const axios = require('axios'); 
const FormData = require('form-data'); 
const fs = require('fs'); 

const URL_ROOT = "https://api.kintsugihello.com/" 
// Initiate endpoint URL.
const URL_INITIATE = new URL('/v1/initiate', URL_ROOT) 
// Predict endpoint URL. 
const URL_PREDICT = new URL('/v1/predict/server/depression/binary', URL_ROOT) 
// Feedback endpoint URL. 
const URL_FEEDBACK = new URL ('/v1/feedback/server/depression/binary', URL_ROOT) 

async function initiate(api_key) {
    console.log('Start initiate!')
    let data = new FormData();
    data.append('user_id', 'USER_ID');
    data.append('is_initiated', 'true');
    let config = {
        method: 'post',
        url: URL_INITIATE,
        headers: {
            'X-API-Key': api_key,
            ...data.getHeaders()
        },
        data: data
    };
    let response = await axios.request(config)
    console.log('Complete initiate! session_id: ' + response.data.session_id)
    return response.data.session_id
}

async function predict(session_id) {
    console.log('Start predict!')
    let data = new FormData();
    data.append('session_id', session_id);
    data.append('file', fs.createReadStream('Sub_PHQ0_GAD0_I.wav'));
    let config = {
        method: 'post',
        url: URL_PREDICT,
        headers: {
            ...data.getHeaders()
        },
        data: data
    };
    let response = await axios.request(config)
    console.log('Complete predict! data: ' + JSON.stringify(response.data))
}

async function feedback(session_id) {
    console.log('Start feedback!')
    let data = new FormData();
    data.append('session_id', session_id);
    // Available options of actual score are: true, false,
    // additional_consideration_required.
    // Feedback endpoint do not return any data.
    data.append('actual_score', 'true');
    let config = {
        method: 'patch',
        url: URL_FEEDBACK,
        headers: {
            ...data.getHeaders()
        },
        data: data
    };
    await axios.request(config)
    console.log('Complete feedback!')
}

async function main() {
    let session_id = await initiate("API_KEY")
    await predict(session_id)
    await feedback(session_id)
}

main().then((data) => {
    console.log("Finish!")
}).catch((error) => {
    console.log(error.message)
});

import requests

API_KEY = '<your api key>'
USER_ID = '<user_id from your system>'
VOICE_SAMPLE = "Sub_PHQ0_GAD0_I.wav"

# Create an HTTP Client. Provide authentication credentials.
session = requests.Session()
session.headers.update({"X-API-Key": API_KEY})

# Initiate session between the patient and a doctor.
initiate_resp = session.post(
    url="https://api.kintsugihealth.com/v1/initiate",
    data={"user_id": USER_ID, "is_initiated": True},
)
initiate_resp.raise_for_status()

# Fetch session_id, it will be used as an identifier to make a prediction and provide feedback.
session_id = initiate_resp.json()["session_id"]

# Make a prediction for the specified patient's voice sample.
with open(VOICE_SAMPLE, 'rb') as patient_voice_sample:
    prediction_resp = session.post(
        url="https://api.kintsugihealth.com/v1/predict/server/depression/binary",
        files={'file': patient_voice_sample},
        data={"session_id": session_id},
    )
    prediction_resp.raise_for_status()

# *PHQ-2: Provide a doctor's feedback on the quality of the prediction.
feedback_resp = session.patch(
    url="https://api.kintsugihealth.com/v1/feedback/server/phq/2",
    json={"session_id": session_id, "actual_score": [1, 2]},
)
feedback_resp.raise_for_status()

# *PHQ-9: Provide a doctor's feedback on the quality of the prediction.
feedback_resp = session.patch(
    url="https://api.kintsugihealth.com/v1/feedback/server/phq/9",
    json={"session_id": session_id, "actual_score": [1, 2, 3, 1, 2, 3, 1, 2, 3]},
)
feedback_resp.raise_for_status()

# *Binary: Provide a doctor's feedback on the quality of the prediction.
feedback_resp = session.patch(
    url="https://api.kintsugihealth.com/v1/feedback/server/depression/binary",
    data={"session_id": session_id, "actual_score": "true"},
)
feedback_resp.raise_for_status()

print("The prediction was completed successfully!")

import requests

API_KEY = '<your api key>'
USER_ID = '<user_id from your system>'
VOICE_SAMPLE = "Sub_PHQ0_GAD0_I.wav"

# Create an HTTP Client. Provide authentication credentials.
session = requests.Session()
session.headers.update({"X-API-Key": API_KEY})

# Initiate session between the patient and a doctor.
initiate_resp = session.post(
    url="https://api.kintsugihealth.com/v1/initiate",
    data={"user_id": USER_ID, "is_initiated": True},
)
initiate_resp.raise_for_status()

# Fetch session_id, it will be used as an identifier to make a prediction and provide feedback.
session_id = initiate_resp.json()["session_id"]

# Make a prediction for the specified patient's voice sample.
with open(VOICE_SAMPLE, 'rb') as patient_voice_sample:
    prediction_resp = session.post(
        url="https://api.kintsugihealth.com/v1/predict/server/depression/severity",
        files={'file': patient_voice_sample},
        data={"session_id": session_id},
    )
    prediction_resp.raise_for_status()

# *PHQ-2: Provide a doctor's feedback on the quality of the prediction.
feedback_resp = session.patch(
    url="https://api.kintsugihealth.com/v1/feedback/server/phq/2",
    json={"session_id": session_id, "actual_score": [1, 2]},
)
feedback_resp.raise_for_status()

# *PHQ-9: Provide a doctor's feedback on the quality of the prediction.
feedback_resp = session.patch(
    url="https://api.kintsugihealth.com/v1/feedback/server/phq/9",
    json={"session_id": session_id, "actual_score": [1, 2, 3, 1, 2, 3, 1, 2, 3]},
)
feedback_resp.raise_for_status()

print("The prediction was completed successfully!")