Create app.py

app.py

@@ -0,0 +1,77 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoProcessor, GenerationConfig
+from PIL import Image
+import torch
+
+# Load the processor and model
+processor = AutoProcessor.from_pretrained(
+    'allenai/Molmo-7B-D-0924',
+    trust_remote_code=True,
+    torch_dtype='auto',
+    device_map='auto'
+)
+
+model = AutoModelForCausalLM.from_pretrained(
+    'allenai/Molmo-7B-D-0924',
+    trust_remote_code=True,
+    torch_dtype='auto',
+    device_map='auto'
+)
+
+def process_image_and_text(image, text):
+    # Process the image and text
+    inputs = processor.process(
+        images=[Image.fromarray(image)],
+        text=text
+    )
+
+    # Move inputs to the correct device and make a batch of size 1
+    inputs = {k: v.to(model.device).unsqueeze(0) for k, v in inputs.items()}
+
+    # Generate output
+    output = model.generate_from_batch(
+        inputs,
+        GenerationConfig(max_new_tokens=200, stop_strings="<|endoftext|>"),
+        tokenizer=processor.tokenizer
+    )
+
+    # Only get generated tokens; decode them to text
+    generated_tokens = output[0, inputs['input_ids'].size(1):]
+    generated_text = processor.tokenizer.decode(generated_tokens, skip_special_tokens=True)
+
+    return generated_text
+
+def chatbot(image, text, history):
+    if image is None:
+        return "Please upload an image first.", history
+
+    response = process_image_and_text(image, text)
+    history.append((text, response))
+    return response, history
+
+# Define the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Chatbot with Molmo-7B-D-0924")
+    
+    with gr.Row():
+        image_input = gr.Image(type="numpy")
+        chatbot_output = gr.Chatbot()
+    
+    text_input = gr.Textbox(placeholder="Ask a question about the image...")
+    submit_button = gr.Button("Submit")
+
+    state = gr.State([])
+
+    submit_button.click(
+        chatbot,
+        inputs=[image_input, text_input, state],
+        outputs=[chatbot_output, state]
+    )
+
+    text_input.submit(
+        chatbot,
+        inputs=[image_input, text_input, state],
+        outputs=[chatbot_output, state]
+    )
+
+demo.launch()