import uvicorn as uvicorn
from fastapi import FastAPI


'''
python code to call api:
response = requests.get("http://127.0.0.1:8000/{}".format(search_input))
emotion = response.json()["label"]
'''

api = FastAPI()

@api.get("/{input}")
def predict(input: str):
    label1 = "wait and see"
    label2 = "again"
    return {"label1": label1, "label2":label2}





cbc486ae8969ee3e021972ede13d4361f7faf82c
<mask token>

<mask token>


@api.get('/{input}')
def predict(input: str):
    label1 = 'wait and see'
    label2 = 'again'
    return {'label1': label1, 'label2': label2}

<mask token>
api = FastAPI()


@api.get('/{input}')
def predict(input: str):
    label1 = 'wait and see'
    label2 = 'again'
    return {'label1': label1, 'label2': label2}

import uvicorn as uvicorn
from fastapi import FastAPI
<mask token>
api = FastAPI()


@api.get('/{input}')
def predict(input: str):
    label1 = 'wait and see'
    label2 = 'again'
    return {'label1': label1, 'label2': label2}

import uvicorn as uvicorn
from fastapi import FastAPI


'''
python code to call api:
response = requests.get("http://127.0.0.1:8000/{}".format(search_input))
emotion = response.json()["label"]
'''

api = FastAPI()

@api.get("/{input}")
def predict(input: str):
    label1 = "wait and see"
    label2 = "again"
    return {"label1": label1, "label2":label2}




