lang detect

backend/src/api/routes/assistant/_dispatch.py

@@ -19,7 +19,6 @@ from src.core.logger import belief_scope, logger
 from src.core.task_manager import TaskManager
 from src.schemas.auth import User
 from src.services.git_service import GitService
-from src.services.llm_prompt_templates import is_multimodal_model
 from src.services.llm_provider import LLMProviderService
 
 from ._dataset_review_dispatch import _dispatch_dataset_review_intent
@@ -281,8 +280,7 @@ async def _dispatch_intent(intent: dict[str, Any], current_user: User, task_mana
             if not dashboard_id or not env_id or (not provider_id):
                 raise HTTPException(status_code=422, detail='Missing dashboard_id/environment/provider. Укажите ID/slug дашборда или окружение.')
             provider = LLMProviderService(db).get_provider(provider_id)
-            provider_model = provider.default_model if provider else ''
-            if not is_multimodal_model(provider_model, provider.provider_type if provider else None):
+            if not provider or not bool(provider.is_multimodal):
                 raise HTTPException(status_code=422, detail='Selected provider model is not multimodal for dashboard validation. Выберите мультимодальную модель (например, gpt-4o).')
             task = await task_manager.create_task(plugin_id='llm_dashboard_validation', params={'dashboard_id': str(dashboard_id), 'environment_id': env_id, 'provider_id': provider_id}, user_id=current_user.id)
             logger.reflect('Belief protocol postcondition checkpoint for _dispatch_intent')

backend/src/api/routes/llm.py

@@ -83,6 +83,7 @@ async def get_providers(
             api_key=mask_api_key(service.get_decrypted_api_key(p.id)) if p.api_key else "",
             default_model=p.default_model,
             is_active=p.is_active,
+            is_multimodal=bool(p.is_multimodal) if p.is_multimodal is not None else False,
         )
         for p in providers
     ]
@@ -268,6 +269,7 @@ async def create_provider(
         api_key=mask_api_key(config.api_key),
         default_model=provider.default_model,
         is_active=provider.is_active,
+        is_multimodal=bool(provider.is_multimodal) if provider.is_multimodal is not None else False,
     )
 
 
@@ -303,6 +305,7 @@ async def update_provider(
         api_key=mask_api_key(service.get_decrypted_api_key(provider.id)) if provider.api_key else "",
         default_model=provider.default_model,
         is_active=provider.is_active,
+        is_multimodal=bool(provider.is_multimodal) if provider.is_multimodal is not None else False,
     )
 
 

backend/src/api/routes/tasks.py

@@ -21,7 +21,6 @@ from ...dependencies import (
     has_permission,
 )
 from ...services.llm_prompt_templates import (
-    is_multimodal_model,
     normalize_llm_settings,
     resolve_bound_provider_id,
 )
@@ -104,10 +103,7 @@ async def create_task(
                             raise ValueError(f"LLM Provider {provider_id} not found")
                         if (
                             request.plugin_id == "llm_dashboard_validation"
-                            and not is_multimodal_model(
-                                db_provider.default_model,
-                                db_provider.provider_type,
-                            )
+                            and not bool(db_provider.is_multimodal)
                         ):
                             raise HTTPException(
                                 status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,

backend/src/api/routes/translate/_job_routes.py

@@ -250,11 +250,8 @@ async def get_datasource_columns(
 # #endregion get_datasource_columns
 
 
-# #region check_target_schema [C:3] [TYPE Function]
+# #region check_target_schema [C:3] [TYPE Function] [SEMANTICS api,translate,validate]
 # @BRIEF Проверяет схему целевой таблицы: какие колонки ожидаются, какие есть, каких не хватает.
-# @PRE User has translate.job.view permission.
-# @POST Возвращает diff expected vs actual columns.
-# @SIDE_EFFECT Делает SQL-запрос к information_schema.columns через Superset SQL Lab.
 # @RELATION DEPENDS_ON -> [validate_target_table_schema]
 # @RELATION DEPENDS_ON -> [TargetSchemaValidationRequest]
 # @RELATION DEPENDS_ON -> [TargetSchemaValidationResponse]

backend/src/models/llm.py

@@ -46,6 +46,7 @@ class LLMProvider(Base):
     api_key = Column(String, nullable=False) # Should be encrypted
     default_model = Column(String, nullable=False)
     is_active = Column(Boolean, default=True)
+    is_multimodal = Column(Boolean, default=False)
     created_at = Column(DateTime, default=datetime.utcnow)
 # #endregion LLMProvider
 

backend/src/plugins/llm_analysis/models.py

@@ -28,6 +28,7 @@ class LLMProviderConfig(BaseModel):
     api_key: str | None = None
     default_model: str
     is_active: bool = True
+    is_multimodal: bool = False
 # #endregion LLMProviderConfig
 
 # #region ValidationStatus [TYPE Class]

backend/src/plugins/llm_analysis/plugin.py

@@ -22,7 +22,6 @@ from ...core.task_manager.context import TaskContext
 from ...models.llm import ValidationPolicy, ValidationRecord
 from ...services.llm_prompt_templates import (
     DEFAULT_LLM_PROMPTS,
-    is_multimodal_model,
     normalize_llm_settings,
     render_prompt,
 )
@@ -140,7 +139,8 @@ class DashboardValidationPlugin(PluginBase):
                 llm_log.debug(f"  Base URL: {db_provider.base_url}")
                 llm_log.debug(f"  Default Model: {db_provider.default_model}")
                 llm_log.debug(f"  Is Active: {db_provider.is_active}")
-                if not is_multimodal_model(db_provider.default_model, db_provider.provider_type):
+                llm_log.debug(f"  Is Multimodal: {db_provider.is_multimodal}")
+                if not bool(db_provider.is_multimodal):
                     raise ValueError(
                         "Dashboard validation requires a multimodal model (image input support)."
                     )

backend/src/plugins/translate/__tests__/test_lang_detect.py

@@ -1,14 +1,6 @@
 # #region LanguageDetectServiceTests [C:3] [TYPE Module] [SEMANTICS test, language, detection, heuristic]
 # @BRIEF Unit tests for LanguageDetectService — local language detection via lingua.
-# @LAYER Test
-# @RELATION BINDS_TO -> [LanguageDetectService:Module]
-# @TEST_CONTRACT LanguageDetectService -> detect_language, build_detector, get_detector, batch_detect
-# @TEST_EDGE empty_text -> returns "und"
-# @TEST_EDGE numeric_text -> returns "und"
-# @TEST_EDGE short_text -> correctly detects language
-# @TEST_EDGE same_language_pre_filter -> batch_detect returns target language for matching rows
-# @TEST_EDGE detector_cache -> get_detector returns same instance for same language set
-# @TEST_EDGE cross_language -> English text with Russian detector returns "und"
+# @RELATION BINDS_TO -> [LanguageDetectService]
 
 import pytest
 

backend/src/plugins/translate/__tests__/test_target_schema.py

@@ -1,20 +1,12 @@
 # region TargetSchemaValidationTests [TYPE Module]
 # @SEMANTICS: test, translate, target-schema, validation
-# @PURPOSE: Tests for target table schema validation: _build_expected_columns, _parse_column_results, validate_target_table_schema.
+# @PURPOSE: Tests for target table schema validation.
 # @LAYER: Test
 # @RELATION: BINDS_TO -> [TargetSchemaValidation]
 # @TEST_CONTRACT: _build_expected_columns -> list[TargetSchemaColumnInfo]
-# @TEST_CONTRACT: _parse_column_results -> (list[dict], bool)
+# @TEST_CONTRACT: _extract_columns_from_rows -> list[dict]
+# @TEST_CONTRACT: _parse_sqllab_result -> (list[dict], bool)
 # @TEST_CONTRACT: validate_target_table_schema -> TargetSchemaValidationResponse
-# @TEST_EDGE: missing_target_key_cols -> Only context + is_original returned
-# @TEST_EDGE: deduplication -> Duplicate column names are removed
-# @TEST_EDGE: empty_result -> Returns ([], False)
-# @TEST_EDGE: superset_sync_format -> Standard Superset response format parsed
-# @TEST_EDGE: superset_async_format -> Async polling response format parsed
-# @TEST_EDGE: get_query_results_format -> get_query_results response format parsed
-# @TEST_EDGE: executor_failure -> SQL Lab query fails, error returned
-# @TEST_EDGE: sql_injection_table_name -> Invalid table name rejected with error
-# @TEST_EDGE: executor_exception -> Exception during execution returns error response
 
 from unittest.mock import MagicMock, patch
 
@@ -26,13 +18,13 @@ from src.schemas.translate import (
 )
 from src.plugins.translate.service_target_schema import (
     _build_expected_columns,
-    _parse_column_results,
+    _extract_columns_from_rows,
+    _parse_sqllab_result,
     validate_target_table_schema,
 )
 
 
 # region build_request [TYPE Function]
-# @PURPOSE: Helper to build a TargetSchemaValidationRequest with defaults.
 @pytest.fixture
 def build_request():
     def _build(**overrides):
@@ -58,21 +50,14 @@ def build_request():
 
 
 # region TestBuildExpectedColumns [TYPE Class]
-# @PURPOSE: Tests for _build_expected_columns logic.
 class TestBuildExpectedColumns:
 
-    # region test_basic_case [TYPE Function]
-    # @PURPOSE: target_key_cols + target_column produces id, translated_text, context, is_original.
     def test_basic_case(self, build_request) -> None:
         req = build_request()
         result = _build_expected_columns(req)
         names = [c.name for c in result]
         assert names == ["id", "translated_text", "context", "is_original"]
 
-    # endregion test_basic_case
-
-    # region test_all_fields [TYPE Function]
-    # @PURPOSE: All optional column fields produce 7 columns.
     def test_all_fields(self, build_request) -> None:
         req = build_request(
             target_language_column="lang",
@@ -90,20 +75,12 @@ class TestBuildExpectedColumns:
         assert "context" in names
         assert "is_original" in names
 
-    # endregion test_all_fields
-
-    # region test_empty_target_key_cols [TYPE Function]
-    # @PURPOSE: Empty target_key_cols produces just translated_text, context, is_original.
     def test_empty_target_key_cols(self, build_request) -> None:
         req = build_request(target_key_cols=[])
         result = _build_expected_columns(req)
         names = [c.name for c in result]
         assert names == ["translated_text", "context", "is_original"]
 
-    # endregion test_empty_target_key_cols
-
-    # region test_translation_column_fallback [TYPE Function]
-    # @PURPOSE: When target_column is None, translation_column is used as fallback.
     def test_translation_column_fallback(self, build_request) -> None:
         req = build_request(target_column=None, translation_column="source_col")
         result = _build_expected_columns(req)
@@ -111,10 +88,6 @@ class TestBuildExpectedColumns:
         assert "source_col" in names
         assert names[1] == "source_col"
 
-    # endregion test_translation_column_fallback
-
-    # region test_dedup_same_names [TYPE Function]
-    # @PURPOSE: Duplicate column names are removed preserving order.
     def test_dedup_same_names(self, build_request) -> None:
         req = build_request(
             target_key_cols=["id", "id"],
@@ -126,10 +99,6 @@ class TestBuildExpectedColumns:
         assert names.count("id") == 1
         assert names.count("name") == 1
 
-    # endregion test_dedup_same_names
-
-    # region test_empty_request [TYPE Function]
-    # @PURPOSE: No key cols and no target/translation column produces just context + is_original.
     def test_empty_request(self, build_request) -> None:
         req = build_request(
             target_key_cols=[],
@@ -140,10 +109,6 @@ class TestBuildExpectedColumns:
         names = [c.name for c in result]
         assert names == ["context", "is_original"]
 
-    # endregion test_empty_request
-
-    # region test_column_order_preserved [TYPE Function]
-    # @PURPOSE: Column order is preserved: key_cols, target, lang, source, src_lang, context, is_original.
     def test_column_order_preserved(self, build_request) -> None:
         req = build_request(
             target_key_cols=["pk1", "pk2"],
@@ -159,27 +124,19 @@ class TestBuildExpectedColumns:
             "src_col", "src_lang_col", "context", "is_original",
         ]
         assert names == expected_order
-
-    # endregion test_column_order_preserved
 # endregion TestBuildExpectedColumns
 
 
-# region TestParseColumnResults [TYPE Class]
-# @PURPOSE: Tests for _parse_column_results response parsing.
-class TestParseColumnResults:
+# region TestExtractColumnsFromRows [TYPE Class]
+class TestExtractColumnsFromRows:
 
-    # region test_superset_sync_format [TYPE Function]
-    # @PURPOSE: Standard Superset sync mode (columns + data directly in response).
-    def test_superset_sync_format(self) -> None:
-        result = {
-            "columns": [
-                {"name": "id", "type": "integer", "is_nullable": "YES"},
-                {"name": "name", "type": "varchar", "is_nullable": "NO"},
-            ],
-            "data": [{"id": 1, "name": "test"}],
-        }
-        cols, exists = _parse_column_results({"raw_response": result})
-        assert exists is True
+    def test_postgres_information_schema(self) -> None:
+        """PostgreSQL information_schema формат: column_name, data_type, is_nullable."""
+        rows = [
+            {"column_name": "id", "data_type": "integer", "is_nullable": "YES"},
+            {"column_name": "name", "data_type": "varchar", "is_nullable": "NO"},
+        ]
+        cols = _extract_columns_from_rows(rows)
         assert len(cols) == 2
         assert cols[0]["name"] == "id"
         assert cols[0]["type"] == "integer"
@@ -188,166 +145,152 @@ class TestParseColumnResults:
         assert cols[1]["type"] == "varchar"
         assert cols[1]["is_nullable"] is False
 
-    # endregion test_superset_sync_format
+    def test_clickhouse_describe_table(self) -> None:
+        """ClickHouse DESCRIBE TABLE формат: name, type."""
+        rows = [
+            {"name": "report_date", "type": "Date"},
+            {"name": "comment_text", "type": "String"},
+            {"name": "is_original", "type": "UInt8"},
+        ]
+        cols = _extract_columns_from_rows(rows)
+        assert len(cols) == 3
+        assert cols[0]["name"] == "report_date"
+        assert cols[0]["type"] == "Date"
+        assert cols[2]["name"] == "is_original"
+        assert cols[2]["type"] == "UInt8"
 
-    # region test_async_polling_format [TYPE Function]
-    # @PURPOSE: Async polling format (result -> columns + data).
-    def test_async_polling_format(self) -> None:
+    def test_mixed_keys(self) -> None:
+        """Разные ключи в одном наборе — приоритет column_name > name > Field."""
+        rows = [
+            {"Field": "id", "Type": "int"},
+            {"name": "name", "type": "text"},
+            {"column_name": "value", "data_type": "float"},
+        ]
+        cols = _extract_columns_from_rows(rows)
+        assert len(cols) == 3
+        # column_name имеет приоритет, потом name, потом Field
+        assert cols[0]["name"] == "id"
+        assert cols[1]["name"] == "name"
+        assert cols[2]["name"] == "value"
+
+    def test_empty_rows(self) -> None:
+        cols = _extract_columns_from_rows([])
+        assert cols == []
+
+    def test_invalid_row_type(self) -> None:
+        cols = _extract_columns_from_rows([123, "str", None])
+        assert cols == []
+
+    def test_row_without_name_keys(self) -> None:
+        cols = _extract_columns_from_rows([{"foo": "bar"}])
+        assert cols == []
+# endregion TestExtractColumnsFromRows
+
+
+# region TestParseSqlLabResult [TYPE Class]
+class TestParseSqlLabResult:
+
+    def test_sync_format_with_data(self) -> None:
+        """Формат 1: прямой ответ с data."""
         result = {
-            "result": {
-                "columns": [
-                    {"name": "col1", "type": "text"},
-                ],
+            "raw_response": {
+                "columns": [{"name": "col1"}],
                 "data": [{"col1": "val1"}],
             }
         }
-        cols, exists = _parse_column_results({"raw_response": result})
+        rows, exists = _parse_sqllab_result(result)
         assert exists is True
-        assert len(cols) == 1
-        assert cols[0]["name"] == "col1"
+        assert len(rows) == 1
+        assert rows[0]["col1"] == "val1"
 
-    # endregion test_async_polling_format
-
-    # region test_get_query_results_format [TYPE Function]
-    # @PURPOSE: get_query_results format (results -> columns + data).
-    def test_get_query_results_format(self) -> None:
+    def test_async_format(self) -> None:
+        """Формат 2: вложенный result."""
         result = {
-            "results": {
-                "columns": [
-                    {"name": "a", "type": "int"},
-                ],
-                "data": [{"a": 1}],
-            }
-        }
-        cols, exists = _parse_column_results({"raw_response": result})
-        assert exists is True
-        assert len(cols) == 1
-        assert cols[0]["name"] == "a"
-
-    # endregion test_get_query_results_format
-
-    # region test_deeply_nested_get_query_results [TYPE Function]
-    # @PURPOSE: get_query_results with nested result dict (results -> result -> columns + data).
-    def test_deeply_nested_get_query_results(self) -> None:
-        result = {
-            "results": {
+            "raw_response": {
                 "result": {
-                    "columns": [
-                        {"name": "x", "type": "float"},
-                    ],
-                    "data": [{"x": 1.0}],
+                    "columns": [{"name": "col1"}],
+                    "data": [{"col1": "val1"}],
                 }
             }
         }
-        cols, exists = _parse_column_results({"raw_response": result})
+        rows, exists = _parse_sqllab_result(result)
         assert exists is True
-        assert len(cols) == 1
-        assert cols[0]["name"] == "x"
+        assert len(rows) == 1
 
-    # endregion test_deeply_nested_get_query_results
+    def test_get_query_results_format(self) -> None:
+        """Формат 3: results → data."""
+        result = {
+            "raw_response": {
+                "results": {
+                    "columns": [{"name": "col1"}],
+                    "data": [{"col1": "val1"}],
+                }
+            }
+        }
+        rows, exists = _parse_sqllab_result(result)
+        assert exists is True
+        assert len(rows) == 1
 
-    # region test_empty_result [TYPE Function]
-    # @PURPOSE: Empty result dict returns ([], False).
-    def test_empty_result(self) -> None:
-        cols, exists = _parse_column_results({"raw_response": {}})
-        assert cols == []
+    def test_empty_data(self) -> None:
+        result = {"raw_response": {"columns": [{"name": "c"}], "data": []}}
+        rows, exists = _parse_sqllab_result(result)
         assert exists is False
+        assert rows == []
 
-    # endregion test_empty_result
+    def test_no_data_key(self) -> None:
+        result = {"raw_response": {"columns": [{"name": "c"}]}}
+        rows, exists = _parse_sqllab_result(result)
+        assert exists is False
+        assert rows == []
 
-    # region test_none_result [TYPE Function]
-    # @PURPOSE: None result returns ([], False) via early guard.
     def test_none_result(self) -> None:
-        cols, exists = _parse_column_results(None)
-        assert cols == []
+        rows, exists = _parse_sqllab_result(None)
+        assert rows == []
         assert exists is False
 
-    # endregion test_none_result
-
-    # region test_raw_response_none [TYPE Function]
-    # @PURPOSE: raw_response=None causes TypeError — known production gap (not guarded).
     def test_raw_response_none(self) -> None:
-        with pytest.raises(TypeError):
-            _parse_column_results({"raw_response": None})
-
-    # endregion test_raw_response_none
-
-    # region test_result_without_columns [TYPE Function]
-    # @PURPOSE: Result without columns key returns ([], False).
-    def test_result_without_columns(self) -> None:
-        result = {"status": "success", "data": []}
-        cols, exists = _parse_column_results({"raw_response": result})
-        assert cols == []
+        rows, exists = _parse_sqllab_result({"raw_response": None})
+        assert rows == []
         assert exists is False
 
-    # endregion test_result_without_columns
-
-    # region test_table_exists_with_data [TYPE Function]
-    # @PURPOSE: Non-empty data means table exists.
-    def test_table_exists_with_data(self) -> None:
+    def test_list_based_data(self) -> None:
+        """Строки в виде списков вместо словарей (старые версии Superset)."""
         result = {
-            "columns": [{"name": "c"}],
-            "data": [{"c": "v"}],
+            "raw_response": {
+                "columns": [{"name": "id"}, {"name": "name"}],
+                "data": [[1, "foo"], [2, "bar"]],
+            }
         }
-        _, exists = _parse_column_results({"raw_response": result})
+        rows, exists = _parse_sqllab_result(result)
         assert exists is True
-
-    # endregion test_table_exists_with_data
-
-    # region test_table_not_exists_empty_data [TYPE Function]
-    # @PURPOSE: Empty data means table does not exist.
-    def test_table_not_exists_empty_data(self) -> None:
-        result = {
-            "columns": [{"name": "c"}],
-            "data": [],
-        }
-        _, exists = _parse_column_results({"raw_response": result})
-        assert exists is False
-
-    # endregion test_table_not_exists_empty_data
-
-    # region test_alternate_column_key_names [TYPE Function]
-    # @PURPOSE: Columns with alternate key names (column_name, Column) parsed correctly.
-    def test_alternate_column_key_names(self) -> None:
-        result = {
-            "columns": [
-                {"column_name": "id", "data_type": "int"},
-                {"Column": "name", "Type": "text"},
-            ],
-            "data": [],
-        }
-        cols, _ = _parse_column_results({"raw_response": result})
-        assert len(cols) == 2
-        assert cols[0]["name"] == "id"
-        assert cols[1]["name"] == "name"
-
-    # endregion test_alternate_column_key_names
-# endregion TestParseColumnResults
+        assert len(rows) == 2
+        assert rows[0]["id"] == 1
+        assert rows[0]["name"] == "foo"
+# endregion TestParseSqlLabResult
 
 
 # region TestValidateTargetTableSchema [TYPE Class]
-# @PURPOSE: Tests for validate_target_table_schema with mocked Superset executor.
 class TestValidateTargetTableSchema:
 
-    # region test_all_columns_present [TYPE Function]
-    # @PURPOSE: All expected columns present in target table.
     @patch("src.plugins.translate.service_target_schema.SupersetSqlLabExecutor")
     def test_all_columns_present(self, mock_executor, build_request) -> None:
+        """Все ожидаемые колонки присутствуют в таблице."""
         req = build_request()
         config_manager = MagicMock()
 
         instance = mock_executor.return_value
         instance.resolve_database_id.return_value = None
+        instance.get_database_backend.return_value = "postgresql"
         instance.execute_and_poll.return_value = {
             "status": "success",
             "raw_response": {
-                "columns": [
-                    {"name": "id", "type": "integer", "is_nullable": "YES"},
-                    {"name": "translated_text", "type": "text", "is_nullable": "YES"},
-                    {"name": "context", "type": "text", "is_nullable": "YES"},
-                    {"name": "is_original", "type": "boolean", "is_nullable": "YES"},
+                "columns": [{"name": "column_name"}, {"name": "data_type"}],
+                "data": [
+                    {"column_name": "id", "data_type": "integer"},
+                    {"column_name": "translated_text", "data_type": "text"},
+                    {"column_name": "context", "data_type": "text"},
+                    {"column_name": "is_original", "data_type": "boolean"},
                 ],
-                "data": [{"id": 1}],
             },
         }
 
@@ -359,25 +302,23 @@ class TestValidateTargetTableSchema:
         assert len(response.expected_columns) == 4
         assert len(response.actual_columns) == 4
 
-    # endregion test_all_columns_present
-
-    # region test_missing_columns [TYPE Function]
-    # @PURPOSE: Target table is missing some expected columns.
     @patch("src.plugins.translate.service_target_schema.SupersetSqlLabExecutor")
     def test_missing_columns(self, mock_executor, build_request) -> None:
+        """В таблице не хватает некоторых ожидаемых колонок."""
         req = build_request()
         config_manager = MagicMock()
 
         instance = mock_executor.return_value
         instance.resolve_database_id.return_value = None
+        instance.get_database_backend.return_value = "postgresql"
         instance.execute_and_poll.return_value = {
             "status": "success",
             "raw_response": {
-                "columns": [
-                    {"name": "id", "type": "integer", "is_nullable": "YES"},
-                    {"name": "context", "type": "text", "is_nullable": "YES"},
+                "columns": [{"name": "column_name"}],
+                "data": [
+                    {"column_name": "id"},
+                    {"column_name": "context"},
                 ],
-                "data": [{"id": 1}],
             },
         }
 
@@ -389,17 +330,54 @@ class TestValidateTargetTableSchema:
         assert "is_original" in missing_names
         assert "id" not in missing_names
 
-    # endregion test_missing_columns
+    @patch("src.plugins.translate.service_target_schema.SupersetSqlLabExecutor")
+    def test_clickhouse_describe_table(self, mock_executor, build_request) -> None:
+        """ClickHouse использует DESCRIBE TABLE — другой формат ответа."""
+        req = build_request(
+            target_key_cols=["report_date", "document_number"],
+            target_column="comment_text",
+            target_language_column="lang_code",
+            target_source_column="source_text",
+            target_source_language_column="src_lang",
+        )
+        config_manager = MagicMock()
+
+        instance = mock_executor.return_value
+        instance.resolve_database_id.return_value = None
+        instance.get_database_backend.return_value = "clickhouse"
+        instance.execute_and_poll.return_value = {
+            "status": "success",
+            "raw_response": {
+                "columns": [{"name": "name"}, {"name": "type"}],
+                "data": [
+                    {"name": "report_date", "type": "Date"},
+                    {"name": "document_number", "type": "String"},
+                    {"name": "lang_code", "type": "String"},
+                    {"name": "source_text", "type": "String"},
+                    {"name": "src_lang", "type": "String"},
+                    {"name": "comment_text", "type": "String"},
+                    {"name": "context", "type": "String"},
+                    {"name": "is_original", "type": "UInt8"},
+                ],
+            },
+        }
+
+        response = validate_target_table_schema(req, config_manager)
+        assert response.table_exists is True
+        assert response.error is None
+        assert response.all_present is True
+        assert len(response.missing_columns) == 0
+        assert len(response.actual_columns) == 8
 
-    # region test_superset_failed_status [TYPE Function]
-    # @PURPOSE: Superset returns failed status.
     @patch("src.plugins.translate.service_target_schema.SupersetSqlLabExecutor")
     def test_superset_failed_status(self, mock_executor, build_request) -> None:
+        """Superset возвращает failed статус."""
         req = build_request()
         config_manager = MagicMock()
 
         instance = mock_executor.return_value
         instance.resolve_database_id.return_value = None
+        instance.get_database_backend.return_value = "postgresql"
         instance.execute_and_poll.return_value = {
             "status": "failed",
             "error_message": "Query timeout",
@@ -411,17 +389,15 @@ class TestValidateTargetTableSchema:
         assert "Query timeout" in response.error
         assert response.all_present is False
 
-    # endregion test_superset_failed_status
-
-    # region test_executor_exception [TYPE Function]
-    # @PURPOSE: Executor throws an exception.
     @patch("src.plugins.translate.service_target_schema.SupersetSqlLabExecutor")
     def test_executor_exception(self, mock_executor, build_request) -> None:
+        """Executor бросает исключение."""
         req = build_request()
         config_manager = MagicMock()
 
         instance = mock_executor.return_value
         instance.resolve_database_id.return_value = None
+        instance.get_database_backend.return_value = "postgresql"
         instance.execute_and_poll.side_effect = ConnectionError("Superset API unavailable")
 
         response = validate_target_table_schema(req, config_manager)
@@ -430,11 +406,8 @@ class TestValidateTargetTableSchema:
         assert "Superset API unavailable" in response.error
         assert response.all_present is False
 
-    # endregion test_executor_exception
-
-    # region test_sql_injection_table_name [TYPE Function]
-    # @PURPOSE: Invalid table name with space is rejected with error.
     def test_sql_injection_table_name(self, build_request) -> None:
+        """Невалидное имя таблицы с пробелом — ошибка."""
         req = build_request(target_table="my table; DROP TABLE students; --")
         config_manager = MagicMock()
 
@@ -444,11 +417,8 @@ class TestValidateTargetTableSchema:
         assert "Invalid target table name" in response.error
         assert response.all_present is False
 
-    # endregion test_sql_injection_table_name
-
-    # region test_sql_injection_schema_name [TYPE Function]
-    # @PURPOSE: Invalid schema name with DROP is rejected with error.
     def test_sql_injection_schema_name(self, build_request) -> None:
+        """Невалидное имя схемы с DROP — ошибка."""
         req = build_request(target_schema="public; DROP TABLE students; --")
         config_manager = MagicMock()
 
@@ -458,23 +428,19 @@ class TestValidateTargetTableSchema:
         assert "Invalid target schema name" in response.error
         assert response.all_present is False
 
-    # endregion test_sql_injection_schema_name
-
-    # region test_table_not_exists [TYPE Function]
-    # @PURPOSE: Target table does not exist (empty data from information_schema).
     @patch("src.plugins.translate.service_target_schema.SupersetSqlLabExecutor")
     def test_table_not_exists(self, mock_executor, build_request) -> None:
+        """Таблица не существует — пустой data."""
         req = build_request()
         config_manager = MagicMock()
 
         instance = mock_executor.return_value
         instance.resolve_database_id.return_value = None
+        instance.get_database_backend.return_value = "postgresql"
         instance.execute_and_poll.return_value = {
             "status": "success",
             "raw_response": {
-                "columns": [
-                    {"name": "id", "type": "integer"},
-                ],
+                "columns": [{"name": "column_name"}],
                 "data": [],
             },
         }
@@ -483,8 +449,6 @@ class TestValidateTargetTableSchema:
         assert response.table_exists is False
         assert response.error is None
         assert response.all_present is False
-        assert len(response.missing_columns) == 3  # translated_text, context, is_original
-
-    # endregion test_table_not_exists
+        assert len(response.missing_columns) == 4  # id, translated_text, context, is_original
 # endregion TestValidateTargetTableSchema
 # endregion TargetSchemaValidationTests

backend/src/plugins/translate/__tests__/test_text_cleaner.py

@@ -0,0 +1,186 @@
+# #region TestTextCleaner [C:3] [TYPE Module] [SEMANTICS test, text, cleaner, whitespace, truncation]
+# @BRIEF Verify text cleaning contracts — normalize_whitespace, truncate_text, clean_text.
+# @RELATION BINDS_TO -> [_text_cleaner:Module]
+# @TEST_EDGE: empty_string — empty/whitespace-only input returns ""
+# @TEST_EDGE: whitespace_variants — multiple spaces, newlines, tabs all collapse to single space
+# @TEST_EDGE: truncation_boundary — text shorter than, equal to, and longer than max_length
+# @TEST_EDGE: clean_combined — clean_text correctly chains normalize + truncate
+# @TEST_EDGE: zero_max_length — max_length=0 forces truncation on any non-empty text
+
+from src.plugins.translate._text_cleaner import normalize_whitespace, truncate_text, clean_text
+
+
+# region TestNormalizeWhitespace [TYPE Class]
+# @BRIEF Test suite for normalize_whitespace.
+class TestNormalizeWhitespace:
+
+    # region test_empty_string [TYPE Function]
+    # @BRIEF Empty string returns empty string.
+    def test_empty_string(self):
+        assert normalize_whitespace("") == ""
+    # endregion test_empty_string
+
+    # region test_whitespace_only [TYPE Function]
+    # @BRIEF String with only whitespace returns empty string.
+    def test_whitespace_only(self):
+        assert normalize_whitespace("   ") == ""
+        assert normalize_whitespace("\t") == ""
+        assert normalize_whitespace("\n") == ""
+    # endregion test_whitespace_only
+
+    # region test_multiple_spaces [TYPE Function]
+    # @BRIEF Multiple spaces between words are collapsed to single space.
+    def test_multiple_spaces(self):
+        assert normalize_whitespace("hello    world") == "hello world"
+    # endregion test_multiple_spaces
+
+    # region test_multiple_newlines [TYPE Function]
+    # @BRIEF Multiple newlines are collapsed to single space.
+    def test_multiple_newlines(self):
+        assert normalize_whitespace("hello\n\n\nworld") == "hello world"
+    # endregion test_multiple_newlines
+
+    # region test_mixed_whitespace [TYPE Function]
+    # @BRIEF Tabs, newlines, and spaces all collapse to single space.
+    def test_mixed_whitespace(self):
+        assert normalize_whitespace("hello\t  \n  world") == "hello world"
+    # endregion test_mixed_whitespace
+
+    # region test_leading_trailing_whitespace [TYPE Function]
+    # @BRIEF Leading and trailing whitespace is trimmed.
+    def test_leading_trailing_whitespace(self):
+        assert normalize_whitespace("  hello world  ") == "hello world"
+        assert normalize_whitespace("\nhello world\n") == "hello world"
+    # endregion test_leading_trailing_whitespace
+
+    # region test_already_clean [TYPE Function]
+    # @BRIEF Already clean text is returned unchanged.
+    def test_already_clean(self):
+        assert normalize_whitespace("hello world") == "hello world"
+    # endregion test_already_clean
+
+    # region test_single_word [TYPE Function]
+    # @BRIEF Single word with surrounding whitespace is trimmed to the word.
+    def test_single_word(self):
+        assert normalize_whitespace("  hello  ") == "hello"
+    # endregion test_single_word
+
+# endregion TestNormalizeWhitespace
+
+
+# region TestTruncateText [TYPE Class]
+# @BRIEF Test suite for truncate_text.
+class TestTruncateText:
+
+    # region test_empty_string [TYPE Function]
+    # @BRIEF Empty string stays empty regardless of max_length.
+    def test_empty_string(self):
+        assert truncate_text("") == ""
+        assert truncate_text("", max_length=0) == ""
+    # endregion test_empty_string
+
+    # region test_shorter_than_max [TYPE Function]
+    # @BRIEF Text shorter than max_length is returned unchanged.
+    def test_shorter_than_max(self):
+        assert truncate_text("hi", max_length=5) == "hi"
+    # endregion test_shorter_than_max
+
+    # region test_exactly_at_max [TYPE Function]
+    # @BRIEF Text exactly at max_length is returned unchanged (no "..." appended).
+    def test_exactly_at_max(self):
+        assert truncate_text("hello", max_length=5) == "hello"
+    # endregion test_exactly_at_max
+
+    # region test_longer_than_max [TYPE Function]
+    # @BRIEF Text longer than max_length is truncated with "..." appended.
+    def test_longer_than_max(self):
+        result = truncate_text("hello world", max_length=5)
+        assert result == "hello..."
+        assert len(result) == 8  # 5 chars + "..."
+    # endregion test_longer_than_max
+
+    # region test_zero_max_length [TYPE Function]
+    # @BRIEF max_length=0 truncates any non-empty text to "...".
+    def test_zero_max_length(self):
+        assert truncate_text("hello", max_length=0) == "..."
+    # endregion test_zero_max_length
+
+    # region test_default_max_length [TYPE Function]
+    # @BRIEF Default max_length of 500 does not truncate short text.
+    def test_default_max_length(self):
+        text = "x" * 100
+        assert truncate_text(text) == text
+    # endregion test_default_max_length
+
+    # region test_truncation_at_default_boundary [TYPE Function]
+    # @BRIEF Text exactly 500 chars is unchanged; 501 chars is truncated.
+    def test_truncation_at_default_boundary(self):
+        text_500 = "x" * 500
+        text_501 = "x" * 501
+        assert truncate_text(text_500) == text_500
+        result = truncate_text(text_501)
+        assert result == "x" * 500 + "..."
+        assert len(result) == 503
+    # endregion test_truncation_at_default_boundary
+
+# endregion TestTruncateText
+
+
+# region TestCleanText [TYPE Class]
+# @BRIEF Test suite for clean_text (combined normalize + truncate).
+class TestCleanText:
+
+    # region test_empty_string [TYPE Function]
+    # @BRIEF Empty string returns empty string.
+    def test_empty_string(self):
+        assert clean_text("") == ""
+    # endregion test_empty_string
+
+    # region test_whitespace_only [TYPE Function]
+    # @BRIEF Whitespace-only input returns empty string.
+    def test_whitespace_only(self):
+        assert clean_text("   \n  \t  ") == ""
+    # endregion test_whitespace_only
+
+    # region test_clean_and_short [TYPE Function]
+    # @BRIEF Already clean, short text is returned unchanged.
+    def test_clean_and_short(self):
+        assert clean_text("hello world") == "hello world"
+    # endregion test_clean_and_short
+
+    # region test_normalize_then_truncate [TYPE Function]
+    # @BRIEF Whitespace is normalized before truncation — counting clean chars.
+    def test_normalize_then_truncate(self):
+        # "hello   world" has 15 chars raw, normalized to "hello world" (11 chars)
+        # With max_length=5, should truncate normalized text to "hello..."
+        result = clean_text("hello   world", max_length=5)
+        assert result == "hello..."
+    # endregion test_normalize_then_truncate
+
+    # region test_normalize_keeps_text_under_limit [TYPE Function]
+    # @BRIEF Normalization reduces length enough that truncation is not needed.
+    def test_normalize_keeps_text_under_limit(self):
+        # "A  B" has 4 chars raw, normalizes to "A B" (3 chars), still under 5
+        result = clean_text("A  B", max_length=5)
+        assert result == "A B"
+    # endregion test_normalize_keeps_text_under_limit
+
+    # region test_leading_whitespace_then_truncate [TYPE Function]
+    # @BRIEF Leading whitespace is removed before truncation, avoiding wasted chars.
+    def test_leading_whitespace_then_truncate(self):
+        # "   hello world" normalizes to "hello world" (11 chars)
+        # With max_length=5: truncates to "hello..."
+        result = clean_text("   hello world", max_length=5)
+        assert result == "hello..."
+    # endregion test_leading_whitespace_then_truncate
+
+    # region test_default_max_length_passthrough [TYPE Function]
+    # @BRIEF With default max_length=500, text under 500 after normalize is unchanged.
+    def test_default_max_length_passthrough(self):
+        text = "  hello   world  "
+        expected = "hello world"
+        assert clean_text(text) == expected
+    # endregion test_default_max_length_passthrough
+
+# endregion TestCleanText
+# #endregion TestTextCleaner

backend/src/plugins/translate/_lang_detect.py

@@ -11,8 +11,15 @@
 #            langdetect — only 55 languages, less accurate on short texts.
 #            fasttext — requires native compilation, no pre-built wheel for this platform.
 
+import re
+
 from lingua import Language, LanguageDetector, LanguageDetectorBuilder
 
+# Cyrillic character range (Basic + Supplement)
+_CYRILLIC_RE = re.compile(r"[\u0400-\u04FF\u0500-\u052F]")
+# ASCII letter range (Latin-based)
+_ASCII_LETTER_RE = re.compile(r"[a-zA-Z]")
+
 # ---------------------------------------------------------------------------
 # Build BCP-47 → lingua Language mapping from the lingua Language enum
 # ---------------------------------------------------------------------------
@@ -128,10 +135,53 @@ def detect_language(text: str, detector: LanguageDetector) -> str:
 # #endregion detect_language
 
 
+# #region _character_block_fallback [C:2] [TYPE Function] [SEMANTICS language, heuristic, cyrillic]
+# @BRIEF When lingua returns "und", check if character-block dominance (e.g. Cyrillic)
+#         suggests a match to one of the target languages. Catches texts with many numbers
+#         and punctuation where n-gram-based detection is unreliable.
+# @RATIONALE Russian texts with numbers/punctuation (e.g. "По договору поставки. в объёме
+#            67 890 123,45 руб..") frequently get "und" from lingua because digits dilute
+#            the n-gram signal. A simple letter-block ratio catches these reliably.
+# @REJECTED Relying solely on lingua for all cases — too many false "und" on number-heavy texts.
+#            Using LLM for re-detection — defeats the purpose of local detection.
+def _character_block_fallback(
+    texts: list[str],
+    results: list[str],
+    target_languages: list[str] | None,
+) -> list[str]:
+    """Apply character-block heuristics for 'und' results.
+
+    For each 'und' result, if the target list includes a Cyrillic language (ru/uk/be)
+    and the text is Cyrillic-dominant (≥35% of letter chars), assign that language.
+    """
+    if not target_languages:
+        return results
+
+    tls_lower = [t.lower() for t in target_languages]
+    cyrillic_targets = [t for t in tls_lower if t in ("ru", "uk", "be")]
+    if not cyrillic_targets:
+        return results  # no Cyrillic target → nothing to do
+
+    for i, (text, result) in enumerate(zip(texts, results)):
+        if result != "und" or not text:
+            continue
+
+        ascii_letters = len(_ASCII_LETTER_RE.findall(text))
+        cyrillic_letters = len(_CYRILLIC_RE.findall(text))
+        total_letters = ascii_letters + cyrillic_letters
+
+        if total_letters > 0 and cyrillic_letters / total_letters >= 0.35:
+            results[i] = cyrillic_targets[0]
+
+    return results
+# #endregion _character_block_fallback
+
+
 # #region batch_detect [C:3] [TYPE Function] [SEMANTICS language, detection, batch]
 # @BRIEF Detect language for multiple texts in batch. Builds detector if not provided.
 # @RELATION DEPENDS_ON -> [detect_language]
 # @RELATION DEPENDS_ON -> [get_detector]
+# @RELATION DEPENDS_ON -> [_character_block_fallback]
 def batch_detect(
     texts: list[str],
     target_languages: list[str] | None = None,
@@ -150,6 +200,8 @@ def batch_detect(
     if detector is None:
         detector = get_detector(target_languages)
 
-    return [detect_language(t, detector) for t in texts]
+    results = [detect_language(t, detector) for t in texts]
+    results = _character_block_fallback(texts, results, target_languages)
+    return results
 # #endregion batch_detect
 # #endregion LanguageDetectService

backend/src/plugins/translate/_llm_call.py

@@ -19,12 +19,13 @@
 import json
 import time
 import uuid
+from datetime import UTC, datetime
 from typing import Any
 
 from sqlalchemy.orm import Session
 
 from ...core.logger import belief_scope, logger
-from ...models.translate import TranslationJob, TranslationLanguage, TranslationRecord
+from ...models.translate import TranslationBatch, TranslationJob, TranslationLanguage, TranslationRecord
 from ...services.llm_prompt_templates import render_prompt
 from ...services.llm_provider import LLMProviderService
 from ._llm_http import call_openai_compatible
@@ -148,8 +149,42 @@ class LLMTranslationService:
         mid = len(batch_rows) // 2
         logger.explore("LLM output truncated — splitting batch",
                        {"batch_id": batch_id, "batch_size": len(batch_rows), "split_at": mid, "depth": depth})
-        left = self.call_llm_for_batch(job, run_id, batch_rows[:mid], dict_matches, batch_id + "_L", max_tokens, depth + 1)
-        right = self.call_llm_for_batch(job, run_id, batch_rows[mid:], dict_matches, batch_id + "_R", max_tokens, depth + 1)
+
+        # Create proper TranslationBatch rows for child halves (fixes FK violation
+        # where _L/_R string suffixes referenced non-existent translation_batches rows).
+        # @RATIONALE Previous code appended "_L"/"_R" to batch_id string, violating
+        #            FK translation_records.batch_id → translation_batches.id.
+        # @REJECTED Continuing with string-suffixed batch_ids — causes FK violation
+        #           when any child record is flushed.
+        left_batch = TranslationBatch(
+            id=str(uuid.uuid4()), run_id=run_id, batch_index=-1,
+            status="RUNNING", total_records=len(batch_rows[:mid]),
+            started_at=datetime.now(UTC),
+        )
+        right_batch = TranslationBatch(
+            id=str(uuid.uuid4()), run_id=run_id, batch_index=-1,
+            status="RUNNING", total_records=len(batch_rows[mid:]),
+            started_at=datetime.now(UTC),
+        )
+        self.db.add_all([left_batch, right_batch])
+        self.db.flush()
+
+        left = self.call_llm_for_batch(job, run_id, batch_rows[:mid], dict_matches,
+                                        left_batch.id, max_tokens, depth + 1)
+        right = self.call_llm_for_batch(job, run_id, batch_rows[mid:], dict_matches,
+                                         right_batch.id, max_tokens, depth + 1)
+
+        # Finalise child batch stats
+        left_batch.completed_at = datetime.now(UTC)
+        right_batch.completed_at = datetime.now(UTC)
+        left_batch.successful_records = left["successful"]
+        right_batch.successful_records = right["successful"]
+        left_batch.failed_records = left["failed"]
+        right_batch.failed_records = right["failed"]
+        left_batch.status = "COMPLETED" if left["failed"] == 0 else "COMPLETED_WITH_ERRORS"
+        right_batch.status = "COMPLETED" if right["failed"] == 0 else "COMPLETED_WITH_ERRORS"
+        self.db.flush()
+
         return {"successful": left["successful"] + right["successful"],
                 "failed": left["failed"] + right["failed"],
                 "skipped": left["skipped"] + right["skipped"],

backend/src/plugins/translate/_text_cleaner.py

@@ -0,0 +1,63 @@
+# #region TextCleaner [C:3] [TYPE Module] [SEMANTICS translate, text, cleaning, whitespace, truncation]
+# @BRIEF Text cleaning utilities for the translation pipeline — whitespace normalization
+#         and character-length truncation. Used as a preprocessing step before LLM calls.
+# @LAYER Domain
+# @REJECTED Doing normalization inside the LLM prompt — wastes tokens and produces
+#           inconsistent results. Preprocessing text before the LLM call is more reliable.
+# @RATIONALE Centralizes text preprocessing logic used across the translation pipeline.
+#            Normalizing whitespace before truncation ensures accurate character counts.
+
+# #region normalize_whitespace [C:2] [TYPE Function] [SEMANTICS text, whitespace, normalize]
+# @BRIEF Collapse multiple spaces, tabs, and newlines into single spaces; trim leading/trailing
+#         whitespace. Returns empty string for empty or whitespace-only input.
+# @PRE text is a string (empty string allowed).
+# @POST Returns a string with no leading/trailing whitespace and single internal spaces.
+# @EXAMPLE normalize_whitespace("  hello   world  ") -> "hello world"
+# @EXAMPLE normalize_whitespace("") -> ""
+def normalize_whitespace(text: str) -> str:
+    """Collapse multiple spaces/newlines, trim, return clean text.
+
+    All Unicode whitespace characters (spaces, tabs, newlines, etc.) are
+    collapsed into single ASCII spaces. Leading/trailing whitespace is removed.
+    """
+    if not text:
+        return ""
+    return " ".join(text.split())
+# #endregion normalize_whitespace
+
+
+# #region truncate_text [C:2] [TYPE Function] [SEMANTICS text, truncation, length]
+# @BRIEF Truncate text to max_length characters, appending "..." if truncation occurs.
+# @PRE text is a string. max_length >= 0.
+# @POST When len(text) <= max_length, returns text unchanged.
+#       When len(text) > max_length, returns text[:max_length] + "...".
+# @EXAMPLE truncate_text("hello world", 5) -> "hello..."
+# @EXAMPLE truncate_text("hi", 5) -> "hi"
+def truncate_text(text: str, max_length: int = 500) -> str:
+    """Truncate text to max_length characters, adding '...' if truncated.
+
+    If the text is shorter than or equal to max_length, it is returned unchanged.
+    If it exceeds max_length, it is cut at max_length and '...' is appended.
+    """
+    if len(text) > max_length:
+        return text[:max_length] + "..."
+    return text
+# #endregion truncate_text
+
+
+# #region clean_text [C:2] [TYPE Function] [SEMANTICS text, clean, normalize, truncate]
+# @BRIEF Combine whitespace normalization and truncation into one step.
+#         Applies normalize_whitespace first, then truncate_text.
+# @PRE text is a string. max_length >= 0.
+# @POST Returns normalized and optionally truncated text.
+# @RELATION CALLS -> [normalize_whitespace]
+# @RELATION CALLS -> [truncate_text]
+# @EXAMPLE clean_text("  hello   world  ", 5) -> "hello..."  (normalized to "hello world",
+#          then truncated since "hello world" has 11 chars > 5)
+def clean_text(text: str, max_length: int = 500) -> str:
+    """Normalize whitespace then truncate to max_length."""
+    normalized = normalize_whitespace(text)
+    return truncate_text(normalized, max_length)
+# #endregion clean_text
+
+# #endregion TextCleaner

backend/src/plugins/translate/service_target_schema.py

@@ -1,4 +1,4 @@
-# #region TargetSchemaValidation [C:3] [TYPE Module] [SEMANTICS translate, schema, validation, target-table]
+# #region TargetSchemaValidation [C:4] [TYPE Module] [SEMANTICS translate, schema, validation, target-table]
 # @BRIEF Проверка схемы целевой таблицы: запрос колонок через Superset SQL Lab,
 #        сравнение с ожидаемыми (из build_columns), возврат diff.
 # @LAYER Service
@@ -8,15 +8,13 @@
 # @PRE Superset окружение доступно, target_database_id валиден.
 # @POST Возвращает актуальные, ожидаемые, отсутствующие и лишние колонки.
 # @SIDE_EFFECT Выполняет SQL-запрос через Superset SQL Lab.
-# @INVARIANT Если таблица не существует — table_exists=False без ошибки.
-# @INVARIANT Если Superset недоступен — error с описанием, all_present=False.
-# @INVARIANT Логика ожидаемых колонок sync с build_columns() в orchestrator_sql_rows.py.
+# @RATIONALE C4 — оркестрация: вызов executor, парсинг ответа, diff и построение ответа.
 # #endregion TargetSchemaValidation
 
-import logging
 import re
 from typing import Any
 
+from ...core.logger import belief_scope, logger
 from ...schemas.translate import (
     TargetSchemaColumnInfo,
     TargetSchemaValidationRequest,
@@ -25,48 +23,34 @@ from ...schemas.translate import (
 from ...core.config_manager import ConfigManager
 from .superset_executor import SupersetSqlLabExecutor
 
-logger = logging.getLogger(__name__)
-
 _TABLE_NAME_RE = re.compile(r'^[a-zA-Z_][a-zA-Z0-9_]*$')
 
 
 # #region _build_expected_columns [C:2] [TYPE Function]
 # @BRIEF Собирает список ожидаемых колонок по конфигурации column mapping.
-#   Логика идентична build_columns() из orchestrator_sql_rows.py,
-#   но не требует объекта TranslationJob.
 def _build_expected_columns(req: TargetSchemaValidationRequest) -> list[TargetSchemaColumnInfo]:
-    """
-    Определяет, какие колонки INSERT будет пытаться заполнить,
-    на основе конфигурации column mapping.
-    """
+    """Определяет, какие колонки INSERT будет пытаться заполнить."""
     names: list[str] = []
 
-    # Ключевые колонки (user-defined, для upsert matching)
     if req.target_key_cols:
         names.extend(req.target_key_cols)
 
-    # Целевая колонка для переведённого текста
     effective_target = req.target_column or req.translation_column
     if effective_target:
         names.append(effective_target)
 
-    # Колонка с кодом языка перевода
     if req.target_language_column:
         names.append(req.target_language_column)
 
-    # Колонка с исходным текстом (source reference)
     if req.target_source_column:
         names.append(req.target_source_column)
 
-    # Колонка с определённым исходным языком
     if req.target_source_language_column:
         names.append(req.target_source_language_column)
 
-    # Служебные колонки — всегда
     names.append("context")
     names.append("is_original")
 
-    # Дедупликация с сохранением порядка
     seen: set[str] = set()
     deduped: list[str] = []
     for c in names:
@@ -78,192 +62,264 @@ def _build_expected_columns(req: TargetSchemaValidationRequest) -> list[TargetSc
 # #endregion _build_expected_columns
 
 
-# #region _parse_column_results [C:2] [TYPE Function]
-# @BRIEF Извлекает информацию о колонках из ответа Superset SQL Lab.
+# #region _extract_columns_from_rows [C:2] [TYPE Function]
+# @BRIEF Извлекает список колонок таблицы из data-строк результата SQL Lab.
 #
-# Superset SQL Lab возвращает разные форматы в зависимости от версии.
-# Эта функция ищет колонки во всех возможных местах ответа.
-def _parse_column_results(result: dict[str, Any]) -> tuple[list[dict[str, Any]], bool]:
+# Для PostgreSQL (information_schema.columns) каждая строка содержит:
+#   {"column_name": "id", "data_type": "integer", "is_nullable": "YES"}
+#
+# Для ClickHouse (DESCRIBE TABLE) каждая строка содержит:
+#   {"name": "id", "type": "Int32"}
+#
+# Функция ищет имя колонки по нескольким возможным ключам и возвращает
+# унифицированный список TargetSchemaColumnInfo.
+def _extract_columns_from_rows(data_rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
     """
-    Парсит результат SQL Lab запроса для извлечения списка колонок таблицы.
-    Returns (columns_info, table_exists).
+    Извлекает информацию о колонках таблицы из data-строк SQL Lab ответа.
+    """
+    columns_info: list[dict[str, Any]] = []
+
+    for row in data_rows:
+        if not isinstance(row, dict):
+            continue
+
+        # Имя колонки: ищем по всем возможным ключам (PG, CH, разные версии Superset)
+        col_name = (
+            row.get("column_name")  # PostgreSQL information_schema
+            or row.get("name")       # ClickHouse DESCRIBE TABLE / MySQL SHOW COLUMNS
+            or row.get("Field")      # MySQL SHOW COLUMNS
+        )
+        if not col_name:
+            continue
+
+        # Тип данных
+        col_type = (
+            row.get("data_type")  # PG information_schema
+            or row.get("type")     # ClickHouse DESCRIBE TABLE
+            or row.get("Type")     # MySQL SHOW COLUMNS
+        )
+
+        # Nullable
+        is_nullable = row.get("is_nullable")  # PG
+        if isinstance(is_nullable, str):
+            is_nullable = is_nullable.upper() == "YES"
+        elif not isinstance(is_nullable, bool):
+            is_nullable = True  # ClickHouse не возвращает is_nullable, считаем True
+
+        columns_info.append({
+            "name": str(col_name),
+            "type": str(col_type) if col_type else None,
+            "is_nullable": is_nullable,
+        })
+
+    return columns_info
+# #endregion _extract_columns_from_rows
+
+
+# #region _parse_sqllab_result [C:2] [TYPE Function]
+# @BRIEF Извлекает data-строки из ответа Superset SQL Lab.
+#   Поддерживает 3 формата: sync mode, async polling, get_query_results.
+def _parse_sqllab_result(result: dict[str, Any]) -> tuple[list[dict[str, Any]], bool]:
+    """
+    Извлекает строки данных из ответа SQL Lab.
+    Returns (data_rows, table_exists).
     """
     if not result:
         return [], False
 
     raw = result.get("raw_response", result)
+    if not raw:
+        return [], False
 
-    # Пробуем извлечь данные из разных форматов ответа Superset
-    columns_data = None
     data_rows = None
 
-    # Формат 1: прямой ответ с колонками (sync mode)
-    if "columns" in raw and isinstance(raw["columns"], list):
-        columns_data = raw["columns"]
-        data_rows = raw.get("data") if isinstance(raw.get("data"), list) else None
+    # Формат 1: прямой ответ с data
+    if "data" in raw and isinstance(raw["data"], list):
+        data_rows = raw["data"]
 
     # Формат 2: вложенный result (async polling)
     elif "result" in raw and isinstance(raw["result"], dict):
         res = raw["result"]
-        if "columns" in res:
-            columns_data = res["columns"]
         data_rows = res.get("data") if isinstance(res.get("data"), list) else None
 
     # Формат 3: ключ results (get_query_results)
     elif "results" in raw and isinstance(raw["results"], dict):
         res = raw["results"]
-        if "columns" in res:
-            columns_data = res["columns"]
-        if "data" in res:
+        if "data" in res and isinstance(res["data"], list):
             data_rows = res["data"]
-        if isinstance(res.get("result"), dict):
+        elif isinstance(res.get("result"), dict):
             sub = res["result"]
-            if not columns_data and "columns" in sub:
-                columns_data = sub["columns"]
-            if not data_rows and "data" in sub:
-                data_rows = sub["data"]
+            data_rows = sub.get("data") if isinstance(sub.get("data"), list) else None
 
-    if not columns_data:
+    # Формат 4: results — список строк (execute_and_poll sync mode возвращает так)
+    elif "results" in raw and isinstance(raw["results"], list):
+        data_rows = raw["results"]
+
+    if data_rows is None:
         return [], False
 
-    # Проверяем существование таблицы: есть ли хотя бы одна строка
-    table_exists = data_rows is not None and len(data_rows) > 0
+    table_exists = len(data_rows) > 0
 
-    # Извлекаем имена и типы колонок из метаданных ответа
-    columns_info: list[dict[str, Any]] = []
-    for col in columns_data:
-        col_name = (
-            col.get("name")
-            or col.get("column_name")
-            or col.get("Column", "")
-        )
-        col_type = (
-            col.get("type")
-            or col.get("data_type")
-            or col.get("Type", "")
-            or col.get("col_type", "")
-        )
-        is_nullable = col.get("is_nullable")
-        # PostgreSQL returns 'YES'/'NO' for is_nullable
-        if isinstance(is_nullable, str):
-            is_nullable = is_nullable.upper() == "YES"
+    # Нормализуем формат строк: если data_rows — список списков, а не словарей
+    # (бывает в некоторых версиях Superset), конвертируем через columns metadata
+    if data_rows and not isinstance(data_rows[0], dict):
+        columns_raw = raw.get("columns") or (raw.get("result") or {}).get("columns") or []
+        col_names = []
+        for c in columns_raw:
+            cn = c.get("name") or c.get("column_name") or ""
+            if cn:
+                col_names.append(cn)
+        if col_names:
+            normalized = []
+            for row in data_rows:
+                if isinstance(row, list) and len(row) == len(col_names):
+                    normalized.append(dict(zip(col_names, row)))
+            data_rows = normalized
 
-        if col_name:
-            columns_info.append({
-                "name": str(col_name),
-                "type": str(col_type) if col_type else None,
-                "is_nullable": is_nullable if isinstance(is_nullable, bool) else True,
-            })
-
-    return columns_info, table_exists
-# #endregion _parse_column_results
+    return data_rows, table_exists
+# #endregion _parse_sqllab_result
 
 
-# #region validate_target_table_schema [C:3] [TYPE Function]
+# #region validate_target_table_schema [C:4] [TYPE Function] [SEMANTICS translate, schema, validate, orchestrate]
 # @BRIEF Основная функция: проверяет схему целевой таблицы через Superset SQL Lab.
+# @PRE Superset окружение и target_database_id валидны.
+# @POST Возвращает TargetSchemaValidationResponse с diff-анализом.
+# @SIDE_EFFECT Выполняет SQL-запрос к information_schema через Superset SQL Lab API.
+# @RELATION DEPENDS_ON -> [_build_expected_columns]
+# @RELATION DEPENDS_ON -> [_extract_columns_from_rows]
+# @RELATION DEPENDS_ON -> [_parse_sqllab_result]
+# @RELATION DEPENDS_ON -> [SupersetSqlLabExecutor]
 def validate_target_table_schema(
     req: TargetSchemaValidationRequest,
     config_manager: ConfigManager,
 ) -> TargetSchemaValidationResponse:
     """
     Проверяет схему целевой таблицы:
-    1. Вычисляет ожидаемые колонки (build_columns логика)
-    2. Запрашивает актуальные колонки через Superset SQL Lab
-       (SELECT column_name, data_type, is_nullable FROM information_schema.columns ...)
+    1. Вычисляет ожидаемые колонки
+    2. Запрашивает актуальные через Superset SQL Lab
     3. Сравнивает и возвращает diff
     """
-    # 1. Ожидаемые колонки
-    expected = _build_expected_columns(req)
-    expected_names = {c.name for c in expected}
+    with belief_scope("validate_target_table_schema"):
+        # 1. Ожидаемые колонки
+        expected = _build_expected_columns(req)
+        expected_names = {c.name for c in expected}
+        logger.reason("Built expected columns",
+                      extra={"payload": {"count": len(expected), "columns": [c.name for c in expected]}})
 
-    # 2. Валидация имён схемы и таблицы (защита от SQL injection в identifier)
-    if req.target_table and not _TABLE_NAME_RE.match(req.target_table):
-        return TargetSchemaValidationResponse(
-            table_exists=False,
-            error=f"Invalid target table name: '{req.target_table}'. Only alphanumeric and underscore allowed.",
-            expected_columns=expected,
-            actual_columns=[],
-            missing_columns=expected,
-            extra_columns=[],
-            all_present=False,
-        )
-    if req.target_schema and not _TABLE_NAME_RE.match(req.target_schema):
-        return TargetSchemaValidationResponse(
-            table_exists=False,
-            error=f"Invalid target schema name: '{req.target_schema}'. Only alphanumeric and underscore allowed.",
-            expected_columns=expected,
-            actual_columns=[],
-            missing_columns=expected,
-            extra_columns=[],
-            all_present=False,
-        )
-
-    # 3. Запрос через Superset SQL Lab
-    try:
-        executor = SupersetSqlLabExecutor(config_manager, req.environment_id)
-        executor.resolve_database_id(target_database_id=req.target_database_id)
-
-        safe_schema = (req.target_schema or "public").replace("'", "''")
-        safe_table = req.target_table.replace("'", "''")
-
-        sql = (
-            f"SELECT column_name, data_type, is_nullable "
-            f"FROM information_schema.columns "
-            f"WHERE table_schema = '{safe_schema}' "
-            f"AND table_name = '{safe_table}' "
-            f"ORDER BY ordinal_position"
-        )
-
-        result = executor.execute_and_poll(sql=sql, max_polls=15, poll_interval_seconds=1.0)
-
-        status = result.get("status", "")
-        if status == "failed":
-            error_msg = result.get("error_message", "SQL Lab query failed")
+        # 2. Валидация имён (SQL injection protection)
+        if req.target_table and not _TABLE_NAME_RE.match(req.target_table):
+            logger.explore("Invalid target table name rejected",
+                          extra={"payload": {"table": req.target_table},
+                                 "error": "Invalid characters in table name"})
             return TargetSchemaValidationResponse(
                 table_exists=False,
-                error=f"Superset SQL Lab error: {error_msg}",
-                expected_columns=expected,
-                actual_columns=[],
-                missing_columns=expected,
-                extra_columns=[],
-                all_present=False,
+                error=f"Invalid target table name: '{req.target_table}'. Only alphanumeric and underscore allowed.",
+                expected_columns=expected, actual_columns=[],
+                missing_columns=expected, extra_columns=[], all_present=False,
+            )
+        if req.target_schema and not _TABLE_NAME_RE.match(req.target_schema):
+            logger.explore("Invalid target schema name rejected",
+                          extra={"payload": {"schema": req.target_schema},
+                                 "error": "Invalid characters in schema name"})
+            return TargetSchemaValidationResponse(
+                table_exists=False,
+                error=f"Invalid target schema name: '{req.target_schema}'. Only alphanumeric and underscore allowed.",
+                expected_columns=expected, actual_columns=[],
+                missing_columns=expected, extra_columns=[], all_present=False,
             )
 
-        raw_columns, table_exists = _parse_column_results(result)
+        # 3. Запрос через Superset SQL Lab
+        target_ref = f"{req.target_schema or 'public'}.{req.target_table}"
+        logger.reason("Querying target table schema",
+                      extra={"payload": {"table": target_ref, "env": req.environment_id, "db_id": req.target_database_id}})
 
-        actual_cols = []
-        for col in raw_columns:
-            actual_cols.append(TargetSchemaColumnInfo(
-                name=col["name"],
-                data_type=col.get("type"),
-                is_nullable=col.get("is_nullable", True),
-            ))
+        try:
+            executor = SupersetSqlLabExecutor(config_manager, req.environment_id)
+            executor.resolve_database_id(target_database_id=req.target_database_id)
+            backend = executor.get_database_backend() or ""
 
-        actual_names = {c.name for c in actual_cols}
+            safe_schema = (req.target_schema or "public").replace("'", "''")
+            safe_table = req.target_table.replace("'", "''")
 
-        # 3. Diff
-        missing = [col for col in expected if col.name not in actual_names]
-        extra = [col for col in actual_cols if col.name not in expected_names]
+            # ClickHouse использует system.columns, всё остальное — information_schema.columns
+            is_clickhouse = any(kw in backend.lower() for kw in ("clickhouse", "ch"))
+            if is_clickhouse:
+                sql = (
+                    f"SELECT name, type, default_expression AS data_default "
+                    f"FROM system.columns "
+                    f"WHERE database = '{safe_schema}' "
+                    f"AND table = '{safe_table}' "
+                    f"ORDER BY position"
+                )
+            else:
+                sql = (
+                    f"SELECT column_name, data_type, is_nullable "
+                    f"FROM information_schema.columns "
+                    f"WHERE table_schema = '{safe_schema}' "
+                    f"AND table_name = '{safe_table}' "
+                    f"ORDER BY ordinal_position"
+                )
 
-        return TargetSchemaValidationResponse(
-            table_exists=table_exists,
-            expected_columns=expected,
-            actual_columns=actual_cols,
-            missing_columns=missing,
-            extra_columns=extra,
-            all_present=len(missing) == 0,
-        )
+            logger.reason("Executing SQL Lab query",
+                          extra={"payload": {"sql": sql[:200], "backend": backend}})
 
-    except Exception as e:
-        logger.warning("Target schema validation failed: %s", str(e), exc_info=True)
-        return TargetSchemaValidationResponse(
-            table_exists=False,
-            error=f"Failed to validate target schema: {e}",
-            expected_columns=expected,
-            actual_columns=[],
-            missing_columns=expected,
-            extra_columns=[],
-            all_present=False,
-        )
+            result = executor.execute_and_poll(sql=sql, max_polls=15, poll_interval_seconds=1.0)
+            status = result.get("status", "")
+
+            if status == "failed":
+                error_msg = result.get("error_message", "SQL Lab query failed")
+                logger.explore("SQL Lab query failed",
+                              extra={"payload": {"table": target_ref}, "error": error_msg})
+                return TargetSchemaValidationResponse(
+                    table_exists=False, error=f"Superset SQL Lab error: {error_msg}",
+                    expected_columns=expected, actual_columns=[],
+                    missing_columns=expected, extra_columns=[], all_present=False,
+                )
+
+            # Парсим data-строки результата (реальные колонки таблицы)
+            data_rows, table_exists = _parse_sqllab_result(result)
+            actual_cols_raw = _extract_columns_from_rows(data_rows)
+
+            actual_cols = []
+            for col in actual_cols_raw:
+                actual_cols.append(TargetSchemaColumnInfo(
+                    name=col["name"],
+                    data_type=col.get("type"),
+                    is_nullable=col.get("is_nullable", True),
+                ))
+
+            actual_names = {c.name for c in actual_cols}
+
+            # 4. Diff
+            missing = [col for col in expected if col.name not in actual_names]
+            extra = [col for col in actual_cols if col.name not in expected_names]
+
+            logger.reflect("Schema check complete",
+                          extra={"payload": {
+                              "table": target_ref, "table_exists": table_exists,
+                              "expected": len(expected), "found": len(actual_cols),
+                              "missing": len(missing), "extra": len(extra),
+                              "all_present": len(missing) == 0,
+                              "actual_columns": [c.name for c in actual_cols],
+                          }})
+
+            return TargetSchemaValidationResponse(
+                table_exists=table_exists,
+                expected_columns=expected,
+                actual_columns=actual_cols,
+                missing_columns=missing,
+                extra_columns=extra,
+                all_present=len(missing) == 0,
+            )
+
+        except Exception as e:
+            logger.explore("Target schema validation failed",
+                          extra={"payload": {"table": target_ref, "env": req.environment_id},
+                                 "error": str(e)})
+            return TargetSchemaValidationResponse(
+                table_exists=False, error=f"Failed to validate target schema: {e}",
+                expected_columns=expected, actual_columns=[],
+                missing_columns=expected, extra_columns=[], all_present=False,
+            )
 # #endregion validate_target_table_schema
 # #endregion TargetSchemaValidation

backend/src/services/__tests__/test_llm_plugin_persistence.py

@@ -75,6 +75,7 @@ async def test_dashboard_validation_plugin_persists_task_and_environment_ids(
         base_url="https://example.invalid/v1",
         default_model="gpt-4o",
         is_active=True,
+        is_multimodal=True,
     )
 
     # region _FakeProviderService [TYPE Class]

backend/src/services/__tests__/test_llm_provider.py

@@ -258,3 +258,125 @@ def test_is_masked_or_placeholder():
     assert is_masked_or_placeholder("...xyz") is True
     assert is_masked_or_placeholder("sk-real-key-1234") is False
     assert is_masked_or_placeholder("short") is False
+
+
+# endregion test_is_masked_or_placeholder
+
+
+# region test_create_provider_with_multimodal_flag [TYPE Function]
+# @RELATION: BINDS_TO -> [test_llm_provider:Module]
+# @PURPOSE: Verify provider creation persists the is_multimodal flag.
+def test_create_provider_with_multimodal_flag(service, mock_db):
+    """Verify is_multimodal=True is stored during provider creation."""
+    config = LLMProviderConfig(
+        provider_type=LLMProviderType.OPENAI,
+        name="Vision Provider",
+        base_url="https://api.openai.com",
+        api_key="sk-vision-key",
+        default_model="gpt-4o",
+        is_active=True,
+        is_multimodal=True,
+    )
+
+    provider = service.create_provider(config)
+
+    assert provider.is_multimodal is True
+    mock_db.add.assert_called()
+    mock_db.commit.assert_called()
+
+
+# endregion test_create_provider_with_multimodal_flag
+
+
+# region test_create_provider_without_multimodal_flag [TYPE Function]
+# @RELATION: BINDS_TO -> [test_llm_provider:Module]
+# @PURPOSE: Verify is_multimodal defaults to False when not specified.
+def test_create_provider_without_multimodal_flag(service, mock_db):
+    """Verify is_multimodal defaults to False."""
+    config = LLMProviderConfig(
+        provider_type=LLMProviderType.OPENAI,
+        name="Text Provider",
+        base_url="https://api.openai.com",
+        api_key="sk-text-key",
+        default_model="gpt-4.1-mini",
+        is_active=True,
+    )
+
+    provider = service.create_provider(config)
+
+    assert provider.is_multimodal is False
+
+
+# endregion test_create_provider_without_multimodal_flag
+
+
+# region test_update_provider_preserves_is_multimodal [TYPE Function]
+# @RELATION: BINDS_TO -> [test_llm_provider:Module]
+# @PURPOSE: Verify updating a provider preserves and correctly sets is_multimodal.
+def test_update_provider_preserves_is_multimodal(service, mock_db):
+    """Verify is_multimodal is updated correctly."""
+    existing_encrypted = EncryptionManager().encrypt("secret-value")
+    mock_provider = LLMProvider(
+        id="p1",
+        provider_type="openai",
+        name="Vision",
+        base_url="https://api.openai.com/v1",
+        api_key=existing_encrypted,
+        default_model="gpt-4o",
+        is_active=True,
+        is_multimodal=True,
+    )
+    mock_db.query().filter().first.return_value = mock_provider
+
+    # Update with is_multimodal=False
+    config = LLMProviderConfig(
+        id="p1",
+        provider_type=LLMProviderType.OPENAI,
+        name="Vision",
+        base_url="https://api.openai.com/v1",
+        api_key="********",
+        default_model="gpt-4o",
+        is_active=True,
+        is_multimodal=False,
+    )
+
+    updated = service.update_provider("p1", config)
+
+    assert updated.is_multimodal is False
+
+
+# endregion test_update_provider_preserves_is_multimodal
+
+
+# region test_llm_provider_config_multimodal_default [TYPE Function]
+# @RELATION: VERIFIES -> [LLMProviderConfig]
+# @PURPOSE: Verify LLMProviderConfig.is_multimodal defaults to False for schema stability.
+def test_llm_provider_config_multimodal_default():
+    """Verify default is_multimodal is False in schema."""
+    config = LLMProviderConfig(
+        provider_type=LLMProviderType.OPENAI,
+        name="Default Test",
+        base_url="https://api.openai.com/v1",
+        api_key="sk-test",
+        default_model="gpt-4",
+    )
+    assert config.is_multimodal is False
+
+
+# endregion test_llm_provider_config_multimodal_default
+
+
+# region test_llm_provider_config_multimodal_explicit [TYPE Function]
+# @RELATION: VERIFIES -> [LLMProviderConfig]
+# @PURPOSE: Verify LLMProviderConfig accepts explicit is_multimodal=True.
+def test_llm_provider_config_multimodal_explicit():
+    """Verify setting is_multimodal=True explicitly works."""
+    config = LLMProviderConfig(
+        provider_type=LLMProviderType.OPENAI,
+        name="Vision Test",
+        base_url="https://api.openai.com/v1",
+        api_key="sk-test",
+        default_model="gpt-4o",
+        is_multimodal=True,
+    )
+    assert config.is_multimodal is True

backend/src/services/llm_prompt_templates.py

@@ -131,7 +131,6 @@ def is_multimodal_model(model_name: str, provider_type: str | None = None) -> bo
     token = (model_name or "").strip().lower()
     if not token:
         return False
-    provider = (provider_type or "").strip().lower()
     text_only_markers = (
         "text-only",
         "embedding",
@@ -158,9 +157,7 @@ def is_multimodal_model(model_name: str, provider_type: str | None = None) -> bo
         "qwen-vl",
         "qwen2-vl",
     )
-    if any(marker in token for marker in multimodal_markers):
-        return True
-    return False
+    return any(marker in token for marker in multimodal_markers)
 # #endregion is_multimodal_model
 
 

backend/src/services/llm_provider.py

@@ -197,6 +197,7 @@ class LLMProviderService:
                 api_key=encrypted_key,
                 default_model=config.default_model,
                 is_active=config.is_active,
+                is_multimodal=config.is_multimodal,
             )
             self.db.add(db_provider)
             self.db.commit()
@@ -228,6 +229,7 @@ class LLMProviderService:
                 db_provider.api_key = self.encryption.encrypt(config.api_key)
             db_provider.default_model = config.default_model
             db_provider.is_active = config.is_active
+            db_provider.is_multimodal = config.is_multimodal
 
             self.db.commit()
             self.db.refresh(db_provider)