改进 模型加载以及增加 GPU 选择

Dockerfile

@@ -1,4 +1,4 @@
-# docker build . --platform linux/amd64 --push  -t leafdev.top/ecosystem/zero-shot-classification:v0.0.1
+# docker build . --platform linux/amd64 --push  -t leafdev.top/ecosystem/zero-shot-classification:v0.0.2
 FROM python:3.12.7
 
 #

classification.py

@@ -1,10 +1,8 @@
-from pprint import pprint
-
 from pydantic import BaseModel
 from transformers import pipeline
+from config import MODEL_ARGS
 
-classifier = pipeline("zero-shot-classification",
+classifier = pipeline("zero-shot-classification", **MODEL_ARGS)
-                      model="MoritzLaurer/mDeBERTa-v3-base-mnli-xnli")
 
 
 # 返回一个结构化的内容

config.py

@@ -0,0 +1,15 @@
+import os
+from pprint import pprint
+
+MODEL_ARGS = {
+    "model": "MoritzLaurer/mDeBERTa-v3-base-mnli-xnli",
+    "device": int(os.environ.get("GPU_DEVICE", -1))
+}
+
+HTTP_ARGS = {
+    "host": os.environ.get("HOST", "0.0.0.0"),
+    "port": int(os.environ.get("PORT", 8000))
+}
+
+pprint(MODEL_ARGS)
+pprint(HTTP_ARGS)

main.py

@@ -2,6 +2,7 @@ import uvicorn
 from fastapi import FastAPI
 from pydantic import BaseModel
 import classification
+from config import HTTP_ARGS
 
 app = FastAPI()
 
@@ -24,4 +25,4 @@ def classify(req: TextClassificationRequest) -> TextClassificationResponse:
 
 
 if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    uvicorn.run(app, **HTTP_ARGS)

manifest.yaml

@@ -45,6 +45,8 @@ spec:
               value: "/app/models"
             - name: HF_ENDPOINT
               value: "https://hf-mirror.com"
+            - name: GPU_DEVICE
+              value: "-1"
 #            - name: CUDA_VISIBLE_DEVICES
 #              value: "1"
           ports: