Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/rohanag03/pdf-insights
https://github.com/rohanag03/pdf-insights
Last synced: 8 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/rohanag03/pdf-insights
- Owner: rohanag03
- Created: 2024-05-17T14:16:12.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-05-17T14:28:53.000Z (6 months ago)
- Last Synced: 2024-05-17T15:58:26.221Z (6 months ago)
- Language: Python
- Size: 3.91 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# PDF Content Analyzer
This project utilizes the power of Google's Generative AI to analyze and answer questions about the content of PDF documents. It provides a user-friendly interface to upload PDFs and ask questions, receiving insightful answers generated by the Gemini AI model.
## Prerequisites
Make sure you have Python installed on your system. Additionally, install the required dependencies with the following command:
```bash
pip install -r requirements.txt
```
## Features
- Upload PDF documents for analysis.
- Ask questions about the uploaded PDF content.
- Utilize the Gemini AI model to generate answers.
- Streamlit-based web interface for ease of use.
## How to Use
1. Run the Streamlit app by executing the following command in your terminal:
```bash
streamlit run main.py
```
2. Upload a PDF document using the provided file uploader.
3. Enter your question about the PDF content in the text input field.
4. View the generated answers based on the PDF content.
## File Structure
- main.py: The main application script for the Streamlit interface.
- requirements.txt: A list of Python libraries required for the project.
## Usage Notes
- The application requires an API key from Google Generative AI, which should be kept confidential.
- The PDF content is processed and stored temporarily for analysis.
## Further Development
- Support for Large Documents: Future updates will aim to optimize the processing of large PDF documents to ensure efficient analysis without compromising performance.