Langfuse Via OpenInference

Export Agno agent spans to Langfuse over OTLP HTTP with base64 basic-auth headers and AgnoInstrumentor.

Demonstrates instrumenting an Agno agent with OpenInference and sending traces to Langfuse.

langfuse_via_openinference.py
"""
Langfuse Via OpenInference
==========================

Demonstrates instrumenting an Agno agent with OpenInference and sending traces to Langfuse.
"""

import asyncio
import base64
import os

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.yfinance import YFinanceTools
from openinference.instrumentation.agno import AgnoInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------
LANGFUSE_AUTH = base64.b64encode(
    f"{os.getenv('LANGFUSE_PUBLIC_KEY')}:{os.getenv('LANGFUSE_SECRET_KEY')}".encode()
).decode()
# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = (
#     "https://us.cloud.langfuse.com/api/public/otel"  # US data region
# )
os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = (
    "https://cloud.langfuse.com/api/public/otel"  # EU data region
)
# os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "http://localhost:3000/api/public/otel"  # Local deployment (>= v3.22.0)

os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = f"Authorization=Basic {LANGFUSE_AUTH}"

tracer_provider = TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter()))

# Start instrumenting agno
AgnoInstrumentor().instrument(tracer_provider=tracer_provider)


# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    name="Stock Price Agent",
    model=OpenAIChat(id="gpt-5.2"),
    tools=[YFinanceTools()],
    instructions="You are a stock price agent. Answer questions in the style of a stock analyst.",
)


# ---------------------------------------------------------------------------
# Run Example
# ---------------------------------------------------------------------------
async def main() -> None:
    await agent.aprint_response(
        "What is the current price of Tesla? Then find the current price of NVIDIA",
        stream=True,
    )


if __name__ == "__main__":
    asyncio.run(main())

Langfuse export settings

Choose the endpoint for your project's region in the copied source. For current direct OTLP ingestion, replace its header assignment before creating the exporter:

os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = (
    f"Authorization=Basic {LANGFUSE_AUTH},x-langfuse-ingestion-version=4"
)

Without the version header, traces can take up to ten minutes to appear in Langfuse's v4 data model. See Langfuse OpenTelemetry configuration.

Run the Example

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate

Install dependencies

uv pip install -U agno openai openinference-instrumentation-agno opentelemetry-exporter-otlp opentelemetry-sdk yfinance

Export environment variables

export LANGFUSE_PUBLIC_KEY="your_langfuse_public_key_here"
export LANGFUSE_SECRET_KEY="your_langfuse_secret_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"

Run the example

Save the code above as langfuse_via_openinference.py, then run:

python langfuse_via_openinference.py

Full source: cookbook/observability/langfuse_via_openinference.py