BeeAI | Respan Docs

BeeAI is an open-source framework for building, deploying, and serving production-ready AI agents. It provides a structured approach to agent development with built-in memory, tools, and LLM integration. Respan gives you full observability over every agent run, tool call, and LLM generation — 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-beeai beeai-framework

Set environment variables

$ export OPENAI_API_KEY="YOUR_OPENAI_API_KEY"
$ export RESPAN_API_KEY="YOUR_RESPAN_API_KEY"

OPENAI_API_KEY is used for LLM requests. RESPAN_API_KEY is used to export traces to Respan.

Initialize and run

1 from beeai import Agent
2 from respan import Respan
3 from openinference.instrumentation.beeai import BeeAIInstrumentor
4 
5 respan = Respan(instrumentations=[BeeAIInstrumentor()])
6 
7 agent = Agent(
8     model="gpt-4.1-nano",
9     instructions="You are a helpful research assistant.",
10 )
11 
12 response = agent.run("Explain the benefits of AI observability in production.")
13 print(response)
14 respan.flush()

View your trace

Open the Traces page to see your BeeAI agent trace with execution loops, tool calls, and LLM generations.

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. `BeeAIInstrumentor()`).
`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.beeai import BeeAIInstrumentor
3 
4 respan = Respan(
5     instrumentations=[BeeAIInstrumentor()],
6     customer_identifier="user_123",
7     metadata={"service": "beeai-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.beeai import BeeAIInstrumentor
3 
4 respan = Respan(instrumentations=[BeeAIInstrumentor()])
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.run(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.