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import torch
import gradio as gr
from PIL import Image
from transformers import AutoTokenizer, AutoModelForSequenceClassification
js = """
function createGradioAnimation() {
var container = document.createElement('div');
container.id = 'gradio-animation';
container.style.fontSize = '2em';
container.style.fontWeight = 'bold';
container.style.textAlign = 'center';
container.style.marginBottom = '20px';
var text = 'Stress Prediction Model';
for (var i = 0; i < text.length; i++) {
(function(i){
setTimeout(function(){
var letter = document.createElement('span');
letter.style.opacity = '0';
letter.style.transition = 'opacity 0.5s';
letter.innerText = text[i];
container.appendChild(letter);
setTimeout(function() {
letter.style.opacity = '1';
}, 50);
}, i * 250);
})(i);
}
var gradioContainer = document.querySelector('.gradio-container');
gradioContainer.insertBefore(container, gradioContainer.firstChild);
return 'Animation created';
}
"""
saved_directory = 'jnyx74/stress-prediction'
tokenizer = AutoTokenizer.from_pretrained(saved_directory)
model = AutoModelForSequenceClassification.from_pretrained(saved_directory)
# gr.load("models/jnyx74/stress-prediction").launch()
#"LABEL_0": "I think you don't feel stress. Perhaps, describe more, so I can understand you more!",
#"LABEL_1": "Darling, I sensed that you were stressed. Are you alright?""
background = Image.open('quote.jpg')
with gr.Blocks(js=js,theme=gr.themes.Soft()) as demo:
gr.Image(background, height = '400px',interactive = False)
gr.Markdown(
'''
# Let me study you, perhaps?
Not everyone tends to express/ knowing to relieve their stress in a proper way. Therefore, are you stress? Perhaps,
I could have a guess here. I am a fine-tuned DeepLearning/Transformers Model on DistilBert Model with training on reddit datasets.
'''
)
gr.Markdown("Start typing below and then click **Study Me** to see the output.")
inp = gr.Text(placeholder = "How do you feel today?", label="Sentence Me:")
btn = gr.Button("Study Me")
with gr.Column(visible=False) as output_col:
out_label = gr.Markdown("# Ooh, I think ...")
out = gr.Text(label="Result",interactive = False)
examples = gr.Examples(examples=["By serendipity, I meet her once again and for real, I miss her.",
"Insomnia and overthinking is really killing me as my final year project is reaching.",
"I just won a lottery and wanting to own a house in Kuching.",
"I can't believe I just hit a car just now and the car driver just ran away, how ridiculous?",
"I hate kids but my wife insists to have one, can't we just adopt?"]
,
inputs = [inp])
def form_submit(inp):
if len(inp)<=15:
gr.Warning("Describe/ Express more, a sentence with expression is more appreciated")
return {
output_col: gr.Column(visible=True),
out: gr.Text(value="Please express more of you!!")}
else:
inputs = tokenizer([inp], return_tensors="pt")
with torch.no_grad():
logits = model(**inputs).logits
predicted_class_id = logits.argmax().item()
result = model.config.id2label[predicted_class_id]
if result == 'LABEL_0':
result_value = "I think you don't feel stress. Perhaps, describe more, so I can understand you more!"
else: result_value = "Darling, I sensed that you were stressed. Are you alright?"
gr.Info("Success Executed")
return {
output_col: gr.Column(visible=True),
out: gr.Text(value=result_value)
}
btn.click(fn=form_submit, inputs=inp, outputs=[out, output_col])
demo.launch() |