🤖 AI Mentor Chatbot (Module-Enforced Learning Assistant)

An interactive AI-powered mentor chatbot built with Streamlit, LangChain, and Hugging Face LLMs that provides strict, domain-specific mentorship.
The system enforces hard module boundaries to ensure focused, distraction-free learning with a mentor persona configurable by industry experience.

✨ Features

• 🎯 Strict Module Enforcement
  Answers are generated only for the selected module. Out-of-scope questions are explicitly refused.

• 🧑‍🏫 Experience-Based Mentorship
  Responses adapt dynamically based on selected years of industry experience.

• 🔁 Dynamic LLM Routing
  Automatically selects the best Hugging Face model for each domain:

  • Python, EDA → DeepSeek
  • SQL, Power BI → LLaMA
  • Machine Learning, Deep Learning → Qwen
  • Generative AI, Agentic AI → MiMo

• 💬 Persistent Chat Memory
  Maintains conversation context per module and resets automatically when the module changes.

• 🎨 Modern Chat UI
  Clean, ChatGPT-style interface built using custom HTML + CSS inside Streamlit.

• 📥 Chat History Export
  Download complete conversations as a .txt file.

📚 Supported Modules

• Python
• SQL
• Power BI
• Exploratory Data Analysis (EDA)
• Machine Learning
• Deep Learning
• Generative AI
• Agentic AI

🛠 Tech Stack

• Frontend: Streamlit, HTML, CSS
• LLM Orchestration: LangChain
• Models: Hugging Face Inference API
• State Management: Streamlit Session State
• Environment Management: python-dotenv

📂 Project Structure

├── app.py                 # Module & experience selection UI
├── pages/
│   └── mentor.py         # Mentor chatbot interface
├── .env                   # Hugging Face API token
├── requirements.txt
└── README.md

🚀 Use Cases

• Focused technical learning without topic drift
• Interview preparation with strict domain boundaries
• Mentor-style Q&A for beginners and intermediates
• Portfolio-ready AI application demonstrating LLM control

⚙️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/ShubhamMohanty680/AI_Mentor_Chatbot.git
cd AI_Mentor_Chatbot

2️⃣ Create Virtual Environment

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

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Set Environment Variables (Create a .env file and add)

GOOGLE_API_KEY=your_gemini_api_key

5️⃣ Run the Application

streamlit run app.py