Delete app.py

app.py

@@ -1,70 +0,0 @@
-# Importing the requirements
-# import warnings
-# warnings.filterwarnings("ignore")
-
-import gradio as gr
-from src.app.response import describe_image
-
-
-# Image, text query, and input parameters
-image = gr.Image(type="pil", label="Image")
-question = gr.Textbox(label="Question", placeholder="Enter your question here")
-temperature = gr.Slider(
-    minimum=0.01, maximum=1.99, step=0.01, value=0.7, label="Temperature"
-)
-top_p = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.8, label="Top P")
-top_k = gr.Slider(minimum=0, maximum=1000, step=1, value=100, label="Top K")
-max_new_tokens = gr.Slider(minimum=1, maximum=4096, step=1, value=512, label="Max Tokens")
-
-# Output for the interface
-answer = gr.Textbox(label="Predicted answer", show_label=True, show_copy_button=True)
-
-# Examples for the interface
-examples = [
-    [
-        "images/cat.jpg",
-        "How many cats are there?",
-        0.7,
-        0.8,
-        100,
-        512,
-    ],
-    [
-        "images/dog.jpg",
-        "¿De qué color es el perro?",
-        0.7,
-        0.8,
-        100,
-        512,
-    ],
-    [
-        "images/bird.jpg",
-        "Que fait l'oiseau ?",
-        0.7,
-        0.8,
-        100,
-        512,
-    ],
-]
-
-# Title, description, and article for the interface
-title = "Visual Question Answering"
-description = "Gradio Demo for the MiniCPM-V 2.6 Vision Language Understanding and Generation model. This model can answer questions about images in natural language. To use it, upload your image, type a question, select associated parameters, use the default values, click 'Submit', or click one of the examples to load them. You can read more at the links below."
-article = "<p style='text-align: center'><a href='https://github.com/OpenBMB/MiniCPM-V' target='_blank'>Model GitHub Repo</a> | <a href='https://huggingface.co/openbmb/MiniCPM-V-2_6' target='_blank'>Model Page</a></p>"
-
-
-# Launch the interface
-interface = gr.Interface(
-    fn=describe_image,
-    inputs=[image, question, temperature, top_p, top_k, max_new_tokens],
-    outputs=answer,
-    examples=examples,
-    cache_examples=True,
-    cache_mode="lazy",
-    title=title,
-    description=description,
-    article=article,
-    theme="Glass",
-    flagging_mode="never",
-)
-interface.launch(debug=False)