Claude-Code-Workflow/EMBEDDINGS_IMPROVEMENTS_SUMMARY.md

CodexLens Embeddings Statistics Improvements

Summary

Improved the CodexLens init and status commands to return comprehensive embeddings statistics, making it easy for users to understand embeddings coverage.

Changes Made

1. Updated init command (Task 1)

File: codex-lens/src/codexlens/cli/commands.py (lines 142-219)

Key Changes:

• Changed from generate_embeddings() to generate_embeddings_recursive()
• Now processes all _index.db files recursively in the index tree
• Passes index_root (directory) instead of index_path (file)
• Returns comprehensive coverage statistics after generation

Imports Added:

from codexlens.cli.embedding_manager import generate_embeddings_recursive, get_embeddings_status

Result Structure:

{
  "embeddings": {
    "generated": true,
    "total_indexes": 26,
    "total_files": 303,
    "files_with_embeddings": 303,
    "coverage_percent": 100.0,
    "total_chunks": 500
  }
}

Console Output:

• Shows files processed count
• Shows total chunks created
• Shows indexes processed (successful/total)

2. Updated status command (Task 2)

File: codex-lens/src/codexlens/cli/commands.py (lines 642-713)

Key Changes:

• Added embeddings coverage check using get_embeddings_status()
• Updates vector_search feature flag based on coverage (>= 50%)
• Includes embeddings data in JSON output
• Displays embeddings statistics in console output

Imports Added:

from codexlens.cli.embedding_manager import get_embeddings_status

Result Structure:

{
  "embeddings": {
    "total_indexes": 26,
    "total_files": 303,
    "files_with_embeddings": 303,
    "files_without_embeddings": 0,
    "coverage_percent": 100.0,
    "total_chunks": 500,
    "indexes_with_embeddings": 26,
    "indexes_without_embeddings": 0
  },
  "features": {
    "exact_fts": true,
    "fuzzy_fts": true,
    "hybrid_search": true,
    "vector_search": true  // true when coverage >= 50%
  }
}

Console Output:

Search Backends:
  Exact FTS: ✓ (unicode61)
  Fuzzy FTS: ✓ (trigram)
  Hybrid Search: ✓ (RRF fusion)
  Vector Search: ✓ (embeddings available)

Embeddings Coverage:
  Total Indexes: 26
  Total Files: 303
  Files with Embeddings: 303
  Coverage: 100.0%
  Total Chunks: 500

Benefits

1. Transparency: Users can now see exactly what embeddings were generated
2. Coverage Visibility: Clear percentage showing embeddings coverage across all files
3. Recursive Processing: All index databases in the tree are processed, not just the root
4. Feature Detection: Vector search is automatically enabled when coverage is sufficient (>= 50%)
5. Comprehensive Stats: Shows total indexes, files, chunks, and coverage percentage

Backward Compatibility

• All changes are backward compatible
• Gracefully handles cases where embeddings are not available
• ImportError handling for when embedding_manager is not available
• Existing JSON output structure is extended, not changed

Testing

Created test script: test_embeddings_improvements.py

Tests verify:

• Init command reports embeddings statistics correctly
• Status command shows embeddings coverage
• JSON output includes all required fields
• Console output displays statistics properly

Usage Examples

Init with embeddings

codexlens init /path/to/project --json
# Returns comprehensive embeddings statistics

Check status

codexlens status --json
# Shows embeddings coverage and feature availability

Init without embeddings

codexlens init /path/to/project --no-embeddings --json
# Returns embeddings: {"generated": false, "error": "Skipped (--no-embeddings)"}

Files Modified

1. codex-lens/src/codexlens/cli/commands.py - Updated init and status commands

Implementation Details

Init Command Flow

1. Build index tree as before
2. If --no-embeddings not set:
   • Call generate_embeddings_recursive(index_root) instead of generate_embeddings(index_path)
   • After generation, call get_embeddings_status(index_root) to get coverage stats
   • Include comprehensive statistics in result
3. Return result with embeddings coverage data

Status Command Flow

1. Collect index statistics as before
2. Call get_embeddings_status(index_root) to check embeddings
3. Set vector_search feature flag based on coverage >= 50%
4. Include embeddings info in JSON output
5. Display embeddings statistics in console output

Error Handling

• Handles ImportError when embedding_manager not available
• Handles cases where embeddings don't exist (returns 0% coverage)
• Graceful fallback if get_embeddings_status fails
• Debug logging for failed operations