Create app.py

app.py

@@ -0,0 +1,72 @@
+import gradio as gr
+import spaces
+from PIL import Image
+import requests
+from transformers import AutoModelForCausalLM, AutoProcessor
+import torch
+
+# Load the model and processor
+model_id = "microsoft/Phi-3.5-vision-instruct"
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    trust_remote_code=True,
+    torch_dtype=torch.float16,
+)
+processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True, num_crops=16)
+
+@spaces.GPU(duration=120)  # Adjust the duration as needed
+def solve_math_problem(image):
+    # Move model to GPU for this function call
+    model.to('cuda')
+    
+    # Prepare the input
+    messages = [
+        {"role": "user", "content": "<|image_1|>\nSolve this math problem step by step. Explain your reasoning clearly."},
+    ]
+    prompt = processor.tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+    )
+    
+    # Process the input
+    inputs = processor(prompt, image, return_tensors="pt").to("cuda")
+    
+    # Generate the response
+    generation_args = {
+        "max_new_tokens": 1000,
+        "temperature": 0.2,
+        "do_sample": True,
+    }
+    generate_ids = model.generate(**inputs, 
+        eos_token_id=processor.tokenizer.eos_token_id, 
+        **generation_args
+    )
+    
+    # Decode the response
+    generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
+    response = processor.batch_decode(generate_ids, 
+        skip_special_tokens=True, 
+        clean_up_tokenization_spaces=False
+    )[0]
+    
+    # Move model back to CPU to free up GPU memory
+    model.to('cpu')
+    
+    return response
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=solve_math_problem,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Visual Math Problem Solver",
+    description="Upload an image of a math problem, and I'll try to solve it step by step!",
+    examples=[
+        ["example_math_problem1.jpg"],
+        ["example_math_problem2.jpg"]
+    ]
+)
+
+# Launch the app
+iface.launch()