import asyncio
import json
import time
import requests
import logging

logging.basicConfig(level=logging.INFO, format="%(asctime)s - [%(levelname)s] - %(message)s")
logger = logging.getLogger("V2AcceptanceVerifier")

BASE_URL = "http://localhost:8000"

def verify_v2_acceptance_suite():
    logger.info("=================================================================")
    logger.info("   12D AI Assessment Engine V2.0 Final Acceptance Verification   ")
    logger.info("=================================================================")

    # 1. 基础服务存活检测
    logger.info("\n[1/4] Checking System V2.0 Health & Prometheus Metrics...")
    r = requests.get(f"{BASE_URL}/health")
    assert r.status_code == 200, f"Health check failed: {r.text}"
    logger.info(f"Health Response: {r.json()}")

    # 2. 模拟加载 Multi-Agent 诊断会商服务 (DSM-5 / ICD-11)
    logger.info("\n[2/4] Testing DSM-5 / ICD-11 Multi-Agent Clinical Consensus...")
    from app.agents.clinical_consensus import ClinicalMultiAgentSystem
    
    class MockVectorStore:
        def search(self, query: str, top_k: int = 3):
            class Doc:
                text = "DSM-5 315.4 (Developmental Coordination Disorder) & ICD-11 6A05."
            return [Doc()]

    agent_system = ClinicalMultiAgentSystem(vector_store_client=MockVectorStore())
    scores = {"Executive_Function": -2.1, "Attention_Control": -1.8, "Visual_Spatial": 0.5}
    report = agent_system.execute_consensus_diagnosis({"age_months": 72}, scores)
    
    assert "primary_diagnostic_impression" in report
    assert len(report["clinical_interventions"]) > 0
    logger.info(f"Generated Clinical Impression: {report['primary_diagnostic_impression']}")
    logger.info(f"Aligned Guidelines: {report['dsm5_icd11_alignment']}")

    # 3. 多模态融合引擎测试
    logger.info("\n[3/4] Verifying Multimodal Fusion Engine (Gaze, AU, Audio)...")
    from app.schemas.multimodal import MultimodalFramePayload, EyeTrackingPoint, MicroExpressionAU
    from app.services.multimodal_fusion import MultimodalFusionEngine
    
    payload = MultimodalFramePayload(
        session_id="v2_test_sess",
        item_id="item_v2_001",
        gaze_stream=[EyeTrackingPoint(x=0.5, y=0.5, pupil_dilation=4.8, timestamp_ms=100)],
        micro_expressions=[MicroExpressionAU(action_unit="AU04", intensity=0.9)],
        audio_metrics=None,
        captured_at="2026-07-29T10:00:00Z"
    )
    cli_score = MultimodalFusionEngine.calculate_cognitive_load(payload)
    logger.info(f"Calculated Cognitive Load Index (CLI): {cli_score}")
    assert cli_score > 0.5

    # 4. 总结
    logger.info("\n[4/4] Final Verification Passed!")
    logger.info("🎉 12D AI Assessment Engine V2.0 GA is READY FOR PRODUCTION DEPLOYMENT!")

if __name__ == "__main__":
    verify_v2_acceptance_suite()