42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
import logging
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from typing import Optional
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from modules.datamodels.datamodelUam import User
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from modules.datamodels.datamodelChat import ChatWorkflow, UserInputRequest
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from modules.workflows.workflowManager import WorkflowManager
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from modules.services import getInterface as getServices
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logger = logging.getLogger(__name__)
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async def chatStart(interfaceDbChat, currentUser: User, userInput: UserInputRequest, workflowId: Optional[str] = None, workflowMode: str = "Actionplan") -> ChatWorkflow:
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"""
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Starts a new chat or continues an existing one, then launches processing asynchronously.
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Args:
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interfaceDbChat: Chat interface instance
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currentUser: Current user
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userInput: User input request
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workflowId: Optional workflow ID to continue existing workflow
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workflowMode: "Actionplan" for traditional task planning, "React" for iterative react-style processing
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Example usage for React mode:
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workflow = await chatStart(interfaceDbChat, currentUser, userInput, workflowMode="React")
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"""
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try:
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services = getServices(currentUser, None)
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workflowManager = WorkflowManager(services)
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workflow = await workflowManager.workflowStart(userInput, workflowId, workflowMode)
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return workflow
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except Exception as e:
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logger.error(f"Error starting chat: {str(e)}")
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raise
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async def chatStop(interfaceDbChat, currentUser: User, workflowId: str) -> ChatWorkflow:
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"""Stops a running chat."""
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try:
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services = getServices(currentUser, None)
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workflowManager = WorkflowManager(services)
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return await workflowManager.workflowStop(workflowId)
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except Exception as e:
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logger.error(f"Error stopping chat: {str(e)}")
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raise
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