PromptoLab

PromptoLab

PromptoLab is a cross-platform desktop application for cataloging, evaluating, testing, and improving LLM prompts. It provides a playground for interactive prompt development and a test set manager for systematic prompt testing.

Key Features

• Prompts Catalog: Seamlessly define and organize prompts using three distinct prompt categories. This centralized hub ensures your prompts are always accessible and well-structured for easy reuse.

• LLM Playground: Dive into experimentation with two dynamic options. Choose to submit a selected prompt from your catalog or request improvements for a given prompt using one of three proven prompt patterns. Customize your experience further by selecting your preferred LLM model and tweaking three critical LLM control parameters. Support for {{variable}} syntax in prompts enables quick testing of prompt variations through an interactive variables table.

• Prompts Test Set Manager: Simplify testing of complex system prompts in generative AI applications. Define and manage test cases to ensure your system prompt guides LLM responses effectively across various user prompts.

• Evaluation Playground: Assess the impact of prompt adjustments with ease. This powerful tool helps you evaluate whether modifications to a system prompt enhance or hinder LLM responses across diverse user scenarios, giving you the confidence to optimize with precision.

With PromptoLab, navigating the complexities of prompt design has never been more intuitive or exciting. Ready to optimize your prompt's performance?

Prerequisites

• Python 3.10 or higher
• One of the following LLM backends:
  • llm command-line tool

    pip install llm

  • LiteLLM library

    pip install litellm (NOTE: not needed because it is already defined inside requirements.txt)

• QSettings configuration for storing LLM backend preferences

Installation

1. Clone the repository:

   git clone https://github.com/crjaensch/PromptoLab.git
   cd PromptoLab

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows: venvScriptsactivate

3. Install dependencies:

   python3 -m pip install -r requirements.txt

Configuration

PromptoLab uses Qt's native configuration system (QSettings) to persist your LLM backend preferences. The settings are automatically saved and restored between application launches, with storage locations optimized for each platform:

• Windows: Registry
• macOS: .plist files
• Linux: INI-style files

You can configure your preferred LLM backend and API settings through the application's interface. The following options are available:

• LLM Backend: Choose between the llm command-line tool or LiteLLM library

• API Configuration: Provide API keys for your preferred LLM models when using LiteLLM, such as:

  • OpenAI API Key
  • Groq API Key
  • Google Gemini API Key

• Note that locally installed LLMs, e.g. via Ollama, are supported for LiteLLM.

Running the Application

1. Ensure your virtual environment is activated:

   source venv/bin/activate  # On Windows: venvScriptsactivate

2. Run the application:

   # If inside PromptoLab, then move to the parent directory
   cd ..
   python3 -m PromptoLab

Application Screenshots

Here's a quick visual overview of PromptoLab's main features:

Prompts Catalog

LLM Playground - Submit Prompt

LLM Playground - Submit Prompt with Variables

LLM Playground - Improve Prompt

Test Set Manager

Eval Playground

Evaluation Results Report

Development

The project uses:

• PySide6 for the GUI to enable cross-platform use
• Simon Willison's llm tool for LLM interactions
• BerriAI's litellm library
• Python's built-in venv for environment management

License

This project is licensed under the MIT License. See the LICENSE file in the repository for the full license text.