Update app.py
Browse files
app.py
CHANGED
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@@ -2,10 +2,11 @@ import gradio as gr
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from huggingface_hub import InferenceClient
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"""
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-
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"""
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def respond(
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message,
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history: list[tuple[str, str]],
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@@ -14,6 +15,9 @@ def respond(
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temperature,
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top_p,
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):
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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@@ -34,34 +38,30 @@ def respond(
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top_p=top_p,
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):
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token = message.choices[0].delta.content
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response += token
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yield response
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# Добавляем идентификационное сообщение к ответу
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final_response = f"{response}\n\nСоздано больницей EMS штата Alta"
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yield final_response
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"""
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"""
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(
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),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Максимальное количество новых токенов"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Температура"),
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="Top-p (
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),
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],
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)
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if __name__ == "__main__":
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demo.launch()
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from huggingface_hub import InferenceClient
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"""
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+
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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"""
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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def respond(
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message,
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history: list[tuple[str, str]],
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temperature,
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top_p,
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):
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# Установим приветственное сообщение для системы
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system_message = "Привет! Я помощник врача в больнице EMS штата Alta! Напиши внизу симптомы заболевания и я поставлю предварительный диагноз! И хирургическую операцию, если надо будет ее провести."
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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top_p=top_p,
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):
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token = message.choices[0].delta.content
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response += token
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yield response
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="Top-p (nucleus sampling)",
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),
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],
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)
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if __name__ == "__main__":
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demo.launch()
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