Strands Agents | Respan Docs

Strands Agents is an open-source SDK from AWS for building AI agents. It provides a model-driven approach to agent development with built-in support for tools, sessions, and multi-agent orchestration. Respan gives you full observability over every agent run, reasoning loop, tool invocation, and LLM call — and gateway routing through the OpenAI-compatible Respan endpoint.

Set up Respan

Create an account at platform.respan.ai and grab an API key. For gateway, also add credits or a provider key.

Run npx @respan/cli setup to set up with your coding agent.

Example projects

Python examples

Tracing

Gateway

Setup

Install packages

$ pip install respan-ai openinference-instrumentation-strands-agents strands-agents

Set environment variables

$ export AWS_ACCESS_KEY_ID="YOUR_AWS_ACCESS_KEY_ID"
$ export AWS_SECRET_ACCESS_KEY="YOUR_AWS_SECRET_ACCESS_KEY"
$ export AWS_REGION="us-east-1"
$ export RESPAN_API_KEY="YOUR_RESPAN_API_KEY"

AWS credentials are used for the underlying Bedrock model. RESPAN_API_KEY is used to export traces to Respan.

Initialize and run

1 from strands import Agent
2 from strands.tools import tool
3 from respan import Respan
4 from openinference.instrumentation.strands_agents import StrandsAgentsInstrumentor
5 
6 respan = Respan(instrumentations=[StrandsAgentsInstrumentor()])
7 
8 @tool
9 def get_weather(location: str) -> str:
10     """Get the current weather for a location."""
11     return f"The weather in {location} is sunny, 72F."
12 
13 agent = Agent(tools=[get_weather])
14 response = agent("What is the weather in Seattle?")
15 print(response)
16 respan.flush()

View your trace

Open the Traces page to see your Strands Agents workflow with reasoning loops, tool invocations, and LLM calls.

Configuration

Parameter	Type	Default	Description
`api_key`	`str \| None`	`None`	Falls back to `RESPAN_API_KEY` env var.
`base_url`	`str \| None`	`None`	Falls back to `RESPAN_BASE_URL` env var.
`instrumentations`	`list`	`[]`	Plugin instrumentations to activate (e.g. `StrandsAgentsInstrumentor()`).
`customer_identifier`	`str \| None`	`None`	Default customer identifier for all spans.
`metadata`	`dict \| None`	`None`	Default metadata attached to all spans.
`environment`	`str \| None`	`None`	Environment tag (e.g. `"production"`).

Attributes

In Respan()

Set defaults at initialization — these apply to all spans.

1 from respan import Respan
2 from openinference.instrumentation.strands_agents import StrandsAgentsInstrumentor
3 
4 respan = Respan(
5     instrumentations=[StrandsAgentsInstrumentor()],
6     customer_identifier="user_123",
7     metadata={"service": "strands-api", "version": "1.0.0"},
8 )

With propagate_attributes

Override per-request using a context scope.

1 from respan import Respan, propagate_attributes
2 from openinference.instrumentation.strands_agents import StrandsAgentsInstrumentor
3 
4 respan = Respan(instrumentations=[StrandsAgentsInstrumentor()])
5 
6 def handle_request(user_id: str, message: str):
7     with propagate_attributes(
8         customer_identifier=user_id,
9         thread_identifier="conv_abc_123",
10         metadata={"plan": "pro"},
11     ):
12         print(agent(message))

Attribute	Type	Description
`customer_identifier`	`str`	Identifies the end user in Respan analytics.
`thread_identifier`	`str`	Groups related messages into a conversation.
`metadata`	`dict`	Custom key-value pairs. Merged with default metadata.