"""多模态内容理解:把帖子的文本 + 图片(+视频) 交给 Gemini,提取真正的创作知识。 走 OpenRouter /chat/completions,模型 google/gemini-3-flash-preview。 消息格式(system + user.content 为 [text, image_url...] 列表)对齐 ContentFindAgentNew 的 gemini_video.GeminiVideoClient,但提示词换成「提取创作知识」,不做相关性审核。 关键:知识常在图片里,不能只读 body_text —— 见 创作知识-重构设计.md。 """ from __future__ import annotations from typing import Any, Callable, Mapping, Optional import httpx from creation_knowledge.config import load_env_file from creation_knowledge.jsonio import extract_json_object, to_bool from creation_knowledge.models import ExtractedContent, Post from creation_knowledge.prompts import load_prompt DEFAULT_MODEL = "google/gemini-3-flash-preview" DEFAULT_BASE_URL = "https://openrouter.ai/api/v1" DEFAULT_TIMEOUT = 90.0 MAX_IMAGES = 6 _SYSTEM_PROMPT = ( "你是创作知识提取助手。从给定的小红书帖子(标题、正文、图片、视频)中," "提取真正能指导『如何创作内容』的知识;知识常在图片/视频里而非正文。" "忠实提取、不编造。只输出一个 JSON 对象,不要解释或 markdown。" ) class ExtractorError(RuntimeError): pass class GeminiExtractor: def __init__( self, *, api_key: str, model: str = DEFAULT_MODEL, base_url: str = DEFAULT_BASE_URL, timeout_seconds: float = DEFAULT_TIMEOUT, http_post: Callable[..., Any] = httpx.post, max_images: int = MAX_IMAGES, ) -> None: if not api_key: raise ExtractorError("missing OPENROUTER_API_KEY") self.api_key = api_key self.model = model self.base_url = base_url.rstrip("/") self.timeout_seconds = timeout_seconds self.http_post = http_post self.max_images = max_images @classmethod def from_env(cls, env: Mapping[str, str] | None = None, env_file: str = ".env") -> "GeminiExtractor": source = dict(load_env_file(env_file)) if env: source.update(env) api_key = source.get("OPENROUTER_API_KEY") or source.get("OPEN_ROUTER_API_KEY") or "" return cls( api_key=api_key, model=source.get("CONTENT_AGENT_VIDEO_LLM_MODEL") or DEFAULT_MODEL, base_url=source.get("OPENROUTER_BASE_URL") or DEFAULT_BASE_URL, timeout_seconds=float(source.get("CONTENT_AGENT_VIDEO_LLM_TIMEOUT_SECONDS") or DEFAULT_TIMEOUT), ) def build_messages(self, post: Post) -> list[dict]: user_text = load_prompt("extract").format( title=post.title or "(无)", topics="、".join(post.topic_list) or "(无)", body=post.body_text or "(空)", ) parts: list[dict] = [{"type": "text", "text": user_text}] for url in post.image_urls[: self.max_images]: parts.append({"type": "image_url", "image_url": {"url": url}}) return [ {"role": "system", "content": _SYSTEM_PROMPT}, {"role": "user", "content": parts}, ] def extract(self, post: Post) -> ExtractedContent: messages = self.build_messages(post) last_exc: Optional[Exception] = None for attempt in range(2): try: resp = self.http_post( f"{self.base_url}/chat/completions", headers={ "Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json", }, json={"model": self.model, "messages": messages}, timeout=self.timeout_seconds, ) resp.raise_for_status() content = resp.json()["choices"][0]["message"]["content"] data = extract_json_object(content) return ExtractedContent( text=str(data.get("text") or ""), from_image=str(data.get("from_image") or ""), from_video=str(data.get("from_video") or ""), is_empty=to_bool(data.get("is_empty")), ) except httpx.HTTPError as exc: last_exc = exc if attempt == 0: continue raise ExtractorError(f"gemini_http_error: {exc}") from exc except (KeyError, IndexError, TypeError, ValueError) as exc: last_exc = exc if attempt == 0: continue raise ExtractorError(f"gemini_response_invalid: {exc}") from exc raise ExtractorError(f"gemini_unknown_error: {last_exc}") def extract_content( post: Post, *, client: Optional[GeminiExtractor] = None, env_file: str = ".env", ) -> ExtractedContent: client = client or GeminiExtractor.from_env(env_file=env_file) return client.extract(post)