Create app.py

app.py

@@ -0,0 +1,87 @@
+import gradio as gr
+from datasets import load_dataset
+import torch
+from transformers import AutoTokenizer, T5ForConditionalGeneration  # Changed model class
+
+# Check if GPU is available
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+print(f"Using device: {device}")
+
+# Load dataset
+ds = load_dataset("AI-MO/NuminaMath-CoT")
+
+# Load model and tokenizer
+model_name = "google/flan-t5-base"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name).to(device)  # Changed model class
+
+def process_example(example):
+    """Process a single example from the dataset"""
+    question = example['question']
+    solution = example['solution']
+    answer = example['answer']
+    return f"Question: {question}\nSolution: {solution}\nAnswer: {answer}"
+
+def get_random_example():
+    """Get a random example from the dataset"""
+    import random
+    idx = random.randint(0, len(ds['train']) - 1)
+    return process_example(ds['train'][idx])
+
+def solve_math_problem(question):
+    """Generate solution for a given math problem"""
+    # Add prefix for T5
+    input_text = "solve math: " + question
+    inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True).to(device)
+    
+    # Generate response
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_length=200,
+        num_return_sequences=1,
+        temperature=0.7,
+        do_sample=True,
+        top_p=0.9,
+    )
+    
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Math Problem Solver")
+    gr.Markdown("Using FLAN-T5 model to solve mathematical problems with step-by-step solutions.")
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Enter your math problem",
+                placeholder="Type your math problem here...",
+                lines=3
+            )
+            with gr.Row():
+                submit_btn = gr.Button("Solve Problem", variant="primary")
+                example_btn = gr.Button("Show Random Example")
+        
+        with gr.Column():
+            output_text = gr.Textbox(
+                label="Solution",
+                lines=8,
+                show_copy_button=True
+            )
+    
+    # Set up event handlers
+    submit_btn.click(
+        fn=solve_math_problem,
+        inputs=input_text,
+        outputs=output_text
+    )
+    
+    example_btn.click(
+        fn=get_random_example,
+        inputs=None,
+        outputs=input_text
+    )
+
+# Launch the interface
+demo.launch(share=True)