app.py

from fastapi import FastAPI
from pydantic import BaseModel

import joblib
import pandas as pd
import maven_text_preprocessing

app = FastAPI()

class ClassificationRequest(BaseModel):
    message: str
    
@app.get("/")
def greet_json():
    return {"Hello": "World!"}

@app.post("/classify")
def sentiment_analysis(payload: ClassificationRequest):
    
    model = joblib.load("naive_bayes.joblib")
    vectorizer = joblib.load("vectorizer.joblib")

    clean_text = maven_text_preprocessing.clean_and_normalize(pd.Series([payload.message]))

    X = vectorizer.transform(clean_text)  # ⚠️ transform, NOT fit_transform

    category_list = ["Politics", "Sport", "Technology", "Entertainment", "Business"]
    
    predictions = model.predict(X)
    
    pred_prob = model.predict_proba(X)
    pred_prob = pred_prob.tolist()[0]
    
    return {
        category_list[0]: pred_prob[0],
        category_list[1]: pred_prob[1],
        category_list[2]: pred_prob[2],
        category_list[3]: pred_prob[3],
        category_list[4]: pred_prob[4]
    }