from typing import TYPE_CHECKING, Optional, Type from langchain_core.callbacks import ( CallbackManagerForToolRun, ) from langchain_core.pydantic_v1 import BaseModel, Field from langchain_core.tools import BaseTool if TYPE_CHECKING: # This is for linting and IDE typehints import multion else: try: # We do this so pydantic can resolve the types when instantiating import multion except ImportError: pass class UpdateSessionSchema(BaseModel): """Input for UpdateSessionTool.""" sessionId: str = Field( ..., description="""The sessionID, received from one of the createSessions run before""", ) query: str = Field( ..., description="The query to run in multion agent.", ) url: str = Field( "https://www.google.com/", description="""The Url to run the agent at. \ Note: accepts only secure links having https://""", ) class MultionUpdateSession(BaseTool): """Tool that updates an existing Multion Browser Window with provided fields. Attributes: name: The name of the tool. Default: "update_multion_session" description: The description of the tool. args_schema: The schema for the tool's arguments. Default: UpdateSessionSchema """ name: str = "update_multion_session" description: str = """Use this tool to update \ an existing corresponding Multion Browser Window with provided fields. \ Note: sessionId must be received from previous Browser window creation.""" args_schema: Type[UpdateSessionSchema] = UpdateSessionSchema sessionId: str = "" def _run( self, sessionId: str, query: str, url: Optional[str] = "https://www.google.com/", run_manager: Optional[CallbackManagerForToolRun] = None, ) -> dict: try: try: response = multion.update_session( sessionId, {"input": query, "url": url} ) content = {"sessionId": sessionId, "Response": response["message"]} self.sessionId = sessionId return content except Exception as e: print(f"{e}, retrying...") return {"error": f"{e}", "Response": "retrying..."} except Exception as e: raise Exception(f"An error occurred: {e}")