💪 FitBot — Fitness FAQ Chatbot

CodeAlpha AI Internship | Task 2

An NLP-powered FAQ chatbot focused on fitness and nutrition. Uses TF-IDF vectorization and cosine similarity to match user questions with the most relevant FAQ answer.

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✨ Features

• 🤖 NLP-powered matching — TF-IDF + cosine similarity via scikit-learn
• 🧹 Text preprocessing — tokenization, stopword removal via NLTK
• 💬 Chat UI — Streamlit chat interface with message history
• ⚡ Quick suggestions — one-click example questions
• 🏋️ 30+ FAQs — covering protein, workouts, supplements, fat loss, muscle building

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🛠️ Tech Stack

Tool	Purpose
Streamlit	Chat UI
NLTK	Tokenization & stopword removal
scikit-learn	TF-IDF vectorization & cosine similarity
Python 3.8+	Core language

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🚀 Setup & Run

1. Clone the repo

git clone https://github.com/YOUR_USERNAME/CodeAlpha_FAQChatbot.git
cd CodeAlpha_FAQChatbot

2. Install dependencies

pip install -r requirements.txt

3. Run the app

streamlit run app.py

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📁 Project Structure

CodeAlpha_FAQChatbot/
├── app.py              # Main Streamlit app + NLP logic
├── faqs.py             # FAQ dataset (70+ Q&A pairs)
├── requirements.txt    # Dependencies
└── README.md           # This file

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🧠 How It Works

1. User types a question
2. Question is preprocessed (lowercased, punctuation removed, stopwords filtered)
3. TF-IDF vectorizer converts all FAQ questions + user question into vectors
4. Cosine similarity finds the closest matching FAQ
5. If similarity > threshold (0.15), the matched answer is returned
6. Otherwise, a fallback message is shown

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👤 Author

Built as part of the CodeAlpha AI Internship program.