https://github.com/mnds18/sydney-local-rag-chatbot

Local RAG Chatbot: Sydney Q&A powered by FAISS, local embeddings, and offline LLMs via Ollama.
https://github.com/mnds18/sydney-local-rag-chatbot

chatbot faiss flask llm localai ollama python3 rag

Last synced: 6 months ago
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Local RAG Chatbot: Sydney Q&A powered by FAISS, local embeddings, and offline LLMs via Ollama.

• Host: GitHub
• URL: https://github.com/mnds18/sydney-local-rag-chatbot
• Owner: mnds18
• License: other
• Created: 2025-04-13T12:52:25.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-04-13T13:49:14.000Z (6 months ago)
• Last Synced: 2025-04-15T01:17:50.356Z (6 months ago)
• Topics: chatbot, faiss, flask, llm, localai, ollama, python3, rag
• Language: Python
• Homepage:
• Size: 1.08 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: license

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# 🐨 Mrig's Sydney Local RAG Chatbot

An end-to-end **Retrieval-Augmented Generation (RAG)** chatbot built **entirely locally** — no APIs, no cloud services.  

It reads **PDF** and **Word documents**, builds a **vectorstore**, retrieves answers using **FAISS**, and **generates responses using a local LLM** (Mistral / DeepSeek / Llama3 running in Ollama).




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## 🚀 Features

- ✅ Full **local-only** document understanding (PDFs + DOCXs)

- ✅ **FAISS** vector database for fast document search

- ✅ **Hard prompting** forcing 1-word or short answers

- ✅ Supports multiple **local LLMs** (DeepSeek, Mistral, Llama3 via Ollama)

- ✅ **Beautiful tourism-themed** front-end chatbot (Flask)

- ✅ Fully **rebuildable vectorstore** on demand

- ✅ Clean, highly commented, production-quality code

- ✅ Designed for **easy personal deployment** or **professional demos**




---

## 📂 Project Structure

```plaintext

.

├── local_chatbot.py      # Main backend: extraction + FAISS + Ollama + Flask

├── templates/

│   └── index.html        # Frontend chat UI

├── faiss_index/

│   ├── faiss.index       # Saved FAISS vector database

│   └── chunks.pkl        # Saved split document chunks

├── pdf_files/            # Your source PDFs

├── docx_files/           # Your source DOCX files

├── README.md             # You are here :)

🔑 Environment Variables

Variable	Purpose

OLLAMA_HOST	Ollama server URL (default: http://localhost:11434)

Ensure Ollama is installed locally with required models downloaded!

🖥️ Demo Screenshots

🏗️ Setup Instructions

# 1. Clone repo

git clone https://github.com/yourusername/sydney-local-rag-chatbot.git

cd sydney-local-rag-chatbot

# 2. (Optional) Create virtual environment

python -m venv venv

source venv/bin/activate  # (Linux/Mac)

venv\Scripts\activate     # (Windows)

# 3. Install required packages

pip install -r requirements.txt

# 4. Run the app

python local_chatbot.py

Access chatbot at: http://127.0.0.1:5000

🛡️ License

This project is licensed under the MIT License.

🤝 Contributing

Contributions are welcome! 🚀

Please create an issue before submitting pull requests.

Ensure you follow basic Python code style guidelines (flake8).

📢 Acknowledgments

FAISS (Facebook AI Similarity Search)

Sentence Transformers (HuggingFace)

Ollama - Local LLM Runtime

Flask Framework

🔥 Connect

If you're passionate about the intersection of

Data Science × AI Engineering × Product Thinking — let's connect!

Always building smart, offline-first AI products! 🚀

LinkedIn : https://www.linkedin.com/in/mrigendranath/