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437 changed files with 4681 additions and 13256 deletions
+5
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@@ -0,0 +1,5 @@
---
"@opencode/core": patch
---
Correct directory page headings when the read offset is zero.
-20
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@@ -24,10 +24,6 @@ on:
description: "Override version (optional)"
required: false
type: string
release_notes:
description: "Reviewed V2 release notes for the Discord announcement (optional)"
required: false
type: string
concurrency: ${{ github.workflow }}-${{ github.ref }}-${{ (github.ref_name == 'v2' && (inputs.version || inputs.bump) && 'release') || inputs.version || inputs.bump }}
@@ -657,19 +653,3 @@ jobs:
OPENCODE_DESKTOP_DIST: /tmp/desktop
CLOUDFLARE_ACCOUNT_ID: 15d29c8639fd3733b1b5486a2acfd968
CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
notify-discord-v2:
needs:
- version
- publish
if: github.repository == 'anomalyco/opencode' && github.ref_name == 'v2' && needs.version.outputs.release && needs.publish.result == 'success'
runs-on: blacksmith-4vcpu-ubuntu-2404
steps:
# Unlike dev, V2 publishes a tag rather than a GitHub Release event.
- name: Announce V2 release in Discord
uses: SethCohen/github-releases-to-discord@24d166886aee4646d448c8a389ff9e1ebcab3682 # v1.20.0
with:
webhook_url: ${{ secrets.DISCORD_WEBHOOK }}
release_name: OpenCode V2 ${{ needs.version.outputs.tag }}
release_body: ${{ inputs.release_notes }}
release_html_url: https://github.com/${{ github.repository }}/tree/${{ needs.version.outputs.tag }}
+1 -1
View File
@@ -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 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 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 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.
+86 -94
View File
@@ -32,7 +32,7 @@
},
"packages/ai": {
"name": "@opencode/ai",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@aws-sdk/credential-providers": "3.1057.0",
"@opencode/schema": "workspace:*",
@@ -54,7 +54,7 @@
},
"packages/app": {
"name": "@opencode/app",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@corvu/drawer": "catalog:",
"@dnd-kit/abstract": "0.5.0",
@@ -112,14 +112,13 @@
},
"packages/cli": {
"name": "@opencode/cli",
"version": "2.0.19",
"version": "2.0.16",
"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",
@@ -136,7 +135,7 @@
"effect": "catalog:",
"immer": "11.1.4",
"jsonc-parser": "3.3.1",
"picocolors": "1.1.1",
"open": "10.1.2",
"solid-js": "catalog:",
"tree-sitter-bash": "0.25.0",
"tree-sitter-powershell": "0.25.10",
@@ -178,7 +177,7 @@
},
"packages/client": {
"name": "@opencode/client",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/protocol": "workspace:*",
"@opencode/schema": "workspace:*",
@@ -204,7 +203,7 @@
},
"packages/codemode": {
"name": "@opencode/codemode",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"acorn": "8.15.0",
"effect": "catalog:",
@@ -217,7 +216,7 @@
},
"packages/console/app": {
"name": "@opencode/console-app",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@cloudflare/vite-plugin": "1.15.2",
"@ibm/plex": "6.4.1",
@@ -253,7 +252,7 @@
},
"packages/console/core": {
"name": "@opencode/console-core",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@aws-sdk/client-sts": "3.782.0",
"@jsx-email/render": "1.1.1",
@@ -280,7 +279,7 @@
},
"packages/console/function": {
"name": "@opencode/console-function",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@openauthjs/openauth": "0.0.0-20250322224806",
"@opencode/console-core": "workspace:*",
@@ -297,7 +296,7 @@
},
"packages/console/mail": {
"name": "@opencode/console-mail",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@jsx-email/all": "2.2.3",
"@jsx-email/cli": "1.4.3",
@@ -321,7 +320,7 @@
},
"packages/console/support": {
"name": "@opencode/console-support",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@cloudflare/vite-plugin": "1.15.2",
"@opencode/console-core": "workspace:*",
@@ -341,7 +340,7 @@
},
"packages/core": {
"name": "@opencode/core",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@ai-sdk/cohere": "3.0.27",
"@ai-sdk/gateway": "3.0.104",
@@ -409,7 +408,7 @@
},
"packages/desktop": {
"name": "@opencode/desktop",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@zip.js/zip.js": "2.7.62",
"electron-context-menu": "5.0.0",
@@ -439,7 +438,7 @@
"drizzle-kit": "catalog:",
"drizzle-orm": "catalog:",
"effect": "catalog:",
"electron": "44.4.5",
"electron": "44.4.3",
"electron-builder": "26.15.7",
"electron-vite": "6.0.0-beta.1",
"puppeteer-core": "25.9.0",
@@ -458,7 +457,7 @@
},
"packages/enterprise": {
"name": "@opencode/enterprise",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@hono/standard-validator": "catalog:",
"@opencode-ai/sdk": "1.18.21",
@@ -495,7 +494,7 @@
},
"packages/function": {
"name": "@opencode/function",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@octokit/auth-app": "8.0.1",
"@octokit/rest": "catalog:",
@@ -511,7 +510,7 @@
},
"packages/http-recorder": {
"name": "@opencode/http-recorder",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@effect/platform-node-shared": "4.0.0-rc.112",
},
@@ -530,7 +529,7 @@
},
"packages/httpapi-codegen": {
"name": "@opencode/httpapi-codegen",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"effect": "catalog:",
"prettier": "3.6.2",
@@ -543,7 +542,7 @@
},
"packages/latex": {
"name": "@opencode/latex",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/plugin": "workspace:*",
"@opentui/core": "catalog:",
@@ -557,7 +556,7 @@
},
"packages/merman": {
"name": "@opencode/merman",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/plugin": "workspace:*",
"@opentui/core": "catalog:",
@@ -572,7 +571,7 @@
},
"packages/plugin": {
"name": "@opencode/plugin",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@ai-sdk/provider": "3.0.8",
"@opencode/ai": "workspace:*",
@@ -598,8 +597,8 @@
},
"peerDependencies": {
"@opencode/theme": "workspace:*",
"@opentui/core": ">=0.5.12",
"@opentui/solid": ">=0.5.12",
"@opentui/core": ">=0.5.10",
"@opentui/solid": ">=0.5.10",
"solid-js": ">=1.9.0",
},
"optionalPeers": [
@@ -611,7 +610,7 @@
},
"packages/plugin-browser": {
"name": "@opencode/plugin-browser",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/plugin": "workspace:*",
"@opencode/schema": "workspace:*",
@@ -641,7 +640,7 @@
},
"packages/protocol": {
"name": "@opencode/protocol",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/schema": "workspace:*",
"effect": "catalog:",
@@ -656,7 +655,7 @@
},
"packages/schema": {
"name": "@opencode/schema",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@standard-schema/spec": "catalog:",
"effect": "catalog:",
@@ -680,7 +679,7 @@
},
"packages/sdk": {
"name": "@opencode/sdk",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/client": "workspace:*",
"@opencode/core": "workspace:*",
@@ -701,7 +700,7 @@
},
"packages/server": {
"name": "@opencode/server",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@effect/platform-node": "catalog:",
"@effect/platform-node-shared": "catalog:",
@@ -723,7 +722,7 @@
},
"packages/session-ui": {
"name": "@opencode/session-ui",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@kobalte/core": "catalog:",
"@opencode/client": "workspace:*",
@@ -758,7 +757,7 @@
},
"packages/simulation": {
"name": "@opencode/simulation",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/ai": "workspace:*",
"@opencode/core": "workspace:*",
@@ -778,7 +777,7 @@
},
"packages/stats/app": {
"name": "@opencode/stats-app",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@ibm/plex": "6.4.1",
"@kobalte/core": "catalog:",
@@ -812,7 +811,7 @@
},
"packages/stats/core": {
"name": "@opencode/stats-core",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@aws-sdk/client-athena": "3.933.0",
"@planetscale/database": "1.19.0",
@@ -831,7 +830,7 @@
},
"packages/stats/server": {
"name": "@opencode/stats-server",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@aws-sdk/client-firehose": "3.933.0",
"@effect/platform-node": "catalog:",
@@ -877,7 +876,7 @@
},
"packages/theme": {
"name": "@opencode/theme",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opentui/core": "catalog:",
"effect": "catalog:",
@@ -891,7 +890,7 @@
},
"packages/tui": {
"name": "@opencode/tui",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@opencode/client": "workspace:*",
"@opencode/core": "workspace:*",
@@ -910,6 +909,7 @@
"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": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@kobalte/core": "catalog:",
"@pierre/diffs": "catalog:",
@@ -960,7 +960,7 @@
},
"packages/util": {
"name": "@opencode/util",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@effect/opentelemetry": "catalog:",
"@effect/platform-node": "catalog:",
@@ -982,7 +982,6 @@
"mime-types": "3.0.2",
"minimatch": "10.2.5",
"npm-package-arg": "13.0.2",
"open": "11.0.4",
"pacote": "21.5.1",
},
"devDependencies": {
@@ -998,7 +997,7 @@
},
"packages/web": {
"name": "@opencode/web",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"@astrojs/cloudflare": "12.6.3",
"@astrojs/markdown-remark": "6.3.1",
@@ -1039,7 +1038,7 @@
},
"services/update": {
"name": "@opencode/update",
"version": "2.0.19",
"version": "2.0.16",
"dependencies": {
"jose": "6.0.11",
"semver": "catalog:",
@@ -1099,7 +1098,6 @@
"@types/node": "catalog:",
"bun-types": "1.4.2",
"effect": "catalog:",
"open": "11.0.4",
"solid-js": "catalog:",
},
"catalog": {
@@ -1116,10 +1114,10 @@
"@npmcli/arborist": "9.4.0",
"@octokit/rest": "22.0.0",
"@openauthjs/openauth": "0.0.0-20250322224806",
"@opentui/core": "0.5.12",
"@opentui/keymap": "0.5.12",
"@opentui/solid": "0.5.12",
"@pierre/diffs": "1.5.1",
"@opentui/core": "0.5.10",
"@opentui/keymap": "0.5.10",
"@opentui/solid": "0.5.10",
"@pierre/diffs": "1.2.10",
"@playwright/test": "1.59.1",
"@sentry/solid": "10.71.0",
"@sentry/vite-plugin": "5.4.0",
@@ -2254,27 +2252,27 @@
"@opentelemetry/semantic-conventions": ["@opentelemetry/semantic-conventions@1.43.0", "", {}, "sha512-eSYWTm620tTk45EKSedaUL8MFYI8hW164hIXsgIHyxu3VobUB3fFCu5t0hQby6OoWRPsG1KkKUG2M5UadiLiVg=="],
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@@ -7666,10 +7674,6 @@
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@@ -8072,10 +8076,6 @@
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@@ -8216,10 +8216,6 @@
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@@ -8322,10 +8318,6 @@
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Generated
+3 -3
View File
@@ -2,11 +2,11 @@
"nodes": {
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"narHash": "sha256-EVMNYv7hYDDD9TGVT/hIyTYgpiXA8y3m5xIEIxuGNU0=",
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"rev": "9dd5558b06dbdacbf635a3dd36dce1b1a7ee3a89",
"type": "github"
},
"original": {
+4 -4
View File
@@ -1,8 +1,8 @@
{
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"x86_64-darwin": "sha256-bCBl63CqBiqilb+YdaOLBYYZx/yf47c1aqgDOkgdegg="
}
}
+5 -6
View File
@@ -2,7 +2,7 @@
"$schema": "https://json.schemastore.org/package.json",
"name": "opencode",
"description": "AI-powered development tool",
"version": "2.0.19",
"version": "2.0.16",
"private": true,
"type": "module",
"packageManager": "bun@1.4.2",
@@ -52,9 +52,9 @@
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"@hono/standard-validator": "0.2.0",
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"@opentui/keymap": "0.5.12",
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"@shikijs/stream": "4.4.3",
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@@ -68,7 +68,7 @@
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"@cloudflare/workers-types": "4.20251008.0",
"@openauthjs/openauth": "0.0.0-20250322224806",
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"@pierre/diffs": "1.2.10",
"opentui-spinner": "0.0.7",
"@solid-primitives/event-listener": "2.4.6",
"@solid-primitives/media": "2.3.6",
@@ -162,7 +162,6 @@
"@types/node": "catalog:",
"bun-types": "1.4.2",
"effect": "catalog:",
"open": "11.0.4",
"solid-js": "catalog:"
},
"patchedDependencies": {
+6 -7
View File
@@ -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`. `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.
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.
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.
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.
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.
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.
`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` (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.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.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.
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`).
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`).
### 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)`, `.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:
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:
```ts
const openai = OpenAI.configure({ apiKey, baseURL })
@@ -275,7 +275,6 @@ 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.
+42 -55
View File
@@ -9,13 +9,15 @@ 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({
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 response = yield* LLM.generate(request)
console.log(response.text)
})
@@ -23,8 +25,7 @@ const program = Effect.gen(function* () {
await Effect.runPromise(program.pipe(Effect.provide(AIClient.layer)))
```
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,
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,
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
@@ -71,11 +72,10 @@ 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 input = { model: openai.responses("gpt-4o-mini"), prompt: "Say hello." }
const text = await ai.llm.generate(input)
const text = await ai.llm.generate({ model: openai.responses("gpt-4o-mini"), prompt: "Say hello." })
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(ai.llm.request(input))) {
for await (const event of ai.llm.stream({ model: openai.responses("gpt-4o-mini"), prompt: "Stream hello." })) {
// LLMEvent
}
await ai.dispose()
@@ -129,9 +129,8 @@ VercelAIGateway.configure().experimental.evaluation("typesafe-ai/jev")
OpenRouter reads `OPENROUTER_API_KEY`. Vercel reads `AI_GATEWAY_API_KEY`, then `VERCEL_OIDC_TOKEN`.
The common API uses `boolean`; System One routes lower it to native `noul`.
Choice and score answers include `confidence` when the provider returns it, such as
`response.answers.department.confidence`. Score legends remain available in provider metadata, and
the provider's rounded probabilities are returned unchanged.
Choice and score confidence plus score legends remain available in provider metadata, and the
provider's rounded probabilities are returned unchanged.
## Alibaba Cloud Model Studio
@@ -476,18 +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`, `/multi`) | ✓ |
| 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`) | ✓ |
| 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.
@@ -622,7 +621,8 @@ 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:
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:
```ts
import { Stream } from "effect"
@@ -699,7 +699,7 @@ const program = Effect.gen(function* () {
})
```
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.
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.
## Video generation
@@ -753,10 +753,7 @@ 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. 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,
`Timeout` reason when `poll.timeout` (default 10 minutes) elapses. 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.
@@ -777,9 +774,7 @@ 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. 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.
created; `refresh()` resolves to a new handle.
```ts
import { ai } from "@opencode/ai/promise"
@@ -845,10 +840,9 @@ 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 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
- **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
`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`);
@@ -877,12 +871,11 @@ 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 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.
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.
```ts
import { Console, Effect, Stream } from "effect"
@@ -894,7 +887,7 @@ 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_0").
// Speaker-labelled segments; labels are provider-native strings ("A", "0", "spk:0").
const response = yield* Transcription.generate({
model: Deepgram.configure({ apiKey }).transcription("nova-3"),
audio,
@@ -904,7 +897,7 @@ 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", "eng", "english", "en_us")
response.language // the provider's own value, lowercased ("en", "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(
@@ -928,12 +921,7 @@ 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`.
- **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.
- **AssemblyAI** uploads inline audio before submitting and is the only route that accepts `speakers`.
The promise client mirrors the Effect API:
@@ -948,7 +936,7 @@ 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`** — run direct input or an `LLMRequest` through `LLMClient` for one-import use.
- **`LLM.generate` / `LLM.stream`** — re-exported from `LLMClient` for one-import use.
- **`Message.user(...)` / `Message.assistant(...)` / `Message.tool(...)`** — message constructors from the canonical schema model.
- **`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.
@@ -956,7 +944,6 @@ 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.
+41 -59
View File
@@ -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 — `.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`.
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`.
```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 portability table
in the README's Image generation section.
`size` and `aspectRatio` are not interchangeable; each route rejects fields it cannot lower — see the README's Image
portability matrix.
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`, 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.
`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.
#### 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 (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.video // Media.Asset: url with expiresAt (+ transient `headers` for Veo downloads)
response.usage // credits on Runway; the other three report none
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}; Veo and xAI succeed without a request
yield* generation.cancel() // fal PUT cancel_url, Runway DELETE /tasks/{id}; no-op for Veo and xAI
// 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.
@@ -188,11 +188,10 @@ 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, 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`.
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`.
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.
@@ -216,7 +215,7 @@ const request = Speech.request({
})
const response = yield* Speech.generate(request) // SpeechResponse: audio: Media.Asset, timestamps?, usage?, providerMetadata?
yield* Speech.stream(request) // Stream<SpeechEvent>: generation-queued | generation-progress | audio-delta { chunk } | timestamps { items } | finish { audio, usage? }
yield* Speech.stream(request) // Stream<SpeechEvent>: 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`
@@ -242,12 +241,10 @@ 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'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"`.
(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"`.
**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
@@ -270,8 +267,8 @@ 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`, `elevenlabs-transcription`,
`assemblyai-transcription`; new `AssemblyAI` facade).
`openai-transcription`, `google-transcription`, `deepgram-transcription`, `assemblyai-transcription`; new `AssemblyAI`
facade).
```ts
const request = Transcription.request({
@@ -280,7 +277,7 @@ const request = Transcription.request({
language: "en", // provider-native passthrough
timestamps: "segment", // none | segment | word
diarize: true,
speakers: 2, // speaker count (AssemblyAI exact, ElevenLabs maximum)
speakers: 2, // expected count, hint only (AssemblyAI)
providerOptions: { known_speaker_names: ["agent"] },
})
@@ -294,11 +291,10 @@ 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 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
`<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
`finish` event carries the whole transcript (text, segments, words, language, duration, usage), so the stream route's
`collect` is just "take `finish`".
@@ -308,23 +304,16 @@ 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, ElevenLabs, 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 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`,
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.
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.
- **Language** is passed through (`language`, OpenAI `gpt-transcribe` `languages[]`, Gemini `languageCodes`,
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.
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.
- **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.
@@ -334,15 +323,14 @@ Settled rules:
| Provider | Kind | Audio input | `timestamps` | `diarize` | Unsupported | Usage |
|---|---|---|---|---|---|---|
| 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` |
| 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` |
| 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.
with the realtime work in phase 5. ElevenLabs Scribe is not implemented yet.
### `Generation` — shared async execution
@@ -365,11 +353,7 @@ GenerationAwaitOptions = { poll?: Poll }
Poll = { interval?: Duration; timeout?: Duration }
```
`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.
`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`.
### Usage
@@ -405,26 +389,24 @@ 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 request = ai.llm.request({ model, prompt })
const text = await ai.llm.generate(request)
const text = await ai.llm.generate({ model, prompt })
for await (const event of ai.llm.stream(request)) { … }
await ai.dispose()
```
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.
Streams become `AsyncIterable` via `Stream.toAsyncIterable`. `AIError` is thrown as-is. `AbortSignal` maps to interruption. Nothing in `src/*` except this entrypoint knows about promises.
### Providers
Existing facades gain per-modality selectors; the modality routes each facade provides (*italics* are not
implemented):
Existing facades gain per-modality selectors; the modality routes each facade provides:
| Facade | llm | image | video | speech | transcription | other |
|---|---|---|---|---|---|---|
| `OpenAI` | responses (default), chat | Images API (stream) | *Sora skipped (decision 8)* | ✓ | ✓ | |
| `OpenAI` | responses (default), chat | Images API (stream) | Sora (deprecated 2026-09-24) | ✓ | ✓ | |
| `Google` | Gemini | Gemini-native | Veo | Gemini TTS | `gemini-3.5-transcribe` | |
| `XAI` | ✓ | ✓ | ✓ | | | |
| `ElevenLabs` | | | | ✓ | Scribe | *soundEffect, music (phase 5)* |
| `ElevenLabs` | | | | ✓ | Scribe | soundEffect, music |
| `Cartesia` | | | | ✓ | | |
| `Deepgram` | | | | Aura | ✓ | |
| `Fal` | | ✓ (queued) | ✓ | | | |
@@ -433,11 +415,11 @@ implemented):
| `Replicate` | | ✓ (queued) | | | | |
| `Stability` | | `image` (inline), `upscale()` (queued) | | | | |
| `Runway` | | | ✓ | | | |
| `Luma`, `Kling`, `MiniMax` | | *deferred* | *deferred* | | | |
| `Luma`, `Kling`, `MiniMax` | | per provider | | | | |
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. 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.
`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.
### Routes and protocols
@@ -477,7 +459,7 @@ 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, 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).
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).
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 -1
View File
@@ -1,6 +1,6 @@
{
"$schema": "https://json.schemastore.org/package.json",
"version": "2.0.19",
"version": "2.0.16",
"name": "@opencode/ai",
"type": "module",
"license": "MIT",
-1
View File
@@ -39,7 +39,6 @@ const resolve = (policy: CachePolicy | undefined): CachePolicyObject => {
// whole policy pass for these — emitting hints would be harmless but pointless.
const RESPECTS_INLINE_HINTS = new Set([
"anthropic-messages",
"anthropic-compatible-messages",
"google-vertex-messages",
"bedrock-converse",
"openrouter",
@@ -63,7 +63,6 @@ export const ChoiceAnswer = Schema.Struct({
type: Schema.Literal("choice"),
choice: Schema.String,
probabilities: Schema.optional(Schema.Record(Schema.String, Probability)),
confidence: Schema.optional(Probability),
})
export type ChoiceAnswer = Schema.Schema.Type<typeof ChoiceAnswer>
@@ -71,7 +70,6 @@ export const ScoreAnswer = Schema.Struct({
type: Schema.Literal("score"),
score: Schema.Number,
probabilities: Schema.optional(Schema.Record(Schema.String, Probability)),
confidence: Schema.optional(Probability),
})
export type ScoreAnswer = Schema.Schema.Type<typeof ScoreAnswer>
@@ -94,7 +92,6 @@ export type AnswerFor<Question extends EvaluationQuestion> = Question extends {
readonly type: "choice"
readonly choice: Extract<keyof Criteria, string>
readonly probabilities?: Readonly<Record<Extract<keyof Criteria, string>, number>>
readonly confidence?: number
}
: Question extends { readonly type: "score" }
? ScoreAnswer
+5 -10
View File
@@ -142,37 +142,32 @@ export const model = <Options extends EvaluationOptions = EvaluationOptions>(cfg
Effect.mapError((cause) => fail("System One returned an invalid response", cause, text)),
)
const confidence: Record<string, number> = {}
const legend: Record<string, Record<string, Schema.Json>> = {}
const answers = Object.fromEntries(
Object.entries(data.answers).map(([id, answer]): [string, EvaluationAnswer] => {
if (answer.type === "noul") return [id, { type: "boolean", probability: answer.noul }]
if (answer.type === "choice") {
if (answer.confidence !== undefined) confidence[id] = answer.confidence
return [
id,
{
type: "choice",
choice: answer.choice,
probabilities: answer.probabilities,
...(answer.confidence === undefined ? {} : { confidence: answer.confidence }),
},
]
}
if (answer.confidence !== undefined) confidence[id] = answer.confidence
if (answer.legend !== undefined) legend[id] = answer.legend
return [
id,
{
type: "score",
score: answer.score,
probabilities: answer.probabilities,
...(answer.confidence === undefined ? {} : { confidence: answer.confidence }),
},
]
return [id, { type: "score", score: answer.score, probabilities: answer.probabilities }]
}),
)
const meta = {
...(data.id === undefined ? {} : { responseId: data.id }),
...(data.provider === undefined ? {} : { provider: data.provider }),
...data.provider_metadata?.[cfg.providerMetadataKey],
...(Object.keys(confidence).length === 0 ? {} : { confidence }),
...(Object.keys(legend).length === 0 ? {} : { legend }),
}
return new EvaluationResponse({
+27 -58
View File
@@ -53,8 +53,6 @@ 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
@@ -83,7 +81,7 @@ export class Generation<Response> {
}
get terminal() {
return isTerminal(this.status)
return TERMINAL.has(this.status)
}
refresh(): Effect.Effect<Generation<Response>, AIError> {
@@ -102,7 +100,7 @@ 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: () => timeoutError(this.id, timeout) }),
Effect.timeoutOrElse({ duration: timeout, orElse: () => this.timeoutError(timeout) }),
)
}
@@ -111,10 +109,9 @@ export class Generation<Response> {
}
/**
* 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.)
* 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.)
*/
events(options?: AwaitOptions): Stream.Stream<Event, AIError> {
if (this.terminal) return Stream.make(this.event())
@@ -123,13 +120,17 @@ export class Generation<Response> {
Clock.currentTimeMillis.pipe(
Effect.map((start) => {
const deadline = start + Duration.toMillis(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)))),
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),
}),
),
),
)
return Stream.fromEffectSchedule(refresh, schedule).pipe(
return Stream.fromEffectSchedule(refresh, this.schedule(options?.poll)).pipe(
Stream.takeUntil((generation) => generation.terminal),
Stream.map((generation) => generation.event()),
)
@@ -144,6 +145,15 @@ 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 }),
@@ -155,53 +165,12 @@ 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> => {
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),
),
),
),
),
),
),
): 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))),
)
}
/**
* 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),
}),
})
+85 -16
View File
@@ -1,30 +1,99 @@
import { Context } from "effect"
import { MediaClient } from "./media-client.js"
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 {
ImageOutputEvent,
ImageFinishEvent,
responseEvents,
type ImageEvent,
type ImageModel,
type ImageOptions,
type ImageRequestFor,
type ImageResponse,
} from "./image.js"
export type Interface = MediaClient.Interface<ImageRequestFor, ImageEvent, ImageResponse>
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 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,
...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,
}),
],
}),
layer,
generate,
stream,
start,
resume,
} as const
+65 -14
View File
@@ -1,8 +1,9 @@
import { Effect, Schema, Stream } from "effect"
import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
import { Media } from "./media.js"
import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
import { MediaModel, composeAnyRoute, 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"
@@ -10,39 +11,75 @@ import { ImageClient, Service } from "./image-client.js"
// Model
// ---------------------------------------------------------------------------
export type ImageOptions = MediaModel.Options
export type ImageOptions = Record<string, unknown>
export type ImageRoute = MediaRoute.AnyRoute<ImageRequestFor, ImageEvent, ImageResponse>
export type ImageRoute<Options extends ImageOptions = ImageOptions> = MediaRoute.AnyRoute<
ImageRequestFor<Options>,
ImageEvent,
ImageResponse
>
export class ImageModel<Options extends ImageOptions = ImageOptions> extends MediaModel<ImageRoute, Options> {
export class ImageModel<Options extends ImageOptions = ImageOptions> extends MediaModel<ImageRoute<Options>, 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: MediaModel.InlineRouteInput<ImageRequestFor<Options>, ImageResponse>,
route: ImageModel.InlineRouteInput<Options>,
input: MediaRoute.ModelInput,
): ImageModel<Options>
static fromRoute<Options extends ImageOptions, Frame, State>(
route: MediaModel.StreamRouteInput<ImageRequestFor<Options>, ImageEvent, Frame, State>,
route: ImageModel.StreamRouteInput<Options, Frame, State>,
input: MediaRoute.ModelInput,
): ImageModel<Options>
static fromRoute<Options extends ImageOptions, Token>(
route: MediaModel.QueuedRouteInput<ImageRequestFor<Options>, ImageResponse, Token>,
route: ImageModel.QueuedRouteInput<Options, Token>,
input: MediaRoute.ModelInput,
): ImageModel<Options>
static fromRoute<Options extends ImageOptions, Frame, State, Token>(
route: MediaModel.AnyRouteInput<ImageRequestFor<Options>, ImageEvent, ImageResponse, Frame, State, Token>,
route: ImageModel.RouteInput<Options, Frame, State, Token>,
input: MediaRoute.ModelInput,
) {
return new ImageModel<Options>({
id: input.id,
provider: route.protocol.provider,
http: input.http,
route: composeRoute(route, input, collectResponse) as ImageRoute,
route: composeAnyRoute(route, input, collectResponse),
})
}
}
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",
})
@@ -153,6 +190,15 @@ 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.
@@ -186,31 +232,36 @@ export function request(input: ImageRequest | ImageRequestInput) {
const requestEffect = (input: ImageRequest | ImageRequestInput) => tryRequest(() => request(input))
export function generate<const Model extends ImageModel>(
input: ImageRequest | ImageRequestInput<Model>,
input: 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: ImageRequest | ImageRequestInput<Model>,
input: 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: ImageRequest | ImageRequestInput<Model>,
input: 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 = (model: ImageModel, token: unknown): Effect.Effect<Generation<ImageResponse>, AIError, Service> =>
ImageClient.resume(model, token)
export const resume = <Options extends ImageOptions>(
model: ImageModel<Options>,
token: unknown,
): Effect.Effect<Generation<ImageResponse>, AIError, Service> => ImageClient.resume(model, token)
export const Image = {
request,
+1 -1
View File
@@ -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, isRetryable } from "./provider-error.js"
export { isContextOverflow, isContextOverflowFailure } from "./provider-error.js"
export type {
RouteLanguageModelInput,
RouteRoutedLanguageModelInput,
+4 -22
View File
@@ -1,6 +1,5 @@
import { Effect, JsonSchema, Schema, Stream } from "effect"
import { tryRequest } from "./media-model.js"
import { LLMClient, Service, type StreamOptions } from "./route/client.js"
import { Effect, JsonSchema, Schema } from "effect"
import { LLMClient, Service } from "./route/client.js"
import {
GenerationOptions,
HttpOptions,
@@ -36,26 +35,9 @@ export type RequestInput<SelectedLanguageModel extends LanguageModel = LanguageM
readonly http?: HttpOptions.Input
}
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 generate = LLMClient.generate
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 stream = LLMClient.stream
export const request = <const SelectedLanguageModel extends LanguageModel>(
input: RequestInput<SelectedLanguageModel>,
-77
View File
@@ -1,77 +0,0 @@
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"
+30 -42
View File
@@ -6,13 +6,11 @@ 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`, `TranscriptionModel`) extend it with their route type and a nominal
* marker so one cannot stand in for the other in requests.
* (`ImageModel`, `VideoModel`, `SpeechModel`) 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> {
// 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
declare protected readonly _Options: (options: Options) => Options
readonly id: ModelID
readonly provider: ProviderID
readonly route: Route
@@ -27,8 +25,6 @@ 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
@@ -45,56 +41,48 @@ 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> =
| InlineRouteInput<Request, Response>
| StreamRouteInput<Request, Event, Frame, State>
| QueuedRouteInput<Request, Response, Token>
| RouteInput<Request, MediaProtocol.Inline<Request, Response>>
| RouteInput<MediaProtocol.Addressed<Request>, MediaProtocol.Streamed<Request, Event, Frame, State>>
| RouteInput<Request, MediaProtocol.Queued<Request, Response, Token>>
}
/** Compose a protocol route input with one deployment through `MediaRoute.inline`, `queued`, or `stream`. */
export const composeRoute = <Request extends MediaRoute.MediaRequest, Event, Response, Frame, State, Token>(
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>(
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 MediaRoute.stream({ ...composition(route, input), collect })
if (isQueuedInput(route)) return MediaRoute.queued(composition(route, input))
return MediaRoute.inline(composition(route, input))
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)
}
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.StreamRouteInput<Request, Event, Frame, State> => route.protocol.kind === "stream"
): route is MediaModel.RouteInput<
MediaProtocol.Addressed<Request>,
MediaProtocol.Streamed<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.QueuedRouteInput<Request, Response, Token> => route.protocol.kind === "queued"
): route is MediaModel.RouteInput<Request, MediaProtocol.Queued<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> =>
+39 -27
View File
@@ -1,22 +1,23 @@
import { Effect, Layer, ManagedRuntime, Stream } from "effect"
import { AIClient } from "./ai-client.js"
import type { AwaitOptions, Event, Generation, Snapshot } from "./generation.js"
import { Image, type ImageModel, type ImageRequest, type ImageRequestInput } from "./image.js"
import { Image, ImageModel, ImageRequest, type ImageOptions, 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, type SpeechModel, type SpeechRequest, type SpeechRequestInput } from "./speech.js"
import { Speech, SpeechModel, SpeechRequest, type SpeechRequestInput } from "./speech.js"
import {
Transcription,
type TranscriptionModel,
type TranscriptionRequest,
TranscriptionModel,
TranscriptionRequest,
type TranscriptionOptions,
type TranscriptionRequestInput,
} from "./transcription.js"
import { fileMediaType } from "./utils/media-type.js"
import { Video, type VideoModel, type VideoRequest, type VideoRequestInput } from "./video.js"
import { Video, VideoModel, VideoRequest, type VideoOptions, type VideoRequestInput } from "./video.js"
/**
* Promise-first entrypoint for scripts and non-Effect callers. One `ManagedRuntime` hosts the LLM, image, video, speech,
@@ -42,7 +43,7 @@ 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 throws `signal.reason`. */
/** Status observations until the first terminal one, polling like `await`; abort ends iteration without throwing. */
readonly events: (options?: AwaitOptions & RunOptions) => AsyncIterable<Event>
/** The result without polling; fails when the generation has not completed. */
readonly result: (options?: RunOptions) => Promise<Response>
@@ -50,16 +51,15 @@ 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<never, unknown>((resume) => {
: Effect.callback<void>((resume) => {
if (signal.aborted) {
resume(Effect.fail(signal.reason))
resume(Effect.void)
return
}
const onAbort = () => resume(Effect.fail(signal.reason))
const onAbort = () => resume(Effect.void)
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.raceFirst(effect, abortEffect(options?.signal)))
runtime.runPromise(effect, { signal: 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, unknown> =>
(context): Stream.Stream<A, E> =>
stream.pipe(Stream.interruptWhen(abortEffect(options?.signal)), Stream.provideContext(context)),
),
),
@@ -93,8 +93,17 @@ 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,
@@ -146,58 +155,61 @@ export const make = (options: Options = {}) => {
generate: <const Model extends ImageModel>(
input: ImageRequestInput<Model> | ImageRequest,
options?: AwaitOptions & RunOptions,
) => run(Image.generate(input, { poll: options?.poll }), options),
) => run(Image.generate(imageRequest(input), { poll: options?.poll }), options),
stream: <const Model extends ImageModel>(
input: ImageRequestInput<Model> | ImageRequest,
options?: AwaitOptions & RunOptions,
) => iterate(Image.stream(input, { poll: options?.poll }), options),
) => iterate(Image.stream(imageRequest(input), { poll: options?.poll }), options),
start: <const Model extends ImageModel>(input: ImageRequestInput<Model> | ImageRequest, options?: RunOptions) =>
run(Image.start(input), options).then(handle),
resume: (model: ImageModel, token: unknown, options?: RunOptions) =>
run(Image.start(imageRequest(input)), options).then(handle),
resume: <Options extends ImageOptions>(model: ImageModel<Options>, 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(input), options).then(handle),
run(Video.start(videoRequest(input)), options).then(handle),
generate: <const Model extends VideoModel>(
input: VideoRequestInput<Model> | VideoRequest,
options?: AwaitOptions & RunOptions,
) => run(Video.generate(input, { poll: options?.poll }), options),
resume: (model: VideoModel, token: unknown, options?: RunOptions) =>
) => run(Video.generate(videoRequest(input), { poll: options?.poll }), options),
resume: <Options extends VideoOptions>(model: VideoModel<Options>, 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(input, { poll: options?.poll }), options),
) => iterate(Video.stream(videoRequest(input), { poll: options?.poll }), options),
},
speech: {
request: Speech.request,
generate: <const Model extends SpeechModel>(
input: SpeechRequestInput<Model> | SpeechRequest,
options?: RunOptions,
) => run(Speech.generate(input), options),
) => run(Speech.generate(speechRequest(input)), options),
stream: <const Model extends SpeechModel>(
input: SpeechRequestInput<Model> | SpeechRequest,
options?: RunOptions,
) => iterate(Speech.stream(input), options),
) => iterate(Speech.stream(speechRequest(input)), options),
},
transcription: {
request: Transcription.request,
generate: <const Model extends TranscriptionModel>(
input: TranscriptionRequestInput<Model> | TranscriptionRequest,
options?: AwaitOptions & RunOptions,
) => run(Transcription.generate(input, { poll: options?.poll }), options),
) => run(Transcription.generate(transcriptionRequest(input), { poll: options?.poll }), options),
stream: <const Model extends TranscriptionModel>(
input: TranscriptionRequestInput<Model> | TranscriptionRequest,
options?: AwaitOptions & RunOptions,
) => iterate(Transcription.stream(input, { poll: options?.poll }), options),
) => iterate(Transcription.stream(transcriptionRequest(input), { poll: options?.poll }), options),
start: <const Model extends TranscriptionModel>(
input: TranscriptionRequestInput<Model> | TranscriptionRequest,
options?: RunOptions,
) => run(Transcription.start(input), options).then(handle),
resume: (model: TranscriptionModel, token: unknown, options?: RunOptions) =>
run(Transcription.resume(model, token), options).then(handle),
) => 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),
},
dispose: () => runtime.dispose(),
}
+1 -5
View File
@@ -70,11 +70,7 @@ export const protocol = Protocol.make({
return {
...(yield* OpenAIChat.protocol.body.from(req)),
enable_thinking: opts.enableThinking,
// Alibaba also rejects an explicit budget that is not below `max_completion_tokens`.
thinking_budget:
opts.thinkingBudget === undefined
? undefined
: ProviderShared.fitThinkingBudget(opts.thinkingBudget, req.generation?.maxTokens),
thinking_budget: opts.thinkingBudget,
preserve_thinking: opts.preserveThinking,
clear_thinking: opts.clearThinking,
thinking: opts.thinking,
@@ -26,21 +26,18 @@ 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 {
...body,
...(yield* AnthropicMessages.protocol.body.from(
LLMRequest.update(req, {
providerOptions: { ...req.providerOptions, thinking: undefined },
}),
)),
thinking:
opts.thinking === undefined
? undefined
: {
type: opts.thinking.type,
budget_tokens:
budget === undefined ? undefined : ProviderShared.fitThinkingBudget(budget, body.max_tokens),
budget_tokens: opts.thinking.budgetTokens ?? opts.thinking.budget_tokens,
},
}
}),
+30 -18
View File
@@ -18,6 +18,7 @@ import {
type CacheHint,
type FinishReasonDetails,
type FinishReason,
type JsonSchema,
type MediaPart,
type ProviderMetadata,
type ProviderOptions,
@@ -29,15 +30,14 @@ import { JsonObject, knownString, optionalArray, optionalNull, ProviderShared }
import { classifyProviderFailure } from "../provider-error.js"
import { effortUpdate, resolveEffortUpdates } from "../effort-updates.js"
import * as Cache from "./utils/cache.js"
import { claudeVersion, supportsThinkingBlockBinding, THINKING_BINDING_BETA } from "./utils/claude-model.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 +524,10 @@ const redactedDataFromMetadata = (metadata: ProviderMetadata | undefined, key: s
return typeof provider.redactedData === "string" ? provider.redactedData : undefined
}
const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition): AnthropicTool => ({
const lowerTool = (breakpoints: Cache.Breakpoints, tool: ToolDefinition, inputSchema: JsonSchema): AnthropicTool => ({
name: tool.name,
description: tool.description,
input_schema: tool.inputSchema,
input_schema: inputSchema,
cache_control: cacheControl(breakpoints, tool.cache),
})
@@ -989,6 +989,22 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
return messages
})
// Accept gateway namespaces and Vertex suffixes without treating a snapshot date as a minor version.
const claudeVersion = (id: string) => {
const match = /(?:^|[./])claude-(?<family>[a-z]+)-(?<major>\d+)(?:[.-](?<minor>\d{1,2}))?(?:$|[-:@])/.exec(
id.toLowerCase(),
)?.groups
if (!match) return undefined
return { family: match.family, major: Number(match.major), minor: Number(match.minor ?? 0) }
}
const supportsThinkingBlockBinding = (model: LLMRequest["model"]) => {
const override = model.compatibility?.supportsThinkingBlockBinding
if (override !== undefined) return override
const version = claudeVersion(model.id)
return version !== undefined && (version.major > 5 || (version.major === 5 && version.minor >= 1))
}
const supportsEffortUpdates = (model: LLMRequest["model"]) => {
const override = model.compatibility?.supportsEffortUpdates
if (override !== undefined) return override
@@ -1011,15 +1027,6 @@ 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
@@ -1032,7 +1039,12 @@ 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))
const tools =
flattened.tools.length === 0
? undefined
: flattened.tools.map((tool) =>
lowerTool(breakpoints, tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model)),
)
// 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)
@@ -1052,7 +1064,6 @@ 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,
@@ -1060,12 +1071,12 @@ const fromRequest = Effect.fn("AnthropicMessages.fromRequest")(function* (reques
tools,
tool_choice: toolChoice,
stream: true as const,
max_tokens: maxTokens,
max_tokens: generation?.maxTokens ?? DEFAULT_MAX_TOKENS,
temperature: generation?.temperature,
top_p: generation?.topP,
top_k: generation?.topK,
stop_sequences: generation?.stop,
thinking: applyThinkingBindingDefault(request.model, fitThinking(options.thinking, maxTokens)),
thinking: applyThinkingBindingDefault(request.model, options.thinking),
output_config,
// top-level passthrough per SDK MessageCreateParamsBase:4638,4643,4649,4654,4670
cache_control: options.cache_control ?? options.cacheControl,
@@ -1637,7 +1648,8 @@ function requiredBetaHeaders(body: Pick<AnthropicMessagesBody, "messages" | "con
betas.push("mid-conversation-output-config-2026-07-01")
const thinking = body.thinking
if (thinking && thinking.type !== "disabled" && thinking.block_binding) betas.push(THINKING_BINDING_BETA)
if (thinking && thinking.type !== "disabled" && thinking.block_binding)
betas.push("thinking-binding-controls-2026-08-01")
return betas
}
@@ -110,11 +110,8 @@ 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, and `speakers_expected` require speaker labels.
speaker_labels:
request.diarize === true || request.timestamps === "segment" || request.speakers !== undefined
? true
: undefined,
// Turn-level `utterances`, the only segments AssemblyAI returns, require speaker labels.
speaker_labels: request.diarize === true || request.timestamps === "segment" ? true : undefined,
speakers_expected: request.speakers,
},
request.providerOptions,
@@ -158,7 +155,8 @@ 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 ? "" : `: ${error}`}`)
if (status !== "completed") return yield* output.pending(context.token.transcriptID)
if (status !== "completed")
return yield* output.invalid(`${route.name} transcript ${context.token.transcriptID} has not finished`)
const duration = transcript.audio_duration ?? undefined
return new TranscriptionResponse({
text: transcript.text ?? "",
+23 -80
View File
@@ -9,6 +9,7 @@ import {
type CacheHint,
type FinishReason,
type FinishReasonDetails,
type JsonSchema,
type LLMRequest,
type LanguageModel,
type ProviderMetadata,
@@ -23,9 +24,9 @@ import { JsonObject, optionalArray, ProviderShared } from "./shared.js"
import { BedrockAuth } from "./utils/bedrock-auth.js"
import { BedrockCache } from "./utils/bedrock-cache.js"
import { BedrockMedia } from "./utils/bedrock-media.js"
import { supportsThinkingBlockBinding, THINKING_BINDING_BETA } from "./utils/claude-model.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"
@@ -220,18 +221,22 @@ type BedrockEvent = Schema.Schema.Type<typeof BedrockEvent>
// =============================================================================
// Request Lowering
// =============================================================================
const lowerToolSpec = (tool: ToolDefinition): BedrockToolSpec => ({
const lowerToolSpec = (tool: ToolDefinition, inputSchema: JsonSchema): BedrockToolSpec => ({
toolSpec: {
name: tool.name,
...(tool.description.trim().length > 0 ? { description: tool.description } : {}),
inputSchema: { json: tool.inputSchema },
inputSchema: { json: inputSchema },
},
})
const lowerTools = (breakpoints: BedrockCache.Breakpoints, tools: ReadonlyArray<ToolDefinition>): BedrockTool[] => {
const lowerTools = (
model: LanguageModel,
breakpoints: BedrockCache.Breakpoints,
tools: ReadonlyArray<ToolDefinition>,
): BedrockTool[] => {
const result: BedrockTool[] = []
for (const tool of tools) {
result.push(lowerToolSpec(tool))
result.push(lowerToolSpec(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, model)))
const cachePoint = BedrockCache.block(breakpoints, tool.cache)
if (cachePoint) result.push(cachePoint)
}
@@ -436,58 +441,19 @@ 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 isThinkingDisabled = Schema.is(
Schema.Struct({
additionalModelRequestFields: Schema.Struct({ thinking: Schema.Struct({ type: Schema.Literal("disabled") }) }),
}),
)
// Claude 5.1+ binds each thinking signature to the prefix above it. Ask Bedrock to drop the affected blocks instead of
// failing when that prefix changes. `http.body` overlays this field by field, so callers can still override it.
const applyThinkingBindingDefault = (request: LLMRequest, thinking: Readonly<Record<string, unknown>> | undefined) => {
if (isThinkingDisabled(request.http?.body)) return thinking
if (!supportsThinkingBlockBinding(request.model)) return thinking
return {
...(thinking ?? { type: "adaptive" as const }),
block_binding: { prefix_mismatch_behavior: "drop_block" },
}
}
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 = applyThinkingBindingDefault(
request,
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(breakpoints, flattened.tools),
tools: lowerTools(request.model, breakpoints, flattened.tools),
// Converse has no native "none". Keep definitions stable for prompt
// caching and omit only the unsupported choice.
toolChoice,
@@ -521,17 +487,9 @@ const fromRequest = Effect.fn("BedrockConverse.fromRequest")(function* (request:
system,
inferenceConfig,
toolConfig,
// 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 }),
// Converse takes Anthropic betas in the body, and Bedrock rejects `block_binding` without this one.
...(thinking?.block_binding === undefined ? {} : { anthropic_beta: [THINKING_BINDING_BETA] }),
},
// 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 },
}
})
@@ -577,7 +535,7 @@ interface ParserState {
readonly hasToolCalls: boolean
readonly lifecycle: Lifecycle.State
readonly reasoningSignatures: Readonly<Record<number, string>>
readonly reasoningRedactedContent: Readonly<Record<number, Uint8Array[]>>
readonly reasoningRedactedContent: Readonly<Record<number, ReadonlyArray<Uint8Array>>>
}
const encodeRedactedContent = (chunks: ReadonlyArray<Uint8Array>) => Encoding.encodeBase64(concatBytes(chunks))
@@ -627,9 +585,10 @@ const step = (state: ParserState, event: BedrockEvent) =>
const index = event.contentBlockDelta.contentBlockIndex
const reasoning = event.contentBlockDelta.delta.reasoningContent
const events: LLMEvent[] = []
const redactedChunk = yield* (() => {
const redactedChunks = yield* (() => {
if (reasoning.redactedContent === undefined) return Effect.succeed(undefined)
return Effect.fromResult(Encoding.decodeBase64(reasoning.redactedContent)).pipe(
Effect.map((chunk) => [...(state.reasoningRedactedContent[index] ?? []), chunk]),
Effect.mapError((cause) =>
ProviderShared.eventError(
ADAPTER,
@@ -640,21 +599,17 @@ const step = (state: ParserState, event: BedrockEvent) =>
),
)
})()
const redactedChunks = state.reasoningRedactedContent[index] ?? []
if (redactedChunk !== undefined) redactedChunks.push(redactedChunk)
const redactedData = redactedChunks === undefined ? reasoning.data : encodeRedactedContent(redactedChunks)
const metadata = (() => {
if (reasoning.signature) return providerMetadata(state.providerMetadataKey, { signature: reasoning.signature })
if (redactedChunk === undefined && reasoning.data !== undefined)
return providerMetadata(state.providerMetadataKey, { redactedData: reasoning.data })
if (redactedData !== undefined) return providerMetadata(state.providerMetadataKey, { redactedData })
})()
const lifecycle = (() => {
if (reasoning.text !== undefined || metadata !== undefined)
return Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text ?? "", metadata)
if (redactedChunk !== undefined) return Lifecycle.reasoningStart(state.lifecycle, events, `reasoning-${index}`)
return state.lifecycle
if (reasoning.text === undefined && metadata === undefined) return state.lifecycle
return Lifecycle.reasoningDelta(state.lifecycle, events, `reasoning-${index}`, reasoning.text ?? "", metadata)
})()
const reasoningRedactedContent = (() => {
if (redactedChunk !== undefined) return { ...state.reasoningRedactedContent, [index]: redactedChunks }
if (redactedChunks !== undefined) return { ...state.reasoningRedactedContent, [index]: redactedChunks }
if (reasoning.data === undefined) return state.reasoningRedactedContent
return Object.fromEntries(
Object.entries(state.reasoningRedactedContent).filter(([key]) => key !== String(index)),
@@ -790,19 +745,7 @@ const onHalt = (state: ParserState): ReadonlyArray<LLMEvent> => {
return state.finishReason.normalized
})()
const events: LLMEvent[] = []
const lifecycle = Object.entries(state.reasoningRedactedContent).reduce((current, [index, chunks]) => {
const signature = state.reasoningSignatures[Number(index)]
return Lifecycle.reasoningEnd(
current,
events,
`reasoning-${index}`,
providerMetadata(
state.providerMetadataKey,
signature ? { signature } : { redactedData: encodeRedactedContent(chunks) },
),
)
}, state.lifecycle)
Lifecycle.finish(lifecycle, events, {
Lifecycle.finish(state.lifecycle, events, {
reason: {
...state.finishReason,
normalized,
+6 -20
View File
@@ -31,21 +31,13 @@ export type Request = ImageRequestFor<BlackForestLabsImageOptions>
// 2. Token and response schemas
// ---------------------------------------------------------------------------
/**
* Regional clusters answer on different hosts, so the returned `polling_url` is followed verbatim. BFL reports the
* credit cost on submit, so it rides on the token; it is optional so tokens persisted before it existed still decode.
*/
export const Token = Schema.Struct({
id: Schema.String,
pollingURL: Schema.String,
cost: Schema.optionalKey(Schema.Number),
})
/** Regional clusters answer on different hosts, so the returned `polling_url` is followed verbatim. */
export const Token = Schema.Struct({ id: Schema.String, pollingURL: Schema.String })
export type Token = Schema.Schema.Type<typeof Token>
const StartResponse = Schema.Struct({
id: Schema.String,
polling_url: Schema.String,
cost: optionalNull(Schema.Number),
})
const Result = Schema.Struct({
@@ -153,11 +145,7 @@ const fromRequest = Effect.fn("BlackForestLabsImages.fromRequest")(function* (re
// ---------------------------------------------------------------------------
const decodeStart = route.decodeStarted(StartResponse, (value) => ({
token: {
id: value.id,
pollingURL: value.polling_url,
...(value.cost === undefined || value.cost === null ? {} : { cost: value.cost }),
},
token: { id: value.id, pollingURL: value.polling_url },
snapshot: { id: value.id, status: "queued" },
}))
@@ -181,16 +169,14 @@ const decodeResult = Effect.fn("BlackForestLabsImages.decodeResult")(function* (
if (isModerated(document.status)) return yield* output.contentPolicy(`${route.name} moderated the generation`)
if (status === "failed" || status === "expired")
return yield* output.ended(status, `${route.name} generation ${context.token.id} ended with ${document.status}`)
if (status !== "completed") return yield* output.pending(context.token.id)
if (document.result === undefined || document.result === null)
if (status !== "completed" || document.result === undefined || document.result === null)
return yield* output.invalid(`${route.name} generation ${context.token.id} has no result`)
const { sample, seed, prompt, ...rest } = document.result
// A settled `cost` on the result supersedes the submit-time cost carried on the token.
const cost = document.cost ?? context.token.cost
return new ImageResponse({
// `sample` is a signed URL that expires 10 minutes after the result is ready, so it is downloaded now.
images: [yield* context.materialize(Media.url(sample))],
usage: cost === undefined ? undefined : { type: "credits", credits: cost },
usage:
document.cost === undefined || document.cost === null ? undefined : { type: "credits", credits: document.cost },
providerMetadata: {
bfl: { id: context.token.id, seed: seed ?? undefined, prompt: prompt ?? undefined, ...rest },
},
+9 -20
View File
@@ -67,9 +67,6 @@ const queryParameters = (request: Request) => {
}
const fromRequest = Effect.fn("DeepgramSpeech.fromRequest")(function* (request: Request) {
// Not in `unsupported`: that list would also reject `timestamps: false`, which asks for nothing.
if (request.timestamps === true)
return yield* route.unsupported("media.timestamps", `${route.name} does not return timestamps`)
if (
request.format !== undefined &&
FORMATS[request.format] === undefined &&
@@ -89,32 +86,24 @@ const fromRequest = Effect.fn("DeepgramSpeech.fromRequest")(function* (request:
// 6. Stream parsing
// ---------------------------------------------------------------------------
/** 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 HEADERLESS_ENCODINGS: Readonly<Record<string, SpeechStream.PcmEncoding>> = {
linear16: "pcm_s16le",
mulaw: "pcm_mulaw",
alaw: "pcm_alaw",
}
const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) => {
const headers = context.http.headers
const mediaType = headers["content-type"]
const format = audioFormat(context.request)
const headerless = HEADERLESS_ENCODINGS[format.encoding ?? ""]
const container = format.container ?? (headerless === undefined ? undefined : "wav")
const encoding = HEADERLESS_ENCODINGS[format.encoding ?? ""]
const requestID = headers["dg-request-id"]
const modelName = headers["dg-model-name"]
return SpeechStream.finish(route, state, {
...(container === "none" && headerless !== undefined
? SpeechStream.pcm(
headerless.encoding,
SpeechStream.sampleRate(mediaType) ?? context.request.providerOptions?.sampleRate ?? headerless.sampleRate,
mediaType,
)
...(format.container === "none" && encoding !== undefined
? SpeechStream.pcm(encoding, SpeechStream.sampleRate(mediaType), mediaType)
: // Deepgram's default encoding is MP3; WAV is a container around any encoding.
{ mediaType, info: { format: container === "wav" ? "wav" : (format.encoding ?? "mp3") } }),
{ mediaType, info: { format: format.container === "wav" ? "wav" : (format.encoding ?? "mp3") } }),
usage: SpeechStream.headerUsage("characters", headers["dg-char-count"]),
providerMetadata:
requestID === undefined && modelName === undefined
@@ -128,7 +117,7 @@ const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) =
// ---------------------------------------------------------------------------
export const protocol = MediaProtocol.stream<Request, SpeechEvent, Uint8Array, State>(route, {
unsupported: ["voice", "language", "instructions"],
unsupported: ["voice", "language", "instructions", "timestamps"],
body: { from: fromRequest },
frames: (bytes) => bytes,
initial: () => ({ chunks: [] }),
@@ -6,7 +6,6 @@ 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"
@@ -116,6 +115,16 @@ 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,
) {
@@ -127,8 +136,6 @@ 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
? [
@@ -139,7 +146,7 @@ const decodeResponse = Effect.fn("DeepgramTranscription.decodeResponse")(functio
speaker: speaker(utterance.speaker),
},
]
: SpeakerTurns.group(utterance.words, (word) => word.speaker).map((turn) => ({
: speakerTurns(utterance.words).map((turn) => ({
text: turn.map(wordText).join(" "),
startSeconds: turn[0].start,
endSeconds: turn[turn.length - 1].end,
@@ -1,211 +0,0 @@
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
+14 -20
View File
@@ -49,7 +49,7 @@ const QueueResult = Schema.StructWithRest(
// ---------------------------------------------------------------------------
const sizing = (model: string) => {
if (/^fal-ai\/(nano-banana|flux-pro\/(v1\.1-ultra|kontext))/.test(model)) return "aspect_ratio"
if (/^fal-ai\/(nano-banana|flux-pro\/v1\.1-ultra)/.test(model)) return "aspect_ratio"
if (model.startsWith("fal-ai/flux")) return "image_size"
return undefined
}
@@ -63,24 +63,20 @@ 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 && !takesImageList(id))
if ((request.images?.length ?? 0) > 1 && !isEdit(id))
return Effect.fail(
route.unsupported(
"media.images",
`${id} takes one image_url; use an /edit or /multi endpoint for several images`,
),
route.unsupported("media.images", `${id} takes one image_url; use an /edit endpoint for several images`),
)
return Effect.void
}
// `/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")
// `/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")
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 list = takesImageList(request.model.id)
const edit = isEdit(request.model.id)
return MediaProtocol.json(
mergeJsonRecords(
{
@@ -90,8 +86,8 @@ 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: list && images.length > 0 ? images : undefined,
image_url: list ? undefined : images[0],
image_urls: edit && images.length > 0 ? images : undefined,
image_url: edit ? undefined : images[0],
mask_url: request.mask === undefined ? undefined : yield* FalQueue.mediaUrl(request.mask, route.name),
},
request.providerOptions,
@@ -116,14 +112,12 @@ 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) => {
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 })
)
}),
images: images.map((image) =>
Media.url(image.url, {
mediaType: image.content_type ?? undefined,
info: { width: image.width ?? undefined, height: image.height ?? undefined },
}),
),
notices:
flagged.length === 0
? undefined
+21 -22
View File
@@ -11,6 +11,7 @@ import {
Usage,
type FinishReason,
type LLMRequest,
type LanguageModel,
type MediaPart,
type ProviderMetadata,
type ProviderOptions,
@@ -23,12 +24,11 @@ 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
@@ -268,11 +268,12 @@ interface ParserState {
// =============================================================================
// Request Lowering
// =============================================================================
// Tool schemas go in `parametersJsonSchema`, which accepts standard JSON Schema.
const lowerTool = (tool: ToolDefinition) => ({
// 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) => ({
name: tool.name,
description: tool.description,
parametersJsonSchema: tool.inputSchema,
parametersJsonSchema: ToolSchemaProjection.modelCompatibility(tool.inputSchema, model, "gemini"),
})
const lowerToolConfig = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
@@ -451,22 +452,10 @@ 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,
thinkingBudget:
options.thinkingConfig.thinkingBudget === undefined
? undefined
: ProviderShared.fitThinkingBudget(
options.thinkingConfig.thinkingBudget,
generation?.maxTokens,
MIN_THINKING_BUDGET,
),
},
: { ...options.thinkingConfig, includeThoughts: options.thinkingConfig.includeThoughts ?? true },
}
return {
@@ -479,7 +468,7 @@ const fromRequest = Effect.fn("Gemini.fromRequest")(function* (request: LLMReque
tools: hasTools
? [
{
functionDeclarations: flattened.tools.map(lowerTool),
functionDeclarations: flattened.tools.map((tool) => lowerTool(tool, request.model)),
},
]
: undefined,
@@ -526,7 +515,19 @@ 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 (GeminiGenerateContent.contentFiltered(finishReason)) return "content-filter"
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 (
finishReason === "MALFORMED_FUNCTION_CALL" ||
finishReason === "UNEXPECTED_TOOL_CALL" ||
@@ -803,8 +804,6 @@ 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) => ({
+1 -1
View File
@@ -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(
"media.n",
"image.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) =>
+6 -27
View File
@@ -56,18 +56,10 @@ 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 accepts raw PCM as an explicit format; omit it to accept the provider's default output`,
`${route.name} only returns raw PCM; request format "pcm" or omit it, then wrap the samples yourself`,
)
const voiceName = SpeechStream.voiceID(request.voice)
return MediaProtocol.json(
@@ -102,29 +94,16 @@ const step = Effect.fn("GoogleSpeech.step")(function* (state: State, frame: stri
part.inlineData === undefined ? [] : [part.inlineData],
)
const next: State = { ...GeminiGenerateContent.track(state, chunk), mimeType: state.mimeType ?? audio[0]?.mimeType }
const events = audio.flatMap((part) => SpeechStream.delta(next, part.data)[1])
const withheld = next.chunks.length === 0 ? GeminiGenerateContent.withheld(route.name, chunk, frame) : undefined
if (withheld !== undefined) return yield* withheld
return [next, events] as const
return [next, audio.flatMap((part) => SpeechStream.delta(next, part.data)[1])] as const
})
const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) => {
if (state.finishReason === undefined) return Effect.fail(route.incomplete())
const finish = (state: State) => {
const sampleRate = SpeechStream.sampleRate(state.mimeType) ?? DEFAULT_SAMPLE_RATE
const output =
state.mimeType?.split(";")[0]?.toLowerCase() === "audio/wav"
? SpeechStream.container("wav", sampleRate)
: SpeechStream.pcm("pcm_s16le", sampleRate, state.mimeType ?? `audio/L16;codec=pcm;rate=${sampleRate}`)
if (context.request.format === "pcm" && output.info.format !== "pcm")
return Effect.fail(
route.frameError(`Google Speech returned ${output.info.format} instead of the requested raw PCM`),
)
return SpeechStream.finish(route, state, {
...output,
...SpeechStream.pcm("pcm_s16le", sampleRate, state.mimeType ?? `audio/L16;codec=pcm;rate=${sampleRate}`),
usage: GeminiGenerateContent.usage(state.usage),
notices: GeminiGenerateContent.notices(route.name, state),
providerMetadata: GeminiGenerateContent.providerMetadata(state),
detail: `finish reason: ${state.finishReason}`,
detail: state.finishReason === undefined ? undefined : `finish reason: ${state.finishReason}`,
})
}
@@ -133,7 +112,7 @@ const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) =
// ---------------------------------------------------------------------------
export const protocol = MediaProtocol.stream<Request, SpeechEvent, string, State>(route, {
unsupported: ["instructions", "speed"],
unsupported: ["instructions", "speed", "timestamps"],
body: { from: fromRequest },
frames: (bytes, context) => GeminiGenerateContent.frames(bytes, context.request.mode),
initial: () => ({ chunks: [] }),
@@ -154,9 +154,6 @@ 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 })),
@@ -172,7 +169,6 @@ 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),
}),
])
+3 -15
View File
@@ -36,9 +36,7 @@ const StartResponse = Schema.Struct({ name: Schema.String })
const Operation = Schema.Struct({
done: Schema.optional(Schema.Boolean),
error: Schema.optional(
Schema.Struct({ code: Schema.optional(Schema.Number), message: Schema.optional(Schema.String) }),
),
error: Schema.optional(Schema.Struct({ message: Schema.optional(Schema.String) })),
response: Schema.optional(
Schema.Struct({
generateVideoResponse: Schema.optional(
@@ -62,16 +60,6 @@ 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
// ---------------------------------------------------------------------------
@@ -161,12 +149,12 @@ 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.pending(context.token.operation)
if (status === "running")
return yield* output.invalid(`${route.name} operation ${context.token.operation} has not finished`)
if (status === "failed")
return yield* output.ended(
"failed",
`${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.
+7 -1
View File
@@ -5,6 +5,7 @@ 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"
@@ -102,7 +103,12 @@ 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)
if (tool.native === undefined)
return yield* OpenResponses.lowerTool(
NAME,
tool,
ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model),
)
return yield* ProviderShared.validateWith(Schema.decodeUnknownEffect(NativeTool))(tool.native.meta)
}),
),
+10 -3
View File
@@ -13,6 +13,7 @@ import {
UnknownProviderError,
Usage,
type FinishReasonDetails,
type JsonSchema,
type LLMRequest,
type MediaPart,
type ToolCallPart,
@@ -22,6 +23,7 @@ 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"
@@ -366,9 +368,9 @@ const lowerMessages = Effect.fn("MistralChat.lowerMessages")(function* (request:
return messages
})
const lowerTool = (tool: ToolDefinition): MistralTool => ({
const lowerTool = (tool: ToolDefinition, inputSchema: JsonSchema): MistralTool => ({
type: "function",
function: { name: tool.name, description: tool.description, parameters: tool.inputSchema, strict: false },
function: { name: tool.name, description: tool.description, parameters: inputSchema, strict: false },
})
export const fromRequest = Effect.fn("MistralChat.fromRequest")(function* (request: LLMRequest) {
@@ -394,7 +396,12 @@ 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(lowerTool) : undefined,
tools:
flattened.tools.length > 0
? flattened.tools.map((tool) =>
lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model)),
)
: undefined,
tool_choice: toolChoice,
stream: true as const,
max_tokens: request.generation?.maxTokens,
+16 -8
View File
@@ -8,6 +8,7 @@ import {
ProviderInternalError,
Usage,
type FinishReason,
type JsonSchema,
type LLMRequest,
type MediaPart,
type ProviderMetadata,
@@ -23,6 +24,7 @@ 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"
@@ -441,24 +443,23 @@ interface ReasoningStreamItem {
// =============================================================================
// Request Lowering
// =============================================================================
export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (protocolName: string, tool: ToolDefinition) {
export const lowerTool = Effect.fn("OpenResponses.lowerTool")(function* (
protocolName: string,
tool: ToolDefinition,
inputSchema: JsonSchema,
) {
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: tool.inputSchema,
parameters: 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,
@@ -820,7 +821,14 @@ export const fromRequestWithAdapter = Effect.fn("OpenResponses.fromRequestWithAd
return {
...(yield* lowerConversation(projected.request, adapter)),
...lowerGeneration(request),
tools: projected.tools.length === 0 ? undefined : yield* lowerTools(projected.tools, adapter),
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)),
),
tool_choice:
allowedToolChoice(request) ??
(request.toolChoice ? yield* lowerToolChoice(adapter.name, request.toolChoice) : undefined),
+26 -29
View File
@@ -17,6 +17,7 @@ import {
type FinishReason,
type FinishReasonDetails,
type CacheHint,
type JsonSchema,
type LLMRequest,
type MediaPart,
type ReasoningPart,
@@ -28,6 +29,7 @@ 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"
@@ -64,14 +66,6 @@ const OpenAIChatTool = Schema.Struct({
})
type OpenAIChatTool = Schema.Schema.Type<typeof OpenAIChatTool>
// Gemini's OpenAI-compatible surface carries thought signatures in tool call
// `extra_content` and rejects replayed parallel calls without them:
// https://ai.google.dev/gemini-api/docs/thinking#signatures
const ExtraContent = Schema.Struct({
google: Schema.Struct({ thought_signature: Schema.String }),
})
const decodeExtraContent = (value: unknown) => Option.getOrUndefined(Schema.decodeUnknownOption(ExtraContent)(value))
const OpenAIChatAssistantToolCall = Schema.Struct({
id: Schema.String,
type: Schema.tag("function"),
@@ -79,7 +73,6 @@ const OpenAIChatAssistantToolCall = Schema.Struct({
name: Schema.String,
arguments: Schema.String,
}),
extra_content: Schema.optional(ExtraContent),
})
type OpenAIChatAssistantToolCall = Schema.Schema.Type<typeof OpenAIChatAssistantToolCall>
@@ -121,6 +114,12 @@ const decodeReasoningDetail = Schema.decodeUnknownOption(ReasoningDetail)
const knownReasoningDetails = (details: ReadonlyArray<unknown>) =>
details.flatMap((detail) => Option.toArray(decodeReasoningDetail(detail)))
// Intentionally omit Gemini's provider-specific `extra_content.google.thought_signature`
// extension until direct Google OpenAI-compatible routing is supported here:
// https://github.com/vercel/ai/issues/11590
// https://github.com/vercel/ai/pull/11745
// https://ai.google.dev/gemini-api/docs/thought-signatures#openai
const OpenAIChatUserContent = Schema.Union([
Schema.Struct({
type: Schema.Literal("text"),
@@ -245,7 +244,6 @@ const OpenAIChatToolCallDelta = Schema.Struct({
index: optionalNull(Schema.Number),
id: optionalNull(Schema.String),
function: optionalNull(OpenAIChatToolCallDeltaFunction),
extra_content: optionalNull(Schema.Unknown),
})
type OpenAIChatToolCallDelta = Schema.Schema.Type<typeof OpenAIChatToolCallDelta>
@@ -298,7 +296,6 @@ interface PendingToolDelta {
readonly id?: string
readonly name?: string
readonly input: string
readonly extraContent?: Schema.Schema.Type<typeof ExtraContent>
}
export interface ParserState {
@@ -333,12 +330,17 @@ interface LoweringOptions {
readonly toolCallID?: (id: string) => string
}
const lowerTool = (tool: ToolDefinition, options: LoweringOptions, supportsStrictMode: boolean): OpenAIChatTool => ({
const lowerTool = (
tool: ToolDefinition,
inputSchema: JsonSchema,
options: LoweringOptions,
supportsStrictMode: boolean,
): OpenAIChatTool => ({
type: "function",
function: {
name: tool.name,
description: tool.description,
parameters: tool.inputSchema,
parameters: inputSchema,
...(supportsStrictMode ? { strict: false } : {}),
},
cache_control: options.cacheControl?.(tool.cache),
@@ -352,17 +354,13 @@ const lowerToolChoice = (toolChoice: NonNullable<LLMRequest["toolChoice"]>) =>
tool: (name) => ({ type: "function" as const, function: { name } }),
})
const lowerToolCall = (
part: ToolCallPart,
options: LoweringOptions & { readonly providerMetadataKey: string },
): OpenAIChatAssistantToolCall => ({
const lowerToolCall = (part: ToolCallPart, options: LoweringOptions): OpenAIChatAssistantToolCall => ({
id: options.toolCallID?.(part.id) ?? part.id,
type: "function",
function: {
name: part.name,
arguments: ProviderShared.encodeJson(part.input === undefined ? {} : part.input),
},
extra_content: decodeExtraContent(part.providerMetadata?.[options.providerMetadataKey]?.extraContent),
})
const lowerMedia = Effect.fn("OpenAIChat.lowerMedia")(function* (part: MediaPart) {
@@ -730,9 +728,7 @@ const detectSupportsStore = (provider: string, baseURL: string | undefined): boo
p === "vercel-ai-gateway" || url.includes("ai-gateway.vercel.sh") || url.includes("vercel.sh")
const isAntLing = p === "ant-ling" || url.includes("api.ant-ling.com")
const isOpencode = p === "opencode" || url.includes("opencode.ai")
const isGemini = url.includes("generativelanguage.googleapis.com")
const isNonStandard =
isGemini ||
isNvidia ||
isCerebras ||
isXai ||
@@ -829,7 +825,14 @@ export const fromRequest = Effect.fn("OpenAIChat.fromRequest")(function* (
? hasHistory
? []
: undefined
: flattened.tools.map((tool) => lowerTool(tool, options, supportsStrictMode)),
: flattened.tools.map((tool) =>
lowerTool(
tool,
ToolSchemaProjection.modelCompatibility(tool.inputSchema, request.model),
options,
supportsStrictMode,
),
),
tool_choice: hasActiveTools && request.toolChoice ? yield* lowerToolChoice(request.toolChoice) : undefined,
stream: true as const,
...(supportsUsageInStreaming ? { stream_options: { include_usage: true } } : {}),
@@ -1125,13 +1128,12 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
const id = current?.id ?? pending?.id ?? (tool.id || undefined)
const name = current?.name ?? pending?.name ?? (tool.function?.name || undefined)
const text = `${pending?.input ?? ""}${tool.function?.arguments ?? ""}`
const extraContent = pending?.extraContent ?? decodeExtraContent(tool.extra_content)
latestToolIndex = index
nextToolIndex = Math.max(nextToolIndex, index + 1)
if (!current && (!id || !name)) {
pendingTools = {
...pendingTools,
[index]: { id: id || undefined, name: name || undefined, input: text, extraContent },
[index]: { id: id || undefined, name: name || undefined, input: text },
}
continue
}
@@ -1143,12 +1145,7 @@ const step = (state: ParserState, event: OpenAIChatEvent) =>
ADAPTER,
tools,
index,
{
id: id || undefined,
name: name || undefined,
text,
providerMetadata: extraContent && { [state.providerMetadataKey]: { extraContent } },
},
{ id: id || undefined, name: name || undefined, text },
"OpenAI Chat tool call delta is missing id or name",
)
if (ToolStream.isError(result))
+24 -54
View File
@@ -48,17 +48,15 @@ const Usage = Schema.Struct({
output_tokens_details: Schema.optional(Schema.Record(Schema.String, Schema.Unknown)),
})
/** 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,
data: Schema.Array(
Schema.Struct({
b64_json: Schema.optional(Schema.String),
url: Schema.optional(Schema.String),
revised_prompt: Schema.optional(Schema.String),
}),
),
output_format: Schema.optional(Schema.String),
usage: Schema.optional(Usage),
})
@@ -71,13 +69,11 @@ 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),
}),
@@ -96,9 +92,6 @@ 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
}
@@ -117,6 +110,10 @@ 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}`),
@@ -197,34 +194,21 @@ const usage = (value: Schema.Schema.Type<typeof Usage> | undefined): MediaUsage
details: { openai: value },
}
/** `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+)$/)
return match ? { format, width: Number(match[1]), height: Number(match[2]) } : { format }
}
const eventImage = (frame: string, label: string, data: string, format: string, size: string | undefined) =>
const eventImage = (frame: string, label: string, data: string, format: string) =>
MediaInput.decodedAsset((message, cause) => route.frameError(message, frame, cause), label, data, `image/${format}`, {
info: info(format, size),
info: { format },
})
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, `${route.name} partial image`, event.b64_json, format, event.size)
const image = yield* eventImage(frame, `${route.name} partial image`, event.b64_json, format)
return [state, [ImagePartialEvent.make({ index: event.partial_image_index, image })]] as const
}
const image = yield* eventImage(frame, `${route.name} result ${state.completed}`, event.b64_json, format, event.size)
const image = yield* eventImage(frame, `${route.name} result ${state.completed}`, event.b64_json, format)
return [
{
completed: state.completed + 1,
format,
size: event.size,
quality: event.quality,
background: event.background,
usage: usage(event.usage),
},
{ ...state, completed: state.completed + 1, format, usage: usage(event.usage) },
[ImageOutputEvent.make({ index: state.completed, image })],
] as const
})
@@ -235,20 +219,16 @@ const onDocument = Effect.fn("OpenAIImages.onDocument")(function* (frame: Exclud
Effect.mapError((cause) => invalid(`${route.name} returned an invalid response`, cause)),
)
const format = decoded.output_format ?? frame.requested ?? "png"
const mediaType = `image/${format}`
const images = yield* Effect.forEach(decoded.data, (item, index) =>
MediaInput.decodedAsset(invalid, `${route.name} result ${index}`, item.b64_json, `image/${format}`, {
info: info(format, decoded.size),
MediaInput.imageOutput(invalid, `${route.name} result ${index}`, item, mediaType, {
info: { format },
providerMetadata:
item.revised_prompt === undefined ? undefined : { openai: { revisedPrompt: item.revised_prompt } },
}),
)
if (images.length === 0) return yield* invalid(`${route.name} returned no images`)
const state: State = {
completed: images.length,
format,
size: decoded.size,
quality: decoded.quality,
background: decoded.background,
usage: usage(decoded.usage),
}
const state: State = { completed: images.length, format, usage: usage(decoded.usage) }
return [state, images.map((image, index) => ImageOutputEvent.make({ index, image }))] as const
})
@@ -257,17 +237,7 @@ 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,
size: state.size,
quality: state.quality,
background: state.background,
},
},
}),
ImageFinishEvent.make({ usage: state.usage, providerMetadata: { openai: { outputFormat: state.format } } }),
])
}
+40 -24
View File
@@ -5,12 +5,20 @@ 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, type ToolDefinition, type ToolEntry } from "../schema/index.js"
import {
LLMRequest,
mergeJsonRecords,
type JsonSchema,
type LanguageModel,
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"
@@ -135,6 +143,11 @@ 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 = {
@@ -143,14 +156,12 @@ const adapter = {
restoreHostedToolItem: (item: unknown) => (Schema.is(OpenAIResponsesHostedToolItem)(item) ? item : undefined),
} satisfies OpenResponses.ProviderAdapter
// 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.
// Only GPT-6 Astra accepts `configuration_update`, 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|sol|luna)$/i.test(request.model.id)
return /(?:^|\/)gpt-6-astra$/i.test(request.model.id)
}
const nativeImageToolInput = (tool: ToolDefinition) => {
@@ -163,19 +174,20 @@ const nativeImageTool = (tool: ToolDefinition) => {
return Schema.is(OpenAIResponsesImageGenerationTool)(native) ? native : undefined
}
const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition) {
const lowerTool = Effect.fn("OpenAIResponses.lowerTool")(function* (tool: ToolDefinition, inputSchema: JsonSchema) {
const native = nativeImageToolInput(tool)
if (native !== undefined) {
if (Schema.is(OpenAIResponsesImageGenerationTool)(native)) return native
return yield* ProviderShared.invalidRequest("OpenAI Responses image generation tool options are invalid")
}
return yield* OpenResponses.lowerTool(NAME, tool)
return yield* OpenResponses.lowerTool(NAME, tool, inputSchema)
})
// 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) {
if (tool.type === "tool") return yield* lowerTool(tool)
const lowerToolEntry = Effect.fn("OpenAIResponses.lowerToolEntry")(function* (tool: ToolEntry, model: LanguageModel) {
if (tool.type === "tool")
return yield* lowerTool(tool, ToolSchemaProjection.modelCompatibility(tool.inputSchema, model))
// OpenAI requires a namespace description; fall back to a generic one so a
// missing description never blocks the request.
return {
@@ -183,13 +195,11 @@ 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),
OpenResponses.lowerTool(NAME, leaf, ToolSchemaProjection.modelCompatibility(leaf.inputSchema, model)),
),
}
})
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,
@@ -213,7 +223,10 @@ 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* lowerTools(request),
tools:
request.tools.length === 0
? undefined
: yield* Effect.forEach(request.tools, (tool) => lowerToolEntry(tool, request.model)),
tool_choice:
request.tools.length === 0
? undefined
@@ -225,6 +238,7 @@ 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 (
@@ -235,13 +249,18 @@ const checkpointBody = {
return yield* ProviderShared.invalidRequest(
"Trigger compaction requires complete canonical history, not an input or continuation override",
)
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 }],
}
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,
})
}),
}
@@ -323,10 +342,7 @@ export const transport = channelTransport({
})
export const route = Route.make({
compact: {
endpoint: ResponsesCompaction.make(adapter, lowerTools),
trigger: ResponsesCheckpoint.make(checkpointBody),
},
compact: { endpoint: ResponsesCompaction.make(adapter), trigger: ResponsesCheckpoint.make(checkpointBody) },
id: ADAPTER,
provider: "openai",
providerMetadataKey: "openai",
+2 -14
View File
@@ -60,17 +60,7 @@ 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(
{
@@ -119,9 +109,7 @@ 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())
// 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"
const format = context.request.format ?? "mp3"
return SpeechStream.finish(route, state, {
...(format === "pcm" ? SpeechStream.pcm("pcm_s16le", PCM_SAMPLE_RATE) : SpeechStream.container(format)),
usage: state.usage,
@@ -133,7 +121,7 @@ const finish = (state: State, context: MediaProtocol.ResponseContext<Request>) =
// ---------------------------------------------------------------------------
export const protocol = MediaProtocol.stream<Request, SpeechEvent, string | Uint8Array, State>(route, {
unsupported: ["language"],
unsupported: ["language", "timestamps"],
body: { from: fromRequest },
frames: (bytes, context) => (isSse(context.body) ? Framing.sse.frame(bytes) : bytes),
initial: () => ({ chunks: [], done: false }),
@@ -1,9 +1,8 @@
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 { AIError, mergeJsonRecords, type MediaUsage } from "../schema/index.js"
import { mergeJsonRecords, type MediaUsage } from "../schema/index.js"
import {
TranscriptionFinishEvent,
TranscriptionModel,
@@ -60,9 +59,6 @@ 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 }),
])
@@ -79,23 +75,14 @@ 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)
@@ -131,12 +118,10 @@ 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", `${id} does not diarize; use gpt-4o-transcribe-diarize`))
if (request.prompt !== undefined && model.diarize)
@@ -188,12 +173,12 @@ const fromRequest = Effect.fn("OpenAITranscription.fromRequest")(function* (requ
timestamp_granularities: responseFormat === "verbose_json" ? [request.timestamps] : undefined,
// Diarizing audio longer than 30 seconds requires a chunking strategy.
chunking_strategy: model.diarize ? "auto" : undefined,
stream: streamsEvents(request) ? true : undefined,
stream: request.mode === "stream" ? true : undefined,
},
{
overlay: mergeJsonRecords(request.providerOptions, request.http?.body),
reserved: RESERVED_FORM_FIELDS,
repeatArrays: "key[]",
repeatArrays: true,
},
)
return MediaProtocol.multipart(form)
@@ -211,15 +196,7 @@ const segment = (value: Schema.Schema.Type<typeof Segment>): TranscriptionSegmen
})
const onEvent = Effect.fn("OpenAITranscription.onEvent")(function* (state: State, frame: string) {
if (!EVENT_TYPES.has((yield* decodeEventType(frame)).type)) return [state, []] as const
const event = yield* decodeEvent(frame)
if (event.type === "error")
return yield* new AIError({
reason: classifyProviderFailure({
message: `${route.name} stream failed: ${event.message ?? event.error?.message ?? "unknown error"}`,
rawBody: frame,
}),
})
if (event.type === "transcript.text.done") return [{ ...state, transcript: event }, []] as const
if (event.type === "transcript.text.delta")
return [state, event.delta.length === 0 ? [] : [TranscriptionTextDeltaEvent.make({ delta: event.delta })]] as const
@@ -269,7 +246,7 @@ export const protocol = MediaProtocol.stream<Request, TranscriptionEvent, Frame,
unsupported: ["speakers"],
body: { from: fromRequest },
frames: (bytes, context) =>
streamsEvents(context.request)
context.request.mode === "stream"
? Framing.sse.frame(bytes)
: Framing.document.frame(bytes).pipe(Stream.map((document) => ({ document }))),
initial: () => ({ segments: [] }),
@@ -132,7 +132,8 @@ const decodeResult = Effect.fn("ReplicateImages.decodeResult")(function* (
status,
`${route.name} prediction ${context.token.id} ${prediction.status}${typeof prediction.error === "string" ? `: ${prediction.error}` : ""}`,
)
if (status !== "completed") return yield* output.pending(context.token.id)
if (status !== "completed")
return yield* output.invalid(`${route.name} prediction ${context.token.id} has not finished`)
if (prediction.data_removed === true)
return yield* output.ended("expired", `${route.name} removed the output of prediction ${context.token.id}`)
if (!isOutput(prediction.output))
+4 -8
View File
@@ -137,16 +137,12 @@ const decodeResult = Effect.fn("RunwayVideo.decodeResult")(function* (
const message = `${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)
// ASSET.INVALID rejects the caller's input media; Runway documents it as not retryable.
return yield* output.ended(
"failed",
message,
code !== undefined && /^ASSET\.INVALID(\.|$)/.test(code) ? "InvalidRequest" : "ProviderInternal",
)
return yield* output.ended("failed", message)
}
if (status === "cancelled")
return yield* output.ended("cancelled", `${route.name} task ${context.token.taskID} was cancelled`)
if (status !== "completed") return yield* output.pending(context.token.taskID)
if (status !== "completed")
return yield* output.invalid(`${route.name} task ${context.token.taskID} has not finished`)
const urls = task.output ?? []
if (urls.length === 0) return yield* output.invalid(`${route.name} task succeeded without any output`)
return new VideoResponse({
@@ -175,7 +171,7 @@ 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, activeOnly: true },
cancel: { method: "DELETE", path: taskPath },
})
const startPath = (request: Request) => {
-8
View File
@@ -110,14 +110,6 @@ 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.pending(context.token.id)
return yield* output.invalid(`${upscaleRoute.name} upscale ${context.token.id} has not finished`)
}
return yield* decodeUpscaleImage(response)
})
@@ -1,19 +0,0 @@
import type { LLMRequest } from "../../schema/index.js"
export const THINKING_BINDING_BETA = "thinking-binding-controls-2026-08-01"
// Accept gateway namespaces and Vertex suffixes without treating a snapshot date as a minor version.
export const claudeVersion = (id: string) => {
const match = /(?:^|[./])claude-(?<family>[a-z]+)-(?<major>\d+)(?:[.-](?<minor>\d{1,2}))?(?:$|[-:@])/.exec(
id.toLowerCase(),
)?.groups
if (!match) return undefined
return { family: match.family, major: Number(match.major), minor: Number(match.minor ?? 0) }
}
export const supportsThinkingBlockBinding = (model: LLMRequest["model"]) => {
const override = model.compatibility?.supportsThinkingBlockBinding
if (override !== undefined) return override
const version = claudeVersion(model.id)
return version !== undefined && (version.major > 5 || (version.major === 5 && version.minor >= 1))
}
@@ -72,44 +72,6 @@ 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 ${state.finishReason}`,
providerMetadata: { google: { finishReason: state.finishReason } },
},
]
export const usage = (usage: UsageMetadata | undefined): MediaUsage | undefined =>
usage === undefined
? undefined
@@ -71,9 +71,8 @@ export const imageOutput = (
}
/**
* Append multipart text fields: strings as-is, other values as JSON, or scalar arrays as one part per item with
* `repeatArrays`, named `key[]` or `key`. `overlay` keys in `reserved` are dropped so `http.body` cannot replace
* route-owned fields.
* Append multipart text fields: strings as-is, other values as JSON, or arrays as repeated `key[]` parts with
* `repeatArrays`. `overlay` keys in `reserved` are dropped so `http.body` cannot replace route-owned fields.
*/
export const appendFields = (
form: FormData,
@@ -81,13 +80,13 @@ export const appendFields = (
options: {
readonly overlay?: Record<string, unknown>
readonly reserved: ReadonlySet<string>
readonly repeatArrays?: "key[]" | "key"
readonly repeatArrays?: true
},
) => {
const overlay = Object.entries(options.overlay ?? {}).filter(([key]) => !options.reserved.has(key))
Object.entries(mergeJsonRecords(fields, Object.fromEntries(overlay)) ?? {}).forEach(([key, value]) => {
if (Array.isArray(value) && value.every(isScalar) && options.repeatArrays !== undefined)
return value.forEach((item) => form.append(options.repeatArrays === "key[]" ? `${key}[]` : key, String(item)))
if (Array.isArray(value) && options.repeatArrays)
return value.forEach((item) => form.append(`${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, LLMEvent, LLMRequest } from "../../schema/index.js"
import { CompactionCheckpointResponse, HttpOptions, LLMEvent, LLMRequest } from "../../schema/index.js"
import { OpenResponses } from "../open-responses.js"
import { ProviderShared } from "../shared.js"
@@ -109,8 +109,12 @@ export const make = <Body>(body: RouteBody<Body>): TriggerCompactOperation =>
transport: source.transport,
})
const native = yield* body.from(request)
const prepared = yield* route.prepareTransport(native, request, options)
yield* route.streamPrepared(prepared, request, { http: executor }, options).pipe(Stream.runDrain)
// 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)
if (!result) return yield* ProviderShared.eventError(source.id, "Compaction response ended without a checkpoint")
return result
})
@@ -19,18 +19,12 @@ 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(
@@ -80,27 +74,17 @@ const Response = Schema.Struct({
usage: Schema.optional(Schema.StructWithRest(OpenResponses.OpenResponsesUsage, [JsonObject])),
})
export const make = (
adapter: OpenResponses.ProviderAdapter,
lowerTools: (request: LLMRequest) => Effect.Effect<ReadonlyArray<Record<string, unknown>>, AIError>,
): CompactOperation =>
export const make = (adapter: OpenResponses.ProviderAdapter): 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: 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,
service_tier: request.providerOptions?.serviceTier,
prompt_cache_key: ProviderShared.promptCacheKey(request),
},
request.http?.body,
),
@@ -1,10 +0,0 @@
/** 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"
@@ -85,7 +85,6 @@ 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
},
@@ -98,7 +97,6 @@ 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,
}),
])
+8 -16
View File
@@ -1,4 +1,4 @@
import { ToolDefinition, type JsonSchema, type LanguageModel, type LLMRequest } from "../../schema/index.js"
import type { JsonSchema, LanguageModel, LanguageModelSanitizerCompatibility } 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): JsonSchema => {
const modelCompatibility = (
schema: JsonSchema,
model: LanguageModel,
protocolDefault?: LanguageModelSanitizerCompatibility,
): JsonSchema => {
const root = objectRoot(schema)
switch (
model.compatibility?.sanitizer ??
model.route.sanitizer ??
MODEL_NAMES.find(([name]) => name.test(model.id))?.[1]
) {
switch (model.compatibility?.sanitizer ?? protocolDefault ?? MODEL_NAMES.find(([name]) => name.test(model.id))?.[1]) {
case "gemini":
return gemini(root)
case "moonshot":
@@ -87,18 +87,10 @@ const modelCompatibility = (schema: JsonSchema, model: LanguageModel): JsonSchem
}
}
// 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
@@ -147,12 +147,7 @@ export const appendOrStart = <K extends StreamKey>(
route: string,
tools: State<K>,
key: K,
delta: {
readonly id?: string
readonly name?: string
readonly text: string
readonly providerMetadata?: ProviderMetadata
},
delta: { readonly id?: string; readonly name?: string; readonly text: string },
missingToolMessage: string,
): AppendOutcome<K> | AIError => {
const current = tools[key]
@@ -166,7 +161,7 @@ export const appendOrStart = <K extends StreamKey>(
namespace: current?.namespace,
input: `${current?.input ?? ""}${delta.text}`,
providerExecuted: current?.providerExecuted,
providerMetadata: current?.providerMetadata ?? delta.providerMetadata,
providerMetadata: current?.providerMetadata,
}
if (current && delta.text.length === 0 && current.id === id && current.name === name)
return { tools, tool: current, events: [] }
+1 -2
View File
@@ -101,8 +101,7 @@ const decodeResponse = Effect.fn("XAIImages.decodeResponse")(function* (
)
if (images.length === 0) return yield* output.invalid(`${route.name} returned no images`)
const usage = ProviderShared.isRecord(decoded.usage) ? decoded.usage : undefined
// xAI reports a USD cost (`cost_in_usd_ticks`) rather than tokens, seconds, or credits; the raw record stays in
// provider metadata.
// xAI reports image counts rather than tokens, seconds, or credits; the raw record stays in provider metadata.
return new ImageResponse({
images,
providerMetadata: usage === undefined ? undefined : { xai: { usage } },
+2 -5
View File
@@ -50,8 +50,7 @@ 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))
})
@@ -94,8 +93,6 @@ export const protocol = Protocol.make({
},
})
export const compact = ResponsesCompaction.make(adapter, (request) =>
OpenResponses.lowerTools(ProviderShared.flattenTools(request.tools), adapter),
)
export const compact = ResponsesCompaction.make(adapter)
export * as XAIResponses from "./xai-responses.js"
+2 -9
View File
@@ -65,13 +65,6 @@ 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
// ---------------------------------------------------------------------------
@@ -143,14 +136,14 @@ 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.pending(context.token.requestID)
if (status === "running")
return yield* output.invalid(`${route.name} request ${context.token.requestID} has not finished`)
if (status === "failed") {
const code = decoded.error?.code ?? undefined
const message = decoded.error?.message ?? undefined
return yield* output.ended(
"failed",
`${route.name} generation failed${code === undefined ? "" : ` (${code})`}${message === undefined ? "" : `: ${message}`}`,
MediaProtocol.failure(FAILURE, code),
)
}
if (status !== "completed")
+3 -3
View File
@@ -1,6 +1,7 @@
import { Duration, Effect, Schema } from "effect"
import { 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"
@@ -8,7 +9,6 @@ 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: yield* Effect.forEach(decoded.data, (item) => MediaProtocol.expiringUrl(item.url, OUTPUT_RETENTION)),
images: decoded.data.map((item) => Media.url(item.url)),
// Z.ai reports applied content filters alongside a successful result; surface them instead of dropping them.
notices:
filters.length === 0
+6 -96
View File
@@ -1,4 +1,4 @@
import { Option, Schema, SchemaGetter } from "effect"
import { Option, Schema } from "effect"
import {
AuthenticationError,
ContentPolicyError,
@@ -33,8 +33,7 @@ const patterns = [
/context[_ ]length[_ ]exceeded/i,
/context length is only \d+ tokens/i,
/input length.*exceeds.*context length/i,
// Z.ai code 1261 arrives as `Prompt too long` or `Prompt 超长`.
/prompt (?:too long|超长)/i,
/prompt too long; exceeded (?:max )?context length/i,
/too large for model with \d+ maximum context length/i,
/prompt has [\d,]+ tokens?, but the configured context size is [\d,]+ tokens?/i,
/model_context_window_exceeded/i,
@@ -59,47 +58,6 @@ 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([
@@ -110,8 +68,7 @@ const QUOTA_CODES = new Set([
"freeusagelimiterror",
"creditlimitexceeded",
])
// Google reports an invalid API key as HTTP 400 INVALID_ARGUMENT with this `details[].reason`.
const AUTH_CODES = new Set(["authentication_error", "permission_error", "api_key_invalid"])
const AUTH_CODES = new Set(["authentication_error", "permission_error"])
const SERVER_CODES = new Set([
"api_error",
"internal_error",
@@ -123,13 +80,7 @@ const SERVER_CODES = new Set([
"slow_down",
"serviceunavailableexception",
])
// `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",
])
const INVALID_REQUEST_CODES = new Set(["invalid_prompt", "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.
@@ -146,53 +97,16 @@ const CONTENT_POLICY_CODES = new Set([
const GATEWAY_CODE_LABEL = /^[^:\n]+: \[([A-Za-z0-9_.-]+)\]/
const RATE_LIMIT_TEXT = /rate increased too quickly|rate[-_\s]?limit|too[_\s]?many[_\s]?requests/i
// Only consulted on 429, where throttles and account caps share a status.
// Z.ai reports balance, plan expiry, plan limits, plan model access, and fair-use restrictions on 429.
const QUOTA_TEXT =
/insufficient[-_\s]?(?:quota|balance)|quota[-_\s]?exceeded|budget exceeded|usage limit|limit exhausted|package has expired|plan does not yet include|fair usage policy/i
const QUOTA_TEXT = /insufficient[-_\s]?quota|quota[-_\s]?exceeded|budget exceeded|usage limit/i
// Policy rejections without a dedicated code, matched against the provider's own
// explanation only. OpenAI reuses `invalid_prompt` for usage-policy rejections while
// Bedrock Mantle reuses it for schema validation; Anthropic reports blocked output
// under `invalid_request_error`.
const CONTENT_POLICY_TEXT =
/violating our usage policy|blocked by content filtering policy|content[-_\s]?policy|rejected as a result of our safety system|detected potentially unsafe or sensitive content/i
/violating our usage policy|blocked by content filtering policy|content[-_\s]?policy|rejected as a result of our safety system/i
const SERVER_ERROR_TEXT =
/\b(?:try again|(?:please |you can )?retry (?:the |this |your )?request|try (?:the |this |your )?request again|(?:currently |temporarily )?at capacity|overloaded|temporarily unavailable|service[-_\s]?unavailable|(?:server|internal)[-_\s]?error|server (?:is )?busy|provider returned (?:an )?error|resource[-_\s]?exhausted|upstream (?:connect|connection|request)|request buffer limit while retrying upstream)\b/i
const Message = Schema.String.check(Schema.isPattern(/\S/))
const messageAt = <Fields extends Schema.Struct.Fields>(
fields: Fields,
message: (body: Schema.Struct<Fields>["Type"]) => string,
) =>
Schema.Struct(fields).pipe(
Schema.decodeTo(Schema.String, {
decode: SchemaGetter.transform(message),
encode: SchemaGetter.forbidden(() => "Provider error messages are decode-only"),
}),
)
// Common error body layouts that carry a human-readable message, in priority order.
// Provider-specific layouts belong in their protocol.
const decodeMessage = Schema.decodeUnknownOption(
Schema.fromJsonString(
Schema.Union([
messageAt({ error: Schema.Struct({ message: Message }) }, (body) => body.error.message),
messageAt({ error: Message }, (body) => body.error),
messageAt({ message: Message }, (body) => body.message),
// AWS services
messageAt({ Message: Message }, (body) => body.Message),
// RFC 9457 problem details
messageAt({ detail: Message }, (body) => body.detail),
messageAt(
{ errors: Schema.NonEmptyArray(Schema.Struct({ message: Message })) },
(body) => body.errors[0].message,
),
]),
),
)
export const providerErrorMessage = (body: string) => Option.getOrUndefined(decodeMessage(body))
export interface ProviderFailure {
readonly message: string
readonly status?: number | undefined
@@ -298,10 +212,6 @@ function providerCodes(value: unknown) {
error?.type,
error?.status,
error?.error_type,
// Google `google.rpc.ErrorInfo` details carry the specific reason.
...(Array.isArray(error?.details)
? error.details.map((detail) => (isRecord(detail) ? detail.reason : undefined))
: []),
inner?.code,
metadata?.error_type,
responseError?.code,
@@ -31,7 +31,6 @@ 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]
@@ -72,7 +71,6 @@ 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)
@@ -28,8 +28,7 @@ export type Settings = ProviderPackage.Settings &
readonly provider?: string
}
const compatibleRoute = AnthropicMessages.route.with({ id: "anthropic-compatible-messages", provider: id })
export const routes = [compatibleRoute]
export const routes = [AnthropicMessages.route]
const auth = (input: ProviderAuthOption<"optional">) => {
if ("auth" in input && input.auth) return input.auth
@@ -44,7 +43,7 @@ export const configure = (input: Config) => {
message: "Anthropic-compatible providers require a baseURL",
})
const { provider: _, baseURL, apiKey: _apiKey, auth: _auth, ...rest } = input
const route = (provider === "anthropic" ? AnthropicMessages.route : compatibleRoute).with({
const route = AnthropicMessages.route.with({
...rest,
provider,
endpoint: { baseURL },
-5
View File
@@ -3,10 +3,8 @@ 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")
@@ -26,15 +24,12 @@ 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
+15 -4
View File
@@ -32,7 +32,10 @@ const openAIProviderOptions = (options: OpenAIOptionsInput | undefined): Provide
return result
}
export const gpt5DefaultOptions = (modelID: string): ProviderOptions | undefined => {
export const gpt5DefaultOptions = (
modelID: string,
options: { readonly textVerbosity?: boolean } = {},
): 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({
@@ -44,19 +47,27 @@ export const gpt5DefaultOptions = (modelID: string): ProviderOptions | undefined
// 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): ProviderOptions | undefined =>
mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID))
export const openAIDefaultOptions = (
modelID: string,
options: { readonly textVerbosity?: boolean } = {},
): ProviderOptions | undefined =>
mergeProviderOptions(openAIProviderOptions({ store: false }), gpt5DefaultOptions(modelID, options))
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), options.providerOptions),
providerOptions: mergeProviderOptions(openAIDefaultOptions(modelID, defaults), options.providerOptions),
}
}
+1 -1
View File
@@ -100,7 +100,7 @@ export const configure = (input: Config = {}) => {
const modelDefaults = defaults(input)
const responses = (id: string | ModelID) =>
responsesRoute
.with(withOpenAIOptions(id, modelDefaults))
.with(withOpenAIOptions(id, modelDefaults, { textVerbosity: true }))
.model<OpenAIProviderOptionsInput>({ id })
const chat = (id: string | ModelID) =>
chatRoute.with(withOpenAIOptions(id, modelDefaults)).model<OpenAIProviderOptionsInput>({
+4 -11
View File
@@ -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, ProviderShared } from "../protocols/shared.js"
import { isRecord } 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, request.generation?.maxTokens),
...bodyOptions(request.providerOptions),
} as OpenRouterBody
}),
),
@@ -143,14 +143,7 @@ const cacheControl = () => {
}
}
// 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 bodyOptions = (input: unknown) => {
const openrouter = isRecord(input) ? input : {}
const { usage, models, provider, plugins, web_search_options, debug, user, reasoning, promptCacheKey, ...options } =
openrouter
@@ -169,7 +162,7 @@ const bodyOptions = (input: unknown, maxTokens: number | undefined) => {
...(isRecord(web_search_options) ? { web_search_options } : {}),
...(isRecord(debug) ? { debug } : {}),
...(typeof user === "string" ? { user } : {}),
...(isRecord(reasoning) ? { reasoning: fitReasoning(reasoning, maxTokens) } : {}),
...(isRecord(reasoning) ? { reasoning } : {}),
}
}
+3 -3
View File
@@ -35,13 +35,13 @@ const RESPONSES_WEBSOCKET_ROTATE_AFTER_MS = 24 * 60 * 1000
const responsesRoute = Route.make({
compact: { endpoint: XAIResponses.compact },
id: "xai-responses",
id: "openai-responses",
provider: id,
providerMetadataKey: "xai",
protocol: XAIResponses.protocol,
endpoint: Endpoint.path("/responses", { baseURL }),
transport: OpenResponsesChannel.transport({
id: "xai-responses",
id: "openai-responses",
name: "xAI Responses",
rotateAfterMs: RESPONSES_WEBSOCKET_ROTATE_AFTER_MS,
// xAI continues a chain only from stored responses: with `store: false` (the route default) `previous_response_id`
@@ -53,7 +53,7 @@ const responsesRoute = Route.make({
})
const chatRoute = Route.make({
id: "xai-chat",
id: "openai-compatible-chat",
provider: id,
providerMetadataKey: "xai",
protocol: OpenAIChat.protocol,
+2 -7
View File
@@ -11,8 +11,7 @@ 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 { ToolSchemaProjection } from "../protocols/utils/tool-schema.js"
import type { LanguageModelSanitizerCompatibility, ProtocolID, ProviderOptions } from "../schema/index.js"
import type { ProtocolID, ProviderOptions } from "../schema/index.js"
import {
AIError,
CompactionResponse,
@@ -58,7 +57,6 @@ 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 },
@@ -390,7 +388,6 @@ 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({
@@ -562,9 +559,7 @@ const prepareRequest = (request: LLMRequest) => {
tool.type === "tool" ? tool : { ...tool, tools: dedupe(tool.tools) },
)
const resolved = applyCachePolicy(
applyEffortUpdates(
LLMRequest.update(sanitized, { tools: ToolSchemaProjection.tools(dedupe(sanitized.tools), sanitized.model) }),
),
applyEffortUpdates(LLMRequest.update(sanitized, { tools: dedupe(sanitized.tools) })),
)
const headers = resolved.model.route.headers?.({ request: resolved })
return headers === undefined
+14 -10
View File
@@ -8,7 +8,7 @@ import {
HttpClientResponse,
} from "effect/unstable/http"
import { HttpContext, HttpRateLimitDetails, AIError, TransportError } from "../schema/index.js"
import { classifyProviderFailure, providerErrorMessage } from "../provider-error.js"
import { classifyProviderFailure } from "../provider-error.js"
import { Service, type HttpMiddleware, type Interface } from "./executor-service.js"
export { Service } from "./executor-service.js"
@@ -84,17 +84,21 @@ export const responseHttp = (response: HttpClientResponse.HttpClientResponse) =>
headers: headerDetails(response.headers),
})
const MAX_BODY_CHARS = 2000
const decodeProviderBody = Schema.decodeUnknownOption(
Schema.fromJsonString(
Schema.Struct({
message: Schema.optionalKey(Schema.String),
error: Schema.optionalKey(Schema.Struct({ message: Schema.optionalKey(Schema.String) })),
}),
),
)
// Without a recognized message, show the raw body so the provider's explanation is never dropped.
const providerMessage = (status: number, body: string | void) => {
const fallback = `Provider request failed with HTTP ${status}`
const text = body?.trim() ?? ""
const message = providerErrorMessage(text)
if (message) return message
// Gateway and proxy HTML error pages are markup, not an explanation.
if (!text || /^<(?:!doctype|html)/i.test(text)) return fallback
return `${fallback}: ${text.length > MAX_BODY_CHARS ? `${text.slice(0, MAX_BODY_CHARS)}…` : text}`
const decoded = body === undefined ? undefined : Option.getOrUndefined(decodeProviderBody(body))
return (
[decoded?.error?.message, decoded?.message].find((message) => message?.trim()) ??
`Provider request failed with HTTP ${status}`
)
}
const statusError = (response: HttpClientResponse.HttpClientResponse) =>
+7 -41
View File
@@ -5,14 +5,12 @@ 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"
@@ -139,11 +137,6 @@ 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
}
}
@@ -190,16 +183,6 @@ 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 })
@@ -211,10 +194,8 @@ 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`
* 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.
* 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.
*/
const text = Effect.fn("MediaProtocol.text")(function* (response: HttpClientResponse.HttpClientResponse) {
const http = context(response)
@@ -236,25 +217,13 @@ 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,
failure: Failure = "ProviderInternal",
) =>
ended: (status: Exclude<Status, "queued" | "running" | "completed">, message: string) =>
new AIError({
reason:
status === "failed"
? new FAILURES[failure]({ message, body, http })
? new ProviderInternalError({ message, body, http })
: new InvalidRequestError({ message, body, http }),
}),
pending: (id: string) =>
new AIError({
reason: new InvalidRequestError({
message: `${input.name} generation ${id} has not finished; await it before reading the result`,
body,
http,
}),
}),
contentPolicy: (message: string) => new AIError({ reason: new ContentPolicyError({ message, body, http }) }),
}
})
@@ -316,14 +285,11 @@ export const status = <Table extends Record<string, Status>>(
raw: string,
output: Output,
): Effect.Effect<Status, AIError> => {
if (!Object.hasOwn(table, raw)) return Effect.fail(output.invalid(`Unknown generation status "${raw}"`))
return Effect.succeed(table[raw])
const normalized: Status | undefined = table[raw]
if (normalized === undefined) return Effect.fail(output.invalid(`Unknown generation status "${raw}"`))
return Effect.succeed(normalized)
}
/** 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(
+66 -52
View File
@@ -1,13 +1,12 @@
import { Duration, Effect, Schedule, Schema, Stream } from "effect"
import { Effect, 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, isTerminal } from "../generation.js"
import { Generation, resultEvents, type AwaitOptions, type Observation } from "../generation.js"
import type { Media } from "../media.js"
import { isRetryable } from "../provider-error.js"
import {
AIError,
AIErrorReason,
@@ -53,7 +52,7 @@ export const deployment = (
// ---------------------------------------------------------------------------
/** One request, one response. */
export interface InlineRoute<Request extends MediaRequest, Response> {
export interface Route<Request extends MediaRequest, Response> {
readonly kind: "inline"
readonly id: string
readonly provider: ProviderID
@@ -87,7 +86,7 @@ export interface StreamRoute<Request extends MediaRequest, Event, Response> {
}
export type AnyRoute<Request extends MediaRequest, Event, Response> =
| InlineRoute<Request, Response>
| Route<Request, Response>
| StreamRoute<Request, Event, Response>
| QueuedRoute<Request, Response>
@@ -120,7 +119,7 @@ export interface StreamInput<Request extends MediaRequest, Event, Response, Fram
*/
export const inline = <Request extends MediaRequest, Response>(
input: InlineInput<Request, Response>,
): InlineRoute<Request, Response> => {
): Route<Request, Response> => {
const transport = makeTransport(input)
return {
kind: "inline",
@@ -138,32 +137,6 @@ 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
@@ -181,8 +154,6 @@ 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: (
@@ -190,23 +161,17 @@ 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.retry({ schedule: READ_RETRY, while: isRetryable }),
Effect.flatMap((sent) => operation.decode(sent.response, { token, auth: sent.auth, materialize })),
)
const status = poll(protocol.status)
transport
.call("GET", operation.path(token), http, execute)
.pipe(Effect.flatMap((sent) => operation.decode(sent.response, { token, auth: sent.auth, materialize })))
const cancel = protocol.cancel
const send =
cancel === undefined
? undefined
: transport.call(cancel.method, cancel.path(token), http, execute).pipe(Effect.asVoid)
return {
status,
status: poll(protocol.status),
result: poll(protocol.result),
cancel:
send !== undefined && cancel?.activeOnly
? status.pipe(Effect.flatMap((snapshot) => (isTerminal(snapshot.status) ? Effect.void : send)))
: send,
cancel === undefined
? undefined
: transport.call(cancel.method, cancel.path(token), http, execute).pipe(Effect.asVoid),
}
}
@@ -302,6 +267,59 @@ 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
// ---------------------------------------------------------------------------
@@ -415,11 +433,7 @@ const encode = (body: MediaProtocol.Body | undefined, headers: Headers.Headers)
}
}
/**
* 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.
*/
/** Common fields are never silently dropped: a present field the protocol declared unsupported fails typed. */
const rejectUnsupported = <Request extends object>(
route: string,
provider: ProviderID,
+1 -3
View File
@@ -1,5 +1,5 @@
import { Schema, type Effect } from "effect"
import type { AIError, LanguageModelSanitizerCompatibility, LLMEvent, LLMRequest, ProtocolID } from "../schema/index.js"
import type { AIError, LLMEvent, LLMRequest, ProtocolID } from "../schema/index.js"
/**
* The semantic API contract of one model server family.
@@ -43,8 +43,6 @@ 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> {
+44 -22
View File
@@ -1,31 +1,53 @@
import { Context } from "effect"
import { MediaClient } from "./media-client.js"
import {
SpeechTimestampsEvent,
SpeechFinishEvent,
type SpeechEvent,
type SpeechRequestFor,
type SpeechResponse,
} from "./speech.js"
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"
export type Interface = MediaClient.Interface<SpeechRequestFor, SpeechEvent, SpeechResponse>
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 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,
...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,
}),
],
}),
layer,
generate,
stream,
} as const
+41 -31
View File
@@ -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"
@@ -10,39 +10,53 @@ import { SpeechClient, Service } from "./speech-client.js"
// Model
// ---------------------------------------------------------------------------
export type SpeechOptions = MediaModel.Options
export type SpeechOptions = Record<string, unknown>
export type SpeechRoute = MediaRoute.AnyRoute<SpeechRequestFor, SpeechEvent, SpeechResponse>
export type SpeechRoute<Options extends SpeechOptions = SpeechOptions> = MediaRoute.StreamRoute<
SpeechRequestFor<Options>,
SpeechEvent,
SpeechResponse
>
export class SpeechModel<Options extends SpeechOptions = SpeechOptions> extends MediaModel<SpeechRoute, Options> {
export class SpeechModel<Options extends SpeechOptions = SpeechOptions> extends MediaModel<
SpeechRoute<Options>,
Options
> {
declare protected readonly _SpeechModel: void
/** 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>,
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>,
input: MediaRoute.ModelInput,
) {
return new SpeechModel<Options>({
id: input.id,
provider: route.protocol.provider,
http: input.http,
route: composeRoute(route, input, collectResponse) as SpeechRoute,
route: composeRoute(
(composition) => MediaRoute.stream({ ...composition, collect: collectResponse }),
route,
input,
),
})
}
}
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",
})
@@ -134,17 +148,11 @@ export const SpeechFinishEvent = Schema.Struct({
providerMetadata: Schema.optional(ProviderMetadata),
}).annotate({ identifier: "Speech.Event.Finish" })
const speechEventTagged = Schema.Union([
QueuedEvent,
ProgressEvent,
SpeechAudioDeltaEvent,
SpeechTimestampsEvent,
SpeechFinishEvent,
]).pipe(Schema.toTaggedUnion("type"))
const speechEventTagged = Schema.Union([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,
@@ -187,15 +195,17 @@ export function request(input: SpeechRequest | SpeechRequestInput) {
const requestEffect = (input: SpeechRequest | SpeechRequestInput) => tryRequest(() => request(input))
export function generate<const Model extends SpeechModel>(
input: SpeechRequest | SpeechRequestInput<Model>,
input: 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: SpeechRequest | SpeechRequestInput<Model>,
input: 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))))
}
+85 -8
View File
@@ -1,13 +1,34 @@
import { Context } from "effect"
import { MediaClient } from "./media-client.js"
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 {
TranscriptionFinishEvent,
responseEvents,
type TranscriptionEvent,
type TranscriptionModel,
type TranscriptionOptions,
type TranscriptionRequestFor,
type TranscriptionResponse,
} from "./transcription.js"
export type Interface = MediaClient.Interface<TranscriptionRequestFor, TranscriptionEvent, TranscriptionResponse>
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 class TranscriptionClientService extends Context.Service<TranscriptionClientService, Interface>()(
"@opencode/TranscriptionClient",
@@ -15,10 +36,66 @@ 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,
...MediaClient.make(Service, {
modality: "transcription",
responseEvents: (response: TranscriptionResponse) => [TranscriptionFinishEvent.make({ ...response })],
}),
layer,
generate,
stream,
start,
resume,
} as const
+77 -22
View File
@@ -1,8 +1,9 @@
import { Effect, Schema, Stream } from "effect"
import { Generation, ProgressEvent, QueuedEvent, type AwaitOptions } from "./generation.js"
import { Media } from "./media.js"
import { MediaModel, composeRoute, tryRequest } from "./media-model.js"
import { MediaModel, composeAnyRoute, 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"
@@ -10,49 +11,90 @@ import { TranscriptionClient, Service } from "./transcription-client.js"
// Model
// ---------------------------------------------------------------------------
export type TranscriptionOptions = MediaModel.Options
export type TranscriptionOptions = Record<string, unknown>
export type TranscriptionRoute = MediaRoute.AnyRoute<TranscriptionRequestFor, TranscriptionEvent, TranscriptionResponse>
export type TranscriptionRoute<Options extends TranscriptionOptions = TranscriptionOptions> = MediaRoute.AnyRoute<
TranscriptionRequestFor<Options>,
TranscriptionEvent,
TranscriptionResponse
>
export class TranscriptionModel<Options extends TranscriptionOptions = TranscriptionOptions> extends MediaModel<
TranscriptionRoute,
TranscriptionRoute<Options>,
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: MediaModel.InlineRouteInput<TranscriptionRequestFor<Options>, TranscriptionResponse>,
route: TranscriptionModel.InlineRouteInput<Options>,
input: MediaRoute.ModelInput,
): TranscriptionModel<Options>
static fromRoute<Options extends TranscriptionOptions, Frame, State>(
route: MediaModel.StreamRouteInput<TranscriptionRequestFor<Options>, TranscriptionEvent, Frame, State>,
route: TranscriptionModel.StreamRouteInput<Options, Frame, State>,
input: MediaRoute.ModelInput,
): TranscriptionModel<Options>
static fromRoute<Options extends TranscriptionOptions, Token>(
route: MediaModel.QueuedRouteInput<TranscriptionRequestFor<Options>, TranscriptionResponse, Token>,
route: TranscriptionModel.QueuedRouteInput<Options, Token>,
input: MediaRoute.ModelInput,
): TranscriptionModel<Options>
static fromRoute<Options extends TranscriptionOptions, Frame, State, Token>(
route: MediaModel.AnyRouteInput<
TranscriptionRequestFor<Options>,
TranscriptionEvent,
TranscriptionResponse,
Frame,
State,
Token
>,
route: TranscriptionModel.RouteInput<Options, Frame, State, Token>,
input: MediaRoute.ModelInput,
) {
return new TranscriptionModel<Options>({
id: input.id,
provider: route.protocol.provider,
http: input.http,
route: composeRoute(route, input, collectResponse) as TranscriptionRoute,
route: composeAnyRoute(route, input, collectResponse),
})
}
}
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" },
@@ -103,7 +145,7 @@ export type TranscriptionRequestInput<Model extends TranscriptionModel = Transcr
// Response and events
// ---------------------------------------------------------------------------
/** Speaker labels are provider-native (`A`, `0`, `spk:0`, `speaker_0`, or a known speaker name). */
/** Speaker labels are provider-native (`A`, `0`, `spk:0`, or a known speaker name). */
export const TranscriptionSegment = Schema.Struct({
text: Schema.String,
startSeconds: Schema.Number,
@@ -170,6 +212,10 @@ 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.
@@ -197,7 +243,11 @@ export function request(input: TranscriptionRequest | TranscriptionRequestInput)
const requestEffect = (input: TranscriptionRequest | TranscriptionRequestInput) => tryRequest(() => request(input))
export function generate<const Model extends TranscriptionModel>(
input: TranscriptionRequest | TranscriptionRequestInput<Model>,
input: TranscriptionRequestInput<Model>,
options?: AwaitOptions,
): Effect.Effect<TranscriptionResponse, AIError, Service>
export function generate(
input: TranscriptionRequest,
options?: AwaitOptions,
): Effect.Effect<TranscriptionResponse, AIError, Service>
export function generate(input: TranscriptionRequest | TranscriptionRequestInput, options?: AwaitOptions) {
@@ -205,7 +255,11 @@ export function generate(input: TranscriptionRequest | TranscriptionRequestInput
}
export function stream<const Model extends TranscriptionModel>(
input: TranscriptionRequest | TranscriptionRequestInput<Model>,
input: TranscriptionRequestInput<Model>,
options?: AwaitOptions,
): Stream.Stream<TranscriptionEvent, AIError, Service>
export function stream(
input: TranscriptionRequest,
options?: AwaitOptions,
): Stream.Stream<TranscriptionEvent, AIError, Service>
export function stream(input: TranscriptionRequest | TranscriptionRequestInput, options?: AwaitOptions) {
@@ -214,14 +268,15 @@ export function stream(input: TranscriptionRequest | TranscriptionRequestInput,
/** Inline and streaming routes fail with `UnsupportedOperation`. */
export function start<const Model extends TranscriptionModel>(
input: TranscriptionRequest | TranscriptionRequestInput<Model>,
input: 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 = (
model: TranscriptionModel,
export const resume = <Options extends TranscriptionOptions>(
model: TranscriptionModel<Options>,
token: unknown,
): Effect.Effect<Generation<TranscriptionResponse>, AIError, Service> => TranscriptionClient.resume(model, token)
+84 -16
View File
@@ -1,30 +1,98 @@
import { Context } from "effect"
import { MediaClient } from "./media-client.js"
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 {
VideoOutputEvent,
VideoFinishEvent,
responseEvents,
type VideoEvent,
type VideoModel,
type VideoOptions,
type VideoRequestFor,
type VideoResponse,
} from "./video.js"
export type Interface = MediaClient.Interface<VideoRequestFor, VideoEvent, VideoResponse>
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 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,
...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,
}),
],
}),
layer,
start,
resume,
generate,
stream,
} as const
+41 -37
View File
@@ -3,6 +3,7 @@ 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"
@@ -10,39 +11,41 @@ import { VideoClient, Service } from "./video-client.js"
// Model
// ---------------------------------------------------------------------------
export type VideoOptions = MediaModel.Options
export type VideoOptions = Record<string, unknown>
export type VideoRoute = MediaRoute.AnyRoute<VideoRequestFor, VideoEvent, VideoResponse>
export type VideoRoute<Options extends VideoOptions = VideoOptions> = MediaRoute.QueuedRoute<
VideoRequestFor<Options>,
VideoResponse
>
export class VideoModel<Options extends VideoOptions = VideoOptions> extends MediaModel<VideoRoute, Options> {
export class VideoModel<Options extends VideoOptions = VideoOptions> extends MediaModel<VideoRoute<Options>, Options> {
declare protected readonly _VideoModel: void
/** 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>,
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>,
input: MediaRoute.ModelInput,
) {
return new VideoModel<Options>({
id: input.id,
provider: route.protocol.provider,
http: input.http,
route: composeRoute(route, input, collectResponse) as VideoRoute,
route: composeRoute(MediaRoute.queued, route, input),
})
}
}
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",
})
@@ -146,19 +149,15 @@ export const VideoEvent = Object.assign(videoEventTagged, {
})
export type VideoEvent = Schema.Schema.Type<typeof videoEventTagged>
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,
}),
)
}
/** 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,
}),
]
// ---------------------------------------------------------------------------
// Request-shaped call API
@@ -179,28 +178,33 @@ export function request(input: VideoRequest | VideoRequestInput) {
const requestEffect = (input: VideoRequest | VideoRequestInput) => tryRequest(() => request(input))
export function start<const Model extends VideoModel>(
input: VideoRequest | VideoRequestInput<Model>,
input: 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: VideoRequest | VideoRequestInput<Model>,
input: 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 = (model: VideoModel, token: unknown): Effect.Effect<Generation<VideoResponse>, AIError, Service> =>
VideoClient.resume(model, token)
export const resume = <Options extends VideoOptions>(
model: VideoModel<Options>,
token: unknown,
): Effect.Effect<Generation<VideoResponse>, AIError, Service> => VideoClient.resume(model, token)
export function stream<const Model extends VideoModel>(
input: VideoRequest | VideoRequestInput<Model>,
input: 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))))
}
+1 -21
View File
@@ -3,7 +3,7 @@ import { Effect } from "effect"
import { CacheHint, LLM, Message } from "../src/index.js"
import { Auth } from "../src/route.js"
import { compileRequest } from "../src/route/client.js"
import { AmazonBedrock, AnthropicCompatible, GoogleVertexMessages } from "../src/providers.js"
import { AmazonBedrock, GoogleVertexMessages } from "../src/providers.js"
import * as AnthropicMessages from "../src/protocols/anthropic-messages.js"
import * as Gemini from "../src/protocols/gemini.js"
import * as OpenAIChat from "../src/protocols/openai-chat.js"
@@ -107,26 +107,6 @@ describe("applyCachePolicy", () => {
}),
)
it.effect("'auto' emits Anthropic cache markers on Anthropic-compatible routes", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: AnthropicCompatible.configure({ apiKey: "test", baseURL: "https://messages.example.test/v1" }).model(
"compatible",
),
system: "You are concise.",
prompt: "hi",
}),
)
expect(prepared.route).toBe("anthropic-compatible-messages")
expect(prepared.body).toMatchObject({
system: [{ type: "text", text: "You are concise.", cache_control: { type: "ephemeral" } }],
messages: [{ role: "user", content: [{ type: "text", text: "hi", cache_control: { type: "ephemeral" } }] }],
})
}),
)
it.effect("'auto' is a no-op on OpenAI (implicit caching protocol)", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
-24
View File
@@ -351,34 +351,10 @@ 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}`, () =>
+1 -2
View File
@@ -39,18 +39,17 @@ describe("experimental Evaluation", () => {
type: "choice",
choice: "billing",
probabilities: { billing: 0.9, technical: 0.1 },
confidence: 0.8,
})
expect(response.answers.urgency).toEqual({
type: "score",
score: 1.2,
probabilities: { "0": 0, "1": 0.8, "2": 0.2 },
confidence: 0.6,
})
expect(response.answers.refund).toEqual({ type: "boolean", probability: 0.97 })
expect(response.usage?.totalTokens).toBe(36)
expect(response.providerMetadata).toEqual({
typesafe: {
confidence: { department: 0.8, urgency: 0.6 },
legend: { urgency: { "0": "Can wait", "1": "Needs attention", "2": "Blocking" } },
},
})
-2
View File
@@ -26,10 +26,8 @@ const request = Evaluation.request({
const result = EvaluationClient.evaluate(request)
type Result = Success<typeof result>
type Choice = Assert<Equal<Result["answers"]["topic"]["choice"], "billing" | "support">>
type Confidence = Assert<Equal<Result["answers"]["topic"]["confidence"], number | undefined>>
type ClientRequirements = Assert<Equal<Requirements<typeof result>, Service>>
void (true satisfies Choice)
void (true satisfies Confidence)
void (true satisfies ClientRequirements)
Effect.gen(function* () {
+3 -49
View File
@@ -273,56 +273,10 @@ describe("RequestExecutor", () => {
expectAIError(error)
expect(error.reason).toMatchObject({ _tag: "InvalidRequest" })
expect("classification" in error.reason ? error.reason.classification : undefined).toBeUndefined()
expect(error.message).toBe("Provider request failed with HTTP 400: invalid parameter")
expect(error.message).toBe("Provider request failed with HTTP 400")
}).pipe(Effect.provide(fixedResponse("invalid parameter", { status: 400 }))),
)
it.effect("shows unrecognized provider error bodies", () =>
Effect.gen(function* () {
const executor = yield* RequestExecutor.Service
const error = yield* executor.execute(request).pipe(Effect.flip)
expect(error.message).toBe(
'Provider request failed with HTTP 422: {"object":"error","message":{"detail":[{"msg":"Input should be less than or equal to 1.5"}]}}',
)
}).pipe(
Effect.provide(
fixedResponse('{"object":"error","message":{"detail":[{"msg":"Input should be less than or equal to 1.5"}]}}', {
status: 422,
}),
),
),
)
it.effect("shows messages from common provider error layouts", () =>
Effect.gen(function* () {
const executor = yield* RequestExecutor.Service
const error = yield* executor.execute(request).pipe(Effect.flip)
expect(error.message).toBe("Invalid API Key")
}).pipe(Effect.provide(fixedResponse('{"detail":"Invalid API Key"}', { status: 401 }))),
)
it.effect("truncates long unrecognized provider error bodies", () =>
Effect.gen(function* () {
const executor = yield* RequestExecutor.Service
const error = yield* executor.execute(request).pipe(Effect.flip)
expect(error.message).toBe(`Provider request failed with HTTP 400: ${"x".repeat(2000)}…`)
expect(error.reason.body).toHaveLength(5000)
}).pipe(Effect.provide(fixedResponse("x".repeat(5000), { status: 400 }))),
)
it.effect("does not show HTML error pages", () =>
Effect.gen(function* () {
const executor = yield* RequestExecutor.Service
const error = yield* executor.execute(request).pipe(Effect.flip)
expect(error.message).toBe("Provider request failed with HTTP 502")
expect(error.reason.body).toContain("Bad Gateway")
}).pipe(Effect.provide(fixedResponse("<!DOCTYPE html><html><body>Bad Gateway</body></html>", { status: 502 }))),
)
it.effect("preserves structured provider messages from large error bodies", () =>
Effect.gen(function* () {
const executor = yield* RequestExecutor.Service
@@ -345,7 +299,7 @@ describe("RequestExecutor", () => {
),
)
it.effect("shows the body when structured provider messages are empty", () =>
it.effect("falls back when structured provider messages are empty", () =>
Effect.gen(function* () {
const executor = yield* RequestExecutor.Service
const error = yield* executor.execute(request).pipe(Effect.flip)
@@ -354,7 +308,7 @@ describe("RequestExecutor", () => {
expect(error.reason).toMatchObject({
_tag: "InvalidRequest",
})
expect(error.message).toBe('Provider request failed with HTTP 400: {"error":{"message":" "}}')
expect(error.message).toBe("Provider request failed with HTTP 400")
}).pipe(Effect.provide(fixedResponse('{"error":{"message":" "}}', { status: 400 }))),
)
+2 -51
View File
@@ -23,7 +23,6 @@ import { Provider as ProviderSubpath } from "@opencode/ai/provider"
import {
AssemblyAI,
Baseten,
BlackForestLabs,
Cartesia,
CloudflareAIGateway,
CloudflareWorkersAI,
@@ -33,18 +32,14 @@ import {
Fal,
Fireworks,
Google,
Meta,
OpenCodeZen,
OpenAI,
OpenAICompatible,
OpenRouter,
Replicate,
Runway,
Stability,
TypeSafeAI,
VercelAIGateway,
XAI,
ZAI,
} from "@opencode/ai/providers"
import {
OpenAIChat,
@@ -59,19 +54,6 @@ 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()
@@ -154,36 +136,10 @@ describe("public exports", () => {
expect(XAI.model).toBeFunction()
expect(XAI.provider.responses).toBe(XAI.responses)
expect(XAI.provider.chat).toBe(XAI.chat)
expect(XAI.configure({ apiKey: "fixture" }).responses("grok-4.3").route.id).toBe("xai-responses")
expect(XAI.configure({ apiKey: "fixture" }).chat("grok-4.3").route.id).toBe("xai-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" }).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(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")
@@ -197,11 +153,6 @@ 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", () => {
@@ -1,34 +0,0 @@
{
"version": 1,
"metadata": {
"tags": [
"prefix:bedrock-converse-thinking-binding",
"provider:amazon-bedrock",
"protocol:bedrock-converse",
"reasoning"
],
"name": "bedrock-converse-thinking-binding/accepts-the-default-binding-with-no-thinking-configured",
"recordedAt": "2026-09-28T23:09:14.527Z"
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://bedrock-runtime.us-east-1.amazonaws.com/model/global.anthropic.claude-opus-5-5/converse-stream",
"headers": {
"content-type": "application/json"
},
"body": "{\"modelId\":\"global.anthropic.claude-opus-5-5\",\"messages\":[{\"role\":\"user\",\"content\":[{\"text\":\"Say hello.\"}]}],\"system\":[{\"text\":\"Reply with the single word 'Hello'.\"}],\"inferenceConfig\":{\"maxTokens\":1024},\"additionalModelRequestFields\":{\"thinking\":{\"type\":\"adaptive\",\"block_binding\":{\"prefix_mismatch_behavior\":\"drop_block\"}},\"anthropic_beta\":[\"thinking-binding-controls-2026-08-01\"]}}"
},
"response": {
"status": 200,
"headers": {
"content-type": "application/vnd.amazon.eventstream"
},
"body": "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",
"bodyEncoding": "base64"
}
}
]
}
@@ -1,32 +0,0 @@
{
"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"
},
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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.\"}]},{\"type\":\"reasoning\",\"id\":\"rs_0a6277dd90b94da1016aa8c946e33487d1b725d8e9dc874d82\",\"summary\":[],\"encrypted_content\":\"gAAAAABqqMlHtG6yltzgW_UjUcYxvl2hoMkk7cSEH5SJMe9CR5gKIaCwCh4peUo8XZrd-EU-tPCXthv7JzHxYXGVG1fIgTJ7BjBoOh-jgd_oGlyCHj2jVPj7nVoB763tZHdyw_ovL3V7GpJ6VeLGIsRGqNTnBz47ZuKikTKrbTDupn6fT2wOM_69zwdg4-UVnoF2J9E_jIS0E5XRtRwOidqANl61HCwo7LV-Ut1aqCbXb-59vkrVGWPxD_8n4smf7Qjywc0FCH9zwuEDX4cPdqj3MmjvYPrn0jand9LKkAy9rblaKFJSQfVuritbHrdQrnF7hLxu7QCpehOzNXOkpNEqTmXnAZjfMc53hq-ahH6_KoyYlZpompwyGPngFeI2fKRqP8rlpDilD1BHBsh-bl7kXzI8HQ_jameXwPZ1La6gjtFkThXp53BD6BOx11SB9Nypqolu2at5rR32UYcGrYeGtTu-HmYGp0oHVFkHumTNuHKmGXV14dI9swgryfygLhX8EAJrWrjm3e8rvAkHKpAZ0IkmlCcp15UCFDKNeS560fQVRaKXWnQ7m0Ih3C1xG0ifJ89j27c8GHo1kAhEJk-lSB1-FZr9Ls_w7N772kmZ2a7LLswu3kNW78kPas_CtcOnBOHwE1DhcVh5YpxwNftOHZnK1v8NPNF8EWqio4ArZy1thMCzH5zXBNcFzgd8tePMFukBblSP8QGQoVYRqTne2sFoOZXjslXnDvEe-Ycj8X38zWgRiwAk7guOloFC7Se36KCDP357773Vah86gWCt55mSEyhVW_GF1oTuHvJ18GZsXcyN21scF1PSr8YaCM_jR7ZkU1GYXbQK2Y4oTAV9XDptQA5YzEREnn7muC_6v5ZTAglZF1lhn9Q0NwmylZEAXJdSGHaqXt1Hv-vQlprA_9m22vrreBOTLPnVK946J8absKrwfe-jK_1n_9YQR43uwH8XwFBFND0c4lICCQGbxwM8pX4ACWR0c19aORCYm-M5FrJsxmG29_aDVNhcvkoQ3mlP7ITQeqzkrjfytSwLb2BYpXYZKjEHNfV9j3JoxJobUkK5hrxXBhTvZzbVBnE0LSXQNwR-JAcOliP_jXBEeQ-28B-aGW8TI1vEP2i260QKgzOzPC-pOoFp0-vCvxojNO0kE16ECVTLfDNLNGSMZs9vekdLJP2akBp6PsUXsQUTbWO_wr1E2oNU7ctfMRxoh-yP0ZW2_xz_NjE72O5LF_6zuDVV7Q==\"},{\"type\":\"message\",\"id\":\"msg_0a6277dd90b94da1016aa8c947253887d184c150fcbcbcd8da\",\"role\":\"assistant\",\"content\":[{\"type\":\"output_text\",\"text\":\"Alpha.\"}],\"phase\":\"final_answer\",\"status\":\"completed\"},{\"type\":\"message\",\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"Reply exactly: Beta.\"}]}],\"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}"
},
{
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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\":\"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}"
"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}"
},
{
"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\"},\"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\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":30,\"previous_response_id\":\"resp_01cc0cda24c36acf016aa8ca3c1d3c87d1853283f43675e411\"}"
},
{
"direction": "server",
@@ -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}"
"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\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":30}"
},
{
"direction": "server",
File diff suppressed because one or more lines are too long
@@ -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\"},\"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\"},\"text\":{\"verbosity\":\"low\"},\"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\"},\"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\"},\"text\":{\"verbosity\":\"low\"},\"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\"},\"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\"},\"text\":{\"verbosity\":\"low\"},\"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\"},\"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\"},\"text\":{\"verbosity\":\"low\"},\"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\"},\"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\"},\"text\":{\"verbosity\":\"low\"},\"max_output_tokens\":80,\"stream\":true}"
},
"response": {
"status": 200,
-20
View File
@@ -97,26 +97,6 @@ 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")

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