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feat: 增加gpt-image-2 模型

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R524809
2026-08-17 17:28:02 +08:00
parent 9d15d8f784
commit e9d1eef07e
11 changed files with 162 additions and 17 deletions
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server/api/generate.py
+6 -2
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@@ -7,7 +7,8 @@ from config import get_settings
from db import get_db
from models import Suite
from schemas import (
GenerateRequest, PLATFORM_SPECS, SUPPORTED_TYPES, TONGYI_MODELS, SuiteCreateResponse, TextMaterial,
GenerateRequest, PLATFORM_SPECS, SUPPORTED_TYPES, TONGYI_MODELS, RIGHTAPI_MODELS,
SuiteCreateResponse, TextMaterial, resolve_provider,
PlanRequest, PlanResponse, PlanItemOut,
)
from services.generator import run_suite
@@ -84,10 +85,13 @@ async def generate_suite(
spec = PLATFORM_SPECS[req.platform]
settings = get_settings()
provider_name = req.provider or settings.image_provider
# 插件只传模型名：已知模型直接路由到对应 provider（gpt-image-2 → rightapi）
provider_name = resolve_provider(req.model, req.provider, settings.image_provider)
model = req.model
if provider_name == "tongyi" and model and model not in TONGYI_MODELS:
raise HTTPException(status_code=400, detail=f"不支持的模型: {model}（tongyi 支持: {TONGYI_MODELS}）")
if provider_name == "rightapi" and model and model not in RIGHTAPI_MODELS:
raise HTTPException(status_code=400, detail=f"不支持的模型: {model}（rightapi 支持: {RIGHTAPI_MODELS}）")
suite = Suite(
product_id=None,
style_set=req.style_set,
server/api/suites.py
+8 -2
View File
@@ -13,7 +13,10 @@ from sqlalchemy.ext.asyncio import AsyncSession
from config import get_settings
from db import get_db
from models import Product, ProductAsset, Suite, SuiteImage, STATUS_OK
from schemas import PLATFORM_SPECS, SUPPORTED_TYPES, TONGYI_MODELS, SuiteCreateRequest, SuiteCreateResponse, SuiteImageOut, SuiteOut
from schemas import (
PLATFORM_SPECS, SUPPORTED_TYPES, TONGYI_MODELS, RIGHTAPI_MODELS,
SuiteCreateRequest, SuiteCreateResponse, SuiteImageOut, SuiteOut, resolve_provider,
)
from services import storage
from services.generator import run_suite
@@ -76,9 +79,12 @@ async def create_suite(
spec = PLATFORM_SPECS[req.platform]
settings = get_settings()
provider_name = req.provider or settings.image_provider
# 模型名优先路由：已知模型直接定位 provider（gpt-image-2 → rightapi）
provider_name = resolve_provider(req.model, req.provider, settings.image_provider)
if provider_name == "tongyi" and req.model and req.model not in TONGYI_MODELS:
raise HTTPException(status_code=400, detail=f"不支持的模型: {req.model}（tongyi 支持: {TONGYI_MODELS}）")
if provider_name == "rightapi" and req.model and req.model not in RIGHTAPI_MODELS:
raise HTTPException(status_code=400, detail=f"不支持的模型: {req.model}（rightapi 支持: {RIGHTAPI_MODELS}）")
suite = Suite(
product_id=product.id,
style_set=req.style_set,
server/config.py
+6
View File
@@ -41,6 +41,12 @@ class Settings(BaseSettings):
dashscope_base_url: str = "" # 留空按模型自动选择万象异步/千问同步端点
dashscope_model: str = "wan2.7-image-pro"
# RightAPI（OpenAI 兼容中转，gpt-image 系列）
rightapi_api_key: str = ""
rightapi_base_url: str = "https://rightapi.ai/draw"
rightapi_image_model: str = "gpt-image-2"
rightapi_image_quality: str = "high" # auto | low | medium | high
# DeepSeek（出图方案规划器）
deepseek_api_key: str = ""
deepseek_base_url: str = "https://api.deepseek.com/v1"
server/main.py
+1
View File
@@ -50,6 +50,7 @@ async def health():
"provider": settings.image_provider,
"ark_configured": bool(settings.ark_api_key),
"dashscope_configured": bool(settings.dashscope_api_key),
"rightapi_configured": bool(settings.rightapi_api_key),
}
server/schemas.py
+16
View File
@@ -12,6 +12,22 @@ SUPPORTED_TYPES = [
# 通义（DashScope）生图模型白名单：插件下拉可选的模型
TONGYI_MODELS = ["qwen-image-3.0-pro", "wan2.7-image-pro"]
# RightAPI 生图模型白名单
RIGHTAPI_MODELS = ["gpt-image-2"]
# 模型 → provider 推断表：插件只传模型名，服务端据此路由（模型名优先于 provider 字段）
MODEL_PROVIDERS: dict[str, str] = {
**{m: "tongyi" for m in TONGYI_MODELS},
**{m: "rightapi" for m in RIGHTAPI_MODELS},
}
def resolve_provider(model: str | None, requested: str | None, default: str) -> str:
"""已知模型名直接定位 provider；未知模型回退到请求指定的 provider 或默认值。"""
if model and model in MODEL_PROVIDERS:
return MODEL_PROVIDERS[model]
return requested or default
# ── 采集上传 ──
server/services/generator.py
+73 -11
View File
@@ -46,6 +46,9 @@ 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"
@@ -70,27 +73,34 @@ def _bytes_to_data_uri(data: bytes, mime: str) -> str:
return f"data:{mime};base64,{base64.b64encode(data).decode()}"
async def _resolve_ref(url: str) -> str:
"""参考图 URL → data URI。本地 media 文件直读磁盘；远程 URL 带 Referer 下载。
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 base64 data URI 再进请求体。
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:"):
return url
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 _bytes_to_data_uri(path.read_bytes(), mime)
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 _bytes_to_data_uri(data, ctype)
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:
@@ -198,7 +208,56 @@ async def generate_tongyi(prompt: str, ref_images: list[str], size: str = "2048*
return dl.content
GENERATORS = {"doubao": generate_doubao, "tongyi": generate_tongyi}
# ── Provider：RightAPI（gpt-image，OpenAI 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/edits（multipart），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 ────────────────────────────────────────────────────────────
@@ -280,9 +339,10 @@ async def run_suite(suite_id: str) -> None:
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 (
settings.dashscope_model if provider_name == "tongyi" else settings.ark_image_model
)
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)
@@ -317,7 +377,9 @@ async def run_suite(suite_id: str) -> None:
else:
refs = _refs_for_job(list(suite.ref_images or []), job)
data = await generator(prompt, refs, size=size, model=model)
key = storage.write_bytes(data, key_prefix=f"suites/{suite.id}", ext=".jpg")
# 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