Crate cqs 

cqs - Semantic Code Search

Local semantic search for code using ML embeddings. Find functions by what they do, not just their names.

Features

• Semantic search: Uses E5-base-v2 embeddings (769-dim: 768 model + sentiment)
• Notes with sentiment: Unified memory system for AI collaborators
• Multi-language: Rust, Python, TypeScript, JavaScript, Go, C, Java, SQL, Markdown
• GPU acceleration: CUDA/TensorRT with CPU fallback
• CLI tools: Call graph, impact analysis, test mapping, dead code detection

Quick Start

use cqs::{Embedder, Parser, Store};

// Initialize components
let parser = Parser::new()?;
let embedder = Embedder::new()?;
let store = Store::open(std::path::Path::new(".cqs/index.db"))?;

// Parse and embed a file
let chunks = parser.parse_file(std::path::Path::new("src/main.rs"))?;
let embeddings = embedder.embed_documents(
    &chunks.iter().map(|c| c.content.as_str()).collect::<Vec<_>>()
)?;

// Search for similar code
let query_embedding = embedder.embed_query("parse configuration file")?;
let results = store.search(&query_embedding, 5, 0.3)?;

Re-exports

pub use audit::parse_duration;

pub use embedder::Embedder;

pub use embedder::Embedding;

pub use hnsw::HnswIndex;

pub use index::IndexResult;

pub use index::VectorIndex;

pub use note::parse_notes;

pub use note::path_matches_mention;

pub use note::rewrite_notes_file;

pub use note::NoteEntry;

pub use note::NoteError;

pub use note::NoteFile;

pub use note::NOTES_HEADER;

pub use parser::Chunk;

pub use parser::Parser;

pub use store::ModelInfo;

pub use store::SearchFilter;

pub use store::Store;

Modules

audit

Audit mode for excluding notes from search/read

config

Configuration file support for cqs

embedder

Embedding generation with ort + tokenizers

hnsw

HNSW (Hierarchical Navigable Small World) index for fast vector search

index

Vector index trait for nearest neighbor search

language

Language registry for code parsing

note

Note parsing and types

parser

Code parsing with tree-sitter

reference

Reference index support for multi-index search

store

SQLite storage for chunks and embeddings (sqlx async with sync wrappers)

Structs

DiffResult

Result of a semantic diff

GatherOptions

Options for gather operation

ImpactResult

Complete impact analysis result

ProjectRegistry

Global registry of indexed cqs projects

Enums

GatherDirection

Direction of call graph expansion

NlTemplate

Template variants for NL description generation.

Pattern

Known structural patterns

Constants

EMBEDDING_DIM

Embedding dimension: 768 from E5-base-v2 model + 1 sentiment dimension. Single source of truth — all modules import this constant.

INDEX_DIR

Name of the per-project index directory (created by cqs init).

Functions

analyze_impact

Run impact analysis: find callers, affected tests, and transitive callers.

enumerate_files

Enumerate files to index in a project directory.

extract_type_names

Extract non-standard type names from a function signature.

gather

Gather relevant code chunks for a query

generate_nl_description

Generate natural language description from chunk metadata.

generate_nl_with_template

Generate NL description using a specific template variant.

impact_to_json

Serialize impact result to JSON, relativizing paths against the project root

impact_to_mermaid

Generate a mermaid diagram from impact result

index_notes

Index notes into the database (embed and store)

normalize_for_fts

Normalize code text for FTS5 indexing.

parse_target

Parse a target string into (optional_file_filter, function_name).

resolve_index_dir

Resolve the index directory for a project, migrating from .cq/ to .cqs/ if needed.

resolve_target

Resolve a target string to a ChunkSummary.

search_across_projects

Search across all registered projects

semantic_diff

Run a semantic diff between two stores

strip_unc_prefix

No-op on non-Windows platforms