Strands Agents Instrumentation - LangWatch

LangWatch integrates with Strands Agents to automatically capture traces of agent interactions, model calls, and tool executions through OpenTelemetry.

Installation

pip install langwatch strands-agents strands-agents-tools

uv add langwatch strands-agents strands-agents-tools

Usage

The LangWatch API key is configured by default via the LANGWATCH_API_KEY environment variable.

Initialize LangWatch and create your Strands Agent. All agent interactions will be automatically traced.

import langwatch
import os

from strands import Agent
from strands.models.litellm import LiteLLMModel

langwatch.setup()


class MyAgent:
    def __init__(self):
        # Configure the model using LiteLLM for provider flexibility
        self.model = LiteLLMModel(
            client_args={"api_key": os.getenv("OPENAI_API_KEY")},
            model_id="openai/gpt-5-mini",
        )

        # Create the agent with tracing attributes
        self.agent = Agent(
            name="my-agent",
            model=self.model,
            system_prompt="You are a helpful AI assistant.",
        )

    def run(self, prompt: str):
        return self.agent(prompt)


agent = MyAgent()

response = agent.run("Tell me a joke")
print(response)

LangWatch automatically captures all agent interactions, model calls, and tool executions through Strands Agents’ built-in OpenTelemetry support. Use @langwatch.trace() decorators to add custom traces and metadata as needed.

Capturing RAG - Learn how to capture RAG data from retrievers and tools
Capturing Metadata and Attributes - Add custom metadata and attributes to your traces and spans
Capturing Evaluations & Guardrails - Log evaluations and implement guardrails in your Strands Agents applications