javascript代码-

<script>
   async function postFormDataAsJson({ url, formData }) {
    const plainFormData = Object.fromEntries(formData.entries());
    console.log(plainFormData)
    const formDataJsonString = JSON.stringify(plainFormData);
    console.log(formDataJsonString)
    console.log(typeof formDataJsonString)
    const fetchOptions = {
        mode:"no-cors",
        method: "POST",
        headers: {
            "accept": "application/json",
            "Content-Type": "application/json"
        },
        body: formDataJsonString
    };
    const response = await fetch(url, fetchOptions);

    if (!response.ok) {
        const errorMessage = await response.text();
        throw new Error(errorMessage);
    }

    return response.json();
}

async function handleFormSubmit(event) {
    event.preventDefault();

    const form = event.currentTarget;
    const url = "http://127.0.0.1:8000/predict_diabetes";

    try {
        const formData = new FormData(form);
        const responseData = await postFormDataAsJson({ url, formData });

        console.log({ responseData });
    } catch (error) {
        console.error(error);
    }
}

const Form = document.getElementById("form");
Form.addEventListener("submit", handleFormSubmit);

</script>

PYDANTIC代码：其位于单独的文件diabetes_data. py中。

from pydantic import BaseModel
class Diabetes(BaseModel):
    Pregnancies : int
    Glucose : int
    BloodPressure : int
    SkinThickness : int
    Insulin : int
    BMI : int
    DiabetesPedigreeFunction : int
    Age : int

FASTAPI代码：

import numpy as np
import pickle
import pandas as pd
import uvicorn
from fastapi import FastAPI
from diabetes_data import Diabetes
from sklearn.preprocessing import StandardScaler

app = FastAPI()

pickle_in = open("svc_model.pkl","rb")
classifier=pickle.load(pickle_in)

sc = StandardScaler()

@app.post('/predict_diabetes')
def predict_diabetes(data:Diabetes):
    data = data.dict()
    Pregnancies = data['Pregnancies']
    Glucose = data['Glucose']
    BloodPressure = data['BloodPressure']
    SkinThickness = data['SkinThickness']
    Insulin = data['Insulin']
    BMI = data['BMI']
    DiabetesPedigreeFunction = data['DiabetesPedigreeFunction']
    Age = data['Age']
    
    data = sc.fit_transform([[Pregnancies,Glucose,BloodPressure,SkinThickness,Insulin,BMI,DiabetesPedigreeFunction,Age]])
    
    prediction = classifier.predict(data)
    
    if(prediction[0]>0.5):
        prediction="Diabetic"
    else:
        prediction="Not Diabetic"
    return {'prediction': prediction}


if __name__ == '__main__':
    uvicorn.run(app, host='127.0.0.1', port=8000)

将console.log输出复制粘贴到docs上，它工作，但通过javascript发送时不工作。enter image description hereenter image description here
我试图发送表单数据。我首先将表单数据转换成json字符串并使用javascript获取。但得到错误422，但使用快速API文档时一切正常。