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import gradio as gr
from huggingface_hub import InferenceClient

# Initialize the client with your desired model
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

# # Define the system prompt as an AI Dermatologist
# def format_prompt(message, history):
#     prompt = "<s>"
#     # Start the conversation with a system message
#     prompt += "[INST] You are a Travel Companion Chatbot that helps users plan trips by suggesting transport, sightseeing stops, and accommodations based on their preferences. [/INST]"
#     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 format_prompt(message, history):
#     prompt = "<s>"
#     # Start the conversation with a system message
#     prompt += "[INST] You are a Travel Companion Chatbot that helps users plan trips by suggesting transport, sightseeing stops, and accommodations based on their preferences. Please assist the user by asking what they need to know. [/INST]"
    
#     # Only append the user message, without the historical responses or examples
#     prompt += f"[INST] {message} [/INST]"
    
#     return prompt
def format_prompt(message):
    prompt = "<s>"
    # System message to set the context of the AI's purpose
    prompt += "[INST] You are a Travel Companion chatbot designed to assist users in planning their trips. When a user provides the source, destination, and the number of days they are planning for a trip, you should respond by:\n"
    prompt += "- Suggesting the best travel options (bus, train, flight, etc.) with cost-effective choices.\n"
    prompt += "- Recommending cost-effective hotels and restaurants along the route.\n"
    prompt += "- Highlighting the best places to visit on the route.\n"
    prompt += "Please respond directly to the user's input with a detailed plan, without repeating their message. [/INST]"
    
    # Include the user's message as the input to be processed
    prompt += f"{message}"
    
    return prompt



# Function to generate responses with the AI Dermatologist context
def generate(
    prompt, history, temperature=0.9, 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(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

# Customizable input controls for the chatbot interface
additional_inputs = [
    gr.Slider(
        label="Temperature",
        value=0.9,
        minimum=0.0,
        maximum=1.0,
        step=0.05,
        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",
    )
]

# Define the chatbot interface with the starting system message as AI Dermatologist
gr.ChatInterface(
    fn=generate,
    chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, layout="panel"),
    additional_inputs=additional_inputs,
    title="Travel Companion Chatbot"
).launch(show_api=False)

# Load your model after launching the interface
gr.load("models/Bhaskar2611/Capstone").launch()