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Langfuse SDK

Pass-through endpoints for Langfuse - call langfuse endpoints with LiteLLM Virtual Key.

Just replace https://us.cloud.langfuse.com with LITELLM_PROXY_BASE_URL/langfuse 🚀

Example Usage​

from langfuse import Langfuse

langfuse = Langfuse(
    host="http://localhost:4000/langfuse", # your litellm proxy endpoint
    public_key="anything",        # no key required since this is a pass through
    secret_key="LITELLM_VIRTUAL_KEY",        # no key required since this is a pass through
)

print("sending langfuse trace request")
trace = langfuse.trace(name="test-trace-litellm-proxy-passthrough")
print("flushing langfuse request")
langfuse.flush()

print("flushed langfuse request")

Supports ALL Langfuse Endpoints.

See All Langfuse Endpoints

Quick Start​

Let's log a trace to Langfuse.

  1. Add Langfuse Public/Private keys to environment
export LANGFUSE_PUBLIC_KEY=""
export LANGFUSE_PRIVATE_KEY=""
  1. Start LiteLLM Proxy 
litellm

# RUNNING on http://0.0.0.0:4000
  1. Test it!

Let's log a trace to Langfuse! 

from langfuse import Langfuse

langfuse = Langfuse(
    host="http://localhost:4000/langfuse", # your litellm proxy endpoint
    public_key="anything",        # no key required since this is a pass through
    secret_key="anything",        # no key required since this is a pass through
)

print("sending langfuse trace request")
trace = langfuse.trace(name="test-trace-litellm-proxy-passthrough")
print("flushing langfuse request")
langfuse.flush()

print("flushed langfuse request")

Advanced - Use with Virtual Keys​

Pre-requisites

Use this, to avoid giving developers the raw Google AI Studio key, but still letting them use Google AI Studio endpoints.

Usage​

  1. Setup environment
export DATABASE_URL=""
export LITELLM_MASTER_KEY=""
export LANGFUSE_PUBLIC_KEY=""
export LANGFUSE_PRIVATE_KEY=""
litellm

# RUNNING on http://0.0.0.0:4000
  1. Generate virtual key 
curl -X POST 'http://0.0.0.0:4000/key/generate' \
-H 'Authorization: Bearer sk-1234' \
-H 'Content-Type: application/json' \
-d '{}'

Expected Response 

{
    ...
    "key": "sk-1234ewknldferwedojwojw"
}
  1. Test it! 
from langfuse import Langfuse

langfuse = Langfuse(
    host="http://localhost:4000/langfuse", # your litellm proxy endpoint
    public_key="anything",        # no key required since this is a pass through
    secret_key="sk-1234ewknldferwedojwojw",        # no key required since this is a pass through
)

print("sending langfuse trace request")
trace = langfuse.trace(name="test-trace-litellm-proxy-passthrough")
print("flushing langfuse request")
langfuse.flush()

print("flushed langfuse request")

Advanced - Log to separate langfuse projects (by key/team)​