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import os
from fastapi import FastAPI, Request
from pydantic import BaseModel
from transformers import pipeline
# ✅ Set cache to writable directory
os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf_cache"
app = FastAPI()
# Load model once when the app starts
classifier = pipeline("zero-shot-classification", model="syedkhalid076/DeBERTa-Zero-Shot-Classification")
# Request body model
class ClassificationRequest(BaseModel):
text: str
@app.post("/classify")
async def classify(request: ClassificationRequest):
candidate_labels = ["contains electronic components", "doesn't contain electronic components"]
result = classifier(request.text, candidate_labels, multi_label=False)
return {"labels": result["labels"], "scores": result["scores"]}
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