Get Started with Langfuse Tracing
This quickstart helps you to integrate your LLM application with Langfuse Tracing. If you are looking for other features, see the overview.
Create new project in Langfuse
- Create Langfuse account or self-host
- Create a new project
- Create new API credentials in the project settings
Integrate with Langfuse
The @observe()
decorator is the recommended way to get started with Langfuse. It automatically captures traces with minimal code changes and works with any LLM provider.
pip install langfuse
.env
LANGFUSE_SECRET_KEY="sk-lf-..."
LANGFUSE_PUBLIC_KEY="pk-lf-..."
# 🇪🇺 EU region
LANGFUSE_HOST="https://cloud.langfuse.com"
# 🇺🇸 US region
# LANGFUSE_HOST="https://us.cloud.langfuse.com"
main.py
from langfuse import observe, get_client
from langfuse.openai import openai # OpenAI integration
@observe()
def story():
return openai.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": "You are a great storyteller."},
{"role": "user", "content": "Once upon a time in a galaxy far, far away..."}
],
).choices[0].message.content
@observe()
def main():
return story()
main()
For more advanced use cases with manual control, see the Python SDK v3 documentation.
✅
Done. After running your application, visit the Langfuse interface to view the trace you just created.
All Langfuse platform features
This was a very brief introduction to get started with Langfuse. Explore all Langfuse platform features in detail.
Develop
Monitor
Test
References
Python DecoratorPython SDK (v3)JS/TS SDKOpenAI SDK🦜🔗Langchain🦙LlamaIndexAPI referenceFlowiseLangflowLitellm
FAQ
- How to use Langfuse Tracing in Serverless Functions (AWS Lambda, Vercel, Cloudflare Workers, etc.)
- I cannot see my organization in Langfuse
- How to manage different environments in Langfuse?
- I have setup Langfuse, but I do not see any traces in the dashboard. How to solve this?
- Where do I find my Langfuse API keys?
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