app.py

import uvicorn
import pickle
from fastapi import FastAPI
from pydantic import BaseModel
from fastapi.middleware.cors import CORSMiddleware

app = FastAPI()

origins = [
    "*"
]

app.add_middleware(
    CORSMiddleware,
    allow_origins=origins,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


class Music(BaseModel):
    acousticness: float
    danceability: float
    energy: float
    instrumentalness: float
    liveness: float
    speechiness: float
    tempo: float
    valence: float


with open("./model/model.pkl", "rb") as f:
    model = pickle.load(f)


@app.get('/')
def index():
    return {'message': 'This is the homepage of the API '}


@app.post('/prediction')
def get_music_category(data: Music):
    received = data.dict()
    acousticness = received['acousticness']
    danceability = received['danceability']
    energy = received['energy']
    instrumentalness = received['instrumentalness']
    liveness = received['liveness']
    speechiness = received['speechiness']
    tempo = received['tempo']
    valence = received['valence']
    pred_name = model.predict([[acousticness, danceability, energy,
                                instrumentalness, liveness, speechiness, tempo, valence]]).tolist()[0]
    return {'prediction': pred_name}


@app.get('/predict')
def get_cat(acousticness: float, danceability: float, energy: float, instrumentalness: float, liveness: float, speechiness: float, tempo: float, valence: float):
    pred_name = model.predict([[acousticness, danceability, energy,
            instrumentalness, liveness, speechiness, tempo, valence]]).tolist()[0]
    return {'prediction': pred_name}



if __name__ == '__main__':
    uvicorn.run(app, host='127.0.0.1', port=4000, debug=True)