ChatMinds 🧠💬

ChatMinds is an intelligent portfolio chatbot designed to showcase professional skills, projects, and experiences interactively. Now improved with Semantic Search, it understands the context of user queries ensuring highly reliable responses.

🚀 Features

• ✨ Semantic Search (Optimized): Uses TF-IDF Vectorization (scikit-learn) to match user questions with the Knowledge Base by analyzing text similarity.
• Intent Recognition: accurately identifies user intent (e.g., greetings, goodbyes) using regex patterns for instant responses.
• Smart Fallback: If the AI is unsure (low confidence score), it gracefully admits it doesn't know rather than guessing.
• Robust & Secure: Handles edge cases like gibberish, mixed case, and punctuation. Includes basic security sanitization.
• Efficiency: Extremely lightweight and fast, fully compatible with free tier serverless deployment (Vercel).

🛠️ Tech Stack

• Backend: Python 3, Flask
• AI/NLP: Scikit-learn (TF-IDF), NumPy
• Frontend: HTML5, CSS3, JavaScript (Chat Interface)
• Data: JSON (intents.json, questions.json)
• Deployment: Configured for Vercel

📂 Project Structure

Chat-Minds/
├── app.py                # Main Flask application and AI Logic
├── requirements.txt      # Python dependencies
├── vercel.json           # Vercel deployment configuration
├── testing.md            # Detailed testing and validation report (Legacy NLTK tests)
├── data/
│   ├── intents.json      # Definitions for broad intent matching
│   └── questions.json    # Knowledge base for specific Q&A
├── static/               # CSS and JS files for the frontend
├── templates/            # HTML templates (chat.html)

⚙️ Installation & Setup

1. Clone the Repository

   git clone <repository-url>
   cd Chat-Minds

2. Create a Virtual Environment (Optional but Recommended)

   python -m venv venv
   # Windows
   venv\Scripts\activate
   # macOS/Linux
   source venv/bin/activate

3. Install Dependencies

   pip install -r requirements.txt

   Note: The app is now optimized for instant startup.

🏃 Usage

1. Start the Flask Server

   python app.py

2. Access the Chatbot Open your web browser and navigate to: http://127.0.0.1:5000/

🧪 Testing

The logic has been upgraded to use Cosine Similarity.

• High Reliability: "Coding", "Programming", and "Dev" are now treated as related concepts.
• Thresholding: The bot filters out low-confidence matches to avoid hallucinations.

☁️ Deployment

This project includes a vercel.json configuration file. Optimized: The transition to TF-IDF ensures this project stays well within the 250MB limit of Vercel's free tier.

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Generated for ChatMinds Project