from crewai import Agent, Task, Crew, Process
from crewai_tools import SerperDevTool

search_tool = SerperDevTool()

# ── Define Agents with Roles ─────────────────────────────────────────────────

researcher = Agent(
    role="Senior Research Analyst",
    goal="Find comprehensive, accurate information on the given topic",
    backstory=(
        "You are an expert researcher with 10 years of experience synthesizing "
        "complex information from multiple sources. You always cite your sources."
    ),
    tools=[search_tool],
    llm="gpt-4o",
    verbose=True,
)

writer = Agent(
    role="Content Strategist",
    goal="Write clear, engaging content based on research findings",
    backstory=(
        "You transform complex research into accessible, compelling narratives. "
        "You write for a technical audience and always back claims with evidence."
    ),
    llm="gpt-4o",
)

# ── Define Tasks ─────────────────────────────────────────────────────────────

research_task = Task(
    description="Research the current state of {topic}. Find key developments in 2025-2026.",
    expected_output="A structured research report with key findings, sources, and data points.",
    agent=researcher,
)

writing_task = Task(
    description="Write a 500-word article about {topic} based on the research report.",
    expected_output="A complete article with title, intro, 3 body sections, and conclusion.",
    agent=writer,
    context=[research_task],   # this task depends on research_task's output
)

# ── Assemble Crew ─────────────────────────────────────────────────────────────

crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, writing_task],
    process=Process.sequential,   # or Process.hierarchical for supervisor pattern
    verbose=True,
)

result = crew.kickoff(inputs={"topic": "AI agent frameworks in 2026"})

from crewai.flow.flow import Flow, start, listen, router

class ContentFlow(Flow):

    @start()
    def classify_request(self):
        return "technical" if "code" in self.state.get("topic", "") else "general"

    @router(classify_request)
    def route_by_type(self, result: str) -> str:
        return "technical_crew" if result == "technical" else "general_crew"

    @listen("technical_crew")
    def run_technical_crew(self):
        # run technical writing crew
        return technical_crew.kickoff(inputs=self.state)

    @listen("general_crew")
    def run_general_crew(self):
        return general_crew.kickoff(inputs=self.state)

flow = ContentFlow()
result = flow.kickoff(inputs={"topic": "Python async patterns"})

from agents import Agent, Runner, handoff, input_guardrail, GuardrailFunctionOutput
from pydantic import BaseModel

# ── Specialist agents ────────────────────────────────────────────────────────

billing_agent = Agent(
    name="Billing Agent",
    instructions=(
        "You handle billing questions: invoices, charges, refunds, and payment methods. "
        "Be concise and factual. If you cannot resolve the issue, say so."
    ),
)

technical_agent = Agent(
    name="Technical Support Agent",
    instructions=(
        "You handle technical issues: bugs, configuration, API errors, and performance. "
        "Ask for logs or error messages before diagnosing."
    ),
)

# ── Input guardrail — blocks off-topic requests ──────────────────────────────

class TopicCheck(BaseModel):
    is_support_related: bool
    reasoning: str

@input_guardrail
async def support_topic_guardrail(ctx, agent, input_text) -> GuardrailFunctionOutput:
    result = await Runner.run(
        Agent(
            name="Topic Classifier",
            instructions="Determine if this message is customer support related.",
            output_type=TopicCheck,
        ),
        input=input_text,
    )
    check = result.final_output
    return GuardrailFunctionOutput(
        output_info=check,
        tripwire_triggered=not check.is_support_related,
    )

# ── Triage agent — routes to specialists ─────────────────────────────────────

triage_agent = Agent(
    name="Triage Agent",
    instructions=(
        "Classify the customer request and route it to the appropriate specialist. "
        "Use billing_handoff for billing questions, technical_handoff for technical issues."
    ),
    handoffs=[
        handoff(billing_agent, tool_name_override="billing_handoff"),
        handoff(technical_agent, tool_name_override="technical_handoff"),
    ],
    input_guardrails=[support_topic_guardrail],
)

# ── Run ───────────────────────────────────────────────────────────────────────

import asyncio

async def main():
    result = await Runner.run(
        triage_agent,
        input="I was charged twice for my subscription last month. Please help.",
    )
    print(result.final_output)

asyncio.run(main())