Spaces:
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Обновление кода с новым токеном
Browse files
app.py
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import gradio as gr
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from huggingface_hub import InferenceClient
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""
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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system_message,
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max_tokens,
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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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if val[0]:
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messages.append({"role": "user", "content": val[0]})
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if val[1]:
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messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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response = ""
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for message in client.chat_completion(
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messages,
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max_tokens=max_tokens,
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stream=True,
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temperature=temperature,
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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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import os
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import gradio as gr
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from huggingface_hub import InferenceClient
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# Получаем токен из окружения
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hf_token = os.getenv("HUGGINGFACE_TOKEN")
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client = InferenceClient("sambanovasystems/SambaLingo-Russian-Chat", token=hf_token)
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def respond(message):
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response = client.chat_completion(messages=[{"role": "user", "content": message}])
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return response['choices'][0]['message']['content']
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# Интерфейс Gradio
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iface = gr.Interface(fn=respond, inputs="text", outputs="text", title="AI Chat Bot")
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iface.launch()
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bot.py
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import os
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import telebot
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from huggingface_hub import InferenceClient
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# Получаем токены из окружения
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hf_token = os.getenv("HUGGINGFACE_TOKEN")
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tg_token = os.getenv("TG_TOKEN")
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bot = telebot.TeleBot(tg_token)
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client = InferenceClient("sambanovasystems/SambaLingo-Russian-Chat", token=hf_token)
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@bot.message_handler(func=lambda message: True)
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def echo_all(message):
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response = client.chat_completion(messages=[{"role": "user", "content": message.text}])
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bot.reply_to(message, response['choices'][0]['message']['content'])
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bot.polling()
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