import json import logging from typing import Optional, Type from langchain_core.callbacks import CallbackManagerForToolRun from langchain_core.pydantic_v1 import BaseModel, Field from langchain_community.tools.slack.base import SlackBaseTool class SlackGetMessageSchema(BaseModel): """Input schema for SlackGetMessages.""" channel_id: str = Field( ..., description="The channel id, private group, or IM channel to send message to.", ) class SlackGetMessage(SlackBaseTool): name: str = "get_messages" description: str = "Use this tool to get messages from a channel." args_schema: Type[SlackGetMessageSchema] = SlackGetMessageSchema def _run( self, channel_id: str, run_manager: Optional[CallbackManagerForToolRun] = None, ) -> str: logging.getLogger(__name__) try: result = self.client.conversations_history(channel=channel_id) messages = result["messages"] filtered_messages = [ {key: message[key] for key in ("user", "text", "ts")} for message in messages if "user" in message and "text" in message and "ts" in message ] return json.dumps(filtered_messages) except Exception as e: return "Error creating conversation: {}".format(e)