import asyncio
import logging
import os
import sys
from collections.abc import AsyncGenerator
from contextlib import asynccontextmanager

from dotenv import load_dotenv
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

# Load .env BEFORE any module that reads os.environ at import time.
# Without this, GATEWAY_CORS_ORIGINS / AUTH_JWT_SECRET / DEER_FLOW_AUTH_DISABLED
# placed in /workspace/.env are silently ignored when the container is started
# without explicit `-e` flags, leading to ephemeral JWT secrets, missing CORS
# origins, and "Failed to fetch" in the browser.
load_dotenv()

from app.gateway.auth.disabled_mode import is_auth_disabled  # noqa: E402
from app.gateway.auth_middleware import AuthMiddleware
from app.gateway.config import get_gateway_config
from app.gateway.csrf_middleware import CSRFMiddleware
from app.gateway.deps import langgraph_runtime
from app.gateway.routers import (
    agents,
    artifacts,
    assistants_compat,
    auth,
    channels,
    feedback,
    llm_metrics,
    mcp,
    memory,
    models,
    notifications,
    recommended_questions,
    runs,
    scheduled_tasks,
    skills,
    suggestions,
    system_settings,
    tags,
    thread_runs,
    threads,
    uploads,
)
from deerflow.config import app_config as deerflow_app_config
from deerflow.config.app_config import apply_logging_level
from deerflow.runtime.scheduler import ScheduledTaskService, set_scheduled_task_service

AppConfig = deerflow_app_config.AppConfig
get_app_config = deerflow_app_config.get_app_config

# Default logging; lifespan overrides from config.yaml log_level.
logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    datefmt="%Y-%m-%d %H:%M:%S",
)

logger = logging.getLogger(__name__)

# Upper bound (seconds) each lifespan shutdown hook is allowed to run.
# Bounds worker exit time so uvicorn's reload supervisor does not keep
# firing signals into a worker that is stuck waiting for shutdown cleanup.
_SHUTDOWN_HOOK_TIMEOUT_SECONDS = 5.0


async def _ensure_admin_user(app: FastAPI) -> None:
    """Startup hook: handle first boot and migrate orphan threads otherwise.

    After admin creation, migrate orphan threads from the LangGraph
    store (metadata.user_id unset) to the admin account. This is the
    "no-auth → with-auth" upgrade path: users who ran DeerFlow without
    authentication have existing LangGraph thread data that needs an
    owner assigned.
        First boot (no admin exists):
            - Does NOT create any user accounts automatically.
            - The operator must visit ``/setup`` to create the first admin.

    Subsequent boots (admin already exists):
      - Runs the one-time "no-auth → with-auth" orphan thread migration for
        existing LangGraph thread metadata that has no owner_id.

    No SQL persistence migration is needed: the four user_id columns
    (threads_meta, runs, run_events, feedback) only come into existence
    alongside the auth module via create_all, so freshly created tables
    never contain NULL-owner rows.
    """
    from sqlalchemy import select

    from app.gateway.deps import get_local_provider
    from deerflow.persistence.engine import get_session_factory
    from deerflow.persistence.user.model import UserRow

    try:
        provider = get_local_provider()
    except RuntimeError:
        # Auth persistence may not be initialized in some test/boot paths.
        # Skip admin migration work rather than failing gateway startup.
        logger.warning("Auth persistence not ready; skipping admin bootstrap check")
        return

    sf = get_session_factory()
    if sf is None:
        return

    admin_count = await provider.count_admin_users()

    if admin_count == 0:
        logger.info("=" * 60)
        logger.info("  First boot detected — no admin account exists.")
        logger.info("  Visit /setup to complete admin account creation.")
        logger.info("=" * 60)
        return

    # Admin already exists — run orphan thread migration for any
    # LangGraph thread metadata that pre-dates the auth module.
    async with sf() as session:
        stmt = select(UserRow).where(UserRow.system_role == "admin").limit(1)
        row = (await session.execute(stmt)).scalar_one_or_none()

    if row is None:
        return  # Should not happen (admin_count > 0 above), but be safe.

    admin_id = str(row.id)

    # LangGraph store orphan migration — non-fatal.
    # This covers the "no-auth → with-auth" upgrade path for users
    # whose existing LangGraph thread metadata has no user_id set.
    store = getattr(app.state, "store", None)
    if store is not None:
        try:
            migrated = await _migrate_orphaned_threads(store, admin_id)
            if migrated:
                logger.info("Migrated %d orphan LangGraph thread(s) to admin", migrated)
        except Exception:
            logger.exception("LangGraph thread migration failed (non-fatal)")


async def _iter_store_items(store, namespace, *, page_size: int = 500):
    """Paginated async iterator over a LangGraph store namespace.

    Replaces the old hardcoded ``limit=1000`` call with a cursor-style
    loop so that environments with more than one page of orphans do
    not silently lose data. Terminates when a page is empty OR when a
    short page arrives (indicating the last page).
    """
    offset = 0
    while True:
        batch = await store.asearch(namespace, limit=page_size, offset=offset)
        if not batch:
            return
        for item in batch:
            yield item
        if len(batch) < page_size:
            return
        offset += page_size


async def _sync_legacy_skills(app: FastAPI) -> None:
    """Idempotently register existing on-disk ``skills/custom/*`` directories
    in the ``skills`` DB table, owned by the first admin and published=True.

    Without this step, after upgrading to per-user skill ownership the existing
    custom skill folders would not be visible to anyone (the SkillStore
    visibility filter relies on a DB row). Running this once on every boot is
    cheap (folder scan + one ``ensure_legacy`` per name) and idempotent.

    Non-fatal: a failure here MUST NOT block server startup.
    """
    from sqlalchemy import select

    from deerflow.persistence.engine import get_session_factory
    from deerflow.persistence.user.model import UserRow
    from deerflow.skills.storage import get_or_new_skill_storage
    from deerflow.skills.types import SkillCategory

    sf = get_session_factory()
    if sf is None:
        return

    skill_store = getattr(app.state, "skill_store", None)
    if skill_store is None:
        return

    async with sf() as session:
        stmt = select(UserRow).where(UserRow.system_role == "admin").limit(1)
        row = (await session.execute(stmt)).scalar_one_or_none()
    if row is None:
        # No admin yet — leave ownership null; first admin is responsible for
        # claiming via the UI once they exist.
        admin_id: str | None = None
    else:
        admin_id = str(row.id)

    config = getattr(app.state, "config", None)
    storage = get_or_new_skill_storage(app_config=config)
    try:
        skills = storage.load_skills(enabled_only=False)
    except Exception:
        logger.exception("_sync_legacy_skills: could not list on-disk skills")
        return

    inserted = 0
    for skill in skills:
        if skill.category != SkillCategory.CUSTOM:
            continue
        try:
            existing = await skill_store.get_any(skill.name)
            if existing is not None:
                continue
            await skill_store.ensure_legacy(
                {"name": skill.name, "owner_user_id": admin_id, "published": True}
            )
            inserted += 1
        except Exception:
            logger.warning("_sync_legacy_skills: could not register %s", skill.name, exc_info=True)
    if inserted:
        logger.info("Skill ownership migration: registered %d legacy custom skill(s)", inserted)


async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
    """Migrate LangGraph store threads with no user_id to the given admin.

    Uses cursor pagination so all orphans are migrated regardless of
    count. Returns the number of rows migrated.
    """
    migrated = 0
    async for item in _iter_store_items(store, ("threads",)):
        metadata = item.value.get("metadata", {})
        if not metadata.get("user_id"):
            metadata["user_id"] = admin_user_id
            item.value["metadata"] = metadata
            await store.aput(("threads",), item.key, item.value)
            migrated += 1
    return migrated


async def _run_db_migrations() -> None:
    """Run Alembic migrations at startup so schema changes are applied automatically."""
    import asyncio
    from pathlib import Path

    from alembic import command
    from alembic.config import Config

    import deerflow.persistence as _persistence_pkg
    from deerflow.persistence.engine import get_engine

    engine = get_engine()
    if engine is None:
        logger.info("Persistence backend=memory — skipping Alembic migrations")
        return

    db_url = str(engine.url)
    migrations_dir = str(Path(_persistence_pkg.__file__).parent / "migrations")

    def _run_sync() -> None:
        cfg = Config()
        cfg.set_main_option("script_location", migrations_dir)
        cfg.set_main_option("sqlalchemy.url", db_url)
        command.upgrade(cfg, "head")

    try:
        await asyncio.get_running_loop().run_in_executor(None, _run_sync)
        logger.info("Database migrations applied (head)")
    except Exception:
        logger.exception("Database migration failed — schema may be out of date")


# Skill curator 调度参数。
# - 检查间隔:每隔这么久检查一次"需不需要进化";真正是否执行由 should_run_now() 判定。
# - 启动延迟:启动后先等这么久再首次检查,避开启动高峰。
_CURATOR_CHECK_INTERVAL_SECONDS = 3600  # 1 小时
_CURATOR_STARTUP_DELAY_SECONDS = 300  # 5 分钟


def _acquire_singleton_lock(lock_path):
    """跨平台非阻塞独占文件锁,用于多 worker 下的 leader 选举。

    成功 -> 返回持有锁的文件句柄(调用方须保持其存活,直到进程退出/主动释放);
    抢不到锁(已有其它 worker 持有)或打开失败 -> 返回 None。
    进程异常退出时 OS 会自动释放该锁。
    """
    try:
        lock_path.parent.mkdir(parents=True, exist_ok=True)
        handle = open(lock_path, "a+")
    except OSError:
        logger.exception("Curator scheduler: 打开锁文件失败")
        return None
    try:
        if sys.platform == "win32":
            import msvcrt

            handle.seek(0)
            msvcrt.locking(handle.fileno(), msvcrt.LK_NBLCK, 1)
        else:
            import fcntl

            fcntl.flock(handle.fileno(), fcntl.LOCK_EX | fcntl.LOCK_NB)
    except OSError:
        handle.close()
        return None
    return handle


def _release_singleton_lock(handle) -> None:
    """释放并关闭 _acquire_singleton_lock 拿到的锁文件句柄。"""
    try:
        if sys.platform == "win32":
            import msvcrt

            handle.seek(0)
            msvcrt.locking(handle.fileno(), msvcrt.LK_UNLCK, 1)
        else:
            import fcntl

            fcntl.flock(handle.fileno(), fcntl.LOCK_UN)
    except OSError:
        pass
    finally:
        try:
            handle.close()
        except OSError:
            pass


async def _curator_scheduler_loop() -> None:
    """常驻后台任务:每隔 _CURATOR_CHECK_INTERVAL_SECONDS 检查一次需不需要进化。

    多 worker 部署下用文件锁做 leader 选举 —— 只有抢到锁的那个 worker 进程真正
    运行调度,其余 worker 直接退出,避免 curator 被重复触发、重复调用 LLM。
    被 cancel 时 CancelledError 会穿过 ``except Exception``(它是 BaseException
    子类,不会被捕获),协程随之干净退出并在 finally 里释放锁。
    """
    from deerflow.config.runtime_paths import runtime_home
    from deerflow.skills.curator import maybe_run_curator

    lock_handle = _acquire_singleton_lock(runtime_home() / ".curator_scheduler.lock")
    if lock_handle is None:
        logger.info("Curator scheduler: 另一个 worker 已持有调度锁,本 worker 跳过")
        return

    logger.info("Curator scheduler: 取得调度锁,本 worker 负责 curator 调度")
    try:
        # 启动后延迟一会儿再首次检查,避开启动高峰
        await asyncio.sleep(_CURATOR_STARTUP_DELAY_SECONDS)
        while True:
            try:
                await maybe_run_curator()
            except Exception:
                logger.exception("Curator scheduler tick failed (non-fatal)")
            await asyncio.sleep(_CURATOR_CHECK_INTERVAL_SECONDS)
    finally:
        _release_singleton_lock(lock_handle)


@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
    """Application lifespan handler."""

    # Load config and check necessary environment variables at startup
    try:
        app.state.config = get_app_config()
        apply_logging_level(app.state.config.log_level)
        logger.info("Configuration loaded successfully")
    except Exception as e:
        error_msg = f"Failed to load configuration during gateway startup: {e}"
        logger.exception(error_msg)
        raise RuntimeError(error_msg) from e
    config = get_gateway_config()
    logger.info(f"Starting API Gateway on {config.host}:{config.port}")

    # Initialize LangGraph runtime components (StreamBridge, RunManager, checkpointer, store)
    async with langgraph_runtime(app):
        logger.info("LangGraph runtime initialised")

        # Run Alembic migrations before anything else touches the schema.
        await _run_db_migrations()

        # Ensure admin user exists (auto-create on first boot)
        # Must run AFTER langgraph_runtime so app.state.store is available for thread migration
        await _ensure_admin_user(app)

        # Migrate "ownerless" on-disk skills into the new SkillStore table —
        # makes the multitenancy switch transparent for existing deployments.
        try:
            await _sync_legacy_skills(app)
        except Exception:
            logger.exception("Skill ownership migration failed (non-fatal)")

        # 启动 skill curator 调度器:常驻后台任务,每小时检查一次需不需要进化
        # (per-user interval_hours 仍是真正决定要不要跑进化的闸)。
        try:
            app.state.curator_scheduler_task = asyncio.create_task(_curator_scheduler_loop())
        except Exception:
            logger.exception("Skill curator scheduler failed to start (non-fatal)")

        # Start IM channel service if any channels are configured
        try:
            from app.channels.service import start_channel_service

            channel_service = await start_channel_service(app.state.config)
            logger.info("Channel service started: %s", channel_service.get_status())
        except Exception:
            logger.exception("No IM channels configured or channel service failed to start")

        scheduled_tasks_enabled = os.environ.get("SCHEDULED_TASKS_ENABLED", "true").strip().lower()
        if scheduled_tasks_enabled in {"0", "false", "no", "off"}:
            logger.info("Scheduled task service disabled by SCHEDULED_TASKS_ENABLED=%s", scheduled_tasks_enabled)
        else:
            try:
                scheduled_task_store = getattr(app.state, "scheduled_task_store", None)
                if scheduled_task_store is not None:
                    scheduler_service = ScheduledTaskService(app, scheduled_task_store)
                    app.state.scheduled_task_service = scheduler_service
                    set_scheduled_task_service(scheduler_service)
                    await scheduler_service.start()
                    logger.info("Scheduled task service started")
            except Exception:
                logger.exception("Scheduled task service failed to start")

        yield

        # 停止 curator 调度器
        curator_task = getattr(app.state, "curator_scheduler_task", None)
        if curator_task is not None:
            curator_task.cancel()
            try:
                await curator_task
            except asyncio.CancelledError:
                pass
            except Exception:
                logger.exception("Curator scheduler shutdown error")

        try:
            scheduler_service = getattr(app.state, "scheduled_task_service", None)
            if scheduler_service is not None:
                await scheduler_service.stop()
        except Exception:
            logger.exception("Failed to stop scheduled task service")
        finally:
            set_scheduled_task_service(None)

        # Stop channel service on shutdown (bounded to prevent worker hang)
        try:
            from app.channels.service import stop_channel_service

            await asyncio.wait_for(
                stop_channel_service(),
                timeout=_SHUTDOWN_HOOK_TIMEOUT_SECONDS,
            )
        except TimeoutError:
            logger.warning(
                "Channel service shutdown exceeded %.1fs; proceeding with worker exit.",
                _SHUTDOWN_HOOK_TIMEOUT_SECONDS,
            )
        except Exception:
            logger.exception("Failed to stop channel service")

    logger.info("Shutting down API Gateway")


def create_app() -> FastAPI:
    """Create and configure the FastAPI application.

    Returns:
        Configured FastAPI application instance.
    """
    config = get_gateway_config()
    docs_kwargs = {"docs_url": "/docs", "redoc_url": "/redoc", "openapi_url": "/openapi.json"} if config.enable_docs else {"docs_url": None, "redoc_url": None, "openapi_url": None}

    app = FastAPI(
        title="DeerFlow API Gateway",
        description="""
## DeerFlow API Gateway

API Gateway for DeerFlow - A LangGraph-based AI agent backend with sandbox execution capabilities.

### Features

- **Models Management**: Query and retrieve available AI models
- **MCP Configuration**: Manage Model Context Protocol (MCP) server configurations
- **Memory Management**: Access and manage global memory data for personalized conversations
- **Skills Management**: Query and manage skills and their enabled status
- **Artifacts**: Access thread artifacts and generated files
- **Health Monitoring**: System health check endpoints

### Architecture

LangGraph requests are handled by nginx reverse proxy.
This gateway provides custom endpoints for models, MCP configuration, skills, and artifacts.
        """,
        version="0.1.0",
        lifespan=lifespan,
        **docs_kwargs,
        openapi_tags=[
            {
                "name": "models",
                "description": "Operations for querying available AI models and their configurations",
            },
            {
                "name": "mcp",
                "description": "Manage Model Context Protocol (MCP) server configurations",
            },
            {
                "name": "memory",
                "description": "Access and manage global memory data for personalized conversations",
            },
            {
                "name": "skills",
                "description": "Manage skills and their configurations",
            },
            {
                "name": "artifacts",
                "description": "Access and download thread artifacts and generated files",
            },
            {
                "name": "uploads",
                "description": "Upload and manage user files for threads",
            },
            {
                "name": "threads",
                "description": "Manage DeerFlow thread-local filesystem data",
            },
            {
                "name": "agents",
                "description": "Create and manage custom agents with per-agent config and prompts",
            },
            {
                "name": "suggestions",
                "description": "Generate follow-up question suggestions for conversations",
            },
            {
                "name": "channels",
                "description": "Manage IM channel integrations (Feishu, Slack, Telegram)",
            },
            {
                "name": "assistants-compat",
                "description": "LangGraph Platform-compatible assistants API (stub)",
            },
            {
                "name": "runs",
                "description": "LangGraph Platform-compatible runs lifecycle (create, stream, cancel)",
            },
            {
                "name": "scheduled-tasks",
                "description": "Create, manage, and execute user scheduled agent tasks",
            },
            {
                "name": "health",
                "description": "Health check and system status endpoints",
            },
        ],
    )

    # Auth: reject unauthenticated requests to non-public paths (fail-closed safety net)
    app.add_middleware(AuthMiddleware)

    # CSRF: Double Submit Cookie pattern for state-changing requests
    app.add_middleware(CSRFMiddleware)

    # CORS
    if is_auth_disabled():
        logger.warning(
            "DEER_FLOW_AUTH_DISABLED is set — API authentication is bypassed. "
            "Do not use this in production."
        )

    def _cors_allow_any_origin() -> bool:
        """Mirror any browser Origin (works with credentials); cannot use literal '*'."""
        v = os.environ.get("GATEWAY_CORS_ALLOW_ALL", "").strip().lower()
        return v in ("1", "true", "yes", "on") or is_auth_disabled()

    cors_origins_env = os.environ.get("GATEWAY_CORS_ORIGINS", "").strip()
    cors_origins: list[str] = [o.strip() for o in cors_origins_env.split(",") if o.strip()] if cors_origins_env else []

    # Headers the LangGraph SDK / browser clients need to read from cross-origin
    # responses. Without exposing them, the SDK's `response.headers.get(...)` returns
    # null on cross-origin streaming responses, breaking run-id extraction and reconnect.
    cors_expose_headers = [
        "Content-Disposition",
        "Content-Location",
        "Location",
        "X-Run-Id",
        "X-Thread-Id",
    ]

    if _cors_allow_any_origin():
        logger.warning(
            "Permissive CORS enabled — any Origin is echoed back (GATEWAY_CORS_ALLOW_ALL or "
            "DEER_FLOW_AUTH_DISABLED). Do not expose publicly."
        )
        app.add_middleware(
            CORSMiddleware,
            allow_origins=[],
            # fullmatch() on the Origin header; browsers send scheme://host[:port]
            allow_origin_regex=r".+",
            allow_credentials=True,
            allow_methods=["*"],
            allow_headers=["*"],
            expose_headers=cors_expose_headers,
        )
    elif cors_origins:
        if "*" in cors_origins:
            logger.error(
                "GATEWAY_CORS_ORIGINS contains '*' with allow_credentials=True — invalid. "
                "Set GATEWAY_CORS_ALLOW_ALL=1 instead, or list explicit origins."
            )
            cors_origins = [o for o in cors_origins if o != "*"]
        if cors_origins:
            app.add_middleware(
                CORSMiddleware,
                allow_origins=cors_origins,
                allow_credentials=True,
                allow_methods=["*"],
                allow_headers=["*"],
                expose_headers=cors_expose_headers,
            )
    else:
        # Safe-by-default fallback for local frontend development. Without any CORS
        # middleware, browser preflight OPTIONS requests will hit routes directly and
        # fail with 405, which blocks login and all JSON POST APIs.
        dev_origins = [
            "http://localhost:5173",
            "http://127.0.0.1:5173",
        ]
        logger.warning(
            "No CORS configuration found; enabling local dev origins only: %s. "
            "Set GATEWAY_CORS_ORIGINS or GATEWAY_CORS_ALLOW_ALL for deployment.",
            ", ".join(dev_origins),
        )
        app.add_middleware(
            CORSMiddleware,
            allow_origins=dev_origins,
            allow_credentials=True,
            allow_methods=["*"],
            allow_headers=["*"],
            expose_headers=cors_expose_headers,
        )

    # Include routers
    # Models API is mounted at /api/models
    app.include_router(models.router)

    # MCP API is mounted at /api/mcp
    app.include_router(mcp.router)

    # Memory API is mounted at /api/memory
    app.include_router(memory.router)

    # Skills API is mounted at /api/skills
    app.include_router(skills.router)

    # Artifacts API is mounted at /api/threads/{thread_id}/artifacts
    app.include_router(artifacts.router)

    # Uploads API is mounted at /api/threads/{thread_id}/uploads
    app.include_router(uploads.router)

    # Thread cleanup API is mounted at /api/threads/{thread_id}
    app.include_router(threads.router)

    # Agents API is mounted at /api/agents
    app.include_router(agents.router)

    # Recommended Questions API is mounted at /api/recommended-questions
    app.include_router(recommended_questions.router)

    # Suggestions API is mounted at /api/threads/{thread_id}/suggestions
    app.include_router(suggestions.router)

    # Scheduled task API is mounted at /api/scheduled-tasks
    app.include_router(scheduled_tasks.router)

    # System settings API is mounted at /api/system-settings
    app.include_router(system_settings.router)

    # Admin LLM metrics audit + export
    app.include_router(llm_metrics.router)

    # Channels API is mounted at /api/channels
    app.include_router(channels.router)

    # Assistants compatibility API (LangGraph Platform stub)
    app.include_router(assistants_compat.router)

    # Auth API is mounted at /api/v1/auth
    app.include_router(auth.router)

    # Feedback API is mounted at /api/threads/{thread_id}/runs/{run_id}/feedback
    app.include_router(feedback.router)

    # Notifications API is mounted at /api/notifications
    app.include_router(notifications.router)

    # Tags API is mounted at /api/tags
    app.include_router(tags.router)

    # Thread Runs API (LangGraph Platform-compatible runs lifecycle)
    app.include_router(thread_runs.router)

    # Stateless Runs API (stream/wait without a pre-existing thread)
    app.include_router(runs.router)

    @app.get("/health", tags=["health"])
    async def health_check() -> dict:
        """Health check endpoint.

        Returns:
            Service health status information.
        """
        return {"status": "healthy", "service": "deer-flow-gateway"}

    return app


# Create app instance for uvicorn
app = create_app()