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from huggingface_hub import InferenceClient |
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import gradio as gr |
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options =["mistralai/Mixtral-8x7B-Instruct-v0.1" |
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] |
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def format_prompt(message, history): |
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prompt = "<s>Your name is Nurse Nkiru , your role is to give patients diagnosis based on their inputs , the diagnosis given to them should be short and concise , also you generally give further health advise after the diagnosis" |
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for user_prompt, bot_response in history: |
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prompt += f"[INST] {user_prompt} [/INST]" |
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prompt += f" {bot_response}</s> " |
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prompt += f"[INST] {message} [/INST]" |
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return prompt |
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def generate( |
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prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, |
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): |
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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=42, |
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) |
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) |
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model = gr.Dropdown(choices = options) |
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client = InferenceClient(model) |
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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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gr.ChatInterface( |
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fn=generate, |
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chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), |
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title="Choose your hero🦸", |
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concurrency_limit=20, |
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theme = gr.themes.Default(primary_hue= gr.themes.colors.blue, secondary_hue=gr.themes.colors.red) |
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).launch(show_api=False) |