gateway/modules/workflow/agentBase.py
ValueOn AG cf94b1115b ref
2025-05-26 07:04:30 +02:00

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Python

"""
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
from typing import Dict, Any, List, Optional
from modules.shared.mimeUtils import isTextMimeType, determineContentEncoding
from modules.interfaces.serviceChatModel import ChatContent
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 processTask(self, task: Dict[str, Any]) -> Dict[str, Any]:
"""
Process a standardized task structure and return results.
This method must be implemented by all concrete agent classes.
Args:
task: A dictionary containing:
- taskId: Unique ID for this task
- workflowId: ID of the parent workflow
- prompt: The main instruction for the agent
- inputDocuments: List of document objects to process
- outputSpecifications: List of required output documents
- context: Additional contextual information including:
- workflow: The complete workflow object
- workflowRound: Current workflow round
- agentType: Type of agent
- timestamp: Task timestamp
- language: User language
Returns:
A dictionary containing:
- feedback: Text response explaining what the agent did
- documents: List of document objects created by the agent,
each containing a "base64Encoded" flag in addition to "label" and "content"
"""
# Validate service manager
if not self.service:
logger.error("Service container not initialized")
return {
"feedback": "Error: Service container not initialized",
"documents": []
}
# Base implementation - should be overridden by specialized agents
logger.warning(f"Agent {self.name} is using the default implementation of processTask")
return {
"feedback": f"The processTask method was not implemented by agent '{self.name}'.",
"documents": []
}
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}
)