DocuSage is an advanced document processing assistant that enables users to extract text from various document formats, including images and PDFs, in any language. It provides a conversational interface for users to ask questions based on the extracted content, facilitating efficient information retrieval and analysis.
- Document Upload: Users can upload images or PDF documents for processing.
- Text Extraction: Extracts visible text from documents regardless of the language and provides English translations for non-English text.
- Conversational Interface: Users can engage in a dialogue to ask questions about the content extracted from the document.
- Contextual Awareness: Maintains context throughout the conversation for seamless follow-up questions.
- Interactive Responses: Provides detailed, relevant answers based on the extracted content.
To set up the project locally, follow these steps:
- Clone the repository:
git clone https://github.com/Hsinha11/DocuSage-AI-Document-Assistant.git cd DocuSage-AI-Document-Assistant - Create a virtual environment (optional but recommended):
python -m venv venv
- Activate the virtual environment:
.\venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Set up environment variables: Create a
.envfile in the project root and add your Google API key:GOOGLE_API_KEY=your_api_key_here
- Run the application:
streamlit run main.py
- Upload a document: Choose an image or PDF file to upload.
- Ask questions: Use the input field to inquire about the content of the uploaded document.
This project is licensed under the MIT License. See the LICENSE file for more information.
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.
- Special thanks to the creators of the Google Generative AI for providing the powerful API used in this project.