/gemini-generate-content.js"
 import { Lifecycle } from "./utils/lifecycle.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"

 const ADAPTER = "gemini"
 // Google documents this sentinel for replaying Gemini 3 function calls after their original signature was lost.
 const SKIP_THOUGHT_SIGNATURE_VALIDATOR = "skip_thought_signature_validator"
+// Gemini 2.5 rejects a budget under the model's minimum: 512 on Flash-Lite, the highest, and 128 on Pro.
+const MIN_THINKING_BUDGET = 512
 export const DEFAULT_BASE_URL = "https://generativelanguage.googleapis.com/v1beta"

 // Gemini 3 rejects replayed function calls without a thought signature. Google's SDKs avoid that in normal chats by
@@ -268,12 +268,11 @@ interface ParserState {
 // =============================================================================
 // Request Lowering
 // =============================================================================
-// Tool schemas go in `parametersJsonSchema`, which accepts standard JSON Schema. Gemini's schema
-// rules are this API's default, including for tuned endpoints whose IDs do not name Gemini.
-const lowerTool = (tool: ToolDefinition, model: LanguageModel) => ({
+// Tool schemas go in `parametersJsonSchema`, which accepts standard JSON Schema.
+const lowerTool = (tool: ToolDefinition) => ({
  name: tool.name,
  description: tool.description,
-  parametersJsonSchema: ToolSchemaProjection.modelCompatibility(tool.inputSchema, model, "gemini"),
+  parametersJsonSchema: tool.inputSchema,
 })

 const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -452,10 +451,22 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
    presencePenalty: generation?.presencePenalty,
    seed: generation?.seed,
    stopSequences: generation?.stop,
+    // Gemini accepts a budget above `maxOutputTokens`, but thinking then leaves the answer empty.
    thinkingConfig:
      options.thinkingConfig === undefined
        ? undefined
-        : { ...options.thinkingConfig, includeThoughts: options.thinkingConfig.includeThoughts ?? true },
+        : {
+            ...options.thinkingConfig,
+            includeThoughts: options.thinkingConfig.includeThoughts ?? true,
+            thinkingBudget:
+              options.thinkingConfig.thinkingBudget === undefined
+                ? undefined
+                : ProviderShared.fitThinkingBudget(
+                    options.thinkingConfig.thinkingBudget,
+                    generation?.maxTokens,
+                    MIN_THINKING_BUDGET,
+                  ),
+          },
  }

  return {
@@ -468,7 +479,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
    tools: hasTools
      ? [
          {
-            functionDeclarations: flattened.tools.map((tool) => lowerTool(tool, request.model)),
+            functionDeclarations: flattened.tools.map(lowerTool),
          },
        ]
      : undefined,
@@ -515,19 +526,7 @@ const mapFinishReason = (finishReason: string | undefined, hasToolCalls: boolean
  if (finishReason === undefined) return hasToolCalls ? "tool-calls" : "unknown"
  if (finishReason === "STOP") return hasToolCalls ? "tool-calls" : "stop"
  if (finishReason === "MAX_TOKENS") return "length"
-  if (
-    finishReason === "IMAGE_SAFETY" ||
-    finishReason === "RECITATION" ||
-    finishReason === "SAFETY" ||
-    finishReason === "BLOCKLIST" ||
-    finishReason === "PROHIBITED_CONTENT" ||
-    finishReason === "SPII" ||
-    finishReason === "MODEL_ARMOR" ||
-    finishReason === "IMAGE_PROHIBITED_CONTENT" ||
-    finishReason === "IMAGE_RECITATION" ||
-    finishReason === "LANGUAGE"
-  )
-    return "content-filter"
+  if (GeminiGenerateContent.contentFiltered(finishReason)) return "content-filter"
  if (
    finishReason === "MALFORMED_FUNCTION_CALL" ||
    finishReason === "UNEXPECTED_TOOL_CALL" ||
@@ -804,6 +803,8 @@ export const protocol = Protocol.make({
    schema: GeminiBody,
    from: fromRequest,
  },
+  // Gemini's schema rules are this API's default, including for tuned endpoints whose IDs do not name Gemini.
+  sanitizer: "gemini",
  stream: {
    event: Protocol.jsonEvent(GeminiEvent),
    initial: (request) => ({
@@ -101,7 +101,7 @@ const generationConfig = (request: Request) => {
 const fromRequest = Effect.fn("GoogleImages.fromRequest")(function* (request: Request) {
  if (request.n !== undefined && request.n > 1)
    return yield* route.unsupported(
-      "image.n",
+      "media.n",
      `${route.name} generates one image per request; call it once per image instead of n=${request.n}`,
    )
  const parts = yield* Effect.forEach(request.images ?? [], (image) =>
@@ -56,10 +56,18 @@ interface State extends SpeechStream.Audio, GeminiGenerateContent.Metadata {
 // ---------------------------------------------------------------------------

 const fromRequest = Effect.fn("GoogleSpeech.fromRequest")(function* (request: MediaProtocol.Addressed<Request>) {
+  // Not in `unsupported`: that list would also reject `timestamps: false`, which asks for nothing.
+  if (request.timestamps === true)
+    return yield* route.unsupported("media.timestamps", `${route.name} does not return timestamps`)
+  if (request.format === "pcm" && request.mode === "generate" && /^gemini-3\.8-.*-tts(?:-|$)/.test(request.model.id))
+    return yield* route.unsupported(
+      "media.format",
+      `${route.name} returns WAV by default for Gemini 3.8 TTS unary requests; omit the format to accept it`,
+    )
  if (request.format !== undefined && request.format !== "pcm")
    return yield* route.unsupported(
      "media.format",
-      `${route.name} only returns raw PCM; request format "pcm" or omit it, then wrap the samples yourself`,
+      `${route.name} only accepts raw PCM as an explicit format; omit it to accept the provider's default output`,
    )
  const voiceName = SpeechStream.voiceID(request.voice)
  return MediaProtocol.json(
@@ -94,16 +102,29 @@ const step = Effect.fn("GoogleSpeech.step")(function* (state: State, frame: stri
    part.inlineData === undefined ? [] : [part.inlineData],
  )
  const next: State = { ...GeminiGenerateContent.track(state, chunk), mimeType: state.mimeType ?? audio[0]?.mimeType }
-  return [next, audio.flatMap((part) => SpeechStream.delta(next, part.data)[1])] as const
+  const events = audio.flatMap((part) => SpeechStream.delta(next, part.data)[1])
+  const withheld = next.chunks.length === 0 ? GeminiGenerateContent.withheld(route.name, chunk, frame) : undefined
+  if (withheld !== undefined) return yield* withheld
+  return [next, events] as const
 })

-const finish = (state: State) => {
+const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) => {
+  if (state.finishReason === undefined) return Effect.fail(route.incomplete())
  const sampleRate = SpeechStream.sampleRate(state.mimeType) ?? DEFAULT_SAMPLE_RATE
+  const output =
+    state.mimeType?.split(";")[0]?.toLowerCase() === "audio/wav"
+      ? SpeechStream.container("wav", sampleRate)
+      : SpeechStream.pcm("pcm_s16le", sampleRate, state.mimeType ?? `audio/L16;codec=pcm;rate=${sampleRate}`)
+  if (context.request.format === "pcm" && output.info.format !== "pcm")
+    return Effect.fail(
+      route.frameError(`Google Speech returned ${output.info.format} instead of the requested raw PCM`),
+    )
  return SpeechStream.finish(route, state, {
-    ...SpeechStream.pcm("pcm_s16le", sampleRate, state.mimeType ?? `audio/L16;codec=pcm;rate=${sampleRate}`),
+    ...output,
    usage: GeminiGenerateContent.usage(state.usage),
+    notices: GeminiGenerateContent.notices(route.name, state),
    providerMetadata: GeminiGenerateContent.providerMetadata(state),
-    detail: state.finishReason === undefined ? undefined : `finish reason: ${state.finishReason}`,
+    detail: `finish reason: ${state.finishReason}`,
  })
 }

@@ -112,7 +133,7 @@ const finish = (state: State) => {
 // ---------------------------------------------------------------------------

 export const protocol = MediaProtocol.stream<Request, SpeechEvent, string, State>(route, {
-  unsupported: ["instructions", "speed", "timestamps"],
+  unsupported: ["instructions", "speed"],
  body: { from: fromRequest },
  frames: (bytes, context) => GeminiGenerateContent.frames(bytes, context.request.mode),
  initial: () => ({ chunks: [] }),
@@ -154,6 +154,9 @@ const step = Effect.fn("GoogleTranscription.step")(function* (state: State, fram
    .filter((item) => item.length > 0)
    .join(" ")
  const delta = text.length === 0 || state.text.length === 0 ? text : ` ${text}`
+  const withheld =
+    state.text.length + delta.length === 0 ? GeminiGenerateContent.withheld(route.name, chunk, frame) : undefined
+  if (withheld !== undefined) return yield* withheld
  const events: ReadonlyArray<TranscriptionEvent> = [
    ...(delta.length === 0 ? [] : [TranscriptionTextDeltaEvent.make({ delta })]),
    ...segments.map((segment) => TranscriptionSegmentEvent.make({ segment })),
@@ -169,6 +172,7 @@ const finish = (state: State) => {
      segments: state.segments.length === 0 ? undefined : state.segments,
      words: state.words.length === 0 ? undefined : state.words,
      usage: GeminiGenerateContent.usage(state.usage),
+      notices: GeminiGenerateContent.notices(route.name, state),
      providerMetadata: GeminiGenerateContent.providerMetadata(state),
    }),
  ])
@@ -36,7 +36,9 @@ const StartResponse = Schema.Struct({ name: Schema.String })

 const Operation = Schema.Struct({
  done: Schema.optional(Schema.Boolean),
-  error: Schema.optional(Schema.Struct({ message: Schema.optional(Schema.String) })),
+  error: Schema.optional(
+    Schema.Struct({ code: Schema.optional(Schema.Number), message: Schema.optional(Schema.String) }),
+  ),
  response: Schema.optional(
    Schema.Struct({
      generateVideoResponse: Schema.optional(
@@ -60,6 +62,16 @@ const Operation = Schema.Struct({
  metadata: Schema.optional(Schema.Unknown),
 })

+// Operation errors are `google.rpc.Status`; unlisted codes (INTERNAL, UNAVAILABLE, ...) are provider-side.
+const FAILURE = {
+  3: "InvalidRequest", // INVALID_ARGUMENT
+  7: "Authentication", // PERMISSION_DENIED
+  8: "RateLimit", // RESOURCE_EXHAUSTED
+  9: "InvalidRequest", // FAILED_PRECONDITION
+  11: "InvalidRequest", // OUT_OF_RANGE
+  16: "Authentication", // UNAUTHENTICATED
+} as const satisfies Record<number, MediaProtocol.Failure>
+
 // ---------------------------------------------------------------------------
 // 5. Request body construction
 // ---------------------------------------------------------------------------
@@ -149,12 +161,12 @@ const decodeResult = Effect.fn("GoogleVideo.decodeResult")(function* (
  const output = yield* decodeOperation(response)
  const operation = output.value
  const status = statusOf(operation)
-  if (status === "running")
-    return yield* output.invalid(`${route.name} operation ${context.token.operation} has not finished`)
+  if (status === "running") return yield* output.pending(context.token.operation)
  if (status === "failed")
    return yield* output.ended(
      "failed",
      `${route.name} operation failed${operation.error?.message === undefined ? "" : `: ${operation.error.message}`}`,
+      MediaProtocol.failure(FAILURE, operation.error?.code),
    )
  const generated = operation.response?.generateVideoResponse
  // Downloads require the same API key as the poll; the asset carries it transiently and follows the redirect.
@@ -5,7 +5,6 @@ import { LLMEvent, LLMRequest, Message, ToolResultPart } from "../schema/index.j
 import { OpenResponses } from "./open-responses.js"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { ResponsesHostedTools } from "./utils/responses-hosted-tools.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { detectMediaType } from "../utils/media-type.js"

 const ADAPTER = "meta-responses"
@@ -103,12 +102,7 @@ const fromRequest = Effect.fn("MetaResponses.fromRequest")(function* (request: L
        ? undefined
        : yield* Effect.forEach(projected.tools, (tool) =>
            Effect.gen(function* () {
-              if (tool.native === undefined)
-                return yield* OpenResponses.lowerTool(
-                  NAME,
-                  tool,
-                  ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model),
-                )
+              if (tool.native === undefined) return yield* OpenResponses.lowerTool(NAME, tool)
              return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(NativeTool))(tool.native.meta)
            }),
          ),
@@ -13,7 +13,6 @@ import {
  UnknownProviderError,
  Usage,
  type FinishReasonDetails,
-  type JsonSchema,
  type LLMRequest,
  type MediaPart,
  type ToolCallPart,
@@ -23,7 +22,6 @@ import { classifyProviderFailure } from "../provider-error.js"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { Lifecycle } from "./utils/lifecycle.js"
 import { MistralToolID } from "./utils/mistral-tool-id.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { ToolStream } from "./utils/tool-stream.js"

 const ADAPTER = "mistral-chat"
@@ -368,9 +366,9 @@ const lowerMessages = Effect.fn("MistralChat.lowerMessages")(function* (request:
  return messages
 })

-const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): MistralTool => ({
+const lowerTool = (tool: ToolDefinition): MistralTool => ({
  type: "function",
-  function: { name: tool.name, description: tool.description, parameters: inputSchema, strict: false },
+  function: { name: tool.name, description: tool.description, parameters: tool.inputSchema, strict: false },
 })

 export const fromRequest = Effect.fn("MistralChat.fromRequest")(function* (request: LLMRequest) {
@@ -396,12 +394,7 @@ export const fromRequest = Effect.fn("MistralChat.fromRequest")(function* (reque
  return {
    model: request.model.id,
    messages: yield* lowerMessages(flattened.request),
-    tools:
-      flattened.tools.length > 0
-        ? flattened.tools.map((tool) =>
-            lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model)),
-          )
-        : undefined,
+    tools: flattened.tools.length > 0 ? flattened.tools.map(lowerTool) : undefined,
    tool_choice: toolChoice,
    stream: true as const,
    max_tokens: request.generation?.maxTokens,
@@ -8,7 +8,6 @@ import {
  ProviderInternalError,
  Usage,
  type FinishReason,
-  type JsonSchema,
  type LLMRequest,
  type MediaPart,
  type ProviderMetadata,
@@ -24,7 +23,6 @@ import { classifyProviderFailure } from "../provider-error.js"
 import { effortUpdate } from "../effort-updates.js"
 import { OpenResponsesOptions } from "./utils/open-responses-options.js"
 import { Lifecycle } from "./utils/lifecycle.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { ToolStream } from "./utils/tool-stream.js"

 const ADAPTER = "open-responses"
@@ -443,23 +441,24 @@ interface ReasoningStreamItem {
 // =============================================================================
 // Request Lowering
 // =============================================================================
-export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (
-  protocolName: string,
-  tool: ToolDefinition,
-  inputSchema: JsonSchema,
-) {
+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 {
    type: "function" as const,
    name: tool.name,
    description: tool.description,
-    parameters: inputSchema,
+    parameters: tool.inputSchema,
    // The common tool definition does not currently express Responses strict-schema policy.
    strict: false,
  }
 })

+export const lowerTools = (tools: ReadonlyArray<ToolDefinition>, adapter: ProviderAdapter) =>
+  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"]>) =>
  ProviderShared.matchToolChoice(protocolName, toolChoice, {
    auto: () => "auto" as const,
@@ -821,14 +820,7 @@ export const fromRequestWithAdapter = Effect.fn("OpenResponses.fromRequestWithAd
  return {
    ...(yield* lowerConversation(projected.request, adapter)),
    ...lowerGeneration(request),
-    tools:
-      projected.tools.length === 0
-        ? undefined
-        : yield* Effect.forEach(projected.tools, (tool) =>
-            tool.native !== undefined && adapter.nativeTool
-              ? adapter.nativeTool(tool.native)
-              : lowerTool(adapter.name, tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model)),
-          ),
+    tools: projected.tools.length === 0 ? undefined : yield* lowerTools(projected.tools, adapter),
    tool_choice:
      allowedToolChoice(request) ??
      (request.toolChoice ? yield* lowerToolChoice(adapter.name, request.toolChoice) : undefined),
@@ -17,7 +17,6 @@ import {
  type FinishReason,
  type FinishReasonDetails,
  type CacheHint,
-  type JsonSchema,
  type LLMRequest,
  type MediaPart,
  type ReasoningPart,
@@ -29,7 +28,6 @@ import { classifyProviderFailure } from "../provider-error.js"
 import { isRecord, JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { OpenAIOptions } from "./utils/openai-options.js"
 import { Lifecycle } from "./utils/lifecycle.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { ToolStream } from "./utils/tool-stream.js"

 const ADAPTER = "openai-chat"
@@ -330,17 +328,12 @@ interface LoweringOptions {
  readonly toolCallID?: (id: string) => string
 }

-const lowerTool = (
-  tool: ToolDefinition,
-  inputSchema: JsonSchema,
-  options: LoweringOptions,
-  supportsStrictMode: boolean,
-): OpenAIChatTool => ({
+const lowerTool = (tool: ToolDefinition, options: LoweringOptions, supportsStrictMode: boolean): OpenAIChatTool => ({
  type: "function",
  function: {
    name: tool.name,
    description: tool.description,
-    parameters: inputSchema,
+    parameters: tool.inputSchema,
    ...(supportsStrictMode ? { strict: false } : {}),
  },
  cache_control: options.cacheControl?.(tool.cache),
@@ -825,14 +818,7 @@ export const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (
        ? hasHistory
          ? []
          : undefined
-        : flattened.tools.map((tool) =>
-            lowerTool(
-              tool,
-              ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model),
-              options,
-              supportsStrictMode,
-            ),
-          ),
+        : flattened.tools.map((tool) => lowerTool(tool, options, supportsStrictMode)),
    tool_choice: hasActiveTools && request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
    stream: true as const,
    ...(supportsUsageInStreaming ? { stream_options: { include_usage: true } } : {}),
@@ -48,15 +48,17 @@ const Usage = Schema.Struct({
  output_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
 })

-const OpenAIImageResponse = Schema.Struct({
-  data: Schema.Array(
-    Schema.Struct({
-      b64_json: Schema.optional(Schema.String),
-      url: Schema.optional(Schema.String),
-      revised_prompt: Schema.optional(Schema.String),
-    }),
-  ),
+/** What the provider actually rendered; it can differ from the request when `auto` or a default applied. */
+const Settings = {
  output_format: Schema.optional(Schema.String),
+  size: Schema.optional(Schema.String),
+  quality: Schema.optional(Schema.String),
+  background: Schema.optional(Schema.String),
+}
+
+const OpenAIImageResponse = Schema.Struct({
+  data: Schema.Array(Schema.Struct({ b64_json: Schema.String })),
+  ...Settings,
  usage: Schema.optional(Usage),
 })

@@ -69,11 +71,13 @@ const StreamEvent = Schema.Union([
    type: Schema.Literals(["image_generation.partial_image", "image_edit.partial_image"]),
    b64_json: Schema.String,
    partial_image_index: Schema.Number,
+    ...Settings,
    output_format: Schema.String,
  }),
  Schema.Struct({
    type: Schema.Literals(["image_generation.completed", "image_edit.completed"]),
    b64_json: Schema.String,
+    ...Settings,
    output_format: Schema.String,
    usage: Schema.optional(Usage),
  }),
@@ -92,6 +96,9 @@ type Frame = string | { readonly document: string; readonly requested: string |
 interface State {
  readonly completed: number
  readonly format?: string
+  readonly size?: string
+  readonly quality?: string
+  readonly background?: string
  readonly usage?: MediaUsage
 }

@@ -110,10 +117,6 @@ const nativeOptions = (options: OpenAIImageOptions | undefined) => {

 const streamOptions = (request: MediaProtocol.Addressed<Request>) => {
  if (request.mode !== "stream") return Effect.succeed(undefined)
-  if (request.model.id.startsWith("dall-e"))
-    return Effect.fail(
-      route.unsupported("media.stream", `${request.model.id} does not stream; use Image.generate or a GPT image model`),
-    )
  if (request.n !== undefined && request.n > 1)
    return Effect.fail(
      route.unsupported("media.n", `${route.name} streams one image; use Image.generate for n=${request.n}`),
@@ -194,21 +197,34 @@ const usage = (value: Schema.Schema.Type<typeof Usage> | undefined): MediaUsage
        details: { openai: value },
      }

-const eventImage = (frame: string, label: string, data: string, format: string) =>
+/** `size` echoes the rendered `WIDTHxHEIGHT`; `auto` or any other value leaves the dimensions unknown. */
+const info = (format: string, size: string | undefined): Media.Info => {
+  const match = size?.match(/^(\d+)x(\d+)$/)
+  return match ? { format, width: Number(match[1]), height: Number(match[2]) } : { format }
+}
+
+const eventImage = (frame: string, label: string, data: string, format: string, size: string | undefined) =>
  MediaInput.decodedAsset((message, cause) => route.frameError(message, frame, cause), label, data, `image/${format}`, {
-    info: { format },
+    info: info(format, size),
  })

 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) {
-    const image = yield* eventImage(frame, `${route.name} partial image`, event.b64_json, format)
+    const image = yield* eventImage(frame, `${route.name} partial image`, event.b64_json, format, event.size)
    return [state, [ImagePartialEvent.make({ index: event.partial_image_index, image })]] as const
  }
-  const image = yield* eventImage(frame, `${route.name} result ${state.completed}`, event.b64_json, format)
+  const image = yield* eventImage(frame, `${route.name} result ${state.completed}`, event.b64_json, format, event.size)
  return [
-    { ...state, completed: state.completed + 1, format, usage: usage(event.usage) },
+    {
+      completed: state.completed + 1,
+      format,
+      size: event.size,
+      quality: event.quality,
+      background: event.background,
+      usage: usage(event.usage),
+    },
    [ImageOutputEvent.make({ index: state.completed, image })],
  ] as const
 })
@@ -219,16 +235,20 @@ const onDocument = Effect.fn("OpenAIImages.onDocument")(function* (frame: Exclud
    Effect.mapError((cause) => invalid(`${route.name} returned an invalid response`, cause)),
  )
  const format = decoded.output_format ?? frame.requested ?? "png"
-  const mediaType = `image/${format}`
  const images = yield* Effect.forEach(decoded.data, (item, index) =>
-    MediaInput.imageOutput(invalid, `${route.name} result ${index}`, item, mediaType, {
-      info: { format },
-      providerMetadata:
-        item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
+    MediaInput.decodedAsset(invalid, `${route.name} result ${index}`, item.b64_json, `image/${format}`, {
+      info: info(format, decoded.size),
    }),
  )
  if (images.length === 0) return yield* invalid(`${route.name} returned no images`)
-  const state: State = { completed: images.length, format, usage: usage(decoded.usage) }
+  const state: State = {
+    completed: images.length,
+    format,
+    size: decoded.size,
+    quality: decoded.quality,
+    background: decoded.background,
+    usage: usage(decoded.usage),
+  }
  return [state, images.map((image, index) => ImageOutputEvent.make({ index, image }))] as const
 })

@@ -237,7 +257,17 @@ const step = (state: State, frame: Frame) => (typeof frame === "string" ? onEven
 const finish = (state: State) => {
  if (state.completed === 0) return Effect.fail(route.incomplete())
  return Effect.succeed([
-    ImageFinishEvent.make({ usage: state.usage, providerMetadata: { openai: { outputFormat: state.format } } }),
+    ImageFinishEvent.make({
+      usage: state.usage,
+      providerMetadata: {
+        openai: {
+          outputFormat: state.format,
+          size: state.size,
+          quality: state.quality,
+          background: state.background,
+        },
+      },
+    }),
  ])
 }

@@ -5,20 +5,12 @@ import { Auth } from "../route/auth.js"
 import { Endpoint } from "../route/endpoint.js"
 import { Protocol } from "../route/protocol.js"
 import { HttpTransport } from "../route/transport/index.js"
-import {
-  LLMRequest,
-  mergeJsonRecords,
-  type JsonSchema,
-  type LanguageModel,
-  type ToolDefinition,
-  type ToolEntry,
-} from "../schema/index.js"
+import { LLMRequest, type ToolDefinition, type ToolEntry } from "../schema/index.js"
 import { resolveEffortUpdates } from "../effort-updates.js"
 import { OpenResponses } from "./open-responses.js"
 import { OpenResponsesOptions } from "./utils/open-responses-options.js"
 import { JsonObject, optionalArray, optionalNull, ProviderShared } from "./shared.js"
 import { ResponsesHostedTools } from "./utils/responses-hosted-tools.js"
-import { ToolSchemaProjection } from "./utils/tool-schema.js"
 import { OpenResponsesChannel } from "./open-responses-channel.js"
 import { ResponsesCompaction } from "./utils/responses-compaction.js"
 import { ResponsesCheckpoint } from "./utils/responses-checkpoint.js"
@@ -143,11 +135,6 @@ export const CompactionTrigger = Schema.Struct({ type: Schema.Literal("compactio
 const CheckpointBody = Schema.Struct({
  ...OpenAIResponsesBody.fields,
  input: Schema.Array(Schema.Union([OpenAIResponsesInputItem, CompactionTrigger])),
-  store: Schema.Literal(false),
-  prompt_cache_retention: optionalNull(Schema.String),
-  prompt_cache_options: optionalNull(
-    Schema.Struct({ mode: Schema.optional(Schema.String), ttl: Schema.optional(Schema.String) }),
-  ),
 })

 const adapter = {
@@ -156,12 +143,14 @@ const adapter = {
  restoreHostedToolItem: (item: unknown) => (Schema.is(OpenAIResponsesHostedToolItem)(item) ? item : undefined),
 } satisfies OpenResponses.ProviderAdapter

-// Only GPT-6 Astra accepts `configuration_update`, and never alongside automatic `context_management` compaction.
+// GPT-6 Astra, Sol, and Luna accept `configuration_update` only in standard mode (not `reasoning.mode: "pro"` or
+// `-pro` slugs), and never alongside automatic `context_management` compaction.
 const supportsEffortUpdates = (request: LLMRequest) => {
  if (request.providerOptions?.contextManagement !== undefined) return false
+  if (Schema.is(Schema.Struct({ mode: Schema.Literal("pro") }))(request.http?.body?.reasoning)) return false
  const override = request.model.compatibility?.supportsEffortUpdates
  if (override !== undefined) return override
-  return /(?:^|\/)gpt-6-astra$/i.test(request.model.id)
+  return /(?:^|\/)gpt-6-(?:astra|sol|luna)$/i.test(request.model.id)
 }

 const nativeImageToolInput = (tool: ToolDefinition) => {
@@ -174,20 +163,19 @@ const nativeImageTool = (tool: ToolDefinition) => {
  return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
 }

-const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition, inputSchema: JsonSchema) {
+const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition) {
  const native = nativeImageToolInput(tool)
  if (native !== undefined) {
    if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
    return yield* ProviderShared.invalidRequest("OpenAI Responses image generation tool options are invalid")
  }
-  return yield* OpenResponses.lowerTool(NAME, tool, inputSchema)
+  return yield* OpenResponses.lowerTool(NAME, tool)
 })

 // 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.fn("OpenAIResponses.lowerToolEntry")(function* (tool: ToolEntry, model: LanguageModel) {
-  if (tool.type === "tool")
-    return yield* lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, model))
+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.
  return {
@@ -195,11 +183,13 @@ const lowerToolEntry = Effect.fn("OpenAIResponses.lowerToolEntry")(function* (to
    name: tool.name,
    description: tool.description ?? `Tools in the ${tool.name} namespace.`,
    tools: yield* Effect.forEach(ProviderShared.flattenTools(tool.tools), (leaf) =>
-      OpenResponses.lowerTool(NAME, leaf, ToolSchemaProjection.modelCompatibility(leaf.inputSchema, model)),
+      OpenResponses.lowerTool(NAME, leaf),
    ),
  }
 })

+const lowerTools = (request: LLMRequest) => Effect.forEach(request.tools, lowerToolEntry)
+
 const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>, tools: ReadonlyArray<ToolEntry>) =>
  ProviderShared.matchToolChoice(NAME, toolChoice, {
    auto: () => "auto" as const,
@@ -223,10 +213,7 @@ const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request:
    ...(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 })),
-    tools:
-      request.tools.length === 0
-        ? undefined
-        : yield* Effect.forEach(request.tools, (tool) => lowerToolEntry(tool, request.model)),
+    tools: request.tools.length === 0 ? undefined : yield* lowerTools(request),
    tool_choice:
      request.tools.length === 0
        ? undefined
@@ -238,7 +225,6 @@ const fromRequest = Effect.fn("OpenAIResponses.fromRequest")(function* (request:
 const checkpointBody = {
  schema: CheckpointBody,
  from: Effect.fn("OpenAIResponses.checkpointBody")(function* (request: LLMRequest) {
-    const native = yield* fromRequest(LLMRequest.update(request, { toolChoice: undefined }))
    const overlay = request.http?.body
    // Complete history is required for stateless replay and SSE recovery. Raw input overrides bypass that contract.
    if (
@@ -249,18 +235,13 @@ const checkpointBody = {
      return yield* ProviderShared.invalidRequest(
        "Trigger compaction requires complete canonical history, not an input or continuation override",
      )
-    return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(CheckpointBody))({
-      ...mergeJsonRecords(native, overlay),
-      input: [...native.input, { type: "compaction_trigger" }],
-      stream: true,
-      store: false,
-      parallel_tool_calls: true,
-      tool_choice: undefined,
-      context_management: undefined,
-      text: undefined,
-      max_output_tokens: undefined,
-      max_tool_calls: undefined,
-    })
+    if (overlay?.stream !== undefined && overlay.stream !== true)
+      return yield* ProviderShared.invalidRequest("Trigger compaction requires a streamed response")
+    const native = yield* fromRequest(request)
+    return {
+      ...native,
+      input: [...native.input, { type: "compaction_trigger" as const }],
+    }
  }),
 }

@@ -342,7 +323,10 @@ export const transport = channelTransport({
 })

 export const route = Route.make({
-  compact: { endpoint: ResponsesCompaction.make(adapter), trigger: ResponsesCheckpoint.make(checkpointBody) },
+  compact: {
+    endpoint: ResponsesCompaction.make(adapter, lowerTools),
+    trigger: ResponsesCheckpoint.make(checkpointBody),
+  },
  id: ADAPTER,
  provider: "openai",
  providerMetadataKey: "openai",
@@ -60,7 +60,17 @@ interface State extends SpeechStream.Audio {
 // `sse` is not supported for `tts-1` or `tts-1-hd`; those models stream the raw audio body instead.
 const supportsSse = (model: string) => !/^tts-1(-hd)?(-|$)/.test(model)

+const FORMATS = new Set(["mp3", "opus", "aac", "flac", "wav", "pcm"])
+
 const fromRequest = Effect.fn("OpenAISpeech.fromRequest")(function* (request: MediaProtocol.Addressed<Request>) {
+  // Not in `unsupported`: that list would also reject `timestamps: false`, which asks for nothing.
+  if (request.timestamps === true)
+    return yield* route.unsupported("media.timestamps", `${route.name} does not return timestamps`)
+  if (request.format !== undefined && !FORMATS.has(request.format))
+    return yield* route.unsupported(
+      "media.format",
+      `${route.name} supports the mp3, opus, aac, flac, wav, and pcm formats, not "${request.format}"`,
+    )
  return MediaProtocol.json(
    mergeJsonRecords(
      {
@@ -109,7 +119,9 @@ const onEvent = Effect.fn("OpenAISpeech.onEvent")(function* (state: State, frame

 const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) => {
  if (isSse(context.body) && !state.done) return Effect.fail(route.incomplete())
-  const format = context.request.format ?? "mp3"
+  // The sent body reflects `providerOptions` and `http.body` overrides of `format`.
+  const sent = context.body.type === "json" ? context.body.value.response_format : undefined
+  const format = typeof sent === "string" ? sent : "mp3"
  return SpeechStream.finish(route, state, {
    ...(format === "pcm" ? SpeechStream.pcm("pcm_s16le", PCM_SAMPLE_RATE) : SpeechStream.container(format)),
    usage: state.usage,
@@ -121,7 +133,7 @@ const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) =
 // ---------------------------------------------------------------------------

 export const protocol = MediaProtocol.stream<Request, SpeechEvent, string | Uint8Array, State>(route, {
-  unsupported: ["language", "timestamps"],
+  unsupported: ["language"],
  body: { from: fromRequest },
  frames: (bytes, context) => (isSse(context.body) ? Framing.sse.frame(bytes) : bytes),
  initial: () => ({ chunks: [], done: false }),
@@ -1,8 +1,9 @@
 import { Effect, Schema, Stream } from "effect"
+import { classifyProviderFailure } from "../provider-error.js"
 import { Framing } from "../route/framing.js"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"
-import { mergeJsonRecords, type MediaUsage } from "../schema/index.js"
+import { AIError, mergeJsonRecords, type MediaUsage } from "../schema/index.js"
 import {
  TranscriptionFinishEvent,
  TranscriptionModel,
@@ -59,6 +60,9 @@ const Usage = Schema.Union([
    input_tokens: Schema.optional(Schema.Number),
    output_tokens: Schema.optional(Schema.Number),
    total_tokens: Schema.optional(Schema.Number),
+    input_token_details: Schema.optional(
+      Schema.Struct({ audio_tokens: Schema.optional(Schema.Number), text_tokens: Schema.optional(Schema.Number) }),
+    ),
  }),
  Schema.Struct({ type: Schema.Literal("duration"), seconds: Schema.Number }),
 ])
@@ -75,14 +79,23 @@ const transcriptFields = {
  usage: Schema.optional(Usage),
 }

+/** OpenAI may add stream event types; frames outside `EVENT_TYPES` are ignored. */
+const EventType = Schema.Struct({ type: Schema.String })
 const Event = Schema.Union([
  Schema.Struct({ type: Schema.Literal("transcript.text.delta"), delta: Schema.String }),
  Schema.Struct({ type: Schema.Literal("transcript.text.segment"), ...Segment.fields }),
  Schema.Struct({ type: Schema.Literal("transcript.text.done"), ...transcriptFields }),
+  Schema.Struct({
+    type: Schema.Literal("error"),
+    message: Schema.optional(Schema.String),
+    error: Schema.optional(Schema.Struct({ message: Schema.optional(Schema.String) })),
+  }),
 ])
+const EVENT_TYPES = new Set(["transcript.text.delta", "transcript.text.segment", "transcript.text.done", "error"])
 const Transcript = Schema.Struct(transcriptFields)
 type Transcript = Schema.Schema.Type<typeof Transcript>

+const decodeEventType = route.decodeFrame(EventType)
 const decodeEvent = route.decodeFrame(Event)
 const decodeTranscript = route.decodeFrame(Transcript)

@@ -118,10 +131,12 @@ const capabilities = (model: string): Capabilities => {
  return TRANSCRIBE
 }

+/** whisper-1 ignores `stream`, so its `stream` mode sends a plain request and emits only `finish`. */
+const streamsEvents = (request: MediaProtocol.Addressed<Request>) =>
+  request.mode === "stream" && capabilities(request.model.id).stream
+
 const validate = (request: MediaProtocol.Addressed<Request>, model: Capabilities) => {
  const id = request.model.id
-  if (request.mode === "stream" && !model.stream)
-    return Effect.fail(route.unsupported("media.stream", `${id} does not stream; use Transcription.generate`))
  if (request.diarize === true && !model.diarize)
    return Effect.fail(route.unsupported("media.diarize", `${id} does not diarize; use gpt-4o-transcribe-diarize`))
  if (request.prompt !== undefined && model.diarize)
@@ -173,12 +188,12 @@ const fromRequest = Effect.fn("OpenAITranscription.fromRequest")(function* (requ
      timestamp_granularities: responseFormat === "verbose_json" ? [request.timestamps] : undefined,
      // Diarizing audio longer than 30 seconds requires a chunking strategy.
      chunking_strategy: model.diarize ? "auto" : undefined,
-      stream: request.mode === "stream" ? true : undefined,
+      stream: streamsEvents(request) ? true : undefined,
    },
    {
      overlay: mergeJsonRecords(request.providerOptions, request.http?.body),
      reserved: RESERVED_FORM_FIELDS,
-      repeatArrays: true,
+      repeatArrays: "key[]",
    },
  )
  return MediaProtocol.multipart(form)
@@ -196,7 +211,15 @@ const segment = (value: Schema.Schema.Type<typeof Segment>): TranscriptionSegmen
 })

 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")
+    return yield* new AIError({
+      reason: classifyProviderFailure({
+        message: `${route.name} stream failed: ${event.message ?? event.error?.message ?? "unknown error"}`,
+        rawBody: frame,
+      }),
+    })
  if (event.type === "transcript.text.done") return [{ ...state, transcript: event }, []] as const
  if (event.type === "transcript.text.delta")
    return [state, event.delta.length === 0 ? [] : [TranscriptionTextDeltaEvent.make({ delta: event.delta })]] as const
@@ -246,7 +269,7 @@ export const protocol = MediaProtocol.stream<Request, TranscriptionEvent, Frame,
  unsupported: ["speakers"],
  body: { from: fromRequest },
  frames: (bytes, context) =>
-    context.request.mode === "stream"
+    streamsEvents(context.request)
      ? Framing.sse.frame(bytes)
      : Framing.document.frame(bytes).pipe(Stream.map((document) => ({ document }))),
  initial: () => ({ segments: [] }),
@@ -132,8 +132,7 @@ const decodeResult = Effect.fn("ReplicateImages.decodeResult")(function* (
      status,
      `${route.name} prediction ${context.token.id} ${prediction.status}${typeof prediction.error === "string" ? `: ${prediction.error}` : ""}`,
    )
-  if (status !== "completed")
-    return yield* output.invalid(`${route.name} prediction ${context.token.id} has not finished`)
+  if (status !== "completed") return yield* output.pending(context.token.id)
  if (prediction.data_removed === true)
    return yield* output.ended("expired", `${route.name} removed the output of prediction ${context.token.id}`)
  if (!isOutput(prediction.output))
@@ -137,12 +137,16 @@ const decodeResult = Effect.fn("RunwayVideo.decodeResult")(function* (
    const message = `${route.name} task failed${code === undefined ? "" : ` (${code})`}${task.failure ? `: ${task.failure}` : ""}`
    // Runway failure codes are dotted paths; every moderation outcome carries a SAFETY segment.
    if (code !== undefined && /(^|\.)SAFETY(\.|$)/.test(code)) return yield* output.contentPolicy(message)
-    return yield* output.ended("failed", message)
+    // ASSET.INVALID rejects the caller's input media; Runway documents it as not retryable.
+    return yield* output.ended(
+      "failed",
+      message,
+      code !== undefined && /^ASSET\.INVALID(\.|$)/.test(code) ? "InvalidRequest" : "ProviderInternal",
+    )
  }
  if (status === "cancelled")
    return yield* output.ended("cancelled", `${route.name} task ${context.token.taskID} was cancelled`)
-  if (status !== "completed")
-    return yield* output.invalid(`${route.name} task ${context.token.taskID} has not finished`)
+  if (status !== "completed") return yield* output.pending(context.token.taskID)
  const urls = task.output ?? []
  if (urls.length === 0) return yield* output.invalid(`${route.name} task succeeded without any output`)
  return new VideoResponse({
@@ -171,7 +175,7 @@ export const protocol = MediaProtocol.queued<Request, VideoResponse, Token>(rout
  start: { body: { from: fromRequest }, decode: decodeStart },
  status: { path: taskPath, decode: decodeStatus },
  result: { path: taskPath, decode: decodeResult },
-  cancel: { method: "DELETE", path: taskPath },
+  cancel: { method: "DELETE", path: taskPath, activeOnly: true },
 })

 const startPath = (request: Request) => {
@@ -110,6 +110,14 @@ export const sumTokens = (...values: ReadonlyArray<number | undefined>): number
  return values.reduce((acc: number, value) => acc + (value ?? 0), 0)
 }

+/**
+ * Caps an explicit thinking budget at half the output limit. Thinking counts against the output limit, so a budget
+ * near it leaves the answer, a tool call, or a summary without room. Smaller budgets, special values such as `-1` and
+ * `0`, and requests without an output limit pass through unchanged.
+ */
+export const fitThinkingBudget = (budget: number, maxTokens: number | undefined, minimum = 1) =>
+  maxTokens === undefined || budget <= maxTokens / 2 ? budget : Math.max(minimum, Math.floor(maxTokens / 2))
+
 export const eventError = (route: string, message: string, body?: string, cause?: unknown) =>
  new AIError({
    reason: new InvalidProviderOutputError({ route, message, body, cause }),
@@ -175,7 +175,7 @@ const decodeUpscaleResult = Effect.fn("StabilityImages.decodeUpscaleResult")(fun
 ) {
  if (response.status === 202) {
    const output = yield* upscaleRoute.text(response)
-    return yield* output.invalid(`${upscaleRoute.name} upscale ${context.token.id} has not finished`)
+    return yield* output.pending(context.token.id)
  }
  return yield* decodeUpscaleImage(response)
 })
@@ -72,6 +72,44 @@ export const blocked = (name: string, chunk: Chunk, frame: string) => {
  })
 }

+const CONTENT_FILTER_REASONS = new Set([
+  "IMAGE_SAFETY",
+  "RECITATION",
+  "SAFETY",
+  "BLOCKLIST",
+  "PROHIBITED_CONTENT",
+  "SPII",
+  "MODEL_ARMOR",
+  "IMAGE_PROHIBITED_CONTENT",
+  "IMAGE_RECITATION",
+  "LANGUAGE",
+])
+
+/** Finish reasons for which Gemini stops output on safety or policy grounds. */
+export const contentFiltered = (finishReason: string | undefined) =>
+  finishReason !== undefined && CONTENT_FILTER_REASONS.has(finishReason)
+
+/** Callers check that the response produced no output: a policy stop after output is a partial result instead. */
+export const withheld = (name: string, chunk: Chunk, frame: string) => {
+  const finishReason = chunk.candidates?.[0]?.finishReason
+  if (!contentFiltered(finishReason)) return undefined
+  return new AIError({
+    reason: new ContentPolicyError({ message: `${name} withheld its output (${finishReason})`, body: frame }),
+  })
+}
+
+/** Any finish reason other than `STOP` means the output may be cut short, so it is surfaced rather than dropped. */
+export const notices = (name: string, state: Metadata): ReadonlyArray<Media.Notice> | undefined =>
+  state.finishReason === undefined || state.finishReason === "STOP"
+    ? undefined
+    : [
+        {
+          type: contentFiltered(state.finishReason) ? "filtered" : "other",
+          message: `${name} finished with ${state.finishReason}`,
+          providerMetadata: { google: { finishReason: state.finishReason } },
+        },
+      ]
+
 export const usage = (usage: UsageMetadata | undefined): MediaUsage | undefined =>
  usage === undefined
    ? undefined
@@ -71,8 +71,9 @@ export const imageOutput = (
 }

 /**
- * Append multipart text fields: strings as-is, other values as JSON, or arrays as repeated `key[]` parts with
- * `repeatArrays`. `overlay` keys in `reserved` are dropped so `http.body` cannot replace route-owned fields.
+ * Append multipart text fields: strings as-is, other values as JSON, or scalar arrays as one part per item with
+ * `repeatArrays`, named `key[]` or `key`. `overlay` keys in `reserved` are dropped so `http.body` cannot replace
+ * route-owned fields.
 */
 export const appendFields = (
  form: FormData,
@@ -80,13 +81,13 @@ export const appendFields = (
  options: {
    readonly overlay?: Record<string, unknown>
    readonly reserved: ReadonlySet<string>
-    readonly repeatArrays?: true
+    readonly repeatArrays?: "key[]" | "key"
  },
 ) => {
  const overlay = Object.entries(options.overlay ?? {}).filter(([key]) => !options.reserved.has(key))
  Object.entries(mergeJsonRecords(fields, Object.fromEntries(overlay)) ?? {}).forEach(([key, value]) => {
-    if (Array.isArray(value) && options.repeatArrays)
-      return value.forEach((item) => form.append(`${key}[]`, String(item)))
+    if (Array.isArray(value) && value.every(isScalar) && options.repeatArrays !== undefined)
+      return value.forEach((item) => form.append(options.repeatArrays === "key[]" ? `${key}[]` : key, String(item)))
    form.append(key, typeof value === "string" ? value : encodeJson(value))
  })
 }
@@ -1,7 +1,7 @@
 import { Effect, Schema, Stream } from "effect"
 import { Route, type RouteBody, type TriggerCompactOperation } from "../../route/client.js"
 import { Protocol } from "../../route/protocol.js"
-import { CompactionCheckpointResponse, HttpOptions, LLMEvent, LLMRequest } from "../../schema/index.js"
+import { CompactionCheckpointResponse, LLMEvent, LLMRequest } from "../../schema/index.js"
 import { OpenResponses } from "../open-responses.js"
 import { ProviderShared } from "../shared.js"

@@ -109,12 +109,8 @@ export const make = <Body>(body: RouteBody<Body>): TriggerCompactOperation =>
      transport: source.transport,
    })
    const native = yield* body.from(request)
-    // The body builder already applied and validated overlays. Do not let transport reapply them.
-    const preparedRequest = LLMRequest.update(request, {
-      http: request.http === undefined ? undefined : new HttpOptions({ ...request.http, body: undefined }),
-    })
-    const prepared = yield* route.prepareTransport(native, preparedRequest, options)
-    yield* route.streamPrepared(prepared, preparedRequest, { http: executor }, options).pipe(Stream.runDrain)
+    const prepared = yield* route.prepareTransport(native, request, options)
+    yield* route.streamPrepared(prepared, request, { http: executor }, options).pipe(Stream.runDrain)
    if (!result) return yield* ProviderShared.eventError(source.id, "Compaction response ended without a checkpoint")
    return result
  })
@@ -19,12 +19,18 @@ import { OpenResponses } from "../open-responses.js"
 import { JsonObject, optionalNull, ProviderShared } from "../shared.js"
 import { Media } from "../../media.js"

+// /compact has a smaller wire contract than /responses; keep the request controls it accepts.
 const Body = Schema.Struct({
  model: Schema.String,
  input: Schema.Array(Schema.Unknown),
  instructions: optionalNull(Schema.String),
  previous_response_id: optionalNull(Schema.String),
  service_tier: optionalNull(Schema.String),
+  reasoning: Schema.optional(JsonObject),
+  text: Schema.optional(JsonObject),
+  include: OpenResponses.coreFields.include,
+  parallel_tool_calls: OpenResponses.coreFields.parallel_tool_calls,
+  tools: Schema.optional(Schema.Array(JsonObject)),
  prompt_cache_key: optionalNull(Schema.String),
  prompt_cache_retention: optionalNull(Schema.String),
  prompt_cache_options: optionalNull(
@@ -74,17 +80,27 @@ const Response = Schema.Struct({
  usage: Schema.optional(Schema.StructWithRest(OpenResponses.OpenResponsesUsage, [JsonObject])),
 })

-export const make = (adapter: OpenResponses.ProviderAdapter): CompactOperation =>
+export const make = (
+  adapter: OpenResponses.ProviderAdapter,
+  lowerTools: (request: LLMRequest) => Effect.Effect<ReadonlyArray<Record<string, unknown>>, AIError>,
+): CompactOperation =>
  Effect.fn("ResponsesCompaction.execute")(function* (request, executor, options) {
    const route = request.model.route
    // The standalone compaction endpoint rejects histories containing configuration updates.
    const native = yield* OpenResponses.lowerConversation(stripEffortUpdates(request), adapter)
+    const generation = OpenResponses.lowerGeneration(request)
+    const tools = request.tools.length === 0 ? undefined : yield* lowerTools(request)
    const body = yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(Body))(
      mergeJsonRecords(
        {
          ...native,
-          service_tier: request.providerOptions?.serviceTier,
-          prompt_cache_key: ProviderShared.promptCacheKey(request),
+          service_tier: generation.service_tier,
+          reasoning: generation.reasoning,
+          text: generation.text,
+          include: generation.include,
+          parallel_tool_calls: generation.parallel_tool_calls,
+          tools,
+          prompt_cache_key: generation.prompt_cache_key,
        },
        request.http?.body,
      ),
@@ -0,0 +1,10 @@
+/** Split an ordered token list into runs of consecutive tokens with the same speaker. */
+export const group = <Item>(items: ReadonlyArray<Item>, speaker: (item: Item) => unknown) =>
+  items.reduce<Array<Array<Item>>>((turns, item) => {
+    const last = turns.at(-1)
+    if (last === undefined || speaker(last[0]) !== speaker(item)) return [...turns, [item]]
+    last.push(item)
+    return turns
+  }, [])
+
+export * as SpeakerTurns from "./speaker-turns.js"
@@ -85,6 +85,7 @@ export const finish = (
    readonly mediaType: string | undefined
    readonly info?: Media.Info
    readonly usage?: MediaUsage
+    readonly notices?: ReadonlyArray<Media.Notice>
    readonly providerMetadata?: ProviderMetadata
    readonly detail?: string
  },
@@ -97,6 +98,7 @@ export const finish = (
    SpeechFinishEvent.make({
      audio: Media.bytes(concatBytes(state.chunks), output.mediaType, { info: output.info }),
      usage: output.usage,
+      notices: output.notices,
      providerMetadata: output.providerMetadata,
    }),
  ])
@@ -1,4 +1,4 @@
-import type { JsonSchema, LanguageModel, LanguageModelSanitizerCompatibility } from "../../schema/index.js"
+import { ToolDefinition, type JsonSchema, type LanguageModel, type LLMRequest } from "../../schema/index.js"
 import { isRecord } from "../../utils/record.js"
 import { GeminiJsonSchema } from "./gemini-json-schema.js"

@@ -70,13 +70,13 @@ const objectRoot = (schema: JsonSchema): JsonSchema => {
 // Otherwise the protocol's own default applies (the Gemini API always uses Gemini's rules), then the
 // model name selects the family's rules so models reached through gateways and OpenAI-compatible
 // endpoints get the same handling.
-const modelCompatibility = (
-  schema: JsonSchema,
-  model: LanguageModel,
-  protocolDefault?: LanguageModelSanitizerCompatibility,
-): JsonSchema => {
+const modelCompatibility = (schema: JsonSchema, model: LanguageModel): JsonSchema => {
  const root = objectRoot(schema)
-  switch (model.compatibility?.sanitizer ?? protocolDefault ?? MODEL_NAMES.find(([name]) => name.test(model.id))?.[1]) {
+  switch (
+    model.compatibility?.sanitizer ??
+    model.route.sanitizer ??
+    MODEL_NAMES.find(([name]) => name.test(model.id))?.[1]
+  ) {
    case "gemini":
      return gemini(root)
    case "moonshot":
@@ -87,10 +87,18 @@ const modelCompatibility = (
  }
 }

+// Applied once to every request before any protocol builds its body, including tools in namespaces.
+const tools = (entries: LLMRequest["tools"], model: LanguageModel): LLMRequest["tools"] =>
+  entries.map((tool) =>
+    tool.type === "tool"
+      ? new ToolDefinition({ ...tool, inputSchema: modelCompatibility(tool.inputSchema, model) })
+      : { ...tool, tools: tools(tool.tools, model) },
+  )
+
 export const ToolSchemaProjection = {
  gemini,
-  modelCompatibility,
  moonshot,
  openAI,
  responses,
+  tools,
 } as const
@@ -101,7 +101,8 @@ const decodeResponse = Effect.fn("XAIImages.decodeResponse")(function* (
  )
  if (images.length === 0) return yield* output.invalid(`${route.name} returned no images`)
  const usage = ProviderShared.isRecord(decoded.usage) ? decoded.usage : undefined
-  // xAI reports image counts rather than tokens, seconds, or credits; the raw record stays in provider metadata.
+  // xAI reports a USD cost (`cost_in_usd_ticks`) rather than tokens, seconds, or credits; the raw record stays in
+  // provider metadata.
  return new ImageResponse({
    images,
    providerMetadata: usage === undefined ? undefined : { xai: { usage } },
@@ -50,7 +50,8 @@ const fromRequest = Effect.fn("XAIResponses.fromRequest")(function* (request: LL
      operation: "in-band-compaction",
      provider: request.model.provider,
      route: request.model.route.id,
-      message: "xAI requires explicit compaction through LLMClient.compact; automatic context management is not supported",
+      message:
+        "xAI requires explicit compaction through LLMClient.compact; automatic context management is not supported",
    })
  return yield* decodeBody(yield* OpenResponses.fromRequestWithAdapter(request, adapter))
 })
@@ -93,6 +94,8 @@ export const protocol = Protocol.make({
  },
 })

-export const compact = ResponsesCompaction.make(adapter)
+export const compact = ResponsesCompaction.make(adapter, (request) =>
+  OpenResponses.lowerTools(ProviderShared.flattenTools(request.tools), adapter),
+)

 export * as XAIResponses from "./xai-responses.js"
@@ -65,6 +65,13 @@ const STATUS = {
  expired: "expired",
 } as const satisfies Record<string, Status>

+// Documented video error codes; `service_unavailable`, `internal_error`, and unknown codes are provider-side.
+const FAILURE = {
+  invalid_argument: "InvalidRequest",
+  failed_precondition: "InvalidRequest",
+  permission_denied: "Authentication",
+} as const satisfies Record<string, MediaProtocol.Failure>
+
 // ---------------------------------------------------------------------------
 // 5. Request body construction
 // ---------------------------------------------------------------------------
@@ -136,14 +143,14 @@ const decodeResult = Effect.fn("XAIVideo.decodeResult")(function* (
  const output = yield* decodeVideoStatus(response)
  const decoded = output.value
  const status = yield* MediaProtocol.status(STATUS, decoded.status, output)
-  if (status === "running")
-    return yield* output.invalid(`${route.name} request ${context.token.requestID} has not finished`)
+  if (status === "running") return yield* output.pending(context.token.requestID)
  if (status === "failed") {
    const code = decoded.error?.code ?? undefined
    const message = decoded.error?.message ?? undefined
    return yield* output.ended(
      "failed",
      `${route.name} generation failed${code === undefined ? "" : ` (${code})`}${message === undefined ? "" : `: ${message}`}`,
+      MediaProtocol.failure(FAILURE, code),
    )
  }
  if (status !== "completed")
@@ -1,7 +1,6 @@
-import { Effect, Schema } from "effect"
+import { Duration, Effect, Schema } from "effect"
 import type { HttpClientResponse } from "effect/unstable/http"
 import { ImageModel, ImageResponse, type ImageRequestFor } from "../image.js"
-import { Media } from "../media.js"
 import { MediaProtocol } from "../route/media-protocol.js"
 import { MediaRoute } from "../route/media.js"
 import { mergeJsonRecords, type OpenString } from "../schema/index.js"
@@ -9,6 +8,7 @@ import { mergeJsonRecords, type OpenString } from "../schema/index.js"
 const route = MediaProtocol.identity({ id: "zai-images", name: "Z.ai Images", provider: "zai" })
 export const DEFAULT_BASE_URL = "https://api.z.ai/api/paas/v4"
 export const PATH = "/images/generations"
+const OUTPUT_RETENTION = Duration.days(30)

 // ---------------------------------------------------------------------------
 // 1. Public model input
@@ -76,7 +76,7 @@ const decodeResponse = Effect.fn("ZAIImages.decodeResponse")(function* (
  const filters = decoded.content_filter ?? []
  return new ImageResponse({
    // Z.ai returns only URLs and no content type; the media type resolves when the asset is materialized.
-    images: decoded.data.map((item) => Media.url(item.url)),
+    images: yield* Effect.forEach(decoded.data, (item) => MediaProtocol.expiringUrl(item.url, OUTPUT_RETENTION)),
    // Z.ai reports applied content filters alongside a successful result; surface them instead of dropping them.
    notices:
      filters.length === 0
@@ -58,6 +58,47 @@ export const isContextOverflowFailure = (failure: unknown) =>
    ? failure.reason._tag === "InvalidRequest" && failure.reason.classification === "context-overflow"
    : Schema.is(ProviderErrorEvent)(failure) && failure.classification === "context-overflow"

+/**
+ * Whether a failed call may succeed when sent again: rate limits, provider-side failures, transport failures that did
+ * not deliver an accepted write, and unrecognized failures. Callers decide which calls are safe to repeat.
+ */
+export const isRetryable = (error: AIError) => {
+  const override = error.reason.http?.headers["x-should-retry"]
+  if (override === "true") return true
+  if (override === "false") return false
+  switch (error.reason._tag) {
+    case "RateLimit":
+    case "ProviderInternal":
+      return true
+    // A WebSocket acknowledgment marks delivery accepted before model output may exist.
+    // Read failures can still recover; the caller chooses retry versus continuation from durable output.
+    case "Transport":
+      return (
+        error.reason.delivery !== "rejected" &&
+        (error.reason.delivery !== "accepted" || error.reason.operation === "read")
+      )
+    case "InvalidProviderOutput":
+      return error.reason.classification === "incomplete-stream"
+    // Unrecognized failures retry: classification records affirmative
+    // deterministic evidence, and transient failures are exactly the ones
+    // that arrive in shapes no classifier anticipates.
+    case "UnknownProvider":
+      return true
+    case "Authentication":
+    case "QuotaExceeded":
+    case "ContentPolicy":
+    case "InvalidRequest":
+    case "UnsupportedOperation":
+    case "NoRoute":
+    case "Timeout":
+      return false
+    default: {
+      const exhaustive: never = error.reason
+      return exhaustive
+    }
+  }
+}
+
 const decodeJson = Schema.decodeUnknownOption(Schema.fromJsonString(Schema.Unknown))
 // OpenCode Zen reports account caps as typed 429/402 errors that are not throttles.
 const QUOTA_CODES = new Set([
@@ -80,7 +121,13 @@ const SERVER_CODES = new Set([
  "slow_down",
  "serviceunavailableexception",
 ])
-const INVALID_REQUEST_CODES = new Set(["invalid_prompt", "invalid_request_error", "validationexception"])
+// `invalid_request` is the Vercel AI Gateway's code for an upstream request rejection.
+const INVALID_REQUEST_CODES = new Set([
+  "invalid_prompt",
+  "invalid_request",
+  "invalid_request_error",
+  "validationexception",
+])
 // Azure OpenAI reports `content_filter` with `innererror.code` ResponsibleAIPolicyViolation.
 // OpenRouter tags provider failures with a typed `error_type`; its Responses skin also
 // emits `image_content_policy_violation` as the native code.
@@ -31,6 +31,7 @@ export interface Settings extends ProviderPackage.Settings {
  readonly profile?: string
  readonly region?: string
  readonly topP?: number
+  readonly thinking?: BedrockConverse.OptionsInput["thinking"]
 }
 export const routes = [BedrockConverse.route]

@@ -71,6 +72,7 @@ export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, se
    generation: settings.topP === undefined ? undefined : { topP: settings.topP },
    headers: settings.headers === undefined ? undefined : { ...settings.headers },
    http: settings.body === undefined ? undefined : { body: { ...settings.body } },
+    providerOptions: settings.thinking === undefined ? undefined : { thinking: settings.thinking },
    profile: settings.profile,
    region: settings.region,
  }).model(modelID)
@@ -3,8 +3,10 @@ import type { ProviderAuthOption } from "../route/auth-options.js"
 import { MediaRoute } from "../route/media.js"
 import { type HttpOptions, ProviderID, type ModelID } from "../schema/index.js"
 import { ElevenLabsSpeech } from "../protocols/elevenlabs-speech.js"
+import { ElevenLabsTranscription } from "../protocols/elevenlabs-transcription.js"

 export type { ElevenLabsOutputFormat, ElevenLabsSpeechOptions } from "../protocols/elevenlabs-speech.js"
+export type { ElevenLabsTranscriptionOptions } from "../protocols/elevenlabs-transcription.js"

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

@@ -24,12 +26,15 @@ const auth = (options: ProviderAuthOption<"optional">) => {
 export const configure = (input: Config = {}) => {
  const media = MediaRoute.deployment(input, auth(input))
  const speech = (modelID: string | ModelID) => ElevenLabsSpeech.model({ ...media, id: modelID })
+  const transcription = (modelID: string | ModelID) => ElevenLabsTranscription.model({ ...media, id: modelID })
  return {
    id,
    speech,
+    transcription,
    configure,
  }
 }

 export const provider = configure()
 export const speech = provider.speech
+export const transcription = provider.transcription
@@ -32,10 +32,7 @@ const openAIProviderOptions = (options: OpenAIOptionsInput | undefined): Provide
  return result
 }

-export const gpt5DefaultOptions = (
-  modelID: string,
-  options: { readonly textVerbosity?: boolean } = {},
-): ProviderOptions | undefined => {
+export const gpt5DefaultOptions = (modelID: string): ProviderOptions | undefined => {
  const id = modelID.toLowerCase()
  if (!id.includes("gpt-5") || id.includes("gpt-5-chat") || id.includes("gpt-5-pro")) return undefined
  return openAIProviderOptions({
@@ -47,27 +44,19 @@ export const gpt5DefaultOptions = (
    // this, callers using the default model facade get reasoning summaries
    // they cannot replay statelessly.
    include: ["reasoning.encrypted_content"],
-    textVerbosity:
-      options.textVerbosity === true && id.includes("gpt-5.") && !id.includes("codex") && !id.includes("-chat")
-        ? "low"
-        : undefined,
  })
 }

-export const openAIDefaultOptions = (
-  modelID: string,
-  options: { readonly textVerbosity?: boolean } = {},
-): ProviderOptions | undefined =>
-  mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID, options))
+export const openAIDefaultOptions = (modelID: string): ProviderOptions | undefined =>
+  mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID))

 export const withOpenAIOptions = <Options extends { readonly providerOptions?: OpenAIProviderOptionsInput }>(
  modelID: string,
  options: Options,
-  defaults: { readonly textVerbosity?: boolean } = {},
 ): Omit<Options, "providerOptions"> & { readonly providerOptions?: ProviderOptions } => {
  return {
    ...options,
-    providerOptions: mergeProviderOptions(openAIDefaultOptions(modelID, defaults), options.providerOptions),
+    providerOptions: mergeProviderOptions(openAIDefaultOptions(modelID), options.providerOptions),
  }
 }

@@ -100,7 +100,7 @@ export const configure = (input: Config = {}) => {
  const modelDefaults = defaults(input)
  const responses = (id: string | ModelID) =>
    responsesRoute
-      .with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true }))
+      .with(withOpenAIOptions(id, modelDefaults))
      .model<OpenAIProviderOptionsInput>({ id })
  const chat = (id: string | ModelID) =>
    chatRoute.with(withOpenAIOptions(id, modelDefaults)).model<OpenAIProviderOptionsInput>({
@@ -8,7 +8,7 @@ import type { ProviderPackage } from "../provider-package.js"
 import { SystemOne } from "../experimental/system-one.js"
 import { OpenAIChat } from "../protocols/openai-chat.js"
 import { newBreakpoints, ttlBucket } from "../protocols/utils/cache.js"
-import { isRecord } from "../protocols/shared.js"
+import { isRecord, ProviderShared } from "../protocols/shared.js"

 export const id = ProviderID.make("openrouter")
 const baseURL = "https://openrouter.ai/api/v1"
@@ -123,7 +123,7 @@ export const protocol = Protocol.make({
          return {
            ...body,
            messages,
-            ...bodyOptions(request.providerOptions),
+            ...bodyOptions(request.providerOptions, request.generation?.maxTokens),
          } as OpenRouterBody
        }),
      ),
@@ -143,7 +143,14 @@ const cacheControl = () => {
  }
 }

-const bodyOptions = (input: unknown) => {
+// OpenRouter forwards `reasoning.max_tokens` as the upstream thinking budget. Upstreams such as Anthropic and Alibaba
+// reject one that is not below the output limit; 1,024 is Anthropic's minimum budget.
+const fitReasoning = (reasoning: Record<string, unknown>, maxTokens: number | undefined) =>
+  typeof reasoning.max_tokens === "number"
+    ? { ...reasoning, max_tokens: ProviderShared.fitThinkingBudget(reasoning.max_tokens, maxTokens, 1_024) }
+    : reasoning
+
+const bodyOptions = (input: unknown, maxTokens: number | undefined) => {
  const openrouter = isRecord(input) ? input : {}
  const { usage, models, provider, plugins, web_search_options, debug, user, reasoning, promptCacheKey, ...options } =
    openrouter
@@ -162,7 +169,7 @@ const bodyOptions = (input: unknown) => {
    ...(isRecord(web_search_options) ? { web_search_options } : {}),
    ...(isRecord(debug) ? { debug } : {}),
    ...(typeof user === "string" ? { user } : {}),
-    ...(isRecord(reasoning) ? { reasoning } : {}),
+    ...(isRecord(reasoning) ? { reasoning: fitReasoning(reasoning, maxTokens) } : {}),
  }
 }

@@ -11,7 +11,8 @@ import { applyEffortUpdates } from "../effort-updates.js"
 import { normalizeToolHistory } from "../tool-history.js"
 import { sanitizeSurrogates } from "../utils/sanitize.js"
 import * as ProviderShared from "../protocols/shared.js"
-import type { ProtocolID, ProviderOptions } from "../schema/index.js"
+import { ToolSchemaProjection } from "../protocols/utils/tool-schema.js"
+import type { LanguageModelSanitizerCompatibility, ProtocolID, ProviderOptions } from "../schema/index.js"
 import {
  AIError,
  CompactionResponse,
@@ -57,6 +58,7 @@ export interface Route<
  readonly defaults: RouteDefaults
  readonly body: RouteBody<Body>
  readonly supportsEffortUpdates?: (request: LLMRequest) => boolean
+  readonly sanitizer?: LanguageModelSanitizerCompatibility
  readonly with: {
    <Next extends CompactionOperations | undefined>(
      patch: RoutePatch<Body, Prepared> & { readonly compact: Next },
@@ -388,6 +390,7 @@ function makeFromTransport<Body, Prepared, Frame, Event, State>(
      defaults: routeInput.defaults ?? {},
      body: protocol.body,
      supportsEffortUpdates: protocol.supportsEffortUpdates,
+      sanitizer: protocol.sanitizer,
      with: (patch: RoutePatch<Body, Prepared>) => {
        const { compact, id, provider, providerMetadataKey, auth, transport, endpoint, ...defaults } = patch
        return build({
@@ -559,7 +562,9 @@ const prepareRequest = (request: LLMRequest) => {
      tool.type === "tool" ? tool : { ...tool, tools: dedupe(tool.tools) },
    )
  const resolved = applyCachePolicy(
-    applyEffortUpdates(LLMRequest.update(sanitized, { tools: dedupe(sanitized.tools) })),
+    applyEffortUpdates(
+      LLMRequest.update(sanitized, { tools: ToolSchemaProjection.tools(dedupe(sanitized.tools), sanitized.model) }),
+    ),
  )
  const headers = resolved.model.route.headers?.({ request: resolved })
  return headers === undefined
@@ -5,12 +5,14 @@ import { Media } from "../media.js"
 import type { AuthInput } from "./auth.js"
 import {
  AIError,
+  AuthenticationError,
  ContentPolicyError,
  HttpContext,
  InvalidProviderOutputError,
  InvalidRequestError,
  ProviderID,
  ProviderInternalError,
+  RateLimitError,
  UnsupportedOperationError,
 } from "../schema/index.js"

@@ -137,6 +139,11 @@ export interface Queued<Request, Response, Token> {
  readonly cancel?: {
    readonly method: AuthInput["method"]
    readonly path: (token: Token) => string
+    /**
+     * Fetch a fresh status first and skip the call for terminal generations, for providers whose cancel endpoint
+     * destroys finished work (Runway's `DELETE /v1/tasks/{id}` deletes completed tasks and their outputs).
+     */
+    readonly activeOnly?: boolean
  }
 }

@@ -183,6 +190,16 @@ export const stream = <Request, Event, Frame, State>(
 // Response helpers
 // ---------------------------------------------------------------------------

+/** Reasons a provider can report for a `failed` generation; anything it does not classify is `ProviderInternal`. */
+const FAILURES = {
+  InvalidRequest: InvalidRequestError,
+  Authentication: AuthenticationError,
+  RateLimit: RateLimitError,
+  ProviderInternal: ProviderInternalError,
+}
+
+export type Failure = keyof typeof FAILURES
+
 const context = (response: HttpClientResponse.HttpClientResponse) =>
  new HttpContext({ url: response.request.url, status: response.status, headers: response.headers })

@@ -194,8 +211,10 @@ export const identity = (input: { readonly id: string; readonly name: string; re

  /**
   * Read a text body while retaining the original payload and HTTP context on every downstream error. `invalid` is a
-   * malformed provider document; `ended` is a generation that reached a terminal status without output (`failed` is
-   * provider-side, `cancelled`/`expired` mean the result will never exist); `contentPolicy` is a moderated result.
+   * malformed provider document; `ended` is a generation that reached a terminal status without output (`failed`
+   * carries the provider's classification, defaulting to `ProviderInternal`; `cancelled`/`expired` mean the result
+   * will never exist); `pending` is a `result()` read before the generation finished, which is caller misuse;
+   * `contentPolicy` is a moderated result.
   */
  const text = Effect.fn("MediaProtocol.text")(function* (response: HttpClientResponse.HttpClientResponse) {
    const http = context(response)
@@ -217,13 +236,25 @@ export const identity = (input: { readonly id: string; readonly name: string; re
      http,
      invalid: (message: string, cause?: unknown) =>
        new AIError({ reason: new InvalidProviderOutputError({ route: input.id, message, body, http, cause }) }),
-      ended: (status: Exclude<Status, "queued" | "running" | "completed">, message: string) =>
+      ended: (
+        status: Exclude<Status, "queued" | "running" | "completed">,
+        message: string,
+        failure: Failure = "ProviderInternal",
+      ) =>
        new AIError({
          reason:
            status === "failed"
-              ? new ProviderInternalError({ message, body, http })
+              ? new FAILURES[failure]({ message, body, http })
              : new InvalidRequestError({ message, body, http }),
        }),
+      pending: (id: string) =>
+        new AIError({
+          reason: new InvalidRequestError({
+            message: `${input.name} generation ${id} has not finished; await it before reading the result`,
+            body,
+            http,
+          }),
+        }),
      contentPolicy: (message: string) => new AIError({ reason: new ContentPolicyError({ message, body, http }) }),
    }
  })
@@ -285,11 +316,14 @@ export const status = <Table extends Record<string, Status>>(
  raw: string,
  output: Output,
 ): Effect.Effect<Status, AIError> => {
-  const normalized: Status | undefined = table[raw]
-  if (normalized === undefined) return Effect.fail(output.invalid(`Unknown generation status "${raw}"`))
-  return Effect.succeed(normalized)
+  if (!Object.hasOwn(table, raw)) return Effect.fail(output.invalid(`Unknown generation status "${raw}"`))
+  return Effect.succeed(table[raw])
 }

+/** Map a provider error code through the protocol's table; missing or unmapped codes are `ProviderInternal`. */
+export const failure = (table: Readonly<Record<string, Failure>>, code: string | number | undefined): Failure =>
+  code !== undefined && Object.hasOwn(table, code) ? table[code] : "ProviderInternal"
+
 /** A `url` asset whose provider-declared retention window starts now. */
 export const expiringUrl = (url: string, retention: Duration.Duration, options?: Parameters<typeof Media.url>[1]) =>
  Clock.currentTimeMillis.pipe(
@@ -1,12 +1,13 @@
-import { Effect, Schema, Stream } from "effect"
+import { Duration, Effect, Schedule, Schema, Stream } from "effect"
 import { Headers, HttpClientRequest, type HttpClientResponse } from "effect/unstable/http"
 import { Auth, type AuthInput } from "./auth.js"
 import { Endpoint } from "./endpoint.js"
 import { RequestExecutorService, type Interface } from "./executor-service.js"
 import { RequestExecutor } from "./executor.js"
 import { MediaProtocol } from "./media-protocol.js"
-import { Generation, resultEvents, type AwaitOptions, type Observation } from "../generation.js"
+import { Generation, isTerminal } from "../generation.js"
 import type { Media } from "../media.js"
+import { isRetryable } from "../provider-error.js"
 import {
  AIError,
  AIErrorReason,
@@ -52,7 +53,7 @@ export const deployment = (
 // ---------------------------------------------------------------------------

 /** One request, one response. */
-export interface Route<Request extends MediaRequest, Response> {
+export interface InlineRoute<Request extends MediaRequest, Response> {
  readonly kind: "inline"
  readonly id: string
  readonly provider: ProviderID
@@ -86,7 +87,7 @@ export interface StreamRoute<Request extends MediaRequest, Event, Response> {
 }

 export type AnyRoute<Request extends MediaRequest, Event, Response> =
-  | Route<Request, Response>
+  | InlineRoute<Request, Response>
  | StreamRoute<Request, Event, Response>
  | QueuedRoute<Request, Response>

@@ -119,7 +120,7 @@ export interface StreamInput<Request extends MediaRequest, Event, Response, Fram
 */
 export const inline = <Request extends MediaRequest, Response>(
  input: InlineInput<Request, Response>,
-): Route<Request, Response> => {
+): InlineRoute<Request, Response> => {
  const transport = makeTransport(input)
  return {
    kind: "inline",
@@ -137,6 +138,32 @@ export const inline = <Request extends MediaRequest, Response>(
  }
 }

+const READ_RETRY_MAX_DELAY = Duration.seconds(30)
+
+/**
+ * Status and result reads retry transient failures; `start` and `cancel` never do. Gaps grow exponentially from 1s,
+ * jittered, up to 30s each, for at most 8 retries (about two minutes when every attempt fails), so a direct
+ * `Generation.result()` stays bounded; `await` and `events` also cut retries off at `poll.timeout`. A provider
+ * `retryAfterMs` raises the gap, still capped at 30s.
+ */
+const READ_RETRY = Schedule.max([
+  Schedule.min([Schedule.exponential("1 second"), Schedule.spaced(READ_RETRY_MAX_DELAY)]),
+  Schedule.recurs(8),
+]).pipe(
+  Schedule.jittered,
+  Schedule.setInputType<AIError>(),
+  Schedule.modifyDelay(({ input, duration }) =>
+    Effect.succeed(
+      Duration.min(
+        input.reason._tag === "RateLimit" || input.reason._tag === "ProviderInternal"
+          ? Duration.max(duration, Duration.millis(input.reason.retryAfterMs ?? 0))
+          : duration,
+        READ_RETRY_MAX_DELAY,
+      ),
+    ),
+  ),
+)
+
 /**
 * Compose a queued media protocol the same way, adding `start`/`resume` handles whose polls reuse the route's auth,
 * deployment headers, and (for `start`) the request's `http` overlay. The token is decoded once at the boundary and
@@ -154,6 +181,8 @@ export const queued = <Request extends MediaRequest, Response, Token>(
  const generationRoute = (token: Token, http: HttpOptions | undefined, execute: Execute) => {
    const materialize = (asset: Media.Asset) =>
      asset.materialize().pipe(Effect.provideService(RequestExecutorService, { execute }))
+    // Only the GET exchange retries: a decoded terminal failure (`output.ended`) can be a `ProviderInternal` too, and
+    // re-reading it would spin until the caller's deadline.
    const poll = <A>(operation: {
      readonly path: (token: Token) => string
      readonly decode: (
@@ -161,17 +190,23 @@ export const queued = <Request extends MediaRequest, Response, Token>(
        context: MediaProtocol.PollContext<Token>,
      ) => Effect.Effect<A, AIError>
    }) =>
-      transport
-        .call("GET", operation.path(token), http, execute)
-        .pipe(Effect.flatMap((sent) => operation.decode(sent.response, { token, auth: sent.auth, materialize })))
+      transport.call("GET", operation.path(token), http, execute).pipe(
+        Effect.retry({ schedule: READ_RETRY, while: isRetryable }),
+        Effect.flatMap((sent) => operation.decode(sent.response, { token, auth: sent.auth, materialize })),
+      )
+    const status = poll(protocol.status)
    const cancel = protocol.cancel
+    const send =
+      cancel === undefined
+        ? undefined
+        : transport.call(cancel.method, cancel.path(token), http, execute).pipe(Effect.asVoid)
    return {
-      status: poll(protocol.status),
+      status,
      result: poll(protocol.result),
      cancel:
-        cancel === undefined
-          ? undefined
-          : transport.call(cancel.method, cancel.path(token), http, execute).pipe(Effect.asVoid),
+        send !== undefined && cancel?.activeOnly
+          ? status.pipe(Effect.flatMap((snapshot) => (isTerminal(snapshot.status) ? Effect.void : send)))
+          : send,
    }
  }

@@ -267,59 +302,6 @@ export const stream = <Request extends MediaRequest, Event, Response, Frame, Sta
  }
 }

-export const dispatch = <Event, Response>(input: {
-  readonly modality: string
-  readonly execute: Execute
-  readonly responseEvents: (response: Response) => ReadonlyArray<Event>
-}) => {
-  const notQueued = (route: { readonly provider: ProviderID; readonly id: string }, operation: string) =>
-    new AIError({
-      reason: new UnsupportedOperationError({
-        operation: `${input.modality}.${operation}`,
-        provider: route.provider,
-        route: route.id,
-        message: `${route.provider}/${route.id} is not a queued route; use generate or stream`,
-      }),
-    })
-  const start = <Request extends MediaRequest>(route: AnyRoute<Request, Event, Response>, request: Request) => {
-    if (route.kind !== "queued") return Effect.fail(notQueued(route, "start"))
-    return route.start(request, input.execute)
-  }
-  return {
-    start,
-    resume: <Request extends MediaRequest>(
-      route: AnyRoute<Request, Event, Response>,
-      model: MediaRequest["model"],
-      token: unknown,
-    ) => {
-      if (route.kind !== "queued") return Effect.fail(notQueued(route, "resume"))
-      return route.resume(model, token, input.execute)
-    },
-    generate: <Request extends MediaRequest>(
-      route: AnyRoute<Request, Event, Response>,
-      request: Request,
-      options?: AwaitOptions,
-    ) => {
-      if (route.kind !== "queued") return route.generate(request, input.execute)
-      return start(route, request).pipe(Effect.flatMap((generation) => generation.await(options)))
-    },
-    stream: <Request extends MediaRequest>(
-      route: AnyRoute<Request, Event, Response>,
-      request: Request,
-      options?: AwaitOptions,
-    ): Stream.Stream<Event | Observation, AIError> => {
-      if (route.kind === "stream") return route.stream(request, input.execute)
-      if (route.kind === "queued")
-        return Stream.unwrap(
-          start(route, request).pipe(
-            Effect.map((generation) => resultEvents(generation, input.responseEvents, options)),
-          ),
-        )
-      return Stream.fromIterableEffect(Effect.map(route.generate(request, input.execute), input.responseEvents))
-    },
-  }
-}
-
 // ---------------------------------------------------------------------------
 // Transport plumbing shared by every kind
 // ---------------------------------------------------------------------------
@@ -433,7 +415,11 @@ const encode = (body: MediaProtocol.Body | undefined, headers: Headers.Headers)
  }
 }

-/** Common fields are never silently dropped: a present field the protocol declared unsupported fails typed. */
+/**
+ * Common fields are never silently dropped: a present field the protocol declared unsupported fails typed. `false`
+ * counts as present because some booleans mean something when false (video `audio`); protocols reject opt-in
+ * booleans such as speech `timestamps` with `=== true` in `body.from` instead of listing them.
+ */
 const rejectUnsupported = <Request extends object>(
  route: string,
  provider: ProviderID,
@@ -1,5 +1,5 @@
 import { Schema, type Effect } from "effect"
-import type { AIError, LLMEvent, LLMRequest, ProtocolID } from "../schema/index.js"
+import type { AIError, LanguageModelSanitizerCompatibility, LLMEvent, LLMRequest, ProtocolID } from "../schema/index.js"

 /**
 * The semantic API contract of one model server family.
@@ -43,6 +43,8 @@ export interface Protocol<Body, Frame, Event, State> {
  readonly stream: ProtocolStream<Frame, Event, State>
  /** Whether `body.from` lowers `Message.effort(...)` markers; wrappers around another `body.from` must forward it. */
  readonly supportsEffortUpdates?: (request: LLMRequest) => boolean
+  /** Tool schema sanitizer for every model on this protocol unless the model's compatibility sets one; wrappers around another `body.from` must forward it. */
+  readonly sanitizer?: LanguageModelSanitizerCompatibility
 }

 export interface ProtocolBody<Body> {
@@ -1,53 +1,31 @@
-import { Context, Effect, Layer, Stream } from "effect"
-import { RequestExecutor } from "./route/executor.js"
-import type { AIError } from "./schema/index.js"
-import type { SpeechEvent, SpeechOptions, SpeechRequestFor, SpeechResponse } from "./speech.js"
+import { Context } from "effect"
+import { MediaClient } from "./media-client.js"
+import {
+  SpeechTimestampsEvent,
+  SpeechFinishEvent,
+  type SpeechEvent,
+  type SpeechRequestFor,
+  type SpeechResponse,
+} from "./speech.js"

-export interface Interface {
-  readonly generate: <Options extends SpeechOptions>(
-    request: SpeechRequestFor<Options>,
-  ) => Effect.Effect<SpeechResponse, AIError>
-  readonly stream: <Options extends SpeechOptions>(
-    request: SpeechRequestFor<Options>,
-  ) => Stream.Stream<SpeechEvent, AIError>
-}
+export type Interface = MediaClient.Interface<SpeechRequestFor, SpeechEvent, SpeechResponse>

 export class SpeechClientService extends Context.Service<SpeechClientService, Interface>()("@opencode/SpeechClient") {}
 export const Service = SpeechClientService
 export type Service = SpeechClientService

-export const generate = <Options extends SpeechOptions>(
-  request: SpeechRequestFor<Options>,
-): Effect.Effect<SpeechResponse, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.generate(request)
-  })
-
-export const stream = <Options extends SpeechOptions>(
-  request: SpeechRequestFor<Options>,
-): Stream.Stream<SpeechEvent, AIError, Service> =>
-  Stream.unwrap(
-    Effect.gen(function* () {
-      const client = yield* Service
-      return client.stream(request)
-    }),
-  )
-
-export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
-  Service,
-  Effect.gen(function* () {
-    const executor = yield* RequestExecutor.Service
-    return Service.of({
-      generate: (request) => request.model.route.generate(request, executor.execute),
-      stream: (request) => request.model.route.stream(request, executor.execute),
-    })
-  }),
-)
-
 export const SpeechClient = {
  Service,
-  layer,
-  generate,
-  stream,
+  ...MediaClient.make(Service, {
+    modality: "speech",
+    responseEvents: (response: SpeechResponse) => [
+      ...(response.timestamps === undefined ? [] : [SpeechTimestampsEvent.make({ items: response.timestamps })]),
+      SpeechFinishEvent.make({
+        audio: response.audio,
+        usage: response.usage,
+        notices: response.notices,
+        providerMetadata: response.providerMetadata,
+      }),
+    ],
+  }),
 } as const
@@ -1,8 +1,8 @@
 import { Effect, Schema, Stream } from "effect"
+import { ProgressEvent, QueuedEvent } from "./generation.js"
 import { Media } from "./media.js"
 import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
 import { MediaRoute } from "./route/media.js"
-import type { MediaProtocol } from "./route/media-protocol.js"
 import { AIError, HttpOptions, MediaUsage, ProviderMetadata, type OpenString } from "./schema/index.js"
 import { SpeechClient, Service } from "./speech-client.js"

@@ -10,53 +10,39 @@ import { SpeechClient, Service } from "./speech-client.js"
 // Model
 // ---------------------------------------------------------------------------

-export type SpeechOptions = Record<string, unknown>
+export type SpeechOptions = MediaModel.Options

-export type SpeechRoute<Options extends SpeechOptions = SpeechOptions> = MediaRoute.StreamRoute<
-  SpeechRequestFor<Options>,
-  SpeechEvent,
-  SpeechResponse
->
+export type SpeechRoute = MediaRoute.AnyRoute<SpeechRequestFor, SpeechEvent, SpeechResponse>

-export class SpeechModel<Options extends SpeechOptions = SpeechOptions> extends MediaModel<
-  SpeechRoute<Options>,
-  Options
-> {
+export class SpeechModel<Options extends SpeechOptions = SpeechOptions> extends MediaModel<SpeechRoute, Options> {
  declare protected readonly _SpeechModel: void

-  static make<Options extends SpeechOptions = SpeechOptions>(input: MediaModel.Input<SpeechRoute<Options>>) {
-    return new SpeechModel<Options>(input)
-  }
-
-  /** Compose a streaming speech protocol with its canonical path into a model for one deployment. */
-  static fromRoute<Options extends SpeechOptions = SpeechOptions, Frame = unknown, State = unknown>(
-    route: SpeechModel.RouteInput<Options, Frame, State>,
+  /** The number of type arguments selects the kind: `<Options>`, `<Options, Frame, State>`, or `<Options, Token>`. */
+  static fromRoute<Options extends SpeechOptions>(
+    route: MediaModel.InlineRouteInput<SpeechRequestFor<Options>, SpeechResponse>,
+    input: MediaRoute.ModelInput,
+  ): SpeechModel<Options>
+  static fromRoute<Options extends SpeechOptions, Frame, State>(
+    route: MediaModel.StreamRouteInput<SpeechRequestFor<Options>, SpeechEvent, Frame, State>,
+    input: MediaRoute.ModelInput,
+  ): SpeechModel<Options>
+  static fromRoute<Options extends SpeechOptions, Token>(
+    route: MediaModel.QueuedRouteInput<SpeechRequestFor<Options>, SpeechResponse, Token>,
+    input: MediaRoute.ModelInput,
+  ): SpeechModel<Options>
+  static fromRoute<Options extends SpeechOptions, Frame, State, Token>(
+    route: MediaModel.AnyRouteInput<SpeechRequestFor<Options>, SpeechEvent, SpeechResponse, Frame, State, Token>,
    input: MediaRoute.ModelInput,
  ) {
    return new SpeechModel<Options>({
      id: input.id,
      provider: route.protocol.provider,
      http: input.http,
-      route: composeRoute(
-        (composition) => MediaRoute.stream({ ...composition, collect: collectResponse }),
-        route,
-        input,
-      ),
+      route: composeRoute(route, input, collectResponse) as SpeechRoute,
    })
  }
 }

-export namespace SpeechModel {
-  export type RouteInput<
-    Options extends SpeechOptions = SpeechOptions,
-    Frame = unknown,
-    State = unknown,
-  > = MediaModel.RouteInput<
-    MediaProtocol.Addressed<SpeechRequestFor<Options>>,
-    MediaProtocol.Streamed<SpeechRequestFor<Options>, SpeechEvent, Frame, State>
-  >
-}
-
 export const SpeechModelSchema = Schema.declare((value): value is SpeechModel => value instanceof SpeechModel, {
  expected: "Speech.Model",
 })
@@ -148,11 +134,17 @@ export const SpeechFinishEvent = Schema.Struct({
  providerMetadata: Schema.optional(ProviderMetadata),
 }).annotate({ identifier: "Speech.Event.Finish" })

-const speechEventTagged = Schema.Union([SpeechAudioDeltaEvent, SpeechTimestampsEvent, SpeechFinishEvent]).pipe(
-  Schema.toTaggedUnion("type"),
-)
+const speechEventTagged = Schema.Union([
+  QueuedEvent,
+  ProgressEvent,
+  SpeechAudioDeltaEvent,
+  SpeechTimestampsEvent,
+  SpeechFinishEvent,
+]).pipe(Schema.toTaggedUnion("type"))
 export const SpeechEvent = Object.assign(speechEventTagged, {
  is: {
+    generationQueued: speechEventTagged.guards["generation-queued"],
+    generationProgress: speechEventTagged.guards["generation-progress"],
    audioDelta: speechEventTagged.guards["audio-delta"],
    timestamps: speechEventTagged.guards.timestamps,
    finish: speechEventTagged.guards.finish,
@@ -195,17 +187,15 @@ export function request(input: SpeechRequest | SpeechRequestInput) {
 const requestEffect = (input: SpeechRequest | SpeechRequestInput) => tryRequest(() => request(input))

 export function generate<const Model extends SpeechModel>(
-  input: SpeechRequestInput<Model>,
+  input: SpeechRequest | SpeechRequestInput<Model>,
 ): Effect.Effect<SpeechResponse, AIError, Service>
-export function generate(input: SpeechRequest): Effect.Effect<SpeechResponse, AIError, Service>
 export function generate(input: SpeechRequest | SpeechRequestInput) {
  return requestEffect(input).pipe(Effect.flatMap((request) => SpeechClient.generate(request)))
 }

 export function stream<const Model extends SpeechModel>(
-  input: SpeechRequestInput<Model>,
+  input: SpeechRequest | SpeechRequestInput<Model>,
 ): Stream.Stream<SpeechEvent, AIError, Service>
-export function stream(input: SpeechRequest): Stream.Stream<SpeechEvent, AIError, Service>
 export function stream(input: SpeechRequest | SpeechRequestInput) {
  return Stream.unwrap(requestEffect(input).pipe(Effect.map((request) => SpeechClient.stream(request))))
 }
@@ -1,34 +1,13 @@
-import { Context, Effect, Layer, Stream } from "effect"
-import type { AwaitOptions, Generation } from "./generation.js"
-import { RequestExecutor } from "./route/executor.js"
-import { MediaRoute } from "./route/media.js"
-import type { AIError } from "./schema/index.js"
+import { Context } from "effect"
+import { MediaClient } from "./media-client.js"
 import {
-  responseEvents,
+  TranscriptionFinishEvent,
  type TranscriptionEvent,
-  type TranscriptionModel,
-  type TranscriptionOptions,
  type TranscriptionRequestFor,
  type TranscriptionResponse,
 } from "./transcription.js"

-export interface Interface {
-  readonly generate: <Options extends TranscriptionOptions>(
-    request: TranscriptionRequestFor<Options>,
-    options?: AwaitOptions,
-  ) => Effect.Effect<TranscriptionResponse, AIError>
-  readonly stream: <Options extends TranscriptionOptions>(
-    request: TranscriptionRequestFor<Options>,
-    options?: AwaitOptions,
-  ) => Stream.Stream<TranscriptionEvent, AIError>
-  readonly start: <Options extends TranscriptionOptions>(
-    request: TranscriptionRequestFor<Options>,
-  ) => Effect.Effect<Generation<TranscriptionResponse>, AIError>
-  readonly resume: <Options extends TranscriptionOptions>(
-    model: TranscriptionModel<Options>,
-    token: unknown,
-  ) => Effect.Effect<Generation<TranscriptionResponse>, AIError>
-}
+export type Interface = MediaClient.Interface<TranscriptionRequestFor, TranscriptionEvent, TranscriptionResponse>

 export class TranscriptionClientService extends Context.Service<TranscriptionClientService, Interface>()(
  "@opencode/TranscriptionClient",
@@ -36,66 +15,10 @@ export class TranscriptionClientService extends Context.Service<TranscriptionCli
 export const Service = TranscriptionClientService
 export type Service = TranscriptionClientService

-export const generate = <Options extends TranscriptionOptions>(
-  request: TranscriptionRequestFor<Options>,
-  options?: AwaitOptions,
-): Effect.Effect<TranscriptionResponse, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.generate(request, options)
-  })
-
-export const stream = <Options extends TranscriptionOptions>(
-  request: TranscriptionRequestFor<Options>,
-  options?: AwaitOptions,
-): Stream.Stream<TranscriptionEvent, AIError, Service> =>
-  Stream.unwrap(
-    Effect.gen(function* () {
-      const client = yield* Service
-      return client.stream(request, options)
-    }),
-  )
-
-export const start = <Options extends TranscriptionOptions>(
-  request: TranscriptionRequestFor<Options>,
-): Effect.Effect<Generation<TranscriptionResponse>, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.start(request)
-  })
-
-export const resume = <Options extends TranscriptionOptions>(
-  model: TranscriptionModel<Options>,
-  token: unknown,
-): Effect.Effect<Generation<TranscriptionResponse>, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.resume(model, token)
-  })
-
-export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
-  Service,
-  Effect.gen(function* () {
-    const executor = yield* RequestExecutor.Service
-    const dispatch = MediaRoute.dispatch<TranscriptionEvent, TranscriptionResponse>({
-      modality: "transcription",
-      execute: executor.execute,
-      responseEvents,
-    })
-    return Service.of({
-      start: (request) => dispatch.start(request.model.route, request),
-      resume: (model, token) => dispatch.resume(model.route, model, token),
-      generate: (request, options) => dispatch.generate(request.model.route, request, options),
-      stream: (request, options) => dispatch.stream(request.model.route, request, options),
-    })
-  }),
-)
-
 export const TranscriptionClient = {
  Service,
-  layer,
-  generate,
-  stream,
-  start,
-  resume,
+  ...MediaClient.make(Service, {
+    modality: "transcription",
+    responseEvents: (response: TranscriptionResponse) => [TranscriptionFinishEvent.make({ ...response })],
+  }),
 } as const
@@ -1,9 +1,8 @@
 import { Effect, Schema, Stream } from "effect"
 import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
 import { Media } from "./media.js"
-import { MediaModel, composeAnyRoute, tryRequest } from "./media-model.js"
+import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
 import { MediaRoute } from "./route/media.js"
-import type { MediaProtocol } from "./route/media-protocol.js"
 import { AIError, HttpOptions, MediaUsage, ProviderMetadata } from "./schema/index.js"
 import { TranscriptionClient, Service } from "./transcription-client.js"

@@ -11,90 +10,49 @@ import { TranscriptionClient, Service } from "./transcription-client.js"
 // Model
 // ---------------------------------------------------------------------------

-export type TranscriptionOptions = Record<string, unknown>
+export type TranscriptionOptions = MediaModel.Options

-export type TranscriptionRoute<Options extends TranscriptionOptions = TranscriptionOptions> = MediaRoute.AnyRoute<
-  TranscriptionRequestFor<Options>,
-  TranscriptionEvent,
-  TranscriptionResponse
->
+export type TranscriptionRoute = MediaRoute.AnyRoute<TranscriptionRequestFor, TranscriptionEvent, TranscriptionResponse>

 export class TranscriptionModel<Options extends TranscriptionOptions = TranscriptionOptions> extends MediaModel<
-  TranscriptionRoute<Options>,
+  TranscriptionRoute,
  Options
 > {
  declare protected readonly _TranscriptionModel: void

-  static make<Options extends TranscriptionOptions = TranscriptionOptions>(
-    input: MediaModel.Input<TranscriptionRoute<Options>>,
-  ) {
-    return new TranscriptionModel<Options>(input)
-  }
-
  /** The number of type arguments selects the kind: `<Options>`, `<Options, Frame, State>`, or `<Options, Token>`. */
  static fromRoute<Options extends TranscriptionOptions>(
-    route: TranscriptionModel.InlineRouteInput<Options>,
+    route: MediaModel.InlineRouteInput<TranscriptionRequestFor<Options>, TranscriptionResponse>,
    input: MediaRoute.ModelInput,
  ): TranscriptionModel<Options>
  static fromRoute<Options extends TranscriptionOptions, Frame, State>(
-    route: TranscriptionModel.StreamRouteInput<Options, Frame, State>,
+    route: MediaModel.StreamRouteInput<TranscriptionRequestFor<Options>, TranscriptionEvent, Frame, State>,
    input: MediaRoute.ModelInput,
  ): TranscriptionModel<Options>
  static fromRoute<Options extends TranscriptionOptions, Token>(
-    route: TranscriptionModel.QueuedRouteInput<Options, Token>,
+    route: MediaModel.QueuedRouteInput<TranscriptionRequestFor<Options>, TranscriptionResponse, Token>,
    input: MediaRoute.ModelInput,
  ): TranscriptionModel<Options>
  static fromRoute<Options extends TranscriptionOptions, Frame, State, Token>(
-    route: TranscriptionModel.RouteInput<Options, Frame, State, Token>,
+    route: MediaModel.AnyRouteInput<
+      TranscriptionRequestFor<Options>,
+      TranscriptionEvent,
+      TranscriptionResponse,
+      Frame,
+      State,
+      Token
+    >,
    input: MediaRoute.ModelInput,
  ) {
    return new TranscriptionModel<Options>({
      id: input.id,
      provider: route.protocol.provider,
      http: input.http,
-      route: composeAnyRoute(route, input, collectResponse),
+      route: composeRoute(route, input, collectResponse) as TranscriptionRoute,
    })
  }
 }

-export namespace TranscriptionModel {
-  export type InlineRouteInput<Options extends TranscriptionOptions = TranscriptionOptions> = MediaModel.RouteInput<
-    TranscriptionRequestFor<Options>,
-    MediaProtocol.Inline<TranscriptionRequestFor<Options>, TranscriptionResponse>
-  >
-
-  export type StreamRouteInput<
-    Options extends TranscriptionOptions = TranscriptionOptions,
-    Frame = unknown,
-    State = unknown,
-  > = MediaModel.RouteInput<
-    MediaProtocol.Addressed<TranscriptionRequestFor<Options>>,
-    MediaProtocol.Streamed<TranscriptionRequestFor<Options>, TranscriptionEvent, Frame, State>
-  >
-
-  export type QueuedRouteInput<
-    Options extends TranscriptionOptions = TranscriptionOptions,
-    Token = unknown,
-  > = MediaModel.RouteInput<
-    TranscriptionRequestFor<Options>,
-    MediaProtocol.Queued<TranscriptionRequestFor<Options>, TranscriptionResponse, Token>
-  >
-
-  export type RouteInput<
-    Options extends TranscriptionOptions = TranscriptionOptions,
-    Frame = unknown,
-    State = unknown,
-    Token = unknown,
-  > = MediaModel.AnyRouteInput<
-    TranscriptionRequestFor<Options>,
-    TranscriptionEvent,
-    TranscriptionResponse,
-    Frame,
-    State,
-    Token
-  >
-}
-
 export const TranscriptionModelSchema = Schema.declare(
  (value): value is TranscriptionModel => value instanceof TranscriptionModel,
  { expected: "Transcription.Model" },
@@ -145,7 +103,7 @@ export type TranscriptionRequestInput<Model extends TranscriptionModel = Transcr
 // Response and events
 // ---------------------------------------------------------------------------

-/** Speaker labels are provider-native (`A`, `0`, `spk:0`, or a known speaker name). */
+/** Speaker labels are provider-native (`A`, `0`, `spk:0`, `speaker_0`, or a known speaker name). */
 export const TranscriptionSegment = Schema.Struct({
  text: Schema.String,
  startSeconds: Schema.Number,
@@ -212,10 +170,6 @@ export const TranscriptionEvent = Object.assign(transcriptionEventTagged, {
 })
 export type TranscriptionEvent = Schema.Schema.Type<typeof transcriptionEventTagged>

-export const responseEvents = (response: TranscriptionResponse): ReadonlyArray<TranscriptionEvent> => [
-  TranscriptionFinishEvent.make({ ...response }),
-]
-
 const collectResponse = (events: ReadonlyArray<TranscriptionEvent>): Effect.Effect<TranscriptionResponse> => {
  const finish = events.find(TranscriptionEvent.is.finish)
  // Every transcription protocol's `finish` emits the terminal event or fails, so a completed stream always has one.
@@ -243,11 +197,7 @@ export function request(input: TranscriptionRequest | TranscriptionRequestInput)
 const requestEffect = (input: TranscriptionRequest | TranscriptionRequestInput) => tryRequest(() => request(input))

 export function generate<const Model extends TranscriptionModel>(
-  input: TranscriptionRequestInput<Model>,
-  options?: AwaitOptions,
-): Effect.Effect<TranscriptionResponse, AIError, Service>
-export function generate(
-  input: TranscriptionRequest,
+  input: TranscriptionRequest | TranscriptionRequestInput<Model>,
  options?: AwaitOptions,
 ): Effect.Effect<TranscriptionResponse, AIError, Service>
 export function generate(input: TranscriptionRequest | TranscriptionRequestInput, options?: AwaitOptions) {
@@ -255,11 +205,7 @@ export function generate(input: TranscriptionRequest | TranscriptionRequestInput
 }

 export function stream<const Model extends TranscriptionModel>(
-  input: TranscriptionRequestInput<Model>,
-  options?: AwaitOptions,
-): Stream.Stream<TranscriptionEvent, AIError, Service>
-export function stream(
-  input: TranscriptionRequest,
+  input: TranscriptionRequest | TranscriptionRequestInput<Model>,
  options?: AwaitOptions,
 ): Stream.Stream<TranscriptionEvent, AIError, Service>
 export function stream(input: TranscriptionRequest | TranscriptionRequestInput, options?: AwaitOptions) {
@@ -268,15 +214,14 @@ export function stream(input: TranscriptionRequest | TranscriptionRequestInput,

 /** Inline and streaming routes fail with `UnsupportedOperation`. */
 export function start<const Model extends TranscriptionModel>(
-  input: TranscriptionRequestInput<Model>,
+  input: TranscriptionRequest | TranscriptionRequestInput<Model>,
 ): Effect.Effect<Generation<TranscriptionResponse>, AIError, Service>
-export function start(input: TranscriptionRequest): Effect.Effect<Generation<TranscriptionResponse>, AIError, Service>
 export function start(input: TranscriptionRequest | TranscriptionRequestInput) {
  return requestEffect(input).pipe(Effect.flatMap((request) => TranscriptionClient.start(request)))
 }

-export const resume = <Options extends TranscriptionOptions>(
-  model: TranscriptionModel<Options>,
+export const resume = (
+  model: TranscriptionModel,
  token: unknown,
 ): Effect.Effect<Generation<TranscriptionResponse>, AIError, Service> => TranscriptionClient.resume(model, token)

@@ -1,98 +1,30 @@
-import { Context, Effect, Layer, Stream } from "effect"
-import { resultEvents, type AwaitOptions, type Generation } from "./generation.js"
-import { RequestExecutor } from "./route/executor.js"
-import type { AIError } from "./schema/index.js"
+import { Context } from "effect"
+import { MediaClient } from "./media-client.js"
 import {
-  responseEvents,
+  VideoOutputEvent,
+  VideoFinishEvent,
  type VideoEvent,
-  type VideoModel,
-  type VideoOptions,
  type VideoRequestFor,
  type VideoResponse,
 } from "./video.js"

-export interface Interface {
-  readonly start: <Options extends VideoOptions>(
-    request: VideoRequestFor<Options>,
-  ) => Effect.Effect<Generation<VideoResponse>, AIError>
-  readonly resume: <Options extends VideoOptions>(
-    model: VideoModel<Options>,
-    token: unknown,
-  ) => Effect.Effect<Generation<VideoResponse>, AIError>
-  readonly generate: <Options extends VideoOptions>(
-    request: VideoRequestFor<Options>,
-    options?: AwaitOptions,
-  ) => Effect.Effect<VideoResponse, AIError>
-  readonly stream: <Options extends VideoOptions>(
-    request: VideoRequestFor<Options>,
-    options?: AwaitOptions,
-  ) => Stream.Stream<VideoEvent, AIError>
-}
+export type Interface = MediaClient.Interface<VideoRequestFor, VideoEvent, VideoResponse>

 export class VideoClientService extends Context.Service<VideoClientService, Interface>()("@opencode/VideoClient") {}
 export const Service = VideoClientService
 export type Service = VideoClientService

-export const start = <Options extends VideoOptions>(
-  request: VideoRequestFor<Options>,
-): Effect.Effect<Generation<VideoResponse>, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.start(request)
-  })
-
-export const resume = <Options extends VideoOptions>(
-  model: VideoModel<Options>,
-  token: unknown,
-): Effect.Effect<Generation<VideoResponse>, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.resume(model, token)
-  })
-
-export const generate = <Options extends VideoOptions>(
-  request: VideoRequestFor<Options>,
-  options?: AwaitOptions,
-): Effect.Effect<VideoResponse, AIError, Service> =>
-  Effect.gen(function* () {
-    const client = yield* Service
-    return yield* client.generate(request, options)
-  })
-
-export const stream = <Options extends VideoOptions>(
-  request: VideoRequestFor<Options>,
-  options?: AwaitOptions,
-): Stream.Stream<VideoEvent, AIError, Service> =>
-  Stream.unwrap(
-    Effect.gen(function* () {
-      const client = yield* Service
-      return client.stream(request, options)
-    }),
-  )
-
-export const layer: Layer.Layer<Service, never, RequestExecutor.Service> = Layer.effect(
-  Service,
-  Effect.gen(function* () {
-    const executor = yield* RequestExecutor.Service
-    const start = <Options extends VideoOptions>(request: VideoRequestFor<Options>) =>
-      request.model.route.start(request, executor.execute)
-    return Service.of({
-      start,
-      resume: (model, token) => model.route.resume(model, token, executor.execute),
-      generate: (request, options) => start(request).pipe(Effect.flatMap((generation) => generation.await(options))),
-      stream: (request, options) =>
-        Stream.unwrap(
-          start(request).pipe(Effect.map((generation) => resultEvents(generation, responseEvents, options))),
-        ),
-    })
-  }),
-)
-
 export const VideoClient = {
  Service,
-  layer,
-  start,
-  resume,
-  generate,
-  stream,
+  ...MediaClient.make(Service, {
+    modality: "video",
+    responseEvents: (response: VideoResponse) => [
+      ...response.videos.map((video, index) => VideoOutputEvent.make({ index, video })),
+      VideoFinishEvent.make({
+        usage: response.usage,
+        notices: response.notices,
+        providerMetadata: response.providerMetadata,
+      }),
+    ],
+  }),
 } as const
@@ -3,7 +3,6 @@ import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./gen
 import { Media } from "./media.js"
 import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
 import { MediaRoute } from "./route/media.js"
-import type { MediaProtocol } from "./route/media-protocol.js"
 import { AIError, HttpOptions, MediaUsage, ProviderMetadata, type OpenString } from "./schema/index.js"
 import { VideoClient, Service } from "./video-client.js"

@@ -11,41 +10,39 @@ import { VideoClient, Service } from "./video-client.js"
 // Model
 // ---------------------------------------------------------------------------

-export type VideoOptions = Record<string, unknown>
+export type VideoOptions = MediaModel.Options

-export type VideoRoute<Options extends VideoOptions = VideoOptions> = MediaRoute.QueuedRoute<
-  VideoRequestFor<Options>,
-  VideoResponse
->
+export type VideoRoute = MediaRoute.AnyRoute<VideoRequestFor, VideoEvent, VideoResponse>

-export class VideoModel<Options extends VideoOptions = VideoOptions> extends MediaModel<VideoRoute<Options>, Options> {
+export class VideoModel<Options extends VideoOptions = VideoOptions> extends MediaModel<VideoRoute, Options> {
  declare protected readonly _VideoModel: void

-  static make<Options extends VideoOptions = VideoOptions>(input: MediaModel.Input<VideoRoute<Options>>) {
-    return new VideoModel<Options>(input)
-  }
-
-  /** Compose a queued video protocol with its canonical start path into a model for one deployment. */
-  static fromRoute<Options extends VideoOptions = VideoOptions, Token = unknown>(
-    route: VideoModel.RouteInput<Options, Token>,
+  /** The number of type arguments selects the kind: `<Options>`, `<Options, Frame, State>`, or `<Options, Token>`. */
+  static fromRoute<Options extends VideoOptions>(
+    route: MediaModel.InlineRouteInput<VideoRequestFor<Options>, VideoResponse>,
+    input: MediaRoute.ModelInput,
+  ): VideoModel<Options>
+  static fromRoute<Options extends VideoOptions, Frame, State>(
+    route: MediaModel.StreamRouteInput<VideoRequestFor<Options>, VideoEvent, Frame, State>,
+    input: MediaRoute.ModelInput,
+  ): VideoModel<Options>
+  static fromRoute<Options extends VideoOptions, Token>(
+    route: MediaModel.QueuedRouteInput<VideoRequestFor<Options>, VideoResponse, Token>,
+    input: MediaRoute.ModelInput,
+  ): VideoModel<Options>
+  static fromRoute<Options extends VideoOptions, Frame, State, Token>(
+    route: MediaModel.AnyRouteInput<VideoRequestFor<Options>, VideoEvent, VideoResponse, Frame, State, Token>,
    input: MediaRoute.ModelInput,
  ) {
    return new VideoModel<Options>({
      id: input.id,
      provider: route.protocol.provider,
      http: input.http,
-      route: composeRoute(MediaRoute.queued, route, input),
+      route: composeRoute(route, input, collectResponse) as VideoRoute,
    })
  }
 }

-export namespace VideoModel {
-  export type RouteInput<Options extends VideoOptions = VideoOptions, Token = unknown> = MediaModel.RouteInput<
-    VideoRequestFor<Options>,
-    MediaProtocol.Queued<VideoRequestFor<Options>, VideoResponse, Token>
-  >
-}
-
 export const VideoModelSchema = Schema.declare((value): value is VideoModel => value instanceof VideoModel, {
  expected: "Video.Model",
 })
@@ -149,15 +146,19 @@ export const VideoEvent = Object.assign(videoEventTagged, {
 })
 export type VideoEvent = Schema.Schema.Type<typeof videoEventTagged>

-/** A completed response expanded into the streaming event shape. */
-export const responseEvents = (response: VideoResponse): ReadonlyArray<VideoEvent> => [
-  ...response.videos.map((video, index) => VideoOutputEvent.make({ index, video })),
-  VideoFinishEvent.make({
-    usage: response.usage,
-    notices: response.notices,
-    providerMetadata: response.providerMetadata,
-  }),
-]
+const collectResponse = (events: ReadonlyArray<VideoEvent>): Effect.Effect<VideoResponse> => {
+  const finish = events.find(VideoEvent.is.finish)
+  // A streaming video protocol's `finish` emits the terminal event or fails, so a completed stream always has one.
+  if (finish === undefined) return Effect.die(new Error("The video stream completed without a finish event"))
+  return Effect.succeed(
+    new VideoResponse({
+      videos: events.filter(VideoEvent.is.video).map((event) => event.video),
+      usage: finish.usage,
+      notices: finish.notices,
+      providerMetadata: finish.providerMetadata,
+    }),
+  )
+}

 // ---------------------------------------------------------------------------
 // Request-shaped call API
@@ -178,33 +179,28 @@ export function request(input: VideoRequest | VideoRequestInput) {
 const requestEffect = (input: VideoRequest | VideoRequestInput) => tryRequest(() => request(input))

 export function start<const Model extends VideoModel>(
-  input: VideoRequestInput<Model>,
+  input: VideoRequest | VideoRequestInput<Model>,
 ): Effect.Effect<Generation<VideoResponse>, AIError, Service>
-export function start(input: VideoRequest): Effect.Effect<Generation<VideoResponse>, AIError, Service>
 export function start(input: VideoRequest | VideoRequestInput) {
  return requestEffect(input).pipe(Effect.flatMap((request) => VideoClient.start(request)))
 }

 export function generate<const Model extends VideoModel>(
-  input: VideoRequestInput<Model>,
+  input: VideoRequest | VideoRequestInput<Model>,
  options?: AwaitOptions,
 ): Effect.Effect<VideoResponse, AIError, Service>
-export function generate(input: VideoRequest, options?: AwaitOptions): Effect.Effect<VideoResponse, AIError, Service>
 export function generate(input: VideoRequest | VideoRequestInput, options?: AwaitOptions) {
  return requestEffect(input).pipe(Effect.flatMap((request) => VideoClient.generate(request, options)))
 }

 /** Rebuild a generation handle from a persisted `Generation.token`, refreshing its status once. */
-export const resume = <Options extends VideoOptions>(
-  model: VideoModel<Options>,
-  token: unknown,
-): Effect.Effect<Generation<VideoResponse>, AIError, Service> => VideoClient.resume(model, token)
+export const resume = (model: VideoModel, token: unknown): Effect.Effect<Generation<VideoResponse>, AIError, Service> =>
+  VideoClient.resume(model, token)

 export function stream<const Model extends VideoModel>(
-  input: VideoRequestInput<Model>,
+  input: VideoRequest | VideoRequestInput<Model>,
  options?: AwaitOptions,
 ): Stream.Stream<VideoEvent, AIError, Service>
-export function stream(input: VideoRequest, options?: AwaitOptions): Stream.Stream<VideoEvent, AIError, Service>
 export function stream(input: VideoRequest | VideoRequestInput, options?: AwaitOptions) {
  return Stream.unwrap(requestEffect(input).pipe(Effect.map((request) => VideoClient.stream(request, options))))
 }
@@ -351,10 +351,34 @@ describe("OpenAI Responses effort updates", () => {
    }),
  )

+  it.effect("strips markers when the body overlay selects pro reasoning mode", () =>
+    Effect.gen(function* () {
+      const prepared = yield* compileRequest(
+        LLM.request({
+          model: OpenAI.configure({ apiKey: "fixture", http: { body: { reasoning: { mode: "pro" } } } }).responses(
+            "gpt-6-sol",
+          ),
+          messages: conversation,
+          providerOptions: { reasoningEffort: "low" },
+        }),
+      )
+
+      expect(updates(prepared.body)).toEqual([])
+      expect(prepared.body.reasoning).toEqual({ effort: "low" })
+    }),
+  )
+
  for (const [id, supported] of [
    ["gpt-6-astra", true],
    ["openai/gpt-6-astra", true],
+    ["gpt-6-sol", true],
+    ["openai/gpt-6-sol", true],
+    ["gpt-6-luna", true],
+    ["openai/gpt-6-luna", true],
    ["gpt-6-astra-2026-09-01", false],
+    ["gpt-6-sol-pro", false],
+    ["gpt-6-luna-pro", false],
+    ["gpt-6-sol-fast", false],
    ["gpt-5.6-sol", false],
  ] as const) {
    it.effect(`${supported ? "lowers" : "strips"} markers for ${id}`, () =>
@@ -23,6 +23,7 @@ import { Provider as ProviderSubpath } from "@opencode/ai/provider"
 import {
  AssemblyAI,
  Baseten,
+  BlackForestLabs,
  Cartesia,
  CloudflareAIGateway,
  CloudflareWorkersAI,
@@ -32,14 +33,18 @@ import {
  Fal,
  Fireworks,
  Google,
+  Meta,
  OpenCodeZen,
  OpenAI,
  OpenAICompatible,
  OpenRouter,
+  Replicate,
  Runway,
+  Stability,
  TypeSafeAI,
  VercelAIGateway,
  XAI,
+  ZAI,
 } from "@opencode/ai/providers"
 import {
  OpenAIChat,
@@ -54,6 +59,19 @@ import { TestLLM } from "@opencode/ai/testing"
 import { Evaluation, EvaluationClient } from "@opencode/ai/experimental"

 describe("public exports", () => {
+  test("modality, provider, and protocol entrypoints load first in a fresh process", async () => {
+    const results = await Promise.all(
+      ["image", "video", "speech", "transcription", "providers", "protocols"].map(async (entry) => {
+        const child = Bun.spawn(
+          [process.execPath, "-e", `await import(${JSON.stringify(`${import.meta.dir}/../src/${entry}.ts`)})`],
+          { stderr: "pipe" },
+        )
+        return { entry, exitCode: await child.exited, stderr: await new Response(child.stderr).text() }
+      }),
+    )
+    expect(results.filter((result) => result.exitCode !== 0)).toEqual([])
+  })
+
  test("root exposes app-facing runtime APIs", () => {
    expect(LLM.request).toBeFunction()
    expect(LLMClient.Service).toBeFunction()
@@ -138,8 +156,34 @@ describe("public exports", () => {
    expect(XAI.provider.chat).toBe(XAI.chat)
    expect(XAI.configure({ apiKey: "fixture" }).responses("grok-4.3").route.id).toBe("openai-responses")
    expect(XAI.configure({ apiKey: "fixture" }).chat("grok-4.3").route.id).toBe("openai-compatible-chat")
+    expect(OpenAI.configure({ apiKey: "fixture" }).image("gpt-image-2").route.id).toBe("openai-images")
+    expect(OpenAI.provider.image).toBe(OpenAI.image)
+    expect(Google.configure({ apiKey: "fixture" }).image("imagen-4.0-generate-001").route.id).toBe("google-images")
+    expect(Google.provider.image).toBe(Google.image)
+    expect(XAI.configure({ apiKey: "fixture" }).image("grok-imagine-image").route.id).toBe("xai-images")
+    expect(XAI.provider.image).toBe(XAI.image)
+    expect(Fal.configure({ apiKey: "fixture" }).image("fal-ai/flux/dev").route.id).toBe("fal-images")
+    expect(Fal.provider.image).toBe(Fal.image)
+    expect(BlackForestLabs.configure({ apiKey: "fixture" }).image("flux-2-pro").route.id).toBe("bfl-images")
+    expect(BlackForestLabs.provider.image).toBe(BlackForestLabs.image)
+    expect(Replicate.configure({ apiKey: "fixture" }).image("black-forest-labs/flux-schnell").route.id).toBe(
+      "replicate-images",
+    )
+    expect(Replicate.provider.image).toBe(Replicate.image)
+    expect(Stability.configure({ apiKey: "fixture" }).image("sd3.5-large").route.id).toBe("stability-images")
+    expect(Stability.provider.image).toBe(Stability.image)
+    expect(Stability.configure({ apiKey: "fixture" }).upscale().route.id).toBe("stability-upscale")
+    expect(Stability.provider.upscale).toBe(Stability.upscale)
+    expect(Meta.configure({ apiKey: "fixture" }).image("muse-image").route.id).toBe("meta-images")
+    expect(Meta.provider.image).toBe(Meta.image)
+    expect(ZAI.configure({ apiKey: "fixture" }).image("glm-image").route.id).toBe("zai-images")
+    expect(ZAI.provider.image).toBe(ZAI.image)
    expect(XAI.configure({ apiKey: "fixture" }).video("grok-imagine-video-1.5").route.id).toBe("xai-video")
+    expect(XAI.provider.video).toBe(XAI.video)
+    expect(Google.configure({ apiKey: "fixture" }).video("veo-3.1-generate-preview").route.id).toBe("google-video")
+    expect(Google.provider.video).toBe(Google.video)
    expect(Fal.configure({ apiKey: "fixture" }).video("fal-ai/veo3.1").route.id).toBe("fal-video")
+    expect(Fal.provider.video).toBe(Fal.video)
    expect(Runway.configure({ apiKey: "fixture" }).video("gen4.5").route.id).toBe("runway-video")
    expect(Runway.provider.video).toBe(Runway.video)
    expect(OpenAI.configure({ apiKey: "fixture" }).speech("gpt-4o-mini-tts").route.id).toBe("openai-speech")
@@ -153,6 +197,11 @@ describe("public exports", () => {
    expect(Google.configure({ apiKey: "fixture" }).transcription("gemini-3.5-transcribe").route.kind).toBe("stream")
    expect(Deepgram.configure({ apiKey: "fixture" }).transcription("nova-3").route.kind).toBe("inline")
    expect(AssemblyAI.configure({ apiKey: "fixture" }).transcription("universal-3-5-pro").route.kind).toBe("queued")
+    expect(ElevenLabs.configure({ apiKey: "fixture" }).transcription("scribe_v2").route.id).toBe(
+      "elevenlabs-transcription",
+    )
+    expect(ElevenLabs.configure({ apiKey: "fixture" }).transcription("scribe_v2").route.kind).toBe("inline")
+    expect(ElevenLabs.provider.transcription).toBe(ElevenLabs.transcription)
  })

  test("protocol barrels expose supported low-level routes", () => {
@@ -0,0 +1,32 @@
+{
+  "version": 1,
+  "metadata": {
+    "tags": [
+      "prefix:elevenlabs-transcription",
+      "provider:elevenlabs",
+      "protocol:elevenlabs-transcription"
+    ],
+    "name": "elevenlabs-transcription/groups-diarized-words-into-speaker-turns",
+    "recordedAt": "2026-09-27T09:35:28.265Z"
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.elevenlabs.io/v1/speech-to-text",
+        "headers": {
+          "content-type": "multipart/form-data; boundary=----WebKitFormBoundary356bdc14864a477dbacbfcf60d1ecceb"
+        },
+        "body": "--BOUNDARY\r\nContent-Disposition: form-data; name=\"file\"; filename=\"audio.mp3\"\r\nContent-Type: audio/mpeg\r\n\r\n[audio]\r\n--BOUNDARY\r\nContent-Disposition: form-data; name=\"model_id\"\r\n\r\nscribe_v2\r\n--BOUNDARY\r\nContent-Disposition: form-data; name=\"diarize\"\r\n\r\ntrue\r\n--BOUNDARY--\r\n"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "application/json"
+        },
+        "body": "{\"language_code\":\"eng\",\"language_probability\":0.9495430588722229,\"text\":\"Did the release ship? Yes, it shipped this morning\",\"words\":[{\"text\":\"Did\",\"start\":0.34,\"end\":0.44,\"type\":\"word\",\"speaker_id\":\"speaker_0\",\"logprob\":-1.7881377516459906e-6},{\"text\":\" \",\"start\":0.44,\"end\":0.48,\"type\":\"spacing\",\"speaker_id\":\"speaker_0\",\"logprob\":-1.1920928244535389e-7},{\"text\":\"the\",\"start\":0.48,\"end\":0.56,\"type\":\"word\",\"speaker_id\":\"speaker_0\",\"logprob\":-1.1920928244535389e-7},{\"text\":\" \",\"start\":0.56,\"end\":0.6,\"type\":\"spacing\",\"speaker_id\":\"speaker_0\",\"logprob\":-7.152531907195225e-6},{\"text\":\"release\",\"start\":0.6,\"end\":0.92,\"type\":\"word\",\"speaker_id\":\"speaker_0\",\"logprob\":-7.152531907195225e-6},{\"text\":\" \",\"start\":0.92,\"end\":0.94,\"type\":\"spacing\",\"speaker_id\":\"speaker_0\",\"logprob\":-8.344646857949556e-7},{\"text\":\"ship?\",\"start\":0.94,\"end\":1.26,\"type\":\"word\",\"speaker_id\":\"speaker_0\",\"logprob\":-7.414704032271402e-6},{\"text\":\" \",\"start\":1.26,\"end\":1.26,\"type\":\"spacing\",\"speaker_id\":\"speaker_0\",\"logprob\":-0.0009363081189803779},{\"text\":\"Yes,\",\"start\":1.68,\"end\":2.02,\"type\":\"word\",\"speaker_id\":\"speaker_1\",\"logprob\":-0.003542040009030245},{\"text\":\" \",\"start\":2.02,\"end\":2.48,\"type\":\"spacing\",\"speaker_id\":\"speaker_1\",\"logprob\":-3.933898824470816e-6},{\"text\":\"it\",\"start\":2.48,\"end\":2.62,\"type\":\"word\",\"speaker_id\":\"speaker_1\",\"logprob\":-3.933898824470816e-6},{\"text\":\" \",\"start\":2.62,\"end\":2.64,\"type\":\"spacing\",\"speaker_id\":\"speaker_1\",\"logprob\":-0.000013589766240329482},{\"text\":\"shipped\",\"start\":2.66,\"end\":2.9,\"type\":\"word\",\"speaker_id\":\"speaker_1\",\"logprob\":-0.000013589766240329482},{\"text\":\" \",\"start\":2.9,\"end\":2.94,\"type\":\"spacing\",\"speaker_id\":\"speaker_1\",\"logprob\":0.0},{\"text\":\"this\",\"start\":2.94,\"end\":3.12,\"type\":\"word\",\"speaker_id\":\"speaker_1\",\"logprob\":0.0},{\"text\":\" \",\"start\":3.12,\"end\":3.18,\"type\":\"spacing\",\"speaker_id\":\"speaker_1\",\"logprob\":-3.576278118089249e-7},{\"text\":\"morning\",\"start\":3.18,\"end\":3.5,\"type\":\"word\",\"speaker_id\":\"speaker_1\",\"logprob\":-3.576278118089249e-7}],\"transcription_id\":\"cs3I2282TH8hjw12brNg\",\"audio_duration_secs\":3.5526875}"
+      }
+    }
+  ]
+}
@@ -0,0 +1,50 @@
+{
+  "version": 1,
+  "metadata": {
+    "tags": [
+      "prefix:elevenlabs-transcription",
+      "provider:elevenlabs",
+      "protocol:elevenlabs-transcription"
+    ],
+    "name": "elevenlabs-transcription/transcribes-audio-with-word-timestamps",
+    "recordedAt": "2026-09-27T09:35:27.686Z"
+  },
+  "interactions": [
+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.elevenlabs.io/v1/speech-to-text",
+        "headers": {
+          "content-type": "multipart/form-data; boundary=----WebKitFormBoundarye2be7b31e94441bbbeb35a9c890a9d74"
+        },
+        "body": "--BOUNDARY\r\nContent-Disposition: form-data; name=\"file\"; filename=\"audio.mp3\"\r\nContent-Type: audio/mpeg\r\n\r\n[audio]\r\n--BOUNDARY\r\nContent-Disposition: form-data; name=\"model_id\"\r\n\r\nscribe_v2\r\n--BOUNDARY--\r\n"
+      },
+      "response": {
+        "status": 200,
+        "headers": {
+          "content-type": "application/json"
+        },
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+    {
+      "transport": "http",
+      "request": {
+        "method": "POST",
+        "url": "https://api.elevenlabs.io/v1/speech-to-text",
+        "headers": {
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+      },
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+        "headers": {
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+}
@@ -30,7 +30,7 @@
        {
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+          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"What is the weather in Paris?\"}]}],\"instructions\":\"Call get_weather once, then reply exactly: Paris is sunny.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":50}"
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@@ -525,7 +525,7 @@
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@@ -30,7 +30,7 @@
        {
          "direction": "client",
          "kind": "text",
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+          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Alpha.\"}]}],\"instructions\":\"Follow the user's exact reply instruction.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":30}"
        },
        {
          "direction": "server",
@@ -109,7 +109,7 @@
        {
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          "kind": "text",
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@@ -30,7 +30,7 @@
        {
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          "kind": "text",
-          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Ready.\"}]}],\"instructions\":\"Follow the user's exact reply instruction.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":30}"
+          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Ready.\"}]}],\"instructions\":\"Follow the user's exact reply instruction.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":30}"
        },
        {
          "direction": "server",
@@ -109,7 +109,7 @@
        {
          "direction": "client",
          "kind": "text",
-          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Recovered.\"}]}],\"instructions\":\"Follow the user's exact reply instruction.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":30,\"previous_response_id\":\"resp_01cc0cda24c36acf016aa8ca3c1d3c87d1853283f43675e411\"}"
+          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Recovered.\"}]}],\"instructions\":\"Follow the user's exact reply instruction.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":30,\"previous_response_id\":\"resp_01cc0cda24c36acf016aa8ca3c1d3c87d1853283f43675e411\"}"
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@@ -119,7 +119,7 @@
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+          "body": "{\"type\":\"response.create\",\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Ready.\"}]},{\"type\":\"reasoning\",\"id\":\"rs_01cc0cda24c36acf016aa8ca3ced8c87d1a14c5c6a2ced8544\",\"summary\":[],\"encrypted_content\":\"gAAAAABqqMo9M9B15LsV1CLsXpNJpI08GiwCAK97hTheQ2s1lAkKgARMs1HIIXVeAr-tbUq88yN51fiQE8HvGwdF9ZcNI6bZle8D2PS7m8O7UE7C1Z_HX_fz2f0pRHyRfWpVAT2gYQWIDeZu6UdgxbKPBW0lXWzlk_relHG5x6nXkYzZoEeVasqavWoyMMSX7cexe-IYJh6e_3DgRpOchueS8Z-70P0w5R83Ea7UXZQNhMA0yDEYu_td2PmE2Pd2PUTOB3mxF2pb1z7-2t6S0UryhHx0az7Gh2eT60GGUqz9CIZzNE_FX--tszeuO0eI92Cen5tirOUHBTyyDqE0eG26DRl_p_U-xDZwaQONbtYbvkvrj-G7FA2oZXxjJPHuQZsNgBslXS-H0KT1lx3Y8XJ9QMVjFLFaucFG64wCmXPfCH8dYtX_YqfYQR4lwNfiSbyJEX2oDvTVVD_aCJ9NRo7c0aCTtmKBvr6fvvAy3MAFxAp_Sm2nMx4P5GYO4qAmJDByywKw-VK1vHlv3NRmVsAgbArIFgm-axoCs2PLpvZjDqeQGPavaq8zKWTyZYqBsEzKZUtGOZfYjD4mud0Z08I4i2H4K-L00ccVauode3548ZipOIuslbhJxonQXsF6TFdW2Hj8E5JjoEr5IbmwHyI0PBcDWW5AmkjHLwr9v08mFppRoD-2wzPAd5igROAuUbvJhiQd2A-uOaohwMjdpFxrjyUqgGTlI5g7tmI1ceeQWms0bKm8Pd0wIqVM3Nq6YvV7XfEyeogfRMVUQezr_lES42ZMVAoKBSFzMysDwCFkhVNVclcTUpcUUbVp21FChG7Ag-xuq8Cl6OGLA8nWX1C0aCf2HNa-n3dkYr1DtUziurh1MD-UIs5jdGiq3ptrc0VaVZwNdD4jVfAoHB_Ws7GiISXuclfpqsG3DTJEfzlbukI1vxXrt3FArsHiQvQjW5UM7gGel32M6p8AlXRxnez9PgIuU1WrtBUJetk7m39AZwp_aqbqC-AJ-MF70xP1VJZwFN-GeNL3VZsRHePFG4h7Pj---CCZRGlmzuE1-b-sIE7Bn_gbue_qHFMZJhAY55MO25vfZbSoLWHZCGmLMjJVHOYCPoy6l7zyxNmoIcC58QILNWal31KLCDmCsASmZC-xQRjyFwt-kvLbvk38Dc02IKcP3ujhf6WRRr1A0hh1K-gXmv_XI_MUFDcOVIjjhB-rXgjWSCoKfaKI9GCIsb9mnNaBq65BWg==\"},{\"type\":\"message\",\"id\":\"msg_01cc0cda24c36acf016aa8ca3d4a0087d1950121aed4802434\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"Ready.\"}],\"phase\":\"final_answer\",\"status\":\"completed\"},{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Recovered.\"}]}],\"instructions\":\"Follow the user's exact reply instruction.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":30}"
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        {
          "direction": "server",
@@ -26,7 +26,7 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Think briefly, then reply exactly with: Hello!\"}]}],\"instructions\":\"Show concise reasoning when the provider supports visible reasoning summaries.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"low\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":120,\"stream\":true}"
+        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Think briefly, then reply exactly with: Hello!\"}]}],\"instructions\":\"Show concise reasoning when the provider supports visible reasoning summaries.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"low\",\"summary\":\"auto\"},\"max_output_tokens\":120,\"stream\":true}"
      },
      "response": {
        "status": 200,
@@ -44,7 +44,7 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Think briefly, then reply exactly with: Hello!\"}]},{\"type\":\"reasoning\",\"id\":\"rs_052e7ec551f55289016aa8c8d63eac87d19d6b921611f123e7\",\"summary\":[],\"encrypted_content\":\"gAAAAABqqMjWZ2Eei8_Gf-5FeEFAYp-gSzFL4D4lQBKL_fyyTYXv5iJ-2jql1mOq0wZpqHL8O9MWxebQGW56Ahd-p21qrDD52CyUBqKKlF87eC1d-cTgjXQlFMsPxvwyQeuU6A2l8tanTtJ48sKtzZtHrDuBXZ35u-lONnovjFGMX3Q83xoqG_um_w5rT420TA_SyU4fGt7oiQvOPS1q4PNo97O824oRnI7n_BC1jPYCaJhl2I1rPJg4afuOpjG-u7JcXRD4JPwZdqMa5o2d0uDKHuUYwP25qiPKKDqTTqFka5cDJjZNPF3ZkVHR-cagjZGvMnizXXxgUpPJ9j83gqY4QJLKCkzcaBj9H7mAL-v9yl4I5kn_9_DhpMILs2SZkC8AvIYNgmel3sDV_BG4XZ2JXciZz86ukQ6DwXgQqS4HOB91g-sGHOWMU1ohsZlEvvJBjGkJ_rAdXVMqAbvi2zvE3_NI4sTAGUrIugGJePrQYTe8gqL8f9NsYac6pzHNQL1e_jQNUvp49bu7EsPzCP3KPYVvZCFohDdwe7sMd6wrztrCJwM4CLdAQK61A7sYzU0HyglLtPidmS5QkSmV6U_xgih7JbKnY0oAeCyYw4ADYqdNTi0axmBErh-lbh-XKNG_TnoMa-2IS3X041N8OsDfSdQp3QsAm53fF8seQuLFa27Iaq2etMj3yGeqWVjA-Mae3K34mt2YPGjQ-HbIOMVmYXBLzNr-s2fT35Sp6SDEsFyvzXb0Vij58s1wW5zkuKgaJiroGgkY86NImuaa3_-wpMK3_9O_wwAbRwV4uBCVzT_rY6rDQHR9-VkM0MbGK8drbdtjXwy3KtAzkux4N4g2nadYU0IIIEUNj_JChUFSHC7VRg7L7LpZMgAFGwHmaUyzQt31LyiVix9WFtcKfBgzehoRV6vstln-oBRd-vFjUW-7WLm7R_lFNHQZ0CKUvKCSpQxdIevczpYT0_lQiDU7Rfp1UBBnicndpq4YQwgRppdZX-QHG5IZxxHNWYdIBtn3eO3ooDXmI-rYryyVcFG6VY5xqssf8GgXqgNy84X_SgYfhGmNiPPQTl5wIBa49f1sxAI-7ri1xLr6FJhQMasOoxm_VuZYNkq6NrAXprtKa70cBRpm1wWBNcPdMul4GNMDQatQZRDENcNLe45iMX-HB1YYSvyc-y5rfSJkP4EgKXC-OqcrzxAlRfB3Bm4jOQL_PSsNBbh26CWAdAYSftM88fbnuqZX2w==\"},{\"type\":\"message\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"Hello!\"}],\"status\":\"completed\"},{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Now reply exactly with: Done.\"}]}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"low\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":40,\"stream\":true}"
+        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Think briefly, then reply exactly with: Hello!\"}]},{\"type\":\"reasoning\",\"id\":\"rs_052e7ec551f55289016aa8c8d63eac87d19d6b921611f123e7\",\"summary\":[],\"encrypted_content\":\"gAAAAABqqMjWZ2Eei8_Gf-5FeEFAYp-gSzFL4D4lQBKL_fyyTYXv5iJ-2jql1mOq0wZpqHL8O9MWxebQGW56Ahd-p21qrDD52CyUBqKKlF87eC1d-cTgjXQlFMsPxvwyQeuU6A2l8tanTtJ48sKtzZtHrDuBXZ35u-lONnovjFGMX3Q83xoqG_um_w5rT420TA_SyU4fGt7oiQvOPS1q4PNo97O824oRnI7n_BC1jPYCaJhl2I1rPJg4afuOpjG-u7JcXRD4JPwZdqMa5o2d0uDKHuUYwP25qiPKKDqTTqFka5cDJjZNPF3ZkVHR-cagjZGvMnizXXxgUpPJ9j83gqY4QJLKCkzcaBj9H7mAL-v9yl4I5kn_9_DhpMILs2SZkC8AvIYNgmel3sDV_BG4XZ2JXciZz86ukQ6DwXgQqS4HOB91g-sGHOWMU1ohsZlEvvJBjGkJ_rAdXVMqAbvi2zvE3_NI4sTAGUrIugGJePrQYTe8gqL8f9NsYac6pzHNQL1e_jQNUvp49bu7EsPzCP3KPYVvZCFohDdwe7sMd6wrztrCJwM4CLdAQK61A7sYzU0HyglLtPidmS5QkSmV6U_xgih7JbKnY0oAeCyYw4ADYqdNTi0axmBErh-lbh-XKNG_TnoMa-2IS3X041N8OsDfSdQp3QsAm53fF8seQuLFa27Iaq2etMj3yGeqWVjA-Mae3K34mt2YPGjQ-HbIOMVmYXBLzNr-s2fT35Sp6SDEsFyvzXb0Vij58s1wW5zkuKgaJiroGgkY86NImuaa3_-wpMK3_9O_wwAbRwV4uBCVzT_rY6rDQHR9-VkM0MbGK8drbdtjXwy3KtAzkux4N4g2nadYU0IIIEUNj_JChUFSHC7VRg7L7LpZMgAFGwHmaUyzQt31LyiVix9WFtcKfBgzehoRV6vstln-oBRd-vFjUW-7WLm7R_lFNHQZ0CKUvKCSpQxdIevczpYT0_lQiDU7Rfp1UBBnicndpq4YQwgRppdZX-QHG5IZxxHNWYdIBtn3eO3ooDXmI-rYryyVcFG6VY5xqssf8GgXqgNy84X_SgYfhGmNiPPQTl5wIBa49f1sxAI-7ri1xLr6FJhQMasOoxm_VuZYNkq6NrAXprtKa70cBRpm1wWBNcPdMul4GNMDQatQZRDENcNLe45iMX-HB1YYSvyc-y5rfSJkP4EgKXC-OqcrzxAlRfB3Bm4jOQL_PSsNBbh26CWAdAYSftM88fbnuqZX2w==\"},{\"type\":\"message\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"Hello!\"}],\"status\":\"completed\"},{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Now reply exactly with: Done.\"}]}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"low\",\"summary\":\"auto\"},\"max_output_tokens\":40,\"stream\":true}"
      },
      "response": {
        "status": 200,
@@ -24,7 +24,7 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Think briefly, then reply exactly with: Hello!\"}]}],\"instructions\":\"Show concise reasoning when the provider supports visible reasoning summaries.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"low\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":120,\"stream\":true}"
+        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Think briefly, then reply exactly with: Hello!\"}]}],\"instructions\":\"Show concise reasoning when the provider supports visible reasoning summaries.\",\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"low\",\"summary\":\"auto\"},\"max_output_tokens\":120,\"stream\":true}"
      },
      "response": {
        "status": 200,
@@ -25,7 +25,7 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"What is the weather in Paris?\"}]}],\"instructions\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":80,\"stream\":true}"
+        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"What is the weather in Paris?\"}]}],\"instructions\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":80,\"stream\":true}"
      },
      "response": {
        "status": 200,
@@ -43,7 +43,7 @@
        "headers": {
          "content-type": "application/json"
        },
-        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"What is the weather in Paris?\"}]},{\"type\":\"function_call\",\"id\":\"fc_09525c04931d1487016aa8c8d8e12887d193bd327a0f313bd7\",\"call_id\":\"call_p57PJbKe0bX44nj908fpHdRn\",\"name\":\"get_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"},{\"type\":\"function_call_output\",\"call_id\":\"call_p57PJbKe0bX44nj908fpHdRn\",\"output\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}],\"instructions\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":80,\"stream\":true}"
+        "body": "{\"model\":\"gpt-5.5\",\"input\":[{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"What is the weather in Paris?\"}]},{\"type\":\"function_call\",\"id\":\"fc_09525c04931d1487016aa8c8d8e12887d193bd327a0f313bd7\",\"call_id\":\"call_p57PJbKe0bX44nj908fpHdRn\",\"name\":\"get_weather\",\"arguments\":\"{\\\"city\\\":\\\"Paris\\\"}\"},{\"type\":\"function_call_output\",\"call_id\":\"call_p57PJbKe0bX44nj908fpHdRn\",\"output\":\"{\\\"temperature\\\":22,\\\"condition\\\":\\\"sunny\\\"}\"}],\"instructions\":\"Use the get_weather tool exactly once. After the tool result, reply exactly: Paris is sunny.\",\"tools\":[{\"type\":\"function\",\"name\":\"get_weather\",\"description\":\"Get current weather for a city.\",\"parameters\":{\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}},\"required\":[\"city\"],\"additionalProperties\":false},\"strict\":false}],\"store\":false,\"include\":[\"reasoning.encrypted_content\"],\"reasoning\":{\"effort\":\"medium\",\"summary\":\"auto\"},\"max_output_tokens\":80,\"stream\":true}"
      },
      "response": {
        "status": 200,
@@ -97,6 +97,26 @@ describe("Generation", () => {
    }),
  )

+  it.effect("fails an event stream at the deadline when the poll interval is longer than the timeout", () =>
+    Effect.gen(function* () {
+      const scripted = yield* scriptedRoute(["running"], "never")
+      const generation = new Generation(scripted.route, "t", { id: "gen_1", status: "queued" })
+
+      const fiber = yield* Effect.forkChild(
+        generation
+          .events({ poll: { interval: "30 seconds", timeout: "10 seconds" } })
+          .pipe(Stream.runCollect, Effect.flip),
+      )
+      yield* TestClock.adjust("9 seconds")
+      expect(fiber.pollUnsafe()).toBeUndefined()
+      yield* TestClock.adjust("1 second")
+      const error = yield* Fiber.join(fiber)
+
+      expect(error.reason._tag).toBe("Timeout")
+      expect(yield* Ref.get(scripted.polls)).toBe(1)
+    }),
+  )
+
  it.effect("surfaces the route failure body for failed generations", () =>
    Effect.gen(function* () {
      const scripted = yield* scriptedRoute(["running", "failed"], "unused")
@@ -78,8 +78,11 @@ describe("Image", () => {
        mediaType: "image/webp",
      })
      expect(yield* response.image.bytes()).toEqual(Uint8Array.from([1, 2, 3]))
-      expect(response.image.providerMetadata).toEqual({ openai: { revisedPrompt: "A precise robot" } })
+      expect(response.image.info).toEqual({ format: "webp", width: 2048, height: 2048 })
      expect(response.usage).toMatchObject({ type: "tokens", total: 12 })
+      expect(response.providerMetadata).toEqual({
+        openai: { outputFormat: "webp", size: "2048x2048", quality: "high", background: "opaque" },
+      })
    }).pipe(
      Effect.provide(
        ImageClient.layer.pipe(
@@ -107,8 +110,11 @@ describe("Image", () => {
                })
                return input.respond(
                  JSON.stringify({
-                    data: [{ b64_json: "AQID", revised_prompt: "A precise robot" }, { b64_json: "BAUG" }],
+                    data: [{ b64_json: "AQID" }, { b64_json: "BAUG" }],
                    output_format: "webp",
+                    size: "2048x2048",
+                    quality: "high",
+                    background: "opaque",
                    usage: { input_tokens: 4, output_tokens: 8, total_tokens: 12 },
                  }),
                  { headers: { "content-type": "application/json" } },
@@ -144,6 +150,7 @@ describe("Image", () => {
        ),
      )
      expect(response.image.source).toEqual({ type: "bytes", data: Uint8Array.from([1, 2, 3]), mediaType: "image/png" })
+      expect(response.image.info).toEqual({ format: "png" })
    }),
  )

@@ -725,6 +732,7 @@ describe("Image", () => {
      const errors = yield* Effect.all(
        [
          Image.start({ model: Google.configure({ apiKey: "test" }).image("gemini-3.1-flash-image"), prompt }),
+          Image.generate({ model: Google.configure({ apiKey: "test" }).image("gemini-3.1-flash-image"), prompt, n: 2 }),
          Image.start({
            model: BlackForestLabs.configure({ apiKey: "test" }).image("flux-2-pro"),
            prompt,
@@ -735,7 +743,6 @@ describe("Image", () => {
            prompt,
            size: "512x512",
          }),
-          Stream.runCollect(Image.stream({ model: openai.image("dall-e-3"), prompt })),
          Stream.runCollect(Image.stream({ model: openai.image("gpt-image-2"), prompt, n: 2 })),
          Image.start({ model: replicate, prompt, seed: 7 }),
          Image.start({
@@ -749,9 +756,9 @@ describe("Image", () => {
      expect(errors.map((error) => [error.reason._tag, "operation" in error.reason && error.reason.operation])).toEqual(
        [
          ["UnsupportedOperation", "image.start"],
+          ["UnsupportedOperation", "media.n"],
          ["UnsupportedOperation", "media.aspectRatio"],
          ["UnsupportedOperation", "media.size"],
-          ["UnsupportedOperation", "media.stream"],
          ["UnsupportedOperation", "media.n"],
          ["UnsupportedOperation", "media.seed"],
          ["InvalidRequest", false],
@@ -761,6 +768,104 @@ describe("Image", () => {
    }).pipe(Effect.provide(layer(() => Effect.die("an unsupported request reached the network")))),
  )

+  const falToken = {
+    requestID: "r1",
+    statusURL: "https://queue.fal.test/fal-ai/flux/requests/r1/status",
+    responseURL: "https://queue.fal.test/fal-ai/flux/requests/r1",
+    cancelURL: "https://queue.fal.test/fal-ai/flux/requests/r1/cancel",
+  }
+  const falSubmitted = {
+    request_id: falToken.requestID,
+    status_url: falToken.statusURL,
+    response_url: falToken.responseURL,
+    cancel_url: falToken.cancelURL,
+  }
+  const bodies: Array<unknown> = []
+  it.effect("sizes fal Kontext by aspect ratio and sends several images to /multi", () =>
+    Effect.gen(function* () {
+      const fal = Fal.configure({ apiKey: "test", baseURL: "https://queue.fal.test" })
+      const images = [Media.url("https://example.test/a.png"), Media.url("https://example.test/b.png")]
+      const rejected = yield* Image.start({
+        model: fal.image("fal-ai/flux-pro/kontext"),
+        prompt: "A lighthouse",
+        size: "512x512",
+      }).pipe(Effect.flip)
+      yield* Image.start({
+        model: fal.image("fal-ai/flux-pro/kontext"),
+        prompt: "A lighthouse",
+        images: images.slice(0, 1),
+        aspectRatio: "16:9",
+      })
+      yield* Image.start({ model: fal.image("fal-ai/flux-pro/kontext/max/multi"), prompt: "A lighthouse", images })
+
+      expect(rejected.reason).toMatchObject({ _tag: "UnsupportedOperation", operation: "media.size" })
+      expect(bodies).toEqual([
+        { prompt: "A lighthouse", aspect_ratio: "16:9", image_url: "https://example.test/a.png" },
+        { prompt: "A lighthouse", image_urls: ["https://example.test/a.png", "https://example.test/b.png"] },
+      ])
+    }).pipe(
+      Effect.provide(
+        layer((input) => {
+          bodies.push(JSON.parse(input.text))
+          return Effect.succeed(json(input, falSubmitted))
+        }),
+      ),
+    ),
+  )
+
+  it.effect("decodes fal sync_mode data URIs as inline images", () =>
+    Effect.gen(function* () {
+      const generation = yield* Image.resume(Fal.configure({ apiKey: "test" }).image("fal-ai/flux/schnell"), falToken)
+      const response = yield* generation.await()
+
+      expect(response.images.map((image) => image.source)).toEqual([
+        { type: "base64", data: "AQID", mediaType: "image/png" },
+        { type: "url", url: "https://v3.fal.media/out.jpg", mediaType: "image/jpeg" },
+      ])
+      expect(response.image.info).toEqual({ width: 512, height: 512 })
+      expect(yield* response.image.bytes()).toEqual(Uint8Array.from([1, 2, 3]))
+    }).pipe(
+      Effect.provide(
+        layer((input) =>
+          Effect.succeed(
+            input.request.url === falToken.statusURL
+              ? json(input, { status: "COMPLETED" })
+              : json(input, {
+                  images: [
+                    { url: "data:image/png;base64,AQID", width: 512, height: 512, content_type: "image/png" },
+                    { url: "https://v3.fal.media/out.jpg", width: 512, height: 512, content_type: "image/jpeg" },
+                  ],
+                }),
+          ),
+        ),
+      ),
+    ),
+  )
+
+  const falDetail = { detail: [{ loc: ["body", "prompt"], msg: "Invalid input", type: "value_error" }] }
+  it.effect(
+    "fails a fal await whose COMPLETED status carries an error with the response_url body and HTTP context",
+    () =>
+      Effect.gen(function* () {
+        const generation = yield* Image.resume(Fal.configure({ apiKey: "test" }).image("fal-ai/flux/schnell"), falToken)
+        expect(generation.status).toBe("failed")
+        const error = yield* generation.await().pipe(Effect.flip)
+        expect(error.reason._tag).toBe("InvalidRequest")
+        expect(error.reason.body).toBe(JSON.stringify(falDetail))
+        expect(error.reason.http).toMatchObject({ url: falToken.responseURL, status: 422 })
+      }).pipe(
+        Effect.provide(
+          layer((input) =>
+            Effect.succeed(
+              input.request.url === falToken.statusURL
+                ? json(input, { status: "COMPLETED", error: "Invalid input", error_type: "ValidationError" })
+                : json(input, falDetail, { status: 422 }),
+            ),
+          ),
+        ),
+      ),
+  )
+
  const moderated = { id: "req_1", status: "Content Moderated" }
  const prediction = {
    id: "p_1",
@@ -768,6 +873,56 @@ describe("Image", () => {
    output: { text: "not an image" },
    urls: { get: "https://replicate.test/p_1", cancel: "https://replicate.test/p_1/cancel" },
  }
+  for (const pending of [
+    {
+      model: BlackForestLabs.configure({ apiKey: "test" }).image("flux-2-pro"),
+      token: { id: "req_1", pollingURL: "https://bfl.test/v1/get_result?id=req_1" },
+      status: 200,
+      body: { id: "req_1", status: "Pending" },
+      message: "Black Forest Labs generation req_1",
+    },
+    {
+      model: Replicate.configure({ apiKey: "test" }).image("owner/model"),
+      token: { id: "p_1", getURL: "https://replicate.test/p_1", cancelURL: "https://replicate.test/p_1/cancel" },
+      status: 200,
+      body: {
+        id: "p_1",
+        status: "processing",
+        urls: { get: "https://replicate.test/p_1", cancel: "https://replicate.test/p_1/cancel" },
+      },
+      message: "Replicate generation p_1",
+    },
+    {
+      model: Stability.configure({ apiKey: "test", baseURL: "https://stability.test" }).upscale(),
+      token: { id: "up_1" },
+      status: 202,
+      body: { id: "up_1", status: "in-progress" },
+      message: "Stability AI generation up_1",
+    },
+  ]) {
+    it.effect(`rejects reading a ${pending.model.provider} result before the generation finishes`, () =>
+      Effect.gen(function* () {
+        const generation = yield* Image.resume(pending.model, pending.token)
+        const error = yield* generation.result().pipe(Effect.flip)
+        expect(error.reason._tag).toBe("InvalidRequest")
+        expect(error.message).toBe(`${pending.message} has not finished; await it before reading the result`)
+        expect(error.reason.body).toBe(JSON.stringify(pending.body))
+        expect(error.reason.http?.status).toBe(pending.status)
+      }).pipe(
+        Effect.provide(
+          layer((input) =>
+            Effect.succeed(
+              input.respond(JSON.stringify(pending.body), {
+                status: pending.status,
+                headers: { "content-type": "application/json" },
+              }),
+            ),
+          ),
+        ),
+      ),
+    )
+  }
+
  it.effect("classifies terminal outcomes the recordings never saw", () =>
    Effect.gen(function* () {
      const bfl = yield* Image.resume(BlackForestLabs.configure({ apiKey: "test" }).image("flux-2-pro"), {
@@ -7,7 +7,6 @@ import {
  type ImageModelOptions,
  type ImageOptions,
  type ImageRequestFor,
-  type ImageRoute,
 } from "../src/index.js"
 import type { Service } from "../src/image-client.js"
 import { Anthropic, BlackForestLabs, Google, OpenAI, Stability, XAI, ZAI } from "../src/providers.js"
@@ -21,8 +20,7 @@ type GoogleLikeOptions = {
  readonly thinkingLevel?: "LOW" | "HIGH"
 } & Record<string, unknown>

-declare const route: ImageRoute<GoogleLikeOptions>
-const google = ImageModel.make<GoogleLikeOptions>({ id: "gemini-image", provider: "google", route })
+declare const google: ImageModel<GoogleLikeOptions>
 // @ts-expect-error Extracted model options retain known provider fields.
 const invalidGoogleOptions: ImageModelOptions<typeof google> = { imageSize: "8K" }
 void invalidGoogleOptions
@@ -152,6 +150,8 @@ Image.generate({ model: zai, prompt: "A lighthouse", providerOptions: { quality:
 Image.generate({ model: zai, prompt: "A lighthouse", providerOptions: { userID: 1 } })

 declare const generic: ImageModel<ImageOptions>
+const widenImage = <Options extends ImageOptions>(model: ImageModel<Options>): ImageModel => model
+void widenImage
 Image.generate({ model: generic, prompt: "A lighthouse", providerOptions: { arbitrary: true } })
 const explicitAsset: Media.Asset = Media.url("https://example.com/image.png")
 void explicitAsset
@@ -6,6 +6,7 @@ import {
  type LanguageModelProviderOptions,
  type ProviderOptions,
 } from "../src/index.js"
+import { ai } from "../src/promise.js"
 import { OpenAIChat } from "../src/protocols.js"

 interface ExampleOptions {
@@ -31,6 +32,10 @@ const generated = LLM.generate(LLM.request({ model, prompt: "Hello" }))
 type GenerateRequirements = Assert<Equal<Requirements<typeof generated>, LLMClientService>>
 const streamed = LLM.stream(LLM.request({ model, prompt: "Hello" }))
 type StreamClientRequirements = Assert<Equal<StreamRequirements<typeof streamed>, LLMClientService>>
+const generatedFromInput = LLM.generate({ model, prompt: "Hello", providerOptions: { mode: "fast" } })
+type InputGenerateRequirements = Assert<Equal<Requirements<typeof generatedFromInput>, LLMClientService>>
+const streamedFromInput = LLM.stream({ model, prompt: "Hello", providerOptions: { mode: "thorough" } })
+type InputStreamRequirements = Assert<Equal<StreamRequirements<typeof streamedFromInput>, LLMClientService>>

 LLM.request({
  model,
@@ -39,6 +44,11 @@ LLM.request({
  providerOptions: { mode: "slow" },
 })

+// @ts-expect-error Direct input keeps the selected model's provider option types.
+LLM.generate({ model, prompt: "Hello", providerOptions: { mode: "slow" } })
+// @ts-expect-error Stream input keeps the selected model's provider option types.
+LLM.stream({ model, prompt: "Hello", providerOptions: { mode: "slow" } })
+
 const generatedObject = LLM.generateObject({
  model,
  prompt: "Hello",
@@ -69,5 +79,16 @@ const options: LanguageModelProviderOptions<typeof model> = { mode: "fast" }
 void (options satisfies LanguageModelProviderOptions<typeof model>)
 void (true satisfies GenerateRequirements)
 void (true satisfies StreamClientRequirements)
+void (true satisfies InputGenerateRequirements)
+void (true satisfies InputStreamRequirements)
 void (true satisfies GenerateObjectRequirements)
 void (true satisfies GenerateDynamicObjectRequirements)
+
+void ai.llm.generate({ model, prompt: "Hello", providerOptions: { mode: "fast" } })
+void ai.llm.stream({ model, prompt: "Hello", providerOptions: { mode: "thorough" } })
+void ai.llm.generate(ai.llm.request({ model, prompt: "Hello" }))
+void ai.llm.stream(ai.llm.request({ model, prompt: "Hello" }))
+// @ts-expect-error Promise direct input keeps the selected model's provider option types.
+void ai.llm.generate({ model, prompt: "Hello", providerOptions: { mode: "slow" } })
+// @ts-expect-error Promise stream input keeps the selected model's provider option types.
+void ai.llm.stream({ model, prompt: "Hello", providerOptions: { mode: "slow" } })
@@ -1,6 +1,7 @@
 import { describe, expect, test } from "bun:test"
-import { Schema } from "effect"
-import { CacheHint, LLM, LLMResponse, ToolEntry, ToolNamespace } from "../src/index.js"
+import { Effect, Schema, Stream } from "effect"
+import { CacheHint, LLM, LLMEvent, LLMResponse, ToolEntry, ToolNamespace } from "../src/index.js"
+import { OpenAI } from "../src/providers.js"
 import * as OpenAIChat from "../src/protocols/openai-chat.js"
 import * as OpenAIResponses from "../src/protocols/openai-responses.js"
 import {
@@ -13,6 +14,8 @@ import {
  ToolDefinition,
  ToolResultPart,
 } from "../src/schema/index.js"
+import { fixedResponse } from "./lib/http.js"
+import { sseEvents } from "./lib/sse.js"

 const chatRoute = OpenAIChat.route
 const responsesRoute = OpenAIResponses.route
@@ -240,6 +243,26 @@ describe("llm constructors", () => {
    expect(request.messages.map((message) => message.role)).toEqual(["user", "system"])
  })

+  test("generates and streams from input or a prebuilt request", async () => {
+    const model = OpenAI.configure({ apiKey: "test", baseURL: "https://openai.test/v1" }).chat("gpt-4o-mini")
+    const layer = fixedResponse(
+      sseEvents({ choices: [{ delta: { content: "Hello" } }] }, { choices: [{ delta: {}, finish_reason: "stop" }] }),
+    )
+    const input = { model, prompt: "Say hello." }
+    const request = LLM.request(input)
+    const generated = await Effect.runPromise(LLM.generate(input).pipe(Effect.provide(layer)))
+    const generatedFromRequest = await Effect.runPromise(LLM.generate(request).pipe(Effect.provide(layer)))
+    expect(generated.text).toBe("Hello")
+    expect(generatedFromRequest.text).toBe(generated.text)
+
+    const streamed = await Effect.runPromise(LLM.stream(input).pipe(Stream.runCollect, Effect.provide(layer)))
+    const streamedFromRequest = await Effect.runPromise(
+      LLM.stream(request).pipe(Stream.runCollect, Effect.provide(layer)),
+    )
+    expect(Array.from(streamed).some(LLMEvent.is.textDelta)).toBe(true)
+    expect(streamedFromRequest).toEqual(streamed)
+  })
+
  test("extracts output text from response events", () => {
    expect(
      LLMResponse.text({
@@ -3,7 +3,7 @@ import { NodeFileSystem } from "@effect/platform-node"
 import { Effect, Ref, Schema } from "effect"
 import { FileSystem } from "effect"
 import { HttpClientRequest } from "effect/unstable/http"
-import { Media, Message } from "../src/index.js"
+import { AIError, Media, Message } from "../src/index.js"
 import { it } from "./lib/effect.js"
 import { dynamicResponse, scriptedResponses } from "./lib/http.js"

@@ -161,6 +161,56 @@ describe("Media", () => {
    }),
  )

+  it.effect("keeps transient url download headers out of toJSON and AssetSchema encoding", () =>
+    Effect.sync(() => {
+      const asset = Media.url("https://cdn.example.test/video.mp4", {
+        mediaType: "video/mp4",
+        expiresAt: 42,
+        headers: { "x-goog-api-key": "secret" },
+      })
+      expect(asset.headers).toEqual({ "x-goog-api-key": "secret" })
+      const source = { type: "url", url: "https://cdn.example.test/video.mp4", mediaType: "video/mp4", expiresAt: 42 }
+
+      expect(asset.toJSON()).not.toHaveProperty("headers")
+      expect(JSON.stringify(asset)).not.toContain("secret")
+      expect(asset.toJSON().source).toEqual(source)
+
+      const encoded = Schema.encodeSync(Media.AssetSchema)(asset)
+      expect(encoded).not.toHaveProperty("headers")
+      expect(encoded.source).toEqual(source)
+
+      const codec = Schema.fromJsonString(Media.AssetSchema)
+      const json = Schema.encodeSync(codec)(asset)
+      expect(json).not.toContain("secret")
+      const restored = Schema.decodeSync(codec)(json)
+      expect(restored).toBeInstanceOf(Media.Asset)
+      expect(restored.source).toEqual(source)
+      expect(restored.expiresAt).toBe(42)
+      expect(restored.headers).toBeUndefined()
+    }),
+  )
+
+  it.effect("fails url downloads with non-2xx status as a typed AIError keeping http and body", () =>
+    Effect.gen(function* () {
+      const body = JSON.stringify({ error: { message: "file expired" } })
+      const error = yield* Media.url("https://cdn.example.test/expired.png")
+        .bytes()
+        .pipe(
+          Effect.flip,
+          Effect.provide(
+            dynamicResponse((input) =>
+              Effect.succeed(input.respond(body, { status: 404, headers: { "content-type": "application/json" } })),
+            ),
+          ),
+        )
+      expect(error).toBeInstanceOf(AIError)
+      expect(error.message).toContain("file expired")
+      expect(error.reason.http?.status).toBe(404)
+      expect(error.reason.http?.url).toBe("https://cdn.example.test/expired.png")
+      expect(error.reason.body).toBe(body)
+    }),
+  )
+
  it.effect("reads files with sniffed media types and writes materialized assets", () =>
    Effect.gen(function* () {
      const fs = yield* FileSystem.FileSystem
@@ -22,7 +22,8 @@ const chatBody = sseEvents(
 /**
 * Executor layer that answers chat completions with SSE text, image generations with one base64 PNG, Runway video
 * tasks with a queued submission that succeeds on the second poll, speech with raw audio or SSE audio deltas, OpenAI
- * transcription with JSON or SSE text deltas, and AssemblyAI transcripts that complete on the first poll.
+ * transcription with JSON or SSE text deltas, AssemblyAI transcripts that complete on the first poll, and `slow.test`
+ * chat completions that send one text delta and never finish.
 */
 const executor = (seen: Array<string>) =>
  RequestExecutor.layer.pipe(
@@ -55,6 +56,18 @@ const executor = (seen: Array<string>) =>
              output: "https://replicate.test/a.webp",
              urls: { get: "https://replicate.test/p_1", cancel: "https://replicate.test/p_1/cancel" },
            })
+          if (web.url.startsWith("https://slow.test"))
+            return input.respond(
+              new ReadableStream({
+                start: (controller) =>
+                  controller.enqueue(
+                    new TextEncoder().encode(
+                      `data: ${JSON.stringify({ choices: [{ delta: { content: "Hello" } }] })}\n\n`,
+                    ),
+                  ),
+              }),
+              { headers: { "content-type": "text/event-stream" } },
+            )
          if (web.url.endsWith("/chat/completions"))
            return input.respond(chatBody, { headers: { "content-type": "text/event-stream" } })
          if (web.url.endsWith("/audio/speech"))
@@ -116,19 +129,32 @@ describe("AI promise client", () => {
    const seen: Array<string> = []
    const ai = AI.make({ layer: executor(seen) })

-    const text = await ai.llm.generate({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })
+    const request = ai.llm.request({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })
+    const text = await ai.llm.generate(request)
    expect(text.text).toBe("Hello world")
+    expect((await ai.llm.generate({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })).text).toBe(
+      "Hello world",
+    )

    const image = await ai.image.generate({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" })
    expect(image.image).toBeInstanceOf(Media.Asset)
    expect(image.image.mediaType).toBe("image/png")
    expect(await ai.run(image.image.bytes())).toEqual(Uint8Array.from([1, 2, 3]))
+    const requested = await ai.image.generate(
+      ai.image.request({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" }),
+    )
+    expect(requested.image.mediaType).toBe("image/png")

    const deltas: Array<string> = []
-    for await (const event of ai.llm.stream({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })) {
+    for await (const event of ai.llm.stream(request)) {
      if (LLMEvent.is.textDelta(event)) deltas.push(event.text)
    }
    expect(deltas).toEqual(["Hello", " world"])
+    const directDeltas: Array<string> = []
+    for await (const event of ai.llm.stream({ model: openai.chat("gpt-4o-mini"), prompt: "Say hello." })) {
+      if (LLMEvent.is.textDelta(event)) directDeltas.push(event.text)
+    }
+    expect(directDeltas).toEqual(deltas)

    const imageEvents: Array<string> = []
    for await (const event of ai.image.stream({ model: openai.image("gpt-image-2"), prompt: "A lighthouse" })) {
@@ -137,8 +163,11 @@ describe("AI promise client", () => {
    expect(imageEvents).toEqual(["image-partial", "image", "finish"])

    expect(seen).toEqual([
+      "https://openai.test/v1/chat/completions",
      "https://openai.test/v1/chat/completions",
      "https://openai.test/v1/images/generations",
+      "https://openai.test/v1/images/generations",
+      "https://openai.test/v1/chat/completions",
      "https://openai.test/v1/chat/completions",
      "https://openai.test/v1/images/generations",
    ])
@@ -260,22 +289,27 @@ describe("AI promise client", () => {
    const ai = AI.make({ layer: executor([]) })

    const failure = await ai.llm
-      .generate({ model: openai.responses("gpt-5"), prompt: "Hello" })
+      .generate(ai.llm.request({ model: openai.responses("gpt-5"), prompt: "Hello" }))
      .then(() => undefined)
      .catch((error: unknown) => error)
    expect(failure).toBeInstanceOf(AIError)
    expect(failure instanceof AIError && failure.reason.http?.status).toBe(404)

-    const invalid = await ai.llm
-      // @ts-expect-error Invalid input must reject with AIError, not throw synchronously.
+    const invalidLLM = await ai.llm
+      // @ts-expect-error Invalid input must reject with AIError instead of throwing synchronously.
      .generate({ model: openai.responses("gpt-5"), messages: [{ role: "bogus" }] })
      .catch((error: unknown) => error)
+    expect(invalidLLM instanceof AIError && invalidLLM.reason._tag).toBe("InvalidRequest")
+
+    const invalid = await ai.image
+      .generate({ model: openai.image("gpt-image-2"), prompt: "A lighthouse", n: 1.5 })
+      .catch((error: unknown) => error)
    expect(invalid instanceof AIError && invalid.reason._tag).toBe("InvalidRequest")

    const controller = new AbortController()
    controller.abort()
    const aborted = await ai.llm
-      .generate({ model: openai.chat("gpt-4o-mini"), prompt: "Hello" }, { signal: controller.signal })
+      .generate(ai.llm.request({ model: openai.chat("gpt-4o-mini"), prompt: "Hello" }), { signal: controller.signal })
      .then(() => "completed")
      .catch(() => "aborted")
    expect(aborted).toBe("aborted")
@@ -283,6 +317,77 @@ describe("AI promise client", () => {
    await ai.dispose()
  })

+  test("aborted calls reject and aborted streams throw with the signal's reason", async () => {
+    const ai = AI.make({ layer: executor([]) })
+    const slow = OpenAI.configure({ apiKey: "test", baseURL: "https://slow.test/v1" }).chat("gpt-4o-mini")
+    const aborted = new AbortController()
+    aborted.abort()
+    const reason = new Error("mine")
+
+    const rejected = await ai.run(Effect.never, { signal: aborted.signal }).catch((error: unknown) => error)
+    expect(rejected).toBe(aborted.signal.reason)
+    expect(rejected).toMatchObject({ name: "AbortError" })
+
+    const inFlight = new AbortController()
+    setTimeout(() => inFlight.abort(reason), 10)
+    expect(
+      await ai.llm
+        .generate({ model: slow, prompt: "Hello" }, { signal: inFlight.signal })
+        .catch((error: unknown) => error),
+    ).toBe(reason)
+
+    const preAborted = await Array.fromAsync(
+      ai.speech.stream({ model: openai.speech("gpt-4o-mini-tts"), text: "Hello" }, { signal: aborted.signal }),
+    ).catch((error: unknown) => error)
+    expect(preAborted).toBe(aborted.signal.reason)
+    expect(preAborted).toMatchObject({ name: "AbortError" })
+
+    const midStream = new AbortController()
+    const deltas: Array<string> = []
+    const midStreamFailure = await Array.fromAsync(
+      ai.llm.stream({ model: slow, prompt: "Hello" }, { signal: midStream.signal }),
+      (event) => {
+        if (!LLMEvent.is.textDelta(event)) return
+        deltas.push(event.text)
+        midStream.abort()
+      },
+    ).catch((error: unknown) => error)
+    expect(deltas).toEqual(["Hello"])
+    expect(midStreamFailure).toBe(midStream.signal.reason)
+    expect(midStreamFailure).toMatchObject({ name: "AbortError" })
+
+    const model = Runway.configure({ apiKey: "test", baseURL: "https://runway.test/v1" }).video("gen4.5")
+    const generation = await ai.video.start({ model, prompt: "A kite" })
+    const polling = new AbortController()
+    const events: Array<string> = []
+    const eventsFailure = await Array.fromAsync(
+      generation.events({ poll: { interval: 60_000 }, signal: polling.signal }),
+      (event) => {
+        events.push(event.type)
+        polling.abort(reason)
+      },
+    ).catch((error: unknown) => error)
+    expect(events).toEqual(["generation-progress"])
+    expect(eventsFailure).toBe(reason)
+
+    await ai.dispose()
+  })
+
+  test("breaking out of an abortable stream cleans up without throwing", async () => {
+    const ai = AI.make({ layer: executor([]) })
+    const slow = OpenAI.configure({ apiKey: "test", baseURL: "https://slow.test/v1" }).chat("gpt-4o-mini")
+    const controller = new AbortController()
+    const deltas: Array<string> = []
+    for await (const event of ai.llm.stream({ model: slow, prompt: "Hello" }, { signal: controller.signal })) {
+      if (!LLMEvent.is.textDelta(event)) continue
+      deltas.push(event.text)
+      break
+    }
+    controller.abort()
+    expect(deltas).toEqual(["Hello"])
+    await ai.dispose()
+  })
+
  test("the default client is created lazily and can be disposed", async () => {
    expect(typeof AI.ai.llm.generate).toBe("function")
    expect(typeof AI.ai.image.generate).toBe("function")
@@ -216,6 +216,33 @@ it.effect("Alibaba keeps native reasoning controls and future efforts on their s
  }),
 )

+it.effect("Alibaba fits explicit thinking budgets to half the output limit", () =>
+  Effect.gen(function* () {
+    const provider = Alibaba.configure({ region: "ap-southeast-1", apiKey: "fixture" })
+    const chat = (maxTokens?: number) =>
+      compileRequest(
+        LLM.request({
+          model: provider.chat("qwen3.7-plus"),
+          prompt: "hi",
+          ...(maxTokens === undefined ? {} : { generation: { maxTokens } }),
+          providerOptions: { enableThinking: true, thinkingBudget: 131_071 },
+        }),
+      ).pipe(Effect.map((prepared) => prepared.body.thinking_budget))
+    const messages = yield* compileRequest(
+      LLM.request({
+        model: provider.messages("qwen3.7-plus"),
+        prompt: "hi",
+        generation: { maxTokens: 32_000 },
+        providerOptions: { thinking: { type: "enabled", budgetTokens: 131_071 } },
+      }),
+    )
+
+    expect(yield* chat(32_000)).toBe(16_000)
+    expect(yield* chat()).toBe(131_071)
+    expect(messages.body.thinking).toEqual({ type: "enabled", budget_tokens: 16_000 })
+  }),
+)
+
 it.effect("Alibaba validates malformed options before execution", () =>
  Effect.gen(function* () {
    const provider = Alibaba.configure({ region: "ap-southeast-1", apiKey: "fixture" })
@@ -148,11 +148,13 @@ describe("Anthropic Messages route", () => {
    Effect.gen(function* () {
      const enabled = yield* compileRequest(
        LLMRequest.update(request, {
+          generation: { maxTokens: 4_096 },
          providerOptions: { thinking: { type: "enabled", budgetTokens: 1_024 } },
        }),
      )
      const legacy = yield* compileRequest(
        LLMRequest.update(request, {
+          generation: { maxTokens: 4_096 },
          providerOptions: { thinking: { type: "enabled", budget_tokens: 2_048 } },
        }),
      )
@@ -168,6 +170,22 @@ describe("Anthropic Messages route", () => {
    }),
  )

+  it.effect("fits the thinking budget to half the output limit", () =>
+    Effect.gen(function* () {
+      const thinking = (maxTokens: number) =>
+        compileRequest(
+          LLMRequest.update(request, {
+            generation: { maxTokens },
+            providerOptions: { thinking: { type: "enabled", budgetTokens: 31_999 } },
+          }),
+        ).pipe(Effect.map((prepared) => prepared.body.thinking))
+
+      expect(yield* thinking(64_000)).toEqual({ type: "enabled", budget_tokens: 31_999 })
+      expect(yield* thinking(20_000)).toEqual({ type: "enabled", budget_tokens: 10_000 })
+      expect(yield* thinking(1_500)).toEqual({ type: "enabled", budget_tokens: 1_024 })
+    }),
+  )
+
  it.effect("rejects enabled thinking without a budget", () =>
    Effect.gen(function* () {
      const error = yield* compileRequest(
@@ -244,6 +244,29 @@ describe("Bedrock Converse route", () => {
    }),
  )

+  it.effect("fits a Claude thinking budget below maxTokens", () =>
+    Effect.gen(function* () {
+      const fields = (maxTokens: number, budgetTokens: number, topK?: number) =>
+        compileRequest(
+          LLMRequest.update(baseRequest, {
+            model: AmazonBedrock.model("us.anthropic.claude-haiku-4-5-20251001-v1:0", {
+              baseURL: "https://bedrock-runtime.test",
+              apiKey: "test-bearer",
+              thinking: { type: "enabled", budgetTokens },
+            }),
+            generation: GenerationOptions.make({ maxTokens, topK }),
+          }),
+        ).pipe(Effect.map((prepared) => prepared.body.additionalModelRequestFields))
+
+      expect(yield* fields(64_000, 31_999)).toEqual({ thinking: { type: "enabled", budget_tokens: 31_999 } })
+      expect(yield* fields(20_000, 31_999, 40)).toEqual({
+        top_k: 40,
+        thinking: { type: "enabled", budget_tokens: 10_000 },
+      })
+      expect(yield* fields(1_500, 31_999)).toEqual({ thinking: { type: "enabled", budget_tokens: 1_024 } })
+    }),
+  )
+
  it.effect("omits additionalModelRequestFields when topK is unset", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(baseRequest)
@@ -33,6 +33,8 @@ describe("Black Forest Labs Images recorded", () => {

        expect(response.image.source.type).toBe("bytes")
        expect(dimensions(yield* response.image.bytes())).toEqual({ width: 512, height: 512 })
+        // BFL reports cost on submit only; the Ready result omits it.
+        expect(response.usage).toEqual({ type: "credits", credits: 1.4000000000000001 })
      }),
    { timeout: 15 * 60 * 1000 },
  )
@@ -22,21 +22,22 @@ testEffect(
      expect(body).toMatchObject({
        model: "fixture",
        stream: true,
-        store: false,
+        store: true,
        instructions: "Keep the context",
-        parallel_tool_calls: true,
+        parallel_tool_calls: false,
        prompt_cache_key: "session-key",
        service_tier: "priority",
        reasoning: { effort: "high", summary: "auto" },
+        context_management: [{ type: "compaction" }],
+        max_tool_calls: 1,
+        tool_choice: "required",
+        text: { verbosity: "high", format: { type: "json_object" } },
        prompt_cache_retention: "24h",
        prompt_cache_options: { mode: "session", ttl: "1h" },
        input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }, { type: "compaction_trigger" }],
      })
      expect(body.tools).toHaveLength(1)
      expect(body.tools[0].name).toBe("lookup")
-      expect(body.tool_choice).toBeUndefined()
-      expect(body.context_management).toBeUndefined()
-      expect(body.text).toBeUndefined()
      expect(body.max_output_tokens).toBeUndefined()
      expect(body.previous_response_id).toBeUndefined()
      return respond(
@@ -57,7 +58,7 @@ testEffect(
      )
    }),
  ),
-).effect("trigger uses normal request preparation, configured deployment, and supplied subscription headers", () =>
+).effect("trigger keeps request controls, configured deployment, and supplied subscription headers", () =>
  Effect.gen(function* () {
    const calls: string[] = []
    const input = LLM.request({
@@ -67,12 +68,14 @@ testEffect(
      promptCacheKey: "session-key",
      tools: [{ name: "lookup", description: "Lookup", inputSchema: { type: "object", properties: {} } }],
      toolChoice: { type: "tool", name: "lookup" },
-      generation: { maxTokens: 1 },
      providerOptions: {
        store: true,
        reasoningEffort: "high",
        reasoningSummary: "auto",
        contextManagement: [{ type: "compaction" }],
+        parallelToolCalls: false,
+        maxToolCalls: 1,
+        textVerbosity: "low",
      },
      http: {
        headers: { "chatgpt-account-id": "fixture-account", "x-codex-beta-features": "remote_compaction_v2" },
@@ -82,8 +85,7 @@ testEffect(
          prompt_cache_retention: "24h",
          prompt_cache_options: { mode: "session", ttl: "1h" },
          store: true,
-          stream: false,
-          text: { format: { type: "json_object" } },
+          text: { verbosity: "high", format: { type: "json_object" } },
          tool_choice: "required",
        },
      },
@@ -114,6 +116,75 @@ testEffect(
  }),
 )

+testEffect(
+  dynamicResponse(({ text, respond }) =>
+    Effect.sync(() => {
+      expect(JSON.parse(text).text).toEqual({ verbosity: "low", format: { type: "json_object" } })
+      return respond(sseEvents({ type: "response.completed", response: { id: "resp_1", output: [checkpoint] } }), {
+        headers: { "content-type": "text/event-stream" },
+      })
+    }),
+  ),
+).effect("keeps explicit verbosity on a trigger checkpoint for prompt cache reuse", () =>
+  LLMClient.compact(
+    LLM.request({
+      model: OpenAI.configure({ apiKey: "fixture" }).responses("gpt-5.5"),
+      prompt: "Hello.",
+      providerOptions: { textVerbosity: "low" },
+      http: { body: { text: { format: { type: "json_object" } } } },
+    }),
+    trigger,
+  ),
+)
+
+testEffect(
+  dynamicResponse(({ text, respond }) =>
+    Effect.sync(() => {
+      const body = JSON.parse(text)
+      expect(body.text).toEqual({ verbosity: "high", format: { type: "json_object" } })
+      expect(body.max_output_tokens).toBe(20_000)
+      return respond(sseEvents({ type: "response.completed", response: { id: "resp_1", output: [checkpoint] } }), {
+        headers: { "content-type": "text/event-stream" },
+      })
+    }),
+  ),
+).effect("keeps the effective body-overlay verbosity and text formatting", () =>
+  LLMClient.compact(
+    LLM.request({
+      model: OpenAI.configure({ apiKey: "fixture" }).responses("gpt-5.5"),
+      prompt: "Hello.",
+      generation: { maxTokens: 20_000 },
+      providerOptions: { textVerbosity: "low" },
+      http: { body: { text: { verbosity: "high", format: { type: "json_object" } } } },
+    }),
+    trigger,
+  ),
+)
+
+testEffect(
+  dynamicResponse(({ text, respond }) =>
+    Effect.sync(() => {
+      expect(JSON.parse(text).max_output_tokens).toBe(128)
+      return respond(JSON.stringify({ error: { message: "max_output_tokens must be at least 20000" } }), {
+        status: 400,
+        headers: { "content-type": "application/json" },
+      })
+    }),
+  ),
+).effect("passes configured output limits through and leaves rejection to the provider", () =>
+  Effect.gen(function* () {
+    const error = yield* LLMClient.compact(
+      LLM.request({
+        model: OpenAI.configure({ apiKey: "fixture" }).responses("gpt-5.5"),
+        prompt: "Hello.",
+        generation: { maxTokens: 128 },
+      }),
+      trigger,
+    ).pipe(Effect.flip)
+    expect(error.message).toContain("at least 20000")
+  }),
+)
+
 const idless = { type: "compaction", encrypted_content: "opaque" }
 testEffect(
  fixedResponse(
@@ -184,7 +255,7 @@ testEffect(fixedResponse(sseEvents({ type: "response.output_item.done", item: ch
      expect(error.reason._tag).toBe("InvalidProviderOutput")
    }),
 )
-for (const body of [{ input: [] }, { previous_response_id: "stale" }]) {
+for (const body of [{ input: [] }, { previous_response_id: "stale" }, { stream: false }]) {
  testEffect(dynamicResponse(() => Effect.die("Must reject before sending"))).effect(
    `rejects caller-supplied ${Object.keys(body)[0]} before sending trigger`,
    () =>
@@ -0,0 +1,50 @@
+import { describe, expect } from "bun:test"
+import { Effect, Stream } from "effect"
+import { Transcription } from "../../src/index.js"
+import { ElevenLabs } from "../../src/providers.js"
+import { recordedTests } from "../recorded-test.js"
+import { TRANSCRIPT, audio, audioRecording, dialog } from "./transcription-recording.js"
+
+const model = ElevenLabs.configure({ apiKey: process.env.ELEVENLABS_API_KEY ?? "fixture" }).transcription("scribe_v2")
+
+const recorded = recordedTests({
+  prefix: "elevenlabs-transcription",
+  provider: "elevenlabs",
+  protocol: "elevenlabs-transcription",
+  requires: ["ELEVENLABS_API_KEY"],
+  options: audioRecording,
+})
+
+describe("ElevenLabs Transcription recorded", () => {
+  recorded.effect("transcribes audio with word timestamps", () =>
+    Effect.gen(function* () {
+      const request = Transcription.request({ model, audio: yield* audio, timestamps: "word" })
+      const response = yield* Transcription.generate(request)
+
+      expect(response.text).toMatch(TRANSCRIPT)
+      expect(response.words?.map((word) => word.text)).toEqual(["Hello", "from", "OpenCode"])
+      expect(response.words?.every((word) => word.speaker === undefined && (word.confidence ?? 0) > 0)).toBe(true)
+      expect(response.segments).toBeUndefined()
+      expect(response.language).toBe("eng")
+      expect(response.durationSeconds).toBeGreaterThan(0)
+      expect(response.usage).toEqual({ type: "seconds", seconds: response.durationSeconds })
+      expect(response.providerMetadata?.elevenlabs?.transcriptionId).toEqual(expect.any(String))
+
+      const events = Array.from(yield* Stream.runCollect(Transcription.stream(request)))
+      expect(events.map((event) => event.type)).toEqual(["finish"])
+    }),
+  )
+
+  recorded.effect("groups diarized words into speaker turns", () =>
+    Effect.gen(function* () {
+      const response = yield* Transcription.generate({ model, audio: yield* dialog, diarize: true })
+
+      expect(response.segments?.map((segment) => segment.speaker)).toEqual(["speaker_0", "speaker_1"])
+      expect(response.segments?.[0].text).toMatch(/^Did the release ship\?$/)
+      expect(response.segments?.[1].text).toMatch(/^Yes, it shipped this morning\.?$/)
+      expect(response.segments?.map((segment) => segment.text).join(" ")).toBe(response.text)
+      expect(response.words?.some((word) => word.text.trim() === "")).toBe(false)
+      expect(new Set(response.words?.map((word) => word.speaker))).toEqual(new Set(["speaker_0", "speaker_1"]))
+    }),
+  )
+})
@@ -110,11 +110,16 @@ for (const model of [
    dynamicResponse(({ request, text, respond }) =>
      Effect.sync(() => {
        expect(new URL(request.url).pathname).toEndWith("/responses/compact")
-        expect(JSON.parse(text)).toEqual({ model: "fixture", input: [item], instructions: "Keep the context" })
+        expect(JSON.parse(text)).toEqual({
+          model: "fixture",
+          input: [item],
+          instructions: "Keep the context",
+          include: ["reasoning.encrypted_content"],
+        })
        return respond(JSON.stringify({ object: "response.compaction", output: [checkpoint] }))
      }),
    ),
-  ).effect(`${model.provider} compacts provider-specific history without lowering generation settings`, () =>
+  ).effect(`${model.provider} validates tools but ignores unrelated unsupported generation settings`, () =>
    Effect.gen(function* () {
      const request = LLM.request({
        model,
@@ -151,6 +156,11 @@ for (const model of [
      ] as const) {
        const error = yield* LLMClient.generate(candidate).pipe(Effect.flip)
        expect(error.reason._tag).toBe(tag)
+        if (candidate.tools.length > 0) {
+          const compactError = yield* LLMClient.compact(candidate).pipe(Effect.flip)
+          expect(compactError.reason._tag).toBe("InvalidRequest")
+          continue
+        }
        const response = yield* LLMClient.compact(candidate)
        expect(response.replacement[0]?.content[0]?.type).toBe("compaction")
      }
@@ -255,6 +265,13 @@ for (const overlay of [undefined, { service_tier: "priority", prompt_cache_key:
          model: "fixture",
          input: [{ type: "message", role: "user", content: [{ type: "input_text", text: "hello" }] }],
          service_tier: overlay?.service_tier ?? "flex",
+          reasoning: { effort: "low" },
+          text: { verbosity: "low", format: { type: "json_object" } },
+          include: ["reasoning.encrypted_content"],
+          parallel_tool_calls: false,
+          tools: [
+            { type: "function", name: "lookup", description: "Lookup", parameters: { type: "object" }, strict: false },
+          ],
          prompt_cache_key: overlay?.prompt_cache_key ?? "affinity",
          prompt_cache_retention: "24h",
          prompt_cache_options: { mode: "explicit", ttl: "30m" },
@@ -268,12 +285,20 @@ for (const overlay of [undefined, { service_tier: "priority", prompt_cache_key:
        model: OpenAI.configure({ apiKey: "test" }).responses("fixture"),
        prompt: "hello",
        promptCacheKey: "affinity",
-        providerOptions: { serviceTier: "flex" },
+        providerOptions: {
+          serviceTier: "flex",
+          reasoningEffort: "low",
+          textVerbosity: "low",
+          include: ["reasoning.encrypted_content"],
+          parallelToolCalls: false,
+        },
        generation: { maxTokens: 100 },
+        tools: [{ name: "lookup", description: "Lookup", inputSchema: {} }],
        http: {
          body: {
            stream: true,
            store: false,
+            text: { format: { type: "json_object" } },
            prompt_cache_retention: "24h",
            prompt_cache_options: { mode: "explicit", ttl: "30m" },
            ...overlay,
@@ -396,6 +421,8 @@ for (const model of [
            model: model.id,
            input: [{ type: "message", role: "user", content: [{ type: "input_text", text: "original" }] }],
            instructions: "system",
+            include: ["reasoning.encrypted_content"],
+            ...(model.id === "gpt-5.3-codex" ? { reasoning: { effort: "medium", summary: "auto" } } : {}),
          })
          return respond(
            JSON.stringify({
@@ -407,7 +434,10 @@ for (const model of [
          )
        }
        expect(new URL(request.url).pathname.endsWith("/responses")).toBe(true)
-        expect(body.input).toEqual([...output, { type: "message", role: "user", content: [{ type: "input_text", text: "continue" }] }])
+        expect(body.input).toEqual([
+          ...output,
+          { type: "message", role: "user", content: [{ type: "input_text", text: "continue" }] },
+        ])
        return respond(sseEvents({ type: "response.completed", response: { id: "resp_1", output: [] } }), {
          headers: { "content-type": "text/event-stream" },
        })
@@ -90,6 +90,23 @@ describe("Gemini route", () => {
    }),
  )

+  it.effect("fits the thinking budget to half the output limit", () =>
+    Effect.gen(function* () {
+      const thinkingBudget = (budget: number, maxTokens = 32_000) =>
+        compileRequest(
+          LLMRequest.update(request, {
+            generation: { maxTokens },
+            providerOptions: { thinkingConfig: { thinkingBudget: budget } },
+          }),
+        ).pipe(Effect.map((prepared) => prepared.body.generationConfig?.thinkingConfig?.thinkingBudget))
+
+      expect(yield* thinkingBudget(32_768)).toBe(16_000)
+      expect(yield* thinkingBudget(8_000)).toBe(8_000)
+      expect(yield* thinkingBudget(-1)).toBe(-1)
+      expect(yield* thinkingBudget(8_192, 1_000)).toBe(512)
+    }),
+  )
+
  it.effect("forwards standard Gemini generation options", () =>
    Effect.gen(function* () {
      const prepared = yield* compileRequest(
@@ -29,7 +29,11 @@ describe("OpenAI Images recorded", () => {

      expect(response.images).toHaveLength(1)
      expect(response.image.mediaType).toBe("image/jpeg")
+      expect(response.image.info).toEqual({ format: "jpeg", width: 1024, height: 1024 })
      expect((yield* response.image.bytes()).length).toBeGreaterThan(0)
+      expect(response.providerMetadata).toEqual({
+        openai: { outputFormat: "jpeg", size: "1024x1024", quality: "low", background: "opaque" },
+      })
    }),
  )

@@ -76,8 +80,13 @@ describe("OpenAI Images recorded", () => {
      expect(events.map((event) => event.type)).toEqual(["image-partial", "image", "finish"])
      const image = events.find(ImageEvent.is.image)
      expect(image?.image.mediaType).toBe("image/jpeg")
+      expect(image?.image.info).toEqual({ format: "jpeg", width: 1024, height: 1024 })
      expect(dimensions(yield* image!.image.bytes())).toEqual({ width: 1024, height: 1024 })
-      expect(events.find(ImageEvent.is.finish)?.usage).toMatchObject({ type: "tokens" })
+      const finish = events.find(ImageEvent.is.finish)
+      expect(finish?.usage).toMatchObject({ type: "tokens" })
+      expect(finish?.providerMetadata).toEqual({
+        openai: { outputFormat: "jpeg", size: "1024x1024", quality: "low", background: "opaque" },
+      })
    }),
  )
 })
@@ -1945,7 +1945,7 @@ describe("OpenAI Responses route", () => {
      expect(prepared.body.prompt_cache_key).toBe("session_123")
      expect(prepared.body.include).toEqual(["reasoning.encrypted_content"])
      expect(prepared.body.reasoning).toEqual({ effort: "high", summary: "auto" })
-      expect(prepared.body.text).toEqual({ verbosity: "low" })
+      expect(prepared.body.text).toBeUndefined()
      expect(prepared.body.metadata).toEqual({ environment: "test", tenant: "acme" })
      expect(prepared.body.safety_identifier).toBe("user_123")
      expect(prepared.body.stream_options).toEqual({ include_obfuscation: false })
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Aiden Cline	be6d424b67	feat(core): record overflow as a compaction reason	2026-09-27 22:14:42 -05:00
Jérôme BenoitandTest User	0caae608a2	chore(nix): update nixpkgs for Bun 1.4 (#50221 ) Co-authored-by: Test User <test@test.com>	2026-09-27 21:34:52 -05:00
Kit Langton	96f23508be	refactor(core): remove unused project discovery option (#51729 )	2026-09-27 15:05:46 -07:00
Kit Langton	28bb0a7158	refactor(core): drop forwarding shim modules (#51670 )	2026-09-27 14:47:19 -07:00
DS	3d109828ff	fix(tui): truncate btw question preview (#51713 )	2026-09-27 21:05:20 +02:00
Shoubhit Dash	c0d49f101c	feat(ai): retry transient failures on queued generation reads (#51635 )	2026-09-27 19:47:25 +05:30
Shoubhit Dash	be2446e188	feat(ai): add ElevenLabs Scribe transcription route (#51641 )	2026-09-27 19:34:36 +05:30
Shoubhit Dash	107966eddd	fix(ai): reject and throw with signal.reason on abort (#51633 )	2026-09-27 19:24:45 +05:30
Kit Langton	f5e580cde1	chore(core): remove dead modules and exports (#51667 )	2026-09-27 06:38:43 -07:00
Shoubhit Dash	4428a77acd	fix(ai): classify terminal generation failures by provider error code (#51632 )	2026-09-27 18:44:21 +05:30
opencode-agent[bot]	01eb18144b	chore(core): refresh bundled models.dev snapshot	2026-09-27 12:19:33 +00:00
Shoubhit Dash	01208048dc	test(ai): cover queued media failures, resume, cancel, and transcription sources (#51626 )	2026-09-27 17:43:24 +05:30
Shoubhit Dash	995f76cb63	feat(tui): add last turn source to diff viewer (#51639 )	2026-09-27 17:39:41 +05:30
Shoubhit Dash	c33de198e3	fix(ai): surface truncated Gemini speech and transcription results (#51379 )	2026-09-27 14:29:36 +05:30
Shoubhit Dash	24224bcb57	fix(ai): describe speech assets in the format actually sent (#51377 )	2026-09-27 14:16:23 +05:30
Aiden Cline	7913c8db59	feat(core): log provider rejections that trigger overflow compaction (#51582 )	2026-09-26 23:11:33 -05:00
Aiden Cline	d9987ef9c8	feat(core): fit output limits to the context window (#51271 )	2026-09-26 22:58:28 -05:00
Jack	f0ed4f67df	docs: list LongCat 2.5 Preview Free in V2 Console (#51487 )	2026-09-26 21:20:36 +08:00
opencode-agent[bot]	2109d68d39	chore(core): refresh bundled models.dev snapshot	2026-09-26 12:18:22 +00:00
Filip	cefb2968e2	fix(cli): cancel auth attempts on ctrl+c (#51484 )	2026-09-26 11:59:17 +00:00
opencode-agent[bot]	00d179015f	chore: update nix node_modules hashes	2026-09-26 10:01:15 +00:00
opencode-agent[bot]rekram1-node thdxr rekram1-node Filip Hejmowski	1d4e1233e5	feat(cli): share grouped auth picker with MCP auth (#51006 ) Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com> Co-authored-by: thdxr <thdxr@users.noreply.github.com> Co-authored-by: rekram1-node <63023139+rekram1-node@users.noreply.github.com> Co-authored-by: Filip Hejmowski <fhejmowski@simplito.com>	2026-09-26 11:42:04 +02:00
opencode-agent[bot]vimtor Victor Navarro	d14f20b46e	fix(tui): capitalize OpenCode web search provider (#49023 ) Co-authored-by: vimtor <36263538+vimtor@users.noreply.github.com> Co-authored-by: Victor Navarro <vn4varro@gmail.com>	2026-09-26 09:36:20 +00:00
opencode-agent[bot]andrekram1-node	37049a5a13	fix(tui): skip model selection after MCP connection (#51448 ) Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com>	2026-09-26 00:00:25 -05:00
Aiden Cline	a64bc3616e	refactor(core): cleanup session compaction (#51447 )	2026-09-26 00:00:11 -05:00
opencode	39021dfd67	sync release versions for v2.0.18	2026-09-25 23:57:39 +00:00
opencode-agent[bot]	709ddc0d79	chore: update nix node_modules hashes	2026-09-25 23:23:45 +00:00
Kit LangtonandAiden Cline	041885d838	fix(core): decode legacy media in compaction checkpoints (#51409 ) Co-authored-by: Aiden Cline <aidenpcline@gmail.com>	2026-09-25 18:08:16 -05:00
Aiden Cline	29ce49db0f	refactor(util): share a browser opener across cli, tui, and core (#51412 )	2026-09-25 18:00:32 -05:00
opencode	00738c5b2d	sync release versions for v2.0.17	2026-09-25 21:09:12 +00:00
Aiden Cline	6ec8ca920f	feat(core): name Copilot sessions with the free utility model (#51237 )	2026-09-25 14:53:16 -05:00
Shoubhit Dash	6585bb7105	fix(ai): keep OpenAI image output settings and Z.ai URL expiry (#51380 )	2026-09-25 22:51:46 +05:30
Shoubhit Dash	f954688fbb	fix(ai): harden OpenAI transcription stream parsing (#51378 )	2026-09-25 22:51:22 +05:30
Shoubhit Dash	1463dabde9	fix(ai): tighten media error consistency (#51374 )	2026-09-25 22:46:04 +05:30
Shoubhit Dash	29ea6ee05b	test(ai): cover media facade selectors and url asset edges (#51376 )	2026-09-25 22:37:20 +05:30
Shoubhit Dash	b170904731	docs(ai): describe transcription speakers as a constraint (#51382 )	2026-09-25 22:36:02 +05:30
Shoubhit Dash	88e1fa9304	fix(ai): accept timestamps: false on speech routes without timestamps (#51375 )	2026-09-25 22:33:59 +05:30
opencode-agent[bot]andvimtor	ff1bf315ed	docs(www): hide Console Usage API documentation (#51358 ) Co-authored-by: vimtor <36263538+vimtor@users.noreply.github.com>	2026-09-25 19:01:48 +02:00
Shoubhit Dash	144ce00e00	fix(ai): bound generation event poll sleep by the deadline (#51372 )	2026-09-25 22:31:35 +05:30
Shoubhit Dash	ad504094f0	fix(ai): never delete a finished Runway task on cancel (#51373 )	2026-09-25 22:24:16 +05:30
Shoubhit Dash	bad6834a3e	fix(ai): size fal Kontext by aspect ratio and decode sync_mode data URIs (#51371 )	2026-09-25 22:23:14 +05:30
Shoubhit Dash	0c4bbc3cd1	feat(ai): keep prompt cache across effort switches on GPT-6 Sol and Luna (#51339 )	2026-09-25 22:15:23 +05:30
Shoubhit Dash	ae7dd82126	fix(ai): report Black Forest Labs submit cost as image usage (#51370 )	2026-09-25 22:13:55 +05:30
Shoubhit Dash	65d5123ead	fix(ai): enable AssemblyAI speaker labels when speakers is set (#51369 )	2026-09-25 22:11:44 +05:30
Shoubhit Dash	4eb46a8885	fix(core): revert always-thinking variants for Claude Opus 5.5 (#51359 )	2026-09-25 22:03:12 +05:30
Jack	1986e92842	docs(go): show permanent DeepSeek $60 allowance (#51363 )	2026-09-26 00:17:08 +08:00
Shoubhit Dash	14fc63ba9e	fix(core): keep thinking on for Claude Opus 5.5 variants (#51338 )	2026-09-25 18:32:41 +05:30
opencode-agent[bot]andnexxeln	c34ffa117e	fix(ai): preserve Gemini 3.8 TTS WAV output (#51300 ) Co-authored-by: nexxeln <95541290+nexxeln@users.noreply.github.com>	2026-09-25 18:11:36 +05:30
opencode-agent[bot]vimtor vimtor	beeb14e910	feat(prompt): undo queued prompts back into the input (#51124 ) Co-authored-by: vimtor <36263538+vimtor@users.noreply.github.com> Co-authored-by: vimtor <vn4varro@gmail.com>	2026-09-25 14:36:29 +02:00
opencode-agent[bot]	aae42e2e75	chore(core): refresh bundled models.dev snapshot	2026-09-25 12:21:04 +00:00
opencode-agent[bot]vimtor vimtor	cc9011c1ae	fix(tui): virtualize large added-file diffs (#51122 ) Co-authored-by: vimtor <36263538+vimtor@users.noreply.github.com> Co-authored-by: vimtor <vn4varro@gmail.com>	2026-09-25 13:51:00 +02:00
Victor Navarro	6cd938e1e9	feat(core): register Console-hosted MCP servers (#51325 )	2026-09-25 13:16:04 +02:00
Jack	7de6b3fc15	docs(console): document Qwen3.8 Max (#51320 )	2026-09-25 19:13:45 +08:00
opencode-agent[bot]	c1c9a13993	chore: update nix node_modules hashes	2026-09-25 08:37:39 +00:00
Simon Klee	917d904f18	tui: update OpenTUI v0.5.12 (#50567 )	2026-09-25 08:17:14 +00:00
opencode-agent[bot]andBrendonovich	ee5b67eb84	fix(app): unify session project icon resolution (#51288 ) Co-authored-by: Brendonovich <14191578+Brendonovich@users.noreply.github.com>	2026-09-25 07:47:12 +00:00
Aiden Cline	048a47e89e	docs: focus compaction page on user-facing behavior (#51270 )	2026-09-25 00:21:17 -05:00
Aiden Cline	5335347e80	feat(codemode): add WeakMap and WeakSet (#51257 )	2026-09-25 00:15:19 -05:00
Aiden Cline	16b18dff13	Revert "fix(core): fit model limits and recover compaction overflow" (#51273 )	2026-09-25 00:12:14 -05:00
Aiden Cline	61c2349cef	fix(core): fit model limits and recover compaction overflow (#51238 )	2026-09-25 00:11:40 -05:00
opencode-agent[bot]andBrendonovich	684721efb8	feat(app): add provider account switching (#51266 ) Co-authored-by: Brendonovich <Brendonovich@users.noreply.github.com>	2026-09-25 05:03:33 +00:00
Aiden Cline	962c14a49c	fix(codemode): honor thisArg, program toString in computed keys, and ToPrimitive in String and Number arguments (#51264 )	2026-09-24 23:46:15 -05:00
opencode-agent[bot]andrekram1-node	85b98e7da4	fix(tui): handle storage watcher errors after startup (#51243 ) Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com>	2026-09-24 20:25:06 -05:00
Aiden Cline	8061220b08	test(codemode): vendor every eligible test262 directory and bound unsupported globals (#51242 )	2026-09-24 20:19:24 -05:00
Luke Parker	b02cc35f13	fix(desktop): keep browser page visible under floating content (#51240 )	2026-09-25 10:35:17 +10:00
Aiden Cline	e23d89c9a9	fix(codemode): destructure object patterns from primitives and convert Date components through ToPrimitive (#51239 )	2026-09-24 19:32:19 -05:00
ARH Alireza Haghdoost Claude Sonnet 5	e8b3e19e85	fix(tui): don't crash when fs.watch throws (e.g. ENOSPC) (#51210 ) Co-authored-by: Alireza Haghdoost <haghdoost@uber.com> Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>	2026-09-24 19:16:43 -05:00
Aiden Cline	5256f30957	feat(codemode): honor program valueOf and toString in operators and conversions (#50837 )	2026-09-24 18:45:48 -05:00
Aiden Cline	61ecf404b9	fix(core): apply GPT verbosity defaults at request time (#51166 )	2026-09-24 17:13:39 -05:00
Shoubhit Dash	92d2b1700f	refactor(ai): one media client shape and route types erased over options (#51226 )	2026-09-25 03:15:45 +05:30
Aiden Cline	56262121ee	feat(codemode): bind this and arguments in functions, add Function.prototype.call, apply, and bind (#50831 )	2026-09-24 16:34:46 -05:00
Aiden Cline	e3b588e7d2	refactor(ai): apply tool schema rules once per request (#51162 )	2026-09-24 16:27:30 -05:00
opencode-agent[bot]andnexxeln	1de648cb13	feat(ai): restore direct LLM input overloads (#51211 ) Co-authored-by: nexxeln <95541290+nexxeln@users.noreply.github.com>	2026-09-25 02:49:07 +05:30
Aiden Cline	03be7f385b	fix(core): accept 128-character tool names (#51207 )	2026-09-24 14:59:57 -05:00
Aiden Cline	8118690839	fix(core): show line counts when tool output is truncated (#51200 )	2026-09-24 14:50:55 -05:00
Aiden Cline	a16eedfed7	fix(codemode): make derived error constructors inherit from Error (#51045 )	2026-09-24 14:03:10 -05:00
Aiden Cline	e796f2f9a5	fix(core): read provider errors from plain AI SDK stream errors (#51194 )	2026-09-24 13:52:32 -05:00
Aiden Cline	20610e6645	fix(ai): fit Claude thinking budgets on Bedrock Converse (#51190 )	2026-09-24 13:48:39 -05:00
Aiden Cline	7f245b0968	fix(ai): fit OpenRouter reasoning budgets to the output limit (#51189 )	2026-09-24 13:42:10 -05:00
Shoubhit Dash	7013e925f5	refactor(ai): keep LLM calls request-only in the promise client (#51180 )	2026-09-24 23:47:42 +05:30
Aiden Cline	499c2feaa3	fix(core): cap Alibaba thinking budget variants at 64k (#51154 )	2026-09-24 13:14:49 -05:00
Aiden Cline	03af821aa5	fix(core): restore the shell no-output placeholder (#51187 )	2026-09-24 13:12:42 -05:00
Aiden Cline	c903774556	fix(ai): fit thinking budgets to the output limit (#51157 )	2026-09-24 12:58:54 -05:00
James Long	14aaf91e65	fix(tui): mark failed groups with a plain ✗ (#51175 )	2026-09-24 13:52:14 -04:00
James Long	c832432d89	refactor(tui): drop unused yellow alias from opencode theme (#51177 )	2026-09-24 13:17:21 -04:00
opencode-agent[bot]andjlongster	1d431a80df	fix(cli): reuse core declarations during typecheck (#51165 ) Co-authored-by: jlongster <jlongster@users.noreply.github.com>	2026-09-24 13:16:46 -04:00