feat: AI炫图接入gpt-image-2.5云端生图(结构化提示词工程+照片参考合成)

2026-09-25 04:15:45 -07:00
parent 710b3521a2
commit 6726a9fa3a
12 changed files with 496 additions and 48 deletions
@@ -0,0 +1,107 @@
+"""AI 炫图路由：gpt-image 生图代理（Key 仅存后端），提示词由 drawing_data 结构化构建。
+
+- quick 模式: /v1/images/generations 纯提示词生成
+- photo 模式: /v1/images/edits 以用户照片为参考图，把窗型合成进照片
+"""
+import base64
+import json
+
+import httpx
+from fastapi import APIRouter
+from pydantic import BaseModel, Field
+
+from huamenchuang.core.config import settings
+from huamenchuang.core.deps import CurrentUser, DbSession
+from huamenchuang.core.response import fail, ok
+from huamenchuang.services.ai_prompt import build_prompt, describe_window, pick_size
+
+router = APIRouter(prefix="/ai-render", tags=["AI 炫图"])
+
+
+class AiRenderBody(BaseModel):
+    template_id: int | None = None
+    drawing_data: str | dict | None = None
+    mode: str = Field(default="quick", pattern="^(quick|photo)$")
+    style: str = Field(default="modern", pattern="^(modern|chinese|european|nordic)$")
+    time: str = Field(default="day", pattern="^(day|dusk|night)$")
+    # quick: indoor/outdoor/studio; photo: render/install/erase/indoor/villa/fence/blank
+    scene: str = "indoor"
+    photo_b64: str | None = Field(default=None, description="照片模式参考图(base64, 不带 dataURL 前缀)")
+
+
+async def _resolve_drawing(db, body: AiRenderBody) -> str | dict | None:
+    if body.drawing_data:
+        return body.drawing_data
+    if body.template_id:
+        from sqlalchemy import select
+        from huamenchuang.models.windoor_template import WindoorTemplate
+        t = (await db.execute(select(WindoorTemplate).where(
+            WindoorTemplate.id == body.template_id))).scalar_one_or_none()
+        return t.drawing_data if t else None
+    return None
+
+
+@router.post("/prompt")
+async def preview_prompt(body: AiRenderBody, user: CurrentUser, db: DbSession):
+    """提示词预览（前端可展开查看优化后的完整提示词）。"""
+    drawing = await _resolve_drawing(db, body)
+    if drawing is None:
+        return fail("未找到图纸数据")
+    try:
+        info = describe_window(drawing)
+        prompt = build_prompt(drawing, body.style, body.time, body.scene)
+    except Exception:
+        return fail("图纸数据解析失败")
+    return ok(data={"features": info, "prompt": prompt,
+                    "size": pick_size(info["width_mm"], info["height_mm"])})
+
+
+@router.post("/generate")
+async def generate(body: AiRenderBody, user: CurrentUser, db: DbSession):
+    """云端 AI 生图（gpt-image）：quick=生成 / photo=参考图编辑。"""
+    if not settings.ai_api_key:
+        return fail("AI 生图服务未配置(HMC_AI_API_KEY)")
+    drawing = await _resolve_drawing(db, body)
+    if drawing is None:
+        return fail("未找到图纸数据")
+    if body.mode == "photo" and not body.photo_b64:
+        return fail("照片模式需要上传参考照片")
+    try:
+        info = describe_window(drawing)
+        prompt = build_prompt(drawing, body.style, body.time, body.scene)
+        size = pick_size(info["width_mm"], info["height_mm"])
+    except Exception:
+        return fail("图纸数据解析失败")
+
+    base = settings.ai_base_url.rstrip("/")
+    headers = {"Authorization": f"Bearer {settings.ai_api_key}"}
+    timeout = httpx.Timeout(settings.ai_timeout, connect=15)
+    try:
+        async with httpx.AsyncClient(timeout=timeout) as client:
+            if body.mode == "photo":
+                img_bytes = base64.b64decode(body.photo_b64.split(",")[-1])
+                resp = await client.post(
+                    f"{base}/v1/images/edits", headers=headers,
+                    data={"model": settings.ai_model, "prompt": prompt, "size": size, "n": "1"},
+                    files={"image[]": ("photo.png", img_bytes, "image/png")})
+            else:
+                resp = await client.post(
+                    f"{base}/v1/images/generations", headers=headers,
+                    json={"model": settings.ai_model, "prompt": prompt, "n": 1, "size": size})
+        resp.raise_for_status()
+        data = resp.json()
+        item = (data.get("data") or [{}])[0]
+        b64 = item.get("b64_json")
+        if not b64:
+            return fail(f"生图服务返回异常: {str(data)[:200]}")
+    except httpx.TimeoutException:
+        return fail("AI 生图超时，请稍后重试")
+    except httpx.HTTPStatusError as e:
+        detail = e.response.text[:200] if e.response is not None else ""
+        return fail(f"生图服务错误({e.response.status_code if e.response else '?'}): {detail}")
+    except Exception as e:
+        return fail(f"生图失败: {str(e)[:150]}")
+    return ok(data={"image_b64": b64, "prompt": prompt, "size": size,
+                    "features": {"width_mm": info["width_mm"], "height_mm": info["height_mm"],
+                                 "summary": info["summary"]}},
+              message="生成成功")