1.4 Workflow Enforcement and Handoff

from enum import Enum

class WorkflowState(Enum):
    INTAKE = "intake"
    RESEARCH = "research"
    DESIGN = "design"
    REVIEW = "review"
    DELIVER = "deliver"

TRANSITIONS = {
    WorkflowState.INTAKE: [WorkflowState.RESEARCH],
    WorkflowState.RESEARCH: [WorkflowState.DESIGN],
    WorkflowState.DESIGN: [WorkflowState.REVIEW],
    WorkflowState.REVIEW: [WorkflowState.DESIGN, WorkflowState.DELIVER],
    WorkflowState.DELIVER: [],
}

class WorkflowEngine:
    def __init__(self):
        self.state = WorkflowState.INTAKE
        self.context = {}

    def transition(self, next_state):
        if next_state not in TRANSITIONS[self.state]:
            raise ValueError(f"Cannot transition from {self.state} to {next_state}")
        self.state = next_state

    def run_current_step(self):
        agent_prompt = self.build_prompt_for_state(self.state)
        result = run_agent(agent_prompt, context=self.context)
        self.context[self.state.value] = result
        return result

class HandoffPacket:
    def __init__(self):
        self.from_agent: str          # ใครส่ง
        self.to_agent: str            # ส่งให้ใคร
        self.task_summary: str        # สรุปงานที่ทำมาแล้ว
        self.deliverables: list       # output ที่ได้
        self.open_questions: list     # คำถามที่ยังไม่ตอบ
        self.constraints: list        # ข้อจำกัดที่ต้องเคารพ
        self.next_action: str         # สิ่งที่ต้องทำต่อ

phase('Research')
const research = await agent(`
  Research the following requirements and produce verified findings:
  ${requirements}

  Output: research.md with citations
`, {label: 'researcher', phase: 'Research'})

phase('Design')
const design = await agent(`
  Based on the research findings below, design a solution architecture.

  ## Research Findings
  ${research}

  ## Constraints
  - Must support 10k concurrent users
  - Budget: $5k/month cloud cost

  Output: design.md with diagram description
`, {label: 'designer', phase: 'Design'})

class GuardedAgent:
    def __init__(self, allowed_tools, max_cost, max_time):
        self.allowed_tools = allowed_tools
        self.max_cost = max_cost
        self.max_time = max_time
        self.total_cost = 0

    def execute_tool(self, tool_name, params):
        if tool_name not in self.allowed_tools:
            return {"error": f"Tool {tool_name} not allowed in this workflow step"}
        if self.total_cost > self.max_cost:
            return {"error": "Cost budget exceeded"}
        return run_tool(tool_name, params)