Code Search with Vector Embeddings: A Transformer's Approach

• example-vectorize-codebase

  1 6 3.2 TypeScript

  A minimal example of how to vectorize a small project to perform natural language queries on

  For a more detailed walkthrough, including potential customizations and optimizations, check out the companion GitHub repository.

• InfluxDB

  www.influxdata.com featured

  Purpose built for real-time analytics at any scale. InfluxDB Platform is powered by columnar analytics, optimized for cost-efficient storage, and built with open data standards.

  

• faiss

  75 30,378 9.5 C++

  A library for efficient similarity search and clustering of dense vectors.

  

  As the size of the codebase grows, storing and searching through embeddings in memory becomes inefficient. This is where vector databases come into play. Tools like Milvus, Faiss, and others are designed to handle large-scale vector data and provide efficient similarity search capabilities. I've wrtten about how to also use sqlite to store vector embeddings. By integrating a vector database, you can scale your code search tool to handle much larger codebases without compromising on search speed.

• Milvus

  118 29,368 10.0 Go

  A cloud-native vector database, storage for next generation AI applications

  

  As the size of the codebase grows, storing and searching through embeddings in memory becomes inefficient. This is where vector databases come into play. Tools like Milvus, Faiss, and others are designed to handle large-scale vector data and provide efficient similarity search capabilities. I've wrtten about how to also use sqlite to store vector embeddings. By integrating a vector database, you can scale your code search tool to handle much larger codebases without compromising on search speed.

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