leo-prompt-optimizer 0.1.1

A Python library to optimize prompt drafts using LLMs

🧠 leo-prompt-optimizer

leo-prompt-optimizer is a Python library that helps developers optimize raw prompt drafts into structured, high-performance prompts for large language models (LLMs).

It leverages open-source models via Groq API (like LLaMA 3 or Mixtral), making it fast, affordable, and production-ready.

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🚀 Features

• 🛠️ Refines messy or vague prompts into structured, effective ones
• 🧠 Follows a 9-step prompt engineering framework
• 📦 Supports contextual optimization (with user input & LLM output)
• ⚡ Uses blazing-fast open-source LLMs via Groq
• 🔐 Secure API key handling with .env

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📦 Installation

pip install leo-prompt-optimizer

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🔧 Setup

1. Create a .env file at the root of your project:

GROQ_API_KEY=your_groq_api_key_here

2. Install dependencies:

pip install leo-prompt-optimizer

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✍️ Usage Example

from leo_prompt_optimizer.optimizer import optimize_prompt

draft = "I want to understand user feedback better. Can you help me ask the right questions?"

user_input = "Users say the interface feels confusing. I want to understand what they mean exactly."

llm_output = "You could ask: 'Which parts feel confusing?' or 'How could it be more intuitive?'"

optimized = optimize_prompt(draft, user_input, llm_output)

print(optimized)

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📘 Output Format

The optimized prompt follows a structured format like:

Role:
[Define the LLM's persona]

Task:
[Clearly state the specific objective]

Instructions:
* Step-by-step subtasks

Context:
[Any relevant background, constraints, domain]

Output Format:
[e.g., bullet list, JSON, summary]

User Input:
[Original user input or example]

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💡 Why Use It?

Prompt quality is critical when building with LLMs. leo-prompt-optimizer helps you:

• Make prompts explicit and usable across apps
• Reduce hallucination
• Increase repeatability and reliability

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📄 License

MIT © 2025 [Leonard Baesen]