deleted

demo.py

@@ -1,111 +0,0 @@
-import gradio as gr
-from transformers import DebertaTokenizer, DebertaForSequenceClassification
-from transformers import pipeline
-
-save_path_abstract = '/home/raj.tomar/Downloads/MGT/experiments/fine-tuned-deberta/'
-model_abstract = DebertaForSequenceClassification.from_pretrained(save_path_abstract)
-tokenizer_abstract = DebertaTokenizer.from_pretrained(save_path_abstract)
-
-classifier_abstract = pipeline('text-classification', model=model_abstract, tokenizer=tokenizer_abstract)
-
-save_path_essay = '/home/raj.tomar/Downloads/MGT/experiments/fine-tuned-deberta/'
-model_essay = DebertaForSequenceClassification.from_pretrained(save_path_essay)
-tokenizer_essay = DebertaTokenizer.from_pretrained(save_path_essay)
-
-classifier_essay = pipeline('text-classification', model=model_essay, tokenizer=tokenizer_essay)
-
-def update(name, uploaded_file, radio_input):
-    if uploaded_file is not None:
-        return f"{name}, you uploaded a file named {uploaded_file.name}."
-    else:
-        if radio_input == 'Scientific Abstract':
-            data = classifier_abstract(name)[0]['label']
-            if data == 'LABEL_0':
-                return "human_text"
-            if data == 'LABEL_1':
-                return "machine_text"
-            if data == 'LABEL_2':
-                return "human-written | machine-polished"
-            if data == 'LABEL_3':
-                return "machine-generated | machine-humanized"
-        else:
-            if radio_input == 'Student Essay':
-                data = classifier_essay(name)[0]['label']
-                if data == 'LABEL_0':
-                    return "human_text"
-                if data == 'LABEL_1':
-                    return "machine_text"
-                if data == 'LABEL_2':
-                    return "human-written | machine-polished"
-                if data == 'LABEL_3':
-                    return "machine-generated | machine-humanized"
-            # return "Hold on!"
-
-with gr.Blocks() as demo:
-    gr.Markdown(
-        """
-        <style>
-        .gr-button-secondary {
-            width: 100px;
-            height: 30px;
-            padding: 5px;
-        }
-        .gr-row {
-            display: flex;
-            align-items: center;
-            gap: 10px;
-        }
-        .gr-block {
-            padding: 20px;
-        }
-        .gr-markdown p {
-            font-size: 16px;
-        }
-        </style>
-        <span style='font-family: Arial, sans-serif; font-size: 20px;'>Was this text written by <strong>human</strong> or <strong>AI</strong>?</span>
-        <p style='font-family: Arial, sans-serif;'>Try detecting one of our sample texts:</p>
-        """
-    )
-    
-    with gr.Row():
-        for sample in ["Machine-Generated", "Human-Written", "Machine-Humanized", "Machine - Polished"]:
-            gr.Button(sample, variant="outline")
-
-    with gr.Row():
-        radio_button = gr.Radio(['Scientific Abstract', 'Student Essay'], label = 'Text Type', info = 'We have specialized models that work on domain-specific text.')
-    
-    with gr.Row():
-        input_text = gr.Textbox(placeholder="Paste your text here...", label="", lines=10)
-        file_input = gr.File(label="Upload File")
-
-    #file_input = gr.File(label="", visible=False)  # Hide the actual file input
-    
-    with gr.Row():
-        check_button = gr.Button("Check Origin", variant="primary")
-        clear_button = gr.ClearButton([input_text, file_input, radio_button], variant='stop')
-        #upload_button = gr.Button("Upload File", variant="secondary")
-    
-    out = gr.Textbox(label="OUTPUT", placeholder="", lines=2)
-    clear_button.add(out)
-    
-    check_button.click(fn=update, inputs=[input_text, file_input, radio_button], outputs=out)
-    #upload_button.click(lambda: None, inputs=[], outputs=[]).then(fn=update, inputs=[input_text, file_input], outputs=out)
-
-    # Adding JavaScript to simulate file input click
-    gr.Markdown(
-        """
-        <script>
-        document.addEventListener("DOMContentLoaded", function() {
-            const uploadButton = Array.from(document.getElementsByTagName('button')).find(el => el.innerText === "Upload File");
-            if (uploadButton) {
-                uploadButton.onclick = function() {
-                    document.querySelector('input[type="file"]').click();
-                };
-            }
-        });
-        </script>
-        """
-    )
-
-demo.launch(share=True)
-