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provider adapters for Reactive Agents — Anthropic, OpenAI, Ollama, and test providers","maintainers":[{"name":"tylerbuell","email":"tylerjrbuell@gmail.com"}],"readme":"# @reactive-agents/llm-provider\n\n> Version: **0.10.3** — LLM provider adapters for [Reactive Agents](https://docs.reactiveagents.dev/).\n\nA unified `LLMService` interface (`complete`, `stream`, `embed`, structured output) with adapters\nfor **Anthropic**, **OpenAI**, **Google Gemini**, **Groq**, **xAI (Grok)**, **Ollama**, **LiteLLM**,\nand a deterministic **test** provider. Groq and xAI are OpenAI-compatible and share the\n`makeOpenAICompatProvider` factory. Includes provider behavior adapters, calibration,\nretry/circuit-breaker/rate limiting, and a fallback chain.\n\n## Installation\n\n```bash\nbun add @reactive-agents/llm-provider\n```\n\nInstall the SDK for your chosen provider:\n\n```bash\nbun add @anthropic-ai/sdk           # Anthropic Claude\nbun add openai                      # OpenAI GPT-4o, o1 — also Groq & xAI (OpenAI-compatible)\nbun add @google/genai               # Google Gemini\n# Groq, xAI, Ollama, and LiteLLM use OpenAI-compatible / plain HTTP — reuse the openai SDK or none.\n```\n\n## Supported providers\n\n| Provider    | Streaming | Native FC | Embeddings | Structured output | Notes |\n|-------------|-----------|-----------|------------|-------------------|-------|\n| `anthropic` | ✓         | ✓         | —          | ✓                 | claude-sonnet-4, claude-haiku-4-5, claude-opus-4 |\n| `openai`    | ✓         | ✓         | ✓          | ✓                 | gpt-4o, gpt-4o-mini, o1-* |\n| `gemini`    | ✓         | ✓         | ✓          | ✓                 | gemini-2.0-flash, gemini-2.5-pro |\n| `ollama`    | ✓         | ✓         | ✓          | ✓                 | any local model; thinking opt-in |\n| `litellm`   | ✓         | ✓         | ✓          | ✓                 | proxy to 100+ providers |\n| `test`      | ✓         | ✓         | ✓          | —                 | deterministic mock for unit tests |\n\nDefault model per provider is exposed via `getProviderDefaultModel(provider)` /\n`PROVIDER_DEFAULT_MODELS`.\n\n## Usage\n\n### Anthropic\n\n```typescript\nimport { createLLMProviderLayer, LLMService } from \"@reactive-agents/llm-provider\";\nimport { Effect } from \"effect\";\n\nconst layer = createLLMProviderLayer(\"anthropic\");\n\nconst result = await Effect.runPromise(\n  Effect.gen(function* () {\n    const llm = yield* LLMService;\n    return yield* llm.complete({\n      messages: [{ role: \"user\", content: \"Hello!\" }],\n      model: { provider: \"anthropic\", model: \"claude-sonnet-4-6\" },\n    });\n  }).pipe(Effect.provide(layer)),\n);\n```\n\n### Google Gemini\n\n```typescript\nimport { createLLMProviderLayer, LLMService } from \"@reactive-agents/llm-provider\";\nimport { Effect } from \"effect\";\n\n// Set GOOGLE_API_KEY in your environment\nconst layer = createLLMProviderLayer(\"gemini\");\n\nconst out = await Effect.runPromise(\n  Effect.gen(function* () {\n    const llm = yield* LLMService;\n    return yield* llm.complete({\n      messages: [{ role: \"user\", content: \"Explain quantum entanglement.\" }],\n      model: { provider: \"gemini\", model: \"gemini-2.5-pro\" },\n    });\n  }).pipe(Effect.provide(layer)),\n);\n```\n\n### Streaming\n\n```typescript\nconst events = yield* llm.stream({\n  messages: [{ role: \"user\", content: \"Write a haiku.\" }],\n  model: { provider: \"anthropic\", model: \"claude-haiku-4-5-20251001\" },\n});\nfor await (const ev of events) {\n  if (ev.type === \"text-delta\") process.stdout.write(ev.text);\n  if (ev.type === \"tool-use-start\") console.log(\"→ tool:\", ev.name);\n}\n```\n\n## Native function calling\n\nAll providers receive `tools` on **both** `complete()` and `stream()` calls and emit normalized\n`tool_use_start` / `tool_use_delta` events. Provider-specific quirks handled internally:\n\n- **Anthropic streaming** uses raw `streamEvent` (not helper events) to capture `inputJson`\n  before `contentBlock`.\n- **Gemini** walks `candidates[0].content.parts[]` directly (`chunk.text` strips functionCall\n  parts) and surfaces non-OK `finishReason` as explicit errors.\n- **Ollama streaming** flushes `chunk.message.tool_calls` on `chunk.done`.\n\n## Environment variables\n\n```bash\nANTHROPIC_API_KEY=sk-ant-...\nOPENAI_API_KEY=sk-...\nGOOGLE_API_KEY=...\nOLLAMA_ENDPOINT=http://localhost:11434\nLITELLM_BASE_URL=http://localhost:4000\nLITELLM_API_KEY=...\n```\n\n`llmConfigFromEnv` / `LLMConfigFromEnv` build `LLMConfig` from the environment automatically.\n\n## Model presets\n\n```typescript\nimport { ModelPresets } from \"@reactive-agents/llm-provider\";\n\nconst preset = ModelPresets[\"claude-sonnet-4\"];\n// { provider, model, costPer1MInput, costPer1MOutput, ... }\n```\n\n## Provider behavior adapters\n\nPer-tier hooks compose to give each provider/model the right prompting and recovery behavior.\nSeven hooks fire across the kernel lifecycle:\n\n| Hook | Purpose |\n|---|---|\n| `taskFraming` | Reframe task per provider/tier conventions |\n| `toolGuidance` | Inject tool-use guidance and exemplars |\n| `continuationHint` | Encourage long responses to keep going |\n| `errorRecovery` | Provider-specific repair on tool/parse errors |\n| `synthesisPrompt` | Tweak ICS curator output for the model |\n| `qualityCheck` | Provider-aware verifier hints |\n| `systemPromptPatch` | Final system-prompt patch |\n\n```typescript\nimport { selectAdapter, defaultAdapter, midModelAdapter, localModelAdapter } from \"@reactive-agents/llm-provider\";\n\nconst adapter = selectAdapter({ provider: \"ollama\", model: \"qwen3:14b\" });\n```\n\n## Calibration\n\nA three-tier calibration store records per-(provider, model) measured behavior (latency, alias\nfrequency, success rate) and materializes an `ExperienceSummary` that drives\n`buildCalibratedAdapter` for adaptive prompting.\n\n```typescript\nimport { runCalibrationProbes, buildCalibratedAdapter, loadCalibration } from \"@reactive-agents/llm-provider\";\n```\n\n## Resilience: retry, circuit breaker, rate limit, fallbacks\n\n```typescript\nimport {\n  retryPolicy,\n  makeCircuitBreaker,\n  makeRateLimiter,\n  makeRateLimitedProvider,\n  FallbackChain,\n} from \"@reactive-agents/llm-provider\";\n\nconst fallback = new FallbackChain([primaryLayer, secondaryLayer], {\n  onFallback: (err, idx) => console.warn(`fell through to provider #${idx}:`, err),\n});\n```\n\n## Capability port\n\n`Capability` (per-(provider, model) descriptor) supersedes the deprecated `ProviderCapabilities`\nin v0.10.0; `ProviderCapabilities` remains exported for binary compatibility but is **scheduled\nfor removal in v0.11.0**.\n\n```typescript\nimport { resolveCapability } from \"@reactive-agents/llm-provider\";\nconst cap = await resolveCapability(\"ollama\", \"qwen3:14b\");\n// { tier, contextWindow, supportsTools, toolCallDialect, tokenizer, ... }\n```\n\n## Test provider\n\nFor deterministic testing without API calls:\n\n```typescript\nimport { TestLLMServiceLayer } from \"@reactive-agents/llm-provider\";\n\nconst layer = TestLLMServiceLayer({\n  \"capital of France\": \"Paris is the capital of France.\",\n});\n```\n\nPer-turn tool-call sequences are configured via `TestTurn` / `ToolCallSpec`.\n\n## Documentation\n\n- Provider guide: [docs.reactiveagents.dev/guides/providers/](https://docs.reactiveagents.dev/guides/providers/)\n- Calibration: [docs.reactiveagents.dev/guides/calibration/](https://docs.reactiveagents.dev/guides/calibration/)\n- Related: [`@reactive-agents/runtime`](../runtime/README.md),\n  [`@reactive-agents/reasoning`](../reasoning/README.md),\n  [`@reactive-agents/tools`](../tools/README.md).\n\n## License\n\nMIT\n","readmeFilename":"README.md"}