import asyncio
import time
from collections.abc import Callable, Iterator
from typing import Any
from urllib.parse import urlsplit
from uuid import uuid4

import httpx
import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
from sqlalchemy import delete, select

from ai_platform.bootstrap.app import create_app
from ai_platform.infrastructure.config.settings import Settings
from ai_platform.infrastructure.persistence.database import make_session_factory
from ai_platform.infrastructure.persistence.models import AIProfile, ScoringRun, TenantKey
from ai_platform.infrastructure.security import digest


@pytest.fixture
def valid_run_payload():
    return {
        "request_id": "f81c7c4e-a92a-4b19-8d7a-3a5c08eb4e6e",
        "subject_ref": "lead-1",
        "snapshot": {
            "version": "1.0.0",
            "scope": "linked_contact_history",
            "captured_at": "2026-01-01T12:00:00Z",
            "lead_profile": {
                "ems_lead_id": "lead-1",
                "name": "A. Example",
                "custom_fields": {"region": "north"},
            },
            "conversations": [
                {
                    "conversation_id": "conversation-2",
                    "channel": "webchat",
                    "assigned_agent_id": "agent-1",
                    "messages": [
                        {
                            "message_id": "message-2",
                            "sender_type": "agent",
                            "content": "Thanks for contacting us.",
                            "sent_at": "2025-12-31T11:00:00+00:00",
                        },
                        {
                            "message_id": "message-1",
                            "sender_type": "contact",
                            "content": "I am interested.",
                            "sent_at": "2025-12-31T10:00:00+00:00",
                        },
                    ],
                }
            ],
            "identity_context": {
                "match_quality": "phone_only",
                "contact_id": "contact-1",
                "details": {"source": "phone"},
            },
            "trigger_metadata": {
                "trigger_type": "manual_omni",
                "trigger_conversation_id": "conversation-2",
                "actor_id": "user-1",
            },
        },
        "scoring_config": {
            "version": "omni-v1",
            "rules": [
                {
                    "id": "region",
                    "field": "custom_fields.region",
                    "operator": "eq",
                    "value": "north",
                    "points": 25,
                }
            ],
            "rule_weight": 1,
            "ai_weight": 0,
        },
        "ai_profile": "light",
    }


@pytest.fixture
def aihub_test_environment() -> Iterator[dict[str, Any]]:
    loaded = Settings.load()
    database_name = urlsplit(loaded.database_url).path.rstrip("/").rsplit("/", 1)[-1]
    if database_name != "ai_platform_test":
        raise RuntimeError("AIHub scoring integration tests require /ai_platform_test")
    settings = Settings(
        database_url=loaded.database_url,
        environment="development",
        tenant_provisioning_secret=loaded.tenant_provisioning_secret,
        aihub_base_url="http://localhost:8080",
    )
    factory = make_session_factory(settings.database_url)
    suffix = uuid4().hex
    tenant_id = f"aihub-test-{suffix}"
    profile_version = f"aihub-test-{suffix}"
    tenant_key = "test-only-tenant-key"
    vkey = "test-only-vkey-do-not-leak"
    original_active: set[str] = set()

    async def setup() -> None:
        nonlocal original_active
        async with factory() as db:
            profiles = (await db.scalars(select(AIProfile))).all()
            original_active = {profile.version for profile in profiles if profile.active}
            for profile in profiles:
                profile.active = False
            db.add(
                AIProfile(
                    version=profile_version,
                    model="openai/gpt-4o-mini",
                    system_prompt="Dùng tiếng Việt. Chỉ phân tích dữ liệu được cung cấp.",
                    timeout_seconds=4,
                    limits={},
                    active=True,
                )
            )
            db.add(TenantKey(tenant_id=tenant_id, verifier=digest(tenant_key)))
            await db.commit()
        await factory.kw["bind"].dispose()

    async def cleanup() -> None:
        async with factory() as db:
            await db.execute(delete(ScoringRun).where(ScoringRun.tenant_id == tenant_id))
            await db.execute(delete(TenantKey).where(TenantKey.tenant_id == tenant_id))
            await db.execute(delete(AIProfile).where(AIProfile.version == profile_version))
            profiles = (await db.scalars(select(AIProfile))).all()
            for profile in profiles:
                profile.active = profile.version in original_active
            await db.commit()
        await factory.kw["bind"].dispose()

    asyncio.run(setup())

    def app_for(handler: Callable[[httpx.Request], httpx.Response]) -> FastAPI:
        return create_app(settings, aihub_transport=httpx.MockTransport(handler))

    try:
        yield {
            "app_for": app_for,
            "factory": factory,
            "profile_version": profile_version,
            "tenant_id": tenant_id,
            "tenant_key": tenant_key,
            "vkey": vkey,
        }
    finally:
        asyncio.run(cleanup())


def _wait_for_terminal(client: TestClient, run_id: str, headers: dict[str, str]) -> dict:
    for _ in range(100):
        response = client.get(f"/v1/lead-scoring/runs/{run_id}", headers=headers)
        assert response.status_code == 200
        result = response.json()
        if result["status"] in {"completed", "failed"}:
            return result
        time.sleep(0.02)
    pytest.fail("Scoring run did not reach a terminal state")


@pytest.fixture
def wait_for_terminal():
    return _wait_for_terminal