PromptLab transforms basic user queries into optimized prompts for AI systems by automatically detecting content type and applying tailored templates from a YAML-based system. The server implementation uses FastMCP to expose specialized tools for generating enhanced prompts across four categories: essays, emails, technical explanations, and creative writing. With its modular architecture, PromptLab enables non-technical users to create and manage prompt templates, ultimately producing higher-quality AI responses through better-structured inputs.
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Register a new prompt or version in MLflow.
Update an existing prompt, archiving the previous production version.
List all registered prompts in MLflow.
Register multiple prompts from a JSON file.
Initialize MLflow with standard sample prompts.
Load all available prompts from MLflow at server startup.
Match user queries to the appropriate prompt templates.
Apply the selected prompt template to the user's query.
Validate enhanced queries to ensure they meet necessary criteria.