import gradio as gr
from openai import OpenAI
import os

ACCESS_TOKEN = os.getenv("HF_TOKEN")
print("Access token loaded.")

client = OpenAI(
    base_url="https://api-inference.huggingface.co/v1/",
    api_key=ACCESS_TOKEN,
)
print("OpenAI client initialized.")

def respond(
    message,
    history: list[tuple[str, str]],
    system_message
):
    print(f"Received message: {message}")
    print(f"History: {history}")
    print(f"System message: {system_message}")
    
    messages = [{"role": "system", "content": system_message}]
    
    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})
    
    messages.append({"role": "user", "content": message})
    
    model_to_use = "meta-llama/Llama-3.2-3B-Instruct"
    
    response = ""
    
    for message_chunk in client.chat.completions.create(
        model=model_to_use,
        max_tokens=2048,
        stream=True,
        temperature=0.7,
        top_p=0.95,
        frequency_penalty=0.0,
        seed=None,
        messages=messages,
    ):
        token_text = message_chunk.choices[0].delta.content
        response += token_text
        yield response

chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="ChatGPT is initializing...", likeable=True, layout="panel")

demo = gr.ChatInterface(
    fn=respond,
    fill_height=True,
    chatbot=chatbot,
    theme="Nymbo/Nymbo_Theme",
)

if __name__ == "__main__":
    print("Launching the ChatGPT-Llama...")
    demo.launch()