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