emotion_detection.py

import json

import requests


def emotion_detector(text_to_analyze):
    url = "https://sn-watson-emotion.labs.skills.network/v1/watson.runtime.nlp.v1/NlpService/EmotionPredict"
    header = {"grpc-metadata-mm-model-id": "emotion_aggregated-workflow_lang_en_stock"}
    input_json = {"raw_document": {"text": text_to_analyze}}
    response = requests.post(url, json=input_json, headers=header, timeout=200)
    status_code = response.status_code

    emotions = {}

    if status_code == 200:
        formatted_response = json.loads(response.text)
        emotions = formatted_response["emotionPredictions"][0]["emotion"]
        dominant_emotion = max(emotions.items(), key=lambda x: x[1])
        emotions["dominant_emotion"] = dominant_emotion[0]
    elif status_code == 400:
        emotions["anger"] = None
        emotions["disgust"] = None
        emotions["fear"] = None
        emotions["joy"] = None
        emotions["sadness"] = None
        emotions["dominant_emotion"] = None
    return emotions