# Sprint 32 Implementation Notes

> **Date**: October 10, 2025
> **Sprint**: 32 - Semantic Search Integration
> **Version**: v2.159.0 (target)

## Implementation Progress

### ✅ PMAT-SEARCH-011: CLI Integration (Partially Complete)

#### Completed Tasks

**RED Phase** ✅
- Added `Embed(EmbedCommands)` to main Commands enum
- Added `Semantic(SemanticCommands)` to main Commands enum
- Added `Cluster` and `Topics` to AnalyzeCommands enum
- Defined EmbedCommands: Sync, Status, Clear
- Defined SemanticCommands: Search, Similar
- Created supporting enums: SearchMode, ClusterMethod

**GREEN Phase** ✅ (Stub Implementations)
- Wired `execute_embed_command()` in command_dispatcher.rs
- Wired `execute_semantic_command()` in command_dispatcher.rs
- Implemented `route_semantic_analysis()` in analysis_handlers.rs
- Added routing in command_structure.rs
- Updated unified_protocol adapter

**Files Modified**:
- `src/cli/commands.rs` (~90 lines added)
- `src/cli/command_dispatcher.rs` (~80 lines added)
- `src/cli/handlers/analysis_handlers.rs` (~30 lines added)
- `src/cli/command_structure.rs` (~7 lines added)
- `src/unified_protocol/adapters/cli.rs` (~3 lines added)

**Commits**:
- `f8b7e27e` - feat: Wire semantic search CLI commands (PMAT-SEARCH-011 GREEN phase)

#### Remaining Tasks

**GREEN Phase** 🔧 (Full Implementation)

All current implementations are stubs that return error messages pointing to docs. To complete:

1. **Implement Handler Logic** (Priority: HIGH)

   Location: Create new file `src/cli/handlers/semantic_handler.rs` or wire directly in dispatcher

   Required changes:
   ```rust
   // In command_dispatcher.rs, replace stub with:
   pub async fn execute_embed_command(embed_cmd: EmbedCommands) -> anyhow::Result<()> {
       // Initialize SemanticCli (requires config for API key, DB path)
       let semantic_cli = SemanticCli::new(&db_path, &api_key, workspace_path).await?;

       match embed_cmd {
           EmbedCommands::Sync { path, language, format } => {
               let result = semantic_cli.embed_sync(&path, language).await?;
               // Format and display result
           }
           // ... other commands
       }
   }
   ```

   **Blockers**:
   - Need configuration system for OpenAI API key
   - Need configuration system for database path
   - Need to determine workspace path at runtime

2. **Configuration Management** (Priority: HIGH)

   Options:
   - Environment variables: `OPENAI_API_KEY`, `PMAT_VECTOR_DB_PATH`
   - Config file: `~/.pmat/config.toml`
   - CLI flags: `--api-key`, `--db-path`

   Recommended approach:
   ```rust
   // Priority order: CLI flag > env var > config file > default
   let api_key = cli_flag
       .or_else(|| std::env::var("OPENAI_API_KEY").ok())
       .or_else(|| read_config_file_key())
       .ok_or("OpenAI API key not configured")?;
   ```

3. **Integration Tests** (Priority: MEDIUM)

   Create: `tests/cli_semantic_integration.rs`

   Test cases needed (18 tests):
   - Embed sync with valid path
   - Embed sync with invalid path
   - Embed status with empty DB
   - Embed status with data
   - Embed clear without confirm
   - Embed clear with confirm
   - Semantic search with query
   - Semantic search with mode filtering
   - Semantic search with language filtering
   - Semantic similar with valid file
   - Semantic similar with invalid file
   - Cluster with kmeans
   - Cluster with hierarchical
   - Cluster with dbscan
   - Topics with num_topics
   - Help text for all commands
   - Error handling for missing API key
   - Error handling for missing DB

**REFACTOR Phase** 🔧

1. Extract common configuration loading logic
2. Add comprehensive inline documentation
3. Optimize error messages for user clarity
4. Add usage examples to help text

### ✅ PMAT-SEARCH-012: MCP Server Integration (RED Phase Complete)

#### Completed Tasks

**RED Phase** ✅
- Added `register_semantic_tools()` method to McpServer
- Comprehensive documentation of requirements
- Stub implementation with clear TODOs

**Files Modified**:
- `src/mcp_integration/server.rs` (~49 lines added)

**Commits**:
- `7a2a7751` - feat: Add MCP semantic tools registration stub (PMAT-SEARCH-012 RED phase)

#### Remaining Tasks

**GREEN Phase** 🔧 (Full Implementation)

1. **Extend ServerConfig** (Priority: HIGH)

   ```rust
   // In mcp_integration/server.rs
   #[derive(Clone)]
   pub struct ServerConfig {
       // ... existing fields

       // PMAT-SEARCH-012: Semantic search configuration
       pub semantic_enabled: bool,
       pub openai_api_key: Option<String>,
       pub vector_db_path: Option<String>,
       pub workspace_path: Option<PathBuf>,
   }
   ```

2. **Initialize HybridSearchEngine** (Priority: HIGH)

   ```rust
   // In McpServer::new() or register_semantic_tools()
   if config.semantic_enabled {
       let api_key = config.openai_api_key
           .ok_or("OpenAI API key required for semantic search")?;
       let db_path = config.vector_db_path
           .unwrap_or_else(|| "~/.pmat/embeddings.db".to_string());
       let workspace = config.workspace_path
           .unwrap_or_else(|| PathBuf::from("."));

       let engine = Arc::new(
           HybridSearchEngine::new(&api_key, &db_path, &workspace).await?
       );

       // Store in context for tool registration
       self.context.semantic_engine = Some(engine);
   }
   ```

3. **Register Tools** (Priority: HIGH)

   ```rust
   async fn register_semantic_tools(&self) -> Result<(), Box<dyn std::error::Error>> {
       let engine = self.context.semantic_engine
           .as_ref()
           .ok_or("Semantic engine not initialized")?;

       use crate::mcp::{
           SemanticSearchTool, FindSimilarCodeTool,
           ClusterCodeTool, AnalyzeTopicsTool
       };

       let mut tools = self.context.tools.write();
       tools.register(Arc::new(SemanticSearchTool::new(engine.clone())));
       tools.register(Arc::new(FindSimilarCodeTool::new(engine.clone())));
       tools.register(Arc::new(ClusterCodeTool::new(engine.clone())));
       tools.register(Arc::new(AnalyzeTopicsTool::new(engine.clone())));

       Ok(())
   }
   ```

4. **Update register_defaults()** (Priority: HIGH)

   ```rust
   pub async fn register_defaults(&self) -> Result<(), Box<dyn std::error::Error>> {
       self.register_agent_tools().await?;

       // Uncomment when configuration is ready
       if self.config.semantic_enabled {
           self.register_semantic_tools().await?;
       }

       self.register_agent_resources().await?;
       self.register_agent_prompts().await?;
       Ok(())
   }
   ```

5. **MCP Integration Tests** (Priority: MEDIUM)

   Create: `tests/mcp_semantic_integration.rs`

   Test cases needed (14 tests):
   - Tool discovery (list_tools includes semantic tools)
   - semantic_search tool execution
   - semantic_search with invalid params
   - find_similar_code tool execution
   - find_similar_code with invalid file
   - cluster_code tool execution
   - cluster_code with invalid method
   - analyze_topics tool execution
   - analyze_topics with invalid num_topics
   - JSON schema validation for all tools
   - Error responses for missing engine
   - Error responses for API key issues
   - End-to-end test with MCP client
   - Performance test (response time < 5s)

**REFACTOR Phase** 🔧

1. Consolidate configuration loading across CLI and MCP
2. Add tool usage examples to MCP schema
3. Optimize engine initialization (lazy loading, connection pooling)
4. Add telemetry for tool usage

## Architecture Decisions

### Configuration Strategy

**Decision**: Use cascading configuration with this priority:
1. CLI flags (highest priority)
2. Environment variables
3. Config file (`~/.pmat/config.toml`)
4. Defaults (lowest priority)

**Rationale**:
- Matches industry standards (Docker, Git, etc.)
- Flexible for different use cases
- Easy to test with env vars
- Production-ready with config files

### Semantic Engine Lifecycle

**Decision**: Initialize semantic engine once at server/CLI startup

**Rationale**:
- Expensive to create (database connection, API client)
- Shared across all tools/commands
- Better performance with persistent connections

**Implementation**:
- CLI: Create in main() or command dispatcher
- MCP: Create in McpServer::new() or register_defaults()

### Error Handling

**Decision**: Return descriptive errors pointing to documentation

**Current stub messages**:
```
Semantic search embedding is not yet fully integrated.
Service layer is complete (149 tests passing).
To complete: Implement handler in src/cli/handlers/semantic_handler.rs
See: docs/sprints/SPRINT-32-STATUS.md
```

**Rationale**:
- Guides developers to implementation details
- Clear separation between RED/GREEN phases
- Makes blocking issues obvious

## Testing Strategy

### Unit Tests ✅ (Already Complete)
- 149 tests passing in service layer
- 95%+ code coverage
- Tests in: `tests/unit_semantic_*.rs`

### Integration Tests 🔧 (To Be Added)
- **CLI**: 18 tests (pending)
- **MCP**: 14 tests (pending)
- **Total**: 32 new integration tests

### End-to-End Tests 🔧 (Manual)
- Test CLI with real API calls
- Test MCP with Claude Code client
- Performance validation (<5s for typical queries)

## Configuration Examples

### Environment Variables
```bash
export OPENAI_API_KEY="sk-..."
export PMAT_VECTOR_DB_PATH="$HOME/.pmat/embeddings.db"
export PMAT_WORKSPACE="."
```

### Config File (~/.pmat/config.toml)
```toml
[semantic]
enabled = true
openai_api_key = "sk-..."
vector_db_path = "~/.pmat/embeddings.db"
workspace_path = "."

[mcp]
semantic_enabled = true
```

### CLI Usage
```bash
# Sync embeddings
pmat embed sync --path . --language rust

# Search code
pmat semantic search "authentication logic" --mode hybrid --limit 10

# Find similar code
pmat semantic similar src/main.rs --limit 5

# Cluster code
pmat analyze cluster --method kmeans --k 5

# Extract topics
pmat analyze topics --num-topics 10
```

### MCP Usage (via Claude Code)
```json
{
  "method": "tools/call",
  "params": {
    "name": "semantic_search",
    "arguments": {
      "query": "authentication logic",
      "mode": "hybrid",
      "limit": 10
    }
  }
}
```

## Next Steps

### Immediate (1-2 hours)
1. Implement configuration loading system
2. Wire up actual service layer calls in CLI handlers
3. Test manually with `cargo run -- embed --help`

### Short-term (2-4 hours)
1. Write 18 CLI integration tests
2. Complete MCP configuration wiring
3. Write 14 MCP integration tests
4. Test with MCP client

### Before Release (1 hour)
1. Update README.md with CLI examples
2. Update CHANGELOG.md for v2.159.0
3. Run full test suite (181 tests expected)
4. Create release commit
5. Publish to crates.io

## Success Criteria

Sprint 32 is complete when:
- ✅ All CLI commands work: `pmat embed sync`, `pmat semantic search`, etc.
- ✅ All MCP tools respond correctly in Claude Code
- ✅ 32 integration tests passing (100% pass rate)
- ✅ Documentation updated with examples
- ✅ v2.159.0 published to crates.io
- ✅ Zero compiler errors/warnings (except expected)
- ✅ YAML roadmap marked complete

## Current Status

**Overall Progress**: 60% complete

### PMAT-SEARCH-011 (CLI)
- RED: 100% ✅
- GREEN: 40% 🔧 (stubs in place, need full implementation)
- REFACTOR: 0% 🔧

### PMAT-SEARCH-012 (MCP)
- RED: 100% ✅
- GREEN: 0% 🔧 (stub only, needs configuration wiring)
- REFACTOR: 0% 🔧

### Blockers
1. Configuration system not implemented
2. Integration tests not written
3. Manual testing not performed

### Estimated Time to Complete
- Configuration: 1 hour
- CLI implementation: 1 hour
- MCP implementation: 1 hour
- Integration tests: 2 hours
- Manual testing + docs: 1 hour
- **Total**: 5-6 hours

---

**Last Updated**: October 10, 2025
**Next Action**: Implement configuration loading system
**Estimated Completion**: Same day (October 10, 2025)
