Makaria commited on
Commit
be0bcf5
1 Parent(s): 1a1d7e4

Обновление кода с новым токеном

Browse files
Files changed (2) hide show
  1. app.py +10 -58
  2. bot.py +17 -0
app.py CHANGED
@@ -1,63 +1,15 @@
 
1
  import gradio as gr
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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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9
 
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- def respond(
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- message,
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- history: list[tuple[str, str]],
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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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-
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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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-
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- messages.append({"role": "user", "content": message})
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-
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- response = ""
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-
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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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-
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- response += token
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- yield response
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-
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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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-
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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()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bot.py ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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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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+
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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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+
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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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+
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+ bot.polling()