An AI-powered FAQ Chatbot built using Python, Streamlit, and Natural Language Processing (NLP). The chatbot answers frequently asked questions about StudyBuddy and basic programming topics using TF-IDF Vectorization and Cosine Similarity.
The StudyBuddy FAQ Chatbot is designed to provide quick and accurate answers to users by matching their questions with a predefined FAQ dataset.
Instead of relying on exact keyword matching, the chatbot uses Natural Language Processing techniques to understand user queries and return the most relevant answer.
This project was developed as part of the CodeAlpha Artificial Intelligence Internship.
- 💬 Interactive chat interface
- 🧠 FAQ matching using NLP
- 📚 Supports StudyBuddy-related questions
- 💻 Answers basic programming questions
- ⚡ Fast and lightweight
- 📝 Displays suggested questions for unknown queries
- 🧹 Clear Chat option
- 📱 Clean Streamlit interface
- Python
- Streamlit
- Scikit-learn
- TF-IDF Vectorizer
- Cosine Similarity
- JSON
StudyBuddy-FAQ-Chatbot/
│
├── app.py
├── chatbot.py
├── faq.json
├── requirements.txt
├── README.md
└── screenshots/
└── app.png
git clone https://github.com/vortex-001/StudyBuddy-FAQ-Chatbot.gitcd StudyBuddy-FAQ-Chatbotpip install -r requirements.txtstreamlit run app.pyThe application will automatically open in your default browser.
- Voice input support
- Text-to-Speech
- Multi-language support
- Better NLP preprocessing
- AI-powered conversational responses
- User authentication
- Chat history
- Export conversation
While building this project, I learned:
- Building web applications using Streamlit
- Implementing TF-IDF Vectorization
- Using Cosine Similarity for text matching
- Working with JSON datasets
- Basic Natural Language Processing concepts
- Managing projects using Git and GitHub
Harsh Garg
B.Tech Computer Science Engineering
GitHub: https://github.com/vortex-001
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