import os
import gradio as gr
from openai import OpenAI
from typing import List, Tuple

# Define available models
AVAILABLE_MODELS = {
    "DeepSeek V3 (Hyperbolic.xyz)": "deepseek-ai/DeepSeek-V3",
    "DeepSeek V3 (HuggingFace.co)": "deepseek-ai/DeepSeek-V3",
    "Llama3.3-70b-Instruct": "meta-llama/Llama-3.3-70B-Instruct",
    "Llama3.1-8b-Instruct": "meta-llama/Meta-Llama-3.1-8B-Instruct",
}

HYPERB_ENDPOINT_URL = "https://api.hyperbolic.xyz/v1"
HF_ENDPOINT_URL = "https://huggingface.co/api/inference-proxy/together"
HYPERB_API_KEY = os.getenv('HYPERBOLIC_XYZ_KEY')
HF_API_KEY = os.getenv('HF_KEY')
PASSWORD = os.getenv("PASSWD")  # Store the password in an environment variable

hyperb_client = OpenAI(base_url=HYPERB_ENDPOINT_URL, api_key=HYPERB_API_KEY)
hf_client = OpenAI(base_url=HF_ENDPOINT_URL, api_key=HF_API_KEY)

def respond(
    message: str,
    history: List[Tuple[str, str]],
    system_message: str,
    model_choice: str,
    max_tokens: int,
    temperature: float,
    top_p: float,
):
    messages = [{"role": "system", "content": system_message}]
    for user_msg, assistant_msg in history:
        if user_msg:
            messages.append({"role": "user", "content": user_msg})
        if assistant_msg:
            messages.append({"role": "assistant", "content": assistant_msg})
    messages.append({"role": "user", "content": message})

    response = ""

    if "(HuggingFace.co)" in model_choice:
        this_client = hf_client
    else:
        this_client = hyperb_client

    for chunk in this_client.chat.completions.create(
        model=AVAILABLE_MODELS[model_choice],  # Use the selected model
        messages=messages,
        max_tokens=max_tokens,
        temperature=temperature,
        top_p=top_p,
        stream=True,
    ):
        token = chunk.choices[0].delta.content or ""
        response += token
        yield response

def check_password(input_password):
    if input_password == PASSWORD:
        return gr.update(visible=False), gr.update(visible=True)
    else:
        return gr.update(value="", interactive=True), gr.update(visible=False)

with gr.Blocks() as demo:
    with gr.Column():
        password_input = gr.Textbox(
            type="password", label="Enter Password", interactive=True
        )
        submit_button = gr.Button("Submit")
        error_message = gr.Textbox(
            label="Error", visible=False, interactive=False
        )

    with gr.Column(visible=False) as chat_interface:
        chat = gr.ChatInterface(
            respond,
            api_name=False,
            additional_inputs=[
                gr.Textbox(value="You are a helpful assistant.", label="System message"),
                gr.Dropdown(
                    choices=list(AVAILABLE_MODELS.keys()),
                    value=list(AVAILABLE_MODELS.keys())[0],
                    label="Select Model"
                ),
                gr.Slider(minimum=1, maximum=30000, value=2048, step=100, 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)"),
            ],
        )

    submit_button.click(check_password, inputs=password_input, outputs=[password_input, chat_interface])

if __name__ == "__main__":
    demo.launch(share=True)