langsmith-trace

LANGSMITH_API_KEY=lsv2_pt_your_api_key_here          # REQUIRED
LANGSMITH_PROJECT=your-project-name                   # Optional: default project
LANGSMITH_WORKSPACE_ID=your-workspace-id              # Optional: for org-scoped keys

Authentication is REQUIRED: either set the LANGSMITH_API_KEY environment variable, or pass the --api-key flag to CLI commands (preferred):

langsmith trace list --project my-project --api-key $LANGSMITH_API_KEY

IMPORTANT: Always check the environment variables or .env file for LANGSMITH_PROJECT before querying or interacting with LangSmith. This tells you which project contains the relevant traces and data. If the LangSmith project is not available, use your best judgement to identify the right one.

CLI Tool

curl -sSL https://raw.githubusercontent.com/langchain-ai/langsmith-cli/main/scripts/install.sh | sh

<trace_langchain_oss> For LangChain/LangGraph apps, tracing is automatic. Just set environment variables:

export LANGSMITH_TRACING=true
export LANGSMITH_API_KEY=<your-api-key>
export OPENAI_API_KEY=<your-openai-api-key>  # or your LLM provider's key

Optional variables:

• LANGSMITH_PROJECT - specify project name (defaults to "default")
• LANGCHAIN_CALLBACKS_BACKGROUND=false - use for serverless to ensure traces complete before function exit (Python) </trace_langchain_oss>

<trace_other_frameworks> For anything other than LangChain/LangGraph, read the matching reference file in references/ before writing tracing code. Each reference covers install, env vars, setup snippet, and gotchas specific to that framework. The setup is rarely identical across frameworks — picking the wrong pattern (e.g. using @traceable when the framework has native OTel) creates duplicate/missing spans.

Decision order:

1. Framework has a dedicated reference below → use it
2. Framework has native OpenTelemetry but no dedicated reference → references/otel.md
3. No framework, or unsupported framework → references/traceable.md
4. Cannot run a LangSmith SDK at all → references/api.md (last resort)

Routing table:

If you're tracing…	Read
OpenAI / Azure OpenAI / Anthropic / any plain LLM client	references/traceable.md
AutoGen	references/autogen.md
CrewAI	references/crewai.md
Google ADK	references/google-adk.md
Google Gemini (google-genai SDK directly)	references/google-gemini.md
Instructor (structured outputs)	references/instructor.md
LiveKit Agents (voice AI)	references/livekit.md
Mastra (TypeScript)	references/mastra.md
Microsoft Agent Framework	references/microsoft-agent-framework.md
Mistral	references/mistral.md
n8n (self-hosted)	references/n8n.md
OpenAI Agents SDK	references/openai-agents-sdk.md
OpenCode	references/opencode.md
OpenAI Codex CLI	references/codex.md
Pipecat (voice AI)	references/pipecat.md
PydanticAI	references/pydantic-ai.md
Semantic Kernel	references/semantic-kernel.md
Strands Agents	references/strands-agents.md
Temporal workflows (Go/Python/TS)	references/temporal.md
Vercel AI SDK	references/vercel-ai-sdk.md
Any other framework with native OTel	references/otel.md
Multi-backend OTel fan-out	references/otel.md (Collector section)
Raw REST (no SDK available)	references/api.md

If the framework you need isn't listed here, check references/ — new integrations are added there, not inline. </trace_other_frameworks>

<traces_vs_runs> Use the langsmith CLI to query trace data.

Understanding the difference is critical:

• Trace = A complete execution tree (root run + all child runs). A trace represents one full agent invocation with all its LLM calls, tool calls, and nested operations.
• Run = A single node in the tree (one LLM call, one tool call, etc.)