7f419f4c8b
- 015-017迁移：image_candidate 文案复审/AI视觉分/重生标记 - constants C7素人感约束(反电商摆拍对齐真实笔记)+C3叠字口子 - celery visibility_timeout=2h 防长任务被误判重投重复烧钱(task75教训) - image_scorer 评图分(只筛选+展示,真实信号才进飞轮权重) - storyboard/image_gen/pipeline_io 生图存量 - task_actions/tasks/task_service/flywheel 审核回路+飞轮存量 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
205 lines
9.8 KiB
Python
205 lines
9.8 KiB
Python
"""
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生图通道 — gpt-image-2 主（edits 带产品图） / Gemini 备 + 重试退避
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扒自：worker/src/image.js generateOneImage / requestProviderImage / imageProviderOrder
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新增：asyncio 重试退避（上线版缺的，banana 有 _retry 思路）
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铁律：
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- IMAGE_PROVIDER_PRIMARY/FALLBACK 走环境变量，不写死
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- GPT 主通道必须有产品参考图，无图报错（禁纯文生图防产品跑偏）
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- key 不在本模块，由 worker 传入构造好的 async HTTP client
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"""
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from __future__ import annotations
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import asyncio
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import logging
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import os
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from typing import Any, Protocol
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from .constants import IMAGE_RETRY_ATTEMPTS, IMAGE_RETRY_BACKOFF_BASE, IMAGE_SIZE_DEFAULT
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from .image_scorer import score_image
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from .storyboard import plan_image_set, sanitize_text
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logger = logging.getLogger(__name__)
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class ImageClient(Protocol):
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"""worker 注入的图片生成客户端协议（隔离 key 细节）"""
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async def gpt_edits(
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self, prompt: str, reference_images: list[bytes], size: str, provider: str | None = None
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) -> bytes: ...
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async def gpt_generate(self, prompt: str, size: str, provider: str | None = None) -> bytes: ...
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async def gemini_generate(
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self, prompt: str, reference_images: list[bytes], model: str
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) -> bytes: ...
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def _image_provider_order() -> list[str]:
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"""从环境变量读主备顺序（扒 imageProviderOrder）"""
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primary = os.environ.get("IMAGE_PROVIDER_PRIMARY", "gpt").lower()
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fallback = os.environ.get("IMAGE_PROVIDER_FALLBACK", "gemini").lower()
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seen: list[str] = []
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for p in [primary, fallback]:
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if p and p not in seen:
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seen.append(p)
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return seen
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def _gemini_models() -> list[str]:
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"""Gemini fallback 模型列表（多模型依次重试）"""
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env_val = os.environ.get("GEMINI_IMAGE_MODELS", "gemini-2.0-flash-preview-image-generation,imagen-3.0-generate-002")
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return [m.strip() for m in env_val.split(",") if m.strip()]
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async def _retry(coro_fn, attempts: int = IMAGE_RETRY_ATTEMPTS, backoff: float = IMAGE_RETRY_BACKOFF_BASE) -> Any:
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"""指数退避重试（扒 banana _retry 思路）"""
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last_exc: Exception | None = None
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for i in range(attempts):
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try:
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return await coro_fn()
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except Exception as exc:
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last_exc = exc
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if i < attempts - 1:
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wait = backoff ** i
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logger.warning("生图失败第%d次，%.1fs后重试：%s", i + 1, wait, exc)
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await asyncio.sleep(wait)
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raise RuntimeError(f"重试{attempts}次均失败") from last_exc
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async def _request_gpt(client: ImageClient, prompt: str, reference_images: list[bytes], provider: str | None = None) -> bytes:
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if reference_images:
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return await client.gpt_edits(prompt, reference_images, IMAGE_SIZE_DEFAULT, provider)
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# 无产品参考图时降级为纯文生图（需 ALLOW_TEXT_ONLY_IMAGE=true 或 M2阶段）
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allow_text_only = os.environ.get("ALLOW_TEXT_ONLY_IMAGE", "true").lower() == "true"
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if allow_text_only:
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logger.warning("无产品参考图，降级为纯文生图（可能产品跑偏，建议前端上传参考图）")
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return await client.gpt_generate(prompt, IMAGE_SIZE_DEFAULT, provider)
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raise ValueError("GPT 主通道缺产品图：禁止纯文生图以免产品跑偏（设 ALLOW_TEXT_ONLY_IMAGE=true 可解锁）")
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async def _request_gemini(client: ImageClient, prompt: str, reference_images: list[bytes]) -> bytes:
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errors: list[str] = []
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for model in _gemini_models():
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try:
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return await client.gemini_generate(prompt, reference_images, model)
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except Exception as exc:
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errors.append(f"{model}: {exc}")
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raise RuntimeError("Gemini 全部模型失败：" + "；".join(errors))
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async def generate_one_image(
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client: ImageClient,
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prompt: str,
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reference_images: list[bytes] | None = None,
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) -> bytes:
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"""
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主入口：按主备顺序依次尝试，每个 provider 内部有重试退避。
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返回图片 bytes（PNG/JPEG）。
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"""
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refs = reference_images or []
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providers = _image_provider_order()
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errors: list[str] = []
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for provider in providers:
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try:
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# apiports/codeproxy/openai 都是 OpenAI 兼容中转站，走 gpt 协议，
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# 但传 provider 进去 → client 按 provider 切到对应中转站的 base+key。
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# 这才是真主备：apiports 503 → codeproxy 用独立 base+key 顶上。
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if provider in ("apiports", "codeproxy", "openai"):
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img = await _retry(lambda p=provider: _request_gpt(client, prompt, refs, p))
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elif provider == "gpt":
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img = await _retry(lambda: _request_gpt(client, prompt, refs, None))
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elif provider == "gemini":
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img = await _retry(lambda: _request_gemini(client, prompt, refs))
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else:
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raise ValueError(f"未知图片通道：{provider}")
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return img
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except Exception as exc:
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errors.append(f"{provider}: {exc}")
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logger.warning("图片通道 %s 失败，尝试下一个：%s", provider, exc)
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raise RuntimeError("所有图片通道均失败：" + "；".join(errors))
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async def generate_storyboard_images(
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client: ImageClient,
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note: dict,
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product: dict,
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image_count: int = 3,
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reference_images: list[bytes] | None = None,
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analysis: dict | None = None,
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strategy: str | None = None,
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target_role: str | None = None,
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custom_prompt: str | None = None,
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) -> list[dict]:
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"""
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按 storyboard 逐张生图（asyncio.gather 并发），返回每张结果列表。
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strategy: None=默认叙事，'A'/'B'/'C'=三套正交叙事策略
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target_role: 非空时只生成该 role 那一张（R2 单张重生）
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custom_prompt: 非空时追加到每张 per_prompt 末尾（R2 人工提示词）
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每项：{role, name, image_bytes, error}
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"""
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plan = plan_image_set(note, product, image_count, analysis, strategy=strategy)
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storyboard = plan["storyboard"]
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base_prompt = plan["base_prompt"]
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# R2 单张重生：只保留目标 role 的分镜（匹配不到则原样全跑，避免空结果）
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if target_role:
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_filtered = [it for it in storyboard if it.get("role") == target_role]
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if _filtered:
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storyboard = _filtered
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async def _gen_one(item: dict) -> dict:
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# 逐图 prompt 9 字段（扒 promptFromStoryboard:323-334），每张差异化
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brand_line = ""
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if item.get("brand_keyword"):
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brand_line = f"品牌词=「{item['brand_keyword']}」，{item.get('brand_keyword_rule','自然植入')}。"
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per_prompt = (
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f"{base_prompt}\n"
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f"本张名称={item['name']}。"
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f"本张目标={item.get('goal') or item['focus']}。"
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f"图上主文字=「{sanitize_text(item.get('overlay_text',''), 20)}」。"
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f"使用卖点={item.get('selling_point','')}。"
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f"文案依据={item.get('source_basis','')}。"
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f"画面主体={item.get('visual_strategy','')}。"
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f"素材使用={item.get('asset_use','')}。"
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f"{brand_line}"
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f"禁止事项={item.get('forbidden','')}。"
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"排版要求：独立小红书3:4图文海报，画面完整；标题只出现一次，不与其他页重复；"
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"中文文字少而清晰，主标题+最多3个短点位；可自然用✅✨🌿💧🪞🧴📦🔍种草符号但不堆砌；"
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"不要生成App截图或笔记详情页界面。"
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)
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# R2 人工提示词：追加到末尾权重最高，但不覆盖前面合规/真实约束
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if custom_prompt:
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per_prompt += f"\n运营补充要求（在不违反上述合规与真实约束前提下尽量满足）：{sanitize_text(custom_prompt, 200)}。"
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try:
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img_bytes = await generate_one_image(client, per_prompt, reference_images)
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# 注：gpt-image-2 渲染中文偶发错别字(约1/6)。vision/OCR 文字校验闸门实测
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# 不可靠(漏报形近字+幻觉误伤品牌词),倩倩姐2026-06-16拍板先撤,纯生图,
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# 错别字作已知问题记录,后续迭代再处理。详见记忆 clover-image-text-check-shelved。
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#
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# C3 canvas 叠字口子(倩倩姐2026-06-12拍板"只留口子不实现")：
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# 当 OVERLAY_TEXT_RENDER_ENABLED=True 时，此处由 PIL 在模型出的干净底图上
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# 叠 item['overlay_text']/brand_keyword(字体资源+排版坐标后续补)，彻底解决中文乱码。
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# TODO(C3-overlay): from .constants import OVERLAY_TEXT_RENDER_ENABLED
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# if OVERLAY_TEXT_RENDER_ENABLED: img_bytes = overlay_text_on_image(img_bytes, item)
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# E12 AI评图分：只做展示+排序,绝不进飞轮权重,失败返 None 不阻断(倩倩姐2026-06-16)。
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visual = await score_image(client, img_bytes)
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return {"role": item["role"], "name": item["name"], "image_bytes": img_bytes,
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"error": None, "text_review": None,
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"ai_visual_score": (visual or {}).get("score"),
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"ai_visual_note": (visual or {}).get("note")}
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except Exception as exc:
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logger.error("分镜 %s 生图失败: %s", item["role"], exc)
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return {"role": item["role"], "name": item["name"], "image_bytes": None,
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"error": str(exc), "text_review": None,
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"ai_visual_score": None, "ai_visual_note": None}
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# 限并发：apiports 图片接口有 QPS 限制，6 张全并发会撞 429/503
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concurrency = int(os.environ.get("IMAGE_CONCURRENCY", "2"))
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sem = asyncio.Semaphore(max(1, concurrency))
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async def _gen_guarded(item: dict) -> dict:
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async with sem:
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return await _gen_one(item)
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results = await asyncio.gather(*(_gen_guarded(item) for item in storyboard))
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return list(results)
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