Multi Agent Collaboration

This example resembles the example from following cookbook.

There are two implementations:

1. hamilton/ -- this uses Hamilton inside the defined actions.
2. lcel/ -- this uses LangChain's LCEL inside the defined actions.

hamilton/application.py vs lcel/application.py:

• They should be functionally equivalent, except that langchain uses deprecated openai function constructs underneath, while Hamilton uses the non-deprecated tool calling constructs.
• Compare the two examples to see the code. Burr however doesn't change.

show me the prompts

With Hamilton the prompts can be found in the moduel hamilton/func_agent.py.

With LangChain that‘s difficult. You’ll need to dive into their code to see what ends up being sent.

Tracing

You‘ll see that both hamilton/application.py and lcel/application.py have some lightweight tracing set up. 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

To run the example, you can do:

Run the notebook:

python hamilton/application.py

Application run:

or

Run the notebook:

python lcel/application.py

Application run: