+-------------------+
|   應(yīng)用接口層       |
|  (API Gateway)    |
+-------------------+
         |
+-------------------+
|   工作流引擎       |
|  (LangGraph Core) |
+-------------------+
         |
+-------------------+
| 功能組件層         |
| - 數(shù)據(jù)采集        |
| - 內(nèi)容生成        |
| - 質(zhì)量審核        |
| - 發(fā)布適配        |
+-------------------+

from langgraph.graph import StateGraph


class ArticleState:
    topics: list
    titles: list
    outlines: dict
    contents: str
    media: dict


workflow = StateGraph(ArticleState)


# 定義狀態(tài)節(jié)點
workflow.add_node("collect", data_collection)
workflow.add_node("generate", content_generation)
workflow.add_node("verify", quality_verification)


# 構(gòu)建條件轉(zhuǎn)移邏輯
workflow.add_conditional_edges(
    "verify",
    lambda s: "generate" if s.need_revision else "publish"
)

class DataCollector:
    def __init__(self):
        self.adapters = {
            'wechat': WeChatAdapter(),
            'zhihu': ZhihuAdapter()
        }


    async def fetch(self, platform):
        return await self.adapters[platform].get_hot_topics()


class WeChatAdapter:
    async def get_hot_topics(self):
        # 實現(xiàn)微信特定數(shù)據(jù)解析邏輯
        return processed_data

title_prompt = """
基于以下熱點話題生成候選標(biāo)題：
{topics}


要求：
- 包含數(shù)字和表情符號
- 長度不超過25字
- 使用疑問句式結(jié)構(gòu)"""

Root
├─ 現(xiàn)狀分析
├─ 核心論點
│   ├─ 數(shù)據(jù)支撐
│   └─ 案例佐證
└─ 結(jié)論展望

class ContentExpander:
    def __init__(self, retriever):
        self.retriever = retriever
        
    def expand(self, outline):
        context = self.retriever.query(outline['keywords'])
        return self._merge_content(outline, context)

def validate_image(text, image):
    inputs = processor(text=text, images=image, return_tensors="pt")
    return model(**inputs).logits_per_image

class CitationGenerator:
    def generate(self, claims):
        return [self._find_source(c) for c in claims]

class ComplianceChecker:
    def check(self, text):
        return all([
            self._sensitive_words_check(text),
            self._copyright_check(text),
            self._platform_rules_check(text)
        ])

class StateManager:
    def save_checkpoint(self, state):
        # 序列化存儲狀態(tài)快照
        pass
        
    def load_checkpoint(self, run_id):
        # 恢復(fù)執(zhí)行狀態(tài)
        pass

ERROR_HANDLERS = {
    'retry': lambda e: logger.warning(f"Retrying: {e}"),
    'fallback': lambda e: switch_alternative_method(),
    'critical': lambda e: abort_workflow()
}

class Component(ABC):
    @abstractmethod
    def execute(self, state):
        pass
        
    @property
    def version(self):
        return "1.0"