mirror of
https://github.com/jxxghp/MoviePilot.git
synced 2026-09-04 23:17:20 +08:00
add MoviePilot AI agent implementation and workflow manager
This commit is contained in:
jxxghp
@@ -0,0 +1,106 @@
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from abc import ABC, abstractmethod
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from typing import Union
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from app.chain import ChainBase
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from app.db.systemconfig_oper import SystemConfigOper
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from app.schemas import ActionContext, ActionParams
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class ActionChain(ChainBase):
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pass
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class BaseAction(ABC):
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"""
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工作流动作基类
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"""
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# 动作ID
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_action_id = None
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# 完成标志
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_done_flag = False
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# 执行信息
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_message = ""
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# 缓存键值
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_cache_key = "WorkflowCache-%s"
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def __init__(self, action_id: str):
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self._action_id = action_id
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self.systemconfigoper = SystemConfigOper()
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@classmethod
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@property
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@abstractmethod
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def name(cls) -> str: # noqa
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pass
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@classmethod
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@property
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@abstractmethod
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def description(cls) -> str: # noqa
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pass
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@classmethod
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@property
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@abstractmethod
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def data(cls) -> dict: # noqa
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pass
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@property
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def done(self) -> bool:
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"""
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判断动作是否完成
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"""
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return self._done_flag
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@property
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@abstractmethod
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def success(self) -> bool:
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"""
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判断动作是否成功
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"""
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pass
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@property
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def message(self) -> str:
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"""
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执行信息
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"""
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return self._message
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def job_done(self, message: str = None):
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"""
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标记动作完成
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"""
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self._message = message
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self._done_flag = True
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def check_cache(self, workflow_id: int, key: str) -> bool:
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"""
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检查是否处理过
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"""
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workflow_key = self._cache_key % workflow_id
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workflow_cache = self.systemconfigoper.get(workflow_key) or {}
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action_cache = workflow_cache.get(self._action_id) or []
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return key in action_cache
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def save_cache(self, workflow_id: int, data: Union[list, str]):
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"""
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保存缓存
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"""
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workflow_key = self._cache_key % workflow_id
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workflow_cache = self.systemconfigoper.get(workflow_key) or {}
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action_cache = workflow_cache.get(self._action_id) or []
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if isinstance(data, list):
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action_cache.extend(data)
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else:
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action_cache.append(data)
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workflow_cache[self._action_id] = action_cache
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self.systemconfigoper.set(workflow_key, workflow_cache)
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@abstractmethod
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def execute(self, workflow_id: int, params: ActionParams, context: ActionContext) -> ActionContext:
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"""
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执行动作
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"""
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raise NotImplementedError
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@@ -0,0 +1,116 @@
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from typing import Optional
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from pydantic import Field
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from app.workflow.actions import BaseAction
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from app.chain.download import DownloadChain
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from app.chain.media import MediaChain
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from app.core.config import global_vars
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from app.core.metainfo import MetaInfo
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from app.log import logger
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from app.schemas import ActionParams, ActionContext, DownloadTask, MediaType
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class AddDownloadParams(ActionParams):
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"""
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添加下载资源参数
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"""
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downloader: Optional[str] = Field(default=None, description="下载器")
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save_path: Optional[str] = Field(default=None, description="保存路径")
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labels: Optional[str] = Field(default=None, description="标签（,分隔）")
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only_lack: Optional[bool] = Field(default=False, description="仅下载缺失的资源")
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class AddDownloadAction(BaseAction):
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"""
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添加下载资源
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"""
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def __init__(self, action_id: str):
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super().__init__(action_id)
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self._added_downloads = []
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self._has_error = False
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@classmethod
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@property
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def name(cls) -> str: # noqa
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return "添加下载"
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@classmethod
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@property
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def description(cls) -> str: # noqa
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return "根据资源列表添加下载任务"
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@classmethod
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@property
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def data(cls) -> dict: # noqa
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return AddDownloadParams().dict()
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@property
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def success(self) -> bool:
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return not self._has_error
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def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
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"""
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将上下文中的torrents添加到下载任务中
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"""
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params = AddDownloadParams(**params)
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_started = False
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for t in context.torrents:
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if global_vars.is_workflow_stopped(workflow_id):
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break
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# 检查缓存
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cache_key = f"{t.torrent_info.site}-{t.torrent_info.title}"
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if self.check_cache(workflow_id, cache_key):
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logger.info(f"{t.torrent_info.title} 已添加过下载，跳过")
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continue
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if not t.meta_info:
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t.meta_info = MetaInfo(title=t.torrent_info.title, subtitle=t.torrent_info.description)
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if not t.media_info:
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t.media_info = MediaChain().recognize_media(meta=t.meta_info)
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if not t.media_info:
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self._has_error = True
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logger.warning(f"{t.torrent_info.title} 未识别到媒体信息，无法下载")
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continue
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if params.only_lack:
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exists_info = DownloadChain().media_exists(t.media_info)
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if exists_info:
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if t.media_info.type == MediaType.MOVIE:
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# 电影
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logger.warning(f"{t.torrent_info.title} 媒体库中已存在，跳过")
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continue
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else:
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# 电视剧
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exists_seasons = exists_info.seasons or {}
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if len(t.meta_info.season_list) > 1:
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# 多季不下载
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logger.warning(f"{t.meta_info.title} 有多季，跳过")
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continue
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else:
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exists_episodes = exists_seasons.get(t.meta_info.begin_season)
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if exists_episodes:
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if set(t.meta_info.episode_list).issubset(exists_episodes):
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logger.warning(
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f"{t.meta_info.title} 第 {t.meta_info.begin_season} 季第 {t.meta_info.episode_list} 集已存在，跳过")
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continue
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_started = True
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did = DownloadChain().download_single(context=t,
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downloader=params.downloader,
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save_path=params.save_path,
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label=params.labels)
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if did:
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self._added_downloads.append(did)
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# 保存缓存
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self.save_cache(workflow_id, cache_key)
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if self._added_downloads:
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logger.info(f"已添加 {len(self._added_downloads)} 个下载任务")
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context.downloads.extend(
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[DownloadTask(download_id=did, downloader=params.downloader) for did in self._added_downloads]
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)
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elif _started:
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self._has_error = True
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self.job_done(f"已添加 {len(self._added_downloads)} 个下载任务")
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return context
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@@ -0,0 +1,88 @@
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from app.workflow.actions import BaseAction
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from app.chain.subscribe import SubscribeChain
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from app.core.config import settings, global_vars
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from app.core.context import MediaInfo
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from app.db.subscribe_oper import SubscribeOper
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from app.log import logger
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from app.schemas import ActionParams, ActionContext
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class AddSubscribeParams(ActionParams):
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"""
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添加订阅参数
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"""
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pass
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class AddSubscribeAction(BaseAction):
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"""
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添加订阅
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"""
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def __init__(self, action_id: str):
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super().__init__(action_id)
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self._added_subscribes = []
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self._has_error = False
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@classmethod
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@property
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def name(cls) -> str: # noqa
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return "添加订阅"
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@classmethod
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@property
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def description(cls) -> str: # noqa
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return "根据媒体列表添加订阅"
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@classmethod
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@property
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def data(cls) -> dict: # noqa
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return AddSubscribeParams().dict()
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@property
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def success(self) -> bool:
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return not self._has_error
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def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
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"""
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将medias中的信息添加订阅，如果订阅不存在的话
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"""
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_started = False
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for media in context.medias:
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if global_vars.is_workflow_stopped(workflow_id):
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break
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# 检查缓存
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cache_key = f"{media.type}-{media.title}-{media.year}-{media.season}"
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if self.check_cache(workflow_id, cache_key):
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logger.info(f"{media.title} {media.year} 已添加过订阅，跳过")
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continue
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mediainfo = MediaInfo()
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mediainfo.from_dict(media.dict())
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subscribechain = SubscribeChain()
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if subscribechain.exists(mediainfo):
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logger.info(f"{media.title} 已存在订阅")
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continue
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# 添加订阅
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_started = True
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sid, message = subscribechain.add(mtype=mediainfo.type,
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title=mediainfo.title,
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year=mediainfo.year,
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tmdbid=mediainfo.tmdb_id,
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season=mediainfo.season,
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doubanid=mediainfo.douban_id,
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bangumiid=mediainfo.bangumi_id,
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username=settings.SUPERUSER)
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if sid:
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self._added_subscribes.append(sid)
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# 保存缓存
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self.save_cache(workflow_id, cache_key)
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if self._added_subscribes:
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logger.info(f"已添加 {len(self._added_subscribes)} 个订阅")
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for sid in self._added_subscribes:
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context.subscribes.append(SubscribeOper().get(sid))
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elif _started:
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self._has_error = True
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self.job_done(f"已添加 {len(self._added_subscribes)} 个订阅")
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return context
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@@ -0,0 +1,65 @@
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from app.workflow.actions import BaseAction, ActionChain
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from app.core.config import global_vars
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from app.schemas import ActionParams, ActionContext
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from app.log import logger
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class FetchDownloadsParams(ActionParams):
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"""
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获取下载任务参数
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"""
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pass
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class FetchDownloadsAction(BaseAction):
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"""
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获取下载任务
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"""
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def __init__(self, action_id: str):
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super().__init__(action_id)
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self._downloads = []
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@classmethod
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@property
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def name(cls) -> str: # noqa
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return "获取下载任务"
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@classmethod
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@property
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def description(cls) -> str: # noqa
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return "获取下载队列中的任务状态"
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@classmethod
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@property
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def data(cls) -> dict: # noqa
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return FetchDownloadsParams().dict()
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@property
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def success(self) -> bool:
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return self.done
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def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
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"""
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更新downloads中的下载任务状态
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"""
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__all_complete = False
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for download in self._downloads:
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if global_vars.is_workflow_stopped(workflow_id):
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break
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logger.info(f"获取下载任务 {download.download_id} 状态 ...")
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torrents = ActionChain().list_torrents(hashs=[download.download_id])
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if not torrents:
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download.completed = True
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continue
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for t in torrents:
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download.path = t.path
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if t.progress >= 100:
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logger.info(f"下载任务 {download.download_id} 已完成")
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download.completed = True
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else:
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logger.info(f"下载任务 {download.download_id} 未完成")
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download.completed = False
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if all([d.completed for d in self._downloads]):
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self.job_done()
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return context
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@@ -0,0 +1,186 @@
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from typing import List, Optional
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from pydantic import Field
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from app.workflow.actions import BaseAction
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from app.chain.recommend import RecommendChain
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from app.schemas import ActionParams, ActionContext
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from app.core.config import settings, global_vars
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from app.core.event import eventmanager
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from app.log import logger
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from app.schemas import RecommendSourceEventData, MediaInfo
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from app.schemas.types import ChainEventType
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from app.utils.http import RequestUtils
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class FetchMediasParams(ActionParams):
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"""
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获取媒体数据参数
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"""
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source_type: Optional[str] = Field(default="ranking", description="来源")
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sources: Optional[List[str]] = Field(default=[], description="榜单")
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api_path: Optional[str] = Field(default=None, description="API路径")
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||||
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||||
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class FetchMediasAction(BaseAction):
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"""
|
||||
获取媒体数据
|
||||
"""
|
||||
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def __init__(self, action_id: str):
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super().__init__(action_id)
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||||
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self._medias = []
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||||
self._has_error = False
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self.__inner_sources = [
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{
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"func": RecommendChain().tmdb_trending,
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"name": '流行趋势',
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"api_path": "recommend/tmdb_trending"
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},
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{
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"func": RecommendChain().douban_movie_showing,
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"name": '正在热映',
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"api_path": "recommend/douban_showing"
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||||
},
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||||
{
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"func": RecommendChain().bangumi_calendar,
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||||
"name": 'Bangumi每日放送',
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||||
"api_path": "recommend/bangumi_calendar"
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||||
},
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||||
{
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"func": RecommendChain().tmdb_movies,
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"name": 'TMDB热门电影',
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||||
"api_path": "recommend/tmdb_movies"
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},
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||||
{
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||||
"func": RecommendChain().tmdb_tvs,
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"name": 'TMDB热门电视剧',
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||||
"api_path": "recommend/tmdb_tvs?with_original_language=zh|en|ja|ko"
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||||
},
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||||
{
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||||
"func": RecommendChain().douban_movie_hot,
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"name": '豆瓣热门电影',
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"api_path": "recommend/douban_movie_hot"
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||||
},
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||||
{
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||||
"func": RecommendChain().douban_tv_hot,
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||||
"name": '豆瓣热门电视剧',
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||||
"api_path": "recommend/douban_tv_hot"
|
||||
},
|
||||
{
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||||
"func": RecommendChain().douban_tv_animation,
|
||||
"name": '豆瓣热门动漫',
|
||||
"api_path": "recommend/douban_tv_animation"
|
||||
},
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||||
{
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||||
"func": RecommendChain().douban_movies,
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||||
"name": '豆瓣最新电影',
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||||
"api_path": "recommend/douban_movies"
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||||
},
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||||
{
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"func": RecommendChain().douban_tvs,
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"name": '豆瓣最新电视剧',
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||||
"api_path": "recommend/douban_tvs"
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||||
},
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||||
{
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||||
"func": RecommendChain().douban_movie_top250,
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||||
"name": '豆瓣电影TOP250',
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||||
"api_path": "recommend/douban_movie_top250"
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||||
},
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||||
{
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||||
"func": RecommendChain().douban_tv_weekly_chinese,
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||||
"name": '豆瓣国产剧集榜',
|
||||
"api_path": "recommend/douban_tv_weekly_chinese"
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||||
},
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||||
{
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||||
"func": RecommendChain().douban_tv_weekly_global,
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||||
"name": '豆瓣全球剧集榜',
|
||||
"api_path": "recommend/douban_tv_weekly_global"
|
||||
}
|
||||
]
|
||||
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||||
# 广播事件，请示额外的推荐数据源支持
|
||||
event_data = RecommendSourceEventData()
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||||
event = eventmanager.send_event(ChainEventType.RecommendSource, event_data)
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||||
# 使用事件返回的上下文数据
|
||||
if event and event.event_data:
|
||||
event_data: RecommendSourceEventData = event.event_data
|
||||
if event_data.extra_sources:
|
||||
self.__inner_sources.extend([s.dict() for s in event_data.extra_sources])
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "获取媒体数据"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "获取榜单等媒体数据列表"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return FetchMediasParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return not self._has_error
|
||||
|
||||
def __get_source(self, source: str):
|
||||
"""
|
||||
获取数据源
|
||||
"""
|
||||
for s in self.__inner_sources:
|
||||
if s['api_path'] == source:
|
||||
return s
|
||||
return None
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
获取媒体数据，填充到medias
|
||||
"""
|
||||
params = FetchMediasParams(**params)
|
||||
try:
|
||||
if params.source_type == "ranking":
|
||||
for api_path in params.sources:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
source = self.__get_source(api_path)
|
||||
if not source:
|
||||
continue
|
||||
logger.info(f"获取媒体数据 {source} ...")
|
||||
name = source.get("name")
|
||||
results = []
|
||||
if source.get("func"):
|
||||
results = source['func']()
|
||||
else:
|
||||
# 调用内部API获取数据
|
||||
api_url = f"http://127.0.0.1:{settings.PORT}/api/v1/{source['api_path']}?token={settings.API_TOKEN}"
|
||||
res = RequestUtils(timeout=15).post_res(api_url)
|
||||
if res:
|
||||
results = res.json()
|
||||
if results:
|
||||
logger.info(f"{name} 获取到 {len(results)} 条数据")
|
||||
self._medias.extend([MediaInfo(**r) for r in results])
|
||||
else:
|
||||
logger.error(f"{name} 获取数据失败")
|
||||
else:
|
||||
# 调用内部API获取数据
|
||||
api_url = f"http://127.0.0.1:{settings.PORT}{params.api_path}?token={settings.API_TOKEN}"
|
||||
res = RequestUtils(timeout=15).post_res(api_url)
|
||||
if res:
|
||||
results = res.json()
|
||||
if results:
|
||||
logger.info(f"{params.api_path} 获取到 {len(results)} 条数据")
|
||||
self._medias.extend([MediaInfo(**r) for r in results])
|
||||
except Exception as e:
|
||||
logger.error(f"获取媒体数据失败: {e}")
|
||||
self._has_error = True
|
||||
|
||||
if self._medias:
|
||||
context.medias.extend(self._medias)
|
||||
|
||||
self.job_done(f"获取到 {len(self._medias)} 条媒数据")
|
||||
return context
|
||||
@@ -0,0 +1,112 @@
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction, ActionChain
|
||||
from app.core.config import settings, global_vars
|
||||
from app.core.context import Context
|
||||
from app.core.metainfo import MetaInfo
|
||||
from app.helper.rss import RssHelper
|
||||
from app.log import logger
|
||||
from app.schemas import ActionParams, ActionContext, TorrentInfo
|
||||
|
||||
|
||||
class FetchRssParams(ActionParams):
|
||||
"""
|
||||
获取RSS资源列表参数
|
||||
"""
|
||||
url: str = Field(default=None, description="RSS地址")
|
||||
proxy: Optional[bool] = Field(default=False, description="是否使用代理")
|
||||
timeout: Optional[int] = Field(default=15, description="超时时间")
|
||||
content_type: Optional[str] = Field(default=None, description="Content-Type")
|
||||
referer: Optional[str] = Field(default=None, description="Referer")
|
||||
ua: Optional[str] = Field(default=None, description="User-Agent")
|
||||
match_media: Optional[str] = Field(default=None, description="匹配媒体信息")
|
||||
|
||||
|
||||
class FetchRssAction(BaseAction):
|
||||
"""
|
||||
获取RSS资源列表
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._rss_torrents = []
|
||||
self._has_error = False
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "获取RSS资源"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "订阅RSS地址获取资源"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return FetchRssParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return not self._has_error
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
请求RSS地址获取数据，并解析为资源列表
|
||||
"""
|
||||
params = FetchRssParams(**params)
|
||||
if not params.url:
|
||||
return context
|
||||
|
||||
headers = {}
|
||||
if params.content_type:
|
||||
headers["Content-Type"] = params.content_type
|
||||
if params.referer:
|
||||
headers["Referer"] = params.referer
|
||||
if params.ua:
|
||||
headers["User-Agent"] = params.ua
|
||||
|
||||
rss_items = RssHelper().parse(url=params.url,
|
||||
proxy=settings.PROXY if params.proxy else None,
|
||||
timeout=params.timeout,
|
||||
headers=headers)
|
||||
if rss_items is None or rss_items is False:
|
||||
logger.error(f'RSS地址 {params.url} 请求失败！')
|
||||
self._has_error = True
|
||||
return context
|
||||
|
||||
if not rss_items:
|
||||
logger.error(f'RSS地址 {params.url} 未获取到RSS数据！')
|
||||
return context
|
||||
|
||||
# 组装种子
|
||||
for item in rss_items:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if not item.get("title"):
|
||||
continue
|
||||
torrentinfo = TorrentInfo(
|
||||
title=item.get("title"),
|
||||
enclosure=item.get("enclosure"),
|
||||
page_url=item.get("link"),
|
||||
size=item.get("size"),
|
||||
pubdate=item["pubdate"].strftime("%Y-%m-%d %H:%M:%S") if item.get("pubdate") else None,
|
||||
)
|
||||
meta = MetaInfo(title=torrentinfo.title, subtitle=torrentinfo.description)
|
||||
mediainfo = None
|
||||
if params.match_media:
|
||||
mediainfo = ActionChain().recognize_media(meta)
|
||||
if not mediainfo:
|
||||
logger.warning(f"{torrentinfo.title} 未识别到媒体信息")
|
||||
continue
|
||||
self._rss_torrents.append(Context(meta_info=meta, media_info=mediainfo, torrent_info=torrentinfo))
|
||||
|
||||
if self._rss_torrents:
|
||||
logger.info(f"获取到 {len(self._rss_torrents)} 个RSS资源")
|
||||
context.torrents.extend(self._rss_torrents)
|
||||
|
||||
self.job_done(f"获取到 {len(self._rss_torrents)} 个资源")
|
||||
return context
|
||||
@@ -0,0 +1,102 @@
|
||||
import random
|
||||
import time
|
||||
from typing import Optional, List
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.chain.search import SearchChain
|
||||
from app.core.config import global_vars
|
||||
from app.log import logger
|
||||
from app.schemas import ActionParams, ActionContext, MediaType
|
||||
|
||||
|
||||
class FetchTorrentsParams(ActionParams):
|
||||
"""
|
||||
获取站点资源参数
|
||||
"""
|
||||
search_type: Optional[str] = Field(default="keyword", description="搜索类型")
|
||||
name: Optional[str] = Field(default=None, description="资源名称")
|
||||
year: Optional[str] = Field(default=None, description="年份")
|
||||
type: Optional[str] = Field(default=None, description="资源类型 (电影/电视剧)")
|
||||
season: Optional[int] = Field(default=None, description="季度")
|
||||
sites: Optional[List[int]] = Field(default=[], description="站点列表")
|
||||
match_media: Optional[bool] = Field(default=False, description="匹配媒体信息")
|
||||
|
||||
|
||||
class FetchTorrentsAction(BaseAction):
|
||||
"""
|
||||
搜索站点资源
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._torrents = []
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "搜索站点资源"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "搜索站点种子资源列表"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return FetchTorrentsParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return self.done
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
搜索站点，获取资源列表
|
||||
"""
|
||||
params = FetchTorrentsParams(**params)
|
||||
searchchain = SearchChain()
|
||||
if params.search_type == "keyword":
|
||||
# 按关键字搜索
|
||||
torrents = searchchain.search_by_title(title=params.name, sites=params.sites)
|
||||
for torrent in torrents:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if params.year and torrent.meta_info.year != params.year:
|
||||
continue
|
||||
if params.type and torrent.media_info and torrent.media_info.type != MediaType(params.type):
|
||||
continue
|
||||
if params.season and torrent.meta_info.begin_season != params.season:
|
||||
continue
|
||||
# 识别媒体信息
|
||||
if params.match_media:
|
||||
torrent.media_info = searchchain.recognize_media(torrent.meta_info)
|
||||
if not torrent.media_info:
|
||||
logger.warning(f"{torrent.torrent_info.title} 未识别到媒体信息")
|
||||
continue
|
||||
self._torrents.append(torrent)
|
||||
else:
|
||||
# 搜索媒体列表
|
||||
for media in context.medias:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
torrents = searchchain.search_by_id(tmdbid=media.tmdb_id,
|
||||
doubanid=media.douban_id,
|
||||
mtype=MediaType(media.type),
|
||||
sites=params.sites)
|
||||
for torrent in torrents:
|
||||
self._torrents.append(torrent)
|
||||
|
||||
# 随机休眠 5-30秒
|
||||
sleep_time = random.randint(5, 30)
|
||||
logger.info(f"随机休眠 {sleep_time} 秒 ...")
|
||||
time.sleep(sleep_time)
|
||||
|
||||
if self._torrents:
|
||||
context.torrents.extend(self._torrents)
|
||||
logger.info(f"共搜索到 {len(self._torrents)} 条资源")
|
||||
|
||||
self.job_done(f"搜索到 {len(self._torrents)} 个资源")
|
||||
return context
|
||||
@@ -0,0 +1,69 @@
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.core.config import global_vars
|
||||
from app.log import logger
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
|
||||
|
||||
class FilterMediasParams(ActionParams):
|
||||
"""
|
||||
过滤媒体数据参数
|
||||
"""
|
||||
type: Optional[str] = Field(default=None, description="媒体类型 (电影/电视剧)")
|
||||
vote: Optional[int] = Field(default=0, description="评分")
|
||||
year: Optional[str] = Field(default=None, description="年份")
|
||||
|
||||
|
||||
class FilterMediasAction(BaseAction):
|
||||
"""
|
||||
过滤媒体数据
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._medias = []
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "过滤媒体数据"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "对媒体数据列表进行过滤"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return FilterMediasParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return self.done
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
过滤medias中媒体数据
|
||||
"""
|
||||
params = FilterMediasParams(**params)
|
||||
for media in context.medias:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if params.type and media.type != params.type:
|
||||
continue
|
||||
if params.vote and media.vote_average < params.vote:
|
||||
continue
|
||||
if params.year and media.year != params.year:
|
||||
continue
|
||||
self._medias.append(media)
|
||||
|
||||
logger.info(f"过滤后剩余 {len(self._medias)} 条媒体数据")
|
||||
|
||||
context.medias = self._medias
|
||||
|
||||
self.job_done(f"过滤后剩余 {len(self._medias)} 条媒体数据")
|
||||
return context
|
||||
@@ -0,0 +1,84 @@
|
||||
from typing import Optional, List
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction, ActionChain
|
||||
from app.core.config import global_vars
|
||||
from app.helper.torrent import TorrentHelper
|
||||
from app.log import logger
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
|
||||
|
||||
class FilterTorrentsParams(ActionParams):
|
||||
"""
|
||||
过滤资源数据参数
|
||||
"""
|
||||
rule_groups: Optional[List[str]] = Field(default=[], description="规则组")
|
||||
quality: Optional[str] = Field(default=None, description="资源质量")
|
||||
resolution: Optional[str] = Field(default=None, description="资源分辨率")
|
||||
effect: Optional[str] = Field(default=None, description="特效")
|
||||
include: Optional[str] = Field(default=None, description="包含规则")
|
||||
exclude: Optional[str] = Field(default=None, description="排除规则")
|
||||
size: Optional[str] = Field(default=None, description="资源大小范围（MB）")
|
||||
|
||||
|
||||
class FilterTorrentsAction(BaseAction):
|
||||
"""
|
||||
过滤资源数据
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._torrents = []
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "过滤资源"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "对资源列表数据进行过滤"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return FilterTorrentsParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return self.done
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
过滤torrents中的资源
|
||||
"""
|
||||
params = FilterTorrentsParams(**params)
|
||||
for torrent in context.torrents:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if TorrentHelper().filter_torrent(
|
||||
torrent_info=torrent.torrent_info,
|
||||
filter_params={
|
||||
"quality": params.quality,
|
||||
"resolution": params.resolution,
|
||||
"effect": params.effect,
|
||||
"include": params.include,
|
||||
"exclude": params.exclude,
|
||||
"size": params.size
|
||||
}
|
||||
):
|
||||
if ActionChain().filter_torrents(
|
||||
rule_groups=params.rule_groups,
|
||||
torrent_list=[torrent.torrent_info],
|
||||
mediainfo=torrent.media_info
|
||||
):
|
||||
self._torrents.append(torrent)
|
||||
|
||||
logger.info(f"过滤后剩余 {len(self._torrents)} 个资源")
|
||||
|
||||
context.torrents = self._torrents
|
||||
|
||||
self.job_done(f"过滤后剩余 {len(self._torrents)} 个资源")
|
||||
return context
|
||||
@@ -0,0 +1,70 @@
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.core.plugin import PluginManager
|
||||
from app.log import logger
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
|
||||
|
||||
class InvokePluginParams(ActionParams):
|
||||
"""
|
||||
调用插件动作参数
|
||||
"""
|
||||
plugin_id: str = Field(default=None, description="插件ID")
|
||||
action_id: str = Field(default=None, description="动作ID")
|
||||
action_params: dict = Field(default={}, description="动作参数")
|
||||
|
||||
|
||||
class InvokePluginAction(BaseAction):
|
||||
"""
|
||||
调用插件
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._success = False
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "调用插件"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "调用插件提供的动作"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return InvokePluginParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return self._success
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
执行插件定义的动作
|
||||
"""
|
||||
params = InvokePluginParams(**params)
|
||||
if not params.plugin_id or not params.action_id:
|
||||
return context
|
||||
try:
|
||||
plugin_actions = PluginManager().get_plugin_actions(params.plugin_id)
|
||||
if not plugin_actions:
|
||||
logger.error(f"插件不存在: {params.plugin_id}")
|
||||
return context
|
||||
actions = plugin_actions[0].get("actions", [])
|
||||
action = next((action for action in actions if action.get("action_id") == params.action_id), None)
|
||||
if not action or not action.get("func"):
|
||||
logger.error(f"插件动作不存在: {params.plugin_id} - {params.action_id}")
|
||||
return context
|
||||
# 执行插件动作
|
||||
self._success, context = action["func"](context, **params.action_params)
|
||||
except Exception as e:
|
||||
self._success = False
|
||||
logger.error(f"调用插件动作失败: {e}")
|
||||
return context
|
||||
self.job_done()
|
||||
return context
|
||||
@@ -0,0 +1,30 @@
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.schemas import ActionContext
|
||||
|
||||
|
||||
class NoteAction(BaseAction):
|
||||
"""
|
||||
备注
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "备注"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "给工作流添加备注"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return {}
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return True
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
return context
|
||||
@@ -0,0 +1,77 @@
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.chain.storage import StorageChain
|
||||
from app.core.config import global_vars, settings
|
||||
from app.log import logger
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
|
||||
|
||||
class ScanFileParams(ActionParams):
|
||||
"""
|
||||
整理文件参数
|
||||
"""
|
||||
# 存储
|
||||
storage: Optional[str] = Field(default="local", description="存储")
|
||||
directory: Optional[str] = Field(default=None, description="目录")
|
||||
|
||||
|
||||
class ScanFileAction(BaseAction):
|
||||
"""
|
||||
整理文件
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._fileitems = []
|
||||
self._has_error = False
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "扫描目录"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "扫描目录文件到队列"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return ScanFileParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return not self._has_error
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
扫描目录中的所有文件，记录到fileitems
|
||||
"""
|
||||
params = ScanFileParams(**params)
|
||||
if not params.storage or not params.directory:
|
||||
return context
|
||||
storagechain = StorageChain()
|
||||
fileitem = storagechain.get_file_item(params.storage, Path(params.directory))
|
||||
if not fileitem:
|
||||
logger.error(f"目录不存在: 【{params.storage}】{params.directory}")
|
||||
self._has_error = True
|
||||
return context
|
||||
files = storagechain.list_files(fileitem, recursion=True)
|
||||
for file in files:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if not file.extension or f".{file.extension.lower()}" not in settings.RMT_MEDIAEXT:
|
||||
continue
|
||||
# 添加文件到队列，而不是目录
|
||||
self._fileitems.append(file)
|
||||
|
||||
if self._fileitems:
|
||||
context.fileitems.extend(self._fileitems)
|
||||
|
||||
self.job_done(f"扫描到 {len(self._fileitems)} 个文件")
|
||||
return context
|
||||
@@ -0,0 +1,82 @@
|
||||
from pathlib import Path
|
||||
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.core.config import global_vars
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
from app.chain.media import MediaChain
|
||||
from app.chain.storage import StorageChain
|
||||
from app.core.metainfo import MetaInfoPath
|
||||
from app.log import logger
|
||||
|
||||
|
||||
class ScrapeFileParams(ActionParams):
|
||||
"""
|
||||
刮削文件参数
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
class ScrapeFileAction(BaseAction):
|
||||
"""
|
||||
刮削文件
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._scraped_files = []
|
||||
self._has_error = False
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "刮削文件"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "刮削媒体信息和图片"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return ScrapeFileParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return not self._has_error
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
刮削fileitems中的所有文件
|
||||
"""
|
||||
# 失败次数
|
||||
_failed_count = 0
|
||||
for fileitem in context.fileitems:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if fileitem in self._scraped_files:
|
||||
continue
|
||||
if not StorageChain().exists(fileitem):
|
||||
continue
|
||||
# 检查缓存
|
||||
cache_key = f"{fileitem.path}"
|
||||
if self.check_cache(workflow_id, cache_key):
|
||||
logger.info(f"{fileitem.path} 已刮削过，跳过")
|
||||
continue
|
||||
meta = MetaInfoPath(Path(fileitem.path))
|
||||
mediachain = MediaChain()
|
||||
mediainfo = mediachain.recognize_media(meta)
|
||||
if not mediainfo:
|
||||
_failed_count += 1
|
||||
logger.info(f"{fileitem.path} 未识别到媒体信息，无法刮削")
|
||||
continue
|
||||
mediachain.scrape_metadata(fileitem=fileitem, meta=meta, mediainfo=mediainfo)
|
||||
self._scraped_files.append(fileitem)
|
||||
# 保存缓存
|
||||
self.save_cache(workflow_id, cache_key)
|
||||
|
||||
if not self._scraped_files and _failed_count:
|
||||
self._has_error = True
|
||||
|
||||
self.job_done(f"成功刮削 {len(self._scraped_files)} 个文件，失败 {_failed_count} 个")
|
||||
return context
|
||||
@@ -0,0 +1,48 @@
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.core.event import eventmanager
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
from app.schemas.types import ChainEventType
|
||||
|
||||
|
||||
class SendEventParams(ActionParams):
|
||||
"""
|
||||
发送事件参数
|
||||
"""
|
||||
pass
|
||||
|
||||
|
||||
class SendEventAction(BaseAction):
|
||||
"""
|
||||
发送事件
|
||||
"""
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "发送事件"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "发送任务执行事件"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return SendEventParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return self.done
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
发送工作流事件，以更插件干预工作流执行
|
||||
"""
|
||||
# 触发资源下载事件，更新执行上下文
|
||||
event = eventmanager.send_event(ChainEventType.WorkflowExecution, context)
|
||||
if event and event.event_data:
|
||||
context = event.event_data
|
||||
|
||||
self.job_done()
|
||||
return context
|
||||
@@ -0,0 +1,73 @@
|
||||
from typing import List, Optional, Union
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction, ActionChain
|
||||
from app.schemas import ActionParams, ActionContext, Notification
|
||||
from app.core.config import settings
|
||||
|
||||
|
||||
class SendMessageParams(ActionParams):
|
||||
"""
|
||||
发送消息参数
|
||||
"""
|
||||
client: Optional[List[str]] = Field(default=[], description="消息渠道")
|
||||
userid: Optional[Union[str, int]] = Field(default=None, description="用户ID")
|
||||
|
||||
|
||||
class SendMessageAction(BaseAction):
|
||||
"""
|
||||
发送消息
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "发送消息"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "发送任务执行消息"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return SendMessageParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return self.done
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
发送messages中的消息
|
||||
"""
|
||||
params = SendMessageParams(**params)
|
||||
msg_text = f"当前进度：{context.progress}%"
|
||||
index = 1
|
||||
if context.execute_history:
|
||||
for history in context.execute_history:
|
||||
if not history.message:
|
||||
continue
|
||||
msg_text += f"\n{index}. {history.action}：{history.message}"
|
||||
index += 1
|
||||
# 发送消息
|
||||
if not params.client:
|
||||
params.client = [""]
|
||||
for client in params.client:
|
||||
ActionChain().post_message(
|
||||
Notification(
|
||||
source=client,
|
||||
userid=params.userid,
|
||||
title="【工作流执行结果】",
|
||||
text=msg_text,
|
||||
link=settings.MP_DOMAIN("#/workflow")
|
||||
)
|
||||
)
|
||||
|
||||
self.job_done()
|
||||
return context
|
||||
@@ -0,0 +1,136 @@
|
||||
import copy
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from app.workflow.actions import BaseAction
|
||||
from app.core.config import global_vars
|
||||
from app.db.transferhistory_oper import TransferHistoryOper
|
||||
from app.schemas import ActionParams, ActionContext
|
||||
from app.chain.storage import StorageChain
|
||||
from app.chain.transfer import TransferChain
|
||||
from app.log import logger
|
||||
|
||||
|
||||
class TransferFileParams(ActionParams):
|
||||
"""
|
||||
整理文件参数
|
||||
"""
|
||||
# 来源
|
||||
source: Optional[str] = Field(default="downloads", description="来源")
|
||||
|
||||
|
||||
class TransferFileAction(BaseAction):
|
||||
"""
|
||||
整理文件
|
||||
"""
|
||||
|
||||
def __init__(self, action_id: str):
|
||||
super().__init__(action_id)
|
||||
self._fileitems = []
|
||||
self._has_error = False
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def name(cls) -> str: # noqa
|
||||
return "整理文件"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def description(cls) -> str: # noqa
|
||||
return "整理队列中的文件"
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def data(cls) -> dict: # noqa
|
||||
return TransferFileParams().dict()
|
||||
|
||||
@property
|
||||
def success(self) -> bool:
|
||||
return not self._has_error
|
||||
|
||||
def execute(self, workflow_id: int, params: dict, context: ActionContext) -> ActionContext:
|
||||
"""
|
||||
从 downloads / fileitems 中整理文件，记录到fileitems
|
||||
"""
|
||||
|
||||
def check_continue():
|
||||
"""
|
||||
检查是否继续整理文件
|
||||
"""
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
return False
|
||||
return True
|
||||
|
||||
params = TransferFileParams(**params)
|
||||
# 失败次数
|
||||
_failed_count = 0
|
||||
storagechain = StorageChain()
|
||||
transferchain = TransferChain()
|
||||
transferhis = TransferHistoryOper()
|
||||
if params.source == "downloads":
|
||||
# 从下载任务中整理文件
|
||||
for download in context.downloads:
|
||||
if global_vars.is_workflow_stopped(workflow_id):
|
||||
break
|
||||
if not download.completed:
|
||||
logger.info(f"下载任务 {download.download_id} 未完成")
|
||||
continue
|
||||
# 检查缓存
|
||||
cache_key = f"{download.download_id}"
|
||||
if self.check_cache(workflow_id, cache_key):
|
||||
logger.info(f"{download.path} 已整理过，跳过")
|
||||
continue
|
||||
fileitem = storagechain.get_file_item(storage="local", path=Path(download.path))
|
||||
if not fileitem:
|
||||
logger.info(f"文件 {download.path} 不存在")
|
||||
continue
|
||||
transferd = transferhis.get_by_src(fileitem.path, storage=fileitem.storage)
|
||||
if transferd:
|
||||
# 已经整理过的文件不再整理
|
||||
continue
|
||||
logger.info(f"开始整理文件 {download.path} ...")
|
||||
state, errmsg = transferchain.do_transfer(fileitem, background=False)
|
||||
if not state:
|
||||
_failed_count += 1
|
||||
logger.error(f"整理文件 {download.path} 失败: {errmsg}")
|
||||
continue
|
||||
logger.info(f"整理文件 {download.path} 完成")
|
||||
self._fileitems.append(fileitem)
|
||||
self.save_cache(workflow_id, cache_key)
|
||||
else:
|
||||
# 从 fileitems 中整理文件
|
||||
for fileitem in copy.deepcopy(context.fileitems):
|
||||
if not check_continue():
|
||||
break
|
||||
# 检查缓存
|
||||
cache_key = f"{fileitem.path}"
|
||||
if self.check_cache(workflow_id, cache_key):
|
||||
logger.info(f"{fileitem.path} 已整理过，跳过")
|
||||
continue
|
||||
transferd = transferhis.get_by_src(fileitem.path, storage=fileitem.storage)
|
||||
if transferd:
|
||||
# 已经整理过的文件不再整理
|
||||
continue
|
||||
logger.info(f"开始整理文件 {fileitem.path} ...")
|
||||
state, errmsg = transferchain.do_transfer(fileitem, background=False,
|
||||
continue_callback=check_continue)
|
||||
if not state:
|
||||
_failed_count += 1
|
||||
logger.error(f"整理文件 {fileitem.path} 失败: {errmsg}")
|
||||
continue
|
||||
logger.info(f"整理文件 {fileitem.path} 完成")
|
||||
# 从 fileitems 中移除已整理的文件
|
||||
context.fileitems.remove(fileitem)
|
||||
self._fileitems.append(fileitem)
|
||||
# 记录已整理的文件
|
||||
self.save_cache(workflow_id, cache_key)
|
||||
|
||||
if self._fileitems:
|
||||
context.fileitems.extend(self._fileitems)
|
||||
elif _failed_count:
|
||||
self._has_error = True
|
||||
|
||||
self.job_done(f"整理成功 {len(self._fileitems)} 个文件，失败 {_failed_count} 个")
|
||||
return context
|
||||
Reference in New Issue
Block a user