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Advanced Document Analyzer

A Streamlit web application for extracting text from documents, performing analysis, generating AI-powered summaries, and answering questions.

Features

  • Multi-format Support: Supports PDF, DOCX, and TXT file uploads.
  • Text Extraction and Splitting: Extracts text from uploaded files and splits it into manageable paragraphs or chunks.
  • Semantic Search: Implements TF-IDF vectorization and cosine similarity to enable searching within the document.
  • AI Summarization: Generates summaries using the Ollama API.
  • Question Answering: Answers user queries based on document content using the Ollama API.
  • Text-to-Speech: Converts text to speech using gTTS.
  • Document History: Keeps track of recently uploaded documents.
  • Document Statistics: Calculates and displays various document statistics.
  • Document Comparison: Compares two documents for similarity.
  • Export Features: Allows exporting activity logs as CSV and analysis results as ZIP archives.
  • Customizable Settings: Includes configurable options for summary length, search result highlighting, dark mode, and more.
  • Robust Logging: Logs user actions and any errors encountered.

Installation

  1. Clone the repository:

    git clone <repository_url>
cd <repository_directory>

  2. Create a virtual environment (recommended):

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

  3. Install the required packages:

    pip install -r requirements.txt

  4. Set up Ollama:

    • Ensure that you have Ollama installed and running.
    • Verify that the Ollama API is accessible at http://localhost:11434.

Usage

  1. Run the Streamlit app:

    streamlit run docsummarizer.py

  2. Upload Documents:

    • Use the file uploader to upload your PDF, DOCX, or TXT files.

  3. Explore Features:

    • View extracted text.
    • Search within the document.
    • Generate summaries and ask questions using the AI model.
    • Listen to the text using the text-to-speech functionality.
    • Compare documents if desired.
    • View and export activity logs.

Configuration

Adjust the following settings in the sidebar:

  • Default Model: Select the default AI model to use.
  • Summary Length: Choose between short, medium, and long summaries.
  • Search Results Count: Set the number of search results to display.
  • Highlight Enabled: Toggle search term highlighting.
  • Save Logs: Enable or disable saving logs to a file.
  • Dark Mode: Switch between light and dark themes.

Logging

  • The application logs various activities and errors. Logs are stored in document_analyzer.log.
  • You can disable logging via the sidebar settings.
  • Export activity logs to CSV format for analysis.

Dependencies

  • streamlit
  • pandas
  • PyPDF2
  • python-docx
  • sklearn
  • gTTS
  • requests
  • plotly
  • numpy

Troubleshooting

  • Ollama API Connection Issues: Ensure Ollama is running and accessible at http://localhost:11434.
  • File Extraction Errors: Check the file format and ensure it's a valid PDF, DOCX, or TXT file.

License

This project is licensed under the MIT License.