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Quest Dev Copilot

Quest Dev Copilot is an AI-powered debugging assistant for Unreal Engine Quest VR development. This system combines Retrieval-Augmented Generation (RAG), Llama API integration, Gemini for embeddings, and Unreal Engine plugins to provide intelligent error analysis and potential fixes.

Project Goals

  • Provide intelligent analysis of Unreal Engine logs for Quest VR development.
  • Suggest potential fixes and relevant documentation for identified errors.
  • Integrate with Unreal Engine via a Slate UI plugin.
  • Utilize Llama API for advanced reasoning and Gemini for embeddings.
  • Implement a robust backend for processing and a user-friendly CLI.

Core Technologies

  • AI/ML: Llama API, Gemini, ChromaDB
  • Backend: Flask, asyncio/aiohttp, BeautifulSoup
  • Frontend/Client: Unreal Engine Slate (C++), Rich CLI (Python)
  • Data: Forum scraping, vector embeddings, JSON processing

Getting Started

Prerequisites

  • Python 3.9+
  • Unreal Engine (Specify Version)
  • Access to Llama API
  • Access to Google Gemini API

Setup

  1. Clone the repository:

    git clone <repository-url>
cd quest-dev-copilot

  2. Create and populate .env file: Copy .env.example to .env and fill in your API keys and any other necessary environment variables:

    cp .env.example .env
# Open .env and add your LLAMA_API_KEY and GEMINI_API_KEY

  3. Backend Setup:

    cd backend
# python -m venv venv
# source venv/bin/activate (or venv\Scripts\activate on Windows)
# pip install -r requirements.txt
# flask run

    (Detailed backend setup steps will be added here)

  4. RAG Setup: (Detailed RAG setup and data ingestion steps will be added here)

  5. Unreal Engine Plugin Setup: (Detailed steps for integrating the plugin will be added here)

  6. CLI Setup: (Detailed CLI setup steps will be added here)

Usage

(Usage instructions for the Unreal Engine plugin and CLI will be added here)

Project Structure

quest-dev-copilot/
├── backend/            # Flask backend application
│   ├── app.py          # Main Flask application
│   ├── routes/         # API route definitions
│   ├── models/         # Data models and schemas
│   └── utils/          # Helper functions
├── rag/                # Retrieval-Augmented Generation components
│   ├── vector_store.py # ChromaDB interface
│   ├── embeddings.py   # Embedding utilities (using Gemini)
│   └── retrieval.py    # Document retrieval logic
├── llama/              # Llama API integration
│   ├── client.py       # Main Llama API client
│   ├── models.py       # Response models
│   └── cost_tracker.py # Usage analytics
├── unreal_plugin/      # Unreal Engine Slate plugin (C++)
│   └── ...
├── cli/                # Python Rich CLI
│   └── ...
├── tests/              # Unit and integration tests
│   ├── unit/
│   ├── integration/
│   └── fixtures/
├── .env.example        # Example environment variables
├── requirements.txt    # Python dependencies for the backend/CLI
└── README.md           # This file

Contributing

(Contribution guidelines will be added here)

License

(License information will be added here)