Langfuse Python SDK
The Langfuse Python SDK covers the full platform: observability/tracing (OpenTelemetry-based, with OpenAI and LangChain integrations), datasets & experiments (offline evaluation and regression testing of prompt/model changes, including CI via GitHub Actions), LLM-as-a-judge and custom evaluations/scores, prompt management, and a full REST API client.
Installation
pip install langfuse
Quickstart
# env: LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, LANGFUSE_BASE_URL
from langfuse import get_client
langfuse = get_client()
# Create a span using a context manager
with langfuse.start_as_current_observation(as_type="span", name="process-request") as span:
# Your processing logic here
span.update(output="Processing complete")
# Create a nested generation for an LLM call
with langfuse.start_as_current_observation(as_type="generation", name="llm-response", model="gpt-5.6") as generation:
# Your LLM call logic here
generation.update(output="Generated response")
# All spans are automatically closed when exiting their context blocks
# Flush events in short-lived applications
langfuse.flush()
Docs
- SDK guide: https://langfuse.com/docs/observability/sdk/overview
- Full documentation: https://langfuse.com/docs
- Machine-readable docs index (for AI agents): https://langfuse.com/llms.txt
- API reference of this package: https://python.reference.langfuse.com
- REST API reference (Observations API v2, Metrics API v2, Scores API v3): https://api.reference.langfuse.com
- Data freshness and real-time ingestion: https://langfuse.com/docs/compatibility#faq-delay
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