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https://github.com/thecarbun/asknotes

Ai model on question answering from PDF notes
https://github.com/thecarbun/asknotes

artificial-intelligence langchain langchain-python openai-api openai-chatgpt streamlit

Last synced: 2 days ago
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Ai model on question answering from PDF notes

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README 

        
# AskNotes.ai



### ✨Try for free --> : [https://asknotes.streamlit.app/](https://asknotes.streamlit.app/home)



## 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](#about)

- [Features](#features)

- [Tech Stack](#tech-stack)

- [Getting Started](#getting-started)

- [Usage](#usage)

- [Project Structure](#project-structure)

- [Error Handling](#error-handling)

- [Future Enhancements](#future-enhancements)

- [Contributing](#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**:

    ```bash

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

    cd Asknotes

    ```

   

2. **Install dependencies**:

    ```bash

    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:

    ```toml

    [OPENAI_API_KEY]

    key = "your_openai_api_key_here"

    ```



4. **Run the app**:

    ```bash

    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.