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from typing import Dict |
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from fastapi import Depends, FastAPI, HTTPException, Query |
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from pydantic import BaseModel |
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from .classifier.model import Model, get_model |
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app = FastAPI() |
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class SentimentResponse(BaseModel): |
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probabilities: Dict[str, float] |
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sentiment: str |
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confidence: float |
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@app.get("/") |
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def read_root(): |
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return {"TrueFoundry": "Internship Project"} |
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@app.post("/predict", response_model=SentimentResponse) |
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def predict(review:str = Query(None, title="Airline Review", decription="Enter the review for airline"), model: Model = Depends(get_model)): |
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if type(review) != str: |
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raise HTTPException(status_code=404, detail="Bad request") |
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sentiment, confidence, probabilities = model.predict(review) |
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return SentimentResponse( |
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sentiment=sentiment, confidence=confidence, probabilities=probabilities |
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) |
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