refactor app generate

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

@@ -5,14 +5,14 @@ from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.schema import Generation, LLMResult
 from langchain.schema.language_model import BaseLanguageModel
 
-from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
+from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 from core.entities.message_entities import lc_messages_to_prompt_messages
 from core.model_manager import ModelInstance
 from core.rag.retrieval.agent.fake_llm import FakeLLM
 
 
 class LLMChain(LCLLMChain):
-    model_config: EasyUIBasedModelConfigEntity
+    model_config: ModelConfigWithCredentialsEntity
     """The language model instance to use."""
     llm: BaseLanguageModel = FakeLLM(response="")
     parameters: dict[str, Any] = {}

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.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
+from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 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: EasyUIBasedModelConfigEntity
+    model_config: ModelConfigWithCredentialsEntity
 
     class Config:
         """Configuration for this pydantic object."""
@@ -156,7 +156,7 @@ class MultiDatasetRouterAgent(OpenAIFunctionsAgent):
     @classmethod
     def from_llm_and_tools(
             cls,
-            model_config: EasyUIBasedModelConfigEntity,
+            model_config: ModelConfigWithCredentialsEntity,
             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.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity
+from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 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: EasyUIBasedModelConfigEntity,
+            model_config: ModelConfigWithCredentialsEntity,
             tools: Sequence[BaseTool],
             callback_manager: Optional[BaseCallbackManager] = None,
             output_parser: Optional[AgentOutputParser] = None,

api/core/rag/retrieval/agent_based_dataset_executor.py

@@ -7,7 +7,7 @@ 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.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
 from core.entities.agent_entities import PlanningStrategy
 from core.entities.message_entities import prompt_messages_to_lc_messages
 from core.helper import moderation
@@ -22,9 +22,9 @@ from core.tools.tool.dataset_retriever.dataset_retriever_tool import DatasetRetr
 
 class AgentConfiguration(BaseModel):
     strategy: PlanningStrategy
-    model_config: EasyUIBasedModelConfigEntity
+    model_config: ModelConfigWithCredentialsEntity
     tools: list[BaseTool]
-    summary_model_config: Optional[EasyUIBasedModelConfigEntity] = None
+    summary_model_config: Optional[ModelConfigWithCredentialsEntity] = None
     memory: Optional[TokenBufferMemory] = None
     callbacks: Callbacks = None
     max_iterations: int = 6

api/core/rag/retrieval/dataset_retrieval.py

@@ -3,7 +3,7 @@ from typing import Optional, cast
 from langchain.tools import BaseTool
 
 from core.app.app_config.entities import DatasetEntity, DatasetRetrieveConfigEntity
-from core.app.entities.app_invoke_entities import EasyUIBasedModelConfigEntity, InvokeFrom
+from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity, InvokeFrom
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.entities.agent_entities import PlanningStrategy
 from core.memory.token_buffer_memory import TokenBufferMemory
@@ -18,7 +18,7 @@ from models.dataset import Dataset
 
 class DatasetRetrieval:
     def retrieve(self, tenant_id: str,
-                 model_config: EasyUIBasedModelConfigEntity,
+                 model_config: ModelConfigWithCredentialsEntity,
                  config: DatasetEntity,
                  query: str,
                  invoke_from: InvokeFrom,