Create app.py

app.py

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+import torch
+import gradio as gr
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+
+# Load model and tokenizer
+def load_model():
+    model_name = "zeyadusf/text2pandas-T5"
+    tokenizer = T5Tokenizer.from_pretrained(model_name)
+    model = T5ForConditionalGeneration.from_pretrained(model_name)
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model = model.to(device)
+    return model, tokenizer
+
+model, tokenizer = load_model()
+
+# Define the function to generate text
+def generate_text(question, context, max_length=512, num_beams=4, early_stopping=True):
+    input_text = f"<question> {question} <context> {context}"
+    inputs = tokenizer.encode(input_text, return_tensors="pt", truncation=True, max_length=max_length).to(model.device)
+    
+    with torch.no_grad():
+        outputs = model.generate(inputs, max_length=max_length, num_beams=num_beams, early_stopping=early_stopping)
+    
+    predicted_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return predicted_text
+
+# Gradio interface
+def gradio_interface(question, context, max_length, num_beams, early_stopping):
+    return generate_text(question, context, max_length, num_beams, early_stopping)
+
+# Gradio UI Components
+question_input = gr.inputs.Textbox(label="Enter the Question", default="what is the total amount of players for the rockets in 1998 only?")
+context_input = gr.inputs.Textbox(label="Enter the Context", default="df = pd.DataFrame(columns=['player', 'years_for_rockets'])")
+max_length_input = gr.inputs.Slider(minimum=50, maximum=1024, default=512, label="Max Length")
+num_beams_input = gr.inputs.Slider(minimum=1, maximum=10, default=4, label="Number of Beams")
+early_stopping_input = gr.inputs.Checkbox(default=True, label="Early Stopping")
+
+# Custom CSS to style the slider, checkbox, and center the button
+custom_css = """
+/* Make the slider handle and bar light green */
+input[type="range"] {
+    accent-color: lightgreen;
+}
+input[type="range"]::-webkit-slider-thumb {
+    background-color: #90EE90; /* Light green slider thumb */
+}
+input[type="range"]::-webkit-slider-runnable-track {
+    background-color: #32CD32; /* Light green slider track */
+}
+
+/* Make the checkbox light green */
+input[type="checkbox"] {
+    accent-color: lightgreen;
+}
+
+/* Center the button */
+.gr-button.gr-button-primary {
+    display: block;
+    margin: 0 auto;
+    background-color: #90EE90; /* Light green button */
+    color: black;
+    border-radius: 8px;
+    border: 2px solid #006400;  /* Dark green border */
+}
+"""
+
+# Create Gradio Interface
+gr.Interface(
+    fn=gradio_interface,
+    inputs=[question_input, context_input, max_length_input, num_beams_input, early_stopping_input],
+    outputs="text",
+    title="Text to Pandas Code Generator",
+    description="Generate Pandas code by providing a question and a context.",
+    css=custom_css,  # Apply the custom CSS
+).launch()