Feature Request: Implement Local RAG System for CodeBuddy

[olasunkanmi-SE]

Description:

A Retrieval-Augmented Generation (RAG) system for our VS Code copilot extension. The key feature of this system is that all indexing and querying will happen on the user's local machine, ensuring privacy and reducing dependency on external services.

Objectives:

1. Local Indexing:

   • Implement a system to index the user's codebase on their local machine.
   • Support indexing of multiple programming languages and file types.
   • Ensure efficient indexing to handle large codebases without significant performance impact.

2. Local Vector Database:

   • Set up a lightweight, file-based vector database that can run locally.
   • Implement efficient storage and retrieval of code embeddings.

3. Embedding Generation:

   • Integrate a local embedding model to convert code snippets into vector representations.
   • Ensure the embedding process is fast and resource-efficient.

4. Query Processing:

   • Develop a query system that can understand natural language or code-related questions.
   • Implement semantic search functionality using the local vector database.

5. Privacy and Security:

   • Ensure all operations are performed locally without sending data to external servers.
   • Implement secure storage for any sensitive information.

6. Performance Optimization:

   • Optimize the system to minimize impact on VS Code's performance.
   • Implement background processing and caching mechanisms.

7. Documentation and Testing:

   • Provide comprehensive documentation for setup and usage.
   • Develop a thorough test suite to ensure reliability and accuracy.

Acceptance Criteria:

• The RAG system operates entirely on the local machine without external API calls.
• Indexing and querying perform efficiently on codebases of varying sizes.
• The system provides accurate and relevant code suggestions and completions.
• User experience is smooth with minimal latency in VS Code.
• Clear documentation and configuration options are available to users.

This feature will significantly enhance codebuddy by providing personalized, context-aware assistance while maintaining user privacy and data security.

Labels: enhancement, privacy, machine-learning, vscode-extension