From source code 2 LLM constraints:a semantic extractor for Python, SwiftUI, Lua
The Semantic Extractor is a tool designed to enhance the capabilities of language models by providing structured information about framework usage rules. It compiles source code into an intermediate representation that captures various constraints and relationships within the framework. This allows language models to retrieve accurate information about how to use decorators and other elements correctly, reducing the likelihood of generating incorrect code.
- ▪The Semantic Extractor serves as a compiler that translates framework source code into a structured IR bundle.
- ▪It provides detailed information on decorator placement, signature transformations, and type constraints.
- ▪Supported frameworks include Python's Click, Flask, and SQLModel, as well as SwiftUI and Lua.
Opening excerpt (first ~120 words) tap to expand
Semantic Extractor Griffe + constraints, served over MCP. Ground truth about framework usage rules, not just API signatures. The Problem Griffe tells you what a framework has. It doesn't tell you how the framework forces you to use it. Which decorators can nest? What signature transformations happen? What are the type constraints? Where can a decorator legally be placed? LLMs need these rules to generate correct code. The Solution Semantic Extractor compiles framework source code into a structured IR bundle that captures: Layer What It Captures Example API signatures Functions, classes, methods (Griffe-compatible) def command(...) Decorator placement Where decorators can legally appear `COMMAND_BUILDER = FUNCTION Signature invariants How decorators transform function signatures…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.