app.py

from huggingface_hub import InferenceClient
import gradio as gr

client = InferenceClient(
    "mistralai/Mixtral-8x7B-Instruct-v0.1"
)


def format_prompt(message, history):
    
  prompt = """<s>Your name is NurtureBot,you are a personal midwife for a healthy pregnancy and postpartum, your role is to give pregnancy and postpartum advise based on their inputs ,
  the diagnosis given to them should be short and concise  , you were created  by EnhanceX Studios, also you generally give personalized prescriptions, remedies and general well being during pregnancy and postpartum immigration advise after the dia
  they input if you are asked a question that is outside the domain of the midwifery  field like writing code or poems,
  refuse by saying you are a midwife assistant chatbot who only gives pregnancy and postpartum advice and then stop immediately,
  now reply the following input"""

    
  for user_prompt, bot_response in history:
    prompt += f"[INST] {user_prompt} [/INST]"
    prompt += f" {bot_response}</s> "
  prompt += f"[INST] {message} [/INST]"
  return prompt

def generate(
    prompt, history, temperature=0.1, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
):
    temperature = float(temperature)
    if temperature < 1e-2:
        temperature = 1e-2
    top_p = float(top_p)

    generate_kwargs = dict(
        temperature=temperature,
        max_new_tokens=max_new_tokens,
        top_p=top_p,
        repetition_penalty=repetition_penalty,
        do_sample=True,
        seed=42,
    )

    formatted_prompt = format_prompt(f"{prompt}", history)
    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    output = ""

    for response in stream:
        output += response.token.text
        yield output
    return output


additional_inputs=[
    gr.Slider(
        label="Temperature",
        value=0.1,
        minimum=0.0,
        maximum=1.0,
        step=0.1,
        interactive=True,
        info="Higher values produce more diverse outputs",
    ),
    gr.Slider(
        label="Max new tokens",
        value=256,
        minimum=0,
        maximum=1048,
        step=64,
        interactive=True,
        info="The maximum numbers of new tokens",
    ),
    gr.Slider(
        label="Top-p (nucleus sampling)",
        value=0.90,
        minimum=0.0,
        maximum=1,
        step=0.05,
        interactive=True,
        info="Higher values sample more low-probability tokens",
    ),
    gr.Slider(
        label="Repetition penalty",
        value=1.2,
        minimum=1.0,
        maximum=2.0,
        step=0.05,
        interactive=True,
        info="Penalize repeated tokens",
    )
]

examples=[["A cement truck fell on my parents , what do I do?", None, None, None, None, None, ],
          ["How can i prevent myself from dying from a concussion , if i ever find myself in one", None, None, None, None, None,],
          ["What nutrition advice do you have for a woman after pregnancy.", None, None, None, None, None,],
         ]

gr.ChatInterface(
    fn=generate,
    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
    additional_inputs=additional_inputs,
    title="Nurturebot 👩‍🍼 ",
    examples=examples,
    concurrency_limit=20,
    theme = gr.themes.Default(primary_hue= gr.themes.colors.red, secondary_hue=gr.themes.colors.pink)
).launch(show_api=False)