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codeprysm-search

Semantic code search with vector embeddings and Qdrant.

Part of the CodePrism project.

Features

Semantic Search: Natural language queries using vector embeddings
Hybrid Search: Combines semantic and keyword matching with score fusion
GPU Acceleration: Metal (macOS) and CUDA (Linux/Windows) support
Qdrant Integration: Scalable vector database for production use
Code-Optimized Embeddings: Uses Jina embeddings tuned for code

Installation

[dependencies]

codeprysm-search = "0.1"



# With GPU acceleration

codeprysm-search = { version = "0.1", features = ["metal"] }  # macOS

codeprysm-search = { version = "0.1", features = ["cuda"] }   # Linux/Windows

Usage

use codeprysm_search::{QdrantClient, SearchQuery};

// Connect to Qdrant
let client = QdrantClient::new("http://localhost:6334").await?;

// Search for code
let results = client.search(SearchQuery {
    query: "authentication handler".to_string(),
    limit: 10,
    ..Default::default()
}).await?;

for result in results {
    println!("{}: {} (score: {:.2})", result.file_path, result.name, result.score);
}

GPU Acceleration

GPU provides 7-9x faster inference for embedding generation:

Device	Per-iteration	Notes
CPU	170-180ms	Default
Metal GPU	20-25ms	macOS Apple Silicon
CUDA GPU	15-20ms	NVIDIA GPUs

License