tree: 2a5f202ae02e059e10c3e6ee3a7b65996c13b9d2
  1. __init__.py
  2. application.py
  3. notebook.ipynb
  4. README.md
  5. requirements.txt
  6. statemachine.png
examples/multi-agent-collaboration/lcel/README.md

Multi Agent Collaboration

This example resembles the example found originally here.

Tracing

You‘ll see that in application.py we have some lightweight tracing set up for Hamilton. This is a simple way to plug into Burr’s tracer functionality -- this will allow you to see more in the Burr UI.

More functionality is on the roadmap!

Running the example

Install the dependencies:

pip install "burr[start]" -r requirements.txt

Make sure you have the API Keys in your environment:

export OPENAI_API_KEY=YOUR_KEY
export TAVILY_API_KEY=YOUR_KEY

Run the notebook: or do it manually:

jupyter notebook

and open the notebook notebook.ipynb.

python application.py

Application run: lcel image

What to adjust

There are a few things:

  1. The query that you provide for the agents to work over. Set this as the initial human message in state.
  2. You can adjust the prompts used by the agents in the code.