Module semantic 

Semantic analysis and compression module

This module provides semantic code understanding through embeddings, enabling similarity search and intelligent code compression.

Feature: embeddings

When the embeddings feature is enabled, this module provides:

• Embedding generation for code content (currently uses character-frequency heuristics)
• Cosine similarity computation between code snippets
• Clustering-based compression that groups similar code chunks

Current Implementation Status

Important: The current embeddings implementation uses a simple character-frequency based algorithm, NOT neural network embeddings. This is a lightweight placeholder that provides reasonable results for basic similarity detection without requiring external model dependencies.

Future versions may integrate actual transformer-based embeddings via:

• Candle (Rust-native ML framework)
• ONNX Runtime for pre-trained models
• External embedding services (OpenAI, Cohere, etc.)

Without embeddings Feature

Falls back to heuristic-based compression that:

• Splits content at paragraph boundaries
• Keeps every Nth chunk based on budget ratio
• No similarity computation (all operations return 0.0)

Structs

CodeChunk

A chunk of code

SemanticAnalyzer

Semantic analyzer using code embeddings

SemanticCompressor

Semantic compressor for code content

SemanticConfig

Configuration for semantic compression

Enums

SemanticError

Errors that can occur during semantic operations

Type Aliases

CharacterFrequencyAnalyzer

Alias for SemanticAnalyzer - more honest name reflecting the actual implementation.

HeuristicCompressionConfig

Alias for SemanticConfig - more honest name.

HeuristicCompressor

Alias for SemanticCompressor - more honest name reflecting the actual implementation.

Result

Result type for semantic operations