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An AI-powered web app for real-time sentiment analysis using Hugging Face Transformers and Streamlit.

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Multi Language Sentiment Analysis App

📌 Overview

This is a Multi Language Sentiment Analysis App built with Streamlit and Hugging Face Transformers. It allows users to analyze the sentiment (Positive, Negative) of any given text using state-of-the-art NLP models.

🚀 Features

  • Sentiment History to track past analyses in a session.
  • Graphical Representation of sentiment confidence using a progress bar.
  • Multi-Language Support via Google Translate.
  • File Upload Support for bulk sentiment analysis.
  • Download Results as a CSV file.
  • Emoji-based Sentiment Display for better UX.

🛠️ Installation

  1. Clone the repository:
    git clone https://github.com/hasanulmukit/sentiment-analysis-app.git
    cd sentiment-analysis-app
  2. Install dependencies:
    pip install -r requirements.txt
  3. Run the app:
    streamlit run app.py

📊 Usage

  • Enter Text: Type or paste a sentence in the text area.
  • Analyze Sentiment: Click the "Analyze" button to get sentiment results.
  • View History: Check previous sentiment analyses.
  • Upload Files: Upload .txt or .csv files for batch analysis.
  • Download Results: Save the analysis as a CSV file.

🏗️ Technologies Used

  • Python 🐍
  • Streamlit 🎨 (for UI)
  • Transformers 🤗 (Hugging Face NLP Models)
  • SpeechRecognition 🎙️ (for voice input)
  • GoogleTrans 🌍 (for multi-language support)
  • Matplotlib & Pandas 📊 (for visualization & data processing)

🎯 Future Improvements

  • Improve accuracy with fine-tuned models.
  • Add support for more advanced NLP techniques.
  • Deploy the app using Streamlit Cloud or Hugging Face Spaces.

💡 Contribution

Feel free to fork this repo, improve it, and submit a pull request! 🚀

📜 License

This project is licensed under the MIT License.


🌟 Show Your Support

Give a ⭐️ if you found this useful!

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An AI-powered web app for real-time sentiment analysis using Hugging Face Transformers and Streamlit.

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