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https://github.com/vishnun0027/document-chatbot
A Document ChatBot based on Conversational RAG(Retrieval-augmented generation) that retrieves and summarizes information from uploaded documents
https://github.com/vishnun0027/document-chatbot
conversational-rag document-chatbot langchain llm python rag streamlit
Last synced: 7 days ago
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A Document ChatBot based on Conversational RAG(Retrieval-augmented generation) that retrieves and summarizes information from uploaded documents
- Host: GitHub
- URL: https://github.com/vishnun0027/document-chatbot
- Owner: vishnun0027
- Created: 2024-10-27T14:56:22.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2024-10-27T15:22:59.000Z (about 2 months ago)
- Last Synced: 2024-10-27T17:51:20.413Z (about 2 months ago)
- Topics: conversational-rag, document-chatbot, langchain, llm, python, rag, streamlit
- Language: Python
- Homepage:
- Size: 228 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Document ChatBot
### Conversational RAG
A Document ChatBot based on Conversational RAG(Retrieval-augmented generation) that retrieves and summarizes information from uploaded documents (PDF files or URLs).
It provides concise, context-based answers to user questions by analyzing the contents of the uploaded files or web pages.
## Features
- **Document Retrieval**: Upload PDF files or provide URLs to retrieve content.
- **Conversational RAG**: Uses Retrieval-Augmented Generation to offer more accurate, context-aware answers.
- **Contextualized Question Reformulation**: Rephrases questions for standalone clarity, retaining chat history context.
- **Concise Responses**: Generates short, clear answers, using minimal text for easy readability.
- **Session Management**: Independently manages chat history and session data.
## Installation
To get started with the PDF Q&A System, follow these steps:
2.Clone the repository:
```bash
git clone https://github.com/vishnun0027/Document-ChatBot.git
cd Document-ChatBot
```
2.Install the required packages:
```bash
pip install -r requirements.txt
```
3.Set up environment variables: Create a .env file in the root directory of the project and add your API keys:
```bash
GROQ_API_KEY=your_groq_api_key
HF_API_KEY=your_hugging_face_api_key
```
## Usage
1. Run the Streamlit application:
2. run app
```gash
streamlit run bot.py
```
3. Upload a PDF:
Use the sidebar to upload your PDF/link of document.
4. Ask Questions in chat:
After processing, enter your questions in the chat input field to receive answers based on the content of the document.