[Chore/Refactor] Switch from MyPy to Basedpyright for type checking (#25047)

Signed-off-by: -LAN- <laipz8200@outlook.com>

api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py

@@ -228,7 +228,7 @@ class AnalyticdbVectorBySql:
             )
             documents = []
             for record in cur:
-                id, vector, score, page_content, metadata = record
+                _, vector, score, page_content, metadata = record
                 if score >= score_threshold:
                     metadata["score"] = score
                     doc = Document(
@@ -260,7 +260,7 @@ class AnalyticdbVectorBySql:
             )
             documents = []
             for record in cur:
-                id, vector, page_content, metadata, score = record
+                _, vector, page_content, metadata, score = record
                 metadata["score"] = score
                 doc = Document(
                     page_content=page_content,

api/core/rag/datasource/vdb/clickzetta/clickzetta_vector.py

@@ -701,7 +701,7 @@ class ClickzettaVector(BaseVector):
                         len(data_rows),
                         vector_dimension,
                     )
-                except (RuntimeError, ValueError, TypeError, ConnectionError) as e:
+                except (RuntimeError, ValueError, TypeError, ConnectionError):
                     logger.exception("Parameterized SQL execution failed for %d documents", len(data_rows))
                     logger.exception("SQL template: %s", insert_sql)
                     logger.exception("Sample data row: %s", data_rows[0] if data_rows else "None")
@@ -787,7 +787,7 @@ class ClickzettaVector(BaseVector):
         document_ids_filter = kwargs.get("document_ids_filter")
 
         # Handle filter parameter from canvas (workflow)
-        filter_param = kwargs.get("filter", {})
+        _ = kwargs.get("filter", {})
 
         # Build filter clause
         filter_clauses = []
@@ -879,7 +879,7 @@ class ClickzettaVector(BaseVector):
         document_ids_filter = kwargs.get("document_ids_filter")
 
         # Handle filter parameter from canvas (workflow)
-        filter_param = kwargs.get("filter", {})
+        _ = kwargs.get("filter", {})
 
         # Build filter clause
         filter_clauses = []
@@ -938,7 +938,7 @@ class ClickzettaVector(BaseVector):
                                     metadata = {}
                             else:
                                 metadata = {}
-                        except (json.JSONDecodeError, TypeError) as e:
+                        except (json.JSONDecodeError, TypeError):
                             logger.exception("JSON parsing failed")
                             # Fallback: extract document_id with regex
 
@@ -956,7 +956,7 @@ class ClickzettaVector(BaseVector):
                         metadata["score"] = 1.0  # Clickzetta doesn't provide relevance scores
                         doc = Document(page_content=row[1], metadata=metadata)
                         documents.append(doc)
-                except (RuntimeError, ValueError, TypeError, ConnectionError) as e:
+                except (RuntimeError, ValueError, TypeError, ConnectionError):
                     logger.exception("Full-text search failed")
                     # Fallback to LIKE search if full-text search fails
                     return self._search_by_like(query, **kwargs)
@@ -978,7 +978,7 @@ class ClickzettaVector(BaseVector):
         document_ids_filter = kwargs.get("document_ids_filter")
 
         # Handle filter parameter from canvas (workflow)
-        filter_param = kwargs.get("filter", {})
+        _ = kwargs.get("filter", {})
 
         # Build filter clause
         filter_clauses = []

api/core/rag/datasource/vdb/couchbase/couchbase_vector.py

@@ -212,10 +212,10 @@ class CouchbaseVector(BaseVector):
 
         documents_to_insert = [
             {"text": text, "embedding": vector, "metadata": metadata}
-            for id, text, vector, metadata in zip(uuids, texts, embeddings, metadatas)
+            for _, text, vector, metadata in zip(uuids, texts, embeddings, metadatas)
         ]
         for doc, id in zip(documents_to_insert, uuids):
-            result = self._scope.collection(self._collection_name).upsert(id, doc)
+            _ = self._scope.collection(self._collection_name).upsert(id, doc)
 
         doc_ids.extend(uuids)
 
@@ -241,7 +241,7 @@ class CouchbaseVector(BaseVector):
             """
         try:
             self._cluster.query(query, named_parameters={"doc_ids": ids}).execute()
-        except Exception as e:
+        except Exception:
             logger.exception("Failed to delete documents, ids: %s", ids)
 
     def delete_by_document_id(self, document_id: str):

api/core/rag/datasource/vdb/matrixone/matrixone_vector.py

@@ -99,7 +99,7 @@ class MatrixoneVector(BaseVector):
                 return client
             try:
                 client.create_full_text_index()
-            except Exception as e:
+            except Exception:
                 logger.exception("Failed to create full text index")
             redis_client.set(collection_exist_cache_key, 1, ex=3600)
             return client

api/core/rag/datasource/vdb/opensearch/opensearch_vector.py

@@ -197,7 +197,7 @@ class OpenSearchVector(BaseVector):
 
         try:
             response = self._client.search(index=self._collection_name.lower(), body=query)
-        except Exception as e:
+        except Exception:
             logger.exception("Error executing vector search, query: %s", query)
             raise
 

api/core/rag/datasource/vdb/tablestore/tablestore_vector.py

@@ -71,7 +71,7 @@ class TableStoreVector(BaseVector):
         table_result = result.get_result_by_table(self._table_name)
         for item in table_result:
             if item.is_ok and item.row:
-                kv = {k: v for k, v, t in item.row.attribute_columns}
+                kv = {k: v for k, v, _ in item.row.attribute_columns}
                 docs.append(
                     Document(
                         page_content=kv[Field.CONTENT_KEY.value], metadata=json.loads(kv[Field.METADATA_KEY.value])