R524809
429 lines
20 KiB
Python
429 lines
20 KiB
Python
"""套图生成服务：图像 provider（豆包 Seedream / 通义万相）+ 任务执行器。
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Provider 调用方式移植自 ecommerce-image-suite/scripts/generate.py：
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- doubao：火山方舟 images/generations，同步返回 URL；参考图走 image 字段（data URI）
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- tongyi：wan* 万象模型走异步任务轮询；qwen* 走同步 multimodal-generation
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"""
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from __future__ import annotations
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import asyncio
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import base64
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import logging
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import mimetypes
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import re
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import httpx
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from config import get_settings
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from services import storage
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from services.prompts import build_prompt, build_context, type_name
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from services.tasks import Task, TaskImage, TASK_FAILED, TASK_RUNNING, TASK_DONE, TASK_PARTIAL, IMG_FAILED, IMG_OK
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log = logging.getLogger("suite.generator")
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class ApiError(RuntimeError):
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"""带 HTTP 状态码的 API 错误（用于区分可重试的网关/限流错误）。"""
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def __init__(self, message: str, status: int = 0):
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super().__init__(message)
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self.status = status
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_HTML_TITLE_RE = re.compile(r"<title[^>]*>(.*?)</title>", re.IGNORECASE | re.DOTALL)
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def _raise_api_error(resp, provider: str):
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"""HTTP 错误时抛出带 API 错误码/信息的异常（响应体里有真正的失败原因）。"""
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if resp.is_success:
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return
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text = resp.text or ""
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if "<html" in text[:300].lower() or text.lstrip()[:15].lower().startswith("<!doctype"):
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# Cloudflare/网关错误页：取 <title> 作摘要，避免整段 HTML 进错误信息
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m = _HTML_TITLE_RE.search(text)
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detail = (re.sub(r"\s+", " ", m.group(1)).strip() if m else "") or "网关返回 HTML 错误页（上游/CDN 故障）"
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raise ApiError(f"{provider} API HTTP {resp.status_code} — {detail}", resp.status_code)
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try:
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body = resp.json()
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detail = f"{body.get('code', '')}: {body.get('message', '')}".strip(': ')
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except Exception: # noqa: BLE001
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detail = text[:200]
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raise ApiError(f"{provider} API HTTP {resp.status_code} — {detail or '无错误详情'}", resp.status_code)
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# 参考图选择：material 用第 2 张（背面/细节），其余用第 1 张（正面）
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TYPE_REF_INDEX = {
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"material": 1,
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}
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DEFAULT_REF_COUNT = 2 # 每次生图最多带的参考图数（正面 1 张 + 背面/细节 1 张）
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def _image_size(provider: str, ratio: str, is_wan: bool = True, model: str = "") -> str:
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"""平台比例 → provider 尺寸参数。3:4 竖版（Ozon/WB），1:1 方图（国内）。"""
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if provider == "doubao":
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return "1536x2048" if ratio == "3:4" else "2048x2048"
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if provider == "rightapi":
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# gpt-image 自定义尺寸约束：16 的倍数、长短边比 ≤ 3:1（1536x2048 合法）
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return "1536x2048" if ratio == "3:4" else "2048x2048"
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# tongyi：万象与千问的 size 语法相同（* 分隔），档位不同
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# wan2.6 系列总像素限制在 [1280², 1440²]，wan2.7 的 1536*2048/2048*2048 会超限
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if model.startswith("wan2.6"):
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return "1152*1536" if ratio == "3:4" else "1440*1440"
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if ratio == "3:4":
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return "1536*2048" if is_wan else "768*1024"
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return "2048*2048" if is_wan else "1024*1024"
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_DOUBAO_ANTI_AI = (
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"authentic real-world photography, natural imperfections, genuine texture, "
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"no synthetic look, no CGI quality, no heavy post-processing"
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)
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DEFAULT_NEGATIVE_PROMPT = (
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"AI-generated look, artificial, CGI quality, 3D render, synthetic texture, "
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"plastic skin, mannequin-like, too perfect, oversaturated, HDR, heavy vignette, "
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"low resolution, blurry, deformed, bad anatomy, overexposed, underexposed, grainy, "
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"watermark, text distortion, bad typography, overlapping text, cheap look, cartoon"
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)
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# ── 参考图解析 ────────────────────────────────────────────────────────────
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def _bytes_to_data_uri(data: bytes, mime: str) -> str:
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return f"data:{mime};base64,{base64.b64encode(data).decode()}"
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async def _resolve_ref_bytes(url: str) -> tuple[bytes, str]:
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"""参考图 URL → (bytes, mime)。本地 media 文件直读磁盘；远程 URL 带 Referer 下载。
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生图 API 的服务器无法访问 127.0.0.1，代理 URL 也不能直接透传，
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所以统一在本地解析成原始字节再进请求体（data URI 或 multipart）。
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"""
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if url.startswith("data:"):
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head, _, b64 = url.partition(",")
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mime = head[5:].split(";", 1)[0] or "image/jpeg"
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return base64.b64decode(b64), mime
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path = storage.local_path(url)
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if path is not None:
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mime = mimetypes.guess_type(path.name)[0] or "image/jpeg"
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return path.read_bytes(), mime
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if url.startswith(("http://", "https://")):
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from api.proxy import guess_referer
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data, ctype = await storage.download_bytes(url, referer=guess_referer(url))
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if not ctype.startswith("image/"):
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ctype = "image/jpeg"
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return data, ctype
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raise FileNotFoundError(f"无法解析参考图: {url}")
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async def _resolve_ref(url: str) -> str:
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data, mime = await _resolve_ref_bytes(url)
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return _bytes_to_data_uri(data, mime)
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# ── Provider：豆包 Seedream（火山方舟）────────────────────────────────────
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async def generate_doubao(prompt: str, ref_images: list[str], size: str = "2048x2048", model: str | None = None) -> bytes:
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s = get_settings()
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if not s.ark_api_key:
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raise RuntimeError("未配置 ARK_API_KEY（.env）")
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body = {
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"model": model or s.ark_image_model,
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"prompt": prompt.rstrip(". ") + ". " + _DOUBAO_ANTI_AI,
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"size": size,
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"response_format": "url",
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"watermark": False,
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"n": 1,
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}
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if ref_images:
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body["image"] = [await _resolve_ref(u) for u in ref_images]
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async with httpx.AsyncClient(timeout=s.request_timeout, verify=False) as client:
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resp = await client.post(
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s.ark_base_url,
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headers={"Authorization": f"Bearer {s.ark_api_key}", "Content-Type": "application/json"},
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json=body,
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)
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_raise_api_error(resp, "豆包")
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img_url = resp.json()["data"][0]["url"]
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dl = await client.get(img_url, timeout=s.request_timeout)
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dl.raise_for_status()
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return dl.content
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# ── Provider：通义万相 / 千问（DashScope）────────────────────────────────
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def _is_wan_model(model: str) -> bool:
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return model.lower().startswith("wan")
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def _is_t2i_model(model: str) -> bool:
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"""纯文生图模型（如 wan2.6-t2i）：不接受参考图，商品一致性只能靠文案描述。"""
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return "t2i" in model.lower()
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async def _tongyi_poll_task(client: httpx.AsyncClient, key: str, task_id: str, max_wait: int) -> str:
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poll_url = "https://dashscope.aliyuncs.com/api/v1/tasks/" + task_id
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elapsed, interval = 0, 3
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while elapsed < max_wait:
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resp = await client.get(poll_url, headers={"Authorization": f"Bearer {key}"}, timeout=30)
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resp.raise_for_status()
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result = resp.json()
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status = result.get("output", {}).get("task_status", "")
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if status == "SUCCEEDED":
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choices = result["output"].get("choices", [])
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if choices:
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content = choices[0].get("message", {}).get("content", [])
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if content:
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return content[0].get("image", "")
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results = result["output"].get("results", [])
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if results:
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return results[0].get("url") or results[0].get("b64_image", "")
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raise RuntimeError(f"通义任务成功但无结果: {result}")
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if status in ("FAILED", "UNKNOWN"):
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raise RuntimeError(f"通义任务失败: {result}")
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await asyncio.sleep(interval)
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elapsed += interval
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interval = min(interval + 2, 10)
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raise TimeoutError(f"通义异步任务超时 ({max_wait}s): task_id={task_id}")
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async def generate_tongyi(prompt: str, ref_images: list[str], size: str = "2048*2048", model: str | None = None) -> bytes:
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s = get_settings()
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if not s.dashscope_api_key:
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raise RuntimeError("未配置 DASHSCOPE_API_KEY（.env）")
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model = model or s.dashscope_model
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is_wan = _is_wan_model(model)
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url = s.dashscope_base_url or (
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"https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation"
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if is_wan
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else "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
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)
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# t2i 模型不接受参考图：content 只有文本，商品一致性依赖 prompt 里的标题/卖点描述
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content: list[dict] = []
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if not _is_t2i_model(model):
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content = [{"image": await _resolve_ref(u)} for u in ref_images]
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content.append({"text": prompt})
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params = {"size": size, "n": 1, "watermark": False}
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if not is_wan:
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params["prompt_extend"] = False
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params["negative_prompt"] = DEFAULT_NEGATIVE_PROMPT[:500]
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headers = {"Authorization": f"Bearer {s.dashscope_api_key}", "Content-Type": "application/json"}
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if is_wan:
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headers["X-DashScope-Async"] = "enable"
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body = {"model": model, "input": {"messages": [{"role": "user", "content": content}]}, "parameters": params}
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async with httpx.AsyncClient(timeout=s.request_timeout, verify=False) as client:
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resp = await client.post(url, headers=headers, json=body)
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_raise_api_error(resp, "通义")
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data = resp.json()
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if is_wan:
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task_id = data.get("output", {}).get("task_id", "")
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if not task_id:
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raise RuntimeError(f"通义万象未返回 task_id: {data}")
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img_url = await _tongyi_poll_task(client, s.dashscope_api_key, task_id, s.poll_max_wait)
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if img_url.startswith("data:") or len(img_url) > 500:
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return base64.b64decode(img_url.split(",", 1)[-1] if "," in img_url else img_url)
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dl = await client.get(img_url, timeout=s.request_timeout)
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dl.raise_for_status()
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return dl.content
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img_url = data["output"]["choices"][0]["message"]["content"][0]["image"]
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dl = await client.get(img_url, timeout=s.request_timeout)
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dl.raise_for_status()
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return dl.content
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# ── Provider：RightAPI（gpt-image，OpenAI 兼容中转）──────────────────────
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# 可重试的状态码：中转限流/网关抖动（该中转限流时返回 Cloudflare 502 而非 429）
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RETRYABLE_STATUS = {429, 500, 502, 503, 504}
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# 中转对 input_fidelity 参数的支持探测：按模型记忆不支持该参数的模型（gpt-image 系列支持，
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# nano-banana 系列可能不认；降级只影响触发过的模型，不牵连其他模型）
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_rightapi_fidelity_unsupported: set[str] = set()
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async def _rightapi_request(s, prompt: str, ref_images: list[str], size: str, model: str) -> bytes:
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"""RightAPI 各模型：有参考图走 /v1/images/edits（multipart），无参考图走 /v1/images/generations。
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OpenAI 兼容协议：响应固定 b64_json（不支持 response_format 参数，传了报 400）；
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同步调用无任务轮询，高质量档单张 1-5 分钟，超时按文档建议兜底 600s。
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input_fidelity=high 是 gpt-image-1 的 edits 保真参数（gpt-image-2 官方已移除、默认高保真，
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官逆通道更是不识别）；带上是为了兼容按 gpt-image-1 语义实现的中转，中转不认（400）则按模型
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自动去掉重试并记住，该模型后续请求不再带。
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"""
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base = s.rightapi_base_url.rstrip("/")
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headers = {"Authorization": f"Bearer {s.rightapi_api_key}"}
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use_fidelity = (
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bool(ref_images) and s.rightapi_input_fidelity and model not in _rightapi_fidelity_unsupported
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)
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async with httpx.AsyncClient(timeout=max(s.request_timeout, 600), verify=False) as client:
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common = {
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"model": model,
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"prompt": prompt,
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"size": size,
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"quality": s.rightapi_image_quality,
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"output_format": "jpeg", # 与落盘 .jpg 后缀一致
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"n": 1,
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}
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if use_fidelity:
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common["input_fidelity"] = s.rightapi_input_fidelity
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if ref_images:
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files = []
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for i, u in enumerate(ref_images):
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data, mime = await _resolve_ref_bytes(u)
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files.append(("image[]", (f"ref-{i + 1}.{mime.split('/')[-1]}", data, mime)))
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resp = await client.post(f"{base}/v1/images/edits", headers=headers, files=files, data=common)
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# 中转不认 input_fidelity：去掉参数重试一次（仅一次探测），降级只记到当前模型
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if resp.status_code == 400 and use_fidelity and "input_fidelity" in resp.text:
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_rightapi_fidelity_unsupported.add(model)
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log.warning("RightAPI 模型 %s 不支持 input_fidelity 参数，已自动去掉并降级（该模型后续请求不再带）", model)
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common.pop("input_fidelity", None)
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resp = await client.post(f"{base}/v1/images/edits", headers=headers, files=files, data=common)
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else:
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resp = await client.post(
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f"{base}/v1/images/generations",
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headers={**headers, "Content-Type": "application/json"},
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json=common,
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)
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_raise_api_error(resp, "RightAPI")
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item = resp.json()["data"][0]
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b64 = item.get("b64_json") or ""
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if b64:
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return base64.b64decode(b64.split(",", 1)[-1] if "," in b64 else b64)
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img_url = item.get("url") or ""
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if not img_url:
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raise RuntimeError(f"RightAPI 响应里没有图片数据: {item}")
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dl = await client.get(img_url, timeout=s.request_timeout)
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dl.raise_for_status()
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return dl.content
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async def generate_rightapi(prompt: str, ref_images: list[str], size: str = "2048x2048", model: str | None = None) -> bytes:
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"""带重试的 RightAPI 入口：429/5xx/超时按递增间隔重试。
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实测该中转对同 key 连续请求有分钟级冷却（成功一张后紧接着的请求会被网关秒拒 502），
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60s → 120s → 240s 的退避基本能等到窗口放开。
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"""
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s = get_settings()
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if not s.rightapi_api_key:
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raise RuntimeError("未配置 RIGHTAPI_API_KEY（.env）")
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model = model or s.rightapi_image_model
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attempts = max(1, s.rightapi_max_retries)
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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 _rightapi_request(s, prompt, ref_images, size, model)
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except ApiError as exc:
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last_exc = exc
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if exc.status not in RETRYABLE_STATUS:
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raise # 参数错误等不可重试，立即失败
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except (httpx.TimeoutException, httpx.TransportError) as exc:
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last_exc = exc # 网络抖动/超时可重试
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if i == attempts - 1:
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break
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wait = s.rightapi_retry_wait * (2 ** i)
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log.warning("RightAPI 第 %d/%d 次请求失败（%s），%ds 后重试", i + 1, attempts, last_exc, wait)
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await asyncio.sleep(wait)
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raise last_exc # type: ignore[misc]
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GENERATORS = {"doubao": generate_doubao, "tongyi": generate_tongyi, "rightapi": generate_rightapi}
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# ── 任务执行器 ────────────────────────────────────────────────────────────
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def _order_refs(refs: list[str], type_id: str) -> list[str]:
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"""参考图槽位选择 + 截断：material 偏好第 2 张，其余用第 1 张。"""
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preferred = TYPE_REF_INDEX.get(type_id)
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if preferred is not None and len(refs) > preferred:
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refs = [refs[preferred]] + [r for i, r in enumerate(refs) if i != preferred]
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return refs[:DEFAULT_REF_COUNT]
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def _refs_for_job(images: list[dict], job: dict) -> list[str]:
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"""无状态路径：按方案项选参考图。
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优先 variant_name 精确匹配（「主图·粉色」用粉色那张 SKU 图）；
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匹配不到则回退 main 组第一张（再退到任意第一张）。
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"""
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variant = job.get("variant_name")
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if variant:
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matched = [i["url"] for i in images if i.get("variant_name") == variant]
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if matched:
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return matched[:DEFAULT_REF_COUNT]
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mains = [i["url"] for i in images if i.get("group_key") == "main"]
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others = [i["url"] for i in images if i.get("group_key") != "main"]
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pool = mains or others or [i["url"] for i in images]
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if not pool:
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raise RuntimeError("任务没有参考图")
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return _order_refs(pool, job.get("kind", ""))
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# 串行生成队列：所有用户共享同一批 API key，并发生成会触发中转限流
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# （rightapi 同 key 分钟级冷却）；同一时间只跑一个任务，其余保持 pending 排队。
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_GEN_LOCK = asyncio.Lock()
|
||
|
||
|
||
async def run_suite(task: Task) -> None:
|
||
"""后台执行套图任务：排队 → 逐张生成 → 落盘 → 更新内存状态；单张失败不中断。"""
|
||
settings = get_settings()
|
||
provider_name = task.provider or settings.image_provider
|
||
generator = GENERATORS.get(provider_name)
|
||
if generator is None:
|
||
task.status = TASK_FAILED
|
||
task.error = f"未知 provider: {provider_name}"
|
||
return
|
||
|
||
ctx = build_context(task.context or {}, fallback_name="")
|
||
model = task.model or {
|
||
"tongyi": settings.dashscope_model,
|
||
"rightapi": settings.rightapi_image_model,
|
||
}.get(provider_name, settings.ark_image_model)
|
||
is_wan = provider_name == "tongyi" and _is_wan_model(model)
|
||
size = _image_size(provider_name, task.ratio, is_wan=is_wan, model=model)
|
||
jobs = [dict(j) for j in task.plan]
|
||
|
||
async with _GEN_LOCK:
|
||
task.status = TASK_RUNNING
|
||
ok, failed = 0, 0
|
||
failures: list[str] = []
|
||
for job in jobs:
|
||
type_id = job["kind"]
|
||
image = TaskImage(type_id=type_id, name=job.get("title") or type_name(type_id))
|
||
task.images.append(image)
|
||
try:
|
||
# 提示词按模型家族分发：国产主体参考 / gpt edits 保真 / google 主体保持
|
||
prompt = build_prompt(
|
||
provider_name, model, type_id, ctx, task.style_set, task.lang,
|
||
extra=job, style_prompt=task.style_prompt, requirements=task.requirements,
|
||
)
|
||
refs = _refs_for_job(list(task.ref_images or []), job)
|
||
data = await generator(prompt, refs, size=size, model=model)
|
||
# 部分中转不遵守 output_format（要 jpeg 回 PNG），按魔数定扩展名
|
||
ext = ".png" if data[:8] == b"\x89PNG\r\n\x1a\n" else ".jpg"
|
||
key = storage.write_bytes(data, key_prefix=f"suites/{task.id}", ext=ext)
|
||
image.url = storage.public_url(key)
|
||
image.status = IMG_OK
|
||
ok += 1
|
||
except Exception as exc: # noqa: BLE001
|
||
log.exception("套图 %s 类型 %s 生成失败", task.id, type_id)
|
||
image.status = IMG_FAILED # 默认 pending，失败显式置 failed
|
||
image.error = str(exc)[:500]
|
||
failures.append(f"{job.get('title') or type_name(type_id)}：{str(exc)[:200]}")
|
||
failed += 1
|
||
|
||
task.status = TASK_DONE if failed == 0 else (TASK_PARTIAL if ok > 0 else TASK_FAILED)
|
||
if failed:
|
||
uniq = list(dict.fromkeys(failures)) # 去重保序
|
||
detail = "；".join(uniq[:6])
|
||
if len(uniq) > 6:
|
||
detail += f"；…等共 {failed} 张失败"
|
||
if ok == 0:
|
||
task.error = f"全部生成失败。{detail}"
|
||
else:
|
||
task.error = f"部分生成失败（{failed} 张）。{detail}"
|