""" Agent Base Module. Provides the base class for all chat agents. Defines the standardized interface for task processing. """ import os import logging import uuid from datetime import datetime, UTC from typing import Dict, Any, List, Optional from modules.shared.mimeUtils import isTextMimeType, determineContentEncoding from modules.interfaces.serviceChatModel import ChatContent, Task, AgentResponse, ChatMessage logger = logging.getLogger(__name__) class AgentBase: """ Base class for all chat agents. Defines the standardized interface for task processing. """ def __init__(self): """Initialize the base agent.""" self.name = "base" self.label = "Base Agent" self.description = "Base agent functionality" self.capabilities = [] self.service = None def setService(self, service): """ Set the service container reference and validate required interfaces. Args: service: The service container with required interfaces """ if not service: logger.warning("Attempted to set null service container") return False # Validate required interfaces required_interfaces = ['base', 'msft', 'google'] missing_interfaces = [] for interface in required_interfaces: if not hasattr(service, interface): missing_interfaces.append(interface) if missing_interfaces: logger.warning(f"Service container missing required interfaces: {', '.join(missing_interfaces)}") return False self.service = service return True def getAgentInfo(self) -> Dict[str, Any]: """ Return standardized information about the agent's capabilities. Returns: Dictionary with name, description, and capabilities """ return { "name": self.name, "label": self.label, "description": self.description, "capabilities": self.capabilities } async def execute(self, task: Task) -> AgentResponse: """ Execute a task and return the response. This method must be implemented by all concrete agent classes. Args: task: Task object containing all necessary information Returns: AgentResponse object with execution results """ # Validate service manager if not self.service: logger.error("Service container not initialized") return AgentResponse( success=False, message=ChatMessage( id=str(uuid.uuid4()), workflowId=task.workflowId, agentName=self.name, message="Error: Service container not initialized", role="system", status="error", sequenceNr=0, startedAt=datetime.now(UTC).isoformat(), finishedAt=datetime.now(UTC).isoformat(), success=False ), performance={}, progress=0.0 ) try: # Process the task using the concrete implementation result = await self.processTask(task) # Create response message message = ChatMessage( id=str(uuid.uuid4()), workflowId=task.workflowId, agentName=self.name, message=result.get("feedback", ""), role="assistant", status="completed", sequenceNr=0, startedAt=datetime.now(UTC).isoformat(), finishedAt=datetime.now(UTC).isoformat(), success=True ) # Create response with performance metrics return AgentResponse( success=True, message=message, performance=result.get("performance", {}), progress=result.get("progress", 100.0) ) except Exception as e: logger.error(f"Error processing task: {str(e)}", exc_info=True) return AgentResponse( success=False, message=ChatMessage( id=str(uuid.uuid4()), workflowId=task.workflowId, agentName=self.name, message=f"Error processing task: {str(e)}", role="system", status="error", sequenceNr=0, startedAt=datetime.now(UTC).isoformat(), finishedAt=datetime.now(UTC).isoformat(), success=False ), performance={}, progress=0.0 ) async def processTask(self, task: Task) -> Dict[str, Any]: """ Process a task and return the results. This method must be implemented by all concrete agent classes. Args: task: Task object containing all necessary information Returns: Dictionary containing: - feedback: Text response explaining what the agent did - performance: Optional performance metrics - progress: Task progress (0-100) """ raise NotImplementedError("processTask must be implemented by concrete agent classes") def determineBase64EncodingFlag(self, filename: str, content: Any, mimeType: str = None) -> bool: """ Determine if content should be base64 encoded. Args: filename: Name of the file content: Content to check mimeType: Optional MIME type Returns: Boolean indicating if content should be base64 encoded """ return determineContentEncoding(filename, content, mimeType) def isTextMimeType(self, mimeType: str) -> bool: """ Check if MIME type is text-based. Args: mimeType: MIME type to check Returns: Boolean indicating if MIME type is text-based """ return isTextMimeType(mimeType) def formatAgentDocumentOutput(self, label: str, content: str, contentType: str, base64Encoded: bool = False) -> ChatContent: """ Format agent document output using ChatContent model. Args: label: Document label/filename content: Document content contentType: MIME type of content base64Encoded: Whether content is base64 encoded Returns: ChatContent object with the following attributes: - sequenceNr: Sequence number (defaults to 1) - name: Document label/filename - mimeType: MIME type of content - data: Actual content - metadata: Additional metadata including base64Encoded flag """ return ChatContent( sequenceNr=1, name=label, mimeType=contentType, data=content, metadata={"base64Encoded": base64Encoded} )