app.py

import gradio as gr
import soundfile as sf
from PIL import Image
import spaces
from transformers import AutoModelForCausalLM, AutoProcessor, GenerationConfig

# Define model path
model_path = "microsoft/Phi-4-multimodal-instruct"

# Load model and processor
processor = AutoProcessor.from_pretrained(model_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
    model_path, 
    device_map="auto", 
    torch_dtype="auto", 
    trust_remote_code=True, 
    attn_implementation='eager',
)

generation_config = GenerationConfig.from_pretrained(model_path)

# Define prompt structure
user_prompt = '<|user|>'
assistant_prompt = '<|assistant|>'
prompt_suffix = '<|end|>'

@spaces.GPU
def process_multimodal(input_file, query):
    if input_file is None:
        return "Please upload an image or an audio file."
    
    file_type = input_file.type
    prompt = f"{user_prompt}<|media_1|>{query}{prompt_suffix}{assistant_prompt}"
    
    if "image" in file_type:
        image = Image.open(input_file)
        inputs = processor(text=prompt, images=image, return_tensors='pt').to('cuda:0')
    elif "audio" in file_type:
        audio, samplerate = sf.read(input_file.name)
        inputs = processor(text=prompt, audios=[(audio, samplerate)], return_tensors='pt').to('cuda:0')
    else:
        return "Unsupported file format. Please upload an image or audio file."
    
    generate_ids = model.generate(
        **inputs,
        max_new_tokens=1000,
        generation_config=generation_config,
        num_logits_to_keep=0,
    )
    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]
    
    return response

with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # Phi-4 Multimodal Chat
    Upload an image or an audio file and ask questions related to it!
    """)
    
    with gr.Row():
        with gr.Column():
            input_file = gr.File(label="Upload Image or Audio")
            query = gr.Textbox(label="Ask a question")
            submit_btn = gr.Button("Submit")
        
        with gr.Column():
            output = gr.Textbox(label="Response", interactive=False)
    
    submit_btn.click(process_multimodal, inputs=[input_file, query], outputs=output)

demo.launch()