Sean Browning (NCEZID/OD Data Science Team)
I wanted to learn how to create and use language agents to solve complex problems. LangChain wasn't cutting it for me, so I made my own library from first principles to suit a few projects we're working on.
This package contains a few classes that can be used as building blocks for language agents and agentic systems. I plan to expand it with additional functionality as I need it, but keep a minimal footprint (ie. if you're already using openai and pydantic, this should bring no additional dependencies).
All code uses asyncio by design, and though I've tried to generalize as I can, I mostly built around OpenAI and specifically Azure OpenAI since that's what we are allowed to work with internally.
Maybe you shouldn't use this library.
After all, there are whole teams and companies of real software engineers working on similar frameworks that should suit your use-case:
By design, this library was designed to be python-ic, minimally invasive, and not require a lot of boilerplate to do what is essentially just string formatting and API request handling. It serves me well, but may not serve you.
This isn't currently on pypi, so just use pip to install directly via GitHub:
pip install git+https://github.com/cdcai/multiagent.git
| Example | Link |
|---|---|
| Taking output from one agent as input to another in a callback | agent_with_callback.py |
| Getting structured output from agent / Text Prediction | structured_prediction.py |
| Batch processing large inputs over the same agent in parallel | batch_processing.py |
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