A rule-based Prompt Optimizer that improves user prompts before they are sent to a Large Language Model (LLM). The project aims to transform simple or unstructured prompts into clear, structured, and context-rich prompts using predefined optimization rules.
The project is currently in the rule-based development phase.
- Project setup using FastAPI
- Modular project structure
- Prompt preprocessing
- Rule-based optimization framework
- Intent detection logic for identifying the user's request type (e.g., code, resume, email)
- Creating optimization rules for each detected intent
- Prompt formatting and enhancement
- Complete rule-based optimization pipeline
- Grammar and text normalization
- Support for multiple prompt categories
- AI-powered optimization using LLMs (future enhancement)
The objective of this project is to automatically identify the user's intent and optimize the prompt by applying predefined rules, making it more detailed, structured, and effective for AI models.