"""
Unit tests for LangGraph multi-agent orchestrator.
"""
from __future__ import annotations

import pytest
from unittest.mock import patch, AsyncMock, MagicMock
from httpx import AsyncClient

from agents.planner import planner_node
from agents.graph import run_copilot_pipeline
from app.services.llm_gateway import LLMResponse


@pytest.mark.asyncio
async def test_planner_node_classification():
    mock_llm_res = LLMResponse(
        content='{"routing_decision": "retrieval", "explanation": "Asks for policy", "doc_type_filter": "hr"}',
        provider="groq",
        model="llama-3.1-8b-instant",
        tokens_used=20,
        latency_ms=100.0,
    )

    with patch("app.services.llm_gateway.llm_gateway.generate", new_callable=AsyncMock) as mock_gen:
        mock_gen.return_value = mock_llm_res

        initial_state = {
            "query": "What is our leave policy?",
            "user_role": "employee",
        }
        res_state = await planner_node(initial_state)

        assert res_state["routing_decision"] == "retrieval"
        assert res_state["doc_type_filter"] == "hr"


@pytest.mark.asyncio
async def test_copilot_pipeline_execution():
    mock_llm_res = LLMResponse(
        content="According to the policy, employees receive 20 days of paid leave per year.",
        provider="groq",
        model="llama-3.1-8b-instant",
        tokens_used=45,
        latency_ms=150.0,
    )

    with patch("app.services.llm_gateway.llm_gateway.generate", new_callable=AsyncMock) as mock_gen:
        mock_gen.return_value = mock_llm_res

        result = await run_copilot_pipeline(
            query="Hello copilot",
            tenant_id="tenant-123",
            user_id="user-456",
        )

        assert "response" in result
        assert result["latency_ms"] >= 0
        assert "routing_decision" in result


@pytest.mark.asyncio
async def test_chat_api_endpoint(client: AsyncClient):
    # 1. Register user
    reg = await client.post("/api/v1/auth/register", json={
        "email": "agent_user@company.com",
        "password": "Password123!",
        "full_name": "Agent User",
        "tenant_name": "Agent Org"
    })
    token = reg.json()["tokens"]["access_token"]
    headers = {"Authorization": f"Bearer {token}"}

    # 2. Mock LLM generate call inside chat
    mock_llm_res = LLMResponse(
        content="Hello! How can I assist you with your enterprise automation today?",
        provider="groq",
        model="llama-3.1-8b-instant",
        tokens_used=12,
        latency_ms=50.0,
    )

    with patch("app.services.llm_gateway.llm_gateway.generate", new_callable=AsyncMock) as mock_gen:
        mock_gen.return_value = mock_llm_res

        chat_req = {"message": "Hi there!"}
        response = await client.post("/api/v1/chat/", headers=headers, json=chat_req)

        assert response.status_code == 200, response.text
        data = response.json()
        assert "response" in data
        assert "session_id" in data
        assert "routing_decision" in data