Claude Context

# Semantic Code Search VSCode Extension [](https://marketplace.visualstudio.com/items?itemName=zilliz.semanticcodesearch) A code indexing and semantic search VSCode extension powered by [Claude Context](https://github.com/zilliztech/claude-context). > 📖 **New to Claude Context?** Check out the [main project README](https://github.com/zilliztech/claude-context/blob/master/README.md) for an overview and setup instructions.  ## Features - 🔍 **Semantic Search**: Intelligent code search based on semantic understanding, not just keyword matching - 📁 **Codebase Indexing**: Automatically index entire codebase and build semantic vector database - 🎯 **Context Search**: Search related code by selecting code snippets - 🔧 **Multi-platform Support**: Support for OpenAI, VoyageAI, Gemini, and Ollama as embedding providers - 💾 **Vector Storage**: Integrated with Milvus vector database for efficient storage and retrieval ## Requirements - **VSCode Version**: 1.74.0 or higher ## Installation ### From VS Code Marketplace 1. **Direct Link**: [Install from VS Code Marketplace](https://marketplace.visualstudio.com/items?itemName=zilliz.semanticcodesearch) 2. **Manual Search**: - Open Extensions view in VSCode (Ctrl+Shift+X or Cmd+Shift+X on Mac) - Search for "Semantic Code Search" - Click Install ## Quick Start ### Configuration The first time you open Claude Context, you need to click on Settings icon to configure the relevant options. #### Embedding Configuration Configure your embedding provider to convert code into semantic vectors. **OpenAI Configuration:** - `Embedding Provider`: Select "OpenAI" from the dropdown - `Model name`: Choose the embedding model (e.g., `text-embedding-3-small`, `text-embedding-3-large`) - `OpenAI API key`: Your OpenAI API key for authentication - `Custom API endpoint URL`: Optional custom endpoint (defaults to `https://api.openai.com/v1`) **Other Supported Providers:** - **Gemini**: Google's state-of-the-art embedding model with Matryoshka representation learning - **VoyageAI**: Alternative embedding provider with competitive performance - **Ollama**: For local embedding models #### Code Splitter Configuration Configure how your code is split into chunks for indexing. **Splitter Settings:** - `Splitter Type`: Choose between "AST Splitter" (syntax-aware) or "LangChain Splitter" (character-based) - `Chunk Size`: Maximum size of each code chunk (default: 1000 characters) - `Chunk Overlap`: Number of overlapping characters between chunks (default: 200 characters) > **Recommendation**: Use AST Splitter for better semantic understanding of code structure. #### Zilliz Cloud configuration Get a free Milvus vector database on Zilliz Cloud. Claude Context needs a vector database. You can [sign up](https://cloud.zilliz.com/signup?utm_source=github&utm_medium=referral&utm_campaign=2507-codecontext-readme) on Zilliz Cloud to get a free Serverless cluster.  After creating your cluster, open your Zilliz Cloud console and copy both the **public endpoint** and your **API key**. These will be used as `your-zilliz-cloud-public-endpoint` and `your-zilliz-cloud-api-key` in the configuration examples.  Keep both values handy for the configuration steps below. If you need help creating your free vector database or finding these values, see the [Zilliz Cloud documentation](https://docs.zilliz.com/docs/create-cluster) for detailed instructions. ```bash MILVUS_ADDRESS=your-zilliz-cloud-public-endpoint MILVUS_TOKEN=your-zilliz-cloud-api-key ``` ### Usage 1. **Set the Configuration**: - Open VSCode Settings (Ctrl+, or Cmd+, on Mac) - Search for "Semantic Code Search" - Set the configuration 2. **Index Codebase**: - Open Command Palette (Ctrl+Shift+P or Cmd+Shift+P on Mac) - Run "Semantic Code Search: Index Codebase" 3. **Start Searching**: - Open Semantic Code Search panel in sidebar - Enter search query or right-click on selected code to search ## Commands - `Semantic Code Search: Semantic Search` - Perform semantic search - `Semantic Code Search: Index Codebase` - Index current codebase - `Semantic Code Search: Clear Index` - Clear the index ## Configuration - `semanticCodeSearch.embeddingProvider.provider` - Embedding provider (OpenAI/VoyageAI/Gemini/Ollama) - `semanticCodeSearch.embeddingProvider.model` - Embedding model to use - `semanticCodeSearch.embeddingProvider.apiKey` - API key for embedding provider - `semanticCodeSearch.embeddingProvider.baseURL` - Custom API endpoint URL (optional, for OpenAI and Gemini) - `semanticCodeSearch.embeddingProvider.outputDimensionality` - Output dimension for Gemini (supports 3072, 1536, 768, 256) - `semanticCodeSearch.milvus.address` - Milvus server address ## Contributing This VSCode extension is part of the Claude Context monorepo. Please see: - [Main Contributing Guide](https://github.com/zilliztech/claude-context/blob/master/CONTRIBUTING.md) - General contribution guidelines - [VSCode Extension Contributing](https://github.com/zilliztech/claude-context/blob/master/packages/vscode-extension/CONTRIBUTING.md) - Specific development guide for this extension ## Related Packages - **[@zilliz/claude-context-core](https://github.com/zilliztech/claude-context/tree/master/packages/core)** - Core indexing engine used by this extension - **[@zilliz/claude-context-mcp](https://github.com/zilliztech/claude-context/tree/master/packages/mcp)** - Alternative MCP server integration ## Tech Stack - TypeScript - VSCode Extension API - Milvus Vector Database - OpenAI/VoyageAI Embeddings ## License MIT - See [LICENSE](https://github.com/zilliztech/claude-context/blob/master/LICENSE) for details