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instrumentation for Anthropic","maintainers":[{"name":"mikeldking","email":"mikeldking@gmail.com"},{"name":"parker-stafford","email":"parker.stafford92@gmail.com"},{"name":"remiarize","email":"remi@arize.com"},{"name":"cephalization","email":"powell.anthonyd@proton.me"},{"name":"jackyxcs","email":"jacky@arize.com"}],"readme":"# OpenInference Anthropic Instrumentation\n\nJavaScript auto-instrumentation library for the [Anthropic](https://www.anthropic.com/) SDK\n\nThis package implements OpenInference tracing for the following Anthropic SDK methods:\n\n- `messages.create` (including streaming)\n- `beta.messages.create` (including server-side fallback and streaming)\n\nThese traces are fully OpenTelemetry compatible and can be sent to an OpenTelemetry collector for viewing, such as [Arize Phoenix](https://github.com/Arize-ai/phoenix) or [Arize AX](https://arize.com/products/ax?utm_source=docs&utm_medium=web&utm_content=openinference).\n\n## Installation\n\n```shell\nnpm install @arizeai/openinference-instrumentation-anthropic\n```\n\n## Quickstart\n\nInstall required packages:\n\n```shell\nnpm install @arizeai/openinference-instrumentation-anthropic @arizeai/openinference-semantic-conventions @anthropic-ai/sdk @opentelemetry/sdk-node @opentelemetry/exporter-trace-otlp-proto @opentelemetry/sdk-trace-node @opentelemetry/semantic-conventions\n```\n\nSet up instrumentation in your application:\n\n```typescript\nimport { NodeSDK, resources } from \"@opentelemetry/sdk-node\";\nimport { AnthropicInstrumentation } from \"@arizeai/openinference-instrumentation-anthropic\";\nimport { OTLPTraceExporter } from \"@opentelemetry/exporter-trace-otlp-proto\";\nimport { SimpleSpanProcessor } from \"@opentelemetry/sdk-trace-node\";\nimport { ATTR_SERVICE_NAME } from \"@opentelemetry/semantic-conventions\";\nimport { SEMRESATTRS_PROJECT_NAME } from \"@arizeai/openinference-semantic-conventions\";\n\nimport Anthropic from \"@anthropic-ai/sdk\";\n\n// Configure the SDK with Anthropic instrumentation\nconst instrumentation = new AnthropicInstrumentation({\n  // Optional: configure trace settings\n  traceConfig: {\n    // hideInputs: true,\n    // hideOutputs: true,\n  },\n});\n// necessary when instrumenting in an ESM environment\ninstrumentation.manuallyInstrument(Anthropic);\nconst sdk = new NodeSDK({\n  spanProcessors: [\n    new SimpleSpanProcessor(\n      new OTLPTraceExporter({\n        url: \"http://localhost:6006/v1/traces\",\n      }),\n    ),\n  ],\n  resource: resources.resourceFromAttributes({\n    [ATTR_SERVICE_NAME]: \"anthropic-service\",\n    [SEMRESATTRS_PROJECT_NAME]: \"anthropic-service\",\n  }),\n  instrumentations: [instrumentation],\n});\n\n// Initialize the SDK\nsdk.start();\n\n// Now use Anthropic as normal\n\nconst anthropic = new Anthropic({\n  apiKey: process.env.ANTHROPIC_API_KEY,\n});\n\nconst message = await anthropic.messages.create({\n  model: \"claude-3-5-haiku-latest\",\n  max_tokens: 1000,\n  messages: [{ role: \"user\", content: \"Hello, Claude!\" }],\n});\n\nconsole.log(message.content);\n\nsdk.shutdown();\n```\n\n## Configuration\n\nThe `AnthropicInstrumentation` constructor accepts the following options:\n\n- `instrumentationConfig`: Standard OpenTelemetry instrumentation configuration\n- `traceConfig`: OpenInference-specific trace configuration for masking/redacting sensitive information\n- `tracerProvider`: Optional custom tracer provider\n\n## Supported Features\n\n- **Messages API**: Full support for `anthropic.messages.create()`\n- **Beta Messages API**: Full support for `anthropic.beta.messages.create()`\n- **Server-Side Fallback**: Captures requested and serving models across fallback boundaries, records the `fallback` handoff (declining model and refusal category) as message content, and takes token counts from the attempt that served the response\n- **Refusals**: Records `llm.finish_reason`, so a classifier decline (`stop_reason: \"refusal\"`) is visible on the span\n- **Streaming**: Automatic handling of streaming responses\n- **Tool Use**: Captures tool/function calling information\n- **Token Usage**: Records input/output token counts when available\n- **Error Handling**: Proper error recording and span status management\n\n## Semantic Conventions\n\nThis instrumentation follows the [OpenInference semantic conventions](https://github.com/Arize-ai/openinference/blob/main/spec/semantic_conventions.md) for LLM observability, capturing:\n\n- Model name and provider information\n- Input/output messages and content\n- Token usage statistics\n- Tool calling details\n- Invocation parameters\n\n## Examples\n\nTo run an example, run the following commands:\n\n```shell\ncd js/packages/openinference-instrumentation-anthropic\npnpm install\npnpm -r build\npnpx tsx examples/basic-usage.ts # or streaming.ts, tool-use.ts, etc\n```\n\nSee the [examples](./examples) directory for more detailed usage examples.\n\nTo exercise server-side fallback:\n\n```shell\nexport ANTHROPIC_API_KEY=your-api-key\n\n# Real Anthropic beta request that triggers a reasoning-extraction fallback\npnpm exec tsx examples/server-side-fallback.ts\n\n# Deterministic SSE fixture that guarantees a mid-stream fallback boundary\npnpm exec tsx examples/server-side-fallback-streaming.ts\n```\n\n## License\n\nApache-2.0\n","readmeFilename":"README.md"}