metadata

title: Docs Qachat
emoji: 🚀
colorFrom: gray
colorTo: gray
sdk: gradio
sdk_version: 4.2.0
app_file: app.py
pinned: false

Docs QAchat 🚀

Overview

Docs QAchat is an advanced Documentation AI helper, demonstrating a fine-tuned 7b model's capabilities in aiding users with software documentation. This application integrates technologies like Retrieval-Augmented Generation (RAG), LangChain, Gradio UI, Chroma DB, and FAISS to offer insightful documentation assistance. It's designed to help users navigate and utilize software tools efficiently by retrieving relevant documentation pages and maintaining conversational flow.

Key Features

AI-Powered Documentation Retrieval: Utilizes various fine-tuned 7b models for precise and context-aware responses.
Rich User Interface: Features a user-friendly interface built with Gradio.
Advanced Language Understanding: Employs LangChain for implementing RAG setups and sophisticated natural language processing.
Efficient Data Handling: Leverages Chroma DB and FAISS for optimized data storage and retrieval.
Retrieval Chain with Prompt Tuning: Includes a retrieval chain with a prompt template for prompt tuning.
Conversation Memory: Incorporates BufferMemory for short-term conversation memory, enhancing conversational flow.

Models Used

This setup is tested with the following models:

mistralai/Mistral-7B-v0.1
mistralai/Mistral-7B-Instruct-v0.1
HuggingFaceH4/zephyr-7b-beta
HuggingFaceH4/zephyr-7b-alpha
tiiuae/falcon-7b-instruct
microsoft/Orca-2-7b
teknium/OpenHermes-2.5-Mistral-7B

Prerequisites

Python 3.8 or later
[Additional prerequisites as needed]

Installation

Clone the repository:

git clone https://github.com/yourusername/Docs-QAchat.git

Navigate to the project directory:
```
cd Docs-QAchat
```
Install required packages:
```
pip install -r requirements.txt
```

Configuration

Create a .env file in the project root.

Add the following environment variables to the .env file:

HUGGINGFACEHUB_API_TOKEN=""
AWS_S3_LOCATION=""
AWS_S3_FILE=""
VS_DESTINATION=""

Usage

Start the application by running:

python app.py

[Include additional usage instructions and examples]

Contributing

Contributions to Docs QAchat are welcome. [Include contribution guidelines]

Support

For support, contact [Support Contact Information].

Authors and Acknowledgement

[Name]
Acknowledgements to the contributors of the used models and technologies.

License

This project is licensed under the [License] - see the LICENSE file for details.