import pytest
from unittest.mock import patch, MagicMock
from src.api_hook_client import ApiHookClient

@pytest.mark.asyncio
async def test_mma_track_lifecycle_simulation():
 """
 This test simulates the sequence of API calls an external orchestrator
 would make to manage an MMA track lifecycle via the Hook API.
 It verifies that ApiHookClient correctly routes requests to the 
 corresponding endpoints in src/api_hooks.py.
 """
 
 client = ApiHookClient("http://localhost:8999")
 
 with patch('requests.get') as mock_get, patch('requests.post') as mock_post:
  # --- PHASE 1: Initialization & Discovery ---
  
  # Mock successful status check
  mock_get.return_value.status_code = 200
  mock_get.return_value.json.return_value = {"status": "ok"}
  assert client.get_status()["status"] == "ok"
  
  # Mock project state retrieval
  mock_get.return_value.json.return_value = {"project": {"name": "test_project"}}
  project = client.get_project()
  assert project["project"]["name"] == "test_project"
  
  # --- PHASE 2: Track Planning & Initialization ---
  
  # Inject some files into context for the AI to work with
  mock_post.return_value.status_code = 200
  mock_post.return_value.json.return_value = {"status": "queued"}
  inject_data = {"files": ["src/app_controller.py", "tests/test_basic.py"]}
  res = client.inject_context(inject_data)
  assert res["status"] == "queued"
  mock_post.assert_called_with("http://localhost:8999/api/context/inject", json=inject_data, headers={}, timeout=5.0)
  
  # --- PHASE 3: Worker Spawn & Execution ---
  
  # Spawn a worker to start a ticket
  spawn_data = {
   "track_id": "track_20260311",
   "ticket_id": "TKT-001",
   "role": "tier3-worker",
   "prompt": "Implement the new logging feature"
  }
  res = client.spawn_mma_worker(spawn_data)
  assert res["status"] == "queued"
  mock_post.assert_called_with("http://localhost:8999/api/mma/workers/spawn", json=spawn_data, headers={}, timeout=5.0)
  
  # --- PHASE 4: DAG Mutation & Dependency Management ---
  
  # Add a second ticket that depends on the first one
  dag_mutation = {
   "action": "add_ticket",
   "ticket": {
    "id": "TKT-002",
    "deps": ["TKT-001"],
    "role": "tier4-qa",
    "prompt": "Verify the logging feature"
   }
  }
  res = client.mutate_mma_dag(dag_mutation)
  assert res["status"] == "queued"
  mock_post.assert_called_with("http://localhost:8999/api/mma/dag/mutate", json=dag_mutation, headers={}, timeout=5.0)
  
  # --- PHASE 5: Monitoring & Status Polling ---
  
  # Poll for MMA status
  mock_get.return_value.json.return_value = {
   "mma_status": "running",
   "active_tickets": ["TKT-001"],
   "active_tier": "Tier 3",
   "tracks": [{"id": "track_20260311", "status": "active"}]
  }
  mma_status = client.get_mma_status()
  assert mma_status["mma_status"] == "running"
  assert "TKT-001" in mma_status["active_tickets"]
  
  # Check worker stream status
  mock_get.return_value.json.return_value = {
   "workers": {
    "TKT-001": {"status": "running", "output": "Starting work..."}
   }
  }
  workers = client.get_mma_workers()
  assert workers["workers"]["TKT-001"]["status"] == "running"
  
  # --- PHASE 6: Human-in-the-Loop Interaction ---
  
  # Mock a tool approval request
  # In a real scenario, this would block until a POST to /api/ask/respond occurs
  mock_post.return_value.json.return_value = {"status": "ok", "response": True}
  approved = client.request_confirmation("run_powershell", {"script": "ls -Recurse"})
  assert approved is True
  
  # --- PHASE 7: Completion & Cleanup ---
  
  # Mock completion status
  mock_get.return_value.json.return_value = {
   "mma_status": "idle",
   "active_tickets": [],
   "tracks": [{"id": "track_20260311", "status": "completed"}]
  }
  final_status = client.get_mma_status()
  assert final_status["mma_status"] == "idle"
  assert len(final_status["active_tickets"]) == 0
  
  # Reset session to clean up
  client.reset_session()
  # Verify reset click was pushed
  mock_post.assert_called_with("http://localhost:8999/api/gui", json={"action": "click", "item": "btn_reset", "user_data": None}, headers={}, timeout=5.0)

if __name__ == "__main__":
 import asyncio
 asyncio.run(test_mma_track_lifecycle_simulation())