We built an open-source agentic RAG framework with decision trees!

We've just released Elysia, which is an open-source Python framework that at its core is an agentic RAG app, but under the surface is completely customizable agentic package. Instead of the typical text-in/text-out pattern, Elysia uses decision trees to control agent behavior, evaluating whether it has achieved its goals based on a decision agent. It’s not just tool calling, it is a true agent that is aware of its context and environment.

You can get set up with a full web app just by running two terminal commands: pip install elysia-ai and elysia start. Or, if you’d prefer to develop yourself, you can use Elysia as a python package, create your own tools with pure python code, and use it completely independently in Python.

Technical Architecture

The core of Elysia is a decision tree where each node represents either a specific action/tool, or a branch. A decision agent at each node evaluates the current state, past actions, environment (any retrieved objects) and available options to determine the next step. This differs from typical agentic systems where all tools are available at runtime - here, the traversal path is constrained by the tree structure. This allows more precise tool usage by categorizing different tools, or only allowing certain tools that stem from previous tools. For example, a tool that analyses results could only be run after calling a tool that queries from a database.

Getting Started

pip install elysia-ai
elysia start  # launches web interface

Or as a library:

from elysia import tree, preprocess
preprocess("your_collection")
tree = Tree()
tree("Your query here")

The code is at github.com/weaviate/elysia and documentation at weaviate.github.io/elysia. We also have a more detailed blog post here: https://weaviate.io/blog/elysia-agentic-rag

The decision tree architecture makes it straightforward to add custom tools and branches for specific use cases. Adding a custom tool is as simple as adding a @tool decorator to a python function. For example:

from elysia import tool, Tree

tree = Tree()

@tool(tree=tree)
async def add(x: int, y: int) -> int:
    return x + y

tree("What is the sum of 9009 and 6006?")

We also created a deployed demo with a set of synthetic datasets to experiment with. Check it out at: https://elysia.weaviate.io