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PromptBuster

A Python GUI tool for systematically improving prompts using LLM feedback. PromptBuster implements a 7-step workflow that leverages the LLM's own weights to generate better prompts than you could write manually.

Features

  • 7-Step Workflow: Guided process for prompt improvement
  • Multiple LLM Providers: Support for OpenAI, Anthropic, and local models
  • Modern GUI: Clean Tkinter interface with CustomTkinter
  • Configuration Management: Save/load settings and sessions
  • Async Processing: Non-blocking LLM requests

Installation

  1. Clone the repository:
git clone <repository-url>
cd PromptBuster
  1. Create a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. Install dependencies:
pip install -r requirements.txt
  1. Set up environment variables:
cp .env.example .env
# Edit .env with your API keys

Usage

  1. Run the application:
python main.py
  1. Configure your LLM provider in the left panel
  2. Follow the 7-step workflow:
    • Step 1: Define your target role and generate initial prompt guide
    • Step 2: Input 5 examples of desired input/output behavior
    • Step 3: Generate a prompt from your examples
    • Step 4: Generate an evaluation guide for your role
    • Step 5: Evaluate the generated prompt
    • Step 6: Generate 3 improved alternatives
    • Step 7: Select and edit your final prompt

The 7-Step Workflow

  1. Initial Prompt Guide: Generate a detailed prompt engineering guide for your target audience
  2. Examples Input: Provide 5 examples of how you want your prompt to work
  3. Prompt Generation: Generate a prompt that could produce your examples' outputs
  4. Evaluation Guide: Generate a detailed prompt evaluation guide
  5. Prompt Evaluation: Evaluate the generated prompt using the evaluation guide
  6. Improved Alternatives: Generate 3 improved alternative prompts
  7. Final Selection: Select and edit your final prompt

Supported LLM Providers

  • OpenAI: GPT-4, GPT-3.5-turbo, etc.
  • Anthropic: Claude-3 models
  • Local: Any OpenAI-compatible API endpoint

Configuration

Set your API keys in environment variables:

  • OPENAI_API_KEY: For OpenAI models
  • ANTHROPIC_API_KEY: For Anthropic models

Or configure them directly in the GUI.

Benefits

  • Better than manual: LLM's own weights influence prompt generation
  • Systematic: Follows a proven 7-step methodology
  • Family-optimized: Best results when using the same model family for generation and final use
  • Iterative: Each step builds on the previous to improve quality

Requirements

  • Python 3.8+
  • See requirements.txt for full dependency list

License

See LICENSE file for details.