Quantum Insights ⚡️

Welcome to Quantum Insights, a research assistant designed to simplify access to cutting-edge research in quantum physics. This project leverages LLMs (Large Language Models) to synthesize, summarize and explain complex scientific papers, making them accessible to everyone—whether you're a seasoned scientist or just starting out.

For the moment, you have to use your proper 'Pro Hugging Face API Key' to run the application. You can get one by signing up on the Hugging Face website, the key should be placed in a src/app/.env file.

Project is still in development, stay tuned for the next updates ! 😉

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Key Features

• Research Summaries: Extract key information from ArXiv papers.
• Concept Explanation: Break down complex scientific topics into simple, digestible concepts.
• Code Extraction: Identify and explain code snippets from research papers.
• Multilevel Support: Adjust research papers explanation level to reach a global audience.

Example Usage

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Stack

1. Arxiv API Integration: Search and fetch the latest papers from ArXiv's extensive database.
2. Document Processing: Structure detection with SpaCy en_core_web_sm and sentiment analysis using DistilBERT [Model card].
3. Embeddings: Generate document embeddings with sentence-transformers all-MiniLM-L6-v2 [Model card].
4. Vector Storage: Persistently store document embeddings using ChromaDB.
5. RAG System: Implement Retrieval-Augmented Generation to retrieve relevant documents via ChromaDB.
6. Text Generation: Utilize LLaMA 2 (Llama-2-7b-chat-hf) for text-to-text generation [Model card].
7. Streamlit UI: User interface with Streamlit for seamless interaction.
8. CI/CD: Testing and deployment using GitHub Actions and Docker.
9. Cloud Deployment: Application deployment on AWS.

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Why Use This Project?

Whether you’re a scientist, industry professional, or beginner, this project empowers you to dive deep into the latest breakthroughs in quantum research. You’ll be able to search, summarize, and explore complex topics without the typical technical barriers. The integration of modern NLP ensure an efficient and user-friendly experience.

Get started today and bridge the gap between research and innovation! 🌐

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Table of Contents

• Installation
• Usage
• Project Structure
• License

Prerequisites

Before you begin, ensure you have the following software installed on your system:

• Python 3.10+: This project uses Python, so you'll need to have Python installed. You can download it from python.org.
• Poetry: This project uses Poetry for dependency management. Install it by following the instructions at python-poetry.org.
• Docker (Optional): If you prefer to run the project in a Docker container, ensure Docker is installed. Instructions can be found at docker.com.

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Installation

Follow these steps to install and set up the project:

1. Clone the Repository:

   git clone https://github.com/mriusero/projet-sda-mlops
   cd projet-sda-mlops

2. Install Dependencies:

   Using Poetry:

   poetry install

   This will create a virtual environment and install all dependencies listed in pyproject.toml.

3. Activate the Virtual Environment:

   If Poetry does not automatically activate the virtual environment, you can activate it manually:

   poetry shell

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Usage

You can run the application locally or inside a Docker container.

Running Locally

To run the application locally, execute the following command:

python streamlit run app.py

Running with Docker

1. Build the Docker Image:

   docker build -t streamlit .

2. Run the Docker Container:

   docker run -p 8501:8501 streamlit

   This will start the application, and you can access it in your web browser at http://localhost:8501.

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Project Structure

The project follows a modular structure, with the following directories and files:

├── Dockerfile
├── LICENSE
├── README.md
├── app.py
├── database
│   ├── arxiv_data.db
│   └── conversations
│       ├── About-Quantum-Physics_2024-10-16-17-09-39.json
│       ├── Code-Algorithms_2024-10-16-17-21-50.json
│       ├── Industrial-Applications_2024-10-16-17-33-34.json
│       ├── Mathematics_2024-10-16-17-29-38.json
│       └── Quantum-Discoveries_2024-10-16-17-38-32.json
├── poetry.lock
├── pyproject.toml
├── src
│   ├── __init__.py
│   └── app
│       ├── __init__.py
│       ├── components
│       │   ├── __init__.py
│       │   ├── repo_button.py
│       │   └── utils.py
│       ├── features
│       │   ├── __init__.py
│       │   ├── arxiv_data_manager
│       │   │   ├── __init__.py
│       │   │   ├── arxiv_client.py
│       │   │   ├── arxiv_db.py
│       │   │   ├── arxiv_parser.py
│       │   │   └── search_and_update.py
│       │   └── research_assistant
│       │      ├── __init__.py
│       │      ├── checkpoints
│       │      │   └── processed_pdfs.pkl
│       │      ├── processing
│       │      │   ├── __init__.py
│       │      │   ├── preprocessing.py
│       │      │   ├── preprocessor.py
│       │      │   └── store_manager.py
│       │      ├── qa_system
│       │      │   ├── __init__.py
│       │      │   ├── conversation_saving.py
│       │      │   ├── conversation_ui.py
│       │      │   ├── qa_helper.py
│       │      │   └── qa_system.py
│       │      ├── skeleton.py
│       │      └── utilities
│       │          ├── __init__.py
│       │          └── helper.py
│       ├── layout
│       │   ├── __init__.py
│       │   ├── images
│       │   │   └── llama-icon.png
│       │   ├── layout0.py
│       │   ├── layout1.py
│       │   ├── layout2.py
│       │   ├── layout3.py
│       ├── streamlit_app.py
│       └── styles.css
└── tests
    └── test.py

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License

This project is licensed under the terms of the MIT License.