LLM-Polished-Version

Project Overview

LLM-Polished-Version is a Dockerized AI assistant designed to interact with users and provide intelligent responses. The project leverages advanced language models and is tailored for specific use cases, including petroleum-related queries. The assistant has been optimized for simplicity and supports terminal-based communication, ensuring compatibility with Arabic text.

Features

• AI Assistant: Powered by advanced language models for intelligent responses.
• Dockerized Setup: Encapsulated in a Docker container for easy deployment.
• Terminal-Based Interaction: Simplified communication via the terminal.
• Arabic Text Support: Ensures proper encoding and handling of Arabic letters.
• Customizable: Easily extendable for various use cases.

Project Structure

Dockerfile
requirements.txt
Docker/
LLM-Web/
    environment.yml
    llm_handler.py
    llm_handler.spec
    package.json
    server.js
    build/
        llm_handler/
            ...
    GeneratedContracts/
LLM/
    Model.gguf
    PetroBot.py
    PetroBot.spec
    petroleum_qa_1000.json
    Data/
        Contrat_Template_Placeholders.docx
        CostumerService/
            ...
        Learning/
            ...
        Petroleum/
            ...
    faiss_behavioral/
        ...
    faiss_expert/
        ...
    faiss_petroleum/
        ...
    GeneratedContracts/
        ...
webLLm/
    eslint.config.js
    index.html
    package.json
    README.md
    vite.config.js
    public/
        ...
    src/
        App.jsx
        main.jsx
        UserInfoForm.jsx
        assets/

Prerequisites

• Docker: Ensure Docker is installed on your system.
• Python: Version 3.10 or higher.
• Node.js: For managing the web interface.

Installation

1. Clone the repository:

   git clone https://github.com/Aminbcf/LLM-Polished-Version.git

2. Navigate to the project directory:

   cd LLM-Polished-Version

3. Build the Docker image:

   docker build -t petrobot-llm .

4. Run the Docker container:

   docker run -it petrobot-llm

Usage

• Terminal Interaction: The assistant communicates directly via the terminal. Ensure proper encoding for Arabic text.
• Custom Queries: Modify PetroBot.py to tailor the assistant for specific use cases.

Dependencies

• langchain_community
• sentence_transformers
• docxtpl
• docx2pdf

Ensure these dependencies are installed in the Docker image.

Contributing

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-branch-name

3. Commit your changes:

   git commit -m "Add new feature"

4. Push to the branch:

   git push origin feature-branch-name

5. Open a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

• Inspired by advancements in AI and language models.
• Special thanks to contributors and the open-source community.