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https://github.com/anubhab-m02/pdf-qna
Project that uses the Gemini Pro Model to ask anything from the relevant document.
https://github.com/anubhab-m02/pdf-qna
gemini generative-ai pdf-question-answer
Last synced: about 1 month ago
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Project that uses the Gemini Pro Model to ask anything from the relevant document.
- Host: GitHub
- URL: https://github.com/anubhab-m02/pdf-qna
- Owner: anubhab-m02
- Created: 2024-08-30T16:06:48.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-10-26T06:03:48.000Z (4 months ago)
- Last Synced: 2024-11-08T12:27:58.662Z (3 months ago)
- Topics: gemini, generative-ai, pdf-question-answer
- Language: Python
- Homepage:
- Size: 43 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
# AI-Powered Personalized Learning Assistant
Elevate your learning experience with our cutting-edge AI-powered assistant that transforms the way you interact with educational content. Leveraging the advanced capabilities of Google's Gemini Pro LLM, this application offers a suite of features designed to enhance comprehension, retention, and engagement with your study materials.
## 🚀 Features
- **Intelligent Document Processing:** Easily upload and analyze multiple PDF documents.
- **Interactive Q&A:** Have dynamic conversations about your content.
- **Adaptive Quiz Generation:** Automatically generate quizzes to test your knowledge.(**Still glitchy, working on fixes!!**)
- **Smart Summarization:** Receive concise overviews of complex documents.
- **Flashcard Creation:** Create study aids for efficient revision.
- **Multilingual Support:** Translate content into various languages.
- **Document Sharing:** Share processed documents via email.
- **Text Complexity Analysis:** Understand the readability of your materials.
- **Key Concept Extraction:** Quickly identify crucial ideas.
- **Audio Learning:** Convert text to speech for on-the-go studying. (**Coming Soon**)
- **Progress Tracking:** Keep a comprehensive chat history of your learning journey.
## 🛠️ Technology Stack
- **Core:** `Python 3.11`
- **Framework:** `Streamlit`
- **AI Model:** `Google Gemini Pro`
- **NLP & ML:** `LangChain`, `Transformers`, `Scikit-learn`
- **Data Processing:** `PyPDF2`, `FAISS`
- **Visualization:** `Matplotlib`, `Seaborn`
- **Audio:** `gTTS` (Google Text-to-Speech)
## 🚀 Getting Started
1. **Clone & Setup:**
**For Mac/Linux:**
```bash
git clone https://github.com/anubhab-m02/PDF-QnA.git
cd PDF-QnA
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
**For Windows:**
```bash
git clone https://github.com/anubhab-m02/PDF-QnA.git
cd PDF-QnA
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
```
2. **API Configuration:**
- Obtain a Google Cloud API key with Gemini Pro access.
- Create a `.env` file in the project root:
```
GOOGLE_API_KEY=your_api_key_here
```
3. **Launch:**
```bash
streamlit run app.py
```
## 💡 Usage Guide
1. **Document Upload:** Use the sidebar to upload your PDF documents.
2. **Processing:** Click "Process Documents" to analyze your materials.
3. **Feature Selection:** Choose from a variety of learning tools in the main interface.
4. **Interaction:** Engage with the AI assistant through your chosen feature.
## 🔐 Security & Performance
- **Safe Deserialization:** Exercise caution with `allow_dangerous_deserialization=True`. Only use with trusted FAISS index sources.
- **Efficient Indexing:** The FAISS index updates incrementally, preserving knowledge from all uploaded documents.
- **Automatic Cleanup:** Old data and large caches are periodically removed to maintain performance.
## 🤝 Contributing
Contributions are welcome! Whether it's feature suggestions, bug reports, or code improvements, please feel free to open an issue or submit a pull request.