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README.md

@@ -1,13 +1,12 @@
 ---
-title: Predicting Stress From Textual Context
-emoji: 🚀
-colorFrom: blue
-colorTo: blue
+title: Stress Prediction Model
+emoji: 💻
+colorFrom: indigo
+colorTo: yellow
 sdk: gradio
-sdk_version: 4.44.0
+sdk_version: 4.26.0
 app_file: app.py
 pinned: false
-license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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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()

requirements.txt

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+gradio
+torch
+transformers
+nltk