📚 Conversational AI Data Science Tutor

A Conversational AI Chatbot built with **Streamlit, LangChain, and Google Gemini **.
This AI tutor answers only Data Science-related doubts while maintaining conversation awareness with memory.

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🚀 Features

✅ Uses Google Gemini 1.5 Pro (Free API)
✅ Conversation Memory (Remembers past interactions)
✅ Built with LangChain & Streamlit for a simple UI
✅ Free Deployment on Streamlit Cloud

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🛠 Tech Stack

• Frontend: Streamlit
• AI Model: Google Gemini 1.5 Pro (via LangChain)
• Memory: LangChain ConversationBufferMemory
• Deployment: Streamlit Cloud

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📂 Project Structure

📦 AI-Data-Science-Tutor ┣ 📜 .env # Stores Google API Key (DO NOT SHARE) ┣ 📜 config.py # Loads API key from .env ┣ 📜 app.py # Main Chatbot App (Streamlit) ┣ 📜 requirements.txt # Python Dependencies ┗ 📜 README.md # This File

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🔧 Installation & Setup (Run Locally)

1️⃣ Clone the Repository

git clone https://github.com/YOUR-USERNAME/AI-Data-Science-Tutor.git
cd AI-Data-Science-Tutor
2️⃣ Create a Virtual Environment (Recommended)

python -m venv venv
Activate it:

Windows: venv\Scripts\activate
Mac/Linux: source venv/bin/activate
3️⃣ Install Dependencies

pip install -r requirements.txt
4️⃣ Get Google Gemini API Key
Go to Google AI Studio
Sign in → Get API Key
Copy the API key
Create a .env file in the project folder & add:

GOOGLE_API_KEY=your-api-key
5️⃣ Run the Chatbot

streamlit run app.py
🌍 Deploy on Streamlit Cloud (Free)
Push your code to GitHub
bash
git add .
git commit -m "Initial commit"
git push origin main
Go to Streamlit Cloud
Sign in with GitHub
Deploy App → Set app.py as the main file
Click "Deploy" 🎉

🤖 How It Works
Enter your Data Science-related question
The AI responds with an explanation
Conversation Memory maintains context
🛠 Troubleshooting
LangChain Community Module Not Found?
Run this:

bash
pip install --upgrade langchain langchain-community langchain-google-genai
Streamlit Not Found?
bash
pip install streamlit
🎯 Next Steps
Improve UI design
Add more AI capabilities
Deploy on Hugging Face Spaces
💡 Credits
Developed by: Your Name
Model: Google Gemini 
Frameworks: LangChain, Streamlit
⭐ Like This Project? Give It a Star on GitHub! ⭐


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### **💡 What’s Included?**
✔️ Installation Steps  
✔️ API Key Setup  
✔️ Running Instructions  
✔️ Deployment Guide  
✔️ Troubleshooting Section  

💡 **Next Steps:**  
- Upload this **`README.md`** to GitHub  
- Create a **`requirements.txt`** by running:
  ```bash
  pip freeze > requirements.txt