CLAPP - CLASS LLM Agent for Pair Programming

CLAPP is a Streamlit application that provides an AI pair programming assistant specialized in the CLASS cosmology code. It uses LangChain and OpenAI models, leveraging Retrieval-Augmented Generation (RAG) with CLASS documentation and code examples to provide informed responses and assist with coding tasks.

Collaborators

• Santiago Casas
• Christian Fidler
• Julien Lesgourgues
• With contributions from: Boris Bolliet & Francisco Villaescusa-Navarro
• inspired by the CAMELS-Agent-App

Features

• Conversational AI: Interact with an AI assistant knowledgeable about CLASS and cosmology.
• CLASS Integration: Built-in tools to install, test, and use the CLASS cosmological code.
• Code Execution: Executes Python code snippets in real-time, with automatic error detection and correction.
• Plotting Support: Generates and displays cosmological plots from CLASS outputs.
• RAG Integration: Retrieves relevant information from CLASS documentation and code (./class-data/) to answer questions accurately.
• Multiple Response Modes:
  • Fast Mode: Quick responses with good quality (recommended for most uses)
  • Swarm Mode: Multi-agent refined responses for more complex questions (takes longer)
• Secure User Management: Username-based API key storage allows multiple users to securely save encrypted API keys.
• Real-time Feedback: Streams installation and execution progress in real-time.
• Model Selection: Choose between different OpenAI models (GPT-4o, GPT-4o-mini).

Setup and Installation

This project uses conda/mamba for environment management, which is compatible with CLASS installation requirements.

1. Clone the repository:

   git clone https://github.com/santiagocasas/clapp.git
   cd clapp

2. Create a conda environment from the environment.yml file:

   # Using conda
   conda env create -f environment.yml
   
   # Or using mamba (faster)
   mamba env create -f environment.yml

3. Activate the environment:

   conda activate clapp

4. API Key:

   • You will need an OpenAI API or Gemini key.
   • The application allows you to enter a username, API key, and password to encrypt and store it locally.
   • Keys are saved as {username}_encrypted_api_key to allow multiple users.
   • Get your free Gemini key from https://aistudio.google.com/app/apikey

5. CLASS Installation:

   • CLAPP includes a built-in CLASS installation button that will install CLASS from source.
   • Alternatively, you can check if CLASS is already installed using the provided tool.

6. CLASS Data:

   • Ensure the class-data directory contains the necessary CLASS documentation, code files (.py, .ini, .txt), and potentially PDF documents for the RAG system.

7. System Prompts:

   • Ensure the prompts/ directory contains the necessary instruction files (class_instructions.txt, review_instructions.txt, etc.).

Usage

1. Activate the conda environment:

   conda activate clapp

2. Run the Streamlit application:

   streamlit run CLAPP.py

3. Setup process:

   • Enter your OpenAI API key and optionally a username and password for encryption.
   • Initialize the application by clicking "Initialize with Selected Model".
   • Check if CLASS is installed or install it using the provided buttons.
   • Start chatting with the assistant about CLASS-related questions or cosmology code.

4. Code execution:

   • When the assistant provides code, you can execute it by typing "execute!" in the chat.
   • The system will run the code, display the output, and show any generated plots.
   • If errors occur, the system will automatically attempt to fix them.

Project Structure

• CLAPP.py: The main Streamlit application script.
• install_classy.sh: Script to install CLASS from source.
• test_classy.py: Script to test CLASS installation and functionality.
• environment.yml: Conda environment specification with all required dependencies.
• class-data/: Directory containing data for the RAG system (CLASS code, docs, etc.).
• prompts/: Directory containing system prompts for the AI agents.
• images/: Contains images used in the app interface, including the CLAPP logo.
• {username}_encrypted_api_key: Stores the encrypted OpenAI API keys for each user.

Working with CLASS

CLAPP allows you to:

1. Learn about CLASS: Ask questions about CLASS cosmology code features, parameters, and usage.
2. Develop cosmology code: Get help writing code that uses CLASS for cosmological calculations.
3. Debug and fix errors: Get assistance with error messages and issues in your CLASS code.
4. Visualize results: Generate and view plots of cosmological data.