app.py

from transformers import pipeline
from PIL import Image
import gradio as gr

# Load BLIP VQA model
vqa_pipeline = pipeline(
    "visual-question-answering", model="Salesforce/blip-vqa-capfilt-large"
)

def answer_question(image, question):
    if image is None or question.strip() == "":
        return "Please provide an image and a question."
    outputs = vqa_pipeline(image, question, top_k=1)
    return outputs[0]["answer"]

with gr.Blocks() as demo:
    gr.Markdown("# 🖼️ Visual Question Answering with BLIP")
    with gr.Row():
        with gr.Column():
            image_input = gr.Image(type="pil", label="Upload an Image")
            question_input = gr.Textbox(label="Enter your question")
            submit_btn = gr.Button("Get Answer")
        with gr.Column():
            output_text = gr.Textbox(label="Answer")

    submit_btn.click(fn=answer_question,
                     inputs=[image_input, question_input],
                     outputs=output_text)

demo.launch()