import gradio as gr
from huggingface_hub import InferenceClient

# ----------------------------
# Function to handle user input
# ----------------------------
def respond(
    message,
    history: list[dict[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
    hf_token: gr.OAuthToken,
):
    """
    Respond to user input using Hugging Face Inference API.
    """

    # Create client
    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")

    # Prepare system + chat messages
    messages = [{"role": "system", "content": system_message}]
    messages.extend(history)
    messages.append({"role": "user", "content": message})

    response = ""

    # Stream responses from the model
    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        choices = message.choices
        token = ""
        if len(choices) and choices[0].delta.content:
            token = choices[0].delta.content
        response += token
        yield response


# ----------------------------
# Gradio ChatInterface
# ----------------------------
chatbot = gr.ChatInterface(
    respond,
    type="messages",
    additional_inputs=[
        gr.Textbox(
            value=(
                "You are a medical assistant. "
                "Provide general health information, symptom guidance, "
                "and safety advice. DO NOT give diagnosis or treatment."
            ),
            label="System message",
        ),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

# ----------------------------
# Layout with Sidebar for Login
# ----------------------------
with gr.Blocks(title="🩺 Medical Health Chatbot") as demo:
    with gr.Sidebar():
        gr.Markdown("## Login to access the medical chatbot")
        gr.LoginButton()
    gr.Markdown("# 🏥 Medical Health Assistant")
    gr.Markdown(
        "Ask health-related questions. "
        "This assistant provides general guidance and safety info only."
    )
    chatbot.render()

# ----------------------------
# Launch app
# ----------------------------
if __name__ == "__main__":
    demo.launch()