Promptlab

🚀 PromptLab Project Guide

PromptLab is an intelligent prompt management platform designed to assist users in efficiently creating, managing, and optimizing prompts for AI models. The system supports a variety of functions, including:

• Intelligent Prompt Matching: Automatically selects the most suitable prompt template by analyzing the input text.
• Dynamic Parameter Extraction: Identifies and populates variables in the prompt from the context.
• Version Control: Enables iterative updates and historical tracking of prompts.
• Multi - dimensional Management: Supports quick search and filtering of prompts by name, tag, and other dimensions.

✨ Features

Core Modules

1. Prompt Parser

   • Responsible for matching the input text with existing prompt templates.
   • Automatically identifies and extracts variable parameters in the prompt.
   • Supports multiple context analysis methods.

2. Version Controller

   • Provides functions for creating, updating, and deleting prompts.
   • Manages production and archived versions.
   • Supports rolling back to historical versions.

3. Execution Engine

   • Generates the final execution instructions based on the matched prompt.
   • Supports multiple AI model interfaces.
   • Provides result analysis and optimization suggestions.

📦 Installation

Install Dependencies

# Install dependencies
pip install -r requirements.txt

Initialize the Project

python PromptLab.py init

💻 Usage Examples

Create a New Prompt

python register_prompts.py --name "new_prompt" \
  --template "Your template contains {{ variable }}" \
  --message "Initial version description"

Create and Execute a Prompt

python PromptLab.py run \
  --prompt_name "product_description" \
  --variables product:phone brand:xiaomi features:good_photography

View Historical Versions

python version_control.py list

Delete a Prompt

python register_prompts.py delete --name "obsolete_prompt"

📚 Documentation

Code Structure

Functional Modules

1. PromptLab Core Program

├── PromptLab.py          # Main program entry
├── prompt_manager.py     # Prompt management function
├── version_control.py    # Version control function
└── execution_engine.py   # Execution engine function

2. Support Files

• templates/: Directory for storing prompt templates.
• logs/: Folder for logging.
• config.json: System configuration file.

Prompt Management Guide

Prompt Classification

The system supports the following predefined prompt types:

• Basic: General, Formal
• Task - based: Email, Report, Story
• Domain - specific: Technology, Finance, Education
• Other custom categories

Register a New Prompt

1. Command - line Method

python register_prompts.py register \
  --name "custom_prompt" \
  --template "You are a {{ role }}, with professional knowledge in {{ domain }}. Please generate a {{ document_type }} about {{ topic }}, requiring to reflect {{ quality }}." \
  --message "Custom template description"

2. File Method

• Create a text file template.txt:

The template content contains {{ variable }}

Register the prompt:

python register_prompts.py --file template.txt

3. Batch Registration via JSON File

• Create a JSON file in the following format:

{
  "prompts": [
    {
      "name": "prompt_name",
      "template": "The template content contains {{ variables }}",
      "message": "Description information",
      "tags": {"Type": "Custom", "Task": "Special Purpose"}
    }
  ]
}

Register the prompt:

python register_prompts.py --json config.json

Prompt Optimization Strategies

1. Dynamic Parameter Adjustment: Automatically adjusts prompt parameters based on the context to achieve the best results.
2. Version Iterative Optimization: Continuously optimizes prompt performance through experimental data analysis.
3. Multi - model Adaptation: Supports multiple AI model interfaces to ensure compatibility.

Troubleshooting

Common Issues

1. Prompt registration fails:

   • Check if the template file is correct.
   • Ensure that the configuration file is error - free.
   • Check the error log.

2. Error during execution:

   • Verify the API key and access permissions.
   • Check the network connection status.
   • Update relevant dependency libraries.

📄 More Resources

• Official Documentation
• Example Code Repository
• User support email: support@promptlab.com