https://github.com/duharyan/stud-notegpt
https://github.com/duharyan/stud-notegpt
google-gemini llama3 multimodal-rag optical-character-recognition
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/duharyan/stud-notegpt
- Owner: duharyan
- License: mit
- Created: 2025-01-27T18:51:57.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-19T08:29:57.000Z (2 months ago)
- Last Synced: 2025-02-19T09:29:15.037Z (2 months ago)
- Topics: google-gemini, llama3, multimodal-rag, optical-character-recognition
- Language: Python
- Homepage:
- Size: 349 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Stud-NoteGpt
StudNotesGpt is a Streamlit-based multimodal application that allows students to upload their notes in PPTX or PDF format and interact with them through a Retrieval-Augmented Generation (RAG) approach. Users can ask questions about their uploaded notes and get AI-powered answers.
## Features
- Upload PPTX or PDF files containing lecture notes.
- Extract text and images from uploaded files.
- Perform Optical Character Recognition (OCR) on extracted images.
- Store extracted content in a FAISS vector database.
- Query notes using AI models (Groq's LLaMA 3 or Google's Gemini 1.5 Flash).
- Get AI-generated responses based on document content.
## Installation
### Prerequisites
Ensure you have Python 3.8 or later installed. Then, install the required dependencies:
```sh
pip install -r requirements.txt
```
### Environment Variables
Create a `.env` file in the root directory and add your API keys:
```
GROQ_API_KEY=your_groq_api_key
GOOGLE_API_KEY=your_google_api_key
```
## Usage
Run the application using the following command:
```sh
streamlit run app.py
```
## Contributing
Feel free to submit issues and pull requests to improve StudNotes.