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

# Initialisiere OpenAI-Client mit API Key
client = OpenAI(api_key=os.getenv("openai"))

print("Gradio version:", gr.__version__)

conversation_history = []
model_name = "gpt-3.5-turbo"

def enhanced_chat_response(user_input, max_tokens, temperature, top_p):
    if not user_input.strip():
        return "", "*Bitte gib eine Nachricht ein.*", ""

    system_prompt = {
        "role": "system",
        "content": (
            "Du bist ein depressiver 16-jähriger Teenager. "
            "Bleibe durchgehend in deiner Rolle. "
            "Du weißt NICHT, dass du eine KI bist."
        )
    }

    messages = [system_prompt] + conversation_history[-6:]
    current_message = {"role": "user", "content": user_input}
    messages.append(current_message)

    try:
        response = client.chat.completions.create(
            model=model_name,
            messages=messages,
            max_tokens=min(max_tokens, 500),
            temperature=temperature,
            top_p=top_p,
            frequency_penalty=0.1,
            presence_penalty=0.1
        )
        response_text = response.choices[0].message.content
    except Exception as e:
        print("API Error:", e)
        response_text = "*schweigt und starrt auf den Boden*"

    conversation_history.append(current_message)
    conversation_history.append({"role": "assistant", "content": response_text})

    chat_display = ""
    for msg in conversation_history:
        role = "**Du:**" if msg["role"] == "user" else "**Teenager:**"
        chat_display += f"{role} {msg['content']}\n\n"

    return "", response_text, chat_display

def reset_conversation():
    global conversation_history
    conversation_history = []
    return "Neues Gespräch gestartet.", ""

def test_api_connection():
    try:
        response = client.chat.completions.create(
            model=model_name,
            messages=[{"role": "user", "content": "Hi"}],
            max_tokens=10
        )
        return "✅ API Verbindung erfolgreich"
    except Exception as e:
        return f"❌ API Error: {str(e)}"

# UI
with gr.Blocks() as demo:
    gr.Markdown("## 🧠 Depression Training Simulator")
    gr.Markdown("**Übe realistische Gespräche mit einem 16-jährigen Teenager mit Depressionen.**")

    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown("### ⚙️ Einstellungen")
            max_tokens = gr.Slider(50, 500, value=200, step=10, label="Max. Antwortlänge")
            temperature = gr.Slider(0.7, 1.3, value=1.0, step=0.1, label="Kreativität (Temperature)")
            top_p = gr.Slider(0.5, 1.0, value=0.9, step=0.05, label="Top-p (Fokus)")

            gr.Markdown("### 🔧 API Status")
            api_status = gr.Textbox(label="Status", value="")
            api_test_btn = gr.Button("API testen")

            gr.Markdown("### 🔄 Aktionen")
            reset_btn = gr.Button("Neues Gespräch")

        with gr.Column(scale=2):
            gr.Markdown("### 💬 Gespräch")
            user_input = gr.Textbox(
                label="Deine Nachricht", 
                placeholder="Hallo, wie geht es dir heute?",
                lines=2
            )
            send_btn = gr.Button("📨 Senden")

            bot_response = gr.Textbox(
                label="Antwort", 
                value="",
                lines=3
            )

            chat_history = gr.Textbox(
                label="Gesprächsverlauf",
                value="",
                lines=15
            )

    # Event Bindings
    send_btn.click(
        fn=enhanced_chat_response,
        inputs=[user_input, max_tokens, temperature, top_p],
        outputs=[user_input, bot_response, chat_history]
    )

    user_input.submit(
        fn=enhanced_chat_response,
        inputs=[user_input, max_tokens, temperature, top_p],
        outputs=[user_input, bot_response, chat_history]
    )

    reset_btn.click(
        fn=reset_conversation,
        outputs=[bot_response, chat_history]
    )

    api_test_btn.click(
        fn=test_api_connection,
        outputs=[api_status]
    )

if __name__ == "__main__":
    if not os.getenv("openai"):
        print("❌ FEHLER: openai Umgebungsvariable ist nicht gesetzt!")
    else:
        print("✅ OpenAI API Key gefunden")
        demo.launch(share=False)