Trace the OpenAI Agents SDK with Langfuse

%pip install openai-agents langfuse nest_asyncio "pydantic-ai[logfire]"

import os
 
# 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
 
# Your openai key
os.environ["OPENAI_API_KEY"] = "sk-proj-..."

import nest_asyncio
nest_asyncio.apply()

import logfire
 
# Configure logfire instrumentation.
logfire.configure(
    service_name='my_agent_service',
    send_to_logfire=False,
)
# This method automatically patches the OpenAI Agents SDK to send logs via OTLP to Langfuse.
logfire.instrument_openai_agents()

from langfuse import get_client
 
langfuse = get_client()
 
# Verify connection
if langfuse.auth_check():
    print("Langfuse client is authenticated and ready!")
else:
    print("Authentication failed. Please check your credentials and host.")

import asyncio
from agents import Agent, Runner
 
async def main():
    agent = Agent(
        name="Assistant",
        instructions="You only respond in haikus.",
    )
 
    result = await Runner.run(agent, "Tell me about recursion in programming.")
    print(result.final_output)
 
loop = asyncio.get_running_loop()
await loop.create_task(main())

from agents import Agent, Runner
import asyncio
 
spanish_agent = Agent(
    name="Spanish agent",
    instructions="You only speak Spanish.",
)
 
english_agent = Agent(
    name="English agent",
    instructions="You only speak English",
)
 
triage_agent = Agent(
    name="Triage agent",
    instructions="Handoff to the appropriate agent based on the language of the request.",
    handoffs=[spanish_agent, english_agent],
)
 
result = await Runner.run(triage_agent, input="Hola, ¿cómo estás?")
print(result.final_output)

import asyncio
from agents import Agent, Runner, function_tool
 
# Example function tool.
@function_tool
def get_weather(city: str) -> str:
    return f"The weather in {city} is sunny."
 
agent = Agent(
    name="Hello world",
    instructions="You are a helpful agent.",
    tools=[get_weather],
)
 
async def main():
    result = await Runner.run(agent, input="What's the weather in Tokyo?")
    print(result.final_output)
 
loop = asyncio.get_running_loop()
await loop.create_task(main())

from agents import Agent, Runner, trace
import asyncio
 
async def main():
    agent = Agent(name="Joke generator", instructions="Tell funny jokes.")
 
    with trace("Joke workflow"):
        first_result = await Runner.run(agent, "Tell me a joke")
        second_result = await Runner.run(agent, f"Rate this joke: {first_result.final_output}")
        print(f"Joke: {first_result.final_output}")
        print(f"Rating: {second_result.final_output}")
 
loop = asyncio.get_running_loop()
await loop.create_task(main())

from contextvars import ContextVar
from typing import Optional
from opentelemetry import context as context_api
from opentelemetry.sdk.trace.export import Span, SpanProcessor
 
prompt_info_var = ContextVar("prompt_info", default=None)
 
class LangfuseProcessor(SpanProcessor):
    def on_start(
        self,
        span: 'Span',
        parent_context: Optional[context_api.Context] = None,
    ) -> None:
        if span.name.startswith('Responses API'): # The name of the generation spans in your OpenAI Agent trace 
            prompt_info = prompt_info_var.get()
            if prompt_info:
                span.set_attribute('langfuse.prompt.name', prompt_info.get("name"))
                span.set_attribute('langfuse.prompt.version', prompt_info.get("version"))

import logfire
from langfuse import get_client
 
logfire.configure(
    service_name='my_agent_service',
    additional_span_processors=[LangfuseProcessor()], # Passing the LangfuseProcessor to the logfire configuration will automatically link the prompt to the trace
    send_to_logfire=False,
)
 
logfire.instrument_openai_agents()
langfuse = get_client()

# Fetch the prompt from Langfuse Prompt Management
langfuse_prompt = langfuse.get_prompt("movie-critic")
system_prompt = langfuse_prompt.compile(criticlevel = "expert", movie = "Dune 2")
 
# Pass the prompt to the SpanProcessor
prompt_info_var.set({
    "name": langfuse_prompt.name,
    "version": langfuse_prompt.version,
})
 
# Run the agent ...