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runtime, providers, streaming, and framework adapters extracted from AbsoluteJS","maintainers":[{"name":"alexkahndev","email":"alexkahn2019@gmail.com"}],"readme":"# @absolutejs/ai\n\nStandalone AI runtime and provider package extracted from AbsoluteJS.\n\nThis package currently focuses on generic AI/chat/provider functionality.\nRAG remains a separate package.\n\n## Anthropic hosted web search\n\nThe Anthropic provider can request native hosted web search without a custom\nclient tool. Search blocks are replayable provider data, citations are emitted\nas portable `citation` chunks, usage includes `serverToolUse`, and\n`streamAIWithTools` continues `pause_turn` responses automatically.\n\n```ts\nconst result = await generateAI({\n  provider: anthropic({ apiKey: process.env.ANTHROPIC_API_KEY }),\n  model: \"claude-sonnet-4-6\",\n  messages: [{ role: \"user\", content: \"What changed today?\" }],\n  providerOptions: {\n    anthropic: {\n      serverTools: [\n        {\n          type: \"anthropic:web_search\",\n          parameters: { maxUses: 3 },\n        },\n      ],\n    },\n  },\n});\n```\n\nProvider traffic can cross a trusted control plane without reimplementing a\nvendor protocol. `remoteProvider()` carries normalized provider parameters and\nchunks over SSE, while `createProviderProxyResponse()` hosts any\n`AIProviderConfig` with pre-first-token and inter-token heartbeats. Provider\ncallbacks and abort objects never cross the wire. The Anthropic provider also\naccepts an injectable `fetch`, allowing hosts to retain egress policy, tracing,\nand test transports.\n\n## Conversation turn queues and branches\n\n`aiChat()` serializes turns per conversation. A member may submit follow-ups\nwhile a response is streaming: the server emits `turn_queued`, then\n`turn_started` when that turn becomes active. Every framework adapter sends a\nstable client message ID, and its message state exposes `isQueued` for UI.\n\n`branch(messageId, content)` creates a new conversation through the selected\nmessage and immediately runs `content` as the first turn on that branch. The\ntyped `branched` event switches the client to the new conversation.\n\n`edit(messageId, content)` creates a new conversation through the history before\nthe selected user message, replaces that message with `content`, and runs it\nagain. The original conversation remains unchanged, matching the edit behavior\nof modern AI chat interfaces without rewriting conversation history.\n\nCustom REST/SSE hosts can use the same ordering primitive:\n\n```ts\nimport { createConversationTurnQueue } from \"@absolutejs/ai/client\";\n\nconst queue = createConversationTurnQueue({\n  execute: async (turn, { signal }) => runTurn(turn, signal),\n});\n\nqueue.enqueue({ content: \"First\" });\nqueue.enqueue({ content: \"Send this after the first reply\" });\n```\n\nFailures stop later turns from overtaking the failed message. The host must\nexplicitly retry or remove it. `subscribe()` exposes immutable queue snapshots\nfor framework-independent UI.\n\n## SSE event stream (`streamAIToSSE`)\n\n`streamAIToSSE` yields `{ event, data }` SSE frames. By default `data` is\npre-rendered HTML from the renderers, and the terminal `status` event is\noverloaded across completion, budget stops, and errors — a headless consumer has\nto sniff `ai-usage` vs `ai-error` out of the HTML to tell them apart.\n\nPass `structuredEvents: true` to get typed, machine-readable frames instead: each\n`data` is JSON (parse it), and the overloaded terminal splits into three distinct\nevent names:\n\n| event      | when                    | `JSON.parse(data)`                                          |\n| ---------- | ----------------------- | ----------------------------------------------------------- |\n| `content`  | text delta              | `{ delta, full }`                                           |\n| `thinking` | reasoning delta         | `{ text }` (accumulated)                                    |\n| `tools`    | one per tool transition | `{ name, status: \"running\" \\| \"complete\", input, result? }` |\n| `images`   | generated image         | `{ data, format, revisedPrompt? }`                          |\n| `complete` | normal completion       | `{ usage, durationMs, model }`                              |\n| `stopped`  | ceiling / limit / abort | `{ reason, detail }`                                        |\n| `error`    | thrown / lookup error   | `{ message }`                                               |\n| `ping`     | heartbeat keepalive     | `\"\"` (unchanged)                                            |\n\n`stopped.reason` is one of `\"max_total_tokens\" | \"max_duration_ms\" | \"max_tokens\"\n| \"max_turns\" | \"aborted\"`. Exactly one terminal (`complete` / `stopped` /\n`error`) fires on every path — including an externally aborted loop, which now\nemits `stopped` with `reason: \"aborted\"` rather than masquerading as a\ncompletion. Payload types are exported (`AISSECompletePayload`,\n`AISSEStoppedPayload`, `AISSEErrorPayload`, `AISSEContentPayload`, …).\n\nThe default (HTML) path is unchanged for the built-in HTMX/default UI, except an\nabort now renders the (previously unused) `canceled` renderer instead of a\nmisleading usage chip.\n\n## OpenRouter\n\n`@absolutejs/ai/openrouter` uses the shared provider contract and\nOpenAI-compatible stream parser while adding OpenRouter-specific routing,\nattribution, cost metadata, and local model-policy enforcement.\n\n```ts\nimport { openrouter } from \"@absolutejs/ai/openrouter\";\n\nconst provider = openrouter({\n  apiKey: process.env.OPENROUTER_API_KEY,\n  appName: \"My AbsoluteJS App\",\n  appUrl: \"https://example.com\",\n  // Exact IDs and namespace wildcards are supported. A disallowed model fails\n  // locally before any request reaches OpenRouter.\n  allowedModels: [\"anthropic/*\", \"google/*\", \"mistralai/*\", \"openai/*\"],\n  // This becomes provider.only, so OpenRouter cannot select another inference\n  // provider during fallback.\n  allowedProviders: [\"anthropic\", \"google-vertex\", \"mistral\", \"openai\"],\n  routing: {\n    dataCollection: \"deny\",\n    maxPrice: { prompt: 3, completion: 15 },\n    requireParameters: true,\n    sort: \"price\",\n    zdr: true,\n  },\n});\n```\n\nThe adapter intentionally has no built-in geopolitical model list. Omitting\n`allowedModels` exposes the full OpenRouter catalog; applications that need a\nrestricted catalog can define their own `allowedModels` and `allowedProviders`\npolicy. Auto Router is fully supported with `openrouter/auto` (or\n`openrouter/auto-beta`), a sticky `sessionId`, and its typed plugin controls:\n\n```ts\nconst provider = openrouter({\n  apiKey: process.env.OPENROUTER_API_KEY,\n  // Omit this for unrestricted access to every OpenRouter model.\n  allowedModels: [\"openrouter/auto\", \"anthropic/*\", \"openai/*\"],\n  requestOptions: {\n    sessionId: conversationId,\n    plugins: [\n      {\n        id: \"auto-router\",\n        cost_tier: \"low\",\n        allowed_models: [\"anthropic/*\", \"openai/*\"],\n      },\n    ],\n  },\n});\n```\n\nUnder a strict policy, Auto Router's `allowed_models` is checked locally along\nwith fallback, Fusion, advisor, subagent, and other indirectly selected models.\n\nProvider usage callbacks include OpenRouter's reported `costCredits`,\n`upstreamInferenceCostCredits`, cache-read/write token counts, and reasoning\ntokens when those fields are present in the final streaming usage message.\nHosted-tool counters are exposed as `serverToolUse`.\n\nOpenRouter-specific features are available per request without weakening the\nportable provider contract:\n\n```ts\nawait generateAI({\n  provider,\n  model: \"anthropic/claude-sonnet-4.6\",\n  messages,\n  providerOptions: {\n    openrouter: {\n      fallbackModels: [\"openai/gpt-5.2\"],\n      sessionId: conversationId, // sticky routing improves prompt-cache hits\n      serviceTier: \"flex\", // cheaper, slower capacity when available\n      responseCache: { enabled: true, ttlSeconds: 300 },\n      trace: { trace_id: workflowId, generation_name: \"support-answer\" },\n      serverTools: [\n        { type: \"openrouter:web_search\", parameters: { max_results: 3 } },\n      ],\n      maxToolCalls: 5,\n      stopServerToolsWhen: [{ type: \"max_cost\", value: 0.02 }],\n    },\n  },\n});\n```\n\nOther typed request options include presets, plugins, per-call provider routing,\nmessage transforms, native reasoning controls, prompt and response caching,\ntext-plus-audio output, verbosity, user attribution, and an `extraBody` escape\nhatch for new OpenRouter parameters. The escape hatch cannot replace models,\nfallbacks, providers, presets, messages, plugins, or tools; those fields use\npolicy-aware typed options instead. Advisor, Fusion, Shell, Subagent, model\nsearch, web search/fetch, image generation, Datetime, and Apply Patch server\ntools have typed wire parameters and documented range checks. OpenRouter's old\n`web` plugin is deprecated; use `openrouter:web_search` instead.\n\nURL images and PDFs, base64 audio, and URL/base64 video inputs use the ordinary\nAbsoluteJS content-block contract. URL citations are emitted as `citation`\nchunks. The final `done` chunk includes the generation ID, resolved model,\nselected inference provider, service tier, cache headers, and OpenRouter router\nmetadata when reported.\n\n### OpenRouter platform client\n\n`createOpenRouterClient()` covers model/provider discovery, embeddings,\nreranking, streamed and non-streamed image generation, reusable files,\nResponses, speech, typed transcription, video jobs and downloads, beta batches,\npresets, workspaces and budgets, activity/analytics, task classifications,\ncredits, key metadata, and generation content. It also exports\n`verifyOpenRouterWebhookSignature()` for video completion webhooks. Its typed\noperations enforce the same model allowlist. `request()` and `requestRaw()` are\nforward-compatible access to new or administrative OpenRouter endpoints.\nUser-filtered model discovery and ZDR endpoint previews honor the local model\npolicy, so catalog UIs cannot accidentally reintroduce filtered models.\n\n```ts\nimport { createOpenRouterClient } from \"@absolutejs/ai/openrouter\";\n\nconst openrouterClient = createOpenRouterClient({\n  apiKey: process.env.OPENROUTER_API_KEY,\n  allowedModels: [\"anthropic/*\", \"google/*\", \"mistralai/*\", \"openai/*\"],\n});\n\nconst models = await openrouterClient.listModels({\n  output_modalities: \"all\",\n  sort: \"pricing-low-to-high\",\n});\nconst embedding = await openrouterClient.createEmbedding({\n  model: \"openai/text-embedding-3-small\",\n  input: \"AbsoluteJS supports OpenRouter\",\n});\nconst reranked = await openrouterClient.rerank({\n  model: \"openai/text-embedding-3-small\",\n  query: \"cost controls\",\n  documents: [\"response caching\", \"CSS layout\"],\n});\n\n// Response healing is documented for non-streaming structured responses.\nconst healed = await openrouterClient.chat({\n  model: \"anthropic/claude-sonnet-4.6\",\n  messages: [{ role: \"user\", content: \"Return a JSON object\" }],\n  response_format: { type: \"json_object\" },\n  plugins: [{ id: \"response-healing\" }],\n});\n\nconst batch = await openrouterClient.createBatch({\n  endpoint: \"/v1/chat/completions\",\n  model: \"anthropic/claude-sonnet-4.6\",\n  requests: [\n    { custom_id: \"one\", body: { messages: [{ role: \"user\", content: \"Hi\" }] } },\n  ],\n});\nconst completed = await openrouterClient.waitForBatch(batch.id, {\n  signal: abortController.signal,\n  timeoutMs: 60_000,\n});\n```\n\nBatch traffic uses OpenRouter's separate `/api/beta/batches` API and returns\ninline typed results. `estimateOpenRouterModelCost()` calculates prompt,\ncompletion, request, image, web-search, reasoning, and cache costs directly from\nmodel-discovery pricing fields.\n\nOAuth helpers cover S256 PKCE, web and headless authorization URLs, code\nexchange, authenticated code creation, and user key deep-links:\n\n```ts\nconst pkce = await generateOpenRouterPKCE();\nconst authorizationUrl = createOpenRouterAuthorizationUrl({\n  callbackUrl: \"https://example.com/openrouter/callback\",\n  codeChallenge: pkce.codeChallenge,\n  codeChallengeMethod: pkce.codeChallengeMethod,\n});\n\nconst { key } = await exchangeOpenRouterAuthCode({\n  code,\n  code_verifier: pkce.codeVerifier,\n  code_challenge_method: pkce.codeChallengeMethod,\n});\n```\n\n### Complete OpenRouter management SDK\n\nThe inference adapter stays small and policy-aware. The separate\n`@absolutejs/ai/openrouter/sdk` entry point configures and exposes OpenRouter's\nofficial OpenAPI-generated TypeScript SDK for the complete administrative and\ndata surface:\n\n```ts\nimport { createOpenRouterSDK } from \"@absolutejs/ai/openrouter/sdk\";\n\nconst openrouterAdmin = createOpenRouterSDK({\n  tokenSource: getRotatingManagementKey,\n  appName: \"My AbsoluteJS App\",\n  appUrl: \"https://example.com\",\n  timeoutMs: 15_000,\n  retryConfig: { strategy: \"backoff\" },\n});\n\nconst keys = await openrouterAdmin.apiKeys.list();\nconst guardrails = await openrouterAdmin.guardrails.list();\nconst embeddingModels = await openrouterAdmin.embeddings.listModels();\n```\n\nThis entry point includes API-key management, BYOK, guardrails and assignments,\nobservability destinations, organizations, SCIM, workspaces, public datasets,\nbenchmarks, typed pagination, retries, per-call timeouts, and abort signals. It\ntracks compatible patch releases of OpenRouter's generated SDK so new OpenAPI\nfields do not depend on a handwritten AbsoluteJS type update. Normal\n`@absolutejs/ai/openrouter` imports do not load this management surface.\n\nFor a strict model-origin policy, also assign an OpenRouter key/workspace\nguardrail with the same model allowlist. Provider allowlists restrict where a\nmodel runs; they do not identify who developed it. Presets and router aliases\nmust be explicitly allowed, because their resolved model is controlled outside\nthe request. The raw client is intentionally unopinionated and should be limited\nto trusted server-side administration code. OpenRouter currently documents\nreporting generation feedback through Chatroom and Logs, not through a public\nfeedback API, so AbsoluteJS exposes generation IDs/content without inventing an\nunstable endpoint.\n\nUse `openrouterResponses(config)` when an AbsoluteJS agent should stream through\nOpenRouter's stateless Responses API, or `openrouterMessages(config)` for the\nnative Anthropic Messages protocol. Both accept the same model/provider policies\nand `providerOptions.openrouter` controls, including replayable hosted-tool data.\n","readmeFilename":"README.md"}