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Running
suhyun.kang
commited on
Commit
·
6b89337
1
Parent(s):
67812d2
update (https://screen.yanolja.in/eKUGn6i6wCYX2HBS.png)
Browse files
app.py
CHANGED
@@ -8,24 +8,18 @@ import gradio as gr
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SUPPORTED_MODELS = ["gpt-4", "gpt-4-turbo", "gpt-3.5-turbo"]
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def user(
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state_b = gradio_web_server.State(model_pair[1])
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for state in [
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state.conv.append_message(state.conv.roles[0], user_message)
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state.conv.append_message(state.conv.roles[1], None)
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state.skip_next = False
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empty_prompt = ""
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return [
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state_a.to_gradio_chatbot(),
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state_b.to_gradio_chatbot(), state_a.model_name, state_b.model_name,
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empty_prompt
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]
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@@ -33,8 +27,10 @@ def bot(state_a, state_b, request: gr.Request):
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if state_a is None or state_b is None:
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raise RuntimeError(f"states cannot be None, got [{state_a}, {state_b}]")
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generators = []
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for state in
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try:
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# TODO(#1): Allow user to set configuration.
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# bot_response returns a generator yielding states and chatbots.
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@@ -50,56 +46,52 @@ def bot(state_a, state_b, request: gr.Request):
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print(f"Error in bot_response: {e}")
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raise e
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while True:
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stop = True
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for i in range(2):
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try:
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generator = next(generators[i])
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stop = False
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except StopIteration:
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pass
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yield
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if stop:
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break
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with gr.Blocks() as app:
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with gr.Row():
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value="Summarization",
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label="Response type",
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info="Choose the type of response you want from the model.")
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language = gr.Dropdown(["Korean", "English"],
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value="Korean",
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label="Language",
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info="Choose the target language.")
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chatbots = [None, None]
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with gr.Row():
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chatbots[0] = gr.Chatbot(label="Model A")
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chatbots[1] = gr.Chatbot(label="Model B")
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model_names = [None, None]
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with gr.Accordion("Show models", open=False):
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with gr.Row():
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model_names[0] = gr.Textbox(label="Model A", interactive=False)
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model_names[1] = gr.Textbox(label="Model B", interactive=False)
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prompt
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states = [gr.State(None), gr.State(None)]
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prompt.submit(user,
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states + [prompt],
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states + chatbots + model_names + [prompt],
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queue=False).then(bot, states, states + chatbots)
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if __name__ == "__main__":
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# We need to enable queue to use generators.
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app.queue()
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app.launch()
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SUPPORTED_MODELS = ["gpt-4", "gpt-4-turbo", "gpt-3.5-turbo"]
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def user(user_message):
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model_pair = sample(SUPPORTED_MODELS, 2)
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new_state_a = gradio_web_server.State(model_pair[0])
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new_state_b = gradio_web_server.State(model_pair[1])
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for state in [new_state_a, new_state_b]:
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state.conv.append_message(state.conv.roles[0], user_message)
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state.conv.append_message(state.conv.roles[1], None)
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state.skip_next = False
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return [
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new_state_a, new_state_b, new_state_a.model_name, new_state_b.model_name
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]
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if state_a is None or state_b is None:
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raise RuntimeError(f"states cannot be None, got [{state_a}, {state_b}]")
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new_states = [state_a, state_b]
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generators = []
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for state in new_states:
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try:
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# TODO(#1): Allow user to set configuration.
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# bot_response returns a generator yielding states and chatbots.
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print(f"Error in bot_response: {e}")
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raise e
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new_responses = [None, None]
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# It simulates concurrent response generation from two models.
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while True:
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stop = True
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for i in range(2):
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try:
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generator = next(generators[i])
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new_state = generator[0]
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new_states[i] = new_state
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# conv.messages is a list of [role, message].
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new_responses[i] = new_state.conv.messages[-1][-1]
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stop = False
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except StopIteration:
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pass
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yield new_states + new_responses
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if stop:
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break
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with gr.Blocks() as app:
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model_names = [gr.State(None), gr.State(None)]
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responses = [gr.State(None), gr.State(None)]
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# states stores FastChat-specific conversation states.
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states = [gr.State(None), gr.State(None)]
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prompt = gr.TextArea(label="Prompt", lines=4)
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submit = gr.Button()
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with gr.Row():
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responses[0] = gr.Textbox(label="Model A", interactive=False)
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responses[1] = gr.Textbox(label="Model B", interactive=False)
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with gr.Accordion("Show models", open=False):
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with gr.Row():
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model_names[0] = gr.Textbox(label="Model A", interactive=False)
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model_names[1] = gr.Textbox(label="Model B", interactive=False)
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submit.click(user, prompt, states + model_names,
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queue=False).then(bot, states, states + responses)
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if __name__ == "__main__":
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# We need to enable queue to use generators.
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app.queue()
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app.launch(debug=True)
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