Interactive Document Analyzer (Gemini 1.5 Flash)

This Streamlit application provides an interactive document analysis experience using Google's Gemini 1.5 Flash model. Users can upload documents (PDF, DOCX, TXT) and receive a summarized analysis, including praise and constructive criticism. The application also allows for follow-up questions to further explore the document's content.

Features

• Document Upload: Supports uploading PDF, DOCX, and TXT files.
• Automatic Summarization: Uses Gemini 1.5 Flash to generate a concise summary of the uploaded document.
• Initial Analysis: Provides an initial analysis of the document summary, including praise and constructive criticism.
• Interactive Follow-Up Questions: Allows users to ask follow-up questions about the document's content and receive answers based on the summary.
• Chat History Display: Displays a history of the conversation, showing the user's questions and the AI's responses.

Technologies Used

• Streamlit: For building the interactive web application.
• Google Gemini API (via google-generativeai): For document summarization and analysis.
• pdfminer.six: For extracting text from PDF files.
• python-docx: For extracting text from DOCX files.

Prerequisites

Before running the application, you'll need the following:

• Python 3.7 or higher: Ensure you have a compatible Python version installed.
• Google Cloud Project and API Key: You'll need a Google Cloud project and API key to access the Gemini API. Get an API key from the Google AI Studio: https://makersuite.google.com/app/apikey
• Streamlit Account (Optional): For deploying the application to Streamlit Cloud.

Setup

1. Clone the Repository:

   git clone https://www.github.com/shotintoeternity/google-document-analyzer.git
   cd google-document-analyzer

2. Create a Virtual Environment (Recommended):

   python3 -m venv venv  # Create a virtual environment (Python 3.3+)
   # virtualenv venv       # If you have virtualenv installed

3. Activate the Virtual Environment:

   source venv/bin/activate  # Linux/macOS
   # venv\Scripts\activate   # Windows

4. Install Dependencies:

   pip install -r requirements.txt

   The requirements.txt file contains the list of required Python packages.

5. Configure API Key:

   Store your Google Gemini API key securely using one of the following methods:

   • Streamlit Secrets Management (Recommended for Streamlit Cloud):

     • Go to your Streamlit Cloud app's settings.
     • Add a new secret named GOOGLE_API_KEY and set its value to your API key.

   • Environment Variables:

     • Set an environment variable named GOOGLE_API_KEY on your system:

       export GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY"  # Linux/macOS
       # set GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY"   # Windows

   • secrets.toml file (for local development):

     • Create a file named .streamlit/secrets.toml in your project directory. Note that the file path is important.

     • Add the following line to the file, replacing YOUR_GOOGLE_API_KEY with your actual API key:

       GOOGLE_API_KEY = "YOUR_GOOGLE_API_KEY"

     • Important: Add .streamlit/secrets.toml to your .gitignore file to prevent committing your API key to version control.

Running the Application

1. Start the Streamlit App:

   streamlit run app.py

   Replace app.py with the name of your main Streamlit script.

2. Access the App:

   Streamlit will automatically open the app in your web browser. If it doesn't, you can access it by navigating to the URL displayed in the terminal (usually http://localhost:8501).

Usage

1. Upload a Document: Use the file uploader to select a PDF, DOCX, or TXT file.
2. View the Summary: The application will generate a summary of the document using Gemini 1.5 Flash and display it.
3. Review the Initial Analysis: The application will provide an initial analysis of the document summary, including praise and constructive criticism.
4. Ask Follow-Up Questions: Enter your questions in the text input field at the bottom and press Enter to submit them. The AI's response will be displayed below the input field.
5. View Conversation History: All interactions will be shown in the chat history.

Deployment (Streamlit Cloud)

1. Create a GitHub Repository: Upload your code (including requirements.txt, .streamlit/secrets.toml (make sure this is NOT tracked in Git), and app.py) to a new GitHub repository.
2. Create a Streamlit Cloud Account: Go to https://streamlit.io/cloud and sign up for a free account.
3. Connect to GitHub: In the Streamlit Cloud dashboard, click "New app" and connect to your GitHub repository.
4. Configure Secrets: Add your GOOGLE_API_KEY as a secret in the Streamlit Cloud app settings.
5. Deploy: Click "Deploy!" and Streamlit Cloud will automatically build and deploy your application.

Contributing

Contributions are welcome! If you find a bug, have a suggestion, or want to contribute code, please open an issue or submit a pull request.

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Disclaimer: This application uses AI to analyze documents. The accuracy and completeness of the analysis may vary. Use this tool as a starting point for your own research and analysis, and always consult with relevant experts for critical decisions.