Merge branch 'refs/heads/main' into feat/workflow-parallel-support

# Conflicts:
#	api/core/app/apps/advanced_chat/app_generator.py
#	api/core/app/apps/advanced_chat/generate_task_pipeline.py
#	api/core/app/apps/workflow/app_runner.py
#	api/core/app/apps/workflow/generate_task_pipeline.py
#	api/core/app/task_pipeline/workflow_cycle_state_manager.py
#	api/core/workflow/entities/variable_pool.py
#	api/core/workflow/nodes/code/code_node.py
#	api/core/workflow/nodes/llm/llm_node.py
#	api/core/workflow/nodes/start/start_node.py
#	api/core/workflow/nodes/variable_assigner/__init__.py
#	api/tests/integration_tests/workflow/nodes/test_llm.py
#	api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py
#	api/tests/unit_tests/core/workflow/nodes/test_answer.py
#	api/tests/unit_tests/core/workflow/nodes/test_if_else.py
#	api/tests/unit_tests/core/workflow/nodes/test_variable_assigner.py

.gitignore

@@ -178,3 +178,4 @@ pyrightconfig.json
 api/.vscode
 
 .idea/
+.vscode

api/.env.example

@@ -267,4 +267,13 @@ APP_MAX_ACTIVE_REQUESTS=0
 
 
 # Celery beat configuration
-CELERY_BEAT_SCHEDULER_TIME=1
+CELERY_BEAT_SCHEDULER_TIME=1
+
+# Position configuration
+POSITION_TOOL_PINS=
+POSITION_TOOL_INCLUDES=
+POSITION_TOOL_EXCLUDES=
+
+POSITION_PROVIDER_PINS=
+POSITION_PROVIDER_INCLUDES=
+POSITION_PROVIDER_EXCLUDES=

api/.vscode/launch.json.example

@@ -5,8 +5,8 @@
             "name": "Python: Flask",
             "type": "debugpy",
             "request": "launch",
-            "python": "${workspaceFolder}/api/.venv/bin/python",
-            "cwd": "${workspaceFolder}/api",
+            "python": "${workspaceFolder}/.venv/bin/python",
+            "cwd": "${workspaceFolder}",
             "envFile": ".env",
             "module": "flask",
             "justMyCode": true,
@@ -18,15 +18,15 @@
             "args": [
                 "run",
                 "--host=0.0.0.0",
-                "--port=5001",
+                "--port=5001"
             ]
         },
         {
             "name": "Python: Celery",
             "type": "debugpy",
             "request": "launch",
-            "python": "${workspaceFolder}/api/.venv/bin/python",
-            "cwd": "${workspaceFolder}/api",
+            "python": "${workspaceFolder}/.venv/bin/python",
+            "cwd": "${workspaceFolder}",
             "module": "celery",
             "justMyCode": true,
             "envFile": ".env",

api/configs/app_config.py

@@ -37,6 +37,8 @@ class DifyConfig(
 
     CODE_MAX_NUMBER: int = 9223372036854775807
     CODE_MIN_NUMBER: int = -9223372036854775808
+    CODE_MAX_DEPTH: int = 5
+    CODE_MAX_PRECISION: int = 20
     CODE_MAX_STRING_LENGTH: int = 80000
     CODE_MAX_STRING_ARRAY_LENGTH: int = 30
     CODE_MAX_OBJECT_ARRAY_LENGTH: int = 30

api/configs/feature/__init__.py

@@ -406,6 +406,7 @@ class DataSetConfig(BaseSettings):
         default=False,
     )
 
+
 class WorkspaceConfig(BaseSettings):
     """
     Workspace configs
@@ -442,6 +443,63 @@ class CeleryBeatConfig(BaseSettings):
     )
 
 
+class PositionConfig(BaseSettings):
+
+    POSITION_PROVIDER_PINS: str = Field(
+        description='The heads of model providers',
+        default='',
+    )
+
+    POSITION_PROVIDER_INCLUDES: str = Field(
+        description='The included model providers',
+        default='',
+    )
+
+    POSITION_PROVIDER_EXCLUDES: str = Field(
+        description='The excluded model providers',
+        default='',
+    )
+
+    POSITION_TOOL_PINS: str = Field(
+        description='The heads of tools',
+        default='',
+    )
+
+    POSITION_TOOL_INCLUDES: str = Field(
+        description='The included tools',
+        default='',
+    )
+
+    POSITION_TOOL_EXCLUDES: str = Field(
+        description='The excluded tools',
+        default='',
+    )
+
+    @computed_field
+    def POSITION_PROVIDER_PINS_LIST(self) -> list[str]:
+        return [item.strip() for item in self.POSITION_PROVIDER_PINS.split(',') if item.strip() != '']
+
+    @computed_field
+    def POSITION_PROVIDER_INCLUDES_SET(self) -> set[str]:
+        return {item.strip() for item in self.POSITION_PROVIDER_INCLUDES.split(',') if item.strip() != ''}
+
+    @computed_field
+    def POSITION_PROVIDER_EXCLUDES_SET(self) -> set[str]:
+        return {item.strip() for item in self.POSITION_PROVIDER_EXCLUDES.split(',') if item.strip() != ''}
+
+    @computed_field
+    def POSITION_TOOL_PINS_LIST(self) -> list[str]:
+        return [item.strip() for item in self.POSITION_TOOL_PINS.split(',') if item.strip() != '']
+
+    @computed_field
+    def POSITION_TOOL_INCLUDES_SET(self) -> set[str]:
+        return {item.strip() for item in self.POSITION_TOOL_INCLUDES.split(',') if item.strip() != ''}
+
+    @computed_field
+    def POSITION_TOOL_EXCLUDES_SET(self) -> set[str]:
+        return {item.strip() for item in self.POSITION_TOOL_EXCLUDES.split(',') if item.strip() != ''}
+
+
 class FeatureConfig(
     # place the configs in alphabet order
     AppExecutionConfig,
@@ -466,6 +524,7 @@ class FeatureConfig(
     UpdateConfig,
     WorkflowConfig,
     WorkspaceConfig,
+    PositionConfig,
 
     # hosted services config
     HostedServiceConfig,

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description='Dify version',
-        default='0.7.0',
+        default='0.7.1',
     )
 
     COMMIT_SHA: str = Field(

api/controllers/console/app/app.py

@@ -61,6 +61,7 @@ class AppListApi(Resource):
         parser.add_argument('name', type=str, required=True, location='json')
         parser.add_argument('description', type=str, location='json')
         parser.add_argument('mode', type=str, choices=ALLOW_CREATE_APP_MODES, location='json')
+        parser.add_argument('icon_type', type=str, location='json')
         parser.add_argument('icon', type=str, location='json')
         parser.add_argument('icon_background', type=str, location='json')
         args = parser.parse_args()
@@ -94,6 +95,7 @@ class AppImportApi(Resource):
         parser.add_argument('data', type=str, required=True, nullable=False, location='json')
         parser.add_argument('name', type=str, location='json')
         parser.add_argument('description', type=str, location='json')
+        parser.add_argument('icon_type', type=str, location='json')
         parser.add_argument('icon', type=str, location='json')
         parser.add_argument('icon_background', type=str, location='json')
         args = parser.parse_args()
@@ -167,6 +169,7 @@ class AppApi(Resource):
         parser = reqparse.RequestParser()
         parser.add_argument('name', type=str, required=True, nullable=False, location='json')
         parser.add_argument('description', type=str, location='json')
+        parser.add_argument('icon_type', type=str, location='json')
         parser.add_argument('icon', type=str, location='json')
         parser.add_argument('icon_background', type=str, location='json')
         parser.add_argument('max_active_requests', type=int, location='json')
@@ -208,6 +211,7 @@ class AppCopyApi(Resource):
         parser = reqparse.RequestParser()
         parser.add_argument('name', type=str, location='json')
         parser.add_argument('description', type=str, location='json')
+        parser.add_argument('icon_type', type=str, location='json')
         parser.add_argument('icon', type=str, location='json')
         parser.add_argument('icon_background', type=str, location='json')
         args = parser.parse_args()

api/controllers/console/app/conversation.py

@@ -154,6 +154,8 @@ class ChatConversationApi(Resource):
         parser.add_argument('message_count_gte', type=int_range(1, 99999), required=False, location='args')
         parser.add_argument('page', type=int_range(1, 99999), required=False, default=1, location='args')
         parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
+        parser.add_argument('sort_by', type=str, choices=['created_at', '-created_at', 'updated_at', '-updated_at'],
+                            required=False, default='-updated_at', location='args')
         args = parser.parse_args()
 
         subquery = (
@@ -225,7 +227,17 @@ class ChatConversationApi(Resource):
         if app_model.mode == AppMode.ADVANCED_CHAT.value:
             query = query.where(Conversation.invoke_from != InvokeFrom.DEBUGGER.value)
 
-        query = query.order_by(Conversation.created_at.desc())
+        match args['sort_by']:
+            case 'created_at':
+                query = query.order_by(Conversation.created_at.asc())
+            case '-created_at':
+                query = query.order_by(Conversation.created_at.desc())
+            case 'updated_at':
+                query = query.order_by(Conversation.updated_at.asc())
+            case '-updated_at':
+                query = query.order_by(Conversation.updated_at.desc())
+            case _:
+                query = query.order_by(Conversation.created_at.desc())
 
         conversations = db.paginate(
             query,

api/controllers/console/app/site.py

@@ -16,6 +16,7 @@ from models.model import Site
 def parse_app_site_args():
     parser = reqparse.RequestParser()
     parser.add_argument('title', type=str, required=False, location='json')
+    parser.add_argument('icon_type', type=str, required=False, location='json')
     parser.add_argument('icon', type=str, required=False, location='json')
     parser.add_argument('icon_background', type=str, required=False, location='json')
     parser.add_argument('description', type=str, required=False, location='json')
@@ -53,6 +54,7 @@ class AppSite(Resource):
 
         for attr_name in [
             'title',
+            'icon_type',
             'icon',
             'icon_background',
             'description',

api/controllers/console/app/workflow.py

@@ -460,6 +460,7 @@ class ConvertToWorkflowApi(Resource):
         if request.data:
             parser = reqparse.RequestParser()
             parser.add_argument('name', type=str, required=False, nullable=True, location='json')
+            parser.add_argument('icon_type', type=str, required=False, nullable=True, location='json')
             parser.add_argument('icon', type=str, required=False, nullable=True, location='json')
             parser.add_argument('icon_background', type=str, required=False, nullable=True, location='json')
             args = parser.parse_args()

api/controllers/console/datasets/datasets.py

@@ -573,13 +573,13 @@ class DatasetRetrievalSettingMockApi(Resource):
     @account_initialization_required
     def get(self, vector_type):
         match vector_type:
-            case VectorType.MILVUS | VectorType.RELYT | VectorType.PGVECTOR | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCENT:
+            case VectorType.MILVUS | VectorType.RELYT | VectorType.TIDB_VECTOR | VectorType.CHROMA | VectorType.TENCENT | VectorType.PGVECTO_RS:
                 return {
                     'retrieval_method': [
                         RetrievalMethod.SEMANTIC_SEARCH.value
                     ]
                 }
-            case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH| VectorType.ANALYTICDB | VectorType.MYSCALE | VectorType.ORACLE | VectorType.ELASTICSEARCH:
+            case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH | VectorType.ANALYTICDB | VectorType.MYSCALE | VectorType.ORACLE | VectorType.ELASTICSEARCH | VectorType.PGVECTOR:
                 return {
                     'retrieval_method': [
                         RetrievalMethod.SEMANTIC_SEARCH.value,

api/controllers/service_api/app/conversation.py

@@ -25,6 +25,8 @@ class ConversationApi(Resource):
         parser = reqparse.RequestParser()
         parser.add_argument('last_id', type=uuid_value, location='args')
         parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
+        parser.add_argument('sort_by', type=str, choices=['created_at', '-created_at', 'updated_at', '-updated_at'],
+                            required=False, default='-updated_at', location='args')
         args = parser.parse_args()
 
         try:
@@ -33,7 +35,8 @@ class ConversationApi(Resource):
                 user=end_user,
                 last_id=args['last_id'],
                 limit=args['limit'],
-                invoke_from=InvokeFrom.SERVICE_API
+                invoke_from=InvokeFrom.SERVICE_API,
+                sort_by=args['sort_by']
             )
         except services.errors.conversation.LastConversationNotExistsError:
             raise NotFound("Last Conversation Not Exists.")

api/controllers/service_api/dataset/segment.py

@@ -53,19 +53,22 @@ class SegmentApi(DatasetApiResource):
                 raise ProviderNotInitializeError(
                     "No Embedding Model available. Please configure a valid provider "
                     "in the Settings -> Model Provider.")
-            except ProviderTokenNotInitError as ex:
+            except ProviderTokenNotInitError as ex:   
                 raise ProviderNotInitializeError(ex.description)
         # validate args
         parser = reqparse.RequestParser()
         parser.add_argument('segments', type=list, required=False, nullable=True, location='json')
         args = parser.parse_args()
-        for args_item in args['segments']:
-            SegmentService.segment_create_args_validate(args_item, document)
-        segments = SegmentService.multi_create_segment(args['segments'], document, dataset)
-        return {
-            'data': marshal(segments, segment_fields),
-            'doc_form': document.doc_form
-        }, 200
+        if args['segments'] is not None:
+            for args_item in args['segments']:
+                SegmentService.segment_create_args_validate(args_item, document)
+            segments = SegmentService.multi_create_segment(args['segments'], document, dataset)
+            return {
+                'data': marshal(segments, segment_fields),
+                'doc_form': document.doc_form
+            }, 200
+        else:
+            return {"error": "Segemtns is required"}, 400
 
     def get(self, tenant_id, dataset_id, document_id):
         """Create single segment."""

api/controllers/web/conversation.py

@@ -26,6 +26,8 @@ class ConversationListApi(WebApiResource):
         parser.add_argument('last_id', type=uuid_value, location='args')
         parser.add_argument('limit', type=int_range(1, 100), required=False, default=20, location='args')
         parser.add_argument('pinned', type=str, choices=['true', 'false', None], location='args')
+        parser.add_argument('sort_by', type=str, choices=['created_at', '-created_at', 'updated_at', '-updated_at'],
+                            required=False, default='-updated_at', location='args')
         args = parser.parse_args()
 
         pinned = None
@@ -40,6 +42,7 @@ class ConversationListApi(WebApiResource):
                 limit=args['limit'],
                 invoke_from=InvokeFrom.WEB_APP,
                 pinned=pinned,
+                sort_by=args['sort_by']
             )
         except LastConversationNotExistsError:
             raise NotFound("Last Conversation Not Exists.")

api/controllers/web/site.py

@@ -6,6 +6,7 @@ from configs import dify_config
 from controllers.web import api
 from controllers.web.wraps import WebApiResource
 from extensions.ext_database import db
+from libs.helper import AppIconUrlField
 from models.account import TenantStatus
 from models.model import Site
 from services.feature_service import FeatureService
@@ -28,8 +29,10 @@ class AppSiteApi(WebApiResource):
         'title': fields.String,
         'chat_color_theme': fields.String,
         'chat_color_theme_inverted': fields.Boolean,
+        'icon_type': fields.String,
         'icon': fields.String,
         'icon_background': fields.String,
+        'icon_url': AppIconUrlField,
         'description': fields.String,
         'copyright': fields.String,
         'privacy_policy': fields.String,

api/core/agent/base_agent_runner.py

@@ -64,15 +64,19 @@ class BaseAgentRunner(AppRunner):
         """
         Agent runner
         :param tenant_id: tenant id
+        :param application_generate_entity: application generate entity
+        :param conversation: conversation
         :param app_config: app generate entity
         :param model_config: model config
         :param config: dataset config
         :param queue_manager: queue manager
         :param message: message
         :param user_id: user id
-        :param agent_llm_callback: agent llm callback
-        :param callback: callback
         :param memory: memory
+        :param prompt_messages: prompt messages
+        :param variables_pool: variables pool
+        :param db_variables: db variables
+        :param model_instance: model instance
         """
         self.tenant_id = tenant_id
         self.application_generate_entity = application_generate_entity
@@ -445,7 +449,7 @@ class BaseAgentRunner(AppRunner):
                         try:
                             tool_responses = json.loads(agent_thought.observation)
                         except Exception as e:
-                            tool_responses = { tool: agent_thought.observation for tool in tools }
+                            tool_responses = dict.fromkeys(tools, agent_thought.observation)
 
                         for tool in tools:
                             # generate a uuid for tool call

api/core/agent/cot_agent_runner.py

@@ -292,6 +292,8 @@ class CotAgentRunner(BaseAgentRunner, ABC):
         handle invoke action
         :param action: action
         :param tool_instances: tool instances
+        :param message_file_ids: message file ids
+        :param trace_manager: trace manager
         :return: observation, meta
         """
         # action is tool call, invoke tool

api/core/app/app_config/easy_ui_based_app/dataset/manager.py

@@ -93,7 +93,7 @@ class DatasetConfigManager:
                     reranking_model=dataset_configs.get('reranking_model'),
                     weights=dataset_configs.get('weights'),
                     reranking_enabled=dataset_configs.get('reranking_enabled', True),
-                    rerank_mode=dataset_configs["reranking_mode"],
+                    rerank_mode=dataset_configs.get('rerank_mode', 'reranking_model'),
                 )
             )
 

api/core/app/app_config/easy_ui_based_app/variables/manager.py

@@ -1,6 +1,6 @@
 import re
 
-from core.app.app_config.entities import ExternalDataVariableEntity, VariableEntity
+from core.app.app_config.entities import ExternalDataVariableEntity, VariableEntity, VariableEntityType
 from core.external_data_tool.factory import ExternalDataToolFactory
 
 
@@ -13,7 +13,7 @@ class BasicVariablesConfigManager:
         :param config: model config args
         """
         external_data_variables = []
-        variables = []
+        variable_entities = []
 
         # old external_data_tools
         external_data_tools = config.get('external_data_tools', [])
@@ -30,50 +30,41 @@ class BasicVariablesConfigManager:
             )
 
         # variables and external_data_tools
-        for variable in config.get('user_input_form', []):
-            typ = list(variable.keys())[0]
-            if typ == 'external_data_tool':
-                val = variable[typ]
-                if 'config' not in val:
+        for variables in config.get('user_input_form', []):
+            variable_type = list(variables.keys())[0]
+            if variable_type == VariableEntityType.EXTERNAL_DATA_TOOL:
+                variable = variables[variable_type]
+                if 'config' not in variable:
                     continue
 
                 external_data_variables.append(
                     ExternalDataVariableEntity(
-                        variable=val['variable'],
-                        type=val['type'],
-                        config=val['config']
+                        variable=variable['variable'],
+                        type=variable['type'],
+                        config=variable['config']
                     )
                 )
-            elif typ in [
-                VariableEntity.Type.TEXT_INPUT.value,
-                VariableEntity.Type.PARAGRAPH.value,
-                VariableEntity.Type.NUMBER.value,
+            elif variable_type in [
+                VariableEntityType.TEXT_INPUT,
+                VariableEntityType.PARAGRAPH,
+                VariableEntityType.NUMBER,
+                VariableEntityType.SELECT,
             ]:
-                variables.append(
+                variable = variables[variable_type]
+                variable_entities.append(
                     VariableEntity(
-                        type=VariableEntity.Type.value_of(typ),
-                        variable=variable[typ].get('variable'),
-                        description=variable[typ].get('description'),
-                        label=variable[typ].get('label'),
-                        required=variable[typ].get('required', False),
-                        max_length=variable[typ].get('max_length'),
-                        default=variable[typ].get('default'),
-                    )
-                )
-            elif typ == VariableEntity.Type.SELECT.value:
-                variables.append(
-                    VariableEntity(
-                        type=VariableEntity.Type.SELECT,
-                        variable=variable[typ].get('variable'),
-                        description=variable[typ].get('description'),
-                        label=variable[typ].get('label'),
-                        required=variable[typ].get('required', False),
-                        options=variable[typ].get('options'),
-                        default=variable[typ].get('default'),
+                        type=variable_type,
+                        variable=variable.get('variable'),
+                        description=variable.get('description'),
+                        label=variable.get('label'),
+                        required=variable.get('required', False),
+                        max_length=variable.get('max_length'),
+                        options=variable.get('options'),
+                        default=variable.get('default'),
                     )
                 )
 
-        return variables, external_data_variables
+        return variable_entities, external_data_variables
 
     @classmethod
     def validate_and_set_defaults(cls, tenant_id: str, config: dict) -> tuple[dict, list[str]]:
@@ -183,4 +174,4 @@ class BasicVariablesConfigManager:
                 config=config
             )
 
-        return config, ["external_data_tools"]
+        return config, ["external_data_tools"]

api/core/app/app_config/entities.py

@@ -82,43 +82,29 @@ class PromptTemplateEntity(BaseModel):
     advanced_completion_prompt_template: Optional[AdvancedCompletionPromptTemplateEntity] = None
 
 
+class VariableEntityType(str, Enum):
+    TEXT_INPUT = "text-input"
+    SELECT = "select"
+    PARAGRAPH = "paragraph"
+    NUMBER = "number"
+    EXTERNAL_DATA_TOOL = "external-data-tool"
+
+
 class VariableEntity(BaseModel):
     """
     Variable Entity.
     """
-    class Type(Enum):
-        TEXT_INPUT = 'text-input'
-        SELECT = 'select'
-        PARAGRAPH = 'paragraph'
-        NUMBER = 'number'
-
-        @classmethod
-        def value_of(cls, value: str) -> 'VariableEntity.Type':
-            """
-            Get value of given mode.
-
-            :param value: mode value
-            :return: mode
-            """
-            for mode in cls:
-                if mode.value == value:
-                    return mode
-            raise ValueError(f'invalid variable type value {value}')
 
     variable: str
     label: str
     description: Optional[str] = None
-    type: Type
+    type: VariableEntityType
     required: bool = False
     max_length: Optional[int] = None
     options: Optional[list[str]] = None
     default: Optional[str] = None
     hint: Optional[str] = None
 
-    @property
-    def name(self) -> str:
-        return self.variable
-
 
 class ExternalDataVariableEntity(BaseModel):
     """
@@ -252,4 +238,4 @@ class WorkflowUIBasedAppConfig(AppConfig):
     """
     Workflow UI Based App Config Entity.
     """
-    workflow_id: str
+    workflow_id: str

api/core/app/apps/advanced_chat/app_generator.py

@@ -23,6 +23,8 @@ from core.app.entities.task_entities import ChatbotAppBlockingResponse, ChatbotA
 from core.file.message_file_parser import MessageFileParser
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
 from core.ops.ops_trace_manager import TraceQueueManager
+from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.enums import SystemVariableKey
 from extensions.ext_database import db
 from models.account import Account
 from models.model import App, Conversation, EndUser, Message
@@ -67,8 +69,9 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
 
         # get conversation
         conversation = None
-        if args.get('conversation_id'):
-            conversation = self._get_conversation_by_user(app_model, args.get('conversation_id', ''), user)
+        conversation_id = args.get('conversation_id')
+        if conversation_id:
+            conversation = self._get_conversation_by_user(app_model=app_model, conversation_id=conversation_id, user=user)
 
         # parse files
         files = args['files'] if args.get('files') else []
@@ -225,6 +228,62 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             message_id=message.id
         )
 
+        # Init conversation variables
+        stmt = select(ConversationVariable).where(
+            ConversationVariable.app_id == conversation.app_id, ConversationVariable.conversation_id == conversation.id
+        )
+        with Session(db.engine) as session:
+            conversation_variables = session.scalars(stmt).all()
+            if not conversation_variables:
+                # Create conversation variables if they don't exist.
+                conversation_variables = [
+                    ConversationVariable.from_variable(
+                        app_id=conversation.app_id, conversation_id=conversation.id, variable=variable
+                    )
+                    for variable in workflow.conversation_variables
+                ]
+                session.add_all(conversation_variables)
+            # Convert database entities to variables.
+            conversation_variables = [item.to_variable() for item in conversation_variables]
+
+            session.commit()
+
+            # Increment dialogue count.
+            conversation.dialogue_count += 1
+
+            conversation_id = conversation.id
+            conversation_dialogue_count = conversation.dialogue_count
+            db.session.commit()
+            db.session.refresh(conversation)
+
+        inputs = application_generate_entity.inputs
+        query = application_generate_entity.query
+        files = application_generate_entity.files
+
+        user_id = None
+        if application_generate_entity.invoke_from in [InvokeFrom.WEB_APP, InvokeFrom.SERVICE_API]:
+            end_user = db.session.query(EndUser).filter(EndUser.id == application_generate_entity.user_id).first()
+            if end_user:
+                user_id = end_user.session_id
+        else:
+            user_id = application_generate_entity.user_id
+
+        # Create a variable pool.
+        system_inputs = {
+            SystemVariableKey.QUERY: query,
+            SystemVariableKey.FILES: files,
+            SystemVariableKey.CONVERSATION_ID: conversation_id,
+            SystemVariableKey.USER_ID: user_id,
+            SystemVariableKey.DIALOGUE_COUNT: conversation_dialogue_count,
+        }
+        variable_pool = VariablePool(
+            system_variables=system_inputs,
+            user_inputs=inputs,
+            environment_variables=workflow.environment_variables,
+            conversation_variables=conversation_variables,
+        )
+        contexts.workflow_variable_pool.set(variable_pool)
+
         # new thread
         worker_thread = threading.Thread(target=self._generate_worker, kwargs={
             'flask_app': current_app._get_current_object(), # type: ignore
@@ -296,7 +355,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 logger.exception("Validation Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
             except (ValueError, InvokeError) as e:
-                if os.environ.get("DEBUG") and os.environ.get("DEBUG", "false").lower() == 'true':
+                if os.environ.get("DEBUG", "false").lower() == 'true':
                     logger.exception("Error when generating")
                 queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
             except Exception as e:

api/core/app/apps/advanced_chat/generate_task_pipeline.py

@@ -47,7 +47,7 @@ from core.app.task_pipeline.message_cycle_manage import MessageCycleManage
 from core.app.task_pipeline.workflow_cycle_manage import WorkflowCycleManage
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
 from events.message_event import message_was_created
 from extensions.ext_database import db
@@ -69,7 +69,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
     _application_generate_entity: AdvancedChatAppGenerateEntity
     _workflow: Workflow
     _user: Union[Account, EndUser]
-    _workflow_system_variables: dict[SystemVariable, Any]
+    _workflow_system_variables: dict[SystemVariableKey, Any]
 
     def __init__(
             self,
@@ -102,10 +102,10 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         self._conversation = conversation
         self._message = message
         self._workflow_system_variables = {
-            SystemVariable.QUERY: message.query,
-            SystemVariable.FILES: application_generate_entity.files,
-            SystemVariable.CONVERSATION_ID: conversation.id,
-            SystemVariable.USER_ID: user_id,
+            SystemVariableKey.QUERY: message.query,
+            SystemVariableKey.FILES: application_generate_entity.files,
+            SystemVariableKey.CONVERSATION_ID: conversation.id,
+            SystemVariableKey.USER_ID: user_id,
         }
 
         self._task_state = WorkflowTaskState()
@@ -312,7 +312,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueParallelBranchRunStartedEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_parallel_branch_start_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -321,7 +321,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueParallelBranchRunSucceededEvent | QueueParallelBranchRunFailedEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_parallel_branch_finished_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,

api/core/app/apps/base_app_generator.py

@@ -1,7 +1,7 @@
 from collections.abc import Mapping
 from typing import Any, Optional
 
-from core.app.app_config.entities import AppConfig, VariableEntity
+from core.app.app_config.entities import AppConfig, VariableEntity, VariableEntityType
 
 
 class BaseAppGenerator:
@@ -9,29 +9,29 @@ class BaseAppGenerator:
         user_inputs = user_inputs or {}
         # Filter input variables from form configuration, handle required fields, default values, and option values
         variables = app_config.variables
-        filtered_inputs = {var.name: self._validate_input(inputs=user_inputs, var=var) for var in variables}
+        filtered_inputs = {var.variable: self._validate_input(inputs=user_inputs, var=var) for var in variables}
         filtered_inputs = {k: self._sanitize_value(v) for k, v in filtered_inputs.items()}
         return filtered_inputs
 
     def _validate_input(self, *, inputs: Mapping[str, Any], var: VariableEntity):
-        user_input_value = inputs.get(var.name)
+        user_input_value = inputs.get(var.variable)
         if var.required and not user_input_value:
-            raise ValueError(f'{var.name} is required in input form')
+            raise ValueError(f'{var.variable} is required in input form')
         if not var.required and not user_input_value:
             # TODO: should we return None here if the default value is None?
             return var.default or ''
         if (
             var.type
             in (
-                VariableEntity.Type.TEXT_INPUT,
-                VariableEntity.Type.SELECT,
-                VariableEntity.Type.PARAGRAPH,
+                VariableEntityType.TEXT_INPUT,
+                VariableEntityType.SELECT,
+                VariableEntityType.PARAGRAPH,
             )
             and user_input_value
             and not isinstance(user_input_value, str)
         ):
-            raise ValueError(f"(type '{var.type}') {var.name} in input form must be a string")
-        if var.type == VariableEntity.Type.NUMBER and isinstance(user_input_value, str):
+            raise ValueError(f"(type '{var.type}') {var.variable} in input form must be a string")
+        if var.type == VariableEntityType.NUMBER and isinstance(user_input_value, str):
             # may raise ValueError if user_input_value is not a valid number
             try:
                 if '.' in user_input_value:
@@ -39,14 +39,14 @@ class BaseAppGenerator:
                 else:
                     return int(user_input_value)
             except ValueError:
-                raise ValueError(f"{var.name} in input form must be a valid number")
-        if var.type == VariableEntity.Type.SELECT:
+                raise ValueError(f"{var.variable} in input form must be a valid number")
+        if var.type == VariableEntityType.SELECT:
             options = var.options or []
             if user_input_value not in options:
-                raise ValueError(f'{var.name} in input form must be one of the following: {options}')
-        elif var.type in (VariableEntity.Type.TEXT_INPUT, VariableEntity.Type.PARAGRAPH):
+                raise ValueError(f'{var.variable} in input form must be one of the following: {options}')
+        elif var.type in (VariableEntityType.TEXT_INPUT, VariableEntityType.PARAGRAPH):
             if var.max_length and user_input_value and len(user_input_value) > var.max_length:
-                raise ValueError(f'{var.name} in input form must be less than {var.max_length} characters')
+                raise ValueError(f'{var.variable} in input form must be less than {var.max_length} characters')
 
         return user_input_value
 

api/core/app/apps/base_app_runner.py

@@ -256,6 +256,7 @@ class AppRunner:
         :param invoke_result: invoke result
         :param queue_manager: application queue manager
         :param stream: stream
+        :param agent: agent
         :return:
         """
         if not stream:
@@ -278,6 +279,7 @@ class AppRunner:
         Handle invoke result direct
         :param invoke_result: invoke result
         :param queue_manager: application queue manager
+        :param agent: agent
         :return:
         """
         queue_manager.publish(
@@ -293,6 +295,7 @@ class AppRunner:
         Handle invoke result
         :param invoke_result: invoke result
         :param queue_manager: application queue manager
+        :param agent: agent
         :return:
         """
         model = None

api/core/app/apps/message_based_app_generator.py

@@ -1,6 +1,7 @@
 import json
 import logging
 from collections.abc import Generator
+from datetime import datetime, timezone
 from typing import Optional, Union
 
 from sqlalchemy import and_
@@ -36,17 +37,17 @@ logger = logging.getLogger(__name__)
 class MessageBasedAppGenerator(BaseAppGenerator):
 
     def _handle_response(
-        self, application_generate_entity: Union[
-            ChatAppGenerateEntity,
-            CompletionAppGenerateEntity,
-            AgentChatAppGenerateEntity,
-            AdvancedChatAppGenerateEntity
-        ],
-        queue_manager: AppQueueManager,
-        conversation: Conversation,
-        message: Message,
-        user: Union[Account, EndUser],
-        stream: bool = False,
+            self, application_generate_entity: Union[
+                ChatAppGenerateEntity,
+                CompletionAppGenerateEntity,
+                AgentChatAppGenerateEntity,
+                AdvancedChatAppGenerateEntity
+            ],
+            queue_manager: AppQueueManager,
+            conversation: Conversation,
+            message: Message,
+            user: Union[Account, EndUser],
+            stream: bool = False,
     ) -> Union[
         ChatbotAppBlockingResponse,
         CompletionAppBlockingResponse,
@@ -138,6 +139,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
         """
         Initialize generate records
         :param application_generate_entity: application generate entity
+        :conversation conversation
         :return:
         """
         app_config = application_generate_entity.app_config
@@ -192,6 +194,9 @@ class MessageBasedAppGenerator(BaseAppGenerator):
             db.session.add(conversation)
             db.session.commit()
             db.session.refresh(conversation)
+        else:
+            conversation.updated_at = datetime.now(timezone.utc).replace(tzinfo=None)
+            db.session.commit()
 
         message = Message(
             app_id=app_config.app_id,

api/core/app/apps/workflow/app_runner.py

@@ -13,7 +13,7 @@ from core.app.entities.app_invoke_entities import (
 from core.workflow.callbacks.base_workflow_callback import WorkflowCallback
 from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
 from models.model import App, EndUser
@@ -79,14 +79,14 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
                 user_inputs=self.application_generate_entity.single_iteration_run.inputs
             )
         else:
-        
+
             inputs = self.application_generate_entity.inputs
             files = self.application_generate_entity.files
-        
+
             # Create a variable pool.
             system_inputs = {
-                SystemVariable.FILES: files,
-                SystemVariable.USER_ID: user_id,
+                SystemVariableKey.FILES: files,
+                SystemVariableKey.USER_ID: user_id,
             }
 
             variable_pool = VariablePool(
@@ -98,7 +98,7 @@ class WorkflowAppRunner(WorkflowBasedAppRunner):
 
             # init graph
             graph = self._init_graph(graph_config=workflow.graph_dict)
-        
+
         # RUN WORKFLOW
         workflow_entry = WorkflowEntry(
             tenant_id=workflow.tenant_id,

api/core/app/apps/workflow/generate_task_pipeline.py

@@ -41,7 +41,9 @@ from core.app.entities.task_entities import (
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
 from core.app.task_pipeline.workflow_cycle_manage import WorkflowCycleManage
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.workflow.enums import SystemVariable
+from core.workflow.entities.node_entities import NodeType
+from core.workflow.enums import SystemVariableKey
+from core.workflow.nodes.end.end_node import EndNode
 from extensions.ext_database import db
 from models.account import Account
 from models.model import EndUser
@@ -64,7 +66,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
     _user: Union[Account, EndUser]
     _task_state: WorkflowTaskState
     _application_generate_entity: WorkflowAppGenerateEntity
-    _workflow_system_variables: dict[SystemVariable, Any]
+    _workflow_system_variables: dict[SystemVariableKey, Any]
 
     def __init__(self, application_generate_entity: WorkflowAppGenerateEntity,
                  workflow: Workflow,
@@ -88,8 +90,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
 
         self._workflow = workflow
         self._workflow_system_variables = {
-            SystemVariable.FILES: application_generate_entity.files,
-            SystemVariable.USER_ID: user_id
+            SystemVariableKey.FILES: application_generate_entity.files,
+            SystemVariableKey.USER_ID: user_id
         }
 
         self._task_state = WorkflowTaskState()

api/core/helper/code_executor/code_executor.py

@@ -4,7 +4,7 @@ from enum import Enum
 from threading import Lock
 from typing import Literal, Optional
 
-from httpx import get, post
+from httpx import Timeout, get, post
 from pydantic import BaseModel
 from yarl import URL
 
@@ -21,7 +21,7 @@ logger = logging.getLogger(__name__)
 CODE_EXECUTION_ENDPOINT = dify_config.CODE_EXECUTION_ENDPOINT
 CODE_EXECUTION_API_KEY = dify_config.CODE_EXECUTION_API_KEY
 
-CODE_EXECUTION_TIMEOUT = (10, 60)
+CODE_EXECUTION_TIMEOUT = Timeout(connect=10, write=10, read=60, pool=None)
 
 class CodeExecutionException(Exception):
     pass
@@ -116,7 +116,7 @@ class CodeExecutor:
         if response.data.error:
             raise CodeExecutionException(response.data.error)
         
-        return response.data.stdout
+        return response.data.stdout or ''
 
     @classmethod
     def execute_workflow_code_template(cls, language: CodeLanguage, code: str, inputs: dict, dependencies: Optional[list[CodeDependency]] = None) -> dict:

api/core/helper/code_executor/python3/python3_code_provider.py

@@ -13,7 +13,7 @@ class Python3CodeProvider(CodeNodeProvider):
     def get_default_code(cls) -> str:
         return dedent(
             """
-            def main(arg1: int, arg2: int) -> dict:
+            def main(arg1: str, arg2: str) -> dict:
                 return {
                     "result": arg1 + arg2,
                 }

api/core/helper/position_helper.py

@@ -3,6 +3,7 @@ from collections import OrderedDict
 from collections.abc import Callable
 from typing import Any
 
+from configs import dify_config
 from core.tools.utils.yaml_utils import load_yaml_file
 
 
@@ -19,6 +20,87 @@ def get_position_map(folder_path: str, *, file_name: str = "_position.yaml") ->
     return {name: index for index, name in enumerate(positions)}
 
 
+def get_tool_position_map(folder_path: str, file_name: str = "_position.yaml") -> dict[str, int]:
+    """
+    Get the mapping for tools from name to index from a YAML file.
+    :param folder_path:
+    :param file_name: the YAML file name, default to '_position.yaml'
+    :return: a dict with name as key and index as value
+    """
+    position_map = get_position_map(folder_path, file_name=file_name)
+
+    return pin_position_map(
+        position_map,
+        pin_list=dify_config.POSITION_TOOL_PINS_LIST,
+    )
+
+
+def get_provider_position_map(folder_path: str, file_name: str = "_position.yaml") -> dict[str, int]:
+    """
+    Get the mapping for providers from name to index from a YAML file.
+    :param folder_path:
+    :param file_name: the YAML file name, default to '_position.yaml'
+    :return: a dict with name as key and index as value
+    """
+    position_map = get_position_map(folder_path, file_name=file_name)
+    return pin_position_map(
+        position_map,
+        pin_list=dify_config.POSITION_PROVIDER_PINS_LIST,
+    )
+
+
+def pin_position_map(original_position_map: dict[str, int], pin_list: list[str]) -> dict[str, int]:
+    """
+    Pin the items in the pin list to the beginning of the position map.
+    Overall logic: exclude > include > pin
+    :param position_map: the position map to be sorted and filtered
+    :param pin_list: the list of pins to be put at the beginning
+    :return: the sorted position map
+    """
+    positions = sorted(original_position_map.keys(), key=lambda x: original_position_map[x])
+
+    # Add pins to position map
+    position_map = {name: idx for idx, name in enumerate(pin_list)}
+
+    # Add remaining positions to position map
+    start_idx = len(position_map)
+    for name in positions:
+        if name not in position_map:
+            position_map[name] = start_idx
+            start_idx += 1
+
+    return position_map
+
+
+def is_filtered(
+        include_set: set[str],
+        exclude_set: set[str],
+        data: Any,
+        name_func: Callable[[Any], str],
+) -> bool:
+    """
+    Chcek if the object should be filtered out.
+    Overall logic: exclude > include > pin
+    :param include_set: the set of names to be included
+    :param exclude_set: the set of names to be excluded
+    :param name_func: the function to get the name of the object
+    :param data: the data to be filtered
+    :return: True if the object should be filtered out, False otherwise
+    """
+    if not data:
+        return False
+    if not include_set and not exclude_set:
+        return False
+
+    name = name_func(data)
+
+    if name in exclude_set:  # exclude_set is prioritized
+        return True
+    if include_set and name not in include_set:  # filter out only if include_set is not empty
+        return True
+    return False
+
+
 def sort_by_position_map(
         position_map: dict[str, int],
         data: list[Any],

api/core/indexing_runner.py

@@ -700,6 +700,7 @@ class IndexingRunner:
                 DatasetDocument.tokens: tokens,
                 DatasetDocument.completed_at: datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None),
                 DatasetDocument.indexing_latency: indexing_end_at - indexing_start_at,
+                DatasetDocument.error: None,
             }
         )
 

api/core/model_manager.py

@@ -271,9 +271,8 @@ class ModelInstance:
 
         :param content_text: text content to be translated
         :param tenant_id: user tenant id
-        :param user: unique user id
         :param voice: model timbre
-        :param streaming: output is streaming
+        :param user: unique user id
         :return: text for given audio file
         """
         if not isinstance(self.model_type_instance, TTSModel):
@@ -369,6 +368,15 @@ class ModelManager:
 
         return ModelInstance(provider_model_bundle, model)
 
+    def get_default_provider_model_name(self, tenant_id: str, model_type: ModelType) -> tuple[str, str]:
+        """
+        Return first provider and the first model in the provider
+        :param tenant_id: tenant id
+        :param model_type: model type
+        :return: provider name, model name
+        """
+        return self._provider_manager.get_first_provider_first_model(tenant_id, model_type)
+
     def get_default_model_instance(self, tenant_id: str, model_type: ModelType) -> ModelInstance:
         """
         Get default model instance
@@ -401,6 +409,10 @@ class LBModelManager:
                  managed_credentials: Optional[dict] = None) -> None:
         """
         Load balancing model manager
+        :param tenant_id: tenant_id
+        :param provider: provider
+        :param model_type: model_type
+        :param model: model name
         :param load_balancing_configs: all load balancing configurations
         :param managed_credentials: credentials if load balancing configuration name is __inherit__
         """
@@ -499,7 +511,6 @@ class LBModelManager:
             config.id
         )
 
-
         res = redis_client.exists(cooldown_cache_key)
         res = cast(bool, res)
         return res

api/core/model_runtime/model_providers/__base/ai_model.py

@@ -151,9 +151,9 @@ class AIModel(ABC):
             os.path.join(provider_model_type_path, model_schema_yaml)
             for model_schema_yaml in os.listdir(provider_model_type_path)
             if not model_schema_yaml.startswith('__')
-               and not model_schema_yaml.startswith('_')
-               and os.path.isfile(os.path.join(provider_model_type_path, model_schema_yaml))
-               and model_schema_yaml.endswith('.yaml')
+            and not model_schema_yaml.startswith('_')
+            and os.path.isfile(os.path.join(provider_model_type_path, model_schema_yaml))
+            and model_schema_yaml.endswith('.yaml')
         ]
 
         # get _position.yaml file path

api/core/model_runtime/model_providers/__base/large_language_model.py

@@ -185,7 +185,7 @@ if you are not sure about the structure.
                 stream=stream,
                 user=user
             )
-        
+
         model_parameters.pop("response_format")
         stop = stop or []
         stop.extend(["\n```", "```\n"])
@@ -249,10 +249,10 @@ if you are not sure about the structure.
                     prompt_messages=prompt_messages,
                     input_generator=new_generator()
                 )
-            
+
         return response
 
-    def _code_block_mode_stream_processor(self, model: str, prompt_messages: list[PromptMessage], 
+    def _code_block_mode_stream_processor(self, model: str, prompt_messages: list[PromptMessage],
                                           input_generator: Generator[LLMResultChunk, None, None]
                                         ) -> Generator[LLMResultChunk, None, None]:
         """
@@ -310,7 +310,7 @@ if you are not sure about the structure.
                     )
                 )
 
-    def _code_block_mode_stream_processor_with_backtick(self, model: str, prompt_messages: list, 
+    def _code_block_mode_stream_processor_with_backtick(self, model: str, prompt_messages: list,
                                         input_generator:  Generator[LLMResultChunk, None, None]) \
                                     ->  Generator[LLMResultChunk, None, None]:
         """
@@ -470,7 +470,7 @@ if you are not sure about the structure.
         :return: full response or stream response chunk generator result
         """
         raise NotImplementedError
-    
+
     @abstractmethod
     def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
                        tools: Optional[list[PromptMessageTool]] = None) -> int:
@@ -792,6 +792,13 @@ if you are not sure about the structure.
                 if not isinstance(parameter_value, str):
                     raise ValueError(f"Model Parameter {parameter_name} should be string.")
 
+                # validate options
+                if parameter_rule.options and parameter_value not in parameter_rule.options:
+                    raise ValueError(f"Model Parameter {parameter_name} should be one of {parameter_rule.options}.")
+            elif parameter_rule.type == ParameterType.TEXT:
+                if not isinstance(parameter_value, str):
+                    raise ValueError(f"Model Parameter {parameter_name} should be text.")
+
                 # validate options
                 if parameter_rule.options and parameter_value not in parameter_rule.options:
                     raise ValueError(f"Model Parameter {parameter_name} should be one of {parameter_rule.options}.")

api/core/model_runtime/model_providers/azure_openai/tts/tts.py

@@ -70,7 +70,7 @@ class AzureOpenAIText2SpeechModel(_CommonAzureOpenAI, TTSModel):
             # doc: https://platform.openai.com/docs/guides/text-to-speech
             credentials_kwargs = self._to_credential_kwargs(credentials)
             client = AzureOpenAI(**credentials_kwargs)
-            # max font is 4096,there is 3500 limit for each request
+            # max length is 4096 characters, there is 3500 limit for each request
             max_length = 3500
             if len(content_text) > max_length:
                 sentences = self._split_text_into_sentences(content_text, max_length=max_length)

api/core/model_runtime/model_providers/model_provider_factory.py

@@ -6,7 +6,7 @@ from typing import Optional
 from pydantic import BaseModel, ConfigDict
 
 from core.helper.module_import_helper import load_single_subclass_from_source
-from core.helper.position_helper import get_position_map, sort_to_dict_by_position_map
+from core.helper.position_helper import get_provider_position_map, sort_to_dict_by_position_map
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.entities.provider_entities import ProviderConfig, ProviderEntity, SimpleProviderEntity
 from core.model_runtime.model_providers.__base.model_provider import ModelProvider
@@ -234,7 +234,7 @@ class ModelProviderFactory:
         ]
 
         # get _position.yaml file path
-        position_map = get_position_map(model_providers_path)
+        position_map = get_provider_position_map(model_providers_path)
 
         # traverse all model_provider_dir_paths
         model_providers: list[ModelProviderExtension] = []

api/core/model_runtime/model_providers/moonshot/llm/llm.py

@@ -84,7 +84,8 @@ class MoonshotLargeLanguageModel(OAIAPICompatLargeLanguageModel):
 
     def _add_custom_parameters(self, credentials: dict) -> None:
         credentials['mode'] = 'chat'
-        credentials['endpoint_url'] = 'https://api.moonshot.cn/v1'
+        if 'endpoint_url' not in credentials or credentials['endpoint_url'] == "":
+            credentials['endpoint_url'] = 'https://api.moonshot.cn/v1'
 
     def _add_function_call(self, model: str, credentials: dict) -> None:
         model_schema = self.get_model_schema(model, credentials)

api/core/model_runtime/model_providers/moonshot/moonshot.yaml

@@ -31,6 +31,14 @@ provider_credential_schema:
       placeholder:
         zh_Hans: 在此输入您的 API Key
         en_US: Enter your API Key
+    - variable: endpoint_url
+      label:
+        en_US: API Base
+      type: text-input
+      required: false
+      placeholder:
+        zh_Hans: Base URL, 如：https://api.moonshot.cn/v1
+        en_US: Base URL, e.g. https://api.moonshot.cn/v1
 model_credential_schema:
   model:
     label:

api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini-2024-07-18.yaml

@@ -37,6 +37,9 @@ parameter_rules:
     options:
       - text
       - json_object
+      - json_schema
+  - name: json_schema
+    use_template: json_schema
 pricing:
   input: '0.15'
   output: '0.60'

api/core/model_runtime/model_providers/openrouter/llm/gpt-4o-2024-08-06.yaml

@@ -0,0 +1,44 @@
+model: gpt-4o-2024-08-06
+label:
+  zh_Hans: gpt-4o-2024-08-06
+  en_US: gpt-4o-2024-08-06
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - stream-tool-call
+  - vision
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: presence_penalty
+    use_template: presence_penalty
+  - name: frequency_penalty
+    use_template: frequency_penalty
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 16384
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: response_format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '2.50'
+  output: '10.00'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/siliconflow/rerank/bce-reranker-base_v1.yaml

@@ -0,0 +1,4 @@
+model: netease-youdao/bce-reranker-base_v1
+model_type: rerank
+model_properties:
+  context_size: 512

api/core/model_runtime/model_providers/siliconflow/rerank/bge-reranker-v2-m3.yaml

@@ -0,0 +1,4 @@
+model: BAAI/bge-reranker-v2-m3
+model_type: rerank
+model_properties:
+  context_size: 8192

api/core/model_runtime/model_providers/siliconflow/rerank/rerank.py

@@ -0,0 +1,87 @@
+from typing import Optional
+
+import httpx
+
+from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.rerank_model import RerankModel
+
+
+class SiliconflowRerankModel(RerankModel):
+
+    def _invoke(self, model: str, credentials: dict, query: str, docs: list[str],
+                score_threshold: Optional[float] = None, top_n: Optional[int] = None,
+                user: Optional[str] = None) -> RerankResult:
+        if len(docs) == 0:
+            return RerankResult(model=model, docs=[])
+
+        base_url = credentials.get('base_url', 'https://api.siliconflow.cn/v1')
+        if base_url.endswith('/'):
+            base_url = base_url[:-1]
+        try:
+            response = httpx.post(
+                base_url + '/rerank',
+                json={
+                    "model": model,
+                    "query": query,
+                    "documents": docs,
+                    "top_n": top_n,
+                    "return_documents": True
+                },
+                headers={"Authorization": f"Bearer {credentials.get('api_key')}"}
+            )
+            response.raise_for_status()
+            results = response.json()
+
+            rerank_documents = []
+            for result in results['results']:
+                rerank_document = RerankDocument(
+                    index=result['index'],
+                    text=result['document']['text'],
+                    score=result['relevance_score'],
+                )
+                if score_threshold is None or result['relevance_score'] >= score_threshold:
+                    rerank_documents.append(rerank_document)
+
+            return RerankResult(model=model, docs=rerank_documents)
+        except httpx.HTTPStatusError as e:
+            raise InvokeServerUnavailableError(str(e))
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        try:
+
+            self._invoke(
+                model=model,
+                credentials=credentials,
+                query="What is the capital of the United States?",
+                docs=[
+                    "Carson City is the capital city of the American state of Nevada. At the 2010 United States "
+                    "Census, Carson City had a population of 55,274.",
+                    "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that "
+                    "are a political division controlled by the United States. Its capital is Saipan.",
+                ],
+                score_threshold=0.8
+            )
+        except Exception as ex:
+            raise CredentialsValidateFailedError(str(ex))
+
+    @property
+    def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+        """
+        Map model invoke error to unified error
+        """
+        return {
+            InvokeConnectionError: [httpx.ConnectError],
+            InvokeServerUnavailableError: [httpx.RemoteProtocolError],
+            InvokeRateLimitError: [],
+            InvokeAuthorizationError: [httpx.HTTPStatusError],
+            InvokeBadRequestError: [httpx.RequestError]
+        }

api/core/model_runtime/model_providers/siliconflow/siliconflow.yaml

@@ -12,10 +12,11 @@ help:
     en_US: Get your API Key from SiliconFlow
     zh_Hans: 从 SiliconFlow 获取 API Key
   url:
-    en_US: https://cloud.siliconflow.cn/keys
+    en_US: https://cloud.siliconflow.cn/account/ak
 supported_model_types:
   - llm
   - text-embedding
+  - rerank
   - speech2text
 configurate_methods:
   - predefined-model

api/core/model_runtime/model_providers/volcengine_maas/llm/llm.py

@@ -35,7 +35,10 @@ from core.model_runtime.model_providers.volcengine_maas.errors import (
     RateLimitErrors,
     ServerUnavailableErrors,
 )
-from core.model_runtime.model_providers.volcengine_maas.llm.models import ModelConfigs
+from core.model_runtime.model_providers.volcengine_maas.llm.models import (
+    get_model_config,
+    get_v2_req_params,
+)
 from core.model_runtime.model_providers.volcengine_maas.volc_sdk import MaasException
 
 logger = logging.getLogger(__name__)
@@ -95,37 +98,12 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
             -> LLMResult | Generator:
 
         client = MaaSClient.from_credential(credentials)
-
-        req_params = ModelConfigs.get(
-            credentials['base_model_name'], {}).get('req_params', {}).copy()
-        if credentials.get('context_size'):
-            req_params['max_prompt_tokens'] = credentials.get('context_size')
-        if credentials.get('max_tokens'):
-            req_params['max_new_tokens'] = credentials.get('max_tokens')
-        if model_parameters.get('max_tokens'):
-            req_params['max_new_tokens'] = model_parameters.get('max_tokens')
-        if model_parameters.get('temperature'):
-            req_params['temperature'] = model_parameters.get('temperature')
-        if model_parameters.get('top_p'):
-            req_params['top_p'] = model_parameters.get('top_p')
-        if model_parameters.get('top_k'):
-            req_params['top_k'] = model_parameters.get('top_k')
-        if model_parameters.get('presence_penalty'):
-            req_params['presence_penalty'] = model_parameters.get(
-                'presence_penalty')
-        if model_parameters.get('frequency_penalty'):
-            req_params['frequency_penalty'] = model_parameters.get(
-                'frequency_penalty')
-        if stop:
-            req_params['stop'] = stop
-
+        req_params = get_v2_req_params(credentials, model_parameters, stop)
         extra_model_kwargs = {}
-        
         if tools:
             extra_model_kwargs['tools'] = [
                 MaaSClient.transform_tool_prompt_to_maas_config(tool) for tool in tools
             ]
-
         resp = MaaSClient.wrap_exception(
             lambda: client.chat(req_params, prompt_messages, stream, **extra_model_kwargs))
         if not stream:
@@ -197,10 +175,8 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
         """
             used to define customizable model schema
         """
-        max_tokens = ModelConfigs.get(
-            credentials['base_model_name'], {}).get('req_params', {}).get('max_new_tokens')
-        if credentials.get('max_tokens'):
-            max_tokens = int(credentials.get('max_tokens'))
+        model_config = get_model_config(credentials)
+    
         rules = [
             ParameterRule(
                 name='temperature',
@@ -234,10 +210,10 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
                 name='presence_penalty',
                 type=ParameterType.FLOAT,
                 use_template='presence_penalty',
-                label={
-                    'en_US': 'Presence Penalty',
-                    'zh_Hans': '存在惩罚',
-                },
+                label=I18nObject(
+                    en_US='Presence Penalty',
+                    zh_Hans= '存在惩罚',
+                ),
                 min=-2.0,
                 max=2.0,
             ),
@@ -245,10 +221,10 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
                 name='frequency_penalty',
                 type=ParameterType.FLOAT,
                 use_template='frequency_penalty',
-                label={
-                    'en_US': 'Frequency Penalty',
-                    'zh_Hans': '频率惩罚',
-                },
+                label=I18nObject(
+                    en_US= 'Frequency Penalty',
+                    zh_Hans= '频率惩罚',
+                ),
                 min=-2.0,
                 max=2.0,
             ),
@@ -257,7 +233,7 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
                 type=ParameterType.INT,
                 use_template='max_tokens',
                 min=1,
-                max=max_tokens,
+                max=model_config.properties.max_tokens,
                 default=512,
                 label=I18nObject(
                     zh_Hans='最大生成长度',
@@ -266,17 +242,10 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
             ),
         ]
 
-        model_properties = ModelConfigs.get(
-            credentials['base_model_name'], {}).get('model_properties', {}).copy()
-        if credentials.get('mode'):
-            model_properties[ModelPropertyKey.MODE] = credentials.get('mode')
-        if credentials.get('context_size'):
-            model_properties[ModelPropertyKey.CONTEXT_SIZE] = int(
-                credentials.get('context_size', 4096))
-
-        model_features = ModelConfigs.get(
-            credentials['base_model_name'], {}).get('features', [])
-
+        model_properties = {}
+        model_properties[ModelPropertyKey.CONTEXT_SIZE] = model_config.properties.context_size
+        model_properties[ModelPropertyKey.MODE] = model_config.properties.mode.value
+       
         entity = AIModelEntity(
             model=model,
             label=I18nObject(
@@ -286,7 +255,7 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
             model_type=ModelType.LLM,
             model_properties=model_properties,
             parameter_rules=rules,
-            features=model_features,
+            features=model_config.features,
         )
 
         return entity

api/core/model_runtime/model_providers/volcengine_maas/llm/models.py

@@ -1,181 +1,123 @@
+from pydantic import BaseModel
+
+from core.model_runtime.entities.llm_entities import LLMMode
 from core.model_runtime.entities.model_entities import ModelFeature
 
-ModelConfigs = {
-    'Doubao-pro-4k': {
-        'req_params': {
-            'max_prompt_tokens': 4096,
-            'max_new_tokens': 4096,
-        },
-        'model_properties': {
-            'context_size': 4096,
-            'mode': 'chat',
-        },
-        'features': [
-            ModelFeature.TOOL_CALL
-        ],
-    },
-    'Doubao-lite-4k': {
-        'req_params': {
-            'max_prompt_tokens': 4096,
-            'max_new_tokens': 4096,
-        },
-        'model_properties': {
-            'context_size': 4096,
-            'mode': 'chat',
-        },
-        'features': [
-            ModelFeature.TOOL_CALL
-        ],
-    },
-    'Doubao-pro-32k': {
-        'req_params': {
-            'max_prompt_tokens': 32768,
-            'max_new_tokens': 32768,
-        },
-        'model_properties': {
-            'context_size': 32768,
-            'mode': 'chat',
-        },
-        'features': [
-            ModelFeature.TOOL_CALL
-        ],
-    },
-    'Doubao-lite-32k': {
-        'req_params': {
-            'max_prompt_tokens': 32768,
-            'max_new_tokens': 32768,
-        },
-        'model_properties': {
-            'context_size': 32768,
-            'mode': 'chat',
-        },
-        'features': [
-            ModelFeature.TOOL_CALL
-        ],
-    },
-    'Doubao-pro-128k': {
-        'req_params': {
-            'max_prompt_tokens': 131072,
-            'max_new_tokens': 131072,
-        },
-        'model_properties': {
-            'context_size': 131072,
-            'mode': 'chat',
-        },
-        'features': [
-            ModelFeature.TOOL_CALL
-        ],
-    },
-    'Doubao-lite-128k': {
-        'req_params': {
-            'max_prompt_tokens': 131072,
-            'max_new_tokens': 131072,
-        },
-        'model_properties': {
-            'context_size': 131072,
-            'mode': 'chat',
-        },
-        'features': [
-            ModelFeature.TOOL_CALL
-        ],
-    },
-    'Skylark2-pro-4k': {
-        'req_params': {
-            'max_prompt_tokens': 4096,
-            'max_new_tokens': 4000,
-        },
-        'model_properties': {
-            'context_size': 4096,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'Llama3-8B': {
-        'req_params': {
-            'max_prompt_tokens': 8192,
-            'max_new_tokens': 8192,
-        },
-        'model_properties': {
-            'context_size': 8192,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'Llama3-70B': {
-        'req_params': {
-            'max_prompt_tokens': 8192,
-            'max_new_tokens': 8192,
-        },
-        'model_properties': {
-            'context_size': 8192,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'Moonshot-v1-8k': {
-        'req_params': {
-            'max_prompt_tokens': 8192,
-            'max_new_tokens': 4096,
-        },
-        'model_properties': {
-            'context_size': 8192,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'Moonshot-v1-32k': {
-        'req_params': {
-            'max_prompt_tokens': 32768,
-            'max_new_tokens': 16384,
-        },
-        'model_properties': {
-            'context_size': 32768,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'Moonshot-v1-128k': {
-        'req_params': {
-            'max_prompt_tokens': 131072,
-            'max_new_tokens': 65536,
-        },
-        'model_properties': {
-            'context_size': 131072,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'GLM3-130B': {
-        'req_params': {
-            'max_prompt_tokens': 8192,
-            'max_new_tokens': 4096,
-        },
-        'model_properties': {
-            'context_size': 8192,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'GLM3-130B-Fin': {
-        'req_params': {
-            'max_prompt_tokens': 8192,
-            'max_new_tokens': 4096,
-        },
-        'model_properties': {
-            'context_size': 8192,
-            'mode': 'chat',
-        },
-        'features': [],
-    },
-    'Mistral-7B': {
-        'req_params': {
-            'max_prompt_tokens': 8192,
-            'max_new_tokens': 2048,
-        },
-        'model_properties': {
-            'context_size': 8192,
-            'mode': 'chat',
-        },
-        'features': [],
-    }
+
+class ModelProperties(BaseModel):
+    context_size: int 
+    max_tokens: int 
+    mode: LLMMode
+
+class ModelConfig(BaseModel):
+    properties: ModelProperties
+    features: list[ModelFeature]
+
+
+configs: dict[str, ModelConfig] = {
+    'Doubao-pro-4k': ModelConfig(
+        properties=ModelProperties(context_size=4096, max_tokens=4096, mode=LLMMode.CHAT),
+        features=[ModelFeature.TOOL_CALL]
+    ),
+    'Doubao-lite-4k': ModelConfig(
+        properties=ModelProperties(context_size=4096, max_tokens=4096, mode=LLMMode.CHAT),
+        features=[ModelFeature.TOOL_CALL]
+    ),
+    'Doubao-pro-32k': ModelConfig(
+        properties=ModelProperties(context_size=32768, max_tokens=32768, mode=LLMMode.CHAT),
+        features=[ModelFeature.TOOL_CALL]
+    ),
+    'Doubao-lite-32k': ModelConfig(
+        properties=ModelProperties(context_size=32768, max_tokens=32768, mode=LLMMode.CHAT),
+        features=[ModelFeature.TOOL_CALL]
+    ),
+    'Doubao-pro-128k': ModelConfig(
+        properties=ModelProperties(context_size=131072, max_tokens=131072, mode=LLMMode.CHAT),
+        features=[ModelFeature.TOOL_CALL]
+    ),
+    'Doubao-lite-128k': ModelConfig(
+        properties=ModelProperties(context_size=131072, max_tokens=131072, mode=LLMMode.CHAT),
+        features=[ModelFeature.TOOL_CALL]
+    ),
+    'Skylark2-pro-4k': ModelConfig(
+        properties=ModelProperties(context_size=4096, max_tokens=4000, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'Llama3-8B': ModelConfig(
+        properties=ModelProperties(context_size=8192, max_tokens=8192, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'Llama3-70B': ModelConfig(
+        properties=ModelProperties(context_size=8192, max_tokens=8192, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'Moonshot-v1-8k': ModelConfig(
+        properties=ModelProperties(context_size=8192, max_tokens=4096, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'Moonshot-v1-32k': ModelConfig(
+        properties=ModelProperties(context_size=32768, max_tokens=16384, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'Moonshot-v1-128k': ModelConfig(
+        properties=ModelProperties(context_size=131072, max_tokens=65536, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'GLM3-130B': ModelConfig(
+        properties=ModelProperties(context_size=8192, max_tokens=4096, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'GLM3-130B-Fin': ModelConfig(
+        properties=ModelProperties(context_size=8192, max_tokens=4096, mode=LLMMode.CHAT),
+        features=[]
+    ),
+    'Mistral-7B': ModelConfig(
+        properties=ModelProperties(context_size=8192, max_tokens=2048, mode=LLMMode.CHAT),
+        features=[]
+    )
 }
+
+def get_model_config(credentials: dict)->ModelConfig:
+    base_model = credentials.get('base_model_name', '')
+    model_configs = configs.get(base_model)
+    if not model_configs:
+        return ModelConfig(
+                properties=ModelProperties(
+                context_size=int(credentials.get('context_size', 0)),
+                max_tokens=int(credentials.get('max_tokens', 0)),
+                mode= LLMMode.value_of(credentials.get('mode', 'chat')),
+            ),
+            features=[]
+        )
+    return model_configs
+
+
+def get_v2_req_params(credentials: dict, model_parameters: dict, 
+                      stop: list[str] | None=None):
+    req_params = {}
+    # predefined properties
+    model_configs = get_model_config(credentials)
+    if model_configs:
+        req_params['max_prompt_tokens'] = model_configs.properties.context_size
+        req_params['max_new_tokens'] = model_configs.properties.max_tokens
+
+    # model parameters
+    if model_parameters.get('max_tokens'):
+        req_params['max_new_tokens'] = model_parameters.get('max_tokens')
+    if model_parameters.get('temperature'):
+        req_params['temperature'] = model_parameters.get('temperature')
+    if model_parameters.get('top_p'):
+        req_params['top_p'] = model_parameters.get('top_p')
+    if model_parameters.get('top_k'):
+        req_params['top_k'] = model_parameters.get('top_k')
+    if model_parameters.get('presence_penalty'):
+        req_params['presence_penalty'] = model_parameters.get(
+            'presence_penalty')
+    if model_parameters.get('frequency_penalty'):
+        req_params['frequency_penalty'] = model_parameters.get(
+            'frequency_penalty')
+            
+    if stop:
+        req_params['stop'] = stop
+
+    return req_params

api/core/model_runtime/model_providers/volcengine_maas/text_embedding/models.py

@@ -1,9 +1,27 @@
+from pydantic import BaseModel
+
+
+class ModelProperties(BaseModel):
+    context_size: int 
+    max_chunks: int 
+
+class ModelConfig(BaseModel):
+    properties: ModelProperties
+
 ModelConfigs = {
-    'Doubao-embedding': {
-        'req_params': {},
-        'model_properties': {
-            'context_size': 4096,
-            'max_chunks': 1,
-        }
-    },
+    'Doubao-embedding': ModelConfig(
+        properties=ModelProperties(context_size=4096, max_chunks=1)
+    ),
 }
+
+def get_model_config(credentials: dict)->ModelConfig:
+    base_model = credentials.get('base_model_name', '')
+    model_configs = ModelConfigs.get(base_model)
+    if not model_configs:
+        return ModelConfig(
+                properties=ModelProperties(
+                context_size=int(credentials.get('context_size', 0)),
+                max_chunks=int(credentials.get('max_chunks', 0)),
+            )
+        )
+    return model_configs

api/core/model_runtime/model_providers/volcengine_maas/text_embedding/text_embedding.py

@@ -30,7 +30,7 @@ from core.model_runtime.model_providers.volcengine_maas.errors import (
     RateLimitErrors,
     ServerUnavailableErrors,
 )
-from core.model_runtime.model_providers.volcengine_maas.text_embedding.models import ModelConfigs
+from core.model_runtime.model_providers.volcengine_maas.text_embedding.models import get_model_config
 from core.model_runtime.model_providers.volcengine_maas.volc_sdk import MaasException
 
 
@@ -115,14 +115,10 @@ class VolcengineMaaSTextEmbeddingModel(TextEmbeddingModel):
         """
             generate custom model entities from credentials
         """
-        model_properties = ModelConfigs.get(
-            credentials['base_model_name'], {}).get('model_properties', {}).copy()
-        if credentials.get('context_size'):
-            model_properties[ModelPropertyKey.CONTEXT_SIZE] = int(
-                credentials.get('context_size', 4096))
-        if credentials.get('max_chunks'):
-            model_properties[ModelPropertyKey.MAX_CHUNKS] = int(
-                credentials.get('max_chunks', 4096))
+        model_config = get_model_config(credentials)
+        model_properties = {}
+        model_properties[ModelPropertyKey.CONTEXT_SIZE] = model_config.properties.context_size
+        model_properties[ModelPropertyKey.MAX_CHUNKS] = model_config.properties.max_chunks
         entity = AIModelEntity(
             model=model,
             label=I18nObject(en_US=model),

api/core/model_runtime/model_providers/wenxin/_common.py

@@ -0,0 +1,198 @@
+from datetime import datetime, timedelta
+from threading import Lock
+
+from requests import post
+
+from core.model_runtime.model_providers.wenxin.wenxin_errors import (
+    BadRequestError,
+    InternalServerError,
+    InvalidAPIKeyError,
+    InvalidAuthenticationError,
+    RateLimitReachedError,
+)
+
+baidu_access_tokens: dict[str, 'BaiduAccessToken'] = {}
+baidu_access_tokens_lock = Lock()
+
+
+class BaiduAccessToken:
+    api_key: str
+    access_token: str
+    expires: datetime
+
+    def __init__(self, api_key: str) -> None:
+        self.api_key = api_key
+        self.access_token = ''
+        self.expires = datetime.now() + timedelta(days=3)
+
+    @staticmethod
+    def _get_access_token(api_key: str, secret_key: str) -> str:
+        """
+            request access token from Baidu
+        """
+        try:
+            response = post(
+                url=f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={api_key}&client_secret={secret_key}',
+                headers={
+                    'Content-Type': 'application/json',
+                    'Accept': 'application/json'
+                },
+            )
+        except Exception as e:
+            raise InvalidAuthenticationError(f'Failed to get access token from Baidu: {e}')
+
+        resp = response.json()
+        if 'error' in resp:
+            if resp['error'] == 'invalid_client':
+                raise InvalidAPIKeyError(f'Invalid API key or secret key: {resp["error_description"]}')
+            elif resp['error'] == 'unknown_error':
+                raise InternalServerError(f'Internal server error: {resp["error_description"]}')
+            elif resp['error'] == 'invalid_request':
+                raise BadRequestError(f'Bad request: {resp["error_description"]}')
+            elif resp['error'] == 'rate_limit_exceeded':
+                raise RateLimitReachedError(f'Rate limit reached: {resp["error_description"]}')
+            else:
+                raise Exception(f'Unknown error: {resp["error_description"]}')
+
+        return resp['access_token']
+
+    @staticmethod
+    def get_access_token(api_key: str, secret_key: str) -> 'BaiduAccessToken':
+        """
+            LLM from Baidu requires access token to invoke the API.
+            however, we have api_key and secret_key, and access token is valid for 30 days.
+            so we can cache the access token for 3 days. (avoid memory leak)
+
+            it may be more efficient to use a ticker to refresh access token, but it will cause
+            more complexity, so we just refresh access tokens when get_access_token is called.
+        """
+
+        # loop up cache, remove expired access token
+        baidu_access_tokens_lock.acquire()
+        now = datetime.now()
+        for key in list(baidu_access_tokens.keys()):
+            token = baidu_access_tokens[key]
+            if token.expires < now:
+                baidu_access_tokens.pop(key)
+
+        if api_key not in baidu_access_tokens:
+            # if access token not in cache, request it
+            token = BaiduAccessToken(api_key)
+            baidu_access_tokens[api_key] = token
+            # release it to enhance performance
+            # btw, _get_access_token will raise exception if failed, release lock here to avoid deadlock
+            baidu_access_tokens_lock.release()
+            # try to get access token
+            token_str = BaiduAccessToken._get_access_token(api_key, secret_key)
+            token.access_token = token_str
+            token.expires = now + timedelta(days=3)
+            return token
+        else:
+            # if access token in cache, return it
+            token = baidu_access_tokens[api_key]
+            baidu_access_tokens_lock.release()
+            return token
+
+
+class _CommonWenxin:
+    api_bases = {
+        'ernie-bot': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-4k-0205',
+        'ernie-bot-4': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro',
+        'ernie-bot-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions',
+        'ernie-bot-turbo': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant',
+        'ernie-3.5-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions',
+        'ernie-3.5-8k-0205': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-8k-0205',
+        'ernie-3.5-8k-1222': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-8k-1222',
+        'ernie-3.5-4k-0205': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-4k-0205',
+        'ernie-3.5-128k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-128k',
+        'ernie-4.0-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro',
+        'ernie-4.0-8k-latest': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro',
+        'ernie-speed-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie_speed',
+        'ernie-speed-128k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-speed-128k',
+        'ernie-speed-appbuilder': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ai_apaas',
+        'ernie-lite-8k-0922': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant',
+        'ernie-lite-8k-0308': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-lite-8k',
+        'ernie-character-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k',
+        'ernie-character-8k-0321': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k',
+        'ernie-4.0-turbo-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k',
+        'ernie-4.0-turbo-8k-preview': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k-preview',
+        'yi_34b_chat': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/yi_34b_chat',
+        'embedding-v1': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/embedding-v1',
+        'bge-large-en': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/bge_large_en',
+        'bge-large-zh': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/bge_large_zh',
+        'tao-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/tao_8k',
+    }
+
+    function_calling_supports = [
+        'ernie-bot',
+        'ernie-bot-8k',
+        'ernie-3.5-8k',
+        'ernie-3.5-8k-0205',
+        'ernie-3.5-8k-1222',
+        'ernie-3.5-4k-0205',
+        'ernie-3.5-128k',
+        'ernie-4.0-8k',
+        'ernie-4.0-turbo-8k',
+        'ernie-4.0-turbo-8k-preview',
+        'yi_34b_chat'
+    ]
+
+    api_key: str = ''
+    secret_key: str = ''
+
+    def __init__(self, api_key: str, secret_key: str):
+        self.api_key = api_key
+        self.secret_key = secret_key
+
+    @staticmethod
+    def _to_credential_kwargs(credentials: dict) -> dict:
+        credentials_kwargs = {
+            "api_key": credentials['api_key'],
+            "secret_key": credentials['secret_key']
+        }
+        return credentials_kwargs
+
+    def _handle_error(self, code: int, msg: str):
+        error_map = {
+            1: InternalServerError,
+            2: InternalServerError,
+            3: BadRequestError,
+            4: RateLimitReachedError,
+            6: InvalidAuthenticationError,
+            13: InvalidAPIKeyError,
+            14: InvalidAPIKeyError,
+            15: InvalidAPIKeyError,
+            17: RateLimitReachedError,
+            18: RateLimitReachedError,
+            19: RateLimitReachedError,
+            100: InvalidAPIKeyError,
+            111: InvalidAPIKeyError,
+            200: InternalServerError,
+            336000: InternalServerError,
+            336001: BadRequestError,
+            336002: BadRequestError,
+            336003: BadRequestError,
+            336004: InvalidAuthenticationError,
+            336005: InvalidAPIKeyError,
+            336006: BadRequestError,
+            336007: BadRequestError,
+            336008: BadRequestError,
+            336100: InternalServerError,
+            336101: BadRequestError,
+            336102: BadRequestError,
+            336103: BadRequestError,
+            336104: BadRequestError,
+            336105: BadRequestError,
+            336200: InternalServerError,
+            336303: BadRequestError,
+            337006: BadRequestError
+        }
+
+        if code in error_map:
+            raise error_map[code](msg)
+        else:
+            raise InternalServerError(f'Unknown error: {msg}')
+
+    def _get_access_token(self) -> str:
+        token = BaiduAccessToken.get_access_token(self.api_key, self.secret_key)
+        return token.access_token

api/core/model_runtime/model_providers/wenxin/llm/ernie_bot.py

@@ -1,102 +1,17 @@
 from collections.abc import Generator
-from datetime import datetime, timedelta
 from enum import Enum
 from json import dumps, loads
-from threading import Lock
 from typing import Any, Union
 
 from requests import Response, post
 
 from core.model_runtime.entities.message_entities import PromptMessageTool
-from core.model_runtime.model_providers.wenxin.llm.ernie_bot_errors import (
+from core.model_runtime.model_providers.wenxin._common import _CommonWenxin
+from core.model_runtime.model_providers.wenxin.wenxin_errors import (
     BadRequestError,
     InternalServerError,
-    InvalidAPIKeyError,
-    InvalidAuthenticationError,
-    RateLimitReachedError,
 )
 
-# map api_key to access_token
-baidu_access_tokens: dict[str, 'BaiduAccessToken'] = {}
-baidu_access_tokens_lock = Lock()
-
-class BaiduAccessToken:
-    api_key: str
-    access_token: str
-    expires: datetime
-
-    def __init__(self, api_key: str) -> None:
-        self.api_key = api_key
-        self.access_token = ''
-        self.expires = datetime.now() + timedelta(days=3)
-
-    def _get_access_token(api_key: str, secret_key: str) -> str:
-        """
-            request access token from Baidu
-        """
-        try:
-            response = post(
-                url=f'https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id={api_key}&client_secret={secret_key}',
-                headers={
-                    'Content-Type': 'application/json',
-                    'Accept': 'application/json'
-                },
-            )
-        except Exception as e:
-            raise InvalidAuthenticationError(f'Failed to get access token from Baidu: {e}')
-
-        resp = response.json()
-        if 'error' in resp:
-            if resp['error'] == 'invalid_client':
-                raise InvalidAPIKeyError(f'Invalid API key or secret key: {resp["error_description"]}')
-            elif resp['error'] == 'unknown_error':
-                raise InternalServerError(f'Internal server error: {resp["error_description"]}')
-            elif resp['error'] == 'invalid_request':
-                raise BadRequestError(f'Bad request: {resp["error_description"]}')
-            elif resp['error'] == 'rate_limit_exceeded':
-                raise RateLimitReachedError(f'Rate limit reached: {resp["error_description"]}')
-            else:
-                raise Exception(f'Unknown error: {resp["error_description"]}')
-
-        return resp['access_token']
-
-    @staticmethod
-    def get_access_token(api_key: str, secret_key: str) -> 'BaiduAccessToken':
-        """
-            LLM from Baidu requires access token to invoke the API.
-            however, we have api_key and secret_key, and access token is valid for 30 days.
-            so we can cache the access token for 3 days. (avoid memory leak)
-
-            it may be more efficient to use a ticker to refresh access token, but it will cause
-            more complexity, so we just refresh access tokens when get_access_token is called.
-        """
-
-        # loop up cache, remove expired access token
-        baidu_access_tokens_lock.acquire()
-        now = datetime.now()
-        for key in list(baidu_access_tokens.keys()):
-            token = baidu_access_tokens[key]
-            if token.expires < now:
-                baidu_access_tokens.pop(key)
-
-        if api_key not in baidu_access_tokens:
-            # if access token not in cache, request it
-            token = BaiduAccessToken(api_key)
-            baidu_access_tokens[api_key] = token
-            # release it to enhance performance
-            # btw, _get_access_token will raise exception if failed, release lock here to avoid deadlock
-            baidu_access_tokens_lock.release()
-            # try to get access token
-            token_str = BaiduAccessToken._get_access_token(api_key, secret_key)
-            token.access_token = token_str
-            token.expires = now + timedelta(days=3)
-            return token
-        else:
-            # if access token in cache, return it
-            token = baidu_access_tokens[api_key]
-            baidu_access_tokens_lock.release()
-            return token
-
 
 class ErnieMessage:
     class Role(Enum):
@@ -120,51 +35,7 @@ class ErnieMessage:
         self.content = content
         self.role = role
 
-class ErnieBotModel:
-    api_bases = {
-        'ernie-bot': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-4k-0205',
-        'ernie-bot-4': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro',
-        'ernie-bot-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions',
-        'ernie-bot-turbo': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant',
-        'ernie-3.5-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions',
-        'ernie-3.5-8k-0205': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-8k-0205',
-        'ernie-3.5-8k-1222': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-8k-1222',
-        'ernie-3.5-4k-0205': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-4k-0205',
-        'ernie-3.5-128k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-3.5-128k',
-        'ernie-4.0-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro',
-        'ernie-4.0-8k-latest': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/completions_pro',
-        'ernie-speed-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie_speed',
-        'ernie-speed-128k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-speed-128k',
-        'ernie-speed-appbuilder': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ai_apaas',
-        'ernie-lite-8k-0922': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/eb-instant',
-        'ernie-lite-8k-0308': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-lite-8k',
-        'ernie-character-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k',
-        'ernie-character-8k-0321': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k',
-        'ernie-4.0-turbo-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k',
-        'ernie-4.0-turbo-8k-preview': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k-preview',
-        'yi_34b_chat': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/yi_34b_chat',
-    }
-
-    function_calling_supports = [
-        'ernie-bot',
-        'ernie-bot-8k',
-        'ernie-3.5-8k',
-        'ernie-3.5-8k-0205',
-        'ernie-3.5-8k-1222',
-        'ernie-3.5-4k-0205',
-        'ernie-3.5-128k',
-        'ernie-4.0-8k',
-        'ernie-4.0-turbo-8k',
-        'ernie-4.0-turbo-8k-preview',
-        'yi_34b_chat'
-    ]
-
-    api_key: str = ''
-    secret_key: str = ''
-
-    def __init__(self, api_key: str, secret_key: str):
-        self.api_key = api_key
-        self.secret_key = secret_key
+class ErnieBotModel(_CommonWenxin):
 
     def generate(self, model: str, stream: bool, messages: list[ErnieMessage],
                  parameters: dict[str, Any], timeout: int, tools: list[PromptMessageTool], \
@@ -199,51 +70,6 @@ class ErnieBotModel:
             return self._handle_chat_stream_generate_response(resp)
         return self._handle_chat_generate_response(resp)
 
-    def _handle_error(self, code: int, msg: str):
-        error_map = {
-            1: InternalServerError,
-            2: InternalServerError,
-            3: BadRequestError,
-            4: RateLimitReachedError,
-            6: InvalidAuthenticationError,
-            13: InvalidAPIKeyError,
-            14: InvalidAPIKeyError,
-            15: InvalidAPIKeyError,
-            17: RateLimitReachedError,
-            18: RateLimitReachedError,
-            19: RateLimitReachedError,
-            100: InvalidAPIKeyError,
-            111: InvalidAPIKeyError,
-            200: InternalServerError,
-            336000: InternalServerError,
-            336001: BadRequestError,
-            336002: BadRequestError,
-            336003: BadRequestError,
-            336004: InvalidAuthenticationError,
-            336005: InvalidAPIKeyError,
-            336006: BadRequestError,
-            336007: BadRequestError,
-            336008: BadRequestError,
-            336100: InternalServerError,
-            336101: BadRequestError,
-            336102: BadRequestError,
-            336103: BadRequestError,
-            336104: BadRequestError,
-            336105: BadRequestError,
-            336200: InternalServerError,
-            336303: BadRequestError,
-            337006: BadRequestError
-        }
-
-        if code in error_map:
-            raise error_map[code](msg)
-        else:
-            raise InternalServerError(f'Unknown error: {msg}')
-
-    def _get_access_token(self) -> str:
-        token = BaiduAccessToken.get_access_token(self.api_key, self.secret_key)
-        return token.access_token
-
     def _copy_messages(self, messages: list[ErnieMessage]) -> list[ErnieMessage]:
         return [ErnieMessage(message.content, message.role) for message in messages]
 

api/core/model_runtime/model_providers/wenxin/llm/ernie_bot_errors.py

@@ -1,17 +0,0 @@
-class InvalidAuthenticationError(Exception):
-    pass
-
-class InvalidAPIKeyError(Exception):
-    pass
-
-class RateLimitReachedError(Exception):
-    pass
-
-class InsufficientAccountBalance(Exception):
-    pass
-
-class InternalServerError(Exception):
-    pass
-
-class BadRequestError(Exception):
-    pass

api/core/model_runtime/model_providers/wenxin/llm/llm.py

@@ -11,24 +11,13 @@ from core.model_runtime.entities.message_entities import (
     UserPromptMessage,
 )
 from core.model_runtime.errors.invoke import (
-    InvokeAuthorizationError,
-    InvokeBadRequestError,
-    InvokeConnectionError,
     InvokeError,
-    InvokeRateLimitError,
-    InvokeServerUnavailableError,
 )
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.model_runtime.model_providers.wenxin.llm.ernie_bot import BaiduAccessToken, ErnieBotModel, ErnieMessage
-from core.model_runtime.model_providers.wenxin.llm.ernie_bot_errors import (
-    BadRequestError,
-    InsufficientAccountBalance,
-    InternalServerError,
-    InvalidAPIKeyError,
-    InvalidAuthenticationError,
-    RateLimitReachedError,
-)
+from core.model_runtime.model_providers.wenxin._common import BaiduAccessToken
+from core.model_runtime.model_providers.wenxin.llm.ernie_bot import ErnieBotModel, ErnieMessage
+from core.model_runtime.model_providers.wenxin.wenxin_errors import invoke_error_mapping
 
 ERNIE_BOT_BLOCK_MODE_PROMPT = """You should always follow the instructions and output a valid {{block}} object.
 The structure of the {{block}} object you can found in the instructions, use {"answer": "$your_answer"} as the default structure
@@ -140,7 +129,7 @@ class ErnieBotLargeLanguageModel(LargeLanguageModel):
         api_key = credentials['api_key']
         secret_key = credentials['secret_key']
         try:
-            BaiduAccessToken._get_access_token(api_key, secret_key)
+            BaiduAccessToken.get_access_token(api_key, secret_key)
         except Exception as e:
             raise CredentialsValidateFailedError(f'Credentials validation failed: {e}')
 
@@ -254,22 +243,4 @@ class ErnieBotLargeLanguageModel(LargeLanguageModel):
 
         :return: Invoke error mapping
         """
-        return {
-            InvokeConnectionError: [
-            ],
-            InvokeServerUnavailableError: [
-                InternalServerError
-            ],
-            InvokeRateLimitError: [
-                RateLimitReachedError
-            ],
-            InvokeAuthorizationError: [
-                InvalidAuthenticationError,
-                InsufficientAccountBalance,
-                InvalidAPIKeyError,
-            ],
-            InvokeBadRequestError: [
-                BadRequestError,
-                KeyError
-            ]
-        }
+        return invoke_error_mapping()

api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-en.yaml

@@ -0,0 +1,9 @@
+model: bge-large-en
+model_type: text-embedding
+model_properties:
+  context_size: 512
+  max_chunks: 16
+pricing:
+  input: '0.0005'
+  unit: '0.001'
+  currency: RMB

api/core/model_runtime/model_providers/wenxin/text_embedding/bge-large-zh.yaml

@@ -0,0 +1,9 @@
+model: bge-large-zh
+model_type: text-embedding
+model_properties:
+  context_size: 512
+  max_chunks: 16
+pricing:
+  input: '0.0005'
+  unit: '0.001'
+  currency: RMB

api/core/model_runtime/model_providers/wenxin/text_embedding/embedding-v1.yaml

@@ -0,0 +1,9 @@
+model: embedding-v1
+model_type: text-embedding
+model_properties:
+  context_size: 384
+  max_chunks: 16
+pricing:
+  input: '0.0005'
+  unit: '0.001'
+  currency: RMB

api/core/model_runtime/model_providers/wenxin/text_embedding/tao-8k.yaml

@@ -0,0 +1,9 @@
+model: tao-8k
+model_type: text-embedding
+model_properties:
+  context_size: 8192
+  max_chunks: 1
+pricing:
+  input: '0.0005'
+  unit: '0.001'
+  currency: RMB

api/core/model_runtime/model_providers/wenxin/text_embedding/text_embedding.py

@@ -0,0 +1,184 @@
+import time
+from abc import abstractmethod
+from collections.abc import Mapping
+from json import dumps
+from typing import Any, Optional
+
+import numpy as np
+from requests import Response, post
+
+from core.model_runtime.entities.model_entities import PriceType
+from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
+from core.model_runtime.errors.invoke import InvokeError
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
+from core.model_runtime.model_providers.wenxin._common import BaiduAccessToken, _CommonWenxin
+from core.model_runtime.model_providers.wenxin.wenxin_errors import (
+    BadRequestError,
+    InternalServerError,
+    invoke_error_mapping,
+)
+
+
+class TextEmbedding:
+    @abstractmethod
+    def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int):
+        raise NotImplementedError
+
+
+class WenxinTextEmbedding(_CommonWenxin, TextEmbedding):
+    def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int):
+        access_token = self._get_access_token()
+        url = f'{self.api_bases[model]}?access_token={access_token}'
+        body = self._build_embed_request_body(model, texts, user)
+        headers = {
+            'Content-Type': 'application/json',
+        }
+
+        resp = post(url, data=dumps(body), headers=headers)
+        if resp.status_code != 200:
+            raise InternalServerError(f'Failed to invoke ernie bot: {resp.text}')
+        return self._handle_embed_response(model, resp)
+
+    def _build_embed_request_body(self, model: str, texts: list[str], user: str) -> dict[str, Any]:
+        if len(texts) == 0:
+            raise BadRequestError('The number of texts should not be zero.')
+        body = {
+            'input': texts,
+            'user_id': user,
+        }
+        return body
+
+    def _handle_embed_response(self, model: str, response: Response) -> (list[list[float]], int, int):
+        data = response.json()
+        if 'error_code' in data:
+            code = data['error_code']
+            msg = data['error_msg']
+            # raise error
+            self._handle_error(code, msg)
+
+        embeddings = [v['embedding'] for v in data['data']]
+        _usage = data['usage']
+        tokens = _usage['prompt_tokens']
+        total_tokens = _usage['total_tokens']
+
+        return embeddings, tokens, total_tokens
+
+
+class WenxinTextEmbeddingModel(TextEmbeddingModel):
+    def _create_text_embedding(self, api_key: str, secret_key: str) -> TextEmbedding:
+        return WenxinTextEmbedding(api_key, secret_key)
+
+    def _invoke(self, model: str, credentials: dict, texts: list[str],
+                user: Optional[str] = None) -> TextEmbeddingResult:
+        """
+                Invoke text embedding model
+
+                :param model: model name
+                :param credentials: model credentials
+                :param texts: texts to embed
+                :param user: unique user id
+                :return: embeddings result
+                """
+
+        api_key = credentials['api_key']
+        secret_key = credentials['secret_key']
+        embedding: TextEmbedding = self._create_text_embedding(api_key, secret_key)
+        user = user if user else 'ErnieBotDefault'
+
+        context_size = self._get_context_size(model, credentials)
+        max_chunks = self._get_max_chunks(model, credentials)
+        inputs = []
+        indices = []
+        used_tokens = 0
+        used_total_tokens = 0
+
+        for i, text in enumerate(texts):
+
+            # Here token count is only an approximation based on the GPT2 tokenizer
+            num_tokens = self._get_num_tokens_by_gpt2(text)
+
+            if num_tokens >= context_size:
+                cutoff = int(np.floor(len(text) * (context_size / num_tokens)))
+                # if num tokens is larger than context length, only use the start
+                inputs.append(text[0:cutoff])
+            else:
+                inputs.append(text)
+            indices += [i]
+
+        batched_embeddings = []
+        _iter = range(0, len(inputs), max_chunks)
+        for i in _iter:
+            embeddings_batch, _used_tokens, _total_used_tokens = embedding.embed_documents(
+                model,
+                inputs[i: i + max_chunks],
+                user)
+            used_tokens += _used_tokens
+            used_total_tokens += _total_used_tokens
+            batched_embeddings += embeddings_batch
+
+        usage = self._calc_response_usage(model, credentials, used_tokens, used_total_tokens)
+        return TextEmbeddingResult(
+            model=model,
+            embeddings=batched_embeddings,
+            usage=usage,
+        )
+
+    def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
+        """
+        Get number of tokens for given prompt messages
+
+        :param model: model name
+        :param credentials: model credentials
+        :param texts: texts to embed
+        :return:
+        """
+        if len(texts) == 0:
+            return 0
+        total_num_tokens = 0
+        for text in texts:
+            total_num_tokens += self._get_num_tokens_by_gpt2(text)
+
+        return total_num_tokens
+
+    def validate_credentials(self, model: str, credentials: Mapping) -> None:
+        api_key = credentials['api_key']
+        secret_key = credentials['secret_key']
+        try:
+            BaiduAccessToken.get_access_token(api_key, secret_key)
+        except Exception as e:
+            raise CredentialsValidateFailedError(f'Credentials validation failed: {e}')
+
+    @property
+    def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+        return invoke_error_mapping()
+
+    def _calc_response_usage(self, model: str, credentials: dict, tokens: int, total_tokens: int) -> EmbeddingUsage:
+        """
+        Calculate response usage
+
+        :param model: model name
+        :param credentials: model credentials
+        :param tokens: input tokens
+        :return: usage
+        """
+        # get input price info
+        input_price_info = self.get_price(
+            model=model,
+            credentials=credentials,
+            price_type=PriceType.INPUT,
+            tokens=tokens
+        )
+
+        # transform usage
+        usage = EmbeddingUsage(
+            tokens=tokens,
+            total_tokens=total_tokens,
+            unit_price=input_price_info.unit_price,
+            price_unit=input_price_info.unit,
+            total_price=input_price_info.total_amount,
+            currency=input_price_info.currency,
+            latency=time.perf_counter() - self.started_at
+        )
+
+        return usage

api/core/model_runtime/model_providers/wenxin/wenxin.yaml

@@ -17,6 +17,7 @@ help:
     en_US: https://cloud.baidu.com/wenxin.html
 supported_model_types:
   - llm
+  - text-embedding
 configurate_methods:
   - predefined-model
 provider_credential_schema:

api/core/model_runtime/model_providers/wenxin/wenxin_errors.py

@@ -0,0 +1,57 @@
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+
+
+def invoke_error_mapping() -> dict[type[InvokeError], list[type[Exception]]]:
+    """
+    Map model invoke error to unified error
+    The key is the error type thrown to the caller
+    The value is the error type thrown by the model,
+    which needs to be converted into a unified error type for the caller.
+
+    :return: Invoke error mapping
+    """
+    return {
+        InvokeConnectionError: [
+        ],
+        InvokeServerUnavailableError: [
+            InternalServerError
+        ],
+        InvokeRateLimitError: [
+            RateLimitReachedError
+        ],
+        InvokeAuthorizationError: [
+            InvalidAuthenticationError,
+            InsufficientAccountBalance,
+            InvalidAPIKeyError,
+        ],
+        InvokeBadRequestError: [
+            BadRequestError,
+            KeyError
+        ]
+    }
+
+
+class InvalidAuthenticationError(Exception):
+    pass
+
+class InvalidAPIKeyError(Exception):
+    pass
+
+class RateLimitReachedError(Exception):
+    pass
+
+class InsufficientAccountBalance(Exception):
+    pass
+
+class InternalServerError(Exception):
+    pass
+
+class BadRequestError(Exception):
+    pass

api/core/model_runtime/model_providers/xinference/llm/llm.py

@@ -85,7 +85,8 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
             tools=tools, stop=stop, stream=stream, user=user,
             extra_model_kwargs=XinferenceHelper.get_xinference_extra_parameter(
                 server_url=credentials['server_url'],
-                model_uid=credentials['model_uid']
+                model_uid=credentials['model_uid'],
+                api_key=credentials.get('api_key'),
             )
         )
 
@@ -106,7 +107,8 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
 
             extra_param = XinferenceHelper.get_xinference_extra_parameter(
                 server_url=credentials['server_url'],
-                model_uid=credentials['model_uid']
+                model_uid=credentials['model_uid'],
+                api_key=credentials.get('api_key')
             )
             if 'completion_type' not in credentials:
                 if 'chat' in extra_param.model_ability:
@@ -396,7 +398,8 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
         else:
             extra_args = XinferenceHelper.get_xinference_extra_parameter(
                 server_url=credentials['server_url'],
-                model_uid=credentials['model_uid']
+                model_uid=credentials['model_uid'],
+                api_key=credentials.get('api_key')
             )
 
             if 'chat' in extra_args.model_ability:
@@ -464,6 +467,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
 
         xinference_client = Client(
             base_url=credentials['server_url'],
+            api_key=credentials.get('api_key'),
         )
 
         xinference_model = xinference_client.get_model(credentials['model_uid'])

api/core/model_runtime/model_providers/xinference/rerank/rerank.py

@@ -108,7 +108,8 @@ class XinferenceRerankModel(RerankModel):
 
             # initialize client
             client = Client(
-                base_url=credentials['server_url']
+                base_url=credentials['server_url'],
+                api_key=credentials.get('api_key'),
             )
 
             xinference_client = client.get_model(model_uid=credentials['model_uid'])

api/core/model_runtime/model_providers/xinference/speech2text/speech2text.py

@@ -52,7 +52,8 @@ class XinferenceSpeech2TextModel(Speech2TextModel):
 
             # initialize client
             client = Client(
-                base_url=credentials['server_url']
+                base_url=credentials['server_url'],
+                api_key=credentials.get('api_key'),
             )
 
             xinference_client = client.get_model(model_uid=credentials['model_uid'])

api/core/model_runtime/model_providers/xinference/text_embedding/text_embedding.py

@@ -110,14 +110,22 @@ class XinferenceTextEmbeddingModel(TextEmbeddingModel):
 
             server_url = credentials['server_url']
             model_uid = credentials['model_uid']
-            extra_args = XinferenceHelper.get_xinference_extra_parameter(server_url=server_url, model_uid=model_uid)
+            api_key = credentials.get('api_key')
+            extra_args = XinferenceHelper.get_xinference_extra_parameter(
+                server_url=server_url,
+                model_uid=model_uid,
+                api_key=api_key,
+            )
 
             if extra_args.max_tokens:
                 credentials['max_tokens'] = extra_args.max_tokens
             if server_url.endswith('/'):
                 server_url = server_url[:-1]
 
-            client = Client(base_url=server_url)
+            client = Client(
+                base_url=server_url,
+                api_key=api_key,
+            )
 
             try:
                 handle = client.get_model(model_uid=model_uid)

api/core/model_runtime/model_providers/xinference/tts/tts.py

@@ -81,7 +81,8 @@ class XinferenceText2SpeechModel(TTSModel):
 
             extra_param = XinferenceHelper.get_xinference_extra_parameter(
                 server_url=credentials['server_url'],
-                model_uid=credentials['model_uid']
+                model_uid=credentials['model_uid'],
+                api_key=credentials.get('api_key'),
             )
 
             if 'text-to-audio' not in extra_param.model_ability:
@@ -203,7 +204,11 @@ class XinferenceText2SpeechModel(TTSModel):
             credentials['server_url'] = credentials['server_url'][:-1]
 
         try:
-            handle = RESTfulAudioModelHandle(credentials['model_uid'], credentials['server_url'], auth_headers={})
+            api_key = credentials.get('api_key')
+            auth_headers = {'Authorization': f'Bearer {api_key}'} if api_key else {}
+            handle = RESTfulAudioModelHandle(
+                credentials['model_uid'], credentials['server_url'], auth_headers=auth_headers
+            )
 
             model_support_voice = [x.get("value") for x in
                                    self.get_tts_model_voices(model=model, credentials=credentials)]

api/core/model_runtime/model_providers/xinference/xinference_helper.py

@@ -35,13 +35,13 @@ cache_lock = Lock()
 
 class XinferenceHelper:
     @staticmethod
-    def get_xinference_extra_parameter(server_url: str, model_uid: str) -> XinferenceModelExtraParameter:
+    def get_xinference_extra_parameter(server_url: str, model_uid: str, api_key: str) -> XinferenceModelExtraParameter:
         XinferenceHelper._clean_cache()
         with cache_lock:
             if model_uid not in cache:
                 cache[model_uid] = {
                     'expires': time() + 300,
-                    'value': XinferenceHelper._get_xinference_extra_parameter(server_url, model_uid)
+                    'value': XinferenceHelper._get_xinference_extra_parameter(server_url, model_uid, api_key)
                 }
             return cache[model_uid]['value']
 
@@ -56,7 +56,7 @@ class XinferenceHelper:
             pass
 
     @staticmethod
-    def _get_xinference_extra_parameter(server_url: str, model_uid: str) -> XinferenceModelExtraParameter:
+    def _get_xinference_extra_parameter(server_url: str, model_uid: str, api_key: str) -> XinferenceModelExtraParameter:
         """
             get xinference model extra parameter like model_format and model_handle_type
         """
@@ -70,9 +70,10 @@ class XinferenceHelper:
         session = Session()
         session.mount('http://', HTTPAdapter(max_retries=3))
         session.mount('https://', HTTPAdapter(max_retries=3))
+        headers = {'Authorization': f'Bearer {api_key}'} if api_key else {}
 
         try:
-            response = session.get(url, timeout=10)
+            response = session.get(url, headers=headers, timeout=10)
         except (MissingSchema, ConnectionError, Timeout) as e:
             raise RuntimeError(f'get xinference model extra parameter failed, url: {url}, error: {e}')
         if response.status_code != 200:

api/core/provider_manager.py

@@ -5,6 +5,7 @@ from typing import Optional
 
 from sqlalchemy.exc import IntegrityError
 
+from configs import dify_config
 from core.entities.model_entities import DefaultModelEntity, DefaultModelProviderEntity
 from core.entities.provider_configuration import ProviderConfiguration, ProviderConfigurations, ProviderModelBundle
 from core.entities.provider_entities import (
@@ -18,12 +19,9 @@ from core.entities.provider_entities import (
 )
 from core.helper import encrypter
 from core.helper.model_provider_cache import ProviderCredentialsCache, ProviderCredentialsCacheType
+from core.helper.position_helper import is_filtered
 from core.model_runtime.entities.model_entities import ModelType
-from core.model_runtime.entities.provider_entities import (
-    CredentialFormSchema,
-    FormType,
-    ProviderEntity,
-)
+from core.model_runtime.entities.provider_entities import CredentialFormSchema, FormType, ProviderEntity
 from core.model_runtime.model_providers import model_provider_factory
 from extensions import ext_hosting_provider
 from extensions.ext_database import db
@@ -45,6 +43,7 @@ class ProviderManager:
     """
     ProviderManager is a class that manages the model providers includes Hosting and Customize Model Providers.
     """
+
     def __init__(self) -> None:
         self.decoding_rsa_key = None
         self.decoding_cipher_rsa = None
@@ -117,6 +116,16 @@ class ProviderManager:
 
         # Construct ProviderConfiguration objects for each provider
         for provider_entity in provider_entities:
+
+            # handle include, exclude
+            if is_filtered(
+                    include_set=dify_config.POSITION_PROVIDER_INCLUDES_SET,
+                    exclude_set=dify_config.POSITION_PROVIDER_EXCLUDES_SET,
+                    data=provider_entity,
+                    name_func=lambda x: x.provider,
+            ):
+                continue
+
             provider_name = provider_entity.provider
             provider_records = provider_name_to_provider_records_dict.get(provider_entity.provider, [])
             provider_model_records = provider_name_to_provider_model_records_dict.get(provider_entity.provider, [])
@@ -271,6 +280,24 @@ class ProviderManager:
             )
         )
 
+    def get_first_provider_first_model(self, tenant_id: str, model_type: ModelType) -> tuple[str, str]:
+        """
+        Get names of first model and its provider
+
+        :param tenant_id: workspace id
+        :param model_type: model type
+        :return: provider name, model name
+        """
+        provider_configurations = self.get_configurations(tenant_id)
+
+        # get available models from provider_configurations
+        all_models = provider_configurations.get_models(
+            model_type=model_type,
+            only_active=False
+        )
+
+        return all_models[0].provider.provider, all_models[0].model
+
     def update_default_model_record(self, tenant_id: str, model_type: ModelType, provider: str, model: str) \
             -> TenantDefaultModel:
         """
@@ -811,7 +838,7 @@ class ProviderManager:
             -> list[ModelSettings]:
         """
         Convert to model settings.
-
+        :param provider_entity: provider entity
         :param provider_model_settings: provider model settings include enabled, load balancing enabled
         :param load_balancing_model_configs: load balancing model configs
         :return:

api/core/rag/datasource/vdb/pgvector/pgvector.py

@@ -152,8 +152,27 @@ class PGVector(BaseVector):
         return docs
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
-        # do not support bm25 search
-        return []
+        top_k = kwargs.get("top_k", 5)
+
+        with self._get_cursor() as cur:
+            cur.execute(
+                f"""SELECT meta, text, ts_rank(to_tsvector(coalesce(text, '')), to_tsquery(%s)) AS score
+                FROM {self.table_name}
+                WHERE to_tsvector(text) @@ plainto_tsquery(%s)
+                ORDER BY score DESC
+                LIMIT {top_k}""",
+                # f"'{query}'" is required in order to account for whitespace in query
+                (f"'{query}'", f"'{query}'"),
+            )
+
+            docs = []
+
+            for record in cur:
+                metadata, text, score = record
+                metadata["score"] = score
+                docs.append(Document(page_content=text, metadata=metadata))
+
+        return docs
 
     def delete(self) -> None:
         with self._get_cursor() as cur:

api/core/tools/docs/zh_Hans/advanced_scale_out.md

@@ -21,6 +21,7 @@ Dify支持`文本` `链接` `图片` `文件BLOB` `JSON` 等多种消息类型
             create an image message
 
             :param image: the url of the image
+            :param save_as: save as
             :return: the image message
         """
 ```
@@ -34,6 +35,7 @@ Dify支持`文本` `链接` `图片` `文件BLOB` `JSON` 等多种消息类型
             create a link message
 
             :param link: the url of the link
+            :param save_as: save as
             :return: the link message
         """
 ```
@@ -47,6 +49,7 @@ Dify支持`文本` `链接` `图片` `文件BLOB` `JSON` 等多种消息类型
             create a text message
 
             :param text: the text of the message
+            :param save_as: save as
             :return: the text message
         """
 ```
@@ -63,6 +66,8 @@ Dify支持`文本` `链接` `图片` `文件BLOB` `JSON` 等多种消息类型
             create a blob message
 
             :param blob: the blob
+            :param meta: meta
+            :param save_as: save as
             :return: the blob message
         """
 ```

api/core/tools/provider/builtin/_positions.py

@@ -1,6 +1,6 @@
 import os.path
 
-from core.helper.position_helper import get_position_map, sort_by_position_map
+from core.helper.position_helper import get_tool_position_map, sort_by_position_map
 from core.tools.entities.api_entities import UserToolProvider
 
 
@@ -10,11 +10,11 @@ class BuiltinToolProviderSort:
     @classmethod
     def sort(cls, providers: list[UserToolProvider]) -> list[UserToolProvider]:
         if not cls._position:
-            cls._position = get_position_map(os.path.join(os.path.dirname(__file__), '..'))
+            cls._position = get_tool_position_map(os.path.join(os.path.dirname(__file__), '..'))
 
         def name_func(provider: UserToolProvider) -> str:
             return provider.name
 
         sorted_providers = sort_by_position_map(cls._position, providers, name_func)
 
-        return sorted_providers
+        return sorted_providers

api/core/tools/provider/builtin/crossref/_assets/icon.svg

@@ -0,0 +1,49 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 19.2.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 200 130.2" style="enable-background:new 0 0 200 130.2;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:#3EB1C8;}
+	.st1{fill:#D8D2C4;}
+	.st2{fill:#4F5858;}
+	.st3{fill:#FFC72C;}
+	.st4{fill:#EF3340;}
+</style>
+<g>
+	<polygon class="st0" points="111.8,95.5 111.8,66.8 135.4,59 177.2,73.3 	"/>
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+	<g>
+		<g>
+			<g>
+				<g>
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+						H26.3z"/>
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+						c-5.4,0-7.3,3.9-7.3,8.6v12.1h-7.4V102.5z"/>
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+				</g>
+			</g>
+		</g>
+	</g>
+</g>
+</svg>

api/core/tools/provider/builtin/crossref/crossref.py

@@ -0,0 +1,20 @@
+from core.tools.errors import ToolProviderCredentialValidationError
+from core.tools.provider.builtin.crossref.tools.query_doi import CrossRefQueryDOITool
+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+
+
+class CrossRefProvider(BuiltinToolProviderController):
+    def _validate_credentials(self, credentials: dict) -> None:
+        try:
+            CrossRefQueryDOITool().fork_tool_runtime(
+                runtime={
+                    "credentials": credentials,
+                }
+            ).invoke(
+                user_id='',
+                tool_parameters={
+                    "doi": '10.1007/s00894-022-05373-8',
+                },
+            )
+        except Exception as e:
+            raise ToolProviderCredentialValidationError(str(e))

api/core/tools/provider/builtin/crossref/crossref.yaml

@@ -0,0 +1,29 @@
+identity:
+  author: Sakura4036
+  name: crossref
+  label:
+    en_US: CrossRef
+    zh_Hans: CrossRef
+  description:
+    en_US: Crossref is a cross-publisher reference linking registration query system using DOI technology created in 2000. Crossref establishes cross-database links between the reference list and citation full text of papers, making it very convenient for readers to access the full text of papers.
+    zh_Hans: Crossref是于2000年创建的使用DOI技术的跨出版商参考文献链接注册查询系统。Crossref建立了在论文的参考文献列表和引文全文之间的跨数据库链接，使得读者能够非常便捷地获取文献全文。
+  icon: icon.svg
+  tags:
+    - search
+credentials_for_provider:
+  mailto:
+    type: text-input
+    required: true
+    label:
+      en_US: email address
+      zh_Hans: email地址
+      pt_BR: email address
+    placeholder:
+      en_US: Please input your email address
+      zh_Hans: 请输入你的email地址
+      pt_BR: Please input your email address
+    help:
+      en_US: According to the requirements of Crossref, an email address is required
+      zh_Hans: 根据Crossref的要求，需要提供一个邮箱地址
+      pt_BR: According to the requirements of Crossref, an email address is required
+    url: https://api.crossref.org/swagger-ui/index.html

api/core/tools/provider/builtin/crossref/tools/query_doi.py

@@ -0,0 +1,25 @@
+from typing import Any, Union
+
+import requests
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.errors import ToolParameterValidationError
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class CrossRefQueryDOITool(BuiltinTool):
+    """
+    Tool for querying the metadata of a publication using its DOI.
+    """
+    def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        doi = tool_parameters.get('doi')
+        if not doi:
+            raise ToolParameterValidationError('doi is required.')
+        # doc: https://github.com/CrossRef/rest-api-doc
+        url = f"https://api.crossref.org/works/{doi}"
+        response = requests.get(url)
+        response.raise_for_status()
+        response = response.json()
+        message = response.get('message', {})
+
+        return self.create_json_message(message)

api/core/tools/provider/builtin/crossref/tools/query_doi.yaml

@@ -0,0 +1,23 @@
+identity:
+  name: crossref_query_doi
+  author: Sakura4036
+  label:
+    en_US: CrossRef Query DOI
+    zh_Hans: CrossRef DOI 查询
+    pt_BR: CrossRef Query DOI
+description:
+  human:
+    en_US: A tool for searching literature information using CrossRef by DOI.
+    zh_Hans: 一个使用CrossRef通过DOI获取文献信息的工具。
+    pt_BR: A tool for searching literature information using CrossRef by DOI.
+  llm: A tool for searching literature information using CrossRef by DOI.
+parameters:
+  - name: doi
+    type: string
+    required: true
+    label:
+      en_US: DOI
+      zh_Hans: DOI
+      pt_BR: DOI
+    llm_description: DOI for searching in CrossRef
+    form: llm

api/core/tools/provider/builtin/crossref/tools/query_title.py

@@ -0,0 +1,120 @@
+import time
+from typing import Any, Union
+
+import requests
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+def convert_time_str_to_seconds(time_str: str) -> int:
+    """
+    Convert a time string to seconds.
+    example: 1s -> 1,  1m30s -> 90, 1h30m -> 5400, 1h30m30s -> 5430
+    """
+    time_str = time_str.lower().strip().replace(' ', '')
+    seconds = 0
+    if 'h' in time_str:
+        hours, time_str = time_str.split('h')
+        seconds += int(hours) * 3600
+    if 'm' in time_str:
+        minutes, time_str = time_str.split('m')
+        seconds += int(minutes) * 60
+    if 's' in time_str:
+        seconds += int(time_str.replace('s', ''))
+    return seconds
+
+
+class CrossRefQueryTitleAPI:
+    """
+    Tool for querying the metadata of a publication using its title.
+    Crossref API doc: https://github.com/CrossRef/rest-api-doc
+    """
+    query_url_template: str = "https://api.crossref.org/works?query.bibliographic={query}&rows={rows}&offset={offset}&sort={sort}&order={order}&mailto={mailto}"
+    rate_limit: int = 50
+    rate_interval: float = 1
+    max_limit: int = 1000
+
+    def __init__(self, mailto: str):
+        self.mailto = mailto
+
+    def _query(self, query: str, rows: int = 5, offset: int = 0, sort: str = 'relevance', order: str = 'desc', fuzzy_query: bool = False) -> list[dict]:
+        """
+        Query the metadata of a publication using its title.
+        :param query: the title of the publication
+        :param rows: the number of results to return
+        :param sort: the sort field
+        :param order: the sort order
+        :param fuzzy_query: whether to return all items that match the query
+        """
+        url = self.query_url_template.format(query=query, rows=rows, offset=offset, sort=sort, order=order, mailto=self.mailto)
+        response = requests.get(url)
+        response.raise_for_status()
+        rate_limit = int(response.headers['x-ratelimit-limit'])
+        # convert time string to seconds
+        rate_interval = convert_time_str_to_seconds(response.headers['x-ratelimit-interval'])
+
+        self.rate_limit = rate_limit
+        self.rate_interval = rate_interval
+
+        response = response.json()
+        if response['status'] != 'ok':
+            return []
+
+        message = response['message']
+        if fuzzy_query:
+            # fuzzy query return all items
+            return message['items']
+        else:
+            for paper in message['items']:
+                title = paper['title'][0]
+                if title.lower() != query.lower():
+                    continue
+                return [paper]
+        return []
+
+    def query(self, query: str, rows: int = 5, sort: str = 'relevance', order: str = 'desc', fuzzy_query: bool = False) -> list[dict]:
+        """
+        Query the metadata of a publication using its title.
+        :param query: the title of the publication
+        :param rows: the number of results to return
+        :param sort: the sort field
+        :param order: the sort order
+        :param fuzzy_query: whether to return all items that match the query
+        """
+        rows = min(rows, self.max_limit)
+        if rows > self.rate_limit:
+            # query multiple times
+            query_times = rows // self.rate_limit + 1
+            results = []
+
+            for i in range(query_times):
+                result = self._query(query, rows=self.rate_limit, offset=i * self.rate_limit, sort=sort, order=order, fuzzy_query=fuzzy_query)
+                if fuzzy_query:
+                    results.extend(result)
+                else:
+                    # fuzzy_query=False, only one result
+                    if result:
+                        return result
+                time.sleep(self.rate_interval)
+            return results
+        else:
+            # query once
+            return self._query(query, rows, sort=sort, order=order, fuzzy_query=fuzzy_query)
+
+
+class CrossRefQueryTitleTool(BuiltinTool):
+    """
+    Tool for querying the metadata of a publication using its title.
+    """
+    def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        query = tool_parameters.get('query')
+        fuzzy_query = tool_parameters.get('fuzzy_query', False)
+        rows = tool_parameters.get('rows', 3)
+        sort = tool_parameters.get('sort', 'relevance')
+        order = tool_parameters.get('order', 'desc')
+        mailto = self.runtime.credentials['mailto']
+
+        result = CrossRefQueryTitleAPI(mailto).query(query, rows, sort, order, fuzzy_query)
+
+        return [self.create_json_message(r) for r in result]

api/core/tools/provider/builtin/crossref/tools/query_title.yaml

@@ -0,0 +1,105 @@
+identity:
+  name: crossref_query_title
+  author: Sakura4036
+  label:
+    en_US: CrossRef Title Query
+    zh_Hans: CrossRef 标题查询
+    pt_BR: CrossRef Title Query
+description:
+  human:
+    en_US: A tool for querying literature information using CrossRef by title.
+    zh_Hans: 一个使用CrossRef通过标题搜索文献信息的工具。
+    pt_BR: A tool for querying literature information using CrossRef by title.
+  llm: A tool for querying literature information using CrossRef by title.
+parameters:
+  - name: query
+    type: string
+    required: true
+    label:
+      en_US: 标题
+      zh_Hans: 查询语句
+      pt_BR: 标题
+    human_description:
+      en_US: Query bibliographic information, useful for citation look up. Includes titles, authors, ISSNs and publication years
+      zh_Hans: 用于搜索文献信息，有助于查找引用。包括标题，作者，ISSN和出版年份
+      pt_BR: Query bibliographic information, useful for citation look up. Includes titles, authors, ISSNs and publication years
+    llm_description: key words for querying in Web of Science
+    form: llm
+  - name: fuzzy_query
+    type: boolean
+    default: false
+    label:
+      en_US: Whether to fuzzy search
+      zh_Hans: 是否模糊搜索
+      pt_BR: Whether to fuzzy search
+    human_description:
+      en_US: used for selecting the query type, fuzzy query returns more results, precise query returns 1 or none
+      zh_Hans: 用于选择搜索类型，模糊搜索返回更多结果，精确搜索返回1条结果或无
+      pt_BR: used for selecting the query type, fuzzy query returns more results, precise query returns 1 or none
+    form: form
+  - name: limit
+    type: number
+    required: false
+    label:
+      en_US: max query number
+      zh_Hans: 最大搜索数
+      pt_BR: max query number
+    human_description:
+      en_US: max query number(fuzzy search returns the maximum number of results or precise search the maximum number of matches)
+      zh_Hans: 最大搜索数(模糊搜索返回的最大结果数或精确搜索最大匹配数)
+      pt_BR: max query number(fuzzy search returns the maximum number of results or precise search the maximum number of matches)
+    form: llm
+    default: 50
+  - name: sort
+    type: select
+    required: true
+    options:
+      - value: relevance
+        label:
+          en_US: relevance
+          zh_Hans: 相关性
+          pt_BR: relevance
+      - value: published
+        label:
+          en_US: publication date
+          zh_Hans: 出版日期
+          pt_BR: publication date
+      - value: references-count
+        label:
+          en_US: references-count
+          zh_Hans: 引用次数
+          pt_BR: references-count
+    default: relevance
+    label:
+      en_US: sorting field
+      zh_Hans: 排序字段
+      pt_BR: sorting field
+    human_description:
+      en_US: Sorting of query results
+      zh_Hans: 检索结果的排序字段
+      pt_BR: Sorting of query results
+    form: form
+  - name: order
+    type: select
+    required: true
+    options:
+      - value: desc
+        label:
+          en_US: descending
+          zh_Hans: 降序
+          pt_BR: descending
+      - value: asc
+        label:
+          en_US: ascending
+          zh_Hans: 升序
+          pt_BR: ascending
+    default: desc
+    label:
+      en_US: Order
+      zh_Hans: 排序
+      pt_BR: Order
+    human_description:
+      en_US: Order of query results
+      zh_Hans: 检索结果的排序方式
+      pt_BR: Order of query results
+    form: form

api/core/tools/provider/builtin/gitlab/gitlab.py

@@ -29,6 +29,6 @@ class GitlabProvider(BuiltinToolProviderController):
                 if response.status_code != 200:
                     raise ToolProviderCredentialValidationError((response.json()).get('message'))
             except Exception as e:
-                raise ToolProviderCredentialValidationError("Gitlab Access Tokens and Api Version is invalid. {}".format(e))
+                raise ToolProviderCredentialValidationError("Gitlab Access Tokens is invalid. {}".format(e))
         except Exception as e:
             raise ToolProviderCredentialValidationError(str(e))

api/core/tools/provider/builtin/gitlab/gitlab.yaml

@@ -2,37 +2,37 @@ identity:
   author: Leo.Wang
   name: gitlab
   label:
-    en_US: Gitlab
-    zh_Hans: Gitlab
+    en_US: GitLab
+    zh_Hans: GitLab
   description:
-    en_US: Gitlab plugin for commit
-    zh_Hans: 用于获取Gitlab commit的插件
+    en_US: GitLab plugin, API v4 only.
+    zh_Hans: 用于获取GitLab内容的插件，目前仅支持 API v4。
   icon: gitlab.svg
 credentials_for_provider:
   access_tokens:
     type: secret-input
     required: true
     label:
-      en_US: Gitlab access token
-      zh_Hans: Gitlab access token
+      en_US: GitLab access token
+      zh_Hans: GitLab access token
     placeholder:
-      en_US: Please input your Gitlab access token
-      zh_Hans: 请输入你的 Gitlab access token
+      en_US: Please input your GitLab access token
+      zh_Hans: 请输入你的 GitLab access token
     help:
-      en_US: Get your Gitlab access token from Gitlab
-      zh_Hans: 从 Gitlab 获取您的 access token
+      en_US: Get your GitLab access token from GitLab
+      zh_Hans: 从 GitLab 获取您的 access token
     url: https://docs.gitlab.com/16.9/ee/api/oauth2.html
   site_url:
     type: text-input
     required: false
     default: 'https://gitlab.com'
     label:
-      en_US: Gitlab site url
-      zh_Hans: Gitlab site url
+      en_US: GitLab site url
+      zh_Hans: GitLab site url
     placeholder:
-      en_US: Please input your Gitlab site url
-      zh_Hans: 请输入你的 Gitlab site url
+      en_US: Please input your GitLab site url
+      zh_Hans: 请输入你的 GitLab site url
     help:
-      en_US: Find your Gitlab url
-      zh_Hans: 找到你的Gitlab url
+      en_US: Find your GitLab url
+      zh_Hans: 找到你的 GitLab url
     url: https://gitlab.com/help

api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.py

@@ -18,6 +18,7 @@ class GitlabCommitsTool(BuiltinTool):
         employee = tool_parameters.get('employee', '')
         start_time = tool_parameters.get('start_time', '')
         end_time = tool_parameters.get('end_time', '')
+        change_type = tool_parameters.get('change_type', 'all')
 
         if not project:
             return self.create_text_message('Project is required')
@@ -36,11 +37,11 @@ class GitlabCommitsTool(BuiltinTool):
             site_url = 'https://gitlab.com'
         
         # Get commit content
-        result = self.fetch(user_id, site_url, access_token, project, employee, start_time, end_time)
+        result = self.fetch(user_id, site_url, access_token, project, employee, start_time, end_time, change_type)
 
-        return self.create_text_message(json.dumps(result, ensure_ascii=False))
+        return [self.create_json_message(item) for item in result]
     
-    def fetch(self,user_id: str, site_url: str, access_token: str, project: str, employee: str = None, start_time: str = '', end_time: str = '') -> list[dict[str, Any]]:
+    def fetch(self,user_id: str, site_url: str, access_token: str, project: str, employee: str = None, start_time: str = '', end_time: str = '', change_type: str = '') -> list[dict[str, Any]]:
         domain = site_url
         headers = {"PRIVATE-TOKEN": access_token}
         results = []
@@ -74,7 +75,7 @@ class GitlabCommitsTool(BuiltinTool):
 
                 for commit in commits:
                     commit_sha = commit['id']
-                    print(f"\tCommit SHA: {commit_sha}")
+                    author_name = commit['author_name']
 
                     diff_url = f"{domain}/api/v4/projects/{project_id}/repository/commits/{commit_sha}/diff"
                     diff_response = requests.get(diff_url, headers=headers)
@@ -87,14 +88,23 @@ class GitlabCommitsTool(BuiltinTool):
                         removed_lines = diff['diff'].count('\n-')
                         total_changes = added_lines + removed_lines
 
-                        if total_changes > 1:
-                            final_code = ''.join([line[1:] for line in diff['diff'].split('\n') if line.startswith('+') and not line.startswith('+++')])
-                            results.append({
-                                "project": project_name,
-                                "commit_sha": commit_sha,
-                                "diff": final_code
-                            })
-                            print(f"Commit code:{final_code}")
+                        if change_type == "new":
+                            if added_lines > 1:
+                                final_code = ''.join([line[1:] for line in diff['diff'].split('\n') if line.startswith('+') and not line.startswith('+++')])
+                                results.append({
+                                    "commit_sha": commit_sha,
+                                    "author_name": author_name,
+                                    "diff": final_code
+                                })
+                        else:
+                            if total_changes > 1:
+                                final_code = ''.join([line[1:] for line in diff['diff'].split('\n') if (line.startswith('+') or line.startswith('-')) and not line.startswith('+++') and not line.startswith('---')])
+                                final_code_escaped = json.dumps(final_code)[1:-1]  # Escape the final code
+                                results.append({
+                                    "commit_sha": commit_sha,
+                                    "author_name": author_name,
+                                    "diff": final_code_escaped
+                                })
         except requests.RequestException as e:
             print(f"Error fetching data from GitLab: {e}")
         

api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.yaml

@@ -2,24 +2,24 @@ identity:
   name: gitlab_commits
   author: Leo.Wang
   label:
-    en_US: Gitlab Commits
-    zh_Hans: Gitlab代码提交内容
+    en_US: GitLab Commits
+    zh_Hans: GitLab 提交内容查询
 description:
   human:
-    en_US: A tool for query gitlab commits. Input should be a exists username.
-    zh_Hans: 一个用于查询gitlab代码提交记录的的工具，输入的内容应该是一个已存在的用户名或者项目名。
-  llm: A tool for query gitlab commits. Input should be a exists username or project.
+    en_US: A tool for query GitLab commits, Input should be a exists username or projec.
+    zh_Hans: 一个用于查询 GitLab 代码提交内容的工具，输入的内容应该是一个已存在的用户名或者项目名。
+  llm: A tool for query GitLab commits, Input should be a exists username or project.
 parameters:
-  - name: employee
+  - name: username
     type: string
     required: false
     label:
-      en_US: employee
+      en_US: username
       zh_Hans: 员工用户名
     human_description:
-      en_US: employee
+      en_US: username
       zh_Hans: 员工用户名
-    llm_description: employee for gitlab
+    llm_description: User name for GitLab
     form: llm
   - name: project
     type: string
@@ -30,7 +30,7 @@ parameters:
     human_description:
       en_US: project
       zh_Hans: 项目名
-    llm_description: project for gitlab
+    llm_description: project for GitLab
     form: llm
   - name: start_time
     type: string
@@ -41,7 +41,7 @@ parameters:
     human_description:
       en_US: start_time
       zh_Hans: 开始时间
-    llm_description: start_time for gitlab
+    llm_description: Start time for GitLab
     form: llm
   - name: end_time
     type: string
@@ -52,5 +52,26 @@ parameters:
     human_description:
       en_US: end_time
       zh_Hans: 结束时间
-    llm_description: end_time for gitlab
+    llm_description: End time for GitLab
+    form: llm
+  - name: change_type
+    type: select
+    required: false
+    options:
+      - value: all
+        label:
+          en_US: all
+          zh_Hans: 所有
+      - value: new
+        label:
+          en_US: new
+          zh_Hans: 新增
+    default: all
+    label:
+      en_US: change_type
+      zh_Hans: 变更类型
+    human_description:
+      en_US: change_type
+      zh_Hans: 变更类型
+    llm_description: Content change type for GitLab
     form: llm

api/core/tools/provider/builtin/gitlab/tools/gitlab_files.py

@@ -0,0 +1,95 @@
+from typing import Any, Union
+
+import requests
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class GitlabFilesTool(BuiltinTool):
+    def _invoke(self, 
+                user_id: str,
+                tool_parameters: dict[str, Any]
+        ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        
+        project = tool_parameters.get('project', '')
+        branch = tool_parameters.get('branch', '')
+        path = tool_parameters.get('path', '')
+
+
+        if not project:
+            return self.create_text_message('Project is required')
+        if not branch:
+            return self.create_text_message('Branch is required')
+
+        if not path:
+            return self.create_text_message('Path is required')
+
+        access_token = self.runtime.credentials.get('access_tokens')
+        site_url = self.runtime.credentials.get('site_url')
+
+        if 'access_tokens' not in self.runtime.credentials or not self.runtime.credentials.get('access_tokens'):
+            return self.create_text_message("Gitlab API Access Tokens is required.")
+        if 'site_url' not in self.runtime.credentials or not self.runtime.credentials.get('site_url'):
+            site_url = 'https://gitlab.com'
+    
+        # Get project ID from project name
+        project_id = self.get_project_id(site_url, access_token, project)
+        if not project_id:
+            return self.create_text_message(f"Project '{project}' not found.")
+
+        # Get commit content
+        result = self.fetch(user_id, project_id, site_url, access_token, branch, path)
+
+        return [self.create_json_message(item) for item in result]
+    
+    def extract_project_name_and_path(self, path: str) -> tuple[str, str]:
+        parts = path.split('/', 1)
+        if len(parts) < 2:
+            return None, None
+        return parts[0], parts[1]
+
+    def get_project_id(self, site_url: str, access_token: str, project_name: str) -> Union[str, None]:
+        headers = {"PRIVATE-TOKEN": access_token}
+        try:
+            url = f"{site_url}/api/v4/projects?search={project_name}"
+            response = requests.get(url, headers=headers)
+            response.raise_for_status()
+            projects = response.json()
+            for project in projects:
+                if project['name'] == project_name:
+                    return project['id']
+        except requests.RequestException as e:
+            print(f"Error fetching project ID from GitLab: {e}")
+        return None
+    
+    def fetch(self,user_id: str, project_id: str, site_url: str, access_token: str, branch: str, path: str = None) -> list[dict[str, Any]]:
+        domain = site_url
+        headers = {"PRIVATE-TOKEN": access_token}
+        results = []
+
+        try:
+            # List files and directories in the given path
+            url = f"{domain}/api/v4/projects/{project_id}/repository/tree?path={path}&ref={branch}"
+            response = requests.get(url, headers=headers)
+            response.raise_for_status()
+            items = response.json()
+
+            for item in items:
+                item_path = item['path']
+                if item['type'] == 'tree':  # It's a directory
+                    results.extend(self.fetch(project_id, site_url, access_token, branch, item_path))
+                else:  # It's a file
+                    file_url = f"{domain}/api/v4/projects/{project_id}/repository/files/{item_path}/raw?ref={branch}"
+                    file_response = requests.get(file_url, headers=headers)
+                    file_response.raise_for_status()
+                    file_content = file_response.text
+                    results.append({
+                        "path": item_path,
+                        "branch": branch,
+                        "content": file_content
+                    })
+        except requests.RequestException as e:
+            print(f"Error fetching data from GitLab: {e}")
+        
+        return results

api/core/tools/provider/builtin/gitlab/tools/gitlab_files.yaml

@@ -0,0 +1,45 @@
+identity:
+  name: gitlab_files
+  author: Leo.Wang
+  label:
+    en_US: GitLab Files
+    zh_Hans: GitLab 文件获取
+description:
+  human:
+    en_US: A tool for query GitLab files, Input should be branch and a exists file or directory path.
+    zh_Hans: 一个用于查询 GitLab 文件的工具，输入的内容应该是分支和一个已存在文件或者文件夹路径。
+  llm: A tool for query GitLab files, Input should be a exists file or directory path.
+parameters:
+  - name: project
+    type: string
+    required: true
+    label:
+      en_US: project
+      zh_Hans: 项目
+    human_description:
+      en_US: project
+      zh_Hans: 项目
+    llm_description: Project for GitLab
+    form: llm
+  - name: branch
+    type: string
+    required: true
+    label:
+      en_US: branch
+      zh_Hans: 分支
+    human_description:
+      en_US: branch
+      zh_Hans: 分支
+    llm_description: Branch for GitLab
+    form: llm
+  - name: path
+    type: string
+    required: true
+    label:
+      en_US: path
+      zh_Hans: 文件路径
+    human_description:
+      en_US: path
+      zh_Hans: 文件路径
+    llm_description: File path for GitLab
+    form: llm

api/core/tools/provider/builtin/jina/tools/jina_tokenizer.py

@@ -0,0 +1,43 @@
+from typing import Any
+
+from core.helper import ssrf_proxy
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class JinaTokenizerTool(BuiltinTool):
+    _jina_tokenizer_endpoint = 'https://tokenize.jina.ai/'
+
+    def _invoke(
+        self,
+        user_id: str,
+        tool_parameters: dict[str, Any],
+    ) -> ToolInvokeMessage:
+        content = tool_parameters['content']
+        body = {
+            "content": content
+        }
+
+        headers = {
+            'Content-Type': 'application/json'
+        }
+
+        if 'api_key' in self.runtime.credentials and self.runtime.credentials.get('api_key'):
+            headers['Authorization'] = "Bearer " + self.runtime.credentials.get('api_key')
+
+        if tool_parameters.get('return_chunks', False):
+            body['return_chunks'] = True
+        
+        if tool_parameters.get('return_tokens', False):
+            body['return_tokens'] = True
+        
+        if tokenizer := tool_parameters.get('tokenizer'):
+            body['tokenizer'] = tokenizer
+
+        response = ssrf_proxy.post(
+            self._jina_tokenizer_endpoint,
+            headers=headers,
+            json=body,
+        )
+
+        return self.create_json_message(response.json())

api/core/tools/provider/builtin/jina/tools/jina_tokenizer.yaml

@@ -0,0 +1,70 @@
+identity:
+  name: jina_tokenizer
+  author: hjlarry
+  label:
+    en_US: JinaTokenizer
+description:
+  human:
+    en_US: Free API to tokenize text and segment long text into chunks.
+    zh_Hans: 免费的API可以将文本tokenize，也可以将长文本分割成多个部分。
+  llm: Free API to tokenize text and segment long text into chunks.
+parameters:
+  - name: content
+    type: string
+    required: true
+    label:
+      en_US: Content
+      zh_Hans: 内容
+    llm_description: the content which need to tokenize or segment
+    form: llm
+  - name: return_tokens
+    type: boolean
+    required: false
+    label:
+      en_US: Return the tokens
+      zh_Hans: 是否返回tokens
+    human_description:
+      en_US: Return the tokens and their corresponding ids in the response.
+      zh_Hans: 返回tokens及其对应的ids。
+    form: form
+  - name: return_chunks
+    type: boolean
+    label:
+      en_US: Return the chunks
+      zh_Hans: 是否分块
+    human_description:
+      en_US: Chunking the input into semantically meaningful segments while handling a wide variety of text types and edge cases based on common structural cues.
+      zh_Hans: 将输入分块为具有语义意义的片段，同时根据常见的结构线索处理各种文本类型和边缘情况。
+    form: form
+  - name: tokenizer
+    type: select
+    options:
+      - value: cl100k_base
+        label:
+          en_US: cl100k_base
+      - value: o200k_base
+        label:
+          en_US: o200k_base
+      - value: p50k_base
+        label:
+          en_US: p50k_base
+      - value: r50k_base
+        label:
+          en_US: r50k_base
+      - value: p50k_edit
+        label:
+          en_US: p50k_edit
+      - value: gpt2
+        label:
+          en_US: gpt2
+    label:
+      en_US: Tokenizer
+    human_description:
+      en_US: |
+        · cl100k_base --- gpt-4, gpt-3.5-turbo, gpt-3.5
+        · o200k_base  --- gpt-4o, gpt-4o-mini
+        · p50k_base   --- text-davinci-003, text-davinci-002
+        · r50k_base   --- text-davinci-001, text-curie-001
+        · p50k_edit   --- text-davinci-edit-001, code-davinci-edit-001
+        · gpt2        --- gpt-2
+    form: form

api/core/tools/provider/builtin/novitaai/_novita_tool_base.py

@@ -0,0 +1,73 @@
+from novita_client import (
+    Txt2ImgV3Embedding,
+    Txt2ImgV3HiresFix,
+    Txt2ImgV3LoRA,
+    Txt2ImgV3Refiner,
+    V3TaskImage,
+)
+
+
+class NovitaAiToolBase:
+    def _extract_loras(self, loras_str: str):
+        if not loras_str:
+            return []
+
+        loras_ori_list = lora_str.strip().split(';')
+        result_list = []
+        for lora_str in loras_ori_list:
+            lora_info = lora_str.strip().split(',')
+            lora = Txt2ImgV3LoRA(
+                model_name=lora_info[0].strip(),
+                strength=float(lora_info[1]),
+            )
+            result_list.append(lora)
+
+        return result_list
+
+    def _extract_embeddings(self, embeddings_str: str):
+        if not embeddings_str:
+            return []
+
+        embeddings_ori_list = embeddings_str.strip().split(';')
+        result_list = []
+        for embedding_str in embeddings_ori_list:
+            embedding = Txt2ImgV3Embedding(
+                model_name=embedding_str.strip()
+            )
+            result_list.append(embedding)
+
+        return result_list
+
+    def _extract_hires_fix(self, hires_fix_str: str):
+        hires_fix_info = hires_fix_str.strip().split(',')
+        if 'upscaler' in hires_fix_info:
+            hires_fix = Txt2ImgV3HiresFix(
+                target_width=int(hires_fix_info[0]),
+                target_height=int(hires_fix_info[1]),
+                strength=float(hires_fix_info[2]),
+                upscaler=hires_fix_info[3].strip()
+            )
+        else:
+            hires_fix = Txt2ImgV3HiresFix(
+                target_width=int(hires_fix_info[0]),
+                target_height=int(hires_fix_info[1]),
+                strength=float(hires_fix_info[2])
+            )
+
+        return hires_fix
+
+    def _extract_refiner(self, switch_at: str):
+        refiner = Txt2ImgV3Refiner(
+            switch_at=float(switch_at)
+        )
+        return refiner
+
+    def _is_hit_nsfw_detection(self, image: V3TaskImage, confidence_threshold: float) -> bool:
+        """
+            is hit nsfw
+        """
+        if image.nsfw_detection_result is None:
+            return False
+        if image.nsfw_detection_result.valid and image.nsfw_detection_result.confidence >= confidence_threshold:
+            return True
+        return False

api/core/tools/provider/builtin/novitaai/tools/novitaai_txt2img.py

@@ -4,19 +4,15 @@ from typing import Any, Union
 
 from novita_client import (
     NovitaClient,
-    Txt2ImgV3Embedding,
-    Txt2ImgV3HiresFix,
-    Txt2ImgV3LoRA,
-    Txt2ImgV3Refiner,
-    V3TaskImage,
 )
 
 from core.tools.entities.tool_entities import ToolInvokeMessage
 from core.tools.errors import ToolProviderCredentialValidationError
+from core.tools.provider.builtin.novitaai._novita_tool_base import NovitaAiToolBase
 from core.tools.tool.builtin_tool import BuiltinTool
 
 
-class NovitaAiTxt2ImgTool(BuiltinTool):
+class NovitaAiTxt2ImgTool(BuiltinTool, NovitaAiToolBase):
     def _invoke(self,
                 user_id: str,
                 tool_parameters: dict[str, Any],
@@ -73,65 +69,19 @@ class NovitaAiTxt2ImgTool(BuiltinTool):
 
         # process loras
         if 'loras' in res_parameters:
-            loras_ori_list = res_parameters.get('loras').strip().split(';')
-            locals_list = []
-            for lora_str in loras_ori_list:
-                lora_info = lora_str.strip().split(',')
-                lora = Txt2ImgV3LoRA(
-                    model_name=lora_info[0].strip(),
-                    strength=float(lora_info[1]),
-                )
-                locals_list.append(lora)
-
-            res_parameters['loras'] = locals_list
+            res_parameters['loras'] = self._extract_loras(res_parameters.get('loras'))
 
         # process embeddings
         if 'embeddings' in res_parameters:
-            embeddings_ori_list = res_parameters.get('embeddings').strip().split(';')
-            locals_list = []
-            for embedding_str in embeddings_ori_list:
-                embedding = Txt2ImgV3Embedding(
-                    model_name=embedding_str.strip()
-                )
-                locals_list.append(embedding)
-
-            res_parameters['embeddings'] = locals_list
+            res_parameters['embeddings'] = self._extract_embeddings(res_parameters.get('embeddings'))
 
         # process hires_fix
         if 'hires_fix' in res_parameters:
-            hires_fix_ori = res_parameters.get('hires_fix')
-            hires_fix_info = hires_fix_ori.strip().split(',')
-            if 'upscaler' in hires_fix_info:
-                hires_fix = Txt2ImgV3HiresFix(
-                    target_width=int(hires_fix_info[0]),
-                    target_height=int(hires_fix_info[1]),
-                    strength=float(hires_fix_info[2]),
-                    upscaler=hires_fix_info[3].strip()
-                )
-            else:
-                hires_fix = Txt2ImgV3HiresFix(
-                    target_width=int(hires_fix_info[0]),
-                    target_height=int(hires_fix_info[1]),
-                    strength=float(hires_fix_info[2])
-                )
+            res_parameters['hires_fix'] = self._extract_hires_fix(res_parameters.get('hires_fix'))
 
-            res_parameters['hires_fix'] = hires_fix
-
-            if 'refiner_switch_at' in res_parameters:
-                refiner = Txt2ImgV3Refiner(
-                    switch_at=float(res_parameters.get('refiner_switch_at'))
-                )
-                del res_parameters['refiner_switch_at']
-                res_parameters['refiner'] = refiner
+        # process refiner
+        if 'refiner_switch_at' in res_parameters:
+            res_parameters['refiner'] = self._extract_refiner(res_parameters.get('refiner_switch_at'))
+            del res_parameters['refiner_switch_at']
 
         return res_parameters
-
-    def _is_hit_nsfw_detection(self, image: V3TaskImage, confidence_threshold: float) -> bool:
-        """
-            is hit nsfw
-        """
-        if image.nsfw_detection_result is None:
-            return False
-        if image.nsfw_detection_result.valid and image.nsfw_detection_result.confidence >= confidence_threshold:
-            return True
-        return False

api/core/tools/provider/workflow_tool_provider.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from core.app.app_config.entities import VariableEntity
+from core.app.app_config.entities import VariableEntity, VariableEntityType
 from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
 from core.tools.entities.common_entities import I18nObject
 from core.tools.entities.tool_entities import (
@@ -18,6 +18,13 @@ from models.model import App, AppMode
 from models.tools import WorkflowToolProvider
 from models.workflow import Workflow
 
+VARIABLE_TO_PARAMETER_TYPE_MAPPING = {
+    VariableEntityType.TEXT_INPUT: ToolParameter.ToolParameterType.STRING,
+    VariableEntityType.PARAGRAPH: ToolParameter.ToolParameterType.STRING,
+    VariableEntityType.SELECT: ToolParameter.ToolParameterType.SELECT,
+    VariableEntityType.NUMBER: ToolParameter.ToolParameterType.NUMBER,
+}
+
 
 class WorkflowToolProviderController(ToolProviderController):
     provider_id: str
@@ -28,7 +35,7 @@ class WorkflowToolProviderController(ToolProviderController):
 
         if not app:
             raise ValueError('app not found')
-        
+
         controller = WorkflowToolProviderController(**{
             'identity': {
                 'author': db_provider.user.name if db_provider.user_id and db_provider.user else '',
@@ -46,7 +53,7 @@ class WorkflowToolProviderController(ToolProviderController):
             'credentials_schema': {},
             'provider_id': db_provider.id or '',
         })
-        
+
         # init tools
 
         controller.tools = [controller._get_db_provider_tool(db_provider, app)]
@@ -56,7 +63,7 @@ class WorkflowToolProviderController(ToolProviderController):
     @property
     def provider_type(self) -> ToolProviderType:
         return ToolProviderType.WORKFLOW
-    
+
     def _get_db_provider_tool(self, db_provider: WorkflowToolProvider, app: App) -> WorkflowTool:
         """
             get db provider tool
@@ -93,23 +100,11 @@ class WorkflowToolProviderController(ToolProviderController):
             if variable:
                 parameter_type = None
                 options = None
-                if variable.type in [
-                    VariableEntity.Type.TEXT_INPUT, 
-                    VariableEntity.Type.PARAGRAPH, 
-                ]:
-                    parameter_type = ToolParameter.ToolParameterType.STRING
-                elif variable.type in [
-                    VariableEntity.Type.SELECT
-                ]:
-                    parameter_type = ToolParameter.ToolParameterType.SELECT
-                elif variable.type in [
-                    VariableEntity.Type.NUMBER
-                ]:
-                    parameter_type = ToolParameter.ToolParameterType.NUMBER
-                else:
+                if variable.type not in VARIABLE_TO_PARAMETER_TYPE_MAPPING:
                     raise ValueError(f'unsupported variable type {variable.type}')
-                
-                if variable.type == VariableEntity.Type.SELECT and variable.options:
+                parameter_type = VARIABLE_TO_PARAMETER_TYPE_MAPPING[variable.type]
+
+                if variable.type == VariableEntityType.SELECT and variable.options:
                     options = [
                         ToolParameterOption(
                             value=option,
@@ -200,7 +195,7 @@ class WorkflowToolProviderController(ToolProviderController):
         """
         if self.tools is not None:
             return self.tools
-        
+
         db_providers: WorkflowToolProvider = db.session.query(WorkflowToolProvider).filter(
             WorkflowToolProvider.tenant_id == tenant_id,
             WorkflowToolProvider.app_id == self.provider_id,
@@ -208,11 +203,11 @@ class WorkflowToolProviderController(ToolProviderController):
 
         if not db_providers:
             return []
-        
+
         self.tools = [self._get_db_provider_tool(db_providers, db_providers.app)]
 
         return self.tools
-    
+
     def get_tool(self, tool_name: str) -> Optional[WorkflowTool]:
         """
             get tool by name
@@ -226,5 +221,5 @@ class WorkflowToolProviderController(ToolProviderController):
         for tool in self.tools:
             if tool.identity.name == tool_name:
                 return tool
-        
+
         return None

api/core/tools/tool_manager.py

@@ -10,14 +10,11 @@ from configs import dify_config
 from core.agent.entities import AgentToolEntity
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.helper.module_import_helper import load_single_subclass_from_source
+from core.helper.position_helper import is_filtered
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.tools.entities.api_entities import UserToolProvider, UserToolProviderTypeLiteral
 from core.tools.entities.common_entities import I18nObject
-from core.tools.entities.tool_entities import (
-    ApiProviderAuthType,
-    ToolInvokeFrom,
-    ToolParameter,
-)
+from core.tools.entities.tool_entities import ApiProviderAuthType, ToolInvokeFrom, ToolParameter
 from core.tools.errors import ToolProviderNotFoundError
 from core.tools.provider.api_tool_provider import ApiToolProviderController
 from core.tools.provider.builtin._positions import BuiltinToolProviderSort
@@ -26,10 +23,7 @@ from core.tools.tool.api_tool import ApiTool
 from core.tools.tool.builtin_tool import BuiltinTool
 from core.tools.tool.tool import Tool
 from core.tools.tool_label_manager import ToolLabelManager
-from core.tools.utils.configuration import (
-    ToolConfigurationManager,
-    ToolParameterConfigurationManager,
-)
+from core.tools.utils.configuration import ToolConfigurationManager, ToolParameterConfigurationManager
 from core.tools.utils.tool_parameter_converter import ToolParameterConverter
 from extensions.ext_database import db
 from models.tools import ApiToolProvider, BuiltinToolProvider, WorkflowToolProvider
@@ -37,6 +31,7 @@ from services.tools.tools_transform_service import ToolTransformService
 
 logger = logging.getLogger(__name__)
 
+
 class ToolManager:
     _builtin_provider_lock = Lock()
     _builtin_providers = {}
@@ -106,7 +101,7 @@ class ToolManager:
                          tenant_id: str,
                          invoke_from: InvokeFrom = InvokeFrom.DEBUGGER,
                          tool_invoke_from: ToolInvokeFrom = ToolInvokeFrom.AGENT) \
-        -> Union[BuiltinTool, ApiTool]:
+            -> Union[BuiltinTool, ApiTool]:
         """
             get the tool runtime
 
@@ -345,7 +340,7 @@ class ToolManager:
                     provider_class = load_single_subclass_from_source(
                         module_name=f'core.tools.provider.builtin.{provider}.{provider}',
                         script_path=path.join(path.dirname(path.realpath(__file__)),
-                                            'provider', 'builtin', provider, f'{provider}.py'),
+                                              'provider', 'builtin', provider, f'{provider}.py'),
                         parent_type=BuiltinToolProviderController)
                     provider: BuiltinToolProviderController = provider_class()
                     cls._builtin_providers[provider.identity.name] = provider
@@ -413,6 +408,15 @@ class ToolManager:
 
             # append builtin providers
             for provider in builtin_providers:
+                # handle include, exclude
+                if is_filtered(
+                        include_set=dify_config.POSITION_TOOL_INCLUDES_SET,
+                        exclude_set=dify_config.POSITION_TOOL_EXCLUDES_SET,
+                        data=provider,
+                        name_func=lambda x: x.identity.name
+                ):
+                    continue
+
                 user_provider = ToolTransformService.builtin_provider_to_user_provider(
                     provider_controller=provider,
                     db_provider=find_db_builtin_provider(provider.identity.name),
@@ -472,7 +476,7 @@ class ToolManager:
 
     @classmethod
     def get_api_provider_controller(cls, tenant_id: str, provider_id: str) -> tuple[
-        ApiToolProviderController, dict[str, Any]]:
+            ApiToolProviderController, dict[str, Any]]:
         """
             get the api provider
 
@@ -592,4 +596,5 @@ class ToolManager:
         else:
             raise ValueError(f"provider type {provider_type} not found")
 
+
 ToolManager.load_builtin_providers_cache()

api/core/workflow/entities/variable_pool.py

@@ -7,14 +7,14 @@ from typing_extensions import deprecated
 
 from core.app.segments import Segment, Variable, factory
 from core.file.file_obj import FileVar
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 
 VariableValue = Union[str, int, float, dict, list, FileVar]
 
 
-SYSTEM_VARIABLE_NODE_ID = 'sys'
-ENVIRONMENT_VARIABLE_NODE_ID = 'env'
-CONVERSATION_VARIABLE_NODE_ID = 'conversation'
+SYSTEM_VARIABLE_NODE_ID = "sys"
+ENVIRONMENT_VARIABLE_NODE_ID = "env"
+CONVERSATION_VARIABLE_NODE_ID = "conversation"
 
 
 class VariablePool(BaseModel):
@@ -32,7 +32,7 @@ class VariablePool(BaseModel):
         description='User inputs',
     )
 
-    system_variables: Mapping[SystemVariable, Any] = Field(
+    system_variables: Mapping[SystemVariableKey, Any] = Field(
         description='System variables',
     )
 
@@ -78,7 +78,7 @@ class VariablePool(BaseModel):
             None
         """
         if len(selector) < 2:
-            raise ValueError('Invalid selector')
+            raise ValueError("Invalid selector")
 
         if value is None:
             return
@@ -105,13 +105,13 @@ class VariablePool(BaseModel):
             ValueError: If the selector is invalid.
         """
         if len(selector) < 2:
-            raise ValueError('Invalid selector')
+            raise ValueError("Invalid selector")
         hash_key = hash(tuple(selector[1:]))
         value = self.variable_dictionary[selector[0]].get(hash_key)
 
         return value
 
-    @deprecated('This method is deprecated, use `get` instead.')
+    @deprecated("This method is deprecated, use `get` instead.")
     def get_any(self, selector: Sequence[str], /) -> Any | None:
         """
         Retrieves the value from the variable pool based on the given selector.
@@ -126,7 +126,7 @@ class VariablePool(BaseModel):
             ValueError: If the selector is invalid.
         """
         if len(selector) < 2:
-            raise ValueError('Invalid selector')
+            raise ValueError("Invalid selector")
         hash_key = hash(tuple(selector[1:]))
         value = self.variable_dictionary[selector[0]].get(hash_key)
         return value.to_object() if value else None

api/core/workflow/enums.py

@@ -1,25 +1,13 @@
 from enum import Enum
 
 
-class SystemVariable(str, Enum):
+class SystemVariableKey(str, Enum):
     """
     System Variables.
     """
-    QUERY = 'query'
-    FILES = 'files'
-    CONVERSATION_ID = 'conversation_id'
-    USER_ID = 'user_id'
-    DIALOGUE_COUNT = 'dialogue_count'
 
-    @classmethod
-    def value_of(cls, value: str):
-        """
-        Get value of given system variable.
-
-        :param value: system variable value
-        :return: system variable
-        """
-        for system_variable in cls:
-            if system_variable.value == value:
-                return system_variable
-        raise ValueError(f'invalid system variable value {value}')
+    QUERY = "query"
+    FILES = "files"
+    CONVERSATION_ID = "conversation_id"
+    USER_ID = "user_id"
+    DIALOGUE_COUNT = "dialogue_count"

api/core/workflow/nodes/code/code_node.py

@@ -13,8 +13,8 @@ from models.workflow import WorkflowNodeExecutionStatus
 
 MAX_NUMBER = dify_config.CODE_MAX_NUMBER
 MIN_NUMBER = dify_config.CODE_MIN_NUMBER
-MAX_PRECISION = 20
-MAX_DEPTH = 5
+MAX_PRECISION = dify_config.CODE_MAX_PRECISION
+MAX_DEPTH = dify_config.CODE_MAX_DEPTH
 MAX_STRING_LENGTH = dify_config.CODE_MAX_STRING_LENGTH
 MAX_STRING_ARRAY_LENGTH = dify_config.CODE_MAX_STRING_ARRAY_LENGTH
 MAX_OBJECT_ARRAY_LENGTH = dify_config.CODE_MAX_OBJECT_ARRAY_LENGTH
@@ -23,7 +23,7 @@ MAX_NUMBER_ARRAY_LENGTH = dify_config.CODE_MAX_NUMBER_ARRAY_LENGTH
 
 class CodeNode(BaseNode):
     _node_data_cls = CodeNodeData
-    node_type = NodeType.CODE
+    _node_type = NodeType.CODE
 
     @classmethod
     def get_default_config(cls, filters: Optional[dict] = None) -> dict:
@@ -316,8 +316,8 @@ class CodeNode(BaseNode):
 
     @classmethod
     def _extract_variable_selector_to_variable_mapping(
-        cls, 
-        graph_config: Mapping[str, Any], 
+        cls,
+        graph_config: Mapping[str, Any],
         node_id: str,
         node_data: CodeNodeData
     ) -> Mapping[str, Sequence[str]]:

api/core/workflow/nodes/llm/llm_node.py

@@ -25,7 +25,7 @@ from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptT
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.event import InNodeEvent
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.event import RunCompletedEvent, RunEvent, RunRetrieverResourceEvent, RunStreamChunkEvent
@@ -110,7 +110,7 @@ class LLMNode(BaseNode):
             # fetch prompt messages
             prompt_messages, stop = self._fetch_prompt_messages(
                 node_data=node_data,
-                query=variable_pool.get_any(['sys', SystemVariable.QUERY.value])
+                query=variable_pool.get_any(['sys', SystemVariableKey.QUERY.value])
                 if node_data.memory else None,
                 query_prompt_template=node_data.memory.query_prompt_template if node_data.memory else None,
                 inputs=inputs,
@@ -370,7 +370,7 @@ class LLMNode(BaseNode):
 
                 inputs[variable_selector.variable] = variable_value
 
-        return inputs  # type: ignore
+        return inputs
 
     def _fetch_files(self, node_data: LLMNodeData, variable_pool: VariablePool) -> list["FileVar"]:
         """
@@ -382,7 +382,7 @@ class LLMNode(BaseNode):
         if not node_data.vision.enabled:
             return []
 
-        files = variable_pool.get_any(['sys', SystemVariable.FILES.value])
+        files = variable_pool.get_any(['sys', SystemVariableKey.FILES.value])
         if not files:
             return []
 
@@ -543,7 +543,7 @@ class LLMNode(BaseNode):
             return None
 
         # get conversation id
-        conversation_id = variable_pool.get_any(['sys', SystemVariable.CONVERSATION_ID.value])
+        conversation_id = variable_pool.get_any(['sys', SystemVariableKey.CONVERSATION_ID.value])
         if conversation_id is None:
             return None
 
@@ -722,10 +722,10 @@ class LLMNode(BaseNode):
             variable_mapping['#context#'] = node_data.context.variable_selector
 
         if node_data.vision.enabled:
-            variable_mapping['#files#'] = ['sys', SystemVariable.FILES.value]
+            variable_mapping['#files#'] = ['sys', SystemVariableKey.FILES.value]
 
         if node_data.memory:
-            variable_mapping['#sys.query#'] = ['sys', SystemVariable.QUERY.value]
+            variable_mapping['#sys.query#'] = ['sys', SystemVariableKey.QUERY.value]
 
         if node_data.prompt_config:
             enable_jinja = False

api/core/workflow/nodes/start/entities.py

@@ -1,3 +1,7 @@
+from collections.abc import Sequence
+
+from pydantic import Field
+
 from core.app.app_config.entities import VariableEntity
 from core.workflow.entities.base_node_data_entities import BaseNodeData
 
@@ -6,4 +10,4 @@ class StartNodeData(BaseNodeData):
     """
     Start Node Data
     """
-    variables: list[VariableEntity] = []
+    variables: Sequence[VariableEntity] = Field(default_factory=list)

api/core/workflow/nodes/start/start_node.py

@@ -3,6 +3,7 @@ from collections.abc import Mapping, Sequence
 from typing import Any
 
 from core.workflow.entities.node_entities import NodeRunResult, NodeType
+from core.workflow.entities.variable_pool import SYSTEM_VARIABLE_NODE_ID, VariablePool
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.start.entities import StartNodeData
 from models.workflow import WorkflowNodeExecutionStatus
@@ -17,22 +18,22 @@ class StartNode(BaseNode):
         Run node
         :return:
         """
-        # Get cleaned inputs
-        cleaned_inputs = dict(self.graph_runtime_state.variable_pool.user_inputs)
+        node_inputs = dict(self.graph_runtime_state.variable_pool.user_inputs)
+        system_inputs = self.graph_runtime_state.variable_pool.system_variables
 
-        for var in self.graph_runtime_state.variable_pool.system_variables:
-            cleaned_inputs['sys.' + var.value] = self.graph_runtime_state.variable_pool.system_variables[var]
+        for var in system_inputs:
+            node_inputs[SYSTEM_VARIABLE_NODE_ID + '.' + var] = system_inputs[var]
 
         return NodeRunResult(
             status=WorkflowNodeExecutionStatus.SUCCEEDED,
-            inputs=cleaned_inputs,
-            outputs=cleaned_inputs
+            inputs=node_inputs,
+            outputs=node_inputs
         )
 
     @classmethod
     def _extract_variable_selector_to_variable_mapping(
-        cls, 
-        graph_config: Mapping[str, Any], 
+        cls,
+        graph_config: Mapping[str, Any],
         node_id: str,
         node_data: StartNodeData
     ) -> Mapping[str, Sequence[str]]:

api/core/workflow/nodes/tool/tool_node.py

@@ -2,7 +2,7 @@ from collections.abc import Mapping, Sequence
 from os import path
 from typing import Any, cast
 
-from core.app.segments import ArrayAnyVariable, parser
+from core.app.segments import ArrayAnySegment, ArrayAnyVariable, parser
 from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler
 from core.file.file_obj import FileTransferMethod, FileType, FileVar
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
@@ -11,7 +11,7 @@ from core.tools.tool_manager import ToolManager
 from core.tools.utils.message_transformer import ToolFileMessageTransformer
 from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.tool.entities import ToolNodeData
 from core.workflow.utils.variable_template_parser import VariableTemplateParser
@@ -141,8 +141,8 @@ class ToolNode(BaseNode):
         return result
 
     def _fetch_files(self, variable_pool: VariablePool) -> list[FileVar]:
-        variable = variable_pool.get(['sys', SystemVariable.FILES.value])
-        assert isinstance(variable, ArrayAnyVariable)
+        variable = variable_pool.get(['sys', SystemVariableKey.FILES.value])
+        assert isinstance(variable, ArrayAnyVariable | ArrayAnySegment)
         return list(variable.value) if variable else []
 
     def _convert_tool_messages(self, messages: list[ToolInvokeMessage])\

api/core/workflow/nodes/variable_assigner/__init__.py

@@ -1,109 +1,8 @@
-from collections.abc import Sequence
-from enum import Enum
-from typing import Optional, cast
+from .node import VariableAssignerNode
+from .node_data import VariableAssignerData, WriteMode
 
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-
-from core.app.segments import SegmentType, Variable, factory
-from core.workflow.entities.base_node_data_entities import BaseNodeData
-from core.workflow.entities.node_entities import NodeRunResult, NodeType
-from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.nodes.base_node import BaseNode
-from extensions.ext_database import db
-from models import ConversationVariable, WorkflowNodeExecutionStatus
-
-
-class VariableAssignerNodeError(Exception):
-    pass
-
-
-class WriteMode(str, Enum):
-    OVER_WRITE = 'over-write'
-    APPEND = 'append'
-    CLEAR = 'clear'
-
-
-class VariableAssignerData(BaseNodeData):
-    title: str = 'Variable Assigner'
-    desc: Optional[str] = 'Assign a value to a variable'
-    assigned_variable_selector: Sequence[str]
-    write_mode: WriteMode
-    input_variable_selector: Sequence[str]
-
-
-class VariableAssignerNode(BaseNode):
-    _node_data_cls: type[BaseNodeData] = VariableAssignerData
-    _node_type: NodeType = NodeType.CONVERSATION_VARIABLE_ASSIGNER
-
-    def _run(self) -> NodeRunResult:
-        data = cast(VariableAssignerData, self.node_data)
-
-        # Should be String, Number, Object, ArrayString, ArrayNumber, ArrayObject
-        original_variable = self.graph_runtime_state.variable_pool.get(data.assigned_variable_selector)
-        if not isinstance(original_variable, Variable):
-            raise VariableAssignerNodeError('assigned variable not found')
-
-        match data.write_mode:
-            case WriteMode.OVER_WRITE:
-                income_value = self.graph_runtime_state.variable_pool.get(data.input_variable_selector)
-                if not income_value:
-                    raise VariableAssignerNodeError('input value not found')
-                updated_variable = original_variable.model_copy(update={'value': income_value.value})
-
-            case WriteMode.APPEND:
-                income_value = self.graph_runtime_state.variable_pool.get(data.input_variable_selector)
-                if not income_value:
-                    raise VariableAssignerNodeError('input value not found')
-                updated_value = original_variable.value + [income_value.value]
-                updated_variable = original_variable.model_copy(update={'value': updated_value})
-
-            case WriteMode.CLEAR:
-                income_value = get_zero_value(original_variable.value_type)
-                updated_variable = original_variable.model_copy(update={'value': income_value.to_object()})
-
-            case _:
-                raise VariableAssignerNodeError(f'unsupported write mode: {data.write_mode}')
-
-        # Over write the variable.
-        self.graph_runtime_state.variable_pool.add(data.assigned_variable_selector, updated_variable)
-
-        # Update conversation variable.
-        # TODO: Find a better way to use the database.
-        conversation_id = self.graph_runtime_state.variable_pool.get(['sys', 'conversation_id'])
-        if not conversation_id:
-            raise VariableAssignerNodeError('conversation_id not found')
-        update_conversation_variable(conversation_id=conversation_id.text, variable=updated_variable)
-
-        return NodeRunResult(
-            status=WorkflowNodeExecutionStatus.SUCCEEDED,
-            inputs={
-                'value': income_value.to_object(),
-            },
-        )
-
-
-def update_conversation_variable(conversation_id: str, variable: Variable):
-    stmt = select(ConversationVariable).where(
-        ConversationVariable.id == variable.id, ConversationVariable.conversation_id == conversation_id
-    )
-    with Session(db.engine) as session:
-        row = session.scalar(stmt)
-        if not row:
-            raise VariableAssignerNodeError('conversation variable not found in the database')
-        row.data = variable.model_dump_json()
-        session.commit()
-
-
-def get_zero_value(t: SegmentType):
-    match t:
-        case SegmentType.ARRAY_OBJECT | SegmentType.ARRAY_STRING | SegmentType.ARRAY_NUMBER:
-            return factory.build_segment([])
-        case SegmentType.OBJECT:
-            return factory.build_segment({})
-        case SegmentType.STRING:
-            return factory.build_segment('')
-        case SegmentType.NUMBER:
-            return factory.build_segment(0)
-        case _:
-            raise VariableAssignerNodeError(f'unsupported variable type: {t}')
+__all__ = [
+    'VariableAssignerNode',
+    'VariableAssignerData',
+    'WriteMode',
+]