Structured RAG MVP for Python Developers This project offers a Pythonic port of TypeAgent and related TypeScript packages, aiming to establish a Minimum Viable Product (MVP) for structured Retrieval Augmented Generation (RAG). It targets developers building RAG applications who need a foundational library for experimentation and achieving a shared understanding of data retrieval, providing a Python-native approach to RAG pipeline development.

How It Works

The library translates core logic from TypeAgent and KnowPro into Python, enabling the construction of RAG systems. It facilitates interaction with external Large Language Models (LLMs) to process inputs and derive structured understanding, offering a novel approach to building more predictable and robust RAG applications by focusing on structured outputs.

Quick Start & Requirements

• Install: pip install typeagent
• Prerequisites: Requires access to a third-party hosted LLM. The project explicitly warns against using it for confidential information due to this dependency.
• Documentation: Available within the docs directory.

Highlighted Details

• Experimental prototype focused on structured RAG.
• Aims to provide a Pythonic translation of existing TypeScript RAG tooling.

Maintenance & Community

The provided README does not contain information regarding maintainers, community channels (e.g., Discord, Slack), or a project roadmap.

Licensing & Compatibility

The README does not specify a software license. It references Microsoft's trademark guidelines but provides no details on licensing terms, making commercial or closed-source compatibility undetermined.

Limitations & Caveats

This is an experimental, in-progress project and is considered sample code. A critical limitation is that the library sends input data to a third-party LLM, posing a significant risk for indexing confidential or sensitive information. The extent of available documentation and feature completeness is not detailed.