From 8991927cd90b842a4bde48ce4268af3a7f32a95c Mon Sep 17 00:00:00 2001 From: zcr Date: Mon, 23 Mar 2026 10:18:30 +0800 Subject: [PATCH] 1 --- app/litserve/client.py | 17 ------------- app/{litserve => litserve_app}/app.py | 0 app/{litserve => litserve_app}/cli.py | 0 app/litserve_app/client.py | 16 ++++++++++++ app/{litserve => litserve_app}/model.py | 0 app/litserve_serve.py | 33 +++++-------------------- 6 files changed, 22 insertions(+), 44 deletions(-) delete mode 100755 app/litserve/client.py rename app/{litserve => litserve_app}/app.py (100%) rename app/{litserve => litserve_app}/cli.py (100%) create mode 100755 app/litserve_app/client.py rename app/{litserve => litserve_app}/model.py (100%) diff --git a/app/litserve/client.py b/app/litserve/client.py deleted file mode 100755 index 8f03a5f..0000000 --- a/app/litserve/client.py +++ /dev/null @@ -1,17 +0,0 @@ -import requests -import base64 - -# 将你的图片转为 base64 -with open("/mnt/data/workspace/Code/flux2/20260123_152354_2steps.png", "rb") as f: - img_base64 = base64.b64encode(f.read()).decode("utf-8") - -response = requests.post("http://localhost:8451/predict", json={ - # "image": img_base64, - "prompt": "紫色实木窗帘", - "aspect_ratio": "1:1", - "steps": 4 -}) - -# 保存结果 -with open("result.png", "wb") as f: - f.write(base64.b64decode(response.json()["image"])) diff --git a/app/litserve/app.py b/app/litserve_app/app.py similarity index 100% rename from app/litserve/app.py rename to app/litserve_app/app.py diff --git a/app/litserve/cli.py b/app/litserve_app/cli.py similarity index 100% rename from app/litserve/cli.py rename to app/litserve_app/cli.py diff --git a/app/litserve_app/client.py b/app/litserve_app/client.py new file mode 100755 index 0000000..f094747 --- /dev/null +++ b/app/litserve_app/client.py @@ -0,0 +1,16 @@ +import httpx +import asyncio + + +async def main(): + async with httpx.AsyncClient() as client: + response = await client.post( + "http://localhost:8451/predict", + json={ + "prompt": "紫色实木窗帘", + } + ) + print(response.json()) + + +asyncio.run(main()) diff --git a/app/litserve/model.py b/app/litserve_app/model.py similarity index 100% rename from app/litserve/model.py rename to app/litserve_app/model.py diff --git a/app/litserve_serve.py b/app/litserve_serve.py index fa7e6cf..b302e98 100755 --- a/app/litserve_serve.py +++ b/app/litserve_serve.py @@ -1,10 +1,10 @@ +import logging import uuid import torch from minio import Minio import litserve as ls -from PIL import Image import io from diffusers import Flux2KleinPipeline @@ -13,21 +13,6 @@ from app.utils.new_oss_client import oss_get_image, oss_upload_image, MINIO_URL, minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) -# 保持原有的辅助函数 -def aspect_to_wh(aspect_ratio: str, base_long_edge: int) -> tuple[int, int]: - w_str, h_str = aspect_ratio.split(":") - w, h = float(w_str), float(h_str) - if w >= h: - width = base_long_edge - height = int(round(base_long_edge * (h / w))) - else: - height = base_long_edge - width = int(round(base_long_edge * (w / h))) - width = max(64, (width // 8) * 8) - height = max(64, (height // 8) * 8) - return width, height - - class FluxKleinAPI(ls.LitAPI): def setup(self, device): # 1. 模型初始化 @@ -42,7 +27,7 @@ class FluxKleinAPI(ls.LitAPI): ) self.pipe.to(device) - def decode_request(self, request): + async def decode_request(self, request): """ 解析请求参数并加载OSS图片的接口函数 @@ -67,8 +52,6 @@ class FluxKleinAPI(ls.LitAPI): 推理步数，控制模型生成过程的迭代次数 - guidance : float (可选，默认值4.0) 引导系数，调节提示词对生成结果的影响程度 - - seed : int (可选，默认值42) - 随机种子，保证生成结果的可复现性 返回值说明 ------- @@ -80,7 +63,6 @@ class FluxKleinAPI(ls.LitAPI): - prompt: 文本提示词（默认空字符串） - steps: 推理步数（默认28） - guidance: 引导系数（默认4.0） - - seed: 随机种子（默认42） - height: 图片高度（默认512） - width: 图片宽度（默认512） @@ -106,19 +88,15 @@ class FluxKleinAPI(ls.LitAPI): "prompt": request.get("prompt", ""), "steps": request.get("steps", 4), "guidance": request.get("guidance", 4.0), - "seed": request.get("seed", 42), "height": H, "width": W } - @torch.inference_mode() - def predict(self, payload): + async def predict(self, payload): # 3. 执行推理逻辑 images = payload.get("images", []) prompt = payload.get("prompt", "") gen = torch.Generator(device=self.device) - seed = gen.seed() - print(f"本次使用的随机种子是: {seed}") if images: output = self.pipe( image=images, @@ -144,14 +122,15 @@ class FluxKleinAPI(ls.LitAPI): 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 - def encode_response(self, output_path): + async def encode_response(self, output_path): return {"output_path": output_path} if __name__ == "__main__": # 启动服务器 - api = FluxKleinAPI() + api = FluxKleinAPI(enable_async=True) server = ls.LitServer(api, accelerator="cuda", devices=1) server.run(port=8451)