feat: 添加新的模型，删除后端数据库
This commit is contained in:
Joey
+51
-109
@@ -11,16 +11,13 @@ import base64
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import logging
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import mimetypes
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import re
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from uuid import UUID
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import httpx
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from sqlalchemy import select
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from config import get_settings
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from db import get_session_factory
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from models import Product, ProductAsset, Suite, SuiteImage, SUITE_RUNNING, SUITE_DONE, SUITE_PARTIAL, SUITE_FAILED, STATUS_OK, STATUS_FAILED
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from services import storage
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from services.prompt import build_prompt, build_context, type_name, wrap_prompt_for_gpt_edits
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from services.tasks import Task, TaskImage, TASK_FAILED, TASK_RUNNING, TASK_DONE, TASK_PARTIAL, IMG_OK
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log = logging.getLogger("suite.generator")
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@@ -242,22 +239,25 @@ async def generate_tongyi(prompt: str, ref_images: list[str], size: str = "2048*
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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：None=未探测，True=支持，False=不支持（已降级）
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_rightapi_fidelity_supported: bool | None = None
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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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"""gpt-image 系列：有参考图走 /v1/images/edits（multipart），无参考图走 /v1/images/generations。
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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 强制高保真保留输入图细节（商品一致性关键参数，仅 edits 端点）；
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中转若不认该参数（400），自动去掉重试并记住，后续请求不再带。
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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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global _rightapi_fidelity_supported
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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 = bool(ref_images) and s.rightapi_input_fidelity and _rightapi_fidelity_supported is not False
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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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@@ -276,14 +276,12 @@ async def _rightapi_request(s, prompt: str, ref_images: list[str], size: str, mo
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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）
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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_supported = False
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log.warning("RightAPI 不支持 input_fidelity 参数，已自动去掉并降级（后续请求不再带）")
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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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elif resp.is_success and use_fidelity:
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_rightapi_fidelity_supported = True
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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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@@ -365,123 +363,67 @@ def _refs_for_job(images: list[dict], job: dict) -> list[str]:
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return _order_refs(pool, job.get("kind", ""))
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async def _select_ref_images(db, product_id: UUID, type_id: str) -> list[str]:
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"""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。"""
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assets = (await db.scalars(
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select(ProductAsset).where(
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ProductAsset.product_id == product_id,
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ProductAsset.group_key == "main",
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ProductAsset.type == "img",
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).order_by(ProductAsset.sort_order)
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)).all()
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refs = [a.stored_url or a.source_url for a in assets if (a.stored_url or a.source_url)]
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if not refs:
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raise RuntimeError("商品没有可用参考图（未采集主图）")
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return _order_refs(refs, type_id)
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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()
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async def run_suite(suite_id: str) -> None:
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"""后台执行套图任务：逐张生成 → 落盘 → 记录；单张失败不中断。
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两条路径：
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- 无状态（product_id 为空）：上下文与参考图来自请求自带的 context / ref_images
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- 商品路径（兼容旧流程）：从 product + product_assets 取
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"""
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async def run_suite(task: Task) -> None:
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"""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。"""
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settings = get_settings()
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async with get_session_factory()() as db:
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suite = await db.get(Suite, UUID(suite_id))
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if suite is None:
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return
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provider_name = task.provider or settings.image_provider
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generator = GENERATORS.get(provider_name)
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if generator is None:
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task.status = TASK_FAILED
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task.error = f"未知 provider: {provider_name}"
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return
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product = None
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if suite.product_id:
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product = await db.get(Product, suite.product_id)
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if product is None:
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suite.status = SUITE_FAILED
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suite.error = "商品不存在"
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await db.commit()
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return
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suite.status = SUITE_RUNNING
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await db.commit()
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provider_name = suite.provider or settings.image_provider
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generator = GENERATORS.get(provider_name)
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if generator is None:
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suite.status = SUITE_FAILED
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suite.error = f"未知 provider: {provider_name}"
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await db.commit()
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return
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raw = suite.context if not product else (product.raw or {})
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ctx = build_context(raw or {}, fallback_name=product.name if product else "")
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model = suite.model or {
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"tongyi": settings.dashscope_model,
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"rightapi": settings.rightapi_image_model,
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}.get(provider_name, settings.ark_image_model)
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is_wan = provider_name == "tongyi" and _is_wan_model(model)
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size = _image_size(provider_name, suite.ratio, is_wan=is_wan, model=model)
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# 任务列表：方案（逐张）优先，旧路径按 types
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if suite.plan:
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jobs = [dict(j) for j in suite.plan]
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else:
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jobs = [
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{"kind": t, "title": type_name(t), "detail": "", "prompt_hint": "", "variant_name": None}
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for t in (suite.types or [])
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]
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ctx = build_context(task.context or {}, fallback_name="")
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model = task.model or {
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"tongyi": settings.dashscope_model,
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"rightapi": settings.rightapi_image_model,
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}.get(provider_name, settings.ark_image_model)
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is_wan = provider_name == "tongyi" and _is_wan_model(model)
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size = _image_size(provider_name, task.ratio, is_wan=is_wan, model=model)
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jobs = [dict(j) for j in task.plan]
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async with _GEN_LOCK:
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task.status = TASK_RUNNING
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ok, failed = 0, 0
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failures: list[str] = []
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for job in jobs:
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type_id = job["kind"]
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image_row = SuiteImage(
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suite_id=suite.id,
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type_id=type_id,
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name=job.get("title") or type_name(type_id),
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status=STATUS_FAILED,
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)
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db.add(image_row)
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await db.flush()
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image = TaskImage(type_id=type_id, name=job.get("title") or type_name(type_id))
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task.images.append(image)
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try:
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prompt = build_prompt(
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type_id, ctx, suite.style_set, suite.lang,
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extra=job, style_prompt=suite.style_prompt, requirements=suite.requirements,
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type_id, ctx, task.style_set, task.lang,
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extra=job, style_prompt=task.style_prompt, requirements=task.requirements,
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)
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# gpt-image edits 语义：商品冻结契约前置，防止风格词改商品
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# gpt-image edits 语义：商品冻结契约前置（含商品文字锚定），防止风格词改商品
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if provider_name == "rightapi":
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prompt = wrap_prompt_for_gpt_edits(prompt)
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if product:
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refs = await _select_ref_images(db, product.id, type_id)
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else:
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refs = _refs_for_job(list(suite.ref_images or []), job)
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prompt = wrap_prompt_for_gpt_edits(prompt, ctx)
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refs = _refs_for_job(list(task.ref_images or []), job)
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data = await generator(prompt, refs, size=size, model=model)
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# 部分中转不遵守 output_format（要 jpeg 回 PNG），按魔数定扩展名
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ext = ".png" if data[:8] == b"\x89PNG\r\n\x1a\n" else ".jpg"
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key = storage.write_bytes(data, key_prefix=f"suites/{suite.id}", ext=ext)
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image_row.stored_url = storage.public_url(key)
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image_row.status = STATUS_OK
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key = storage.write_bytes(data, key_prefix=f"suites/{task.id}", ext=ext)
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image.url = storage.public_url(key)
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image.status = IMG_OK
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ok += 1
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except Exception as exc: # noqa: BLE001
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log.exception("套图 %s 类型 %s 生成失败", suite_id, type_id)
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err = str(exc)[:500]
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image_row.error = err
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failures.append(f"{job.get('title') or type_name(type_id)}：{err[:200]}")
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log.exception("套图 %s 类型 %s 生成失败", task.id, type_id)
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image.error = str(exc)[:500]
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failures.append(f"{job.get('title') or type_name(type_id)}：{str(exc)[:200]}")
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failed += 1
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await db.commit()
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suite.status = SUITE_DONE if failed == 0 else (SUITE_PARTIAL if ok > 0 else SUITE_FAILED)
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task.status = TASK_DONE if failed == 0 else (TASK_PARTIAL if ok > 0 else TASK_FAILED)
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if failed:
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uniq = list(dict.fromkeys(failures)) # 去重保序
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detail = "；".join(uniq[:6])
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if len(uniq) > 6:
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detail += f"；…等共 {failed} 张失败"
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if ok == 0:
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suite.error = f"全部生成失败。{detail}"
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task.error = f"全部生成失败。{detail}"
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else:
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suite.error = f"部分生成失败（{failed} 张）。{detail}"
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from datetime import datetime, timezone
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suite.finished_at = datetime.now(timezone.utc)
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if product:
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product.stage = "generated" # 商品路径才有的阶段升级
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await db.commit()
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task.error = f"部分生成失败（{failed} 张）。{detail}"
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+47
-50
@@ -17,47 +17,28 @@ import re
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STYLE_SETS: dict[int, dict] = {
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1: {
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"name": "高级质感大片",
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"tone": "高端电商大片质感，柔和的方向性棚拍光，背景带细腻的浅渐变，材质纹理清晰可见，"
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"色彩层次高级克制，商业画册级品质，构图干净、留白充足",
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"name": "北欧极简",
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"tone": "北欧极简风：浅灰或米白背景，柔和漫射光，低饱和色调，画面留白充足，构图克制干净",
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"bg": "",
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},
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2: {
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"name": "清新生活场景",
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"tone": "明亮通透的生活场景摄影，自然窗光，柔和的低饱和居家环境，浅景深虚化，"
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"真实自然的氛围感，绿植与暖色织物点缀，温馨有人气",
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"name": "清新明亮",
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"tone": "清新明亮风：明亮的白色到浅蓝渐变背景，高调光线，色彩明快通透，整体轻盈干净",
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"bg": "",
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},
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3: {
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"name": "极简白底规范",
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"tone": "极简棚拍风格，纯净无缝的浅色背景，柔和均匀的无影布光，以商品为中心的严谨构图，"
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"安静的高级感，画面只保留轻微的自然接触投影",
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"name": "高级感深色",
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"tone": "高级质感风：深灰或炭黑背景，戏剧性侧光打光，突出商品材质与光泽，沉稳高级",
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"bg": "",
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},
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4: {
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"name": "炫彩促销风",
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"tone": "高能量促销风格，高饱和度色块背景搭配动感几何图形，强对比，节日大促海报氛围，"
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"构图抢眼、视觉冲击力强",
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"name": "暖调生活",
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"tone": "温暖生活风：暖米色背景，暖色灯光氛围，温馨的家居质感，亲和力强",
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"bg": "",
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},
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5: {
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"name": "暗调轻奢",
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"tone": "暗调轻奢质感，深炭灰色背景，轮廓光勾勒商品边缘，材质细节丰富，带轻微雾感，"
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"如美术馆展陈般的呈现",
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"bg": "",
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},
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6: {
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"name": "俄式风情",
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"tone": "俄式风情电商大片，浓郁温暖的色调，红与金的传统配色点缀，冬日节庆氛围，"
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"深色木质与毛毡织物背景，如暖炉烛光般的柔和光晕，厚重扎实的质感，"
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"带一丝巴洛克式的华丽细节，适合俄语区市场",
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"bg": "",
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},
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7: {
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"name": "北欧极简",
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"tone": "北欧极简风格，白色与浅灰的原木空间，大量自然漫射光，干净利落的线条，"
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"浅色木质背景点缀少量绿植，克制的中性配色，画面通透轻盈，"
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"舒适宁静的氛围",
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"name": "纯净棚拍",
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"tone": "标准电商棚拍：纯色浅背景，均匀的正面柔光，无杂物干扰，商品居中突出",
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"bg": "",
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},
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}
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@@ -121,33 +102,49 @@ DEFAULT_NEGATIVE_INTENT = (
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# "主体参考"），风格词会被字面执行到商品上。按 OpenAI 官方提示词指南的编辑模式：
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# 按序号说明输入图、PRESERVE/MAY CHANGE 分列、首尾重申不变量、文案逐字渲染。
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GPT_EDITS_CONTRACT = (
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"INPUT IMAGES: Image 1 (and Image 2 if present) are reference photos of ONE product "
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"from different angles. Use them ONLY as the source of the product's true appearance.\n"
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"PRESERVE (frozen, never change): the product itself — silhouette, proportions, colors, "
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"print/pattern (keep stripes / logos / labels exactly), materials, texture, stitching, "
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"hardware and every design detail. The product in the output must be the same physical "
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"item as in the input images, merely photographed in a new setting.\n"
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"MAY CHANGE: background, scene, props, camera angle, lighting, composition "
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"and in-image marketing typography.\n"
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"STYLE SCOPE: all style, mood, color-palette and decoration instructions below describe "
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"the SCENE AND BACKGROUND ONLY — never apply them to the product itself. "
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"Do not restyle, recolor, re-pattern or redecorate the product. "
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"You may relight the product so it sits naturally in the new scene "
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"(matched shadows and color temperature), but never change its design, colors or pattern."
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)
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def gpt_edits_contract(ctx: dict) -> str:
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"""gpt-image edits 语义契约（放开头，指令权重最高处）。
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|
||||
除通用锁定条款外，注入商品文字锚定（标题 + 关键参数 + 描述）：
|
||||
官逆通道（gpt-image-2-vip 等）会把参考图当对话附件弱化处理，
|
||||
input_fidelity 类 API 参数不生效，此时商品文字描述是保真的唯一兜底。
|
||||
"""
|
||||
anchor = f" The product is: \"{ctx['title']}\""
|
||||
if ctx.get("params_line"):
|
||||
anchor += f" (key specs: {ctx['params_line']})"
|
||||
if ctx.get("desc"):
|
||||
anchor += f". {ctx['desc']}"
|
||||
return (
|
||||
"TASK: Edit the attached product photos — re-photograph THE SAME physical product "
|
||||
"in a new setting. This is an edit of the input images, NOT a new product design.\n"
|
||||
"INPUT IMAGES: Image 1 = product front view (PRIMARY source of truth for the product's "
|
||||
f"true appearance); Image 2 (if present) = product back / detail view.{anchor}\n"
|
||||
"PRODUCT LOCK (highest priority, overrides everything else in this prompt): exactly "
|
||||
"preserve the product's shape, silhouette, proportions, colors, label text, logos, "
|
||||
"print/pattern, materials and texture. Do not redesign, restyle, recolor, re-pattern "
|
||||
"or substitute the product with a similar one. The output must show the very product "
|
||||
"from the input images AND match the product description above; if the generated "
|
||||
"product differs from either in any design detail, the image is rejected.\n"
|
||||
"MAY CHANGE: background, scene, props, camera angle, lighting, composition "
|
||||
"and in-image marketing typography only. You may relight the product so it sits "
|
||||
"naturally in the new scene (matched shadows and color temperature).\n"
|
||||
"STYLE SCOPE: all style, mood, color-palette and decoration instructions below describe "
|
||||
"the SCENE AND BACKGROUND ONLY — never apply them to the product. "
|
||||
"When any style instruction conflicts with product fidelity, product fidelity always wins."
|
||||
)
|
||||
|
||||
|
||||
GPT_EDITS_FINAL_CHECK = (
|
||||
"FINAL CHECK before output: if the product in your result differs from the input product in any "
|
||||
"design detail (shape, color, pattern, material, logo), the image is rejected. "
|
||||
"Render any listed marketing copy / headlines exactly as written (verbatim, no extra characters, "
|
||||
"no paraphrasing)."
|
||||
"FINAL CHECK before output: if the product in your result differs from the input product "
|
||||
"or the product description above in any design detail (shape, color, pattern, material, "
|
||||
"logo), the image is rejected. Render any listed marketing copy / headlines exactly as "
|
||||
"written (verbatim, no extra characters, no paraphrasing)."
|
||||
)
|
||||
|
||||
|
||||
def wrap_prompt_for_gpt_edits(prompt: str) -> str:
|
||||
def wrap_prompt_for_gpt_edits(prompt: str, ctx: dict) -> str:
|
||||
"""gpt-image edits 语义适配：契约放开头（指令权重最高处），终检放结尾。"""
|
||||
return f"{GPT_EDITS_CONTRACT}\n\n{prompt}\n\n{GPT_EDITS_FINAL_CHECK}"
|
||||
return f"{gpt_edits_contract(ctx)}\n\n{prompt}\n\n{GPT_EDITS_FINAL_CHECK}"
|
||||
|
||||
# ── 商品上下文提炼 ────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@@ -0,0 +1,68 @@
|
||||
"""内存任务注册表：套图生成任务的生命周期与进程一致（重启即新会话）。
|
||||
|
||||
轮询/导出只服务「当前会话正在跟踪的任务」——前端没有历史记录功能，
|
||||
任务状态无需跨进程持久化；重启后轮询自然 404，前端提示任务已中断。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
# 任务状态
|
||||
TASK_PENDING = "pending"
|
||||
TASK_RUNNING = "running"
|
||||
TASK_DONE = "done"
|
||||
TASK_PARTIAL = "partial"
|
||||
TASK_FAILED = "failed"
|
||||
|
||||
# 任务内单张图状态
|
||||
IMG_OK = "ok"
|
||||
IMG_FAILED = "failed"
|
||||
|
||||
|
||||
@dataclass
|
||||
class TaskImage:
|
||||
"""任务里单张生成图：完成一张追加一条（前端进度 x/y 依赖此语义）。"""
|
||||
|
||||
type_id: str
|
||||
name: str
|
||||
status: str = IMG_FAILED # 循环里先建后跑，成功后改为 ok
|
||||
url: str = ""
|
||||
error: str | None = None
|
||||
|
||||
|
||||
@dataclass
|
||||
class Task:
|
||||
"""一次套图生成任务：轮询可见字段 + 仅供 run_suite 消费的执行参数。"""
|
||||
|
||||
id: str
|
||||
status: str = TASK_PENDING
|
||||
platform: str = "cn"
|
||||
lang: str = "zh"
|
||||
ratio: str = "1:1"
|
||||
style_set: int = 1
|
||||
style_prompt: str | None = None
|
||||
requirements: str | None = None
|
||||
provider: str = ""
|
||||
model: str | None = None
|
||||
total: int = 0 # 计划总张数（进度分母）
|
||||
images: list[TaskImage] = field(default_factory=list)
|
||||
error: str | None = None
|
||||
# ── 执行参数（不进轮询响应）──
|
||||
context: dict = field(default_factory=dict) # 采集文本素材（build_context 的输入）
|
||||
plan: list[dict] = field(default_factory=list) # 展开后的逐张任务
|
||||
ref_images: list[dict] = field(default_factory=list) # 参考图池（main 优先）
|
||||
|
||||
|
||||
# 进程内任务表：asyncio 单事件循环读写，无并发问题；不做淘汰（单会话量级很小）
|
||||
_TASKS: dict[str, Task] = {}
|
||||
|
||||
|
||||
def create_task(**kwargs) -> Task:
|
||||
task = Task(id=uuid.uuid4().hex, **kwargs)
|
||||
_TASKS[task.id] = task
|
||||
return task
|
||||
|
||||
|
||||
def get_task(task_id: str) -> Task | None:
|
||||
return _TASKS.get(task_id)
|
||||
Reference in New Issue
Block a user