AskNotes.ai

✨Try for free --> : https://asknotes.streamlit.app/

Inspiration for this project:

During my university days, one of the biggest challenges I faced was studying from notes provided in the form of PDFs. Whether it was preparing for term exams or solving previous year's question papers, the process was time-consuming and often frustrating. Scrolling through countless pages just to find relevant answers felt like looking for a needle in a haystack. 🕵️‍♂️
That’s why I built AskNotes—an AI-powered tool designed to make studying faster, smarter, and more efficient! 🚀
With AskNotes, you can:
✅ Upload your notes in PDF format.
✅ Ask specific questions about the content.
✅ Get instant, accurate answers in just a few seconds.
No more wasting hours flipping through pages. Let AskNotes do the heavy lifting so you can focus on what matters most—understanding and learning.

---

Table of Contents

• About
• Features
• Tech Stack
• Getting Started
• Usage
• Project Structure
• Error Handling
• Future Enhancements
• Contributing

---

About

AskNotes is an interactive learning application designed for students to upload their study materials (in PDF format) and get AI-powered assistance in understanding the content. Built using Streamlit and LangChain, AskNotes provides a question-and-answer interface to query the content within PDF files, offering a personalized learning experience.

Features

• Upload Study Materials: Students can upload one or multiple PDFs containing study materials.
• Interactive Q&A: Ask questions about the uploaded content, and AskNotes will provide relevant answers.
• Session-based Chat: Tracks chat history during each session, allowing users to refer back to previous interactions.
• Secure and Temporary Storage: Uploaded PDFs are temporarily stored for processing and deleted automatically after use.
• Streamlit UI: A user-friendly chat interface for engaging with AskNotes, implemented using streamlit_chat.

---

Tech Stack

• Frontend: Streamlit for UI.
• Backend: LangChain (for Q&A processing), FAISS (for efficient vector storage and retrieval).
• Embeddings and Language Models: OpenAI embeddings and ChatGPT (gpt-4) for natural language understanding and answer generation.

---

Getting Started

Prerequisites

• Python 3.8+
• OpenAI API Key (for embeddings and GPT-4 model)

Installation

1. Clone the repository:

   git clone https://github.com/TheCarBun/Asknotes.git
   cd Asknotes

2. Install dependencies:

   pip install -r requirements.txt

3. Set up OpenAI API key: Add your OpenAI API key to Streamlit secrets by creating a secrets.toml file in the .streamlit folder:

   [OPENAI_API_KEY]
   key = "your_openai_api_key_here"

4. Run the app:

   streamlit run app.py

---

Usage

1. Upload PDFs:

   • Use the sidebar file uploader to upload one or more PDF files.
   • Files will be processed and used to create a searchable vector store.

2. Ask Questions:

   • Type a question in the chat input related to the PDF content.
   • The app will display responses based on the contents of the uploaded materials.

3. Clear Chat History:

   • Use the "Clear Chat History" button in the sidebar to reset the chat for a fresh session.

---

Project Structure

├── asknotes.py             # Main application file
├── requirements.txt         # Python dependencies
├── .streamlit/
│   └── secrets.toml         # API keys and secrets
├── README.md                # Project documentation
└── ...                      # Additional project files and configurations

---

Error Handling

The app includes exception handling for better stability:

• API Key Missing: Displays an error if the OpenAI API key is not configured correctly.
• File Loading: Catches errors when loading PDFs and warns the user if a file cannot be processed.
• Vectorstore Creation: Handles issues during vectorstore creation, providing user feedback on errors.
• Query Processing: Informs the user if an error occurs while querying the vectorstore.
• Temp File Deletion: Any issues with file deletion after processing are logged to avoid storage issues.

These exceptions ensure a more resilient app and a smoother user experience.

---

Future Enhancements

• Support for Additional File Types: Extend support to handle TXT, DOCX, and EPUB files for broader usability.
• Answer Summarization: Include a summarization option for longer responses.
• Enhanced NLP: Add fine-tuning capabilities to improve relevance and answer quality based on specific course material.
• User Authentication: Implement session tracking with user authentication to store user chat history for later review.

---

Contributing

We welcome contributions! Please follow these steps to contribute:

1. Fork the project.
2. Create your feature branch (git checkout -b feature/your-feature-name).
3. Commit your changes (git commit -m 'Add your message').
4. Push to the branch (git push origin feature/your-feature-name).
5. Open a Pull Request.

Please ensure your code follows the existing style and includes comments where necessary.

---

Enjoy using AskNotes.ai for your interactive learning journey! Feel free to reach out for any questions or issues with the project.