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Multi-Agent Orchestrator for coordinating the policy analysis pipeline.
"""
import asyncio
from typing import Dict, List, Optional, Any
from datetime import datetime
from collections import defaultdict
from loguru import logger
from agents.base import (
BaseAgent,
AgentRole,
AgentMessage,
MessageType,
AgentStatus
)
class WorkflowStage(str):
"""Workflow stage identifiers."""
SCRAPE = "scrape"
PARSE = "parse"
CLASSIFY = "classify"
ANALYZE = "analyze"
GENERATE = "generate"
class OrchestratorAgent(BaseAgent):
"""
Orchestrator agent that coordinates the multi-agent workflow.
The orchestrator manages the flow of data through the pipeline:
1. Scraper Agent -> Collects meeting minutes
2. Parser Agent -> Extracts structured data
3. Classifier Agent -> Identifies oral health topics
4. Sentiment Agent -> Analyzes policy positions
5. Advocacy Agent -> Generates outreach materials
"""
def __init__(self, agent_id: str = "orchestrator-001"):
"""Initialize the orchestrator agent."""
super().__init__(agent_id, AgentRole.ORCHESTRATOR)
self.agents: Dict[AgentRole, BaseAgent] = {}
self.workflow_state: Dict[str, Any] = defaultdict(dict)
self.active_workflows: Dict[str, Dict[str, Any]] = {}
def register_agent(self, agent: BaseAgent):
"""
Register an agent with the orchestrator.
Args:
agent: The agent to register
"""
self.agents[agent.role] = agent
logger.info(f"Registered {agent.role.value} agent: {agent.agent_id}")
async def process(self, message: AgentMessage) -> List[AgentMessage]:
"""
Process orchestrator commands and route messages.
Args:
message: The incoming message
Returns:
List of response messages
"""
self.update_status(AgentStatus.PROCESSING, "Processing orchestrator command")
try:
if message.message_type == MessageType.COMMAND:
command = message.payload.get("command")
if command == "start_workflow":
return await self._start_workflow(message.payload)
elif command == "check_status":
return await self._check_workflow_status(message.payload)
elif command == "stop_workflow":
return await self._stop_workflow(message.payload)
self.log_success()
return []
except Exception as e:
self.log_failure(str(e))
return [await self.send_message(
message.sender,
MessageType.ERROR,
{"error": str(e)}
)]
async def _start_workflow(self, payload: Dict[str, Any]) -> List[AgentMessage]:
"""
Start a new policy analysis workflow.
Args:
payload: Workflow configuration
Returns:
List of messages to initiate the workflow
"""
import uuid
workflow_id = str(uuid.uuid4())
workflow_config = payload.get("config", {})
# Initialize workflow state
self.active_workflows[workflow_id] = {
"id": workflow_id,
"started_at": datetime.utcnow(),
"stage": WorkflowStage.SCRAPE,
"config": workflow_config,
"status": "running"
}
logger.info(f"Starting workflow {workflow_id}")
# Create initial scraping task
scraper_message = await self.send_message(
AgentRole.SCRAPER,
MessageType.COMMAND,
{
"workflow_id": workflow_id,
"command": "scrape",
"targets": workflow_config.get("scrape_targets", []),
"date_range": workflow_config.get("date_range", {})
}
)
return [scraper_message]
async def _check_workflow_status(self, payload: Dict[str, Any]) -> List[AgentMessage]:
"""
Check the status of active workflows.
Args:
payload: Status check request
Returns:
List containing status response
"""
workflow_id = payload.get("workflow_id")
if workflow_id and workflow_id in self.active_workflows:
workflow = self.active_workflows[workflow_id]
status_payload = {
"workflow_id": workflow_id,
"status": workflow.get("status"),
"stage": workflow.get("stage"),
"started_at": workflow.get("started_at").isoformat()
}
else:
# Return status of all workflows
status_payload = {
"active_workflows": len(self.active_workflows),
"workflows": [
{
"id": wf_id,
"status": wf["status"],
"stage": wf["stage"]
}
for wf_id, wf in self.active_workflows.items()
]
}
response = await self.send_message(
AgentRole.ORCHESTRATOR,
MessageType.RESPONSE,
status_payload
)
return [response]
async def _stop_workflow(self, payload: Dict[str, Any]) -> List[AgentMessage]:
"""
Stop a running workflow.
Args:
payload: Stop request with workflow_id
Returns:
List containing confirmation message
"""
workflow_id = payload.get("workflow_id")
if workflow_id in self.active_workflows:
self.active_workflows[workflow_id]["status"] = "stopped"
logger.info(f"Stopped workflow {workflow_id}")
response = await self.send_message(
AgentRole.ORCHESTRATOR,
MessageType.RESPONSE,
{"workflow_id": workflow_id, "status": "stopped"}
)
else:
response = await self.send_message(
AgentRole.ORCHESTRATOR,
MessageType.ERROR,
{"error": f"Workflow {workflow_id} not found"}
)
return [response]
async def route_message(self, message: AgentMessage) -> Optional[AgentMessage]:
"""
Route a message to the appropriate agent.
Args:
message: The message to route
Returns:
Response from the target agent
"""
target_agent = self.agents.get(message.recipient)
if not target_agent:
logger.error(f"No agent found for role: {message.recipient}")
return None
try:
response = await target_agent.process(message)
return response
except Exception as e:
logger.error(f"Error routing message to {message.recipient}: {e}")
return None
async def execute_pipeline(
self,
scrape_targets: List[Dict[str, Any]],
date_range: Optional[Dict[str, str]] = None
) -> Dict[str, Any]:
"""
Execute the complete policy analysis pipeline.
Args:
scrape_targets: List of government entities to scrape
date_range: Optional date range for historical data
Returns:
Dictionary containing pipeline results
"""
workflow_config = {
"scrape_targets": scrape_targets,
"date_range": date_range or {}
}
# Start the workflow
start_message = await self.send_message(
AgentRole.ORCHESTRATOR,
MessageType.COMMAND,
{
"command": "start_workflow",
"config": workflow_config
}
)
results = await self.process(start_message)
return {
"success": True,
"workflow_initiated": True,
"messages": [msg.dict() for msg in results]
}
def get_all_agent_states(self) -> Dict[str, Any]:
"""Get the current state of all registered agents."""
return {
role.value: agent.get_state().dict()
for role, agent in self.agents.items()
}
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