app.py

from fastapi import FastAPI
from pydantic import BaseModel
from calculator import calculate
from sentimentAnalysis import sentimentAnalysis
from customerSupport import customerConverstaion


class User_input(BaseModel):
    sentence:str
    operation:str
    x:float
    y:float



app = FastAPI()

@app.get("/hello")
def greet_json():
    return {"Hello": "World!"}


@app.post("/calculate")
def calculate_func(input:User_input):
    res= calculate(input.operation, input.x, input.y)
    return res

import requests
# def query(API_URL, headers, payload):
#         response = requests.post(API_URL, headers=headers, json=payload)
#         print(response)
#         return response
@app.post("/HFAPI")
def HF_API():
#     API_TOKEN=""
#     API_URL = "https://api-inference.huggingface.co/models/openai-community/gpt2"
#     headers = {"Authorization": f"Bearer {API_TOKEN}"}
    
#     data = query(API_URL,headers, {
# 	"inputs": "Can you please let us know more details about your ",
# })
    API_URL = "https://api-inference.huggingface.co/models/openai-community/gpt2"
    headers = {"Authorization": "Bearer ......................q"}
    def query(payload):
        response = requests.post(API_URL, headers=headers, json=payload)
        return response.json()
    output = query({
        "inputs": "Can you please let us know more details about India? ",
    })
    return output[0]["generated_text"]
        

@app.post("/sentimentAnalysis")
def sentimentAnalysis_func(input:User_input):
    res= sentimentAnalysis(input.sentence)
    return res

@app.post("/getReply")
def getReply_func(input:User_input):
    res= customerConverstaion(input.sentence)
    return res
@app.post("/hf_spaces")
def HF_interact():
    from huggingface_hub import HfApi
    # Initialize API client
    api = HfApi()

    # Replace these with your values
    repo_id = 'DSU-FDP/Sample-API'
    token = ''

    # Authenticate
   
    api.pause_space(repo_id=repo_id)


    # List all Spaces (not pausing, just showing how to interact)
    spaces = api.list_spaces()
    print(spaces)

    # Example action: delete a space (be cautious with this!)
    # api.delete_repo(repo_id, token=token)