🔐 Smart Feedback Analyzer

A secure, sentiment-aware feedback collection platform built using Streamlit, NLTK, and Matplotlib. Users can create feedback rooms, submit feedback anonymously, analyze sentiments, and download results – all without needing an account.

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🚀 Features

• ✅ Create unique feedback rooms with a title and description
• ✍️ Submit anonymous feedback (with profanity and PII masking)
• 📊 Analyze feedback using:
  • Average sentiment (0–5 scale)
  • Sentiment pie chart (positive/neutral/negative)
  • Top keywords bar chart
  • AI-generated summaries (semantic and contextual)
• 🔼 Vote on feedback (upvote/downvote)
• 📥 Import & merge feedback from CSV
• 📤 Export feedback to CSV
• 🤖 Auto-summarization using keyword frequency and NLTK sentiment

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📦 Dependencies

Install the required Python packages:

pip install streamlit pandas matplotlib nltk

NLTK will download resources at runtime:

nltk.download("stopwords")
nltk.download("vader_lexicon")

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🏁 How to Run

streamlit run main.py

By default, Streamlit will launch on: http://localhost:8501

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🗂️ Folder Structure

📁 rooms/                  # Stores all feedback CSVs and room metadata
├── [room_id].csv         # Feedback data
├── [room_id]_meta.csv    # Metadata (title + description)
📄 main.py                 # Streamlit app script
📄 README.md               # Project documentation

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📌 Notes

• Personal Info Masking: Phone numbers and emails are masked.
• Profanity Filter: Basic offensive words are censored automatically.
• Stateless Voting: Votes are stored in CSV but not tied to IPs or users.
• No Authentication: Fully anonymous by design.

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🙌 Built With

• Streamlit
• NLTK
• Matplotlib
• 💡 Powered by your creativity!

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📃 License

This project is open-source and free to use for educational and non-commercial purposes.

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👨‍💻 Author

Made with ❤️ by Vaibhav Rawat