1

app/litserve_serve.py

@@ -35,6 +35,8 @@ class FluxKleinAPI(ls.LitAPI):
         ----------
         request : dict
             核心请求参数字典，各字段说明如下：
+            - num_images_per_prompt = 1,
+                生成图片数量
             - input_image_paths : list[str] | None (可选)
               OSS图片路径列表，格式为 "bucket/object_name"（如 "test/typical_b/uildi/ng_space_station.png"）
               若不传则为None，会导致后续图片加载失败，建议必传
@@ -61,6 +63,7 @@ class FluxKleinAPI(ls.LitAPI):
             - object_name: 请求中的对象名（None/字符串）
             - images: 从OSS加载的图片列表（按input_image_paths顺序）
             - prompt: 文本提示词（默认空字符串）
+            - num_images_per_prompt: 生成图片数量 默认为1
             - steps: 推理步数（默认28）
             - guidance: 引导系数（默认4.0）
             - height: 图片高度（默认512）
@@ -72,6 +75,7 @@ class FluxKleinAPI(ls.LitAPI):
         - 若OSS图片加载失败（如路径不存在），oss_get_image会抛出对应异常
         """
         input_image_paths = request.get("input_image_paths", None)
+        num_images_per_prompt = request.get("num_images_per_prompt", 1)
         W = request.get("width", 512)
         H = request.get("height", 512)
         images = []
@@ -83,13 +87,14 @@ class FluxKleinAPI(ls.LitAPI):
                 images.append(image)
         return {
             "bucket_name": request.get("bucket_name", "test"),
-            "object_name": request.get("object_name", f"fida_generate_image/{uuid.uuid4().hex}.png"),
+            "object_name": request.get("object_name", f"fida_generate_image/{uuid.uuid4().hex}"),
             "images": images,
             "prompt": request.get("prompt", ""),
             "steps": request.get("steps", 4),
             "guidance": request.get("guidance", 4.0),
             "height": H,
-            "width": W
+            "width": W,
+            "num_images_per_prompt": num_images_per_prompt
         }
 
     async def predict(self, payload):
@@ -100,35 +105,43 @@ class FluxKleinAPI(ls.LitAPI):
         seed = gen.seed()
         print(f"本次使用的随机种子是: {seed}")
         if images:
-            output = self.pipe(
+            outputs = self.pipe(
                 image=images,
+                num_images_per_prompt=payload["num_images_per_prompt"],
                 prompt=prompt,
                 height=payload.get("height", 512),
                 width=payload.get("width", 512),
                 guidance_scale=payload["guidance"],
                 num_inference_steps=payload["steps"],
                 generator=gen,
-            ).images[0]
+            ).images
         else:
-            output = self.pipe(
+            outputs = self.pipe(
                 prompt=prompt,
+                num_images_per_prompt=payload["num_images_per_prompt"],
                 height=payload.get("height", 512),
                 width=payload.get("width", 512),
                 guidance_scale=payload["guidance"],
                 num_inference_steps=payload["steps"],
                 generator=gen,
-            ).images[0]
-        image_data = io.BytesIO()
-        output.save(image_data, format='PNG')
-        image_data.seek(0)
-        image_bytes = image_data.read()
-        req = oss_upload_image(oss_client=minio_client, bucket=payload.get("bucket_name", "test"), object_name=payload.get("object_name", f"fida_generate_image/{uuid.uuid4().hex}.png"), image_bytes=image_bytes)
-        output_path = req.bucket_name + "/" + req.object_name
-        logging.info(f"output_path :{output_path}")
-        return output_path
+            ).images
+        outputs_path = []
 
-    async def encode_response(self, output_path):
-        return {"output_path": output_path}
+        object_name = payload.get("object_name", f"fida_generate_image/{uuid.uuid4().hex}")
+
+        for i, output in enumerate(outputs):
+            image_data = io.BytesIO()
+            output.save(image_data, format='PNG')
+            image_data.seek(0)
+            image_bytes = image_data.read()
+            req = oss_upload_image(oss_client=minio_client, bucket=payload.get("bucket_name", "test"), object_name=f"{object_name}-{i}.png", image_bytes=image_bytes)
+            output_path = req.bucket_name + "/" + req.object_name
+            outputs_path.append(output_path)
+        logging.info(f"outputs_path :{outputs_path}")
+        return outputs_path
+
+    async def encode_response(self, outputs_path):
+        return {"output_path": outputs_path}
 
 
 if __name__ == "__main__":