Call get_flatted_meta_by_kbs in dify retrieval (#13509)

### What problem does this PR solve?

Fix https://github.com/infiniflow/ragflow/issues/13388

Call get_flatted_meta_by_kbs in dify retrieval. Remove get_meta_by_kbs.

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

api/apps/sdk/dify_retrieval.py

@@ -123,7 +123,7 @@ async def retrieval(tenant_id):
     similarity_threshold = float(retrieval_setting.get("score_threshold", 0.0))
     top = int(retrieval_setting.get("top_k", 1024))
     metadata_condition = req.get("metadata_condition", {}) or {}
-    metas = DocMetadataService.get_meta_by_kbs([kb_id])
+    metas = DocMetadataService.get_flatted_meta_by_kbs([kb_id])
 
     doc_ids = []
     try:

api/db/services/doc_metadata_service.py

@@ -694,82 +694,6 @@ class DocMetadataService:
             logging.error(f"Error getting metadata for document {doc_id}: {e}")
             return {}
 
-    @classmethod
-    @DB.connection_context()
-    def get_meta_by_kbs(cls, kb_ids: List[str]) -> Dict:
-        """
-        Get metadata for documents in knowledge bases (Legacy).
-
-        Legacy metadata aggregator (backward-compatible).
-        - Does NOT expand list values and a list is kept as one string key.
-          Example: {"tags": ["foo","bar"]} -> meta["tags"]["['foo', 'bar']"] = [doc_id]
-        - Expects meta_fields is a dict.
-        Use when existing callers rely on the old list-as-string semantics.
-
-        Args:
-            kb_ids: List of knowledge base IDs
-
-        Returns:
-            Metadata dictionary in format: {field_name: {value: [doc_ids]}}
-        """
-        try:
-            # Get tenant_id from first KB
-            kb = Knowledgebase.get_by_id(kb_ids[0])
-            if not kb:
-                return {}
-
-            tenant_id = kb.tenant_id
-            index_name = cls._get_doc_meta_index_name(tenant_id)
-
-            condition = {"kb_id": kb_ids}
-            order_by = OrderByExpr()
-
-            # Query with large limit
-            results = settings.docStoreConn.search(
-                select_fields=["*"],
-                highlight_fields=[],
-                condition=condition,
-                match_expressions=[],
-                order_by=order_by,
-                offset=0,
-                limit=10000,
-                index_names=index_name,
-                knowledgebase_ids=kb_ids
-            )
-
-            logging.debug(f"[get_meta_by_kbs] index_name: {index_name}, kb_ids: {kb_ids}")
-
-            # Aggregate metadata (legacy: keeps lists as string keys)
-            meta = {}
-
-            # Use helper to iterate over results in any format
-            for doc_id, doc in cls._iter_search_results(results):
-                # Extract metadata fields (exclude system fields)
-                doc_meta = cls._extract_metadata(doc)
-
-                # Legacy: Keep lists as string keys (do NOT expand)
-                for k, v in doc_meta.items():
-                    if k not in meta:
-                        meta[k] = {}
-                    # If not list, make it a list
-                    if not isinstance(v, list):
-                        v = [v]
-                    # Legacy: Use the entire list as a string key
-                    # Skip nested lists/dicts
-                    if isinstance(v, list) and any(isinstance(x, (list, dict)) for x in v):
-                        continue
-                    list_key = str(v)
-                    if list_key not in meta[k]:
-                        meta[k][list_key] = []
-                    meta[k][list_key].append(doc_id)
-
-            logging.debug(f"[get_meta_by_kbs] KBs: {kb_ids}, Returning metadata: {meta}")
-            return meta
-
-        except Exception as e:
-            logging.error(f"Error getting metadata for KBs {kb_ids}: {e}")
-            return {}
-
     @classmethod
     @DB.connection_context()
     def get_flatted_meta_by_kbs(cls, kb_ids: List[str]) -> Dict:

test/testcases/test_http_api/test_dataset_management/test_dify_retrieval_routes_unit.py

@@ -161,6 +161,11 @@ def _load_dify_retrieval_module(monkeypatch):
     
     tenant_llm_service_mod.TenantService = _StubTenantService
     tenant_llm_service_mod.TenantLLMService = _StubTenantLLMService
+
+    class _StubLLMFactoriesService:
+        pass
+
+    tenant_llm_service_mod.LLMFactoriesService = _StubLLMFactoriesService
     monkeypatch.setitem(sys.modules, "api.db.services.tenant_llm_service", tenant_llm_service_mod)
 
     # Mock llm_service for LLMService
@@ -265,7 +270,7 @@ def test_retrieval_success_with_metadata_and_kg(monkeypatch):
     )
 
     monkeypatch.setattr(module, "jsonify", lambda payload: payload)
-    monkeypatch.setattr(module.DocMetadataService, "get_meta_by_kbs", lambda _kb_ids: [{"doc_id": "doc-1"}])
+    monkeypatch.setattr(module.DocMetadataService, "get_flatted_meta_by_kbs", lambda _kbs: [{"doc_id": "doc-1"}])
     monkeypatch.setattr(module.KnowledgebaseService, "get_by_id", lambda _kb_id: (True, _DummyKB()))
     monkeypatch.setattr(module, "convert_conditions", lambda cond: cond.get("conditions", []))
     monkeypatch.setattr(module, "meta_filter", lambda *_args, **_kwargs: [])
@@ -303,7 +308,7 @@ def test_retrieval_success_with_metadata_and_kg(monkeypatch):
 def test_retrieval_kb_not_found(monkeypatch):
     module = _load_dify_retrieval_module(monkeypatch)
     _set_request_json(monkeypatch, module, {"knowledge_id": "kb-missing", "query": "hello"})
-    monkeypatch.setattr(module.DocMetadataService, "get_meta_by_kbs", lambda _kb_ids: [])
+    monkeypatch.setattr(module.DocMetadataService, "get_flatted_meta_by_kbs", lambda _kbs: [])
     monkeypatch.setattr(module.KnowledgebaseService, "get_by_id", lambda _kb_id: (False, None))
 
     res = _run(inspect.unwrap(module.retrieval)("tenant-1"))
@@ -315,7 +320,7 @@ def test_retrieval_kb_not_found(monkeypatch):
 def test_retrieval_not_found_exception_mapping(monkeypatch):
     module = _load_dify_retrieval_module(monkeypatch)
     _set_request_json(monkeypatch, module, {"knowledge_id": "kb-1", "query": "hello"})
-    monkeypatch.setattr(module.DocMetadataService, "get_meta_by_kbs", lambda _kb_ids: [])
+    monkeypatch.setattr(module.DocMetadataService, "get_flatted_meta_by_kbs", lambda _kbs: [])
     monkeypatch.setattr(module.KnowledgebaseService, "get_by_id", lambda _kb_id: (True, _DummyKB()))
     monkeypatch.setattr(module, "label_question", lambda *_args, **_kwargs: [])
 
@@ -334,7 +339,7 @@ def test_retrieval_not_found_exception_mapping(monkeypatch):
 def test_retrieval_generic_exception_mapping(monkeypatch):
     module = _load_dify_retrieval_module(monkeypatch)
     _set_request_json(monkeypatch, module, {"knowledge_id": "kb-1", "query": "hello"})
-    monkeypatch.setattr(module.DocMetadataService, "get_meta_by_kbs", lambda _kb_ids: [])
+    monkeypatch.setattr(module.DocMetadataService, "get_flatted_meta_by_kbs", lambda _kbs: [])
     monkeypatch.setattr(module.KnowledgebaseService, "get_by_id", lambda _kb_id: (True, _DummyKB()))
     monkeypatch.setattr(module, "label_question", lambda *_args, **_kwargs: [])