refactor apps

api/controllers/console/app/audio.py

@@ -37,7 +37,7 @@ class ChatMessageAudioApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     def post(self, app_model):
         file = request.files['file']
 

api/controllers/console/app/completion.py

@@ -22,7 +22,7 @@ from controllers.console.app.wraps import get_app_model
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
 from core.app.app_queue_manager import AppQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from libs.helper import uuid_value
@@ -103,7 +103,7 @@ class ChatMessageApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     def post(self, app_model):
         parser = reqparse.RequestParser()
         parser.add_argument('inputs', type=dict, required=True, location='json')
@@ -168,7 +168,7 @@ class ChatMessageStopApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     def post(self, app_model, task_id):
         account = flask_login.current_user
 

api/controllers/console/app/conversation.py

@@ -112,7 +112,7 @@ class CompletionConversationDetailApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     def delete(self, app_model, conversation_id):
         conversation_id = str(conversation_id)
 
@@ -133,7 +133,7 @@ class ChatConversationApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     @marshal_with(conversation_with_summary_pagination_fields)
     def get(self, app_model):
         parser = reqparse.RequestParser()
@@ -218,7 +218,7 @@ class ChatConversationDetailApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     @marshal_with(conversation_detail_fields)
     def get(self, app_model, conversation_id):
         conversation_id = str(conversation_id)
@@ -227,7 +227,7 @@ class ChatConversationDetailApi(Resource):
 
     @setup_required
     @login_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     @account_initialization_required
     def delete(self, app_model, conversation_id):
         conversation_id = str(conversation_id)

api/controllers/console/app/message.py

@@ -42,7 +42,7 @@ class ChatMessageListApi(Resource):
 
     @setup_required
     @login_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     @account_initialization_required
     @marshal_with(message_infinite_scroll_pagination_fields)
     def get(self, app_model):
@@ -194,7 +194,7 @@ class MessageSuggestedQuestionApi(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     def get(self, app_model, message_id):
         message_id = str(message_id)
 

api/controllers/console/app/statistic.py

@@ -203,7 +203,7 @@ class AverageSessionInteractionStatistic(Resource):
     @setup_required
     @login_required
     @account_initialization_required
-    @get_app_model(mode=AppMode.CHAT)
+    @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT])
     def get(self, app_model):
         account = current_user
 

api/controllers/console/explore/completion.py

@@ -22,7 +22,7 @@ from controllers.console.app.error import (
 from controllers.console.explore.error import NotChatAppError, NotCompletionAppError
 from controllers.console.explore.wraps import InstalledAppResource
 from core.app.app_queue_manager import AppQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from extensions.ext_database import db

api/controllers/console/explore/message.py

@@ -24,7 +24,7 @@ from controllers.console.explore.error import (
     NotCompletionAppError,
 )
 from controllers.console.explore.wraps import InstalledAppResource
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from fields.message_fields import message_infinite_scroll_pagination_fields

api/controllers/service_api/app/completion.py

@@ -20,7 +20,7 @@ from controllers.service_api.app.error import (
 )
 from controllers.service_api.wraps import FetchUserArg, WhereisUserArg, validate_app_token
 from core.app.app_queue_manager import AppQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from libs.helper import uuid_value

api/controllers/web/completion.py

@@ -21,7 +21,7 @@ from controllers.web.error import (
 )
 from controllers.web.wraps import WebApiResource
 from core.app.app_queue_manager import AppQueueManager
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from libs.helper import uuid_value

api/controllers/web/message.py

@@ -21,7 +21,7 @@ from controllers.web.error import (
     ProviderQuotaExceededError,
 )
 from controllers.web.wraps import WebApiResource
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
 from core.model_runtime.errors.invoke import InvokeError
 from fields.conversation_fields import message_file_fields

api/core/agent/base_agent_runner.py

@@ -5,17 +5,15 @@ from datetime import datetime
 from mimetypes import guess_extension
 from typing import Optional, Union, cast
 
+from core.agent.entities import AgentEntity, AgentToolEntity
 from core.app.app_queue_manager import AppQueueManager
-from core.app.base_app_runner import AppRunner
+from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfig
+from core.app.apps.base_app_runner import AppRunner
 from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.entities.application_entities import (
+from core.app.entities.app_invoke_entities import (
-    AgentEntity,
+    EasyUIBasedAppGenerateEntity,
-    AgentToolEntity,
+    InvokeFrom, EasyUIBasedModelConfigEntity,
-    ApplicationGenerateEntity,
-    AppOrchestrationConfigEntity,
-    InvokeFrom,
-    ModelConfigEntity,
 )
 from core.file.message_file_parser import FileTransferMethod
 from core.memory.token_buffer_memory import TokenBufferMemory
@@ -50,9 +48,9 @@ logger = logging.getLogger(__name__)
 
 class BaseAgentRunner(AppRunner):
     def __init__(self, tenant_id: str,
-                 application_generate_entity: ApplicationGenerateEntity,
+                 application_generate_entity: EasyUIBasedAppGenerateEntity,
-                 app_orchestration_config: AppOrchestrationConfigEntity,
+                 app_config: AgentChatAppConfig,
-                 model_config: ModelConfigEntity,
+                 model_config: EasyUIBasedModelConfigEntity,
                  config: AgentEntity,
                  queue_manager: AppQueueManager,
                  message: Message,
@@ -66,7 +64,7 @@ class BaseAgentRunner(AppRunner):
         """
         Agent runner
         :param tenant_id: tenant id
-        :param app_orchestration_config: app orchestration config
+        :param app_config: app generate entity
         :param model_config: model config
         :param config: dataset config
         :param queue_manager: queue manager
@@ -78,7 +76,7 @@ class BaseAgentRunner(AppRunner):
         """
         self.tenant_id = tenant_id
         self.application_generate_entity = application_generate_entity
-        self.app_orchestration_config = app_orchestration_config
+        self.app_config = app_config
         self.model_config = model_config
         self.config = config
         self.queue_manager = queue_manager
@@ -97,16 +95,16 @@ class BaseAgentRunner(AppRunner):
         # init dataset tools
         hit_callback = DatasetIndexToolCallbackHandler(
             queue_manager=queue_manager,
-            app_id=self.application_generate_entity.app_id,
+            app_id=self.app_config.app_id,
             message_id=message.id,
             user_id=user_id,
             invoke_from=self.application_generate_entity.invoke_from,
         )
         self.dataset_tools = DatasetRetrieverTool.get_dataset_tools(
             tenant_id=tenant_id,
-            dataset_ids=app_orchestration_config.dataset.dataset_ids if app_orchestration_config.dataset else [],
+            dataset_ids=app_config.dataset.dataset_ids if app_config.dataset else [],
-            retrieve_config=app_orchestration_config.dataset.retrieve_config if app_orchestration_config.dataset else None,
+            retrieve_config=app_config.dataset.retrieve_config if app_config.dataset else None,
-            return_resource=app_orchestration_config.show_retrieve_source,
+            return_resource=app_config.additional_features.show_retrieve_source,
             invoke_from=application_generate_entity.invoke_from,
             hit_callback=hit_callback
         )
@@ -124,14 +122,15 @@ class BaseAgentRunner(AppRunner):
         else:
             self.stream_tool_call = False
 
-    def _repack_app_orchestration_config(self, app_orchestration_config: AppOrchestrationConfigEntity) -> AppOrchestrationConfigEntity:
+    def _repack_app_generate_entity(self, app_generate_entity: EasyUIBasedAppGenerateEntity) \
+            -> EasyUIBasedAppGenerateEntity:
         """
-        Repack app orchestration config
+        Repack app generate entity
         """
-        if app_orchestration_config.prompt_template.simple_prompt_template is None:
+        if app_generate_entity.app_config.prompt_template.simple_prompt_template is None:
-            app_orchestration_config.prompt_template.simple_prompt_template = ''
+            app_generate_entity.app_config.prompt_template.simple_prompt_template = ''
 
-        return app_orchestration_config
+        return app_generate_entity
 
     def _convert_tool_response_to_str(self, tool_response: list[ToolInvokeMessage]) -> str:
         """
@@ -351,7 +350,7 @@ class BaseAgentRunner(AppRunner):
             ))
 
         db.session.close()
-            
+
         return result
         
     def create_agent_thought(self, message_id: str, message: str, 
@@ -462,7 +461,7 @@ class BaseAgentRunner(AppRunner):
 
         db.session.commit()
         db.session.close()
-    
+
     def transform_tool_invoke_messages(self, messages: list[ToolInvokeMessage]) -> list[ToolInvokeMessage]:
         """
         Transform tool message into agent thought

api/core/agent/cot_agent_runner.py

@@ -5,7 +5,7 @@ from typing import Literal, Union
 
 from core.agent.base_agent_runner import BaseAgentRunner
 from core.app.app_queue_manager import PublishFrom
-from core.entities.application_entities import AgentPromptEntity, AgentScratchpadUnit
+from core.agent.entities import AgentPromptEntity, AgentScratchpadUnit
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
@@ -27,7 +27,7 @@ from core.tools.errors import (
 from models.model import Conversation, Message
 
 
-class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
+class CotAgentRunner(BaseAgentRunner):
     _is_first_iteration = True
     _ignore_observation_providers = ['wenxin']
 
@@ -39,30 +39,33 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
         """
         Run Cot agent application
         """
-        app_orchestration_config = self.app_orchestration_config
+        app_generate_entity = self.application_generate_entity
-        self._repack_app_orchestration_config(app_orchestration_config)
+        self._repack_app_generate_entity(app_generate_entity)
 
         agent_scratchpad: list[AgentScratchpadUnit] = []
         self._init_agent_scratchpad(agent_scratchpad, self.history_prompt_messages)
 
-        if 'Observation' not in app_orchestration_config.model_config.stop:
+        # check model mode
-            if app_orchestration_config.model_config.provider not in self._ignore_observation_providers:
+        if 'Observation' not in app_generate_entity.model_config.stop:
-                app_orchestration_config.model_config.stop.append('Observation')
+            if app_generate_entity.model_config.provider not in self._ignore_observation_providers:
+                app_generate_entity.model_config.stop.append('Observation')
+
+        app_config = self.app_config
 
         # override inputs
         inputs = inputs or {}
-        instruction = self.app_orchestration_config.prompt_template.simple_prompt_template
+        instruction = app_config.prompt_template.simple_prompt_template
         instruction = self._fill_in_inputs_from_external_data_tools(instruction, inputs)
 
         iteration_step = 1
-        max_iteration_steps = min(self.app_orchestration_config.agent.max_iteration, 5) + 1
+        max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1
 
         prompt_messages = self.history_prompt_messages
 
         # convert tools into ModelRuntime Tool format
         prompt_messages_tools: list[PromptMessageTool] = []
         tool_instances = {}
-        for tool in self.app_orchestration_config.agent.tools if self.app_orchestration_config.agent else []:
+        for tool in app_config.agent.tools if app_config.agent else []:
             try:
                 prompt_tool, tool_entity = self._convert_tool_to_prompt_message_tool(tool)
             except Exception:
@@ -122,11 +125,11 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
 
             # update prompt messages
             prompt_messages = self._organize_cot_prompt_messages(
-                mode=app_orchestration_config.model_config.mode,
+                mode=app_generate_entity.model_config.mode,
                 prompt_messages=prompt_messages,
                 tools=prompt_messages_tools,
                 agent_scratchpad=agent_scratchpad,
-                agent_prompt_message=app_orchestration_config.agent.prompt,
+                agent_prompt_message=app_config.agent.prompt,
                 instruction=instruction,
                 input=query
             )
@@ -136,9 +139,9 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
             # invoke model
             chunks: Generator[LLMResultChunk, None, None] = model_instance.invoke_llm(
                 prompt_messages=prompt_messages,
-                model_parameters=app_orchestration_config.model_config.parameters,
+                model_parameters=app_generate_entity.model_config.parameters,
                 tools=[],
-                stop=app_orchestration_config.model_config.stop,
+                stop=app_generate_entity.model_config.stop,
                 stream=True,
                 user=self.user_id,
                 callbacks=[],
@@ -550,7 +553,7 @@ class AssistantCotApplicationRunner(BaseAssistantApplicationRunner):
         """
             convert agent scratchpad list to str
         """
-        next_iteration = self.app_orchestration_config.agent.prompt.next_iteration
+        next_iteration = self.app_config.agent.prompt.next_iteration
 
         result = ''
         for scratchpad in agent_scratchpad:

api/core/agent/entities.py

@@ -0,0 +1,61 @@
+from enum import Enum
+from typing import Literal, Any, Union, Optional
+
+from pydantic import BaseModel
+
+
+class AgentToolEntity(BaseModel):
+    """
+    Agent Tool Entity.
+    """
+    provider_type: Literal["builtin", "api"]
+    provider_id: str
+    tool_name: str
+    tool_parameters: dict[str, Any] = {}
+
+
+class AgentPromptEntity(BaseModel):
+    """
+    Agent Prompt Entity.
+    """
+    first_prompt: str
+    next_iteration: str
+
+
+class AgentScratchpadUnit(BaseModel):
+    """
+    Agent First Prompt Entity.
+    """
+
+    class Action(BaseModel):
+        """
+        Action Entity.
+        """
+        action_name: str
+        action_input: Union[dict, str]
+
+    agent_response: Optional[str] = None
+    thought: Optional[str] = None
+    action_str: Optional[str] = None
+    observation: Optional[str] = None
+    action: Optional[Action] = None
+
+
+class AgentEntity(BaseModel):
+    """
+    Agent Entity.
+    """
+
+    class Strategy(Enum):
+        """
+        Agent Strategy.
+        """
+        CHAIN_OF_THOUGHT = 'chain-of-thought'
+        FUNCTION_CALLING = 'function-calling'
+
+    provider: str
+    model: str
+    strategy: Strategy
+    prompt: Optional[AgentPromptEntity] = None
+    tools: list[AgentToolEntity] = None
+    max_iteration: int = 5

api/core/agent/fc_agent_runner.py

@@ -34,9 +34,11 @@ class FunctionCallAgentRunner(BaseAgentRunner):
         """
         Run FunctionCall agent application
         """
-        app_orchestration_config = self.app_orchestration_config
+        app_generate_entity = self.application_generate_entity
 
-        prompt_template = self.app_orchestration_config.prompt_template.simple_prompt_template or ''
+        app_config = self.app_config
+
+        prompt_template = app_config.prompt_template.simple_prompt_template or ''
         prompt_messages = self.history_prompt_messages
         prompt_messages = self.organize_prompt_messages(
             prompt_template=prompt_template,
@@ -47,7 +49,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
         # convert tools into ModelRuntime Tool format
         prompt_messages_tools: list[PromptMessageTool] = []
         tool_instances = {}
-        for tool in self.app_orchestration_config.agent.tools if self.app_orchestration_config.agent else []:
+        for tool in app_config.agent.tools if app_config.agent else []:
             try:
                 prompt_tool, tool_entity = self._convert_tool_to_prompt_message_tool(tool)
             except Exception:
@@ -67,7 +69,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
             tool_instances[dataset_tool.identity.name] = dataset_tool
 
         iteration_step = 1
-        max_iteration_steps = min(app_orchestration_config.agent.max_iteration, 5) + 1
+        max_iteration_steps = min(app_config.agent.max_iteration, 5) + 1
 
         # continue to run until there is not any tool call
         function_call_state = True
@@ -110,9 +112,9 @@ class FunctionCallAgentRunner(BaseAgentRunner):
             # invoke model
             chunks: Union[Generator[LLMResultChunk, None, None], LLMResult] = model_instance.invoke_llm(
                 prompt_messages=prompt_messages,
-                model_parameters=app_orchestration_config.model_config.parameters,
+                model_parameters=app_generate_entity.model_config.parameters,
                 tools=prompt_messages_tools,
-                stop=app_orchestration_config.model_config.stop,
+                stop=app_generate_entity.model_config.stop,
                 stream=self.stream_tool_call,
                 user=self.user_id,
                 callbacks=[],

api/core/app/advanced_chat/config_validator.py

@@ -1,59 +0,0 @@
-from core.app.validators.file_upload import FileUploadValidator
-from core.app.validators.moderation import ModerationValidator
-from core.app.validators.opening_statement import OpeningStatementValidator
-from core.app.validators.retriever_resource import RetrieverResourceValidator
-from core.app.validators.speech_to_text import SpeechToTextValidator
-from core.app.validators.suggested_questions import SuggestedQuestionsValidator
-from core.app.validators.text_to_speech import TextToSpeechValidator
-
-
-class AdvancedChatAppConfigValidator:
-    @classmethod
-    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False) -> dict:
-        """
-        Validate for advanced chat app model config
-
-        :param tenant_id: tenant id
-        :param config: app model config args
-        :param only_structure_validate: if True, only structure validation will be performed
-        """
-        related_config_keys = []
-
-        # file upload validation
-        config, current_related_config_keys = FileUploadValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # opening_statement
-        config, current_related_config_keys = OpeningStatementValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # suggested_questions_after_answer
-        config, current_related_config_keys = SuggestedQuestionsValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # speech_to_text
-        config, current_related_config_keys = SpeechToTextValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # text_to_speech
-        config, current_related_config_keys = TextToSpeechValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # return retriever resource
-        config, current_related_config_keys = RetrieverResourceValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # moderation validation
-        config, current_related_config_keys = ModerationValidator.validate_and_set_defaults(
-            tenant_id=tenant_id,
-            config=config,
-            only_structure_validate=only_structure_validate
-        )
-        related_config_keys.extend(current_related_config_keys)
-
-        related_config_keys = list(set(related_config_keys))
-
-        # Filter out extra parameters
-        filtered_config = {key: config.get(key) for key in related_config_keys}
-
-        return filtered_config

api/core/app/app_config/base_app_config_manager.py

@@ -0,0 +1,73 @@
+from typing import Union, Optional
+
+from core.app.app_config.entities import AppAdditionalFeatures, EasyUIBasedAppModelConfigFrom
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.app_config.features.more_like_this.manager import MoreLikeThisConfigManager
+from core.app.app_config.features.opening_statement.manager import OpeningStatementConfigManager
+from core.app.app_config.features.retrieval_resource.manager import RetrievalResourceConfigManager
+from core.app.app_config.features.speech_to_text.manager import SpeechToTextConfigManager
+from core.app.app_config.features.suggested_questions_after_answer.manager import \
+    SuggestedQuestionsAfterAnswerConfigManager
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
+from models.model import AppModelConfig
+
+
+class BaseAppConfigManager:
+
+    @classmethod
+    def convert_to_config_dict(cls, config_from: EasyUIBasedAppModelConfigFrom,
+                               app_model_config: Union[AppModelConfig, dict],
+                               config_dict: Optional[dict] = None) -> dict:
+        """
+        Convert app model config to config dict
+        :param config_from: app model config from
+        :param app_model_config: app model config
+        :param config_dict: app model config dict
+        :return:
+        """
+        if config_from != EasyUIBasedAppModelConfigFrom.ARGS:
+            app_model_config_dict = app_model_config.to_dict()
+            config_dict = app_model_config_dict.copy()
+
+        return config_dict
+
+    @classmethod
+    def convert_features(cls, config_dict: dict) -> AppAdditionalFeatures:
+        """
+        Convert app config to app model config
+
+        :param config_dict: app config
+        """
+        config_dict = config_dict.copy()
+
+        additional_features = AppAdditionalFeatures()
+        additional_features.show_retrieve_source = RetrievalResourceConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.file_upload = FileUploadConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.opening_statement, additional_features.suggested_questions = \
+            OpeningStatementConfigManager.convert(
+                config=config_dict
+            )
+
+        additional_features.suggested_questions_after_answer = SuggestedQuestionsAfterAnswerConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.more_like_this = MoreLikeThisConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.speech_to_text = SpeechToTextConfigManager.convert(
+            config=config_dict
+        )
+
+        additional_features.text_to_speech = TextToSpeechConfigManager.convert(
+            config=config_dict
+        )
+
+        return additional_features

api/core/app/app_config/common/sensitive_word_avoidance/manager.py

@@ -1,11 +1,24 @@
-import logging
+from typing import Optional
 
+from core.app.app_config.entities import SensitiveWordAvoidanceEntity
 from core.moderation.factory import ModerationFactory
 
-logger = logging.getLogger(__name__)
 
+class SensitiveWordAvoidanceConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[SensitiveWordAvoidanceEntity]:
+        sensitive_word_avoidance_dict = config.get('sensitive_word_avoidance')
+        if not sensitive_word_avoidance_dict:
+            return None
+
+        if 'enabled' in sensitive_word_avoidance_dict and sensitive_word_avoidance_dict['enabled']:
+            return SensitiveWordAvoidanceEntity(
+                type=sensitive_word_avoidance_dict.get('type'),
+                config=sensitive_word_avoidance_dict.get('config'),
+            )
+        else:
+            return None
 
-class ModerationValidator:
     @classmethod
     def validate_and_set_defaults(cls, tenant_id, config: dict, only_structure_validate: bool = False) \
             -> tuple[dict, list[str]]:

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

@@ -0,0 +1,79 @@
+from typing import Optional
+
+from core.agent.entities import AgentEntity, AgentPromptEntity, AgentToolEntity
+from core.tools.prompt.template import REACT_PROMPT_TEMPLATES
+
+
+class AgentConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[AgentEntity]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        if 'agent_mode' in config and config['agent_mode'] \
+                and 'enabled' in config['agent_mode'] \
+                and config['agent_mode']['enabled']:
+
+            agent_dict = config.get('agent_mode', {})
+            agent_strategy = agent_dict.get('strategy', 'cot')
+
+            if agent_strategy == 'function_call':
+                strategy = AgentEntity.Strategy.FUNCTION_CALLING
+            elif agent_strategy == 'cot' or agent_strategy == 'react':
+                strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
+            else:
+                # old configs, try to detect default strategy
+                if config['model']['provider'] == 'openai':
+                    strategy = AgentEntity.Strategy.FUNCTION_CALLING
+                else:
+                    strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
+
+            agent_tools = []
+            for tool in agent_dict.get('tools', []):
+                keys = tool.keys()
+                if len(keys) >= 4:
+                    if "enabled" not in tool or not tool["enabled"]:
+                        continue
+
+                    agent_tool_properties = {
+                        'provider_type': tool['provider_type'],
+                        'provider_id': tool['provider_id'],
+                        'tool_name': tool['tool_name'],
+                        'tool_parameters': tool['tool_parameters'] if 'tool_parameters' in tool else {}
+                    }
+
+                    agent_tools.append(AgentToolEntity(**agent_tool_properties))
+
+            if 'strategy' in config['agent_mode'] and \
+                    config['agent_mode']['strategy'] not in ['react_router', 'router']:
+                agent_prompt = agent_dict.get('prompt', None) or {}
+                # check model mode
+                model_mode = config.get('model', {}).get('mode', 'completion')
+                if model_mode == 'completion':
+                    agent_prompt_entity = AgentPromptEntity(
+                        first_prompt=agent_prompt.get('first_prompt',
+                                                      REACT_PROMPT_TEMPLATES['english']['completion']['prompt']),
+                        next_iteration=agent_prompt.get('next_iteration',
+                                                        REACT_PROMPT_TEMPLATES['english']['completion'][
+                                                            'agent_scratchpad']),
+                    )
+                else:
+                    agent_prompt_entity = AgentPromptEntity(
+                        first_prompt=agent_prompt.get('first_prompt',
+                                                      REACT_PROMPT_TEMPLATES['english']['chat']['prompt']),
+                        next_iteration=agent_prompt.get('next_iteration',
+                                                        REACT_PROMPT_TEMPLATES['english']['chat']['agent_scratchpad']),
+                    )
+
+                return AgentEntity(
+                    provider=config['model']['provider'],
+                    model=config['model']['name'],
+                    strategy=strategy,
+                    prompt=agent_prompt_entity,
+                    tools=agent_tools,
+                    max_iteration=agent_dict.get('max_iteration', 5)
+                )
+
+        return None

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

@@ -1,11 +1,94 @@
-import uuid
+from typing import Optional
 
+from core.app.app_config.entities import DatasetEntity, DatasetRetrieveConfigEntity
 from core.entities.agent_entities import PlanningStrategy
 from models.model import AppMode
 from services.dataset_service import DatasetService
 
 
-class DatasetValidator:
+class DatasetConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[DatasetEntity]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        dataset_ids = []
+        if 'datasets' in config.get('dataset_configs', {}):
+            datasets = config.get('dataset_configs', {}).get('datasets', {
+                'strategy': 'router',
+                'datasets': []
+            })
+
+            for dataset in datasets.get('datasets', []):
+                keys = list(dataset.keys())
+                if len(keys) == 0 or keys[0] != 'dataset':
+                    continue
+
+                dataset = dataset['dataset']
+
+                if 'enabled' not in dataset or not dataset['enabled']:
+                    continue
+
+                dataset_id = dataset.get('id', None)
+                if dataset_id:
+                    dataset_ids.append(dataset_id)
+
+        if 'agent_mode' in config and config['agent_mode'] \
+                and 'enabled' in config['agent_mode'] \
+                and config['agent_mode']['enabled']:
+
+            agent_dict = config.get('agent_mode', {})
+
+            for tool in agent_dict.get('tools', []):
+                keys = tool.keys()
+                if len(keys) == 1:
+                    # old standard
+                    key = list(tool.keys())[0]
+
+                    if key != 'dataset':
+                        continue
+
+                    tool_item = tool[key]
+
+                    if "enabled" not in tool_item or not tool_item["enabled"]:
+                        continue
+
+                    dataset_id = tool_item['id']
+                    dataset_ids.append(dataset_id)
+
+        if len(dataset_ids) == 0:
+            return None
+
+        # dataset configs
+        dataset_configs = config.get('dataset_configs', {'retrieval_model': 'single'})
+        query_variable = config.get('dataset_query_variable')
+
+        if dataset_configs['retrieval_model'] == 'single':
+            return DatasetEntity(
+                dataset_ids=dataset_ids,
+                retrieve_config=DatasetRetrieveConfigEntity(
+                    query_variable=query_variable,
+                    retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
+                        dataset_configs['retrieval_model']
+                    )
+                )
+            )
+        else:
+            return DatasetEntity(
+                dataset_ids=dataset_ids,
+                retrieve_config=DatasetRetrieveConfigEntity(
+                    query_variable=query_variable,
+                    retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
+                        dataset_configs['retrieval_model']
+                    ),
+                    top_k=dataset_configs.get('top_k'),
+                    score_threshold=dataset_configs.get('score_threshold'),
+                    reranking_model=dataset_configs.get('reranking_model')
+                )
+            )
+
     @classmethod
     def validate_and_set_defaults(cls, tenant_id: str, app_mode: AppMode, config: dict) -> tuple[dict, list[str]]:
         """

api/core/app/app_config/easy_ui_based_app/model_config/converter.py

@@ -0,0 +1,104 @@
+from typing import cast
+
+from core.app.app_config.entities import EasyUIBasedAppConfig
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
+
+from core.entities.model_entities import ModelStatus
+from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
+from core.model_runtime.entities.model_entities import ModelType
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+from core.provider_manager import ProviderManager
+
+
+class EasyUIBasedModelConfigEntityConverter:
+    @classmethod
+    def convert(cls, app_config: EasyUIBasedAppConfig,
+                skip_check: bool = False) \
+            -> EasyUIBasedModelConfigEntity:
+        """
+        Convert app model config dict to entity.
+        :param app_config: app config
+        :param skip_check: skip check
+        :raises ProviderTokenNotInitError: provider token not init error
+        :return: app orchestration config entity
+        """
+        model_config = app_config.model
+
+        provider_manager = ProviderManager()
+        provider_model_bundle = provider_manager.get_provider_model_bundle(
+            tenant_id=app_config.tenant_id,
+            provider=model_config.provider,
+            model_type=ModelType.LLM
+        )
+
+        provider_name = provider_model_bundle.configuration.provider.provider
+        model_name = model_config.model
+
+        model_type_instance = provider_model_bundle.model_type_instance
+        model_type_instance = cast(LargeLanguageModel, model_type_instance)
+
+        # check model credentials
+        model_credentials = provider_model_bundle.configuration.get_current_credentials(
+            model_type=ModelType.LLM,
+            model=model_config.model
+        )
+
+        if model_credentials is None:
+            if not skip_check:
+                raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
+            else:
+                model_credentials = {}
+
+        if not skip_check:
+            # check model
+            provider_model = provider_model_bundle.configuration.get_provider_model(
+                model=model_config.model,
+                model_type=ModelType.LLM
+            )
+
+            if provider_model is None:
+                model_name = model_config.model
+                raise ValueError(f"Model {model_name} not exist.")
+
+            if provider_model.status == ModelStatus.NO_CONFIGURE:
+                raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
+            elif provider_model.status == ModelStatus.NO_PERMISSION:
+                raise ModelCurrentlyNotSupportError(f"Dify Hosted OpenAI {model_name} currently not support.")
+            elif provider_model.status == ModelStatus.QUOTA_EXCEEDED:
+                raise QuotaExceededError(f"Model provider {provider_name} quota exceeded.")
+
+        # model config
+        completion_params = model_config.parameters
+        stop = []
+        if 'stop' in completion_params:
+            stop = completion_params['stop']
+            del completion_params['stop']
+
+        # get model mode
+        model_mode = model_config.mode
+        if not model_mode:
+            mode_enum = model_type_instance.get_model_mode(
+                model=model_config.model,
+                credentials=model_credentials
+            )
+
+            model_mode = mode_enum.value
+
+        model_schema = model_type_instance.get_model_schema(
+            model_config.model,
+            model_credentials
+        )
+
+        if not skip_check and not model_schema:
+            raise ValueError(f"Model {model_name} not exist.")
+
+        return EasyUIBasedModelConfigEntity(
+            provider=model_config.provider,
+            model=model_config.model,
+            model_schema=model_schema,
+            mode=model_mode,
+            provider_model_bundle=provider_model_bundle,
+            credentials=model_credentials,
+            parameters=completion_params,
+            stop=stop,
+        )

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

@@ -1,10 +1,40 @@
-
+from core.app.app_config.entities import ModelConfigEntity
-from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType
+from core.model_runtime.entities.model_entities import ModelType, ModelPropertyKey
 from core.model_runtime.model_providers import model_provider_factory
 from core.provider_manager import ProviderManager
 
 
-class ModelValidator:
+class ModelConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> ModelConfigEntity:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        # model config
+        model_config = config.get('model')
+
+        if not model_config:
+            raise ValueError("model is required")
+
+        completion_params = model_config.get('completion_params')
+        stop = []
+        if 'stop' in completion_params:
+            stop = completion_params['stop']
+            del completion_params['stop']
+
+        # get model mode
+        model_mode = model_config.get('mode')
+
+        return ModelConfigEntity(
+            provider=config['model']['provider'],
+            model=config['model']['name'],
+            mode=model_mode,
+            parameters=completion_params,
+            stop=stop,
+        )
+
     @classmethod
     def validate_and_set_defaults(cls, tenant_id: str, config: dict) -> tuple[dict, list[str]]:
         """

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

@@ -1,10 +1,61 @@
-
+from core.app.app_config.entities import PromptTemplateEntity, \
-from core.entities.application_entities import PromptTemplateEntity
+    AdvancedChatPromptTemplateEntity, AdvancedCompletionPromptTemplateEntity
+from core.model_runtime.entities.message_entities import PromptMessageRole
 from core.prompt.simple_prompt_transform import ModelMode
 from models.model import AppMode
 
 
-class PromptValidator:
+class PromptTemplateConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> PromptTemplateEntity:
+        if not config.get("prompt_type"):
+            raise ValueError("prompt_type is required")
+
+        prompt_type = PromptTemplateEntity.PromptType.value_of(config['prompt_type'])
+        if prompt_type == PromptTemplateEntity.PromptType.SIMPLE:
+            simple_prompt_template = config.get("pre_prompt", "")
+            return PromptTemplateEntity(
+                prompt_type=prompt_type,
+                simple_prompt_template=simple_prompt_template
+            )
+        else:
+            advanced_chat_prompt_template = None
+            chat_prompt_config = config.get("chat_prompt_config", {})
+            if chat_prompt_config:
+                chat_prompt_messages = []
+                for message in chat_prompt_config.get("prompt", []):
+                    chat_prompt_messages.append({
+                        "text": message["text"],
+                        "role": PromptMessageRole.value_of(message["role"])
+                    })
+
+                advanced_chat_prompt_template = AdvancedChatPromptTemplateEntity(
+                    messages=chat_prompt_messages
+                )
+
+            advanced_completion_prompt_template = None
+            completion_prompt_config = config.get("completion_prompt_config", {})
+            if completion_prompt_config:
+                completion_prompt_template_params = {
+                    'prompt': completion_prompt_config['prompt']['text'],
+                }
+
+                if 'conversation_histories_role' in completion_prompt_config:
+                    completion_prompt_template_params['role_prefix'] = {
+                        'user': completion_prompt_config['conversation_histories_role']['user_prefix'],
+                        'assistant': completion_prompt_config['conversation_histories_role']['assistant_prefix']
+                    }
+
+                advanced_completion_prompt_template = AdvancedCompletionPromptTemplateEntity(
+                    **completion_prompt_template_params
+                )
+
+            return PromptTemplateEntity(
+                prompt_type=prompt_type,
+                advanced_chat_prompt_template=advanced_chat_prompt_template,
+                advanced_completion_prompt_template=advanced_completion_prompt_template
+            )
+
     @classmethod
     def validate_and_set_defaults(cls, app_mode: AppMode, config: dict) -> tuple[dict, list[str]]:
         """
@@ -83,4 +134,4 @@ class PromptValidator:
         if not isinstance(config["post_prompt"], str):
             raise ValueError("post_prompt must be of string type")
 
-        return config
+        return config

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

@@ -0,0 +1,184 @@
+import re
+from typing import Tuple
+
+from core.app.app_config.entities import VariableEntity, ExternalDataVariableEntity
+from core.external_data_tool.factory import ExternalDataToolFactory
+
+
+class BasicVariablesConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Tuple[list[VariableEntity], list[ExternalDataVariableEntity]]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        external_data_variables = []
+        variables = []
+
+        # old external_data_tools
+        external_data_tools = config.get('external_data_tools', [])
+        for external_data_tool in external_data_tools:
+            if 'enabled' not in external_data_tool or not external_data_tool['enabled']:
+                continue
+
+            external_data_variables.append(
+                ExternalDataVariableEntity(
+                    variable=external_data_tool['variable'],
+                    type=external_data_tool['type'],
+                    config=external_data_tool['config']
+                )
+            )
+
+        # 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]
+                external_data_variables.append(
+                    ExternalDataVariableEntity(
+                        variable=val['variable'],
+                        type=val['type'],
+                        config=val['config']
+                    )
+                )
+            elif typ in [
+                VariableEntity.Type.TEXT_INPUT.value,
+                VariableEntity.Type.PARAGRAPH.value,
+                VariableEntity.Type.NUMBER.value,
+            ]:
+                variables.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'),
+                    )
+                )
+
+        return variables, external_data_variables
+
+    @classmethod
+    def validate_and_set_defaults(cls, tenant_id: str, config: dict) -> tuple[dict, list[str]]:
+        """
+        Validate and set defaults for user input form
+
+        :param tenant_id: workspace id
+        :param config: app model config args
+        """
+        related_config_keys = []
+        config, current_related_config_keys = cls.validate_variables_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        config, current_related_config_keys = cls.validate_external_data_tools_and_set_defaults(tenant_id, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        return config, related_config_keys
+
+    @classmethod
+    def validate_variables_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
+        """
+        Validate and set defaults for user input form
+
+        :param config: app model config args
+        """
+        if not config.get("user_input_form"):
+            config["user_input_form"] = []
+
+        if not isinstance(config["user_input_form"], list):
+            raise ValueError("user_input_form must be a list of objects")
+
+        variables = []
+        for item in config["user_input_form"]:
+            key = list(item.keys())[0]
+            if key not in ["text-input", "select", "paragraph", "number", "external_data_tool"]:
+                raise ValueError("Keys in user_input_form list can only be 'text-input', 'paragraph'  or 'select'")
+
+            form_item = item[key]
+            if 'label' not in form_item:
+                raise ValueError("label is required in user_input_form")
+
+            if not isinstance(form_item["label"], str):
+                raise ValueError("label in user_input_form must be of string type")
+
+            if 'variable' not in form_item:
+                raise ValueError("variable is required in user_input_form")
+
+            if not isinstance(form_item["variable"], str):
+                raise ValueError("variable in user_input_form must be of string type")
+
+            pattern = re.compile(r"^(?!\d)[\u4e00-\u9fa5A-Za-z0-9_\U0001F300-\U0001F64F\U0001F680-\U0001F6FF]{1,100}$")
+            if pattern.match(form_item["variable"]) is None:
+                raise ValueError("variable in user_input_form must be a string, "
+                                 "and cannot start with a number")
+
+            variables.append(form_item["variable"])
+
+            if 'required' not in form_item or not form_item["required"]:
+                form_item["required"] = False
+
+            if not isinstance(form_item["required"], bool):
+                raise ValueError("required in user_input_form must be of boolean type")
+
+            if key == "select":
+                if 'options' not in form_item or not form_item["options"]:
+                    form_item["options"] = []
+
+                if not isinstance(form_item["options"], list):
+                    raise ValueError("options in user_input_form must be a list of strings")
+
+                if "default" in form_item and form_item['default'] \
+                        and form_item["default"] not in form_item["options"]:
+                    raise ValueError("default value in user_input_form must be in the options list")
+
+        return config, ["user_input_form"]
+
+    @classmethod
+    def validate_external_data_tools_and_set_defaults(cls, tenant_id: str, config: dict) -> tuple[dict, list[str]]:
+        """
+        Validate and set defaults for external data fetch feature
+
+        :param tenant_id: workspace id
+        :param config: app model config args
+        """
+        if not config.get("external_data_tools"):
+            config["external_data_tools"] = []
+
+        if not isinstance(config["external_data_tools"], list):
+            raise ValueError("external_data_tools must be of list type")
+
+        for tool in config["external_data_tools"]:
+            if "enabled" not in tool or not tool["enabled"]:
+                tool["enabled"] = False
+
+            if not tool["enabled"]:
+                continue
+
+            if "type" not in tool or not tool["type"]:
+                raise ValueError("external_data_tools[].type is required")
+
+            typ = tool["type"]
+            config = tool["config"]
+
+            ExternalDataToolFactory.validate_config(
+                name=typ,
+                tenant_id=tenant_id,
+                config=config
+            )
+
+        return config, ["external_data_tools"]

api/core/app/app_config/entities.py

@@ -1,12 +1,10 @@
 from enum import Enum
-from typing import Any, Literal, Optional, Union
+from typing import Any, Optional
 
 from pydantic import BaseModel
 
-from core.entities.provider_configuration import ProviderModelBundle
-from core.file.file_obj import FileObj
 from core.model_runtime.entities.message_entities import PromptMessageRole
-from core.model_runtime.entities.model_entities import AIModelEntity
+from models.model import AppMode
 
 
 class ModelConfigEntity(BaseModel):
@@ -15,10 +13,7 @@ class ModelConfigEntity(BaseModel):
     """
     provider: str
     model: str
-    model_schema: Optional[AIModelEntity] = None
+    mode: Optional[str] = None
-    mode: str
-    provider_model_bundle: ProviderModelBundle
-    credentials: dict[str, Any] = {}
     parameters: dict[str, Any] = {}
     stop: list[str] = []
 
@@ -194,149 +189,53 @@ class FileUploadEntity(BaseModel):
     image_config: Optional[dict[str, Any]] = None
 
 
-class AgentToolEntity(BaseModel):
+class AppAdditionalFeatures(BaseModel):
-    """
-    Agent Tool Entity.
-    """
-    provider_type: Literal["builtin", "api"]
-    provider_id: str
-    tool_name: str
-    tool_parameters: dict[str, Any] = {}
-
-
-class AgentPromptEntity(BaseModel):
-    """
-    Agent Prompt Entity.
-    """
-    first_prompt: str
-    next_iteration: str
-
-
-class AgentScratchpadUnit(BaseModel):
-    """
-    Agent First Prompt Entity.
-    """
-
-    class Action(BaseModel):
-        """
-        Action Entity.
-        """
-        action_name: str
-        action_input: Union[dict, str]
-
-    agent_response: Optional[str] = None
-    thought: Optional[str] = None
-    action_str: Optional[str] = None
-    observation: Optional[str] = None
-    action: Optional[Action] = None
-
-
-class AgentEntity(BaseModel):
-    """
-    Agent Entity.
-    """
-
-    class Strategy(Enum):
-        """
-        Agent Strategy.
-        """
-        CHAIN_OF_THOUGHT = 'chain-of-thought'
-        FUNCTION_CALLING = 'function-calling'
-
-    provider: str
-    model: str
-    strategy: Strategy
-    prompt: Optional[AgentPromptEntity] = None
-    tools: list[AgentToolEntity] = None
-    max_iteration: int = 5
-
-
-class AppOrchestrationConfigEntity(BaseModel):
-    """
-    App Orchestration Config Entity.
-    """
-    model_config: ModelConfigEntity
-    prompt_template: PromptTemplateEntity
-    variables: list[VariableEntity] = []
-    external_data_variables: list[ExternalDataVariableEntity] = []
-    agent: Optional[AgentEntity] = None
-
-    # features
-    dataset: Optional[DatasetEntity] = None
     file_upload: Optional[FileUploadEntity] = None
     opening_statement: Optional[str] = None
+    suggested_questions: list[str] = []
     suggested_questions_after_answer: bool = False
     show_retrieve_source: bool = False
     more_like_this: bool = False
     speech_to_text: bool = False
     text_to_speech: Optional[TextToSpeechEntity] = None
+
+
+class AppConfig(BaseModel):
+    """
+    Application Config Entity.
+    """
+    tenant_id: str
+    app_id: str
+    app_mode: AppMode
+    additional_features: AppAdditionalFeatures
+    variables: list[VariableEntity] = []
     sensitive_word_avoidance: Optional[SensitiveWordAvoidanceEntity] = None
 
 
-class InvokeFrom(Enum):
+class EasyUIBasedAppModelConfigFrom(Enum):
     """
-    Invoke From.
+    App Model Config From.
     """
-    SERVICE_API = 'service-api'
+    ARGS = 'args'
-    WEB_APP = 'web-app'
+    APP_LATEST_CONFIG = 'app-latest-config'
-    EXPLORE = 'explore'
+    CONVERSATION_SPECIFIC_CONFIG = 'conversation-specific-config'
-    DEBUGGER = 'debugger'
-
-    @classmethod
-    def value_of(cls, value: str) -> 'InvokeFrom':
-        """
-        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 invoke from value {value}')
-
-    def to_source(self) -> str:
-        """
-        Get source of invoke from.
-
-        :return: source
-        """
-        if self == InvokeFrom.WEB_APP:
-            return 'web_app'
-        elif self == InvokeFrom.DEBUGGER:
-            return 'dev'
-        elif self == InvokeFrom.EXPLORE:
-            return 'explore_app'
-        elif self == InvokeFrom.SERVICE_API:
-            return 'api'
-
-        return 'dev'
 
 
-class ApplicationGenerateEntity(BaseModel):
+class EasyUIBasedAppConfig(AppConfig):
     """
-    Application Generate Entity.
+    Easy UI Based App Config Entity.
     """
-    task_id: str
+    app_model_config_from: EasyUIBasedAppModelConfigFrom
-    tenant_id: str
-
-    app_id: str
     app_model_config_id: str
-    # for save
     app_model_config_dict: dict
-    app_model_config_override: bool
+    model: ModelConfigEntity
+    prompt_template: PromptTemplateEntity
+    dataset: Optional[DatasetEntity] = None
+    external_data_variables: list[ExternalDataVariableEntity] = []
 
-    # Converted from app_model_config to Entity object, or directly covered by external input
-    app_orchestration_config_entity: AppOrchestrationConfigEntity
 
-    conversation_id: Optional[str] = None
+class WorkflowUIBasedAppConfig(AppConfig):
-    inputs: dict[str, str]
+    """
-    query: Optional[str] = None
+    Workflow UI Based App Config Entity.
-    files: list[FileObj] = []
+    """
-    user_id: str
+    workflow_id: str
-    # extras
-    stream: bool
-    invoke_from: InvokeFrom
-
-    # extra parameters, like: auto_generate_conversation_name
-    extras: dict[str, Any] = {}

api/core/app/app_config/features/file_upload/manager.py

@@ -1,6 +1,30 @@
+from typing import Optional
+
+from core.app.app_config.entities import FileUploadEntity
 
 
-class FileUploadValidator:
+class FileUploadConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Optional[FileUploadEntity]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        file_upload_dict = config.get('file_upload')
+        if file_upload_dict:
+            if 'image' in file_upload_dict and file_upload_dict['image']:
+                if 'enabled' in file_upload_dict['image'] and file_upload_dict['image']['enabled']:
+                    return FileUploadEntity(
+                        image_config={
+                            'number_limits': file_upload_dict['image']['number_limits'],
+                            'detail': file_upload_dict['image']['detail'],
+                            'transfer_methods': file_upload_dict['image']['transfer_methods']
+                        }
+                    )
+
+        return None
+
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """

api/core/app/app_config/features/more_like_this/manager.py

@@ -1,6 +1,19 @@
+class MoreLikeThisConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> bool:
+        """
+        Convert model config to model config
 
+        :param config: model config args
+        """
+        more_like_this = False
+        more_like_this_dict = config.get('more_like_this')
+        if more_like_this_dict:
+            if 'enabled' in more_like_this_dict and more_like_this_dict['enabled']:
+                more_like_this = True
+
+        return more_like_this
 
-class MoreLikeThisValidator:
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """

api/core/app/app_config/features/opening_statement/manager.py

@@ -1,6 +1,22 @@
+from typing import Tuple
 
 
-class OpeningStatementValidator:
+class OpeningStatementConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> Tuple[str, list]:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        # opening statement
+        opening_statement = config.get('opening_statement')
+
+        # suggested questions
+        suggested_questions_list = config.get('suggested_questions')
+
+        return opening_statement, suggested_questions_list
+
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """

api/core/app/app_config/features/retrieval_resource/manager.py

@@ -1,6 +1,14 @@
+class RetrievalResourceConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> bool:
+        show_retrieve_source = False
+        retriever_resource_dict = config.get('retriever_resource')
+        if retriever_resource_dict:
+            if 'enabled' in retriever_resource_dict and retriever_resource_dict['enabled']:
+                show_retrieve_source = True
 
+        return show_retrieve_source
 
-class RetrieverResourceValidator:
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """

api/core/app/app_config/features/speech_to_text/manager.py

@@ -1,6 +1,19 @@
+class SpeechToTextConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> bool:
+        """
+        Convert model config to model config
 
+        :param config: model config args
+        """
+        speech_to_text = False
+        speech_to_text_dict = config.get('speech_to_text')
+        if speech_to_text_dict:
+            if 'enabled' in speech_to_text_dict and speech_to_text_dict['enabled']:
+                speech_to_text = True
+
+        return speech_to_text
 
-class SpeechToTextValidator:
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """

api/core/app/app_config/features/suggested_questions_after_answer/manager.py

@@ -1,6 +1,19 @@
+class SuggestedQuestionsAfterAnswerConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> bool:
+        """
+        Convert model config to model config
 
+        :param config: model config args
+        """
+        suggested_questions_after_answer = False
+        suggested_questions_after_answer_dict = config.get('suggested_questions_after_answer')
+        if suggested_questions_after_answer_dict:
+            if 'enabled' in suggested_questions_after_answer_dict and suggested_questions_after_answer_dict['enabled']:
+                suggested_questions_after_answer = True
+
+        return suggested_questions_after_answer
 
-class SuggestedQuestionsValidator:
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """
@@ -16,7 +29,8 @@ class SuggestedQuestionsValidator:
         if not isinstance(config["suggested_questions_after_answer"], dict):
             raise ValueError("suggested_questions_after_answer must be of dict type")
 
-        if "enabled" not in config["suggested_questions_after_answer"] or not config["suggested_questions_after_answer"]["enabled"]:
+        if "enabled" not in config["suggested_questions_after_answer"] or not \
+        config["suggested_questions_after_answer"]["enabled"]:
             config["suggested_questions_after_answer"]["enabled"] = False
 
         if not isinstance(config["suggested_questions_after_answer"]["enabled"], bool):

api/core/app/app_config/features/text_to_speech/manager.py

@@ -1,6 +1,26 @@
+from core.app.app_config.entities import TextToSpeechEntity
 
 
-class TextToSpeechValidator:
+class TextToSpeechConfigManager:
+    @classmethod
+    def convert(cls, config: dict) -> bool:
+        """
+        Convert model config to model config
+
+        :param config: model config args
+        """
+        text_to_speech = False
+        text_to_speech_dict = config.get('text_to_speech')
+        if text_to_speech_dict:
+            if 'enabled' in text_to_speech_dict and text_to_speech_dict['enabled']:
+                text_to_speech = TextToSpeechEntity(
+                    enabled=text_to_speech_dict.get('enabled'),
+                    voice=text_to_speech_dict.get('voice'),
+                    language=text_to_speech_dict.get('language'),
+                )
+
+        return text_to_speech
+
     @classmethod
     def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
         """

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

@@ -0,0 +1,22 @@
+from core.app.app_config.entities import VariableEntity
+from models.workflow import Workflow
+
+
+class WorkflowVariablesConfigManager:
+    @classmethod
+    def convert(cls, workflow: Workflow) -> list[VariableEntity]:
+        """
+        Convert workflow start variables to variables
+
+        :param workflow: workflow instance
+        """
+        variables = []
+
+        # find start node
+        user_input_form = workflow.user_input_form()
+
+        # variables
+        for variable in user_input_form:
+            variables.append(VariableEntity(**variable))
+
+        return variables

api/core/app/app_manager.py

@@ -8,13 +8,18 @@ from typing import Any, Optional, Union, cast
 from flask import Flask, current_app
 from pydantic import ValidationError
 
-from core.app.agent_chat.app_runner import AgentChatAppRunner
+from core.app.app_config.easy_ui_based_app.model_config.converter import EasyUIBasedModelConfigEntityConverter
-from core.app.app_orchestration_config_converter import AppOrchestrationConfigConverter
+from core.app.app_config.entities import EasyUIBasedAppModelConfigFrom, EasyUIBasedAppConfig, VariableEntity
+from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfigManager
+from core.app.apps.agent_chat.app_runner import AgentChatAppRunner
 from core.app.app_queue_manager import AppQueueManager, ConversationTaskStoppedException, PublishFrom
-from core.app.chat.app_runner import ChatAppRunner
+from core.app.apps.chat.app_config_manager import ChatAppConfigManager
+from core.app.apps.chat.app_runner import ChatAppRunner
+from core.app.apps.completion.app_config_manager import CompletionAppConfigManager
+from core.app.apps.completion.app_runner import CompletionAppRunner
 from core.app.generate_task_pipeline import GenerateTaskPipeline
-from core.entities.application_entities import (
+from core.app.entities.app_invoke_entities import (
-    ApplicationGenerateEntity,
+    EasyUIBasedAppGenerateEntity,
     InvokeFrom,
 )
 from core.file.file_obj import FileObj
@@ -23,24 +28,19 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser
 from extensions.ext_database import db
 from models.account import Account
-from models.model import App, Conversation, EndUser, Message, MessageFile
+from models.model import App, Conversation, EndUser, Message, MessageFile, AppMode, AppModelConfig
 
 logger = logging.getLogger(__name__)
 
 
-class AppManager:
+class EasyUIBasedAppManager:
-    """
-    This class is responsible for managing application
-    """
 
-    def generate(self, tenant_id: str,
+    def generate(self, app_model: App,
-                 app_id: str,
+                 app_model_config: AppModelConfig,
-                 app_model_config_id: str,
-                 app_model_config_dict: dict,
-                 app_model_config_override: bool,
                  user: Union[Account, EndUser],
                  invoke_from: InvokeFrom,
                  inputs: dict[str, str],
+                 app_model_config_dict: Optional[dict] = None,
                  query: Optional[str] = None,
                  files: Optional[list[FileObj]] = None,
                  conversation: Optional[Conversation] = None,
@@ -50,14 +50,12 @@ class AppManager:
         """
         Generate App response.
 
-        :param tenant_id: workspace ID
+        :param app_model: App
-        :param app_id: app ID
+        :param app_model_config: app model config
-        :param app_model_config_id: app model config id
-        :param app_model_config_dict: app model config dict
-        :param app_model_config_override: app model config override
         :param user: account or end user
         :param invoke_from: invoke from source
         :param inputs: inputs
+        :param app_model_config_dict: app model config dict
         :param query: query
         :param files: file obj list
         :param conversation: conversation
@@ -67,20 +65,21 @@ class AppManager:
         # init task id
         task_id = str(uuid.uuid4())
 
-        # init application generate entity
+        # convert to app config
-        application_generate_entity = ApplicationGenerateEntity(
+        app_config = self.convert_to_app_config(
-            task_id=task_id,
+            app_model=app_model,
-            tenant_id=tenant_id,
+            app_model_config=app_model_config,
-            app_id=app_id,
-            app_model_config_id=app_model_config_id,
             app_model_config_dict=app_model_config_dict,
-            app_orchestration_config_entity=AppOrchestrationConfigConverter.convert_from_app_model_config_dict(
+            conversation=conversation
-                tenant_id=tenant_id,
+        )
-                app_model_config_dict=app_model_config_dict
+
-            ),
+        # init application generate entity
-            app_model_config_override=app_model_config_override,
+        application_generate_entity = EasyUIBasedAppGenerateEntity(
+            task_id=task_id,
+            app_config=app_config,
+            model_config=EasyUIBasedModelConfigEntityConverter.convert(app_config),
             conversation_id=conversation.id if conversation else None,
-            inputs=conversation.inputs if conversation else inputs,
+            inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query.replace('\x00', '') if query else None,
             files=files if files else [],
             user_id=user.id,
@@ -89,7 +88,7 @@ class AppManager:
             extras=extras
         )
 
-        if not stream and application_generate_entity.app_orchestration_config_entity.agent:
+        if not stream and application_generate_entity.app_config.app_mode == AppMode.AGENT_CHAT:
             raise ValueError("Agent app is not supported in blocking mode.")
 
         # init generate records
@@ -128,8 +127,85 @@ class AppManager:
             stream=stream
         )
 
+    def convert_to_app_config(self, app_model: App,
+                              app_model_config: AppModelConfig,
+                              app_model_config_dict: Optional[dict] = None,
+                              conversation: Optional[Conversation] = None) -> EasyUIBasedAppConfig:
+        if app_model_config_dict:
+            config_from = EasyUIBasedAppModelConfigFrom.ARGS
+        elif conversation:
+            config_from = EasyUIBasedAppModelConfigFrom.CONVERSATION_SPECIFIC_CONFIG
+        else:
+            config_from = EasyUIBasedAppModelConfigFrom.APP_LATEST_CONFIG
+
+        app_mode = AppMode.value_of(app_model.mode)
+        if app_mode == AppMode.AGENT_CHAT or app_model.is_agent:
+            app_model.mode = AppMode.AGENT_CHAT.value
+            app_config = AgentChatAppConfigManager.config_convert(
+                app_model=app_model,
+                config_from=config_from,
+                app_model_config=app_model_config,
+                config_dict=app_model_config_dict
+            )
+        elif app_mode == AppMode.CHAT:
+            app_config = ChatAppConfigManager.config_convert(
+                app_model=app_model,
+                config_from=config_from,
+                app_model_config=app_model_config,
+                config_dict=app_model_config_dict
+            )
+        elif app_mode == AppMode.COMPLETION:
+            app_config = CompletionAppConfigManager.config_convert(
+                app_model=app_model,
+                config_from=config_from,
+                app_model_config=app_model_config,
+                config_dict=app_model_config_dict
+            )
+        else:
+            raise ValueError("Invalid app mode")
+
+        return app_config
+
+    def _get_cleaned_inputs(self, user_inputs: dict, app_config: EasyUIBasedAppConfig):
+        if user_inputs is None:
+            user_inputs = {}
+
+        filtered_inputs = {}
+
+        # Filter input variables from form configuration, handle required fields, default values, and option values
+        variables = app_config.variables
+        for variable_config in variables:
+            variable = variable_config.variable
+
+            if variable not in user_inputs or not user_inputs[variable]:
+                if variable_config.required:
+                    raise ValueError(f"{variable} is required in input form")
+                else:
+                    filtered_inputs[variable] = variable_config.default if variable_config.default is not None else ""
+                    continue
+
+            value = user_inputs[variable]
+
+            if value:
+                if not isinstance(value, str):
+                    raise ValueError(f"{variable} in input form must be a string")
+
+            if variable_config.type == VariableEntity.Type.SELECT:
+                options = variable_config.options if variable_config.options is not None else []
+                if value not in options:
+                    raise ValueError(f"{variable} in input form must be one of the following: {options}")
+            else:
+                if variable_config.max_length is not None:
+                    max_length = variable_config.max_length
+                    if len(value) > max_length:
+                        raise ValueError(f'{variable} in input form must be less than {max_length} characters')
+
+            filtered_inputs[variable] = value.replace('\x00', '') if value else None
+
+        return filtered_inputs
+
     def _generate_worker(self, flask_app: Flask,
-                         application_generate_entity: ApplicationGenerateEntity,
+                         application_generate_entity: EasyUIBasedAppGenerateEntity,
                          queue_manager: AppQueueManager,
                          conversation_id: str,
                          message_id: str) -> None:
@@ -148,7 +224,7 @@ class AppManager:
                 conversation = self._get_conversation(conversation_id)
                 message = self._get_message(message_id)
 
-                if application_generate_entity.app_orchestration_config_entity.agent:
+                if application_generate_entity.app_config.app_mode == AppMode.AGENT_CHAT:
                     # agent app
                     runner = AgentChatAppRunner()
                     runner.run(
@@ -157,8 +233,8 @@ class AppManager:
                         conversation=conversation,
                         message=message
                     )
-                else:
+                elif application_generate_entity.app_config.app_mode == AppMode.CHAT:
-                    # basic app
+                    # chatbot app
                     runner = ChatAppRunner()
                     runner.run(
                         application_generate_entity=application_generate_entity,
@@ -166,6 +242,16 @@ class AppManager:
                         conversation=conversation,
                         message=message
                     )
+                elif application_generate_entity.app_config.app_mode == AppMode.COMPLETION:
+                    # completion app
+                    runner = CompletionAppRunner()
+                    runner.run(
+                        application_generate_entity=application_generate_entity,
+                        queue_manager=queue_manager,
+                        message=message
+                    )
+                else:
+                    raise ValueError("Invalid app mode")
             except ConversationTaskStoppedException:
                 pass
             except InvokeAuthorizationError:
@@ -184,7 +270,7 @@ class AppManager:
             finally:
                 db.session.remove()
 
-    def _handle_response(self, application_generate_entity: ApplicationGenerateEntity,
+    def _handle_response(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
                          queue_manager: AppQueueManager,
                          conversation: Conversation,
                          message: Message,
@@ -217,24 +303,24 @@ class AppManager:
         finally:
             db.session.remove()
 
-    def _init_generate_records(self, application_generate_entity: ApplicationGenerateEntity) \
+    def _init_generate_records(self, application_generate_entity: EasyUIBasedAppGenerateEntity) \
             -> tuple[Conversation, Message]:
         """
         Initialize generate records
         :param application_generate_entity: application generate entity
         :return:
         """
-        app_orchestration_config_entity = application_generate_entity.app_orchestration_config_entity
+        model_type_instance = application_generate_entity.model_config.provider_model_bundle.model_type_instance
-
-        model_type_instance = app_orchestration_config_entity.model_config.provider_model_bundle.model_type_instance
         model_type_instance = cast(LargeLanguageModel, model_type_instance)
         model_schema = model_type_instance.get_model_schema(
-            model=app_orchestration_config_entity.model_config.model,
+            model=application_generate_entity.model_config.model,
-            credentials=app_orchestration_config_entity.model_config.credentials
+            credentials=application_generate_entity.model_config.credentials
         )
 
+        app_config = application_generate_entity.app_config
+
         app_record = (db.session.query(App)
-                      .filter(App.id == application_generate_entity.app_id).first())
+                      .filter(App.id == app_config.app_id).first())
 
         app_mode = app_record.mode
 
@@ -249,8 +335,8 @@ class AppManager:
             account_id = application_generate_entity.user_id
 
         override_model_configs = None
-        if application_generate_entity.app_model_config_override:
+        if app_config.app_model_config_from == EasyUIBasedAppModelConfigFrom.ARGS:
-            override_model_configs = application_generate_entity.app_model_config_dict
+            override_model_configs = app_config.app_model_config_dict
 
         introduction = ''
         if app_mode == 'chat':
@@ -260,9 +346,9 @@ class AppManager:
         if not application_generate_entity.conversation_id:
             conversation = Conversation(
                 app_id=app_record.id,
-                app_model_config_id=application_generate_entity.app_model_config_id,
+                app_model_config_id=app_config.app_model_config_id,
-                model_provider=app_orchestration_config_entity.model_config.provider,
+                model_provider=application_generate_entity.model_config.provider,
-                model_id=app_orchestration_config_entity.model_config.model,
+                model_id=application_generate_entity.model_config.model,
                 override_model_configs=json.dumps(override_model_configs) if override_model_configs else None,
                 mode=app_mode,
                 name='New conversation',
@@ -291,8 +377,8 @@ class AppManager:
 
         message = Message(
             app_id=app_record.id,
-            model_provider=app_orchestration_config_entity.model_config.provider,
+            model_provider=application_generate_entity.model_config.provider,
-            model_id=app_orchestration_config_entity.model_config.model,
+            model_id=application_generate_entity.model_config.model,
             override_model_configs=json.dumps(override_model_configs) if override_model_configs else None,
             conversation_id=conversation.id,
             inputs=application_generate_entity.inputs,
@@ -311,7 +397,7 @@ class AppManager:
             from_source=from_source,
             from_end_user_id=end_user_id,
             from_account_id=account_id,
-            agent_based=app_orchestration_config_entity.agent is not None
+            agent_based=app_config.app_mode == AppMode.AGENT_CHAT,
         )
 
         db.session.add(message)
@@ -333,14 +419,14 @@ class AppManager:
 
         return conversation, message
 
-    def _get_conversation_introduction(self, application_generate_entity: ApplicationGenerateEntity) -> str:
+    def _get_conversation_introduction(self, application_generate_entity: EasyUIBasedAppGenerateEntity) -> str:
         """
         Get conversation introduction
         :param application_generate_entity: application generate entity
         :return: conversation introduction
         """
-        app_orchestration_config_entity = application_generate_entity.app_orchestration_config_entity
+        app_config = application_generate_entity.app_config
-        introduction = app_orchestration_config_entity.opening_statement
+        introduction = app_config.additional_features.opening_statement
 
         if introduction:
             try:

api/core/app/app_orchestration_config_converter.py

@@ -1,421 +0,0 @@
-from typing import cast
-
-from core.entities.application_entities import (
-    AdvancedChatPromptTemplateEntity,
-    AdvancedCompletionPromptTemplateEntity,
-    AgentEntity,
-    AgentPromptEntity,
-    AgentToolEntity,
-    AppOrchestrationConfigEntity,
-    DatasetEntity,
-    DatasetRetrieveConfigEntity,
-    ExternalDataVariableEntity,
-    FileUploadEntity,
-    ModelConfigEntity,
-    PromptTemplateEntity,
-    SensitiveWordAvoidanceEntity,
-    TextToSpeechEntity,
-    VariableEntity,
-)
-from core.entities.model_entities import ModelStatus
-from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
-from core.model_runtime.entities.message_entities import PromptMessageRole
-from core.model_runtime.entities.model_entities import ModelType
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from core.provider_manager import ProviderManager
-from core.tools.prompt.template import REACT_PROMPT_TEMPLATES
-
-
-class AppOrchestrationConfigConverter:
-    @classmethod
-    def convert_from_app_model_config_dict(cls, tenant_id: str,
-                                           app_model_config_dict: dict,
-                                           skip_check: bool = False) \
-            -> AppOrchestrationConfigEntity:
-        """
-        Convert app model config dict to entity.
-        :param tenant_id: tenant ID
-        :param app_model_config_dict: app model config dict
-        :param skip_check: skip check
-        :raises ProviderTokenNotInitError: provider token not init error
-        :return: app orchestration config entity
-        """
-        properties = {}
-
-        copy_app_model_config_dict = app_model_config_dict.copy()
-
-        provider_manager = ProviderManager()
-        provider_model_bundle = provider_manager.get_provider_model_bundle(
-            tenant_id=tenant_id,
-            provider=copy_app_model_config_dict['model']['provider'],
-            model_type=ModelType.LLM
-        )
-
-        provider_name = provider_model_bundle.configuration.provider.provider
-        model_name = copy_app_model_config_dict['model']['name']
-
-        model_type_instance = provider_model_bundle.model_type_instance
-        model_type_instance = cast(LargeLanguageModel, model_type_instance)
-
-        # check model credentials
-        model_credentials = provider_model_bundle.configuration.get_current_credentials(
-            model_type=ModelType.LLM,
-            model=copy_app_model_config_dict['model']['name']
-        )
-
-        if model_credentials is None:
-            if not skip_check:
-                raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
-            else:
-                model_credentials = {}
-
-        if not skip_check:
-            # check model
-            provider_model = provider_model_bundle.configuration.get_provider_model(
-                model=copy_app_model_config_dict['model']['name'],
-                model_type=ModelType.LLM
-            )
-
-            if provider_model is None:
-                model_name = copy_app_model_config_dict['model']['name']
-                raise ValueError(f"Model {model_name} not exist.")
-
-            if provider_model.status == ModelStatus.NO_CONFIGURE:
-                raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
-            elif provider_model.status == ModelStatus.NO_PERMISSION:
-                raise ModelCurrentlyNotSupportError(f"Dify Hosted OpenAI {model_name} currently not support.")
-            elif provider_model.status == ModelStatus.QUOTA_EXCEEDED:
-                raise QuotaExceededError(f"Model provider {provider_name} quota exceeded.")
-
-        # model config
-        completion_params = copy_app_model_config_dict['model'].get('completion_params')
-        stop = []
-        if 'stop' in completion_params:
-            stop = completion_params['stop']
-            del completion_params['stop']
-
-        # get model mode
-        model_mode = copy_app_model_config_dict['model'].get('mode')
-        if not model_mode:
-            mode_enum = model_type_instance.get_model_mode(
-                model=copy_app_model_config_dict['model']['name'],
-                credentials=model_credentials
-            )
-
-            model_mode = mode_enum.value
-
-        model_schema = model_type_instance.get_model_schema(
-            copy_app_model_config_dict['model']['name'],
-            model_credentials
-        )
-
-        if not skip_check and not model_schema:
-            raise ValueError(f"Model {model_name} not exist.")
-
-        properties['model_config'] = ModelConfigEntity(
-            provider=copy_app_model_config_dict['model']['provider'],
-            model=copy_app_model_config_dict['model']['name'],
-            model_schema=model_schema,
-            mode=model_mode,
-            provider_model_bundle=provider_model_bundle,
-            credentials=model_credentials,
-            parameters=completion_params,
-            stop=stop,
-        )
-
-        # prompt template
-        prompt_type = PromptTemplateEntity.PromptType.value_of(copy_app_model_config_dict['prompt_type'])
-        if prompt_type == PromptTemplateEntity.PromptType.SIMPLE:
-            simple_prompt_template = copy_app_model_config_dict.get("pre_prompt", "")
-            properties['prompt_template'] = PromptTemplateEntity(
-                prompt_type=prompt_type,
-                simple_prompt_template=simple_prompt_template
-            )
-        else:
-            advanced_chat_prompt_template = None
-            chat_prompt_config = copy_app_model_config_dict.get("chat_prompt_config", {})
-            if chat_prompt_config:
-                chat_prompt_messages = []
-                for message in chat_prompt_config.get("prompt", []):
-                    chat_prompt_messages.append({
-                        "text": message["text"],
-                        "role": PromptMessageRole.value_of(message["role"])
-                    })
-
-                advanced_chat_prompt_template = AdvancedChatPromptTemplateEntity(
-                    messages=chat_prompt_messages
-                )
-
-            advanced_completion_prompt_template = None
-            completion_prompt_config = copy_app_model_config_dict.get("completion_prompt_config", {})
-            if completion_prompt_config:
-                completion_prompt_template_params = {
-                    'prompt': completion_prompt_config['prompt']['text'],
-                }
-
-                if 'conversation_histories_role' in completion_prompt_config:
-                    completion_prompt_template_params['role_prefix'] = {
-                        'user': completion_prompt_config['conversation_histories_role']['user_prefix'],
-                        'assistant': completion_prompt_config['conversation_histories_role']['assistant_prefix']
-                    }
-
-                advanced_completion_prompt_template = AdvancedCompletionPromptTemplateEntity(
-                    **completion_prompt_template_params
-                )
-
-            properties['prompt_template'] = PromptTemplateEntity(
-                prompt_type=prompt_type,
-                advanced_chat_prompt_template=advanced_chat_prompt_template,
-                advanced_completion_prompt_template=advanced_completion_prompt_template
-            )
-
-        # external data variables
-        properties['external_data_variables'] = []
-
-        # old external_data_tools
-        external_data_tools = copy_app_model_config_dict.get('external_data_tools', [])
-        for external_data_tool in external_data_tools:
-            if 'enabled' not in external_data_tool or not external_data_tool['enabled']:
-                continue
-
-            properties['external_data_variables'].append(
-                ExternalDataVariableEntity(
-                    variable=external_data_tool['variable'],
-                    type=external_data_tool['type'],
-                    config=external_data_tool['config']
-                )
-            )
-
-        properties['variables'] = []
-
-        # variables and external_data_tools
-        for variable in copy_app_model_config_dict.get('user_input_form', []):
-            typ = list(variable.keys())[0]
-            if typ == 'external_data_tool':
-                val = variable[typ]
-                properties['external_data_variables'].append(
-                    ExternalDataVariableEntity(
-                        variable=val['variable'],
-                        type=val['type'],
-                        config=val['config']
-                    )
-                )
-            elif typ in [
-                VariableEntity.Type.TEXT_INPUT.value,
-                VariableEntity.Type.PARAGRAPH.value,
-                VariableEntity.Type.NUMBER.value,
-            ]:
-                properties['variables'].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:
-                properties['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'),
-                    )
-                )
-
-        # show retrieve source
-        show_retrieve_source = False
-        retriever_resource_dict = copy_app_model_config_dict.get('retriever_resource')
-        if retriever_resource_dict:
-            if 'enabled' in retriever_resource_dict and retriever_resource_dict['enabled']:
-                show_retrieve_source = True
-
-        properties['show_retrieve_source'] = show_retrieve_source
-
-        dataset_ids = []
-        if 'datasets' in copy_app_model_config_dict.get('dataset_configs', {}):
-            datasets = copy_app_model_config_dict.get('dataset_configs', {}).get('datasets', {
-                'strategy': 'router',
-                'datasets': []
-            })
-
-            for dataset in datasets.get('datasets', []):
-                keys = list(dataset.keys())
-                if len(keys) == 0 or keys[0] != 'dataset':
-                    continue
-                dataset = dataset['dataset']
-
-                if 'enabled' not in dataset or not dataset['enabled']:
-                    continue
-
-                dataset_id = dataset.get('id', None)
-                if dataset_id:
-                    dataset_ids.append(dataset_id)
-
-        if 'agent_mode' in copy_app_model_config_dict and copy_app_model_config_dict['agent_mode'] \
-                and 'enabled' in copy_app_model_config_dict['agent_mode'] \
-                and copy_app_model_config_dict['agent_mode']['enabled']:
-
-            agent_dict = copy_app_model_config_dict.get('agent_mode', {})
-            agent_strategy = agent_dict.get('strategy', 'cot')
-
-            if agent_strategy == 'function_call':
-                strategy = AgentEntity.Strategy.FUNCTION_CALLING
-            elif agent_strategy == 'cot' or agent_strategy == 'react':
-                strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
-            else:
-                # old configs, try to detect default strategy
-                if copy_app_model_config_dict['model']['provider'] == 'openai':
-                    strategy = AgentEntity.Strategy.FUNCTION_CALLING
-                else:
-                    strategy = AgentEntity.Strategy.CHAIN_OF_THOUGHT
-
-            agent_tools = []
-            for tool in agent_dict.get('tools', []):
-                keys = tool.keys()
-                if len(keys) >= 4:
-                    if "enabled" not in tool or not tool["enabled"]:
-                        continue
-
-                    agent_tool_properties = {
-                        'provider_type': tool['provider_type'],
-                        'provider_id': tool['provider_id'],
-                        'tool_name': tool['tool_name'],
-                        'tool_parameters': tool['tool_parameters'] if 'tool_parameters' in tool else {}
-                    }
-
-                    agent_tools.append(AgentToolEntity(**agent_tool_properties))
-                elif len(keys) == 1:
-                    # old standard
-                    key = list(tool.keys())[0]
-
-                    if key != 'dataset':
-                        continue
-
-                    tool_item = tool[key]
-
-                    if "enabled" not in tool_item or not tool_item["enabled"]:
-                        continue
-
-                    dataset_id = tool_item['id']
-                    dataset_ids.append(dataset_id)
-
-            if 'strategy' in copy_app_model_config_dict['agent_mode'] and \
-                    copy_app_model_config_dict['agent_mode']['strategy'] not in ['react_router', 'router']:
-                agent_prompt = agent_dict.get('prompt', None) or {}
-                # check model mode
-                model_mode = copy_app_model_config_dict.get('model', {}).get('mode', 'completion')
-                if model_mode == 'completion':
-                    agent_prompt_entity = AgentPromptEntity(
-                        first_prompt=agent_prompt.get('first_prompt',
-                                                      REACT_PROMPT_TEMPLATES['english']['completion']['prompt']),
-                        next_iteration=agent_prompt.get('next_iteration',
-                                                        REACT_PROMPT_TEMPLATES['english']['completion'][
-                                                            'agent_scratchpad']),
-                    )
-                else:
-                    agent_prompt_entity = AgentPromptEntity(
-                        first_prompt=agent_prompt.get('first_prompt',
-                                                      REACT_PROMPT_TEMPLATES['english']['chat']['prompt']),
-                        next_iteration=agent_prompt.get('next_iteration',
-                                                        REACT_PROMPT_TEMPLATES['english']['chat']['agent_scratchpad']),
-                    )
-
-                properties['agent'] = AgentEntity(
-                    provider=properties['model_config'].provider,
-                    model=properties['model_config'].model,
-                    strategy=strategy,
-                    prompt=agent_prompt_entity,
-                    tools=agent_tools,
-                    max_iteration=agent_dict.get('max_iteration', 5)
-                )
-
-        if len(dataset_ids) > 0:
-            # dataset configs
-            dataset_configs = copy_app_model_config_dict.get('dataset_configs', {'retrieval_model': 'single'})
-            query_variable = copy_app_model_config_dict.get('dataset_query_variable')
-
-            if dataset_configs['retrieval_model'] == 'single':
-                properties['dataset'] = DatasetEntity(
-                    dataset_ids=dataset_ids,
-                    retrieve_config=DatasetRetrieveConfigEntity(
-                        query_variable=query_variable,
-                        retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
-                            dataset_configs['retrieval_model']
-                        )
-                    )
-                )
-            else:
-                properties['dataset'] = DatasetEntity(
-                    dataset_ids=dataset_ids,
-                    retrieve_config=DatasetRetrieveConfigEntity(
-                        query_variable=query_variable,
-                        retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.value_of(
-                            dataset_configs['retrieval_model']
-                        ),
-                        top_k=dataset_configs.get('top_k'),
-                        score_threshold=dataset_configs.get('score_threshold'),
-                        reranking_model=dataset_configs.get('reranking_model')
-                    )
-                )
-
-        # file upload
-        file_upload_dict = copy_app_model_config_dict.get('file_upload')
-        if file_upload_dict:
-            if 'image' in file_upload_dict and file_upload_dict['image']:
-                if 'enabled' in file_upload_dict['image'] and file_upload_dict['image']['enabled']:
-                    properties['file_upload'] = FileUploadEntity(
-                        image_config={
-                            'number_limits': file_upload_dict['image']['number_limits'],
-                            'detail': file_upload_dict['image']['detail'],
-                            'transfer_methods': file_upload_dict['image']['transfer_methods']
-                        }
-                    )
-
-        # opening statement
-        properties['opening_statement'] = copy_app_model_config_dict.get('opening_statement')
-
-        # suggested questions after answer
-        suggested_questions_after_answer_dict = copy_app_model_config_dict.get('suggested_questions_after_answer')
-        if suggested_questions_after_answer_dict:
-            if 'enabled' in suggested_questions_after_answer_dict and suggested_questions_after_answer_dict['enabled']:
-                properties['suggested_questions_after_answer'] = True
-
-        # more like this
-        more_like_this_dict = copy_app_model_config_dict.get('more_like_this')
-        if more_like_this_dict:
-            if 'enabled' in more_like_this_dict and more_like_this_dict['enabled']:
-                properties['more_like_this'] = True
-
-        # speech to text
-        speech_to_text_dict = copy_app_model_config_dict.get('speech_to_text')
-        if speech_to_text_dict:
-            if 'enabled' in speech_to_text_dict and speech_to_text_dict['enabled']:
-                properties['speech_to_text'] = True
-
-        # text to speech
-        text_to_speech_dict = copy_app_model_config_dict.get('text_to_speech')
-        if text_to_speech_dict:
-            if 'enabled' in text_to_speech_dict and text_to_speech_dict['enabled']:
-                properties['text_to_speech'] = TextToSpeechEntity(
-                    enabled=text_to_speech_dict.get('enabled'),
-                    voice=text_to_speech_dict.get('voice'),
-                    language=text_to_speech_dict.get('language'),
-                )
-
-        # sensitive word avoidance
-        sensitive_word_avoidance_dict = copy_app_model_config_dict.get('sensitive_word_avoidance')
-        if sensitive_word_avoidance_dict:
-            if 'enabled' in sensitive_word_avoidance_dict and sensitive_word_avoidance_dict['enabled']:
-                properties['sensitive_word_avoidance'] = SensitiveWordAvoidanceEntity(
-                    type=sensitive_word_avoidance_dict.get('type'),
-                    config=sensitive_word_avoidance_dict.get('config'),
-                )
-
-        return AppOrchestrationConfigEntity(**properties)

api/core/app/app_queue_manager.py

@@ -6,8 +6,8 @@ from typing import Any
 
 from sqlalchemy.orm import DeclarativeMeta
 
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
-from core.entities.queue_entities import (
+from core.app.entities.queue_entities import (
     AnnotationReplyEvent,
     AppQueueEvent,
     QueueAgentMessageEvent,

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

@@ -0,0 +1,94 @@
+from core.app.app_config.base_app_config_manager import BaseAppConfigManager
+from core.app.app_config.common.sensitive_word_avoidance.manager import SensitiveWordAvoidanceConfigManager
+from core.app.app_config.entities import WorkflowUIBasedAppConfig
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.app_config.features.opening_statement.manager import OpeningStatementConfigManager
+from core.app.app_config.features.retrieval_resource.manager import RetrievalResourceConfigManager
+from core.app.app_config.features.speech_to_text.manager import SpeechToTextConfigManager
+from core.app.app_config.features.suggested_questions_after_answer.manager import \
+    SuggestedQuestionsAfterAnswerConfigManager
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
+from core.app.app_config.workflow_ui_based_app.variables.manager import WorkflowVariablesConfigManager
+from models.model import AppMode, App
+from models.workflow import Workflow
+
+
+class AdvancedChatAppConfig(WorkflowUIBasedAppConfig):
+    """
+    Advanced Chatbot App Config Entity.
+    """
+    pass
+
+
+class AdvancedChatAppConfigManager(BaseAppConfigManager):
+    @classmethod
+    def config_convert(cls, app_model: App, workflow: Workflow) -> AdvancedChatAppConfig:
+        features_dict = workflow.features_dict
+
+        app_config = AdvancedChatAppConfig(
+            tenant_id=app_model.tenant_id,
+            app_id=app_model.id,
+            app_mode=AppMode.value_of(app_model.mode),
+            workflow_id=workflow.id,
+            sensitive_word_avoidance=SensitiveWordAvoidanceConfigManager.convert(
+                config=features_dict
+            ),
+            variables=WorkflowVariablesConfigManager.convert(
+                workflow=workflow
+            ),
+            additional_features=cls.convert_features(features_dict)
+        )
+
+        return app_config
+
+    @classmethod
+    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False) -> dict:
+        """
+        Validate for advanced chat app model config
+
+        :param tenant_id: tenant id
+        :param config: app model config args
+        :param only_structure_validate: if True, only structure validation will be performed
+        """
+        related_config_keys = []
+
+        # file upload validation
+        config, current_related_config_keys = FileUploadConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # opening_statement
+        config, current_related_config_keys = OpeningStatementConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # suggested_questions_after_answer
+        config, current_related_config_keys = SuggestedQuestionsAfterAnswerConfigManager.validate_and_set_defaults(
+            config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # speech_to_text
+        config, current_related_config_keys = SpeechToTextConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # text_to_speech
+        config, current_related_config_keys = TextToSpeechConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # return retriever resource
+        config, current_related_config_keys = RetrievalResourceConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # moderation validation
+        config, current_related_config_keys = SensitiveWordAvoidanceConfigManager.validate_and_set_defaults(
+            tenant_id=tenant_id,
+            config=config,
+            only_structure_validate=only_structure_validate
+        )
+        related_config_keys.extend(current_related_config_keys)
+
+        related_config_keys = list(set(related_config_keys))
+
+        # Filter out extra parameters
+        filtered_config = {key: config.get(key) for key in related_config_keys}
+
+        return filtered_config
+

api/core/app/apps/agent_chat/app_config_manager.py

@@ -1,24 +1,82 @@
 import uuid
+from typing import Optional
 
-from core.app.validators.dataset_retrieval import DatasetValidator
+from core.agent.entities import AgentEntity
-from core.app.validators.external_data_fetch import ExternalDataFetchValidator
+from core.app.app_config.base_app_config_manager import BaseAppConfigManager
-from core.app.validators.file_upload import FileUploadValidator
+from core.app.app_config.easy_ui_based_app.agent.manager import AgentConfigManager
-from core.app.validators.model_validator import ModelValidator
+from core.app.app_config.easy_ui_based_app.dataset.manager import DatasetConfigManager
-from core.app.validators.moderation import ModerationValidator
+from core.app.app_config.easy_ui_based_app.model_config.manager import ModelConfigManager
-from core.app.validators.opening_statement import OpeningStatementValidator
+from core.app.app_config.easy_ui_based_app.prompt_template.manager import PromptTemplateConfigManager
-from core.app.validators.prompt import PromptValidator
+from core.app.app_config.easy_ui_based_app.variables.manager import BasicVariablesConfigManager
-from core.app.validators.retriever_resource import RetrieverResourceValidator
+from core.app.app_config.common.sensitive_word_avoidance.manager import SensitiveWordAvoidanceConfigManager
-from core.app.validators.speech_to_text import SpeechToTextValidator
+from core.app.app_config.entities import EasyUIBasedAppConfig, EasyUIBasedAppModelConfigFrom, DatasetEntity
-from core.app.validators.suggested_questions import SuggestedQuestionsValidator
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
-from core.app.validators.text_to_speech import TextToSpeechValidator
+from core.app.app_config.features.opening_statement.manager import OpeningStatementConfigManager
-from core.app.validators.user_input_form import UserInputFormValidator
+from core.app.app_config.features.retrieval_resource.manager import RetrievalResourceConfigManager
+from core.app.app_config.features.speech_to_text.manager import SpeechToTextConfigManager
+from core.app.app_config.features.suggested_questions_after_answer.manager import \
+    SuggestedQuestionsAfterAnswerConfigManager
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
 from core.entities.agent_entities import PlanningStrategy
-from models.model import AppMode
+from models.model import AppMode, App, AppModelConfig
 
 OLD_TOOLS = ["dataset", "google_search", "web_reader", "wikipedia", "current_datetime"]
 
 
-class AgentChatAppConfigValidator:
+class AgentChatAppConfig(EasyUIBasedAppConfig):
+    """
+    Agent Chatbot App Config Entity.
+    """
+    agent: Optional[AgentEntity] = None
+
+
+class AgentChatAppConfigManager(BaseAppConfigManager):
+    @classmethod
+    def config_convert(cls, app_model: App,
+                       config_from: EasyUIBasedAppModelConfigFrom,
+                       app_model_config: AppModelConfig,
+                       config_dict: Optional[dict] = None) -> AgentChatAppConfig:
+        """
+        Convert app model config to agent chat app config
+        :param app_model: app model
+        :param config_from: app model config from
+        :param app_model_config: app model config
+        :param config_dict: app model config dict
+        :return:
+        """
+        config_dict = cls.convert_to_config_dict(config_from, app_model_config, config_dict)
+
+        app_config = AgentChatAppConfig(
+            tenant_id=app_model.tenant_id,
+            app_id=app_model.id,
+            app_mode=AppMode.value_of(app_model.mode),
+            app_model_config_from=config_from,
+            app_model_config_id=app_model_config.id,
+            app_model_config_dict=config_dict,
+            model=ModelConfigManager.convert(
+                config=config_dict
+            ),
+            prompt_template=PromptTemplateConfigManager.convert(
+                config=config_dict
+            ),
+            sensitive_word_avoidance=SensitiveWordAvoidanceConfigManager.convert(
+                config=config_dict
+            ),
+            dataset=DatasetConfigManager.convert(
+                config=config_dict
+            ),
+            agent=AgentConfigManager.convert(
+                config=config_dict
+            ),
+            additional_features=cls.convert_features(config_dict)
+        )
+
+        app_config.variables, app_config.external_data_variables = BasicVariablesConfigManager.convert(
+            config=config_dict
+        )
+
+        return app_config
+
     @classmethod
     def config_validate(cls, tenant_id: str, config: dict) -> dict:
         """
@@ -32,23 +90,19 @@ class AgentChatAppConfigValidator:
         related_config_keys = []
 
         # model
-        config, current_related_config_keys = ModelValidator.validate_and_set_defaults(tenant_id, config)
+        config, current_related_config_keys = ModelConfigManager.validate_and_set_defaults(tenant_id, config)
         related_config_keys.extend(current_related_config_keys)
 
         # user_input_form
-        config, current_related_config_keys = UserInputFormValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = BasicVariablesConfigManager.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # external data tools validation
-        config, current_related_config_keys = ExternalDataFetchValidator.validate_and_set_defaults(tenant_id, config)
         related_config_keys.extend(current_related_config_keys)
 
         # file upload validation
-        config, current_related_config_keys = FileUploadValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = FileUploadConfigManager.validate_and_set_defaults(config)
         related_config_keys.extend(current_related_config_keys)
 
         # prompt
-        config, current_related_config_keys = PromptValidator.validate_and_set_defaults(app_mode, config)
+        config, current_related_config_keys = PromptTemplateConfigManager.validate_and_set_defaults(app_mode, config)
         related_config_keys.extend(current_related_config_keys)
 
         # agent_mode
@@ -56,27 +110,29 @@ class AgentChatAppConfigValidator:
         related_config_keys.extend(current_related_config_keys)
 
         # opening_statement
-        config, current_related_config_keys = OpeningStatementValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = OpeningStatementConfigManager.validate_and_set_defaults(config)
         related_config_keys.extend(current_related_config_keys)
 
         # suggested_questions_after_answer
-        config, current_related_config_keys = SuggestedQuestionsValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = SuggestedQuestionsAfterAnswerConfigManager.validate_and_set_defaults(
+            config)
         related_config_keys.extend(current_related_config_keys)
 
         # speech_to_text
-        config, current_related_config_keys = SpeechToTextValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = SpeechToTextConfigManager.validate_and_set_defaults(config)
         related_config_keys.extend(current_related_config_keys)
 
         # text_to_speech
-        config, current_related_config_keys = TextToSpeechValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = TextToSpeechConfigManager.validate_and_set_defaults(config)
         related_config_keys.extend(current_related_config_keys)
 
         # return retriever resource
-        config, current_related_config_keys = RetrieverResourceValidator.validate_and_set_defaults(config)
+        config, current_related_config_keys = RetrievalResourceConfigManager.validate_and_set_defaults(config)
         related_config_keys.extend(current_related_config_keys)
 
         # moderation validation
-        config, current_related_config_keys = ModerationValidator.validate_and_set_defaults(tenant_id, config)
+        config, current_related_config_keys = SensitiveWordAvoidanceConfigManager.validate_and_set_defaults(tenant_id,
+                                                                                                            config)
         related_config_keys.extend(current_related_config_keys)
 
         related_config_keys = list(set(related_config_keys))
@@ -143,7 +199,7 @@ class AgentChatAppConfigValidator:
                     except ValueError:
                         raise ValueError("id in dataset must be of UUID type")
 
-                    if not DatasetValidator.is_dataset_exists(tenant_id, tool_item["id"]):
+                    if not DatasetConfigManager.is_dataset_exists(tenant_id, tool_item["id"]):
                         raise ValueError("Dataset ID does not exist, please check your permission.")
             else:
                 # latest style, use key-value pair

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

@@ -2,10 +2,12 @@ import logging
 from typing import cast
 
 from core.agent.cot_agent_runner import CotAgentRunner
+from core.agent.entities import AgentEntity
 from core.agent.fc_agent_runner import FunctionCallAgentRunner
 from core.app.app_queue_manager import AppQueueManager, PublishFrom
-from core.app.base_app_runner import AppRunner
+from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfig
-from core.entities.application_entities import AgentEntity, ApplicationGenerateEntity, ModelConfigEntity
+from core.app.apps.base_app_runner import AppRunner
+from core.app.entities.app_invoke_entities import EasyUIBasedAppGenerateEntity, EasyUIBasedModelConfigEntity
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMUsage
@@ -24,7 +26,7 @@ class AgentChatAppRunner(AppRunner):
     """
     Agent Application Runner
     """
-    def run(self, application_generate_entity: ApplicationGenerateEntity,
+    def run(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
             queue_manager: AppQueueManager,
             conversation: Conversation,
             message: Message) -> None:
@@ -36,12 +38,13 @@ class AgentChatAppRunner(AppRunner):
         :param message: message
         :return:
         """
-        app_record = db.session.query(App).filter(App.id == application_generate_entity.app_id).first()
+        app_config = application_generate_entity.app_config
+        app_config = cast(AgentChatAppConfig, app_config)
+
+        app_record = db.session.query(App).filter(App.id == app_config.app_id).first()
         if not app_record:
             raise ValueError("App not found")
 
-        app_orchestration_config = application_generate_entity.app_orchestration_config_entity
-
         inputs = application_generate_entity.inputs
         query = application_generate_entity.query
         files = application_generate_entity.files
@@ -53,8 +56,8 @@ class AgentChatAppRunner(AppRunner):
         # Not Include: memory, external data, dataset context
         self.get_pre_calculate_rest_tokens(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query
@@ -64,22 +67,22 @@ class AgentChatAppRunner(AppRunner):
         if application_generate_entity.conversation_id:
             # get memory of conversation (read-only)
             model_instance = ModelInstance(
-                provider_model_bundle=app_orchestration_config.model_config.provider_model_bundle,
+                provider_model_bundle=application_generate_entity.model_config.provider_model_bundle,
-                model=app_orchestration_config.model_config.model
+                model=application_generate_entity.model_config.model
             )
 
             memory = TokenBufferMemory(
                 conversation=conversation,
                 model_instance=model_instance
             )
-        
+
         # organize all inputs and template to prompt messages
         # Include: prompt template, inputs, query(optional), files(optional)
         #          memory(optional)
         prompt_messages, _ = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query,
@@ -91,15 +94,15 @@ class AgentChatAppRunner(AppRunner):
             # process sensitive_word_avoidance
             _, inputs, query = self.moderation_for_inputs(
                 app_id=app_record.id,
-                tenant_id=application_generate_entity.tenant_id,
+                tenant_id=app_config.tenant_id,
-                app_orchestration_config_entity=app_orchestration_config,
+                app_generate_entity=application_generate_entity,
                 inputs=inputs,
                 query=query,
             )
         except ModerationException as e:
             self.direct_output(
                 queue_manager=queue_manager,
-                app_orchestration_config=app_orchestration_config,
+                app_generate_entity=application_generate_entity,
                 prompt_messages=prompt_messages,
                 text=str(e),
                 stream=application_generate_entity.stream
@@ -123,7 +126,7 @@ class AgentChatAppRunner(AppRunner):
                 )
                 self.direct_output(
                     queue_manager=queue_manager,
-                    app_orchestration_config=app_orchestration_config,
+                    app_generate_entity=application_generate_entity,
                     prompt_messages=prompt_messages,
                     text=annotation_reply.content,
                     stream=application_generate_entity.stream
@@ -131,7 +134,7 @@ class AgentChatAppRunner(AppRunner):
                 return
 
         # fill in variable inputs from external data tools if exists
-        external_data_tools = app_orchestration_config.external_data_variables
+        external_data_tools = app_config.external_data_variables
         if external_data_tools:
             inputs = self.fill_in_inputs_from_external_data_tools(
                 tenant_id=app_record.tenant_id,
@@ -146,8 +149,8 @@ class AgentChatAppRunner(AppRunner):
         #          memory(optional), external data, dataset context(optional)
         prompt_messages, _ = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query,
@@ -164,25 +167,25 @@ class AgentChatAppRunner(AppRunner):
         if hosting_moderation_result:
             return
 
-        agent_entity = app_orchestration_config.agent
+        agent_entity = app_config.agent
 
         # load tool variables
         tool_conversation_variables = self._load_tool_variables(conversation_id=conversation.id,
                                                    user_id=application_generate_entity.user_id,
-                                                   tenant_id=application_generate_entity.tenant_id)
+                                                   tenant_id=app_config.tenant_id)
 
         # convert db variables to tool variables
         tool_variables = self._convert_db_variables_to_tool_variables(tool_conversation_variables)
 
         # init model instance
         model_instance = ModelInstance(
-            provider_model_bundle=app_orchestration_config.model_config.provider_model_bundle,
+            provider_model_bundle=application_generate_entity.model_config.provider_model_bundle,
-            model=app_orchestration_config.model_config.model
+            model=application_generate_entity.model_config.model
         )
         prompt_message, _ = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query,
@@ -203,10 +206,10 @@ class AgentChatAppRunner(AppRunner):
         # start agent runner
         if agent_entity.strategy == AgentEntity.Strategy.CHAIN_OF_THOUGHT:
             assistant_cot_runner = CotAgentRunner(
-                tenant_id=application_generate_entity.tenant_id,
+                tenant_id=app_config.tenant_id,
                 application_generate_entity=application_generate_entity,
-                app_orchestration_config=app_orchestration_config,
+                app_config=app_config,
-                model_config=app_orchestration_config.model_config,
+                model_config=application_generate_entity.model_config,
                 config=agent_entity,
                 queue_manager=queue_manager,
                 message=message,
@@ -225,10 +228,10 @@ class AgentChatAppRunner(AppRunner):
             )
         elif agent_entity.strategy == AgentEntity.Strategy.FUNCTION_CALLING:
             assistant_fc_runner = FunctionCallAgentRunner(
-                tenant_id=application_generate_entity.tenant_id,
+                tenant_id=app_config.tenant_id,
                 application_generate_entity=application_generate_entity,
-                app_orchestration_config=app_orchestration_config,
+                app_config=app_config,
-                model_config=app_orchestration_config.model_config,
+                model_config=application_generate_entity.model_config,
                 config=agent_entity,
                 queue_manager=queue_manager,
                 message=message,
@@ -289,7 +292,7 @@ class AgentChatAppRunner(AppRunner):
             'pool': db_variables.variables
         })
 
-    def _get_usage_of_all_agent_thoughts(self, model_config: ModelConfigEntity,
+    def _get_usage_of_all_agent_thoughts(self, model_config: EasyUIBasedModelConfigEntity,
                                          message: Message) -> LLMUsage:
         """
         Get usage of all agent thoughts

api/core/app/apps/base_app_runner.py

@@ -2,16 +2,13 @@ import time
 from collections.abc import Generator
 from typing import Optional, Union, cast
 
+from core.app.app_config.entities import PromptTemplateEntity, ExternalDataVariableEntity
 from core.app.app_queue_manager import AppQueueManager, PublishFrom
 from core.app.features.annotation_reply.annotation_reply import AnnotationReplyFeature
 from core.app.features.hosting_moderation.hosting_moderation import HostingModerationFeature
-from core.entities.application_entities import (
+from core.app.entities.app_invoke_entities import (
-    ApplicationGenerateEntity,
+    EasyUIBasedAppGenerateEntity,
-    AppOrchestrationConfigEntity,
+    InvokeFrom, EasyUIBasedModelConfigEntity,
-    ExternalDataVariableEntity,
-    InvokeFrom,
-    ModelConfigEntity,
-    PromptTemplateEntity,
 )
 from core.external_data_tool.external_data_fetch import ExternalDataFetch
 from core.file.file_obj import FileObj
@@ -29,7 +26,7 @@ from models.model import App, AppMode, Message, MessageAnnotation
 
 class AppRunner:
     def get_pre_calculate_rest_tokens(self, app_record: App,
-                                      model_config: ModelConfigEntity,
+                                      model_config: EasyUIBasedModelConfigEntity,
                                       prompt_template_entity: PromptTemplateEntity,
                                       inputs: dict[str, str],
                                       files: list[FileObj],
@@ -85,7 +82,7 @@ class AppRunner:
 
         return rest_tokens
 
-    def recalc_llm_max_tokens(self, model_config: ModelConfigEntity,
+    def recale_llm_max_tokens(self, model_config: EasyUIBasedModelConfigEntity,
                               prompt_messages: list[PromptMessage]):
         # recalc max_tokens if sum(prompt_token +  max_tokens) over model token limit
         model_type_instance = model_config.provider_model_bundle.model_type_instance
@@ -121,7 +118,7 @@ class AppRunner:
                     model_config.parameters[parameter_rule.name] = max_tokens
 
     def organize_prompt_messages(self, app_record: App,
-                                 model_config: ModelConfigEntity,
+                                 model_config: EasyUIBasedModelConfigEntity,
                                  prompt_template_entity: PromptTemplateEntity,
                                  inputs: dict[str, str],
                                  files: list[FileObj],
@@ -170,7 +167,7 @@ class AppRunner:
         return prompt_messages, stop
 
     def direct_output(self, queue_manager: AppQueueManager,
-                      app_orchestration_config: AppOrchestrationConfigEntity,
+                      app_generate_entity: EasyUIBasedAppGenerateEntity,
                       prompt_messages: list,
                       text: str,
                       stream: bool,
@@ -178,7 +175,7 @@ class AppRunner:
         """
         Direct output
         :param queue_manager: application queue manager
-        :param app_orchestration_config: app orchestration config
+        :param app_generate_entity: app generate entity
         :param prompt_messages: prompt messages
         :param text: text
         :param stream: stream
@@ -189,7 +186,7 @@ class AppRunner:
             index = 0
             for token in text:
                 queue_manager.publish_chunk_message(LLMResultChunk(
-                    model=app_orchestration_config.model_config.model,
+                    model=app_generate_entity.model_config.model,
                     prompt_messages=prompt_messages,
                     delta=LLMResultChunkDelta(
                         index=index,
@@ -201,7 +198,7 @@ class AppRunner:
 
         queue_manager.publish_message_end(
             llm_result=LLMResult(
-                model=app_orchestration_config.model_config.model,
+                model=app_generate_entity.model_config.model,
                 prompt_messages=prompt_messages,
                 message=AssistantPromptMessage(content=text),
                 usage=usage if usage else LLMUsage.empty_usage()
@@ -294,14 +291,14 @@ class AppRunner:
 
     def moderation_for_inputs(self, app_id: str,
                               tenant_id: str,
-                              app_orchestration_config_entity: AppOrchestrationConfigEntity,
+                              app_generate_entity: EasyUIBasedAppGenerateEntity,
                               inputs: dict,
                               query: str) -> tuple[bool, dict, str]:
         """
         Process sensitive_word_avoidance.
         :param app_id: app id
         :param tenant_id: tenant id
-        :param app_orchestration_config_entity: app orchestration config entity
+        :param app_generate_entity: app generate entity
         :param inputs: inputs
         :param query: query
         :return:
@@ -310,12 +307,12 @@ class AppRunner:
         return moderation_feature.check(
             app_id=app_id,
             tenant_id=tenant_id,
-            app_orchestration_config_entity=app_orchestration_config_entity,
+            app_config=app_generate_entity.app_config,
             inputs=inputs,
             query=query,
         )
     
-    def check_hosting_moderation(self, application_generate_entity: ApplicationGenerateEntity,
+    def check_hosting_moderation(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
                                  queue_manager: AppQueueManager,
                                  prompt_messages: list[PromptMessage]) -> bool:
         """
@@ -334,7 +331,7 @@ class AppRunner:
         if moderation_result:
             self.direct_output(
                 queue_manager=queue_manager,
-                app_orchestration_config=application_generate_entity.app_orchestration_config_entity,
+                app_generate_entity=application_generate_entity,
                 prompt_messages=prompt_messages,
                 text="I apologize for any confusion, " \
                      "but I'm an AI assistant to be helpful, harmless, and honest.",

api/core/app/apps/chat/app_config_manager.py

@@ -0,0 +1,135 @@
+from typing import Optional
+
+from core.app.app_config.base_app_config_manager import BaseAppConfigManager
+from core.app.app_config.easy_ui_based_app.dataset.manager import DatasetConfigManager
+from core.app.app_config.easy_ui_based_app.model_config.manager import ModelConfigManager
+from core.app.app_config.easy_ui_based_app.prompt_template.manager import PromptTemplateConfigManager
+from core.app.app_config.easy_ui_based_app.variables.manager import BasicVariablesConfigManager
+from core.app.app_config.common.sensitive_word_avoidance.manager import SensitiveWordAvoidanceConfigManager
+from core.app.app_config.entities import EasyUIBasedAppConfig, EasyUIBasedAppModelConfigFrom
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.app_config.features.opening_statement.manager import OpeningStatementConfigManager
+from core.app.app_config.features.retrieval_resource.manager import RetrievalResourceConfigManager
+from core.app.app_config.features.speech_to_text.manager import SpeechToTextConfigManager
+from core.app.app_config.features.suggested_questions_after_answer.manager import \
+    SuggestedQuestionsAfterAnswerConfigManager
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
+from models.model import AppMode, App, AppModelConfig
+
+
+class ChatAppConfig(EasyUIBasedAppConfig):
+    """
+    Chatbot App Config Entity.
+    """
+    pass
+
+
+class ChatAppConfigManager(BaseAppConfigManager):
+    @classmethod
+    def config_convert(cls, app_model: App,
+                       config_from: EasyUIBasedAppModelConfigFrom,
+                       app_model_config: AppModelConfig,
+                       config_dict: Optional[dict] = None) -> ChatAppConfig:
+        """
+        Convert app model config to chat app config
+        :param app_model: app model
+        :param config_from: app model config from
+        :param app_model_config: app model config
+        :param config_dict: app model config dict
+        :return:
+        """
+        config_dict = cls.convert_to_config_dict(config_from, app_model_config, config_dict)
+
+        app_config = ChatAppConfig(
+            tenant_id=app_model.tenant_id,
+            app_id=app_model.id,
+            app_mode=AppMode.value_of(app_model.mode),
+            app_model_config_from=config_from,
+            app_model_config_id=app_model_config.id,
+            app_model_config_dict=config_dict,
+            model=ModelConfigManager.convert(
+                config=config_dict
+            ),
+            prompt_template=PromptTemplateConfigManager.convert(
+                config=config_dict
+            ),
+            sensitive_word_avoidance=SensitiveWordAvoidanceConfigManager.convert(
+                config=config_dict
+            ),
+            dataset=DatasetConfigManager.convert(
+                config=config_dict
+            ),
+            additional_features=cls.convert_features(config_dict)
+        )
+
+        app_config.variables, app_config.external_data_variables = BasicVariablesConfigManager.convert(
+            config=config_dict
+        )
+
+        return app_config
+
+    @classmethod
+    def config_validate(cls, tenant_id: str, config: dict) -> dict:
+        """
+        Validate for chat app model config
+
+        :param tenant_id: tenant id
+        :param config: app model config args
+        """
+        app_mode = AppMode.CHAT
+
+        related_config_keys = []
+
+        # model
+        config, current_related_config_keys = ModelConfigManager.validate_and_set_defaults(tenant_id, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # user_input_form
+        config, current_related_config_keys = BasicVariablesConfigManager.validate_and_set_defaults(tenant_id, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # file upload validation
+        config, current_related_config_keys = FileUploadConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # prompt
+        config, current_related_config_keys = PromptTemplateConfigManager.validate_and_set_defaults(app_mode, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # dataset_query_variable
+        config, current_related_config_keys = DatasetConfigManager.validate_and_set_defaults(tenant_id, app_mode,
+                                                                                             config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # opening_statement
+        config, current_related_config_keys = OpeningStatementConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # suggested_questions_after_answer
+        config, current_related_config_keys = SuggestedQuestionsAfterAnswerConfigManager.validate_and_set_defaults(
+            config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # speech_to_text
+        config, current_related_config_keys = SpeechToTextConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # text_to_speech
+        config, current_related_config_keys = TextToSpeechConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # return retriever resource
+        config, current_related_config_keys = RetrievalResourceConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # moderation validation
+        config, current_related_config_keys = SensitiveWordAvoidanceConfigManager.validate_and_set_defaults(tenant_id,
+                                                                                                            config)
+        related_config_keys.extend(current_related_config_keys)
+
+        related_config_keys = list(set(related_config_keys))
+
+        # Filter out extra parameters
+        filtered_config = {key: config.get(key) for key in related_config_keys}
+
+        return filtered_config

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

@@ -1,10 +1,12 @@
 import logging
+from typing import cast
 
 from core.app.app_queue_manager import AppQueueManager, PublishFrom
-from core.app.base_app_runner import AppRunner
+from core.app.apps.chat.app_config_manager import ChatAppConfig
+from core.app.apps.base_app_runner import AppRunner
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.entities.application_entities import (
+from core.app.entities.app_invoke_entities import (
-    ApplicationGenerateEntity,
+    EasyUIBasedAppGenerateEntity,
 )
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
@@ -21,7 +23,7 @@ class ChatAppRunner(AppRunner):
     Chat Application Runner
     """
 
-    def run(self, application_generate_entity: ApplicationGenerateEntity,
+    def run(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
             queue_manager: AppQueueManager,
             conversation: Conversation,
             message: Message) -> None:
@@ -33,12 +35,13 @@ class ChatAppRunner(AppRunner):
         :param message: message
         :return:
         """
-        app_record = db.session.query(App).filter(App.id == application_generate_entity.app_id).first()
+        app_config = application_generate_entity.app_config
+        app_config = cast(ChatAppConfig, app_config)
+
+        app_record = db.session.query(App).filter(App.id == app_config.app_id).first()
         if not app_record:
             raise ValueError("App not found")
 
-        app_orchestration_config = application_generate_entity.app_orchestration_config_entity
-
         inputs = application_generate_entity.inputs
         query = application_generate_entity.query
         files = application_generate_entity.files
@@ -50,8 +53,8 @@ class ChatAppRunner(AppRunner):
         # Not Include: memory, external data, dataset context
         self.get_pre_calculate_rest_tokens(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query
@@ -61,8 +64,8 @@ class ChatAppRunner(AppRunner):
         if application_generate_entity.conversation_id:
             # get memory of conversation (read-only)
             model_instance = ModelInstance(
-                provider_model_bundle=app_orchestration_config.model_config.provider_model_bundle,
+                provider_model_bundle=application_generate_entity.model_config.provider_model_bundle,
-                model=app_orchestration_config.model_config.model
+                model=application_generate_entity.model_config.model
             )
 
             memory = TokenBufferMemory(
@@ -75,8 +78,8 @@ class ChatAppRunner(AppRunner):
         #          memory(optional)
         prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query,
@@ -88,15 +91,15 @@ class ChatAppRunner(AppRunner):
             # process sensitive_word_avoidance
             _, inputs, query = self.moderation_for_inputs(
                 app_id=app_record.id,
-                tenant_id=application_generate_entity.tenant_id,
+                tenant_id=app_config.tenant_id,
-                app_orchestration_config_entity=app_orchestration_config,
+                app_generate_entity=application_generate_entity,
                 inputs=inputs,
                 query=query,
             )
         except ModerationException as e:
             self.direct_output(
                 queue_manager=queue_manager,
-                app_orchestration_config=app_orchestration_config,
+                app_generate_entity=application_generate_entity,
                 prompt_messages=prompt_messages,
                 text=str(e),
                 stream=application_generate_entity.stream
@@ -120,7 +123,7 @@ class ChatAppRunner(AppRunner):
                 )
                 self.direct_output(
                     queue_manager=queue_manager,
-                    app_orchestration_config=app_orchestration_config,
+                    app_generate_entity=application_generate_entity,
                     prompt_messages=prompt_messages,
                     text=annotation_reply.content,
                     stream=application_generate_entity.stream
@@ -128,7 +131,7 @@ class ChatAppRunner(AppRunner):
                 return
 
         # fill in variable inputs from external data tools if exists
-        external_data_tools = app_orchestration_config.external_data_variables
+        external_data_tools = app_config.external_data_variables
         if external_data_tools:
             inputs = self.fill_in_inputs_from_external_data_tools(
                 tenant_id=app_record.tenant_id,
@@ -140,7 +143,7 @@ class ChatAppRunner(AppRunner):
 
         # get context from datasets
         context = None
-        if app_orchestration_config.dataset and app_orchestration_config.dataset.dataset_ids:
+        if app_config.dataset and app_config.dataset.dataset_ids:
             hit_callback = DatasetIndexToolCallbackHandler(
                 queue_manager,
                 app_record.id,
@@ -152,11 +155,11 @@ class ChatAppRunner(AppRunner):
             dataset_retrieval = DatasetRetrieval()
             context = dataset_retrieval.retrieve(
                 tenant_id=app_record.tenant_id,
-                model_config=app_orchestration_config.model_config,
+                model_config=application_generate_entity.model_config,
-                config=app_orchestration_config.dataset,
+                config=app_config.dataset,
                 query=query,
                 invoke_from=application_generate_entity.invoke_from,
-                show_retrieve_source=app_orchestration_config.show_retrieve_source,
+                show_retrieve_source=app_config.additional_features.show_retrieve_source,
                 hit_callback=hit_callback,
                 memory=memory
             )
@@ -166,8 +169,8 @@ class ChatAppRunner(AppRunner):
         #          memory(optional), external data, dataset context(optional)
         prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query,
@@ -186,22 +189,22 @@ class ChatAppRunner(AppRunner):
             return
 
         # Re-calculate the max tokens if sum(prompt_token +  max_tokens) over model token limit
-        self.recalc_llm_max_tokens(
+        self.recale_llm_max_tokens(
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
             prompt_messages=prompt_messages
         )
 
         # Invoke model
         model_instance = ModelInstance(
-            provider_model_bundle=app_orchestration_config.model_config.provider_model_bundle,
+            provider_model_bundle=application_generate_entity.model_config.provider_model_bundle,
-            model=app_orchestration_config.model_config.model
+            model=application_generate_entity.model_config.model
         )
 
         db.session.close()
 
         invoke_result = model_instance.invoke_llm(
             prompt_messages=prompt_messages,
-            model_parameters=app_orchestration_config.model_config.parameters,
+            model_parameters=application_generate_entity.model_config.parameters,
             stop=stop,
             stream=application_generate_entity.stream,
             user=application_generate_entity.user_id,

api/core/app/apps/completion/app_config_manager.py

@@ -0,0 +1,118 @@
+from typing import Optional
+
+from core.app.app_config.base_app_config_manager import BaseAppConfigManager
+from core.app.app_config.easy_ui_based_app.dataset.manager import DatasetConfigManager
+from core.app.app_config.easy_ui_based_app.model_config.manager import ModelConfigManager
+from core.app.app_config.easy_ui_based_app.prompt_template.manager import PromptTemplateConfigManager
+from core.app.app_config.easy_ui_based_app.variables.manager import BasicVariablesConfigManager
+from core.app.app_config.common.sensitive_word_avoidance.manager import SensitiveWordAvoidanceConfigManager
+from core.app.app_config.entities import EasyUIBasedAppConfig, EasyUIBasedAppModelConfigFrom
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.app_config.features.more_like_this.manager import MoreLikeThisConfigManager
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
+from models.model import AppMode, App, AppModelConfig
+
+
+class CompletionAppConfig(EasyUIBasedAppConfig):
+    """
+    Completion App Config Entity.
+    """
+    pass
+
+
+class CompletionAppConfigManager(BaseAppConfigManager):
+    @classmethod
+    def config_convert(cls, app_model: App,
+                       config_from: EasyUIBasedAppModelConfigFrom,
+                       app_model_config: AppModelConfig,
+                       config_dict: Optional[dict] = None) -> CompletionAppConfig:
+        """
+        Convert app model config to completion app config
+        :param app_model: app model
+        :param config_from: app model config from
+        :param app_model_config: app model config
+        :param config_dict: app model config dict
+        :return:
+        """
+        config_dict = cls.convert_to_config_dict(config_from, app_model_config, config_dict)
+
+        app_config = CompletionAppConfig(
+            tenant_id=app_model.tenant_id,
+            app_id=app_model.id,
+            app_mode=AppMode.value_of(app_model.mode),
+            app_model_config_from=config_from,
+            app_model_config_id=app_model_config.id,
+            app_model_config_dict=config_dict,
+            model=ModelConfigManager.convert(
+                config=config_dict
+            ),
+            prompt_template=PromptTemplateConfigManager.convert(
+                config=config_dict
+            ),
+            sensitive_word_avoidance=SensitiveWordAvoidanceConfigManager.convert(
+                config=config_dict
+            ),
+            dataset=DatasetConfigManager.convert(
+                config=config_dict
+            ),
+            additional_features=cls.convert_features(config_dict)
+        )
+
+        app_config.variables, app_config.external_data_variables = BasicVariablesConfigManager.convert(
+            config=config_dict
+        )
+
+        return app_config
+
+    @classmethod
+    def config_validate(cls, tenant_id: str, config: dict) -> dict:
+        """
+        Validate for completion app model config
+
+        :param tenant_id: tenant id
+        :param config: app model config args
+        """
+        app_mode = AppMode.COMPLETION
+
+        related_config_keys = []
+
+        # model
+        config, current_related_config_keys = ModelConfigManager.validate_and_set_defaults(tenant_id, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # user_input_form
+        config, current_related_config_keys = BasicVariablesConfigManager.validate_and_set_defaults(tenant_id, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # file upload validation
+        config, current_related_config_keys = FileUploadConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # prompt
+        config, current_related_config_keys = PromptTemplateConfigManager.validate_and_set_defaults(app_mode, config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # dataset_query_variable
+        config, current_related_config_keys = DatasetConfigManager.validate_and_set_defaults(tenant_id, app_mode,
+                                                                                             config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # text_to_speech
+        config, current_related_config_keys = TextToSpeechConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # more_like_this
+        config, current_related_config_keys = MoreLikeThisConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # moderation validation
+        config, current_related_config_keys = SensitiveWordAvoidanceConfigManager.validate_and_set_defaults(tenant_id,
+                                                                                                            config)
+        related_config_keys.extend(current_related_config_keys)
+
+        related_config_keys = list(set(related_config_keys))
+
+        # Filter out extra parameters
+        filtered_config = {key: config.get(key) for key in related_config_keys}
+
+        return filtered_config

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

@@ -1,10 +1,12 @@
 import logging
+from typing import cast
 
 from core.app.app_queue_manager import AppQueueManager
-from core.app.base_app_runner import AppRunner
+from core.app.apps.completion.app_config_manager import CompletionAppConfig
+from core.app.apps.base_app_runner import AppRunner
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.entities.application_entities import (
+from core.app.entities.app_invoke_entities import (
-    ApplicationGenerateEntity,
+    EasyUIBasedAppGenerateEntity,
 )
 from core.model_manager import ModelInstance
 from core.moderation.base import ModerationException
@@ -20,7 +22,7 @@ class CompletionAppRunner(AppRunner):
     Completion Application Runner
     """
 
-    def run(self, application_generate_entity: ApplicationGenerateEntity,
+    def run(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
             queue_manager: AppQueueManager,
             message: Message) -> None:
         """
@@ -30,12 +32,13 @@ class CompletionAppRunner(AppRunner):
         :param message: message
         :return:
         """
-        app_record = db.session.query(App).filter(App.id == application_generate_entity.app_id).first()
+        app_config = application_generate_entity.app_config
+        app_config = cast(CompletionAppConfig, app_config)
+
+        app_record = db.session.query(App).filter(App.id == app_config.app_id).first()
         if not app_record:
             raise ValueError("App not found")
 
-        app_orchestration_config = application_generate_entity.app_orchestration_config_entity
-
         inputs = application_generate_entity.inputs
         query = application_generate_entity.query
         files = application_generate_entity.files
@@ -47,8 +50,8 @@ class CompletionAppRunner(AppRunner):
         # Not Include: memory, external data, dataset context
         self.get_pre_calculate_rest_tokens(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query
@@ -58,8 +61,8 @@ class CompletionAppRunner(AppRunner):
         # Include: prompt template, inputs, query(optional), files(optional)
         prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query
@@ -70,15 +73,15 @@ class CompletionAppRunner(AppRunner):
             # process sensitive_word_avoidance
             _, inputs, query = self.moderation_for_inputs(
                 app_id=app_record.id,
-                tenant_id=application_generate_entity.tenant_id,
+                tenant_id=app_config.tenant_id,
-                app_orchestration_config_entity=app_orchestration_config,
+                app_generate_entity=application_generate_entity,
                 inputs=inputs,
                 query=query,
             )
         except ModerationException as e:
             self.direct_output(
                 queue_manager=queue_manager,
-                app_orchestration_config=app_orchestration_config,
+                app_generate_entity=application_generate_entity,
                 prompt_messages=prompt_messages,
                 text=str(e),
                 stream=application_generate_entity.stream
@@ -86,7 +89,7 @@ class CompletionAppRunner(AppRunner):
             return
 
         # fill in variable inputs from external data tools if exists
-        external_data_tools = app_orchestration_config.external_data_variables
+        external_data_tools = app_config.external_data_variables
         if external_data_tools:
             inputs = self.fill_in_inputs_from_external_data_tools(
                 tenant_id=app_record.tenant_id,
@@ -98,7 +101,7 @@ class CompletionAppRunner(AppRunner):
 
         # get context from datasets
         context = None
-        if app_orchestration_config.dataset and app_orchestration_config.dataset.dataset_ids:
+        if app_config.dataset and app_config.dataset.dataset_ids:
             hit_callback = DatasetIndexToolCallbackHandler(
                 queue_manager,
                 app_record.id,
@@ -107,18 +110,18 @@ class CompletionAppRunner(AppRunner):
                 application_generate_entity.invoke_from
             )
 
-            dataset_config = app_orchestration_config.dataset
+            dataset_config = app_config.dataset
             if dataset_config and dataset_config.retrieve_config.query_variable:
                 query = inputs.get(dataset_config.retrieve_config.query_variable, "")
 
             dataset_retrieval = DatasetRetrieval()
             context = dataset_retrieval.retrieve(
                 tenant_id=app_record.tenant_id,
-                model_config=app_orchestration_config.model_config,
+                model_config=application_generate_entity.model_config,
                 config=dataset_config,
                 query=query,
                 invoke_from=application_generate_entity.invoke_from,
-                show_retrieve_source=app_orchestration_config.show_retrieve_source,
+                show_retrieve_source=app_config.additional_features.show_retrieve_source,
                 hit_callback=hit_callback
             )
 
@@ -127,8 +130,8 @@ class CompletionAppRunner(AppRunner):
         #          memory(optional), external data, dataset context(optional)
         prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
-            prompt_template_entity=app_orchestration_config.prompt_template,
+            prompt_template_entity=app_config.prompt_template,
             inputs=inputs,
             files=files,
             query=query,
@@ -147,19 +150,19 @@ class CompletionAppRunner(AppRunner):
 
         # Re-calculate the max tokens if sum(prompt_token +  max_tokens) over model token limit
         self.recale_llm_max_tokens(
-            model_config=app_orchestration_config.model_config,
+            model_config=application_generate_entity.model_config,
             prompt_messages=prompt_messages
         )
 
         # Invoke model
         model_instance = ModelInstance(
-            provider_model_bundle=app_orchestration_config.model_config.provider_model_bundle,
+            provider_model_bundle=application_generate_entity.model_config.provider_model_bundle,
-            model=app_orchestration_config.model_config.model
+            model=application_generate_entity.model_config.model
         )
 
         invoke_result = model_instance.invoke_llm(
             prompt_messages=prompt_messages,
-            model_parameters=app_orchestration_config.model_config.parameters,
+            model_parameters=application_generate_entity.model_config.parameters,
             stop=stop,
             stream=application_generate_entity.stream,
             user=application_generate_entity.user_id,

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

@@ -0,0 +1,71 @@
+from core.app.app_config.base_app_config_manager import BaseAppConfigManager
+from core.app.app_config.common.sensitive_word_avoidance.manager import SensitiveWordAvoidanceConfigManager
+from core.app.app_config.entities import WorkflowUIBasedAppConfig
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
+from core.app.app_config.features.text_to_speech.manager import TextToSpeechConfigManager
+from core.app.app_config.workflow_ui_based_app.variables.manager import WorkflowVariablesConfigManager
+from models.model import AppMode, App
+from models.workflow import Workflow
+
+
+class WorkflowAppConfig(WorkflowUIBasedAppConfig):
+    """
+    Workflow App Config Entity.
+    """
+    pass
+
+
+class WorkflowAppConfigManager(BaseAppConfigManager):
+    @classmethod
+    def config_convert(cls, app_model: App, workflow: Workflow) -> WorkflowAppConfig:
+        features_dict = workflow.features_dict
+
+        app_config = WorkflowAppConfig(
+            tenant_id=app_model.tenant_id,
+            app_id=app_model.id,
+            app_mode=AppMode.value_of(app_model.mode),
+            workflow_id=workflow.id,
+            sensitive_word_avoidance=SensitiveWordAvoidanceConfigManager.convert(
+                config=features_dict
+            ),
+            variables=WorkflowVariablesConfigManager.convert(
+                workflow=workflow
+            ),
+            additional_features=cls.convert_features(features_dict)
+        )
+
+        return app_config
+
+    @classmethod
+    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False) -> dict:
+        """
+        Validate for workflow app model config
+
+        :param tenant_id: tenant id
+        :param config: app model config args
+        :param only_structure_validate: only validate the structure of the config
+        """
+        related_config_keys = []
+
+        # file upload validation
+        config, current_related_config_keys = FileUploadConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # text_to_speech
+        config, current_related_config_keys = TextToSpeechConfigManager.validate_and_set_defaults(config)
+        related_config_keys.extend(current_related_config_keys)
+
+        # moderation validation
+        config, current_related_config_keys = SensitiveWordAvoidanceConfigManager.validate_and_set_defaults(
+            tenant_id=tenant_id,
+            config=config,
+            only_structure_validate=only_structure_validate
+        )
+        related_config_keys.extend(current_related_config_keys)
+
+        related_config_keys = list(set(related_config_keys))
+
+        # Filter out extra parameters
+        filtered_config = {key: config.get(key) for key in related_config_keys}
+
+        return filtered_config

api/core/app/chat/config_validator.py

@@ -1,82 +0,0 @@
-from core.app.validators.dataset_retrieval import DatasetValidator
-from core.app.validators.external_data_fetch import ExternalDataFetchValidator
-from core.app.validators.file_upload import FileUploadValidator
-from core.app.validators.model_validator import ModelValidator
-from core.app.validators.moderation import ModerationValidator
-from core.app.validators.opening_statement import OpeningStatementValidator
-from core.app.validators.prompt import PromptValidator
-from core.app.validators.retriever_resource import RetrieverResourceValidator
-from core.app.validators.speech_to_text import SpeechToTextValidator
-from core.app.validators.suggested_questions import SuggestedQuestionsValidator
-from core.app.validators.text_to_speech import TextToSpeechValidator
-from core.app.validators.user_input_form import UserInputFormValidator
-from models.model import AppMode
-
-
-class ChatAppConfigValidator:
-    @classmethod
-    def config_validate(cls, tenant_id: str, config: dict) -> dict:
-        """
-        Validate for chat app model config
-
-        :param tenant_id: tenant id
-        :param config: app model config args
-        """
-        app_mode = AppMode.CHAT
-
-        related_config_keys = []
-
-        # model
-        config, current_related_config_keys = ModelValidator.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # user_input_form
-        config, current_related_config_keys = UserInputFormValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # external data tools validation
-        config, current_related_config_keys = ExternalDataFetchValidator.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # file upload validation
-        config, current_related_config_keys = FileUploadValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # prompt
-        config, current_related_config_keys = PromptValidator.validate_and_set_defaults(app_mode, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # dataset_query_variable
-        config, current_related_config_keys = DatasetValidator.validate_and_set_defaults(tenant_id, app_mode, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # opening_statement
-        config, current_related_config_keys = OpeningStatementValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # suggested_questions_after_answer
-        config, current_related_config_keys = SuggestedQuestionsValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # speech_to_text
-        config, current_related_config_keys = SpeechToTextValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # text_to_speech
-        config, current_related_config_keys = TextToSpeechValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # return retriever resource
-        config, current_related_config_keys = RetrieverResourceValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # moderation validation
-        config, current_related_config_keys = ModerationValidator.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        related_config_keys = list(set(related_config_keys))
-
-        # Filter out extra parameters
-        filtered_config = {key: config.get(key) for key in related_config_keys}
-
-        return filtered_config

api/core/app/completion/config_validator.py

@@ -1,67 +0,0 @@
-from core.app.validators.dataset_retrieval import DatasetValidator
-from core.app.validators.external_data_fetch import ExternalDataFetchValidator
-from core.app.validators.file_upload import FileUploadValidator
-from core.app.validators.model_validator import ModelValidator
-from core.app.validators.moderation import ModerationValidator
-from core.app.validators.more_like_this import MoreLikeThisValidator
-from core.app.validators.prompt import PromptValidator
-from core.app.validators.text_to_speech import TextToSpeechValidator
-from core.app.validators.user_input_form import UserInputFormValidator
-from models.model import AppMode
-
-
-class CompletionAppConfigValidator:
-    @classmethod
-    def config_validate(cls, tenant_id: str, config: dict) -> dict:
-        """
-        Validate for completion app model config
-
-        :param tenant_id: tenant id
-        :param config: app model config args
-        """
-        app_mode = AppMode.COMPLETION
-
-        related_config_keys = []
-
-        # model
-        config, current_related_config_keys = ModelValidator.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # user_input_form
-        config, current_related_config_keys = UserInputFormValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # external data tools validation
-        config, current_related_config_keys = ExternalDataFetchValidator.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # file upload validation
-        config, current_related_config_keys = FileUploadValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # prompt
-        config, current_related_config_keys = PromptValidator.validate_and_set_defaults(app_mode, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # dataset_query_variable
-        config, current_related_config_keys = DatasetValidator.validate_and_set_defaults(tenant_id, app_mode, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # text_to_speech
-        config, current_related_config_keys = TextToSpeechValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # more_like_this
-        config, current_related_config_keys = MoreLikeThisValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # moderation validation
-        config, current_related_config_keys = ModerationValidator.validate_and_set_defaults(tenant_id, config)
-        related_config_keys.extend(current_related_config_keys)
-
-        related_config_keys = list(set(related_config_keys))
-
-        # Filter out extra parameters
-        filtered_config = {key: config.get(key) for key in related_config_keys}
-
-        return filtered_config

api/core/app/entities/app_invoke_entities.py

@@ -0,0 +1,111 @@
+from enum import Enum
+from typing import Any, Optional
+
+from pydantic import BaseModel
+
+from core.app.app_config.entities import EasyUIBasedAppConfig, WorkflowUIBasedAppConfig
+from core.entities.provider_configuration import ProviderModelBundle
+from core.file.file_obj import FileObj
+from core.model_runtime.entities.model_entities import AIModelEntity
+
+
+class InvokeFrom(Enum):
+    """
+    Invoke From.
+    """
+    SERVICE_API = 'service-api'
+    WEB_APP = 'web-app'
+    EXPLORE = 'explore'
+    DEBUGGER = 'debugger'
+
+    @classmethod
+    def value_of(cls, value: str) -> 'InvokeFrom':
+        """
+        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 invoke from value {value}')
+
+    def to_source(self) -> str:
+        """
+        Get source of invoke from.
+
+        :return: source
+        """
+        if self == InvokeFrom.WEB_APP:
+            return 'web_app'
+        elif self == InvokeFrom.DEBUGGER:
+            return 'dev'
+        elif self == InvokeFrom.EXPLORE:
+            return 'explore_app'
+        elif self == InvokeFrom.SERVICE_API:
+            return 'api'
+
+        return 'dev'
+
+
+class EasyUIBasedModelConfigEntity(BaseModel):
+    """
+    Model Config Entity.
+    """
+    provider: str
+    model: str
+    model_schema: AIModelEntity
+    mode: str
+    provider_model_bundle: ProviderModelBundle
+    credentials: dict[str, Any] = {}
+    parameters: dict[str, Any] = {}
+    stop: list[str] = []
+
+
+class EasyUIBasedAppGenerateEntity(BaseModel):
+    """
+    EasyUI Based Application Generate Entity.
+    """
+    task_id: str
+
+    # app config
+    app_config: EasyUIBasedAppConfig
+    model_config: EasyUIBasedModelConfigEntity
+
+    conversation_id: Optional[str] = None
+    inputs: dict[str, str]
+    query: Optional[str] = None
+    files: list[FileObj] = []
+    user_id: str
+    # extras
+    stream: bool
+    invoke_from: InvokeFrom
+
+    # extra parameters, like: auto_generate_conversation_name
+    extras: dict[str, Any] = {}
+
+
+class WorkflowUIBasedAppGenerateEntity(BaseModel):
+    """
+    Workflow UI Based Application Generate Entity.
+    """
+    task_id: str
+
+    # app config
+    app_config: WorkflowUIBasedAppConfig
+
+    inputs: dict[str, str]
+    files: list[FileObj] = []
+    user_id: str
+    # extras
+    stream: bool
+    invoke_from: InvokeFrom
+
+    # extra parameters
+    extras: dict[str, Any] = {}
+
+
+class AdvancedChatAppGenerateEntity(WorkflowUIBasedAppGenerateEntity):
+    conversation_id: Optional[str] = None
+    query: str

api/core/app/features/annotation_reply/annotation_reply.py

@@ -1,7 +1,7 @@
 import logging
 from typing import Optional
 
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.rag.datasource.vdb.vector_factory import Vector
 from extensions.ext_database import db
 from models.dataset import Dataset

api/core/app/features/hosting_moderation/hosting_moderation.py

@@ -1,6 +1,6 @@
 import logging
 
-from core.entities.application_entities import ApplicationGenerateEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedAppGenerateEntity
 from core.helper import moderation
 from core.model_runtime.entities.message_entities import PromptMessage
 
@@ -8,7 +8,7 @@ logger = logging.getLogger(__name__)
 
 
 class HostingModerationFeature:
-    def check(self, application_generate_entity: ApplicationGenerateEntity,
+    def check(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
               prompt_messages: list[PromptMessage]) -> bool:
         """
         Check hosting moderation
@@ -16,8 +16,7 @@ class HostingModerationFeature:
         :param prompt_messages: prompt messages
         :return:
         """
-        app_orchestration_config = application_generate_entity.app_orchestration_config_entity
+        model_config = application_generate_entity.model_config
-        model_config = app_orchestration_config.model_config
 
         text = ""
         for prompt_message in prompt_messages:

api/core/app/generate_task_pipeline.py

@@ -7,8 +7,8 @@ from typing import Optional, Union, cast
 from pydantic import BaseModel
 
 from core.app.app_queue_manager import AppQueueManager, PublishFrom
-from core.entities.application_entities import ApplicationGenerateEntity, InvokeFrom
+from core.app.entities.app_invoke_entities import EasyUIBasedAppGenerateEntity, InvokeFrom
-from core.entities.queue_entities import (
+from core.app.entities.queue_entities import (
     AnnotationReplyEvent,
     QueueAgentMessageEvent,
     QueueAgentThoughtEvent,
@@ -58,7 +58,7 @@ class GenerateTaskPipeline:
     GenerateTaskPipeline is a class that generate stream output and state management for Application.
     """
 
-    def __init__(self, application_generate_entity: ApplicationGenerateEntity,
+    def __init__(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
                  queue_manager: AppQueueManager,
                  conversation: Conversation,
                  message: Message) -> None:
@@ -75,7 +75,7 @@ class GenerateTaskPipeline:
         self._message = message
         self._task_state = TaskState(
             llm_result=LLMResult(
-                model=self._application_generate_entity.app_orchestration_config_entity.model_config.model,
+                model=self._application_generate_entity.model_config.model,
                 prompt_messages=[],
                 message=AssistantPromptMessage(content=""),
                 usage=LLMUsage.empty_usage()
@@ -127,7 +127,7 @@ class GenerateTaskPipeline:
                 if isinstance(event, QueueMessageEndEvent):
                     self._task_state.llm_result = event.llm_result
                 else:
-                    model_config = self._application_generate_entity.app_orchestration_config_entity.model_config
+                    model_config = self._application_generate_entity.model_config
                     model = model_config.model
                     model_type_instance = model_config.provider_model_bundle.model_type_instance
                     model_type_instance = cast(LargeLanguageModel, model_type_instance)
@@ -210,7 +210,7 @@ class GenerateTaskPipeline:
                 if isinstance(event, QueueMessageEndEvent):
                     self._task_state.llm_result = event.llm_result
                 else:
-                    model_config = self._application_generate_entity.app_orchestration_config_entity.model_config
+                    model_config = self._application_generate_entity.model_config
                     model = model_config.model
                     model_type_instance = model_config.provider_model_bundle.model_type_instance
                     model_type_instance = cast(LargeLanguageModel, model_type_instance)
@@ -569,7 +569,7 @@ class GenerateTaskPipeline:
         :return:
         """
         prompts = []
-        if self._application_generate_entity.app_orchestration_config_entity.model_config.mode == 'chat':
+        if self._application_generate_entity.model_config.mode == 'chat':
             for prompt_message in prompt_messages:
                 if prompt_message.role == PromptMessageRole.USER:
                     role = 'user'
@@ -638,13 +638,13 @@ class GenerateTaskPipeline:
         Init output moderation.
         :return:
         """
-        app_orchestration_config_entity = self._application_generate_entity.app_orchestration_config_entity
+        app_config = self._application_generate_entity.app_config
-        sensitive_word_avoidance = app_orchestration_config_entity.sensitive_word_avoidance
+        sensitive_word_avoidance = app_config.sensitive_word_avoidance
 
         if sensitive_word_avoidance:
             return OutputModeration(
-                tenant_id=self._application_generate_entity.tenant_id,
+                tenant_id=app_config.tenant_id,
-                app_id=self._application_generate_entity.app_id,
+                app_id=app_config.app_id,
                 rule=ModerationRule(
                     type=sensitive_word_avoidance.type,
                     config=sensitive_word_avoidance.config

api/core/app/validators/external_data_fetch.py

@@ -1,39 +0,0 @@
-
-from core.external_data_tool.factory import ExternalDataToolFactory
-
-
-class ExternalDataFetchValidator:
-    @classmethod
-    def validate_and_set_defaults(cls, tenant_id: str, config: dict) -> tuple[dict, list[str]]:
-        """
-        Validate and set defaults for external data fetch feature
-
-        :param tenant_id: workspace id
-        :param config: app model config args
-        """
-        if not config.get("external_data_tools"):
-            config["external_data_tools"] = []
-
-        if not isinstance(config["external_data_tools"], list):
-            raise ValueError("external_data_tools must be of list type")
-
-        for tool in config["external_data_tools"]:
-            if "enabled" not in tool or not tool["enabled"]:
-                tool["enabled"] = False
-
-            if not tool["enabled"]:
-                continue
-
-            if "type" not in tool or not tool["type"]:
-                raise ValueError("external_data_tools[].type is required")
-
-            typ = tool["type"]
-            config = tool["config"]
-
-            ExternalDataToolFactory.validate_config(
-                name=typ,
-                tenant_id=tenant_id,
-                config=config
-            )
-
-        return config, ["external_data_tools"]

api/core/app/validators/user_input_form.py

@@ -1,61 +0,0 @@
-import re
-
-
-class UserInputFormValidator:
-    @classmethod
-    def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
-        """
-        Validate and set defaults for user input form
-
-        :param config: app model config args
-        """
-        if not config.get("user_input_form"):
-            config["user_input_form"] = []
-
-        if not isinstance(config["user_input_form"], list):
-            raise ValueError("user_input_form must be a list of objects")
-
-        variables = []
-        for item in config["user_input_form"]:
-            key = list(item.keys())[0]
-            if key not in ["text-input", "select", "paragraph", "number", "external_data_tool"]:
-                raise ValueError("Keys in user_input_form list can only be 'text-input', 'paragraph'  or 'select'")
-
-            form_item = item[key]
-            if 'label' not in form_item:
-                raise ValueError("label is required in user_input_form")
-
-            if not isinstance(form_item["label"], str):
-                raise ValueError("label in user_input_form must be of string type")
-
-            if 'variable' not in form_item:
-                raise ValueError("variable is required in user_input_form")
-
-            if not isinstance(form_item["variable"], str):
-                raise ValueError("variable in user_input_form must be of string type")
-
-            pattern = re.compile(r"^(?!\d)[\u4e00-\u9fa5A-Za-z0-9_\U0001F300-\U0001F64F\U0001F680-\U0001F6FF]{1,100}$")
-            if pattern.match(form_item["variable"]) is None:
-                raise ValueError("variable in user_input_form must be a string, "
-                                 "and cannot start with a number")
-
-            variables.append(form_item["variable"])
-
-            if 'required' not in form_item or not form_item["required"]:
-                form_item["required"] = False
-
-            if not isinstance(form_item["required"], bool):
-                raise ValueError("required in user_input_form must be of boolean type")
-
-            if key == "select":
-                if 'options' not in form_item or not form_item["options"]:
-                    form_item["options"] = []
-
-                if not isinstance(form_item["options"], list):
-                    raise ValueError("options in user_input_form must be a list of strings")
-
-                if "default" in form_item and form_item['default'] \
-                        and form_item["default"] not in form_item["options"]:
-                    raise ValueError("default value in user_input_form must be in the options list")
-
-        return config, ["user_input_form"]

api/core/app/workflow/config_validator.py

@@ -1,39 +0,0 @@
-from core.app.validators.file_upload import FileUploadValidator
-from core.app.validators.moderation import ModerationValidator
-from core.app.validators.text_to_speech import TextToSpeechValidator
-
-
-class WorkflowAppConfigValidator:
-    @classmethod
-    def config_validate(cls, tenant_id: str, config: dict, only_structure_validate: bool = False) -> dict:
-        """
-        Validate for workflow app model config
-
-        :param tenant_id: tenant id
-        :param config: app model config args
-        :param only_structure_validate: only validate the structure of the config
-        """
-        related_config_keys = []
-
-        # file upload validation
-        config, current_related_config_keys = FileUploadValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # text_to_speech
-        config, current_related_config_keys = TextToSpeechValidator.validate_and_set_defaults(config)
-        related_config_keys.extend(current_related_config_keys)
-
-        # moderation validation
-        config, current_related_config_keys = ModerationValidator.validate_and_set_defaults(
-            tenant_id=tenant_id,
-            config=config,
-            only_structure_validate=only_structure_validate
-        )
-        related_config_keys.extend(current_related_config_keys)
-
-        related_config_keys = list(set(related_config_keys))
-
-        # Filter out extra parameters
-        filtered_config = {key: config.get(key) for key in related_config_keys}
-
-        return filtered_config

api/core/callback_handler/agent_loop_gather_callback_handler.py

@@ -1,262 +0,0 @@
-import json
-import logging
-import time
-from typing import Any, Optional, Union, cast
-
-from langchain.agents import openai_functions_agent, openai_functions_multi_agent
-from langchain.callbacks.base import BaseCallbackHandler
-from langchain.schema import AgentAction, AgentFinish, BaseMessage, LLMResult
-
-from core.app.app_queue_manager import AppQueueManager, PublishFrom
-from core.callback_handler.entity.agent_loop import AgentLoop
-from core.entities.application_entities import ModelConfigEntity
-from core.model_runtime.entities.llm_entities import LLMResult as RuntimeLLMResult
-from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, UserPromptMessage
-from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
-from extensions.ext_database import db
-from models.model import Message, MessageAgentThought, MessageChain
-
-
-class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
-    """Callback Handler that prints to std out."""
-    raise_error: bool = True
-
-    def __init__(self, model_config: ModelConfigEntity,
-                 queue_manager: AppQueueManager,
-                 message: Message,
-                 message_chain: MessageChain) -> None:
-        """Initialize callback handler."""
-        self.model_config = model_config
-        self.queue_manager = queue_manager
-        self.message = message
-        self.message_chain = message_chain
-        model_type_instance = self.model_config.provider_model_bundle.model_type_instance
-        self.model_type_instance = cast(LargeLanguageModel, model_type_instance)
-        self._agent_loops = []
-        self._current_loop = None
-        self._message_agent_thought = None
-
-    @property
-    def agent_loops(self) -> list[AgentLoop]:
-        return self._agent_loops
-
-    def clear_agent_loops(self) -> None:
-        self._agent_loops = []
-        self._current_loop = None
-        self._message_agent_thought = None
-
-    @property
-    def always_verbose(self) -> bool:
-        """Whether to call verbose callbacks even if verbose is False."""
-        return True
-
-    @property
-    def ignore_chain(self) -> bool:
-        """Whether to ignore chain callbacks."""
-        return True
-
-    def on_llm_before_invoke(self, prompt_messages: list[PromptMessage]) -> None:
-        if not self._current_loop:
-            # Agent start with a LLM query
-            self._current_loop = AgentLoop(
-                position=len(self._agent_loops) + 1,
-                prompt="\n".join([prompt_message.content for prompt_message in prompt_messages]),
-                status='llm_started',
-                started_at=time.perf_counter()
-            )
-
-    def on_llm_after_invoke(self, result: RuntimeLLMResult) -> None:
-        if self._current_loop and self._current_loop.status == 'llm_started':
-            self._current_loop.status = 'llm_end'
-            if result.usage:
-                self._current_loop.prompt_tokens = result.usage.prompt_tokens
-            else:
-                self._current_loop.prompt_tokens = self.model_type_instance.get_num_tokens(
-                    model=self.model_config.model,
-                    credentials=self.model_config.credentials,
-                    prompt_messages=[UserPromptMessage(content=self._current_loop.prompt)]
-                )
-
-            completion_message = result.message
-            if completion_message.tool_calls:
-                self._current_loop.completion \
-                    = json.dumps({'function_call': completion_message.tool_calls})
-            else:
-                self._current_loop.completion = completion_message.content
-
-            if result.usage:
-                self._current_loop.completion_tokens = result.usage.completion_tokens
-            else:
-                self._current_loop.completion_tokens = self.model_type_instance.get_num_tokens(
-                    model=self.model_config.model,
-                    credentials=self.model_config.credentials,
-                    prompt_messages=[AssistantPromptMessage(content=self._current_loop.completion)]
-                )
-
-    def on_chat_model_start(
-            self,
-            serialized: dict[str, Any],
-            messages: list[list[BaseMessage]],
-            **kwargs: Any
-    ) -> Any:
-        pass
-
-    def on_llm_start(
-        self, serialized: dict[str, Any], prompts: list[str], **kwargs: Any
-    ) -> None:
-        pass
-
-    def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
-        """Do nothing."""
-        pass
-
-    def on_llm_error(
-        self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
-    ) -> None:
-        logging.debug("Agent on_llm_error: %s", error)
-        self._agent_loops = []
-        self._current_loop = None
-        self._message_agent_thought = None
-
-    def on_tool_start(
-        self,
-        serialized: dict[str, Any],
-        input_str: str,
-        **kwargs: Any,
-    ) -> None:
-        """Do nothing."""
-        # kwargs={'color': 'green', 'llm_prefix': 'Thought:', 'observation_prefix': 'Observation: '}
-        # input_str='action-input'
-        # serialized={'description': 'A search engine. Useful for when you need to answer questions about current events. Input should be a search query.', 'name': 'Search'}
-        pass
-
-    def on_agent_action(
-        self, action: AgentAction, color: Optional[str] = None, **kwargs: Any
-    ) -> Any:
-        """Run on agent action."""
-        tool = action.tool
-        tool_input = json.dumps({"query": action.tool_input}
-                                if isinstance(action.tool_input, str) else action.tool_input)
-        completion = None
-        if isinstance(action, openai_functions_agent.base._FunctionsAgentAction) \
-                or isinstance(action, openai_functions_multi_agent.base._FunctionsAgentAction):
-            thought = action.log.strip()
-            completion = json.dumps({'function_call': action.message_log[0].additional_kwargs['function_call']})
-        else:
-            action_name_position = action.log.index("Action:") if action.log else -1
-            thought = action.log[:action_name_position].strip() if action.log else ''
-
-        if self._current_loop and self._current_loop.status == 'llm_end':
-            self._current_loop.status = 'agent_action'
-            self._current_loop.thought = thought
-            self._current_loop.tool_name = tool
-            self._current_loop.tool_input = tool_input
-            if completion is not None:
-                self._current_loop.completion = completion
-
-            self._message_agent_thought = self._init_agent_thought()
-
-    def on_tool_end(
-        self,
-        output: str,
-        color: Optional[str] = None,
-        observation_prefix: Optional[str] = None,
-        llm_prefix: Optional[str] = None,
-        **kwargs: Any,
-    ) -> None:
-        """If not the final action, print out observation."""
-        # kwargs={'name': 'Search'}
-        # llm_prefix='Thought:'
-        # observation_prefix='Observation: '
-        # output='53 years'
-
-        if self._current_loop and self._current_loop.status == 'agent_action' and output and output != 'None':
-            self._current_loop.status = 'tool_end'
-            self._current_loop.tool_output = output
-            self._current_loop.completed = True
-            self._current_loop.completed_at = time.perf_counter()
-            self._current_loop.latency = self._current_loop.completed_at - self._current_loop.started_at
-
-            self._complete_agent_thought(self._message_agent_thought)
-
-            self._agent_loops.append(self._current_loop)
-            self._current_loop = None
-            self._message_agent_thought = None
-
-    def on_tool_error(
-        self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
-    ) -> None:
-        """Do nothing."""
-        logging.debug("Agent on_tool_error: %s", error)
-        self._agent_loops = []
-        self._current_loop = None
-        self._message_agent_thought = None
-
-    def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any:
-        """Run on agent end."""
-        # Final Answer
-        if self._current_loop and (self._current_loop.status == 'llm_end' or self._current_loop.status == 'agent_action'):
-            self._current_loop.status = 'agent_finish'
-            self._current_loop.completed = True
-            self._current_loop.completed_at = time.perf_counter()
-            self._current_loop.latency = self._current_loop.completed_at - self._current_loop.started_at
-            self._current_loop.thought = '[DONE]'
-            self._message_agent_thought = self._init_agent_thought()
-
-            self._complete_agent_thought(self._message_agent_thought)
-
-            self._agent_loops.append(self._current_loop)
-            self._current_loop = None
-            self._message_agent_thought = None
-        elif not self._current_loop and self._agent_loops:
-            self._agent_loops[-1].status = 'agent_finish'
-
-    def _init_agent_thought(self) -> MessageAgentThought:
-        message_agent_thought = MessageAgentThought(
-            message_id=self.message.id,
-            message_chain_id=self.message_chain.id,
-            position=self._current_loop.position,
-            thought=self._current_loop.thought,
-            tool=self._current_loop.tool_name,
-            tool_input=self._current_loop.tool_input,
-            message=self._current_loop.prompt,
-            message_price_unit=0,
-            answer=self._current_loop.completion,
-            answer_price_unit=0,
-            created_by_role=('account' if self.message.from_source == 'console' else 'end_user'),
-            created_by=(self.message.from_account_id
-                        if self.message.from_source == 'console' else self.message.from_end_user_id)
-        )
-
-        db.session.add(message_agent_thought)
-        db.session.commit()
-
-        self.queue_manager.publish_agent_thought(message_agent_thought, PublishFrom.APPLICATION_MANAGER)
-
-        return message_agent_thought
-
-    def _complete_agent_thought(self, message_agent_thought: MessageAgentThought) -> None:
-        loop_message_tokens = self._current_loop.prompt_tokens
-        loop_answer_tokens = self._current_loop.completion_tokens
-
-        # transform usage
-        llm_usage = self.model_type_instance._calc_response_usage(
-            self.model_config.model,
-            self.model_config.credentials,
-            loop_message_tokens,
-            loop_answer_tokens
-        )
-
-        message_agent_thought.observation = self._current_loop.tool_output
-        message_agent_thought.tool_process_data = ''  # currently not support
-        message_agent_thought.message_token = loop_message_tokens
-        message_agent_thought.message_unit_price = llm_usage.prompt_unit_price
-        message_agent_thought.message_price_unit = llm_usage.prompt_price_unit
-        message_agent_thought.answer_token = loop_answer_tokens
-        message_agent_thought.answer_unit_price = llm_usage.completion_unit_price
-        message_agent_thought.answer_price_unit = llm_usage.completion_price_unit
-        message_agent_thought.latency = self._current_loop.latency
-        message_agent_thought.tokens = self._current_loop.prompt_tokens + self._current_loop.completion_tokens
-        message_agent_thought.total_price = llm_usage.total_price
-        message_agent_thought.currency = llm_usage.currency
-        db.session.commit()

api/core/callback_handler/entity/agent_loop.py

@@ -1,23 +0,0 @@
-from pydantic import BaseModel
-
-
-class AgentLoop(BaseModel):
-    position: int = 1
-
-    thought: str = None
-    tool_name: str = None
-    tool_input: str = None
-    tool_output: str = None
-
-    prompt: str = None
-    prompt_tokens: int = 0
-    completion: str = None
-    completion_tokens: int = 0
-
-    latency: float = None
-
-    status: str = 'llm_started'
-    completed: bool = False
-
-    started_at: float = None
-    completed_at: float = None

api/core/callback_handler/index_tool_callback_handler.py

@@ -1,6 +1,6 @@
 
 from core.app.app_queue_manager import AppQueueManager, PublishFrom
-from core.entities.application_entities import InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.rag.models.document import Document
 from extensions.ext_database import db
 from models.dataset import DatasetQuery, DocumentSegment

api/core/external_data_tool/external_data_fetch.py

@@ -5,7 +5,7 @@ from typing import Optional
 
 from flask import Flask, current_app
 
-from core.entities.application_entities import ExternalDataVariableEntity
+from core.app.app_config.entities import ExternalDataVariableEntity
 from core.external_data_tool.factory import ExternalDataToolFactory
 
 logger = logging.getLogger(__name__)

api/core/file/file_obj.py

@@ -3,6 +3,7 @@ from typing import Optional
 
 from pydantic import BaseModel
 
+from core.app.app_config.entities import FileUploadEntity
 from core.file.upload_file_parser import UploadFileParser
 from core.model_runtime.entities.message_entities import ImagePromptMessageContent
 from extensions.ext_database import db
@@ -50,7 +51,7 @@ class FileObj(BaseModel):
     transfer_method: FileTransferMethod
     url: Optional[str]
     upload_file_id: Optional[str]
-    file_config: dict
+    file_upload_entity: FileUploadEntity
 
     @property
     def data(self) -> Optional[str]:
@@ -63,7 +64,7 @@ class FileObj(BaseModel):
     @property
     def prompt_message_content(self) -> ImagePromptMessageContent:
         if self.type == FileType.IMAGE:
-            image_config = self.file_config.get('image')
+            image_config = self.file_upload_entity.image_config
 
             return ImagePromptMessageContent(
                 data=self.data,

api/core/file/message_file_parser.py

@@ -1,11 +1,12 @@
-from typing import Optional, Union
+from typing import Union
 
 import requests
 
+from core.app.app_config.entities import FileUploadEntity
 from core.file.file_obj import FileBelongsTo, FileObj, FileTransferMethod, FileType
 from extensions.ext_database import db
 from models.account import Account
-from models.model import AppModelConfig, EndUser, MessageFile, UploadFile
+from models.model import EndUser, MessageFile, UploadFile
 from services.file_service import IMAGE_EXTENSIONS
 
 
@@ -15,18 +16,16 @@ class MessageFileParser:
         self.tenant_id = tenant_id
         self.app_id = app_id
 
-    def validate_and_transform_files_arg(self, files: list[dict], app_model_config: AppModelConfig,
+    def validate_and_transform_files_arg(self, files: list[dict], file_upload_entity: FileUploadEntity,
                                          user: Union[Account, EndUser]) -> list[FileObj]:
         """
         validate and transform files arg
 
         :param files:
-        :param app_model_config:
+        :param file_upload_entity:
         :param user:
         :return:
         """
-        file_upload_config = app_model_config.file_upload_dict
-
         for file in files:
             if not isinstance(file, dict):
                 raise ValueError('Invalid file format, must be dict')
@@ -45,17 +44,17 @@ class MessageFileParser:
                 raise ValueError('Missing file upload_file_id')
 
         # transform files to file objs
-        type_file_objs = self._to_file_objs(files, file_upload_config)
+        type_file_objs = self._to_file_objs(files, file_upload_entity)
 
         # validate files
         new_files = []
         for file_type, file_objs in type_file_objs.items():
             if file_type == FileType.IMAGE:
                 # parse and validate files
-                image_config = file_upload_config.get('image')
+                image_config = file_upload_entity.image_config
 
                 # check if image file feature is enabled
-                if not image_config['enabled']:
+                if not image_config:
                     continue
 
                 # Validate number of files
@@ -96,27 +95,27 @@ class MessageFileParser:
         # return all file objs
         return new_files
 
-    def transform_message_files(self, files: list[MessageFile], file_upload_config: Optional[dict]) -> list[FileObj]:
+    def transform_message_files(self, files: list[MessageFile], file_upload_entity: FileUploadEntity) -> list[FileObj]:
         """
         transform message files
 
         :param files:
-        :param file_upload_config:
+        :param file_upload_entity:
         :return:
         """
         # transform files to file objs
-        type_file_objs = self._to_file_objs(files, file_upload_config)
+        type_file_objs = self._to_file_objs(files, file_upload_entity)
 
         # return all file objs
         return [file_obj for file_objs in type_file_objs.values() for file_obj in file_objs]
 
     def _to_file_objs(self, files: list[Union[dict, MessageFile]],
-                      file_upload_config: dict) -> dict[FileType, list[FileObj]]:
+                      file_upload_entity: FileUploadEntity) -> dict[FileType, list[FileObj]]:
         """
         transform files to file objs
 
         :param files:
-        :param file_upload_config:
+        :param file_upload_entity:
         :return:
         """
         type_file_objs: dict[FileType, list[FileObj]] = {
@@ -133,7 +132,7 @@ class MessageFileParser:
                 if file.belongs_to == FileBelongsTo.ASSISTANT.value:
                     continue
 
-            file_obj = self._to_file_obj(file, file_upload_config)
+            file_obj = self._to_file_obj(file, file_upload_entity)
             if file_obj.type not in type_file_objs:
                 continue
 
@@ -141,7 +140,7 @@ class MessageFileParser:
 
         return type_file_objs
 
-    def _to_file_obj(self, file: Union[dict, MessageFile], file_upload_config: dict) -> FileObj:
+    def _to_file_obj(self, file: Union[dict, MessageFile], file_upload_entity: FileUploadEntity) -> FileObj:
         """
         transform file to file obj
 
@@ -156,7 +155,7 @@ class MessageFileParser:
                 transfer_method=transfer_method,
                 url=file.get('url') if transfer_method == FileTransferMethod.REMOTE_URL else None,
                 upload_file_id=file.get('upload_file_id') if transfer_method == FileTransferMethod.LOCAL_FILE else None,
-                file_config=file_upload_config
+                file_upload_entity=file_upload_entity
             )
         else:
             return FileObj(
@@ -166,7 +165,7 @@ class MessageFileParser:
                 transfer_method=FileTransferMethod.value_of(file.transfer_method),
                 url=file.url,
                 upload_file_id=file.upload_file_id or None,
-                file_config=file_upload_config
+                file_upload_entity=file_upload_entity
             )
 
     def _check_image_remote_url(self, url):

api/core/helper/moderation.py

@@ -1,7 +1,7 @@
 import logging
 import random
 
-from core.entities.application_entities import ModelConfigEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
 from core.model_runtime.errors.invoke import InvokeBadRequestError
 from core.model_runtime.model_providers.openai.moderation.moderation import OpenAIModerationModel
 from extensions.ext_hosting_provider import hosting_configuration
@@ -10,7 +10,7 @@ from models.provider import ProviderType
 logger = logging.getLogger(__name__)
 
 
-def check_moderation(model_config: ModelConfigEntity, text: str) -> bool:
+def check_moderation(model_config: EasyUIBasedModelConfigEntity, text: str) -> bool:
     moderation_config = hosting_configuration.moderation_config
     if (moderation_config and moderation_config.enabled is True
             and 'openai' in hosting_configuration.provider_map

api/core/memory/token_buffer_memory.py

@@ -1,3 +1,5 @@
+from core.app.app_config.entities import FileUploadEntity
+from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.file.message_file_parser import MessageFileParser
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.message_entities import (
@@ -43,12 +45,18 @@ class TokenBufferMemory:
         for message in messages:
             files = message.message_files
             if files:
-                file_objs = message_file_parser.transform_message_files(
+                if self.conversation.mode not in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]:
-                    files,
+                    file_upload_entity = FileUploadConfigManager.convert(message.app_model_config.to_dict())
-                    message.app_model_config.file_upload_dict
+                else:
-                    if self.conversation.mode not in [AppMode.ADVANCED_CHAT.value, AppMode.WORKFLOW.value]
+                    file_upload_entity = FileUploadConfigManager.convert(message.workflow_run.workflow.features_dict)
-                    else message.workflow_run.workflow.features_dict.get('file_upload', {})
+
-                )
+                if file_upload_entity:
+                    file_objs = message_file_parser.transform_message_files(
+                        files,
+                        file_upload_entity
+                    )
+                else:
+                    file_objs = []
 
                 if not file_objs:
                     prompt_messages.append(UserPromptMessage(content=message.query))

api/core/moderation/input_moderation.py

@@ -1,6 +1,6 @@
 import logging
 
-from core.entities.application_entities import AppOrchestrationConfigEntity
+from core.app.app_config.entities import AppConfig
 from core.moderation.base import ModerationAction, ModerationException
 from core.moderation.factory import ModerationFactory
 
@@ -10,22 +10,22 @@ logger = logging.getLogger(__name__)
 class InputModeration:
     def check(self, app_id: str,
               tenant_id: str,
-              app_orchestration_config_entity: AppOrchestrationConfigEntity,
+              app_config: AppConfig,
               inputs: dict,
               query: str) -> tuple[bool, dict, str]:
         """
         Process sensitive_word_avoidance.
         :param app_id: app id
         :param tenant_id: tenant id
-        :param app_orchestration_config_entity: app orchestration config entity
+        :param app_config: app config
         :param inputs: inputs
         :param query: query
         :return:
         """
-        if not app_orchestration_config_entity.sensitive_word_avoidance:
+        if not app_config.sensitive_word_avoidance:
             return False, inputs, query
 
-        sensitive_word_avoidance_config = app_orchestration_config_entity.sensitive_word_avoidance
+        sensitive_word_avoidance_config = app_config.sensitive_word_avoidance
         moderation_type = sensitive_word_avoidance_config.type
 
         moderation_factory = ModerationFactory(

api/core/prompt/advanced_prompt_transform.py

@@ -1,10 +1,7 @@
 from typing import Optional
 
-from core.entities.application_entities import (
+from core.app.app_config.entities import PromptTemplateEntity, AdvancedCompletionPromptTemplateEntity
-    AdvancedCompletionPromptTemplateEntity,
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
-    ModelConfigEntity,
-    PromptTemplateEntity,
-)
 from core.file.file_obj import FileObj
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.message_entities import (
@@ -31,7 +28,7 @@ class AdvancedPromptTransform(PromptTransform):
                    files: list[FileObj],
                    context: Optional[str],
                    memory: Optional[TokenBufferMemory],
-                   model_config: ModelConfigEntity) -> list[PromptMessage]:
+                   model_config: EasyUIBasedModelConfigEntity) -> list[PromptMessage]:
         prompt_messages = []
 
         model_mode = ModelMode.value_of(model_config.mode)
@@ -65,7 +62,7 @@ class AdvancedPromptTransform(PromptTransform):
                                               files: list[FileObj],
                                               context: Optional[str],
                                               memory: Optional[TokenBufferMemory],
-                                              model_config: ModelConfigEntity) -> list[PromptMessage]:
+                                              model_config: EasyUIBasedModelConfigEntity) -> list[PromptMessage]:
         """
         Get completion model prompt messages.
         """
@@ -113,7 +110,7 @@ class AdvancedPromptTransform(PromptTransform):
                                         files: list[FileObj],
                                         context: Optional[str],
                                         memory: Optional[TokenBufferMemory],
-                                        model_config: ModelConfigEntity) -> list[PromptMessage]:
+                                        model_config: EasyUIBasedModelConfigEntity) -> list[PromptMessage]:
         """
         Get chat model prompt messages.
         """
@@ -202,7 +199,7 @@ class AdvancedPromptTransform(PromptTransform):
                                 role_prefix: AdvancedCompletionPromptTemplateEntity.RolePrefixEntity,
                                 prompt_template: PromptTemplateParser,
                                 prompt_inputs: dict,
-                                model_config: ModelConfigEntity) -> dict:
+                                model_config: EasyUIBasedModelConfigEntity) -> dict:
         if '#histories#' in prompt_template.variable_keys:
             if memory:
                 inputs = {'#histories#': '', **prompt_inputs}

api/core/prompt/prompt_transform.py

@@ -1,6 +1,6 @@
 from typing import Optional, cast
 
-from core.entities.application_entities import ModelConfigEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.message_entities import PromptMessage
 from core.model_runtime.entities.model_entities import ModelPropertyKey
@@ -10,14 +10,14 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
 class PromptTransform:
     def _append_chat_histories(self, memory: TokenBufferMemory,
                                prompt_messages: list[PromptMessage],
-                               model_config: ModelConfigEntity) -> list[PromptMessage]:
+                               model_config: EasyUIBasedModelConfigEntity) -> list[PromptMessage]:
         rest_tokens = self._calculate_rest_token(prompt_messages, model_config)
         histories = self._get_history_messages_list_from_memory(memory, rest_tokens)
         prompt_messages.extend(histories)
 
         return prompt_messages
 
-    def _calculate_rest_token(self, prompt_messages: list[PromptMessage], model_config: ModelConfigEntity) -> int:
+    def _calculate_rest_token(self, prompt_messages: list[PromptMessage], model_config: EasyUIBasedModelConfigEntity) -> int:
         rest_tokens = 2000
 
         model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)

api/core/prompt/simple_prompt_transform.py

@@ -3,10 +3,8 @@ import json
 import os
 from typing import Optional
 
-from core.entities.application_entities import (
+from core.app.app_config.entities import PromptTemplateEntity
-    ModelConfigEntity,
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
-    PromptTemplateEntity,
-)
 from core.file.file_obj import FileObj
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.message_entities import (
@@ -54,7 +52,7 @@ class SimplePromptTransform(PromptTransform):
                    files: list[FileObj],
                    context: Optional[str],
                    memory: Optional[TokenBufferMemory],
-                   model_config: ModelConfigEntity) -> \
+                   model_config: EasyUIBasedModelConfigEntity) -> \
             tuple[list[PromptMessage], Optional[list[str]]]:
         model_mode = ModelMode.value_of(model_config.mode)
         if model_mode == ModelMode.CHAT:
@@ -83,7 +81,7 @@ class SimplePromptTransform(PromptTransform):
         return prompt_messages, stops
 
     def get_prompt_str_and_rules(self, app_mode: AppMode,
-                                 model_config: ModelConfigEntity,
+                                 model_config: EasyUIBasedModelConfigEntity,
                                  pre_prompt: str,
                                  inputs: dict,
                                  query: Optional[str] = None,
@@ -164,7 +162,7 @@ class SimplePromptTransform(PromptTransform):
                                         context: Optional[str],
                                         files: list[FileObj],
                                         memory: Optional[TokenBufferMemory],
-                                        model_config: ModelConfigEntity) \
+                                        model_config: EasyUIBasedModelConfigEntity) \
             -> tuple[list[PromptMessage], Optional[list[str]]]:
         prompt_messages = []
 
@@ -202,7 +200,7 @@ class SimplePromptTransform(PromptTransform):
                                               context: Optional[str],
                                               files: list[FileObj],
                                               memory: Optional[TokenBufferMemory],
-                                              model_config: ModelConfigEntity) \
+                                              model_config: EasyUIBasedModelConfigEntity) \
             -> tuple[list[PromptMessage], Optional[list[str]]]:
         # get prompt
         prompt, prompt_rules = self.get_prompt_str_and_rules(

api/core/rag/retrieval/agent/agent_llm_callback.py

@@ -1,101 +0,0 @@
-import logging
-from typing import Optional
-
-from core.callback_handler.agent_loop_gather_callback_handler import AgentLoopGatherCallbackHandler
-from core.model_runtime.callbacks.base_callback import Callback
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
-from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
-from core.model_runtime.model_providers.__base.ai_model import AIModel
-
-logger = logging.getLogger(__name__)
-
-
-class AgentLLMCallback(Callback):
-
-    def __init__(self, agent_callback: AgentLoopGatherCallbackHandler) -> None:
-        self.agent_callback = agent_callback
-
-    def on_before_invoke(self, llm_instance: AIModel, model: str, credentials: dict,
-                         prompt_messages: list[PromptMessage], model_parameters: dict,
-                         tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-                         stream: bool = True, user: Optional[str] = None) -> None:
-        """
-        Before invoke callback
-
-        :param llm_instance: LLM instance
-        :param model: model name
-        :param credentials: model credentials
-        :param prompt_messages: prompt messages
-        :param model_parameters: model parameters
-        :param tools: tools for tool calling
-        :param stop: stop words
-        :param stream: is stream response
-        :param user: unique user id
-        """
-        self.agent_callback.on_llm_before_invoke(
-            prompt_messages=prompt_messages
-        )
-
-    def on_new_chunk(self, llm_instance: AIModel, chunk: LLMResultChunk, model: str, credentials: dict,
-                     prompt_messages: list[PromptMessage], model_parameters: dict,
-                     tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-                     stream: bool = True, user: Optional[str] = None):
-        """
-        On new chunk callback
-
-        :param llm_instance: LLM instance
-        :param chunk: chunk
-        :param model: model name
-        :param credentials: model credentials
-        :param prompt_messages: prompt messages
-        :param model_parameters: model parameters
-        :param tools: tools for tool calling
-        :param stop: stop words
-        :param stream: is stream response
-        :param user: unique user id
-        """
-        pass
-
-    def on_after_invoke(self, llm_instance: AIModel, result: LLMResult, model: str, credentials: dict,
-                        prompt_messages: list[PromptMessage], model_parameters: dict,
-                        tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-                        stream: bool = True, user: Optional[str] = None) -> None:
-        """
-        After invoke callback
-
-        :param llm_instance: LLM instance
-        :param result: result
-        :param model: model name
-        :param credentials: model credentials
-        :param prompt_messages: prompt messages
-        :param model_parameters: model parameters
-        :param tools: tools for tool calling
-        :param stop: stop words
-        :param stream: is stream response
-        :param user: unique user id
-        """
-        self.agent_callback.on_llm_after_invoke(
-            result=result
-        )
-
-    def on_invoke_error(self, llm_instance: AIModel, ex: Exception, model: str, credentials: dict,
-                        prompt_messages: list[PromptMessage], model_parameters: dict,
-                        tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
-                        stream: bool = True, user: Optional[str] = None) -> None:
-        """
-        Invoke error callback
-
-        :param llm_instance: LLM instance
-        :param ex: exception
-        :param model: model name
-        :param credentials: model credentials
-        :param prompt_messages: prompt messages
-        :param model_parameters: model parameters
-        :param tools: tools for tool calling
-        :param stop: stop words
-        :param stream: is stream response
-        :param user: unique user id
-        """
-        self.agent_callback.on_llm_error(
-            error=ex
-        )

api/core/rag/retrieval/agent/llm_chain.py

@@ -5,19 +5,17 @@ from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.schema import Generation, LLMResult
 from langchain.schema.language_model import BaseLanguageModel
 
-from core.entities.application_entities import ModelConfigEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
 from core.entities.message_entities import lc_messages_to_prompt_messages
 from core.model_manager import ModelInstance
-from core.rag.retrieval.agent.agent_llm_callback import AgentLLMCallback
 from core.rag.retrieval.agent.fake_llm import FakeLLM
 
 
 class LLMChain(LCLLMChain):
-    model_config: ModelConfigEntity
+    model_config: EasyUIBasedModelConfigEntity
     """The language model instance to use."""
     llm: BaseLanguageModel = FakeLLM(response="")
     parameters: dict[str, Any] = {}
-    agent_llm_callback: Optional[AgentLLMCallback] = None
 
     def generate(
         self,
@@ -38,7 +36,6 @@ class LLMChain(LCLLMChain):
             prompt_messages=prompt_messages,
             stream=False,
             stop=stop,
-            callbacks=[self.agent_llm_callback] if self.agent_llm_callback else None,
             model_parameters=self.parameters
         )
 

api/core/rag/retrieval/agent/multi_dataset_router_agent.py

@@ -10,7 +10,7 @@ from langchain.schema import AgentAction, AgentFinish, AIMessage, SystemMessage
 from langchain.tools import BaseTool
 from pydantic import root_validator
 
-from core.entities.application_entities import ModelConfigEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
 from core.entities.message_entities import lc_messages_to_prompt_messages
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.message_entities import PromptMessageTool
@@ -21,7 +21,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
     """
     An Multi Dataset Retrieve Agent driven by Router.
     """
-    model_config: ModelConfigEntity
+    model_config: EasyUIBasedModelConfigEntity
 
     class Config:
         """Configuration for this pydantic object."""
@@ -156,7 +156,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
     @classmethod
     def from_llm_and_tools(
             cls,
-            model_config: ModelConfigEntity,
+            model_config: EasyUIBasedModelConfigEntity,
             tools: Sequence[BaseTool],
             callback_manager: Optional[BaseCallbackManager] = None,
             extra_prompt_messages: Optional[list[BaseMessagePromptTemplate]] = None,

api/core/rag/retrieval/agent/structed_multi_dataset_router_agent.py

@@ -12,7 +12,7 @@ from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate, Sy
 from langchain.schema import AgentAction, AgentFinish, OutputParserException
 from langchain.tools import BaseTool
 
-from core.entities.application_entities import ModelConfigEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
 from core.rag.retrieval.agent.llm_chain import LLMChain
 
 FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
@@ -206,7 +206,7 @@ Thought: {agent_scratchpad}
     @classmethod
     def from_llm_and_tools(
             cls,
-            model_config: ModelConfigEntity,
+            model_config: EasyUIBasedModelConfigEntity,
             tools: Sequence[BaseTool],
             callback_manager: Optional[BaseCallbackManager] = None,
             output_parser: Optional[AgentOutputParser] = None,

api/core/rag/retrieval/agent_based_dataset_executor.py

@@ -7,13 +7,12 @@ from langchain.callbacks.manager import Callbacks
 from langchain.tools import BaseTool
 from pydantic import BaseModel, Extra
 
+from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
 from core.entities.agent_entities import PlanningStrategy
-from core.entities.application_entities import ModelConfigEntity
 from core.entities.message_entities import prompt_messages_to_lc_messages
 from core.helper import moderation
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.errors.invoke import InvokeError
-from core.rag.retrieval.agent.agent_llm_callback import AgentLLMCallback
 from core.rag.retrieval.agent.multi_dataset_router_agent import MultiDatasetRouterAgent
 from core.rag.retrieval.agent.output_parser.structured_chat import StructuredChatOutputParser
 from core.rag.retrieval.agent.structed_multi_dataset_router_agent import StructuredMultiDatasetRouterAgent
@@ -23,15 +22,14 @@ from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetr
 
 class AgentConfiguration(BaseModel):
     strategy: PlanningStrategy
-    model_config: ModelConfigEntity
+    model_config: EasyUIBasedModelConfigEntity
     tools: list[BaseTool]
-    summary_model_config: Optional[ModelConfigEntity] = None
+    summary_model_config: Optional[EasyUIBasedModelConfigEntity] = None
     memory: Optional[TokenBufferMemory] = None
     callbacks: Callbacks = None
     max_iterations: int = 6
     max_execution_time: Optional[float] = None
     early_stopping_method: str = "generate"
-    agent_llm_callback: Optional[AgentLLMCallback] = None
     # `generate` will continue to complete the last inference after reaching the iteration limit or request time limit
 
     class Config:

api/core/rag/retrieval/dataset_retrieval.py

@@ -2,9 +2,10 @@ from typing import Optional, cast
 
 from langchain.tools import BaseTool
 
+from core.app.app_config.entities import DatasetEntity, DatasetRetrieveConfigEntity
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.entities.agent_entities import PlanningStrategy
-from core.entities.application_entities import DatasetEntity, DatasetRetrieveConfigEntity, InvokeFrom, ModelConfigEntity
+from core.app.entities.app_invoke_entities import InvokeFrom, EasyUIBasedModelConfigEntity
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.model_entities import ModelFeature
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
@@ -17,7 +18,7 @@ from models.dataset import Dataset
 
 class DatasetRetrieval:
     def retrieve(self, tenant_id: str,
-                 model_config: ModelConfigEntity,
+                 model_config: EasyUIBasedModelConfigEntity,
                  config: DatasetEntity,
                  query: str,
                  invoke_from: InvokeFrom,

api/core/tools/tool/dataset_retriever_tool.py

@@ -2,8 +2,9 @@ from typing import Any
 
 from langchain.tools import BaseTool
 
+from core.app.app_config.entities import DatasetRetrieveConfigEntity
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.entities.application_entities import DatasetRetrieveConfigEntity, InvokeFrom
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
 from core.tools.entities.common_entities import I18nObject
 from core.tools.entities.tool_entities import ToolDescription, ToolIdentity, ToolInvokeMessage, ToolParameter

api/events/event_handlers/deduct_quota_when_messaeg_created.py

@@ -1,4 +1,4 @@
-from core.entities.application_entities import ApplicationGenerateEntity
+from core.app.entities.app_invoke_entities import EasyUIBasedAppGenerateEntity
 from core.entities.provider_entities import QuotaUnit
 from events.message_event import message_was_created
 from extensions.ext_database import db
@@ -8,9 +8,9 @@ from models.provider import Provider, ProviderType
 @message_was_created.connect
 def handle(sender, **kwargs):
     message = sender
-    application_generate_entity: ApplicationGenerateEntity = kwargs.get('application_generate_entity')
+    application_generate_entity: EasyUIBasedAppGenerateEntity = kwargs.get('application_generate_entity')
 
-    model_config = application_generate_entity.app_orchestration_config_entity.model_config
+    model_config = application_generate_entity.model_config
     provider_model_bundle = model_config.provider_model_bundle
     provider_configuration = provider_model_bundle.configuration
 
@@ -43,7 +43,7 @@ def handle(sender, **kwargs):
 
     if used_quota is not None:
         db.session.query(Provider).filter(
-            Provider.tenant_id == application_generate_entity.tenant_id,
+            Provider.tenant_id == application_generate_entity.app_config.tenant_id,
             Provider.provider_name == model_config.provider,
             Provider.provider_type == ProviderType.SYSTEM.value,
             Provider.quota_type == system_configuration.current_quota_type.value,