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import gradio as gr
import os
from openai import OpenAI
print("Gradio version:", gr.__version__)
client = OpenAI(api_key=os.getenv("openai"))
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)}"
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)
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, debug=True, show_api=False)
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