feat: Add search result grouping by similarity score

Add functionality to group search results with similar content and scores
into a single representative result with additional locations.

Changes:
- Add AdditionalLocation entity model for storing grouped result locations
- Add additional_locations field to SearchResult for backward compatibility
- Implement group_similar_results() function in ranking.py with:
  - Content-based grouping (by excerpt or content field)
  - Score-based sub-grouping with configurable threshold
  - Metadata preservation with grouped_count tracking
- Add group_results and grouping_threshold options to SearchOptions
- Integrate grouping into ChainSearchEngine.search() after RRF fusion

Test coverage:
- 36 multi-level tests covering unit, boundary, integration, and performance
- Real-world scenario tests for RRF scores and duplicate code detection

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

codex-lens/src/codexlens/search/chain_search.py

@@ -38,6 +38,8 @@ class SearchOptions:
         enable_vector: Enable vector semantic search (default False)
         pure_vector: If True, only use vector search without FTS fallback (default False)
         hybrid_weights: Custom RRF weights for hybrid search (optional)
+        group_results: Enable grouping of similar results (default False)
+        grouping_threshold: Score threshold for grouping similar results (default 0.01)
     """
     depth: int = -1
     max_workers: int = 8
@@ -51,6 +53,8 @@ class SearchOptions:
     enable_vector: bool = False
     pure_vector: bool = False
     hybrid_weights: Optional[Dict[str, float]] = None
+    group_results: bool = False
+    grouping_threshold: float = 0.01
 
 
 @dataclass
@@ -210,6 +214,14 @@ class ChainSearchEngine:
 
         # Step 4: Merge and rank
         final_results = self._merge_and_rank(results, options.total_limit)
+
+        # Step 5: Optional grouping of similar results
+        if options.group_results:
+            from codexlens.search.ranking import group_similar_results
+            final_results = group_similar_results(
+                final_results, score_threshold_abs=options.grouping_threshold
+            )
+
         stats.files_matched = len(final_results)
 
         # Optional: Symbol search