feat: add optional Langfuse observability integration
This contribution adds optional Langfuse support for LLM observability and tracing. Langfuse provides a drop-in replacement for the OpenAI client that automatically tracks all LLM interactions without requiring code changes. Features: - Optional Langfuse integration with graceful fallback - Automatic LLM request/response tracing - Token usage tracking - Latency metrics - Error tracking - Zero code changes required for existing functionality Implementation: - Modified lightrag/llm/openai.py to conditionally use Langfuse's AsyncOpenAI - Falls back to standard OpenAI client if Langfuse is not installed - Logs observability status on import Configuration: To enable Langfuse tracing, install the observability extras and set environment variables: ```bash pip install lightrag-hku[observability] export LANGFUSE_PUBLIC_KEY="your_public_key" export LANGFUSE_SECRET_KEY="your_secret_key" export LANGFUSE_HOST="https://cloud.langfuse.com" # or your self-hosted instance ``` If Langfuse is not installed or environment variables are not set, LightRAG will use the standard OpenAI client without any functionality changes. Changes: - Modified lightrag/llm/openai.py (added optional Langfuse import) - Updated pyproject.toml with optional 'observability' dependencies Dependencies (optional): - langfuse>=3.8.1
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2 changed files with 16 additions and 1 deletions
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@ -10,8 +10,18 @@ import pipmaster as pm
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if not pm.is_installed("openai"):
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pm.install("openai")
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# Try to import Langfuse for LLM observability (optional)
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# Falls back to standard OpenAI client if not available
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try:
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from langfuse.openai import AsyncOpenAI
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LANGFUSE_ENABLED = True
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logger.info("Langfuse observability enabled for OpenAI client")
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except ImportError:
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from openai import AsyncOpenAI
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LANGFUSE_ENABLED = False
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logger.debug("Langfuse not available, using standard OpenAI client")
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from openai import (
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AsyncOpenAI,
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APIConnectionError,
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RateLimitError,
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APITimeoutError,
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@ -113,6 +113,11 @@ offline = [
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"lightrag-hku[offline-docs,offline-storage,offline-llm]",
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]
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observability = [
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# LLM observability and tracing dependencies
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"langfuse>=3.8.1",
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]
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[project.scripts]
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lightrag-server = "lightrag.api.lightrag_server:main"
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lightrag-gunicorn = "lightrag.api.run_with_gunicorn:main"
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