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This commit is contained in:
zcr
2026-03-30 17:21:28 +08:00
parent 453a8fa33e
commit 3ca77ce869
1 changed files with 16 additions and 29 deletions
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45
app/litserve_serve.py
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@@ -35,8 +35,6 @@ 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
@@ -63,7 +61,6 @@ 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）
@@ -75,7 +72,6 @@ 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 = []
@@ -87,14 +83,13 @@ 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}"),
"object_name": request.get("object_name", f"fida_generate_image/{uuid.uuid4().hex}.png"),
"images": images,
"prompt": request.get("prompt", ""),
"steps": request.get("steps", 4),
"guidance": request.get("guidance", 4.0),
"height": H,
"width": W,
"num_images_per_prompt": num_images_per_prompt
"width": W
}
async def predict(self, payload):
@@ -105,43 +100,35 @@ class FluxKleinAPI(ls.LitAPI):
seed = gen.seed()
print(f"本次使用的随机种子是: {seed}")
if images:
outputs = self.pipe(
output = 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
).images[0]
else:
outputs = self.pipe(
output = 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
outputs_path = []
).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
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}
async def encode_response(self, output_path):
return {"output_path": output_path}
if __name__ == "__main__":