import openai
import os
import gradio as gr
from openai import OpenAI

# Ensure the OPENAI_API_KEY environment variable is set
openai.api_key = os.getenv("OPENAI_API_KEY")

if openai.api_key is None:
    raise ValueError("Die Umgebungsvariable OPENAI_API_KEY ist nicht gesetzt.")

client = OpenAI()

def chat_with_gpt(user_input, system_message, temperature, history):
    if not history:
        # If starting a new conversation, add the system message first
        history = [{"role": "system", "content": system_message}]

    # Append the latest user message
    history.append({"role": "user", "content": user_input})
    
    # Get response from GPT-3.5 Turbo
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=history,
        temperature=temperature
    )
    
    # Append the assistant's response
    assistant_message = response.choices[0].message['content']
    history.append({"role": "assistant", "content": assistant_message})
    
    return history, history  # Return updated history for both display and state

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("### Chatte mit deinem Mini-Game")
    with gr.Row():
        system_message = gr.Textbox(value="Du bist ein dickköpfiger Bürokrat, der nicht hilfreich sein will.", label="Systemnachricht", placeholder="Gib hier die Systemnachricht ein...")
        user_input = gr.Textbox(label="Deine Nachricht", placeholder="Gib hier deine Chatnachricht ein...")
        temperature_slider = gr.Slider(minimum=0, maximum=1, step=0.01, value=0.7, label="Temperatur")
        submit_button = gr.Button("Senden")
    chat_container = gr.Chatbot(label="Chatverlauf")
    history_state = gr.State([])  # Using Gradio State to maintain conversation history

    submit_button.click(fn=chat_with_gpt, 
                        inputs=[user_input, system_message, temperature_slider, history_state], 
                        outputs=[chat_container, history_state])

# Launch the Gradio app
demo.launch()