chore: remove Langchain tools import (#3407)

api/core/tools/tool/dataset_retriever/dataset_multi_retriever_tool.py

@@ -1,8 +1,6 @@
 import threading
-from typing import Optional
 
 from flask import Flask, current_app
-from langchain.tools import BaseTool
 from pydantic import BaseModel, Field
 
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
@@ -10,6 +8,7 @@ from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from core.rag.datasource.retrieval_service import RetrievalService
 from core.rerank.rerank import RerankRunner
+from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from extensions.ext_database import db
 from models.dataset import Dataset, Document, DocumentSegment
 
@@ -29,20 +28,15 @@ class DatasetMultiRetrieverToolInput(BaseModel):
     query: str = Field(..., description="dataset multi retriever and rerank")
 
 
-class DatasetMultiRetrieverTool(BaseTool):
+class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool):
     """Tool for querying multi dataset."""
     name: str = "dataset_"
     args_schema: type[BaseModel] = DatasetMultiRetrieverToolInput
     description: str = "dataset multi retriever and rerank. "
-    tenant_id: str
     dataset_ids: list[str]
-    top_k: int = 2
-    score_threshold: Optional[float] = None
     reranking_provider_name: str
     reranking_model_name: str
-    return_resource: bool
-    retriever_from: str
-    hit_callbacks: list[DatasetIndexToolCallbackHandler] = []
+
 
     @classmethod
     def from_dataset(cls, dataset_ids: list[str], tenant_id: str, **kwargs):
@@ -149,9 +143,6 @@ class DatasetMultiRetrieverTool(BaseTool):
 
             return str("\n".join(document_context_list))
 
-    async def _arun(self, tool_input: str) -> str:
-        raise NotImplementedError()
-
     def _retriever(self, flask_app: Flask, dataset_id: str, query: str, all_documents: list,
                    hit_callbacks: list[DatasetIndexToolCallbackHandler]):
         with flask_app.app_context():

api/core/tools/tool/dataset_retriever/dataset_retriever_base_tool.py

@@ -0,0 +1,34 @@
+from abc import abstractmethod
+from typing import Any, Optional
+
+from msal_extensions.persistence import ABC
+from pydantic import BaseModel
+
+from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
+
+
+class DatasetRetrieverBaseTool(BaseModel, ABC):
+    """Tool for querying a Dataset."""
+    name: str = "dataset"
+    description: str = "use this to retrieve a dataset. "
+    tenant_id: str
+    top_k: int = 2
+    score_threshold: Optional[float] = None
+    hit_callbacks: list[DatasetIndexToolCallbackHandler] = []
+    return_resource: bool
+    retriever_from: str
+
+    class Config:
+        arbitrary_types_allowed = True
+
+    @abstractmethod
+    def _run(
+        self,
+        *args: Any,
+        **kwargs: Any,
+    ) -> Any:
+        """Use the tool.
+
+        Add run_manager: Optional[CallbackManagerForToolRun] = None
+        to child implementations to enable tracing,
+        """

api/core/tools/tool/dataset_retriever/dataset_retriever_tool.py

@@ -1,10 +1,8 @@
-from typing import Optional
 
-from langchain.tools import BaseTool
 from pydantic import BaseModel, Field
 
-from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.rag.datasource.retrieval_service import RetrievalService
+from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from extensions.ext_database import db
 from models.dataset import Dataset, Document, DocumentSegment
 
@@ -24,19 +22,13 @@ class DatasetRetrieverToolInput(BaseModel):
     query: str = Field(..., description="Query for the dataset to be used to retrieve the dataset.")
 
 
-class DatasetRetrieverTool(BaseTool):
+class DatasetRetrieverTool(DatasetRetrieverBaseTool):
     """Tool for querying a Dataset."""
     name: str = "dataset"
     args_schema: type[BaseModel] = DatasetRetrieverToolInput
     description: str = "use this to retrieve a dataset. "
-
-    tenant_id: str
     dataset_id: str
-    top_k: int = 2
-    score_threshold: Optional[float] = None
-    hit_callbacks: list[DatasetIndexToolCallbackHandler] = []
-    return_resource: bool
-    retriever_from: str
+
 
     @classmethod
     def from_dataset(cls, dataset: Dataset, **kwargs):
@@ -153,7 +145,4 @@ class DatasetRetrieverTool(BaseTool):
                     for hit_callback in self.hit_callbacks:
                         hit_callback.return_retriever_resource_info(context_list)
 
-            return str("\n".join(document_context_list))
-
-    async def _arun(self, tool_input: str) -> str:
-        raise NotImplementedError()
+            return str("\n".join(document_context_list))

api/core/tools/tool/dataset_retriever_tool.py

@@ -1,7 +1,5 @@
 from typing import Any
 
-from langchain.tools import BaseTool
-
 from core.app.app_config.entities import DatasetRetrieveConfigEntity
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
@@ -14,11 +12,12 @@ from core.tools.entities.tool_entities import (
     ToolParameter,
     ToolProviderType,
 )
+from core.tools.tool.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
 from core.tools.tool.tool import Tool
 
 
 class DatasetRetrieverTool(Tool):
-    langchain_tool: BaseTool
+    retrival_tool: DatasetRetrieverBaseTool
 
     @staticmethod
     def get_dataset_tools(tenant_id: str,
@@ -43,7 +42,7 @@ class DatasetRetrieverTool(Tool):
         # Agent only support SINGLE mode
         original_retriever_mode = retrieve_config.retrieve_strategy
         retrieve_config.retrieve_strategy = DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE
-        langchain_tools = feature.to_dataset_retriever_tool(
+        retrival_tools = feature.to_dataset_retriever_tool(
             tenant_id=tenant_id,
             dataset_ids=dataset_ids,
             retrieve_config=retrieve_config,
@@ -54,17 +53,17 @@ class DatasetRetrieverTool(Tool):
         # restore retrieve strategy
         retrieve_config.retrieve_strategy = original_retriever_mode
 
-        # convert langchain tools to Tools
+        # convert retrival tools to Tools
         tools = []
-        for langchain_tool in langchain_tools:
+        for retrival_tool in retrival_tools:
             tool = DatasetRetrieverTool(
-                langchain_tool=langchain_tool,
-                identity=ToolIdentity(provider='', author='', name=langchain_tool.name, label=I18nObject(en_US='', zh_Hans='')),
+                retrival_tool=retrival_tool,
+                identity=ToolIdentity(provider='', author='', name=retrival_tool.name, label=I18nObject(en_US='', zh_Hans='')),
                 parameters=[],
                 is_team_authorization=True,
                 description=ToolDescription(
                     human=I18nObject(en_US='', zh_Hans=''),
-                    llm=langchain_tool.description),
+                    llm=retrival_tool.description),
                 runtime=DatasetRetrieverTool.Runtime()
             )
 
@@ -96,7 +95,7 @@ class DatasetRetrieverTool(Tool):
             return self.create_text_message(text='please input query')
 
         # invoke dataset retriever tool
-        result = self.langchain_tool._run(query=query)
+        result = self.retrival_tool._run(query=query)
 
         return self.create_text_message(text=result)