改进

Dockerfile

@@ -1,4 +1,4 @@
-# docker build . --platform linux/amd64 --push  -t leafdev.top/ecosystem/zero-shot-classification:v0.0.3
+# docker build . --platform linux/amd64 --push  -t leafdev.top/ecosystem/zero-shot-classification:v0.0.4
 FROM python:3.12.7
 
 #

classification.py

@@ -1,3 +1,5 @@
+from pprint import pprint
+
 from pydantic import BaseModel
 from transformers import pipeline
 from config import MODEL_ARGS
@@ -5,25 +7,27 @@ from config import MODEL_ARGS
 classifier = pipeline("zero-shot-classification", **MODEL_ARGS)
 
 
-# 返回一个结构化的内容
 class ClassifyResult(BaseModel):
     sequence: str
-    rank: list
-    scores: list
     prediction: str
+    prediction_score: float
+    ranks: list[str]
+    labels: list[str]
+    scores: list[float]
+
 
 
 def classify(text: str, labels: list):
     output = classifier(text, labels)
 
-    # pprint(output)
-
     # 根据 score，寻找最高的 label
     prediction_rank = output['scores'].index(max(output['scores']))
 
     return ClassifyResult(
         sequence=text,
-        rank=output['labels'],
+        prediction=output['labels'][prediction_rank],
+        prediction_score=output['scores'][prediction_rank],
+        ranks=output['labels'],
+        labels=labels,
         scores=output['scores'],
-        prediction=output['labels'][prediction_rank]
     )

main.py

@@ -1,7 +1,7 @@
 import uvicorn
 from fastapi import FastAPI
 from pydantic import BaseModel
-import classification
+from classification import ClassifyResult, classify as classifier
 from config import HTTP_ARGS
 
 app = FastAPI()
@@ -12,16 +12,15 @@ class TextClassificationRequest(BaseModel):
     labels: list[str]
 
 
-class TextClassificationResponse(BaseModel):
-    prediction: str
-    ranks: list[str]
+# class TextClassificationResponse(BaseModel):
+#     prediction: str
+#     ranks: list[str]
 
 
 @app.post("/classify")
-def classify(req: TextClassificationRequest) -> TextClassificationResponse:
-    result = classification.classify(req.text, req.labels)
+def classify(req: TextClassificationRequest) -> ClassifyResult:
 
-    return TextClassificationResponse(prediction=result.prediction, ranks=result.rank)
+    return classifier(req.text, req.labels)
 
 
 if __name__ == "__main__":

manifest.yaml

@@ -33,7 +33,7 @@ spec:
             claimName: text-classification-pvc
       containers:
         - name: text-classification
-          image: leafdev.top/ecosystem/zero-shot-classification:v0.0.1
+          image: leafdev.top/ecosystem/zero-shot-classification:v0.0.4
           env:
             - name: HF_DATASETS_CACHE
               value: "/app/models"