新增flux2 klein 图像生成模型

src/core/config.py

@@ -34,6 +34,7 @@ class Settings(BaseSettings):
 
     # ---  本地服务器配置信息 ---
     IMAGE_TO_3D_MODEL_URL: str = Field(default='', description="")
+    FLUX2_GEN_IMG_MODEL_URL: str = Field(default='', description="")
 
     # ---  外部工具api配置信息 ---
     TAVILY_API_KEY: str = Field(default="", description="")

src/routers/flux2_gen_img.py

@@ -0,0 +1,72 @@
+import json
+import logging
+import httpx
+from fastapi import APIRouter
+
+from src.core.config import settings
+from src.schemas.flux2_gen_img import Flux2_Gen_Img_Model
+from src.schemas.response_template import ResponseModel
+
+logger = logging.getLogger(__name__)
+router = APIRouter(prefix="/canvas", tags=["Furniture Canvas"])
+
+
+@router.post("/flux2_gen_img")
+async def flux2_gen_img(request_data: Flux2_Gen_Img_Model):
+    """
+    ### 参数说明:
+
+    - **bucket_name**: OSS桶名 (必填)
+    - **object_name**: OSS对象名（文件路径）(必填)
+
+    - **input_image_paths**: 输入图片路径列表  (非必填,默认[])
+    - **width**: 图片宽度，默认512像素 (非必填,默认512)
+    - **height**: 图片高度，默认512像素 (非必填,默认512)
+    - **prompt**: 文本提示词，用于模型推理等场景 (非必填,默认"")
+    - **steps**: 推理步数，控制模型生成过程的迭代次数 (非必填,默认4)
+    - **guidance**: 引导系数，调节提示词对生成结果的影响程度 (非必填,默认 4.0 )
+
+    ### 请求体示例:
+    ```
+        {
+            "input_image_paths": ["test/typical_building_space_station.png","test/typical_creature_dragon.png"],
+            "width": 512,
+            "height": 512,
+            "bucket_name": "my-oss-bucket",
+            "object_name": "generated_images/result.jpg",
+            "prompt": "a beautiful landscape with mountains and rivers",
+            "steps": 4,
+            "guidance": 4.0
+        }
+    ````
+
+    ### 输出示例:
+    ```
+        {
+          "code": 200,
+          "msg": "OK!",
+          "data": {
+            "output_path": "test/generated_images/result.jpg"
+          }
+        }
+    ```
+    """
+    try:
+        logger.info(
+            f"flux2_gen_img request: {json.dumps(request_data.model_dump(), indent=4)}"
+        )
+
+        async with httpx.AsyncClient(timeout=120) as client:
+            resp = await client.post(
+                f"http://{settings.FLUX2_GEN_IMG_MODEL_URL}/predict",
+                json=request_data.model_dump(),
+            )
+
+        result = resp.json()
+
+        logger.info(f"flux2_gen_img response: {json.dumps(result, indent=4)}")
+
+        return ResponseModel(data=result)
+
+    except Exception as e:
+        logger.warning(f"img_to_3D Run Exception: {e}")

src/schemas/flux2_gen_img.py

@@ -0,0 +1,14 @@
+from typing import List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class Flux2_Gen_Img_Model(BaseModel):
+    input_image_paths: Optional[List[str]] = Field(..., description="输入图片路径列表")
+    width: Optional[int] = Field(default=512, description="图片宽度，默认512像素")
+    height: Optional[int] = Field(default=512, description="图片高度，默认512像素")
+    bucket_name: Optional[str] = Field(default="", description="OSS桶名，不传则为None")
+    object_name: Optional[str] = Field(default="", description="OSS对象名（文件路径），不传则为None")
+    prompt: Optional[str] = Field(default="", description="文本提示词，用于模型推理等场景")
+    steps: Optional[int] = Field(default=4, description="推理步数，控制模型生成过程的迭代次数")
+    guidance: Optional[float] = Field(default=4.0, description="引导系数，调节提示词对生成结果的影响程度")