4bed7425a8
A8 多套交付包(packaging_task.py): - 修复交付包只打第1条混乱note的bug,按ImageCandidate.strategy分A/B/C组 - 每组生独立note_0N夹(6图+文案.txt),同seq留最新去重,老数据兼容 - task74端到端验:3套各6图,独立agent7项交叉验证全过 M4 归档(tasks.py/exports.py/前端): - list_tasks加date_from/date_to/product_id筛选+product_name批量填(防N+1) - 新增exports.py:产品JSON导出+标杆CSV导出(UTF-8 BOM) - 前端HistoryFilters日期/产品筛选+产品列+打回原因红banner - response.py加raise_param_error;独立agent验A1/A2/A9通过 R5 产品多图(product_images.py/020迁移/前端): - product_images表+5端点(上传/列/改场景/设主图/删图) - 生图按ROLE_SCENE_PREFERENCE选对应场景图,回落primary - 前端ProductImageManager多图画廊 R6 账号config拆页(settings/): - 配置页按角色拆/settings(运营+组长+admin)+/config(仅admin) - Key只显末4位不显余额(守红线) 核销表对齐真实代码状态:D1改稿框/M7裂变/E12评图分纠偏为已完成(曾漏回写) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
246 lines
12 KiB
Python
246 lines
12 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, ROLE_SCENE_PREFERENCE
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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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def _pick_reference_for_role(
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role: str,
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images_by_scene: dict[str, list[bytes]] | None,
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fallback: list[bytes] | None,
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) -> tuple[list[bytes] | None, str]:
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"""R5多图：按分镜 role 选该场景的产品图。取不到回落主图。
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返回 (参考图bytes列表, 命中scene标签用于日志)。
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"""
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if images_by_scene:
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for scene in ROLE_SCENE_PREFERENCE.get(role, ["primary"]):
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imgs = images_by_scene.get(scene)
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if imgs:
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return imgs, scene
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# 偏好全落空：用任意可用图兜底（仍优先 primary）
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if images_by_scene.get("primary"):
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return images_by_scene["primary"], "primary"
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for scene, imgs in images_by_scene.items():
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if imgs:
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return imgs, f"{scene}(兜底)"
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return fallback, "fallback"
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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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images_by_scene: dict[str, list[bytes]] | None = None,
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flywheel_fragment: 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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images_by_scene: R5多图，{scene: [bytes]}，按分镜 role 选对应场景图；
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为空则全分镜共用 reference_images（向后兼容）。
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flywheel_fragment: R7 飞轮偏好片段（最近选图/打回真实信号聚合），注入图片
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排版偏好；仅影响文字角度/版式取向，绝不改瓶身（合规红线）。
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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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# R7 飞轮偏好：仅作用于文字角度/版式取向参考，绝不改瓶身（合规+真实红线）
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if flywheel_fragment:
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per_prompt += (
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f"\n历史偏好参考（仅影响标题文字角度与排版取向，不得据此改动产品瓶身）："
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f"{sanitize_text(flywheel_fragment, 300)}。"
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)
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try:
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# R5多图：按本张分镜 role 选对应场景产品图；无多图则共用 reference_images
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ref_for_item, _scene_hit = _pick_reference_for_role(
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item["role"], images_by_scene, reference_images
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)
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if images_by_scene:
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logger.info("分镜 %s 选用产品图场景=%s", item["role"], _scene_hit)
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img_bytes = await generate_one_image(client, per_prompt, ref_for_item)
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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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