https://github.com/mdimado/paperchat
PaperChat is an AI-powered chat application designed to handle PDF documents through a user-friendly interface. Users can upload PDF files, ask questions related to the content within those documents, and receive responses generated using advanced natural language processing (NLP) techniques.
https://github.com/mdimado/paperchat
cohere fastapi groq langchain qdrant qdrant-vector-database react reactjs
Last synced: 6 days ago
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PaperChat is an AI-powered chat application designed to handle PDF documents through a user-friendly interface. Users can upload PDF files, ask questions related to the content within those documents, and receive responses generated using advanced natural language processing (NLP) techniques.
- Host: GitHub
- URL: https://github.com/mdimado/paperchat
- Owner: mdimado
- Created: 2024-06-11T15:22:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-26T14:05:37.000Z (11 months ago)
- Last Synced: 2025-01-24T23:55:52.095Z (9 months ago)
- Topics: cohere, fastapi, groq, langchain, qdrant, qdrant-vector-database, react, reactjs
- Language: Python
- Homepage: https://paperchat-ai.netlify.app/
- Size: 3.3 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
PaperChat - AI-Driven PDF Interaction Platform
===================================================
### Overview
This repository contains code for an AI-powered chat application that allows users to upload PDF documents, perform queries, and receive responses based on the content of the uploaded document.
https://github.com/mdimado/PaperChat/assets/123477562/a5adbe2b-6595-4acd-a5e6-8136b2a7fd50
### Setup Instructions
Follow these steps to set up and run the project:
1. Clone the Repository:
```
git clone https://github.com/mdimado/PaperChat.git
cd PaperChat
```
2. Install Backend Dependencies:
```
cd backend
pip install -r requirements.txt
```
3. Pull the Qdrant Docker Image
```
docker pull qdrant/qdrant
```
4. Run the Qdrant Docker Container:
```
docker run -d --name qdrant -p 6333:6333 qdrant/qdrant
```
5. Set Environment Variables:
Create a .env file in the backend directory and add the following variables:
```
COHERE_API_KEY=your-cohere-api-key
GROQ_API_KEY=your-groq-api-key
```
6. Run the Backend Server:
```
uvicorn main:app --reload
```
7. Install Frontend Dependencies:
```
cd ../frontend
npm install
```
8. Run the Frontend Development Server:
```
npm start
```
