#  Copyright 2026 zhaoxi826
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.

from kilostar.utils.ray_hook import ray_actor_hook
from fastapi import APIRouter, Request, HTTPException, Depends
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
from ulid import ULID
import asyncio
from kilostar.utils.access import Accessor, TokenData, RoleChecker
from kilostar.core.postgres_database.model import UserAuthority

workflow_router = APIRouter(prefix="/api/v1/workflow", tags=["workflow"])


class CreateWorkflowRequest(BaseModel):
    title: str
    command: str


@workflow_router.post("")
async def create_workflow(
    request: CreateWorkflowRequest,
    token_data: TokenData = Depends(Accessor.get_current_user),
):
    postgres_database = ray_actor_hook("postgres_database").postgres_database
    trace_id = str(ULID())
    await postgres_database.create_workflow.remote(
        trace_id=trace_id,
        user_id=token_data.user_id,
        title=request.title,
        command=request.command,
    )

    global_workflow_manager = ray_actor_hook(
        "global_workflow_manager"
    ).global_workflow_manager
    await global_workflow_manager.create_trace.remote(trace_id)

    consciousness_node = ray_actor_hook("consciousness_node").consciousness_node
    consciousness_node.start_workflow_design.remote(trace_id, request.command)

    return {"trace_id": trace_id, "status": "creating"}


@workflow_router.get("/list")
async def get_workflow_list(
        token_data: TokenData = Depends(RoleChecker(allowed_roles=UserAuthority.USER))):
    postgres_database = ray_actor_hook("postgres_database").postgres_database
    workflows = await postgres_database.list_workflows.remote(
        user_id=token_data.user_id
    )
    return {"workflows": workflows}


@workflow_router.get("/sse/{trace_id}")
async def get_workflow_sse(
    trace_id: str,
    request: Request,
    token_data: TokenData = Depends(Accessor.get_current_user),
):
    """SSE 事件流。

    鉴权走标准 ``Authorization: Bearer`` 头（前端用 fetch-based SSE，
    token 不进 URL）。校验该 trace_id 属于当前用户。
    """
    postgres_database = ray_actor_hook("postgres_database").postgres_database
    wf = await postgres_database.get_workflow.remote(trace_id)
    if not wf:
        raise HTTPException(status_code=404, detail="Workflow not found")
    if getattr(wf, "user_id", None) != token_data.user_id:
        raise HTTPException(status_code=403, detail="Forbidden")

    global_workflow_manager = ray_actor_hook(
        "global_workflow_manager"
    ).global_workflow_manager

    async def event_generator():
        try:
            while True:
                if await request.is_disconnected():
                    break
                message = await global_workflow_manager.get_pending.remote(trace_id)
                if message:
                    yield f"data: {message}\n\n"
                else:
                    await asyncio.sleep(0.5)
        except asyncio.CancelledError:
            pass

    return StreamingResponse(event_generator(), media_type="text/event-stream")


@workflow_router.post("/reply/{trace_id}")
async def post_workflow_reply(
    trace_id: str,
    request: Request,
    token_data: TokenData = Depends(Accessor.get_current_user),
):
    postgres_database = ray_actor_hook("postgres_database").postgres_database
    wf = await postgres_database.get_workflow.remote(trace_id)
    if not wf:
        raise HTTPException(status_code=404, detail="Workflow not found")
    if getattr(wf, "user_id", None) != token_data.user_id:
        raise HTTPException(status_code=403, detail="Forbidden")

    data = await request.json()
    reply_msg = data.get("message", "")
    global_workflow_manager = ray_actor_hook(
        "global_workflow_manager"
    ).global_workflow_manager
    await global_workflow_manager.put_received.remote(trace_id, reply_msg)
    return {"status": "ok"}


@workflow_router.get("/{trace_id}")
async def get_workflow_detail(
    trace_id: str, token_data: TokenData = Depends(Accessor.get_current_user)
):
    postgres_database = ray_actor_hook("postgres_database").postgres_database
    wf = await postgres_database.get_workflow.remote(trace_id)
    if not wf:
        raise HTTPException(status_code=404, detail="Workflow not found")
    if getattr(wf, "user_id", None) != token_data.user_id:
        raise HTTPException(status_code=403, detail="Forbidden")

    context = await postgres_database.get_workflow_context.remote(trace_id)

    work_link = (
        context.work_link if context and hasattr(context, "work_link") else []
    )
    workflow_log = (
        context.workflow_log if context and hasattr(context, "workflow_log") else []
    )
    workflow_pointer = (
        context.workflow_pointer
        if context and getattr(context, "workflow_pointer", None) is not None
        else 0
    )

    steps = _merge_runtime_status(work_link, workflow_log)

    return {
        "trace_id": trace_id,
        "title": wf.title,
        "status": wf.status,
        "command": wf.command,
        "steps": steps,
        "current_step": workflow_pointer,
        "context_blackboard": context.blackboard if context else {},
    }


def _merge_runtime_status(work_link: list, workflow_log: list) -> list:
    """把运行期状态从 ``workflow_log`` 反推并 merge 到每个静态 step 上。

    ``work_link`` 是 step 的**静态定义**（名字 / node 类型 / action），不含运行期
    状态；运行期状态散落在 ``workflow_log`` 里——其结构为::

        [{"<step_index>": [timestamp, status, message]}, ...]

    同一 step 可能出现多条（working → completed），取**最后一条**的 status 作为
    该 step 当前状态。没有日志记录的 step 视为 ``pending``。

    前端 ``WorkflowDiagram`` 依赖每个 step 的 ``status`` 字段着色，这个拼装让
    后端真正把运行期状态喂过去。
    """
    latest_status: dict[int, str] = {}
    latest_output: dict[int, str] = {}
    for entry in workflow_log or []:
        if not isinstance(entry, dict):
            continue
        for key, payload in entry.items():
            try:
                idx = int(key)
            except (ValueError, TypeError):
                continue
            if isinstance(payload, (list, tuple)) and len(payload) >= 2:
                latest_status[idx] = payload[1]
            if isinstance(payload, (list, tuple)) and len(payload) >= 3:
                latest_output[idx] = payload[2]

    merged = []
    for i, step in enumerate(work_link or []):
        step_copy = dict(step) if isinstance(step, dict) else {}
        step_idx = step_copy.get("step")
        lookup_idx = (step_idx - 1) if isinstance(step_idx, int) else i
        step_copy["status"] = latest_status.get(lookup_idx, "pending")
        step_copy["output"] = latest_output.get(lookup_idx, "")
        merged.append(step_copy)
    return merged


@workflow_router.post("/{trace_id}/resume")
async def resume_workflow(
    trace_id: str,
    token_data: TokenData = Depends(Accessor.get_current_user),
):
    """从 ``workflow_graph_state`` 持久化恢复一个被中断/挂起的工作流。

    新 fire 一个 ray task，task 入口的 ``hydrate`` 检查会自动走 resume 路径
    把剩余节点跑完。
    """
    postgres_database = ray_actor_hook("postgres_database").postgres_database
    wf = await postgres_database.get_workflow.remote(trace_id)
    if not wf:
        raise HTTPException(status_code=404, detail="Workflow not found")
    if getattr(wf, "user_id", None) != token_data.user_id:
        raise HTTPException(status_code=403, detail="Forbidden")

    record = await postgres_database.get_workflow_graph_state.remote(trace_id)
    if record is None:
        raise HTTPException(
            status_code=409, detail="该工作流没有可恢复的图持久化记录"
        )

    global_workflow_manager = ray_actor_hook(
        "global_workflow_manager"
    ).global_workflow_manager
    await global_workflow_manager.create_trace.remote(trace_id)

    from kilostar.core.work.workflow.workflow_engine import run_workflow_task

    # resume_only=True：task 入口 hydrate 失败会 fail-fast，绝不 fall through
    # 到"全新模式空跑"。workflow_data 在 resume 路径上不会被使用，传空 dict 占位。
    run_workflow_task.remote({}, trace_id, resume_only=True)
    return {"trace_id": trace_id, "status": "resuming"}


@workflow_router.get("/{trace_id}/graph")
async def get_workflow_graph_mermaid(
    trace_id: str,
    token_data: TokenData = Depends(Accessor.get_current_user),
):
    """返回当前 workflow 引擎的 mermaid 图源码（节点拓扑）。

    拓扑本身对所有 trace 是同一份；但如果该 trace 已经有 ``workflow_graph_state``
    持久化记录，会读出 history 里"已经成功跑过的节点"作为 ``highlighted_nodes``
    传给 mermaid，前端拿到的 mermaid 源码会自带 visited 节点高亮。
    """
    from kilostar.core.work.workflow.workflow_engine import workflow_graph

    postgres_database = ray_actor_hook("postgres_database").postgres_database
    wf = await postgres_database.get_workflow.remote(trace_id)
    if not wf:
        raise HTTPException(status_code=404, detail="Workflow not found")
    if getattr(wf, "user_id", None) != token_data.user_id:
        raise HTTPException(status_code=403, detail="Forbidden")

    visited: list[str] = []
    record = await postgres_database.get_workflow_graph_state.remote(trace_id)
    if record is not None:
        history = getattr(record, "history", None) or []
        # history 里每条 NodeSnapshot.id 形如 "ClassName:hash"，截前缀作为 NodeIdent
        # 只取 status == "success" 的节点（避免 "created" / "running" 带噪声）
        seen: set[str] = set()
        for entry in history:
            if not isinstance(entry, dict):
                continue
            if entry.get("kind") != "node":
                continue
            if entry.get("status") != "success":
                continue
            sid = entry.get("id") or ""
            cls_name = sid.split(":", 1)[0] if sid else ""
            if cls_name and cls_name not in seen:
                seen.add(cls_name)
                visited.append(cls_name)

    try:
        if visited:
            mermaid = workflow_graph.mermaid_code(highlighted_nodes=visited)
        else:
            mermaid = workflow_graph.mermaid_code()
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"mermaid 生成失败: {e}")
    return {"trace_id": trace_id, "mermaid": mermaid, "visited": visited}