LLM app for chatting with enterprise data using OpenAI
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This repository provides a framework for building ChatGPT-like experiences over proprietary enterprise data, targeting developers and researchers. It enables users to upload their data and query it using large language models (LLMs) via Azure OpenAI Service, with support for various vector stores like Pinecone, Redis, and Azure Cognitive Search.
How It Works
The core approach leverages Retrieval Augmented Generation (RAG) to ground LLM responses in user-provided data. It supports multiple vector store integrations for efficient data indexing and retrieval. The system is designed to be modular, allowing for the integration of advanced RAG techniques and multi-modal capabilities.
Quick Start & Requirements
Highlighted Details
Maintenance & Community
The project is actively updated, with frequent refactoring and feature additions noted in the README. Contributions are welcomed via pull requests.
Licensing & Compatibility
The README does not explicitly state a license. It mentions being adapted from other repositories, but no specific license information is provided for this project. Compatibility for commercial use or closed-source linking is not specified.
Limitations & Caveats
The project is heavily tied to the Azure ecosystem. Some features are in preview or require specific API versions. The README indicates that certain functionalities (e.g., SEC analysis, PitchBook features) have been moved to separate repositories.
7 months ago
Inactive