Prompt Decorators
Prompt Decorators offers a standardized system to modify Large Language Model (LLM) prompts through composable annotations, improving consistency and reusability across different platforms and models.
Added on:
Created by:
Apr 21 2025
Prompt Decorators offers a standardized system to modify Large Language Model (LLM) prompts through composable annotations, improving consistency and reusability across different platforms and models.
Added on:
Created by:
Apr 21 2025
Synapti.ai
Featured
What is Prompt Decorators?
Prompt Decorators is a comprehensive framework designed to enhance how prompts for Large Language Models (LLMs) are structured and processed. It introduces a formal open standard specification along with a Python reference implementation, enabling users to annotate prompts with decorators that control behavior, formatting, and reasoning patterns. Featuring MCP server integration, the system ensures modular, customizable, and consistent prompt engineering, reducing cognitive overhead and increasing interoperability among AI tools.
Who will use Prompt Decorators?
- AI researchers
- Prompt engineers
- Developers integrating LLMs
- AI tool creators
How to use the Prompt Decorators?
- Step1: Install prompt-decorators via pip
- Step2: Load decorator definitions using load_decorator_definitions()
- Step3: Create a decorator instance with create_decorator_instance()
- Step4: Apply the decorator to a prompt with the apply() method
Prompt Decorators's Core Features & Benefits
The Core Features
- Registry-based decorator management
- Parameter validation and type checking
- Decorator versioning
- Compatibility checking
- Documentation generation
- Dynamic loading and discovery
The Benefits
- Standardized prompt annotation syntax
- Reduces prompt verbosity
- Enables reusable patterns
- Supports complex decorator combinations
- Improves prompt consistency across platforms
Prompt Decorators's Main Use Cases & Applications
- Standardizing prompt engineering workflows
- Creating reusable prompt templates
- Ensuring consistent AI responses across models
- Implementing reasoning and formatting decorators
- Enhancing prompt adaptiveness for different use cases
FAQs of Prompt Decorators
Developer
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