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🪢 Langfuse OpenTelemetry Integration

The Langfuse OpenTelemetry integration allows you to send LiteLLM traces and observability data to Langfuse using the OpenTelemetry protocol. This provides a standardized way to collect and analyze your LLM usage data.

Features​

  • Automatic trace collection for all LiteLLM requests
  • Support for Langfuse Cloud (EU and US regions)
  • Support for self-hosted Langfuse instances
  • Custom endpoint configuration
  • Secure authentication using Basic Auth
  • Consistent attribute mapping with other OTEL integrations

Prerequisites​

  1. Langfuse Account: Sign up at Langfuse Cloud or set up a self-hosted instance
  2. API Keys: Get your public and secret keys from your Langfuse project settings
  3. Dependencies: Install required packages: 
    pip install litellm opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp

Configuration​

Environment Variables​

VariableRequiredDescriptionExample
LANGFUSE_PUBLIC_KEYYesYour Langfuse public keypk-lf-...
LANGFUSE_SECRET_KEYYesYour Langfuse secret keysk-lf-...
LANGFUSE_HOSTNoLangfuse host URLhttps://us.cloud.langfuse.com (default)

Endpoint Resolution​

The integration automatically constructs the OTEL endpoint from the LANGFUSE_HOST:

  • Default (US): https://us.cloud.langfuse.com/api/public/otel
  • EU Region: https://cloud.langfuse.com/api/public/otel
  • Self-hosted: {LANGFUSE_HOST}/api/public/otel

Usage​

Basic Setup​

import os
import litellm

# Set your Langfuse credentials
os.environ["LANGFUSE_PUBLIC_KEY"] = "pk-lf-..."
os.environ["LANGFUSE_SECRET_KEY"] = "sk-lf-..."

# Enable Langfuse OTEL integration
litellm.callbacks = ["langfuse_otel"]

# Make LLM requests as usual
response = litellm.completion(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello!"}]
)

Advanced Configuration​

import os
import litellm

# Set your Langfuse credentials
os.environ["LANGFUSE_PUBLIC_KEY"] = "pk-lf-..."
os.environ["LANGFUSE_SECRET_KEY"] = "sk-lf-..."

# Use EU region
os.environ["LANGFUSE_HOST"] = "https://cloud.langfuse.com"  # EU region
# os.environ["LANGFUSE_HOST"] = "https://us.cloud.langfuse.com"  # US region (default)

# Or use self-hosted instance
# os.environ["LANGFUSE_HOST"] = "https://my-langfuse.company.com"

litellm.callbacks = ["langfuse_otel"]

Manual OTEL Configuration​

If you need direct control over the OpenTelemetry configuration:

import os
import base64
import litellm

# Get keys for your project from the project settings page: https://cloud.langfuse.com
os.environ["LANGFUSE_PUBLIC_KEY"] = "pk-lf-..." 
os.environ["LANGFUSE_SECRET_KEY"] = "sk-lf-..." 
os.environ["LANGFUSE_HOST"] = "https://cloud.langfuse.com" # EU region
# os.environ["LANGFUSE_HOST"] = "https://us.cloud.langfuse.com" # US region

LANGFUSE_AUTH = base64.b64encode(
    f"{os.environ.get('LANGFUSE_PUBLIC_KEY')}:{os.environ.get('LANGFUSE_SECRET_KEY')}".encode()
).decode()

os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = os.environ.get("LANGFUSE_HOST") + "/api/public/otel"
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"

litellm.callbacks = ["langfuse_otel"]

With LiteLLM Proxy​

Add the integration to your proxy configuration:

  1. Add the credentials to your environment variables
export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."
export LANGFUSE_HOST="https://us.cloud.langfuse.com"  # Default US region
  1. Setup config.yaml
# config.yaml
litellm_settings:
  callbacks: ["langfuse_otel"]
  1. Run the proxy
litellm --config /path/to/config.yaml

Data Collected​

The integration automatically collects the following data:

  • Request Details: Model, messages, parameters (temperature, max_tokens, etc.)
  • Response Details: Generated content, token usage, finish reason
  • Timing Information: Request duration, time to first token
  • Metadata: User ID, session ID, custom tags (if provided)
  • Error Information: Exception details and stack traces (if errors occur)

Metadata Support​

All metadata fields available in the vanilla Langfuse integration are now fully supported when you use the OTEL integration.

  • Any key you pass in the metadata dictionary (generation_name, trace_id, session_id, tags, and the rest) is exported as an OpenTelemetry span attribute.
  • Attribute names are prefixed with langfuse. so you can filter or search for them easily in your observability backend. Examples: langfuse.generation.name, langfuse.trace.id, langfuse.trace.session_id.

Passing Metadata – Example​

response = litellm.completion(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello!"}],
    metadata={
        "generation_name": "welcome-message",
        "trace_id": "trace-123",
        "session_id": "sess-42",
        "tags": ["prod", "beta-user"]
    }
)

The resulting span will contain attributes similar to:

langfuse.generation.name   = "welcome-message"
langfuse.trace.id          = "trace-123"
langfuse.trace.session_id  = "sess-42"
langfuse.trace.tags        = ["prod", "beta-user"]

Use the Langfuse UI (Traces tab) to search, filter and analyse spans that contain the langfuse.* attributes. The OTEL exporter in this integration sends data directly to Langfuse’s OTLP HTTP endpoint; it is not intended for Grafana, Honeycomb, Datadog, or other generic OTEL back-ends.

Authentication​

The integration uses HTTP Basic Authentication with your Langfuse public and secret keys:

Authorization: Basic <base64(public_key:secret_key)>

This is automatically handled by the integration - you just need to provide the keys via environment variables.

Troubleshooting​

Common Issues​

  1. Missing Credentials Error

    ValueError: LANGFUSE_PUBLIC_KEY and LANGFUSE_SECRET_KEY must be set

    Solution: Ensure both environment variables are set with valid keys.

  2. Connection Issues

    • Check your internet connection
    • Verify the endpoint URL is correct
    • For self-hosted instances, ensure the /api/public/otel endpoint is accessible

  3. Authentication Errors

    • Verify your public and secret keys are correct
    • Check that the keys belong to the same Langfuse project
    • Ensure the keys have the necessary permissions

Debug Mode​

Enable verbose logging to see detailed information:

import litellm
litellm._turn_on_debug()

This will show:

  • Endpoint resolution logic
  • Authentication header creation
  • OTEL trace submission details