initial-dev

app.py

@@ -0,0 +1,106 @@
+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+model = AutoModelForSeq2SeqLM.from_pretrained("vennify/t5-base-grammar-correction")
+tokenizer = AutoTokenizer.from_pretrained("vennify/t5-base-grammar-correction")
+
+def correct_text(text, max_length, max_new_tokens, min_length, num_beams, temperature, top_p):
+    inputs = tokenizer.encode("grammar: " + text, return_tensors="pt")
+    generate_kwargs = {
+        "inputs": inputs,
+        "max_length": max_length,
+        "min_length": min_length,
+        "num_beams": num_beams,
+        "temperature": temperature,
+        "top_p": top_p,
+        "early_stopping": True
+    }
+
+    if max_new_tokens > 0:
+        generate_kwargs["max_new_tokens"] = max_new_tokens
+
+    outputs = model.generate(**generate_kwargs)
+    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return corrected_text
+
+def respond(message, history, max_length, min_length, max_new_tokens, num_beams, temperature, top_p):
+    response = correct_text(message, max_length, max_new_tokens, min_length, num_beams, temperature, top_p)
+    yield response
+
+css = """
+#interface-container {  
+    padding: 20px; 
+    border-radius: 10px; 
+    box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1); 
+    max-width: 800px;
+    margin: auto;
+    font-family: 'Arial', sans-serif;
+}
+#input-container { 
+    margin-bottom: 20px; 
+}
+#output-container { 
+    margin-top: 20px; 
+    font-family: Arial, sans-serif; 
+    font-size: 16px; 
+    color: #333; 
+    padding: 10px; 
+    border-radius: 5px; 
+    border: 1px solid #ddd;
+}
+.gr-button { 
+    background-color: #007bff; 
+    color: white; 
+    border: none; 
+    padding: 10px 20px; 
+    border-radius: 5px; 
+    cursor: pointer; 
+    font-size: 16px; 
+}
+.gr-button:hover { 
+    background-color: #0056b3; 
+}
+.gr-slider .gr-slider-track { 
+    background-color: #007bff; 
+}
+.gr-slider .gr-slider-thumb { 
+    background-color: #0056b3; 
+}
+.gr-textbox input { 
+    border: 1px solid #ddd; 
+    border-radius: 5px; 
+    padding: 10px; 
+}
+.gr-textbox textarea { 
+    border: 1px solid #ddd; 
+    border-radius: 5px; 
+    padding: 10px; 
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    gr.HTML("<h1 style='text-align: center; color: #007bff;'>Grammar Correction Tool</h1>")
+    
+    with gr.Row(elem_id="interface-container"):
+        with gr.Column():
+            user_input = gr.Textbox(lines=2, placeholder="Enter a sentence with grammatical errors...", label="Input Text", elem_id="input-container")
+            max_length = gr.Slider(minimum=1, maximum=256, value=100, step=1, label="Max Length")
+            min_length = gr.Slider(minimum=1, maximum=256, value=0, step=1, label="Min Length")
+            max_new_tokens = gr.Slider(minimum=0, maximum=256, value=0, step=1, label="Max New Tokens (optional)")
+            num_beams = gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Num Beams")
+            temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
+            top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
+            
+            btn = gr.Button("Correct Grammar")
+        
+        with gr.Column():
+            corrected_output = gr.Textbox(lines=2, placeholder="The corrected sentence will appear here...", label="Corrected Text", elem_id="output-container")
+
+    btn.click(
+        fn=correct_text, 
+        inputs=[user_input, max_length, max_new_tokens, min_length, num_beams, temperature, top_p],
+        outputs=corrected_output
+    )
+
+if __name__ == "__main__":
+    demo.launch()