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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, temperature=0.25, max_new_tokens=512, top_p=0.95, 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, **generate_kwargs, stream=True, details=True, 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(bubble_full_width=True, show_label=False, show_copy_button=False, likeable=False) |
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theme = 'syddharth/gray-minimal' |
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demo = gr.ChatInterface(fn=generate, chatbot=samir_chatbot, title="Zitatengenerator", theme=theme) |
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demo.queue().launch(show_api=False) |