🤖 GenAI Project (Local LLM with Ollama)

📌 About

This repository contains a Generative AI (GenAI) application built using Ollama and modern LLM frameworks. The goal of this project is to run powerful AI models locally for tasks like chat, reasoning, and automation.

Unlike cloud-based AI tools, this project ensures:

• 🔐 Privacy (runs completely on your machine)
• ⚡ Low latency responses
• 💻 Offline capability (after model download)

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🚀 What is GenAI?

Generative AI refers to models that can generate content such as:

• Text 📝
• Code 💻
• Conversations 💬
• Ideas 💡

This project leverages LLMs (Large Language Models) to simulate intelligent responses.

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✨ Features

• 🧠 Local LLM execution using Ollama
• 💬 Chat-based interaction system
• ⚡ Fast and efficient responses
• 🔄 Easy model switching (LLaMA, Mistral, etc.)
• 🛠️ Beginner-friendly setup

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🛠️ Tech Stack

• Python 🐍
• Ollama 🧠
• LangChain (optional)
• Environment Variables (.env)

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⚙️ Installation Guide

1️⃣ Clone the Repository

git clone https://github.com/your-username/genai-project.git
cd genai-project

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2️⃣ Setup Virtual Environment

python -m venv venv

Activate:

• Windows:

venv\Scripts\activate

• Linux/Mac:

source venv/bin/activate

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3️⃣ Install Dependencies

pip install -r requirements.txt

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🧠 Setup Ollama

Install Ollama

Download from: https://ollama.com

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Pull a Model

ollama pull llama3

You can also use:

ollama pull mistral

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Run the Model

ollama run llama3

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▶️ Run the Application

python app.py

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🔄 Git Workflow (Clone → Commit → Push)

Clone

git clone https://github.com/your-username/genai-project.git

Add Changes

git add .

Commit

git commit -m "Added GenAI feature"

Push

git push origin main

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What about the HuggingFacemodel that can be used for sure response for Text-generation ??

The models are :

1. meta-llama/Llama-3.1-8B-Instruct
2. deepseek-ai/DeepSeek-R1
3. qwen2.5-coder

How to run Ollama for offline access --

• ollama pull qwen2.5-coder
• ollama run qwen2.5-coder
• ollama pull llama3.2
• ollama run llama3.2

For sureshot access

🤖 FastAPI AI Chat API

An AI-powered REST API built using FastAPI and Hugging Face LLM.

🚀 Features

• FastAPI backend
• AI Chat endpoint using Mistral-7B
• Clean modular structure
• Postman tested APIs

🛠️ Tech Stack

• FastAPI
• LangChain
• Hugging Face
• Python

IF not worked

Install the installations that are :

• pip install langchain langchain-huggingface
• pip install huggingface_hub transformers sentence-transformers

How the Structure Data is working

• TypedDict Schema
• Pydantic
• JSON

📂 Project Structure

genai-project/
│── app.py
│── requirements.txt
│── .env
│── README.md

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💡 Use Cases

• 🤖 Chatbot development
• 🧑‍💻 Code generation
• 📚 Learning AI concepts
• 🧠 Local AI assistants

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🔮 Future Scope

• 🌐 Web-based UI
• 🧾 Memory-based conversations
• 🔊 Voice interaction
• 📊 Integration with databases

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🤝 Contributing

Contributions are welcome! Feel free to fork and improve this project.

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📜 License

MIT License

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🙌 Credits

• Ollama
• Open-source LLM community

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