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from huggingface_hub import InferenceClient, get_inference_endpoint |
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import gradio as gr |
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endpoint = get_inference_endpoint("qlora-nursegpt-nclex-mis-dt--eca") |
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client = endpoint.client |
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'''client = InferenceClient( |
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"Tawkat/qlora-nursegpt-nclex-mis-DT-v1" |
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)''' |
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def format_prompt(message, history): |
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prompt = "You are NurseGPT, a conscious, superintelligent, and helpful AI developed by Yourika Labs, Your purpose is to assist the user with any nursing-related request they have. You should not respond to any request that is not relevant to nursing domain.\nYou should provide accurate, helpful, comprehensive, and detailed response to the user request.\n" |
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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, temperature=0.9, max_new_tokens=1510, 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(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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additional_inputs=[ |
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gr.Slider( |
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label="Temperature", |
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value=0.9, |
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minimum=0.0, |
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maximum=1.0, |
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step=0.05, |
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interactive=True, |
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info="Higher values produce more diverse outputs", |
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), |
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gr.Slider( |
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label="Max new tokens", |
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value=1510, |
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minimum=0, |
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maximum=1510, |
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step=64, |
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interactive=True, |
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info="The maximum numbers of new tokens", |
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), |
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gr.Slider( |
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label="Top-p (nucleus sampling)", |
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value=0.90, |
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minimum=0.0, |
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maximum=1, |
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step=0.05, |
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interactive=True, |
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info="Higher values sample more low-probability tokens", |
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), |
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gr.Slider( |
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label="Repetition penalty", |
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value=1.2, |
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minimum=1.0, |
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maximum=2.0, |
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step=0.05, |
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interactive=True, |
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info="Penalize repeated tokens", |
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), |
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] |
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examples=[ |
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["Generate a NCLEX study plan for me."], |
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["Provide a CV template for a fresh nursing graduate."], |
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["I have a family member that got diagnosed with Buerger's disease, can you explain in easy terms what it is?"], |
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["Could you talk about straight leg rises exercise in the post-surgical context?"], |
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["Could you provide an overview of how the Nurse Practice Act helps regulate the nursing profession in different states?"], |
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] |
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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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additional_inputs=additional_inputs, |
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examples = examples, |
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title="""NGPT-v1""" |
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).launch(show_api=False, share=True) |
