Create app.py

app.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import pipeline
+from typing import List
+
+app = FastAPI(
+   title = "Hate Speech Detection API",
+    description = "A simple API to classify text using the unitary/toxic-bert model.",
+    version = "1.0.0"
+)
+
+classifier= pipeline("text-classification" , model="unitary/toxic-bert", tokenizer="unitary/toxic-bert", device=-1)
+
+#writing pydantic models
+class TextInput(BaseModel):
+    text: str
+
+
+
+@app.get("/")
+def get_root():
+    return {"message": "Welcome to the Hate Speech Detection API!"}
+
+@app.post("/predict")
+def predict_toxicity(input: TextInput):
+    classifier_result = classifier(input.text)
+    prediction=list(classifier_result)[0]
+    final_prediction = {}
+    if prediction['score']>0.5:
+        final_prediction['label']='Toxic'
+        final_prediction['non-toxic-score']=1-prediction['score']
+        final_prediction['toxic-score']=prediction['score']
+    else:
+        final_prediction['label']='Non-Toxic'
+        final_prediction['non-toxic-score']=1- prediction['score']
+        final_prediction['toxic-score']=prediction['score']   
+    
+    return final_prediction
+
+
+
+
+
+
+