Simple AI Chat App 💬

Welcome to the Simple Chat App! This is a full-stack chat application built with Flask (backend), React (frontend), and MongoDB (database). The app allows users to chat with an AI-powered chatbot (using Mistral via Ollama) and stores chat history for future reference. The AI responses are dynamically typed for a more interactive experience.

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• This project was developed during my internship.
• Very very Similar to chatGPT but we have used Mistral model.

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Features ✨

• AI-Powered Chatbot: Interact with an AI model (Mistral via Ollama) for dynamic responses.
• Chat History: View past chats in a sidebar.
• Dynamic Typing: AI responses are displayed letter by letter for a realistic feel.
• Secure MongoDB Integration: Database connection is secured using environment variables.
• Responsive Design: Clean and modern UI with a dark theme.

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Tech Stack 🛠️

• Frontend: React, Axios
• Backend: Flask, Flask-CORS, PyMongo
• Database: MongoDB Atlas
• AI Integration: Ollama (Mistral model)
• Environment Management: python-dotenv

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Getting Started 🚀

Follow these steps to set up the project locally.

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Prerequisites

• Python 3.8+
• Node.js 16+
• MongoDB Atlas account (or local MongoDB instance)
• Ollama installed and running locally (for AI responses)

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Installation

1. Clone the Repository

git clone https://github.com/your-username/simple-chat-app.git
cd simple-chat-app

2. Install Ollama

Ollama is required to run the Mistral model locally. Follow these steps to install it:

Download Ollama:

Visit the Ollama GitHub repository and download the latest release for your operating system.

Install Ollama:

Follow the installation instructions for your OS:

• Windows: Run the installer.
• macOS: Drag the Ollama app to your Applications folder.
• Linux: Use the provided .deb or .rpm package.

Start Ollama:

Open a terminal and run:

ollama serve

Pull the Mistral Model:

In a new terminal, run:

ollama pull mistral

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3. Set Up the Backend

Navigate to the backend directory:

cd backend

Create a virtual environment and activate it:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install the required Python packages:

pip install -r requirements.txt

Create a .env file in the backend directory and add your MongoDB URI:

MONGO_URI=mongodb+srv://<username>:<password>@cluster0.ln25i.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0

Run the Flask server:

python app.py

The backend will start at http://localhost:5000.

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4. Set Up the Frontend

Navigate to the frontend directory:

cd ../frontend

Install the required Node.js packages:

npm install

Start the React development server:

npm start

The frontend will start at http://localhost:3000.

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Running the Application

Ensure the backend (Flask) and frontend (React) servers are running.

Open your browser and go to http://localhost:3000.

Start chatting with the AI-powered chatbot! 🎉

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Contributing 🤝

We welcome contributions from the community! If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.

2. Create a new branch for your feature or bugfix:

   git checkout -b feature/your-feature-name

3. Commit your changes

   git commit -m "Add your commit message here"

4. Push your branch to your forked repository

   git push origin feature/your-feature-name

5. Open a pull request and describe your changes.

Acknowledgments 🙏

• Ollama for providing the AI model.
• Flask and React communities for their amazing documentation and support.
• MongoDB Atlas for free-tier database hosting.# chatbot_ai