add-ai-integration

द्वारा sentry

Sentry JavaScript SDK में एक नया AI प्रदाता एकीकरण जोड़ें। नए AI इंस्ट्रुमेंटेशन (OpenAI, Anthropic, Vercel AI, LangChain, आदि) का योगदान करते समय उपयोग करें…

npx skills add https://github.com/getsentry/sentry-javascript --skill add-ai-integration

Adding a New AI Integration

Decision Tree

Does the AI SDK have native OpenTelemetry support?
|- YES -> Does it emit OTel spans automatically?
|   |- YES (like Vercel AI) -> Pattern 1: OTel Span Processors
|   +- NO -> Pattern 2: OTel Instrumentation (wrap client)
+- NO -> Does the SDK provide hooks/callbacks?
    |- YES (like LangChain) -> Pattern 3: Callback/Hook Based
    +- NO -> Pattern 4: Client Wrapping

Runtime-Specific Placement

If an AI SDK only works in one runtime, code lives exclusively in that runtime's package. Do NOT add it to packages/core/.

  • Node.js-only -> packages/node/src/integrations/tracing/{provider}/
  • Cloudflare-only -> packages/cloudflare/src/integrations/tracing/{provider}.ts
  • Browser-only -> packages/browser/src/integrations/tracing/{provider}/
  • Multi-runtime -> shared core in packages/core/src/tracing/{provider}/ with runtime-specific wrappers

Span Hierarchy

  • gen_ai.invoke_agent — parent/pipeline spans (chains, agents, orchestration)
  • gen_ai.chat, gen_ai.generate_text, etc. — child spans (actual LLM calls)

Shared Utilities (packages/core/src/tracing/ai/)

  • gen-ai-attributes.ts — OTel Semantic Convention attribute constants. Always use these, never hardcode.
  • utils.tssetTokenUsageAttributes(), getTruncatedJsonString(), truncateGenAiMessages(), buildMethodPath()
  • Only use attributes from Sentry Gen AI Conventions.

Streaming

  • Non-streaming: startSpan(), set attributes from response
  • Streaming: startSpanManual(), accumulate state via async generator or event listeners, set GEN_AI_RESPONSE_STREAMING_ATTRIBUTE: true, call span.end() in finally block
  • Detect via params.stream === true
  • References: openai/streaming.ts (async generator), anthropic-ai/streaming.ts (event listeners)

Token Accumulation

  • Child spans: Set tokens directly from API response via setTokenUsageAttributes()
  • Parent spans (invoke_agent): Accumulate from children using event processor (see vercel-ai/)

Pattern 1: OTel Span Processors

Use when: SDK emits OTel spans automatically (Vercel AI)

  1. Core: Create add{Provider}Processors() in packages/core/src/tracing/{provider}/index.ts — registers spanStart listener + event processor
  2. Node.js: Add callWhenPatched() optimization in packages/node/src/integrations/tracing/{provider}/index.ts — defers registration until package is imported
  3. Edge: Direct registration in packages/cloudflare/src/integrations/tracing/{provider}.ts — no OTel, call processors immediately

Reference: packages/node/src/integrations/tracing/vercelai/

Pattern 2: OTel Instrumentation (Client Wrapping)

Use when: SDK has no native OTel support (OpenAI, Anthropic, Google GenAI)

  1. Core: Create instrument{Provider}Client() in packages/core/src/tracing/{provider}/index.ts — Proxy to wrap client methods, create spans manually
  2. Node.js instrumentation.ts: Patch module exports, wrap client constructor. Check _INTERNAL_shouldSkipAiProviderWrapping() for LangChain compatibility.
  3. Node.js index.ts: Export integration function using generateInstrumentOnce() helper

Reference: packages/node/src/integrations/tracing/openai/

Pattern 3: Callback/Hook Based

Use when: SDK provides lifecycle hooks (LangChain, LangGraph)

  1. Core: Create create{Provider}CallbackHandler() — implement SDK's callback interface, create spans in callbacks
  2. Node.js instrumentation.ts: Auto-inject callbacks by patching runnable methods. Disable underlying AI provider wrapping.

Reference: packages/node/src/integrations/tracing/langchain/

Auto-Instrumentation (Node.js)

Mandatory for Node.js AI integrations. OTel only patches when the package is imported (zero cost if unused).

Steps

  1. Add to getAutoPerformanceIntegrations() in packages/node/src/integrations/tracing/index.ts — LangChain MUST come first
  2. Add to getOpenTelemetryInstrumentationToPreload() for OTel-based integrations
  3. Export from packages/node/src/index.ts: integration function + options type
  4. Add E2E tests:
    • Node.js: dev-packages/node-integration-tests/suites/tracing/{provider}/
    • Cloudflare: dev-packages/cloudflare-integration-tests/suites/tracing/{provider}/
    • Browser: dev-packages/browser-integration-tests/suites/tracing/ai-providers/{provider}/

Key Rules

  1. Respect sendDefaultPii for recordInputs/recordOutputs
  2. Set SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN = 'auto.ai.{provider}' (alphanumerics, _, . only)
  3. Truncate large data with helper functions from utils.ts
  4. gen_ai.invoke_agent for parent ops, gen_ai.chat for child ops

Checklist

  • Runtime-specific code placed only in that runtime's package
  • Added to getAutoPerformanceIntegrations() in correct order (Node.js)
  • Added to getOpenTelemetryInstrumentationToPreload() (Node.js with OTel)
  • Exported from appropriate package index
  • E2E tests added and verifying auto-instrumentation
  • Only used attributes from Sentry Gen AI Conventions
  • JSDoc says "enabled by default" or "not enabled by default"
  • Documented how to disable (if auto-enabled)
  • Verified OTel only patches when package imported (Node.js)

Reference Implementations

  • Pattern 1 (Span Processors): packages/node/src/integrations/tracing/vercelai/
  • Pattern 2 (Client Wrapping): packages/node/src/integrations/tracing/openai/
  • Pattern 3 (Callback/Hooks): packages/node/src/integrations/tracing/langchain/

When in doubt, follow the pattern of the most similar existing integration.

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