app.py

import json
import gradio as gr
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification

model_name = "michellejieli/emotion_text_classifier"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

classifier = pipeline(task="text-classification", model=model, tokenizer=tokenizer, top_k=None)

def get_chatbot_response(sentences_json):
    sentences = json.loads(sentences_json)
    model_outputs = classifier(sentences)
    return json.dumps(model_outputs)  # produces a list of dicts for each of the labels


# Create the Gradio interface
app = gr.Interface(
    fn=get_chatbot_response,
    inputs=gr.Textbox(label="Your message (JSON format)", lines=5, placeholder='[{"user": "Hi!"}]'),
    outputs=gr.Textbox(label="System response"),
)


if __name__ == "__main__":
    app.launch()