Create app.py
Browse files
app.py
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from huggingface_hub import InferenceClient
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import gradio as gr
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import os
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
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secret_prompt = os.getenv("SECRET_PROMPT")
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def format_prompt(new_message, history):
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prompt = secret_prompt
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for user_msg, bot_msg in history:
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prompt += f"[INST] {user_msg} [/INST]"
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prompt += f" {bot_msg}</s> "
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prompt += f"[INST] {new_message} [/INST]"
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return prompt
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def generate(prompt, history,
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temperature=0.25,
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max_new_tokens=512,
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top_p=0.95,
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repetition_penalty=1.0):
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temperature = float(temperature)
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if temperature < 1e-2:
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temperature = 1e-2
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top_p = float(top_p)
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generate_kwargs = dict(
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temperature=temperature,
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max_new_tokens=max_new_tokens,
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top_p=top_p,
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repetition_penalty=repetition_penalty,
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do_sample=True,
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seed=727,
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)
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formatted_prompt = format_prompt(prompt, history)
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stream = client.text_generation(formatted_prompt,
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**generate_kwargs,
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stream=True,
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details=True,
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return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield output
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return output
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samir_chatbot = gr.Chatbot(avatar_images=["./user.png", "./bot.png"],
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bubble_full_width=False,
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show_label=False,
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show_copy_button=True,
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likeable=True,)
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# Gradio-Demo konfigurieren
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theme = 'syddharth/gray-minimal'
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demo = gr.ChatInterface(fn=generate,
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chatbot=samir_chatbot,
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title="Ailexs Mixtral 8x7b Chat",
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theme=theme)
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demo.queue().launch(show_api=False)
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