app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Specify the model name from Hugging Face Hub
model_name = "openbmb/MiniCPM-V"

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

def generate_text(prompt):
    # Tokenize the input prompt
    inputs = tokenizer(prompt, return_tensors="pt")
    # Generate output tokens
    outputs = model.generate(**inputs, max_new_tokens=50)
    # Decode tokens to text
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Create a simple Gradio interface
iface = gr.Interface(fn=generate_text, inputs="text", outputs="text", title="MiniCPM-V Demo")
iface.launch()