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image-suite-studio/server/services/generator.py
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2026-08-17 17:28:02 +08:00

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"""套图生成服务:图像 provider(豆包 Seedream / 通义万相)+ 任务执行器。
Provider 调用方式移植自 ecommerce-image-suite/scripts/generate.py
- doubao:火山方舟 images/generations,同步返回 URL;参考图走 image 字段(data URI
- tongyi:wan* 万象模型走异步任务轮询;qwen* 走同步 multimodal-generation
"""
from __future__ import annotations
import asyncio
import base64
import logging
import mimetypes
from uuid import UUID
import httpx
from sqlalchemy import select
from config import get_settings
from db import get_session_factory
from models import Product, ProductAsset, Suite, SuiteImage, SUITE_RUNNING, SUITE_DONE, SUITE_PARTIAL, SUITE_FAILED, STATUS_OK, STATUS_FAILED
from services import storage
from services.prompt import build_prompt, build_context, type_name
log = logging.getLogger("suite.generator")
def _raise_api_error(resp, provider: str):
"""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)。"""
if resp.is_success:
return
try:
body = resp.json()
detail = f"{body.get('code', '')}: {body.get('message', '')}".strip(': ')
except Exception: # noqa: BLE001
detail = resp.text[:200]
raise RuntimeError(f"{provider} API HTTP {resp.status_code}{detail or '无错误详情'}")
# 参考图选择:material 用第 2 张(背面/细节),其余用第 1 张(正面)
TYPE_REF_INDEX = {
"material": 1,
}
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)
def _image_size(provider: str, ratio: str, is_wan: bool = True) -> str:
"""平台比例 → provider 尺寸参数。3:4 竖版(Ozon/WB),1:1 方图(国内)。"""
if provider == "doubao":
return "1536x2048" if ratio == "3:4" else "2048x2048"
if provider == "rightapi":
# gpt-image 自定义尺寸约束:16 的倍数、长短边比 ≤ 3:1(1536x2048 合法)
return "1536x2048" if ratio == "3:4" else "2048x2048"
# tongyi:万象与千问的 size 语法相同(* 分隔),档位不同
if ratio == "3:4":
return "1536*2048" if is_wan else "768*1024"
return "2048*2048" if is_wan else "1024*1024"
_DOUBAO_ANTI_AI = (
"authentic real-world photography, natural imperfections, genuine texture, "
"no synthetic look, no CGI quality, no heavy post-processing"
)
DEFAULT_NEGATIVE_PROMPT = (
"AI-generated look, artificial, CGI quality, 3D render, synthetic texture, "
"plastic skin, mannequin-like, too perfect, oversaturated, HDR, heavy vignette, "
"low resolution, blurry, deformed, bad anatomy, overexposed, underexposed, grainy, "
"watermark, text distortion, bad typography, overlapping text, cheap look, cartoon"
)
# ── 参考图解析 ────────────────────────────────────────────────────────────
def _bytes_to_data_uri(data: bytes, mime: str) -> str:
return f"data:{mime};base64,{base64.b64encode(data).decode()}"
async def _resolve_ref_bytes(url: str) -> tuple[bytes, str]:
"""参考图 URL → (bytes, mime)。本地 media 文件直读磁盘;远程 URL 带 Referer 下载。
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,
所以统一在本地解析成原始字节再进请求体(data URI 或 multipart)。
"""
if url.startswith("data:"):
head, _, b64 = url.partition(",")
mime = head[5:].split(";", 1)[0] or "image/jpeg"
return base64.b64decode(b64), mime
path = storage.local_path(url)
if path is not None:
mime = mimetypes.guess_type(path.name)[0] or "image/jpeg"
return path.read_bytes(), mime
if url.startswith(("http://", "https://")):
from api.proxy import guess_referer
data, ctype = await storage.download_bytes(url, referer=guess_referer(url))
if not ctype.startswith("image/"):
ctype = "image/jpeg"
return data, ctype
raise FileNotFoundError(f"无法解析参考图: {url}")
async def _resolve_ref(url: str) -> str:
data, mime = await _resolve_ref_bytes(url)
return _bytes_to_data_uri(data, mime)
# ── Provider:豆包 Seedream(火山方舟)────────────────────────────────────
async def generate_doubao(prompt: str, ref_images: list[str], size: str = "2048x2048", model: str | None = None) -> bytes:
s = get_settings()
if not s.ark_api_key:
raise RuntimeError("未配置 ARK_API_KEY.env")
body = {
"model": model or s.ark_image_model,
"prompt": prompt.rstrip(". ") + ". " + _DOUBAO_ANTI_AI,
"size": size,
"response_format": "url",
"watermark": False,
"n": 1,
}
if ref_images:
body["image"] = [await _resolve_ref(u) for u in ref_images]
async with httpx.AsyncClient(timeout=s.request_timeout, verify=False) as client:
resp = await client.post(
s.ark_base_url,
headers={"Authorization": f"Bearer {s.ark_api_key}", "Content-Type": "application/json"},
json=body,
)
_raise_api_error(resp, "豆包")
img_url = resp.json()["data"][0]["url"]
dl = await client.get(img_url, timeout=s.request_timeout)
dl.raise_for_status()
return dl.content
# ── Provider:通义万相 / 千问(DashScope)────────────────────────────────
def _is_wan_model(model: str) -> bool:
return model.lower().startswith("wan")
async def _tongyi_poll_task(client: httpx.AsyncClient, key: str, task_id: str, max_wait: int) -> str:
poll_url = "https://dashscope.aliyuncs.com/api/v1/tasks/" + task_id
elapsed, interval = 0, 3
while elapsed < max_wait:
resp = await client.get(poll_url, headers={"Authorization": f"Bearer {key}"}, timeout=30)
resp.raise_for_status()
result = resp.json()
status = result.get("output", {}).get("task_status", "")
if status == "SUCCEEDED":
choices = result["output"].get("choices", [])
if choices:
content = choices[0].get("message", {}).get("content", [])
if content:
return content[0].get("image", "")
results = result["output"].get("results", [])
if results:
return results[0].get("url") or results[0].get("b64_image", "")
raise RuntimeError(f"通义任务成功但无结果: {result}")
if status in ("FAILED", "UNKNOWN"):
raise RuntimeError(f"通义任务失败: {result}")
await asyncio.sleep(interval)
elapsed += interval
interval = min(interval + 2, 10)
raise TimeoutError(f"通义异步任务超时 ({max_wait}s): task_id={task_id}")
async def generate_tongyi(prompt: str, ref_images: list[str], size: str = "2048*2048", model: str | None = None) -> bytes:
s = get_settings()
if not s.dashscope_api_key:
raise RuntimeError("未配置 DASHSCOPE_API_KEY.env")
model = model or s.dashscope_model
is_wan = _is_wan_model(model)
url = s.dashscope_base_url or (
"https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation/generation"
if is_wan
else "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
)
content: list[dict] = [{"image": await _resolve_ref(u)} for u in ref_images]
content.append({"text": prompt})
params = {"size": size, "n": 1, "watermark": False}
if not is_wan:
params["prompt_extend"] = False
params["negative_prompt"] = DEFAULT_NEGATIVE_PROMPT[:500]
headers = {"Authorization": f"Bearer {s.dashscope_api_key}", "Content-Type": "application/json"}
if is_wan:
headers["X-DashScope-Async"] = "enable"
body = {"model": model, "input": {"messages": [{"role": "user", "content": content}]}, "parameters": params}
async with httpx.AsyncClient(timeout=s.request_timeout, verify=False) as client:
resp = await client.post(url, headers=headers, json=body)
_raise_api_error(resp, "通义")
data = resp.json()
if is_wan:
task_id = data.get("output", {}).get("task_id", "")
if not task_id:
raise RuntimeError(f"通义万象未返回 task_id: {data}")
img_url = await _tongyi_poll_task(client, s.dashscope_api_key, task_id, s.poll_max_wait)
if img_url.startswith("data:") or len(img_url) > 500:
return base64.b64decode(img_url.split(",", 1)[-1] if "," in img_url else img_url)
dl = await client.get(img_url, timeout=s.request_timeout)
dl.raise_for_status()
return dl.content
img_url = data["output"]["choices"][0]["message"]["content"][0]["image"]
dl = await client.get(img_url, timeout=s.request_timeout)
dl.raise_for_status()
return dl.content
# ── ProviderRightAPIgpt-imageOpenAI 兼容中转)──────────────────────
async def generate_rightapi(prompt: str, ref_images: list[str], size: str = "2048x2048", model: str | None = None) -> bytes:
"""gpt-image 系列:有参考图走 /v1/images/editsmultipart),无参考图走 /v1/images/generations。
OpenAI 兼容协议:响应固定 b64_json(不支持 response_format 参数,传了报 400);
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。
"""
s = get_settings()
if not s.rightapi_api_key:
raise RuntimeError("未配置 RIGHTAPI_API_KEY.env")
model = model or s.rightapi_image_model
base = s.rightapi_base_url.rstrip("/")
headers = {"Authorization": f"Bearer {s.rightapi_api_key}"}
async with httpx.AsyncClient(timeout=max(s.request_timeout, 600), verify=False) as client:
common = {
"model": model,
"prompt": prompt,
"size": size,
"quality": s.rightapi_image_quality,
"output_format": "jpeg", # 与落盘 .jpg 后缀一致
"n": 1,
}
if ref_images:
files = []
for i, u in enumerate(ref_images):
data, mime = await _resolve_ref_bytes(u)
files.append(("image[]", (f"ref-{i + 1}.{mime.split('/')[-1]}", data, mime)))
resp = await client.post(f"{base}/v1/images/edits", headers=headers, files=files, data=common)
else:
resp = await client.post(
f"{base}/v1/images/generations",
headers={**headers, "Content-Type": "application/json"},
json=common,
)
_raise_api_error(resp, "RightAPI")
item = resp.json()["data"][0]
b64 = item.get("b64_json") or ""
if b64:
return base64.b64decode(b64.split(",", 1)[-1] if "," in b64 else b64)
img_url = item.get("url") or ""
if not img_url:
raise RuntimeError(f"RightAPI 响应里没有图片数据: {item}")
dl = await client.get(img_url, timeout=s.request_timeout)
dl.raise_for_status()
return dl.content
GENERATORS = {"doubao": generate_doubao, "tongyi": generate_tongyi, "rightapi": generate_rightapi}
# ── 任务执行器 ────────────────────────────────────────────────────────────
def _order_refs(refs: list[str], type_id: str) -> list[str]:
"""参考图槽位选择 + 截断:material 偏好第 2 张,其余用第 1 张。"""
preferred = TYPE_REF_INDEX.get(type_id)
if preferred is not None and len(refs) > preferred:
refs = [refs[preferred]] + [r for i, r in enumerate(refs) if i != preferred]
return refs[:DEFAULT_REF_COUNT]
def _refs_for_job(images: list[dict], job: dict) -> list[str]:
"""无状态路径:按方案项选参考图。
优先 variant_name 精确匹配(「主图·粉色」用粉色那张 SKU 图);
匹配不到则回退 main 组第一张(再退到任意第一张)。
"""
variant = job.get("variant_name")
if variant:
matched = [i["url"] for i in images if i.get("variant_name") == variant]
if matched:
return matched[:DEFAULT_REF_COUNT]
mains = [i["url"] for i in images if i.get("group_key") == "main"]
others = [i["url"] for i in images if i.get("group_key") != "main"]
pool = mains or others or [i["url"] for i in images]
if not pool:
raise RuntimeError("任务没有参考图")
return _order_refs(pool, job.get("kind", ""))
async def _select_ref_images(db, product_id: UUID, type_id: str) -> list[str]:
"""商品路径:主图组前几张。转存完成的用本地文件,未完成的直接用源站 URL。"""
assets = (await db.scalars(
select(ProductAsset).where(
ProductAsset.product_id == product_id,
ProductAsset.group_key == "main",
ProductAsset.type == "img",
).order_by(ProductAsset.sort_order)
)).all()
refs = [a.stored_url or a.source_url for a in assets if (a.stored_url or a.source_url)]
if not refs:
raise RuntimeError("商品没有可用参考图(未采集主图)")
return _order_refs(refs, type_id)
async def run_suite(suite_id: str) -> None:
"""后台执行套图任务:逐张生成 → 落盘 → 记录;单张失败不中断。
两条路径:
- 无状态(product_id 为空):上下文与参考图来自请求自带的 context / ref_images
- 商品路径(兼容旧流程):从 product + product_assets 取
"""
settings = get_settings()
async with get_session_factory()() as db:
suite = await db.get(Suite, UUID(suite_id))
if suite is None:
return
product = None
if suite.product_id:
product = await db.get(Product, suite.product_id)
if product is None:
suite.status = SUITE_FAILED
suite.error = "商品不存在"
await db.commit()
return
suite.status = SUITE_RUNNING
await db.commit()
provider_name = suite.provider or settings.image_provider
generator = GENERATORS.get(provider_name)
if generator is None:
suite.status = SUITE_FAILED
suite.error = f"未知 provider: {provider_name}"
await db.commit()
return
raw = suite.context if not product else (product.raw or {})
ctx = build_context(raw or {}, fallback_name=product.name if product else "")
model = suite.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, suite.ratio, is_wan=is_wan)
# 任务列表:方案(逐张)优先,旧路径按 types
if suite.plan:
jobs = [dict(j) for j in suite.plan]
else:
jobs = [
{"kind": t, "title": type_name(t), "detail": "", "prompt_hint": "", "variant_name": None}
for t in (suite.types or [])
]
ok, failed = 0, 0
failures: list[str] = []
for job in jobs:
type_id = job["kind"]
image_row = SuiteImage(
suite_id=suite.id,
type_id=type_id,
name=job.get("title") or type_name(type_id),
status=STATUS_FAILED,
)
db.add(image_row)
await db.flush()
try:
prompt = build_prompt(
type_id, ctx, suite.style_set, suite.lang,
extra=job, style_prompt=suite.style_prompt, requirements=suite.requirements,
)
if product:
refs = await _select_ref_images(db, product.id, type_id)
else:
refs = _refs_for_job(list(suite.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/{suite.id}", ext=ext)
image_row.stored_url = storage.public_url(key)
image_row.status = STATUS_OK
ok += 1
except Exception as exc: # noqa: BLE001
log.exception("套图 %s 类型 %s 生成失败", suite_id, type_id)
err = str(exc)[:500]
image_row.error = err
failures.append(f"{job.get('title') or type_name(type_id)}{err[:200]}")
failed += 1
await db.commit()
suite.status = SUITE_DONE if failed == 0 else (SUITE_PARTIAL if ok > 0 else SUITE_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:
suite.error = f"全部生成失败。{detail}"
else:
suite.error = f"部分生成失败({failed} 张)。{detail}"
from datetime import datetime, timezone
suite.finished_at = datetime.now(timezone.utc)
if product:
product.stage = "generated" # 商品路径才有的阶段升级
await db.commit()