Skip to main content
The Strands Agent SDK integration provides automatic tracing and logging of agent executions to Braintrust using OpenTelemetry. It captures agent invocations, tool calls, and multi-step interactions. This integration uses Braintrust’s Python SDK configuration for OpenTelemetry. The code below adapts the Weather Forecaster Strands example to send traces and logs to Braintrust. First, install the necessary dependencies and set environment variables. 
pip install braintrust[otel] strands-agents-tools strands-agents[openai]
.env
BRAINTRUST_API_KEY="<your Braintrust API key>"
BRAINTRUST_PARENT="project_name:<your Braintrust Project Name>"
OPENAI_API_KEY="<your OpenAI API key>"

# If you are self-hosting Braintrust, set the URL of your hosted dataplane. You can omit this otherwise.
# BRAINTRUST_API_URL=https://api.braintrust.dev
Use BraintrustSpanProcessor to configure Strands agent traces to send to Braintrust. This example adapts the Weather Forecaster Strands example to send traces and logs to Braintrust.
trace-strands-agent.py
# Load packages to form the Strands agent using an OpenAI model
# Load packages to execute the agent
import asyncio
import os

from braintrust.otel import BraintrustSpanProcessor
from dotenv import load_dotenv

# Load OpenTelemetry assets and Braintrust span processor added to the project from the braintrust[otel] library
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from strands import Agent
from strands.models.openai import OpenAIModel
from strands.telemetry import StrandsTelemetry
from strands_tools import http_request

load_dotenv()

# Define a weather-focused system prompt
WEATHER_SYSTEM_PROMPT = """You are a weather assistant with HTTP capabilities. You can:

1. Make HTTP requests to the National Weather Service API
2. Process and display weather forecast data
3. Provide weather information for locations in the United States

When retrieving weather information:
1. First get the coordinates or grid information using https://api.weather.gov/points/{latitude},{longitude} or https://api.weather.gov/points/{zipcode}
2. Then use the returned forecast URL to get the actual forecast

When displaying responses:
- Format weather data in a human-readable way
- Highlight important information like temperature, precipitation, and alerts
- Handle errors appropriately
- Convert technical terms to user-friendly language

Always explain the weather conditions clearly and provide context for the forecast.
"""

# Configure the global OTel tracer provider
provider = TracerProvider()
trace.set_tracer_provider(provider)

# Add the Braintrust span processor to the tracer provider and configure Strands telemetry
provider.add_span_processor(BraintrustSpanProcessor())
telemetry = StrandsTelemetry(provider)

# Configure the OpenAI model to be used by the Strands agent
model = OpenAIModel(
    client_args={
        "api_key": os.getenv("OPENAI_API_KEY"),
    },
    # **model_config
    model_id="gpt-4o-mini",
)

# Create an agent with HTTP tool call capabilities and the OpenAI model
weather_agent = Agent(
    system_prompt=WEATHER_SYSTEM_PROMPT,
    tools=[http_request],  # Explicitly enable http_request tool
    model=model,
)

# Create an async function to run the agent
async def main():
    result = await weather_agent.invoke_async(prompt="What is the weather in San Francisco?")
    print(result)

if __name__ == "__main__":
    asyncio.run(main())
Example of automatic Strands agent tracing and logs sent to Braintrust