Spaces:
Runtime error
Runtime error
stevengrove
commited on
Commit
β’
0164d1b
1
Parent(s):
dd1fecf
add example cache and resize input image
Browse files
app.py
CHANGED
@@ -39,6 +39,28 @@ def bot_request(method, *args, **kwargs):
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return response
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--temperature', type=float, default=0.0, help='temperature for the llm model')
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@@ -61,17 +83,20 @@ if __name__ == '__main__':
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os.makedirs('image')
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=0.3):
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with gr.Row():
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image = gr.Image(type=
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with gr.Row():
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txt = gr.Textbox(lines=7, show_label=False, elem_id=
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placeholder=
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with gr.Row():
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submit = gr.Button(
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with gr.Row():
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clear = gr.Button(
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with gr.Row():
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keep_last_n_paragraphs = gr.Slider(
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minimum=0,
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@@ -79,44 +104,51 @@ if __name__ == '__main__':
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value=args.keep_last_n_paragraphs,
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step=1,
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interactive=True,
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label=
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max_new_token = gr.Slider(
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minimum=64,
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maximum=512,
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value=args.max_new_tokens,
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step=1,
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interactive=True,
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label=
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temperature = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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value=args.temperature,
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step=0.1,
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interactive=True,
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label=
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top_p = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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value=args.top_p,
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step=0.1,
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interactive=True,
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label=
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with gr.Column(scale=0.7):
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chatbot = gr.Chatbot(elem_id=
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lambda: None, None, image)
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clear.click(partial(bot_request, 'clear'))
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clear.click(lambda: [], None, chatbot)
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with gr.Row():
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gr.Examples(
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examples=examples,
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inputs=[image, txt],
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)
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-
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return response
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def run_image(image, *args, **kwargs):
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if image is not None:
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width, height = image.size
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ratio = min(512 / width, 512 / height)
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width_new, height_new = (round(width * ratio), round(height * ratio))
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width_new = int(np.round(width_new / 64.0)) * 64
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height_new = int(np.round(height_new / 64.0)) * 64
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image = image.resize((width_new, height_new))
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image = image.convert('RGB')
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return bot_request('run_image', image, *args, **kwargs)
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def predict_example(temperature, top_p, max_new_token, keep_last_n_paragraphs, image, text):
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state = []
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buffer = ''
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chatbot, state, text, buffer = run_image(image, state, text, buffer)
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chatbot, state, text, buffer = bot_request(
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'run_text', text, state, temperature, top_p,
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max_new_token, keep_last_n_paragraphs, buffer)
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return chatbot, state, text, None, buffer
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument('--temperature', type=float, default=0.0, help='temperature for the llm model')
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os.makedirs('image')
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with gr.Blocks() as demo:
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state = gr.Chatbot([], visible=False)
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buffer = gr.Textbox('', visible=False)
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with gr.Row():
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with gr.Column(scale=0.3):
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with gr.Row():
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image = gr.Image(type='pil', label='input image')
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with gr.Row():
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txt = gr.Textbox(lines=7, show_label=False, elem_id='textbox',
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placeholder='Enter text and press submit, or upload an image').style(container=False)
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with gr.Row():
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submit = gr.Button('Submit')
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with gr.Row():
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clear = gr.Button('Clear')
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with gr.Row():
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keep_last_n_paragraphs = gr.Slider(
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minimum=0,
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value=args.keep_last_n_paragraphs,
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step=1,
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interactive=True,
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label='Remember Last N Paragraphs')
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max_new_token = gr.Slider(
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minimum=64,
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maximum=512,
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value=args.max_new_tokens,
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step=1,
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interactive=True,
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label='Max New Tokens')
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temperature = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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value=args.temperature,
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step=0.1,
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interactive=True,
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label='Temperature')
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top_p = gr.Slider(
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minimum=0.0,
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maximum=1.0,
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value=args.top_p,
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step=0.1,
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interactive=True,
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label='Top P')
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with gr.Column(scale=0.7):
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chatbot = gr.Chatbot(elem_id='chatbot', label='π¦ GPT4Tools').style(height=690)
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image.upload(lambda: '', None, txt)
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submit.click(run_image,
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[image, state, txt, buffer],
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[chatbot, state, txt, buffer]).then(
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partial(bot_request, 'run_text'),
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[txt, state, temperature, top_p, max_new_token, keep_last_n_paragraphs, buffer],
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[chatbot, state, txt, buffer]).then(
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lambda: None, None, image)
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clear.click(partial(bot_request, 'clear'))
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clear.click(lambda: [[], [], '', ''], None, [chatbot, state, txt, buffer])
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with gr.Row():
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gr.Examples(
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examples=examples,
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fn=partial(predict_example, args.temperature, args.top_p,
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args.max_new_tokens, args.keep_last_n_paragraphs),
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inputs=[image, txt],
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outputs=[chatbot, state, txt, image, buffer],
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cache_examples=True,
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)
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demo.queue(concurrency_count=6)
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demo.launch()
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