https://github.com/sujeethshingade/bizrag-bot
RAG Chatbot for Predictive Analysis
https://github.com/sujeethshingade/bizrag-bot
faiss flask huggingface langchain llama machine-learning nextjs predictive-analytics python rag supabase
Last synced: 3 months ago
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RAG Chatbot for Predictive Analysis
- Host: GitHub
- URL: https://github.com/sujeethshingade/bizrag-bot
- Owner: sujeethshingade
- Created: 2024-10-10T12:49:53.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-29T05:25:36.000Z (over 1 year ago)
- Last Synced: 2026-01-03T14:35:48.429Z (6 months ago)
- Topics: faiss, flask, huggingface, langchain, llama, machine-learning, nextjs, predictive-analytics, python, rag, supabase
- Language: Python
- Homepage: https://bizrag-bot.vercel.app
- Size: 896 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.MD
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README
# Bizrag Bot
- Bizrag Bot leverages a RAG framework, where it combines a retrieval mechanism (to pull relevant data or documents) with a generative model, providing answers grounded in accurate, business-specific information.
- This architecture allows it to handle complex queries that require contextual understanding and up-to-date, reliable answers, making it highly suitable for business support, client queries, and decision-making tasks.
### Features
- **Information Retrieval:** Pulls data from a structured source (like a database) or unstructured documents, ensuring answers are fact-based and relevant.
- **Scalable Knowledge Base:** Easily incorporates additional documents, FAQs, or datasets, which makes it adaptable to growing or changing business knowledge.
- **History Management:** Keeps track of chat history, Dashboard provides all of previous interactions.
- **User Authentication:** Allows authenticated sessions, restricting access to sensitive business information only to verified users.
- **Real-time Querying:** Answers questions promptly, suitable for client support or internal team assistance, reducing response time for queries.
### Installation
#### Frontend
```
npm install
```
```
npm run dev
```
#### Backend
```
cd backend && python -m venv venv
```
```
source venv/Scripts/activate
```
```
pip install -r requirements.txt
```
```
python app.py
```
### Login Credentials
Username:
Password: 123456