Create app.py

app.py

@@ -0,0 +1,105 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+
+# Deutsche LLM Konfiguration
+HF_TOKEN = os.getenv("tomoniaccess")
+current_model = "dbmdz/german-gpt2"
+client = InferenceClient(model=current_model, token=HF_TOKEN)
+
+conversation_history = []
+
+def enhanced_chat_response(user_input, max_tokens, temperature, top_p):
+    if not user_input.strip():
+        return "", "Bitte gib eine Nachricht ein.", "", ""
+    
+    messages = [{"role": "user", "content": user_input}]
+    
+    response_text = ""
+    try:
+        for message in client.chat_completion(
+            messages=messages,
+            max_tokens=min(max_tokens, 100),
+            stream=True,
+            temperature=temperature,
+            top_p=top_p
+        ):
+            token = message.choices[0].delta.content
+            if token:
+                response_text += token
+                
+    except Exception as e:
+        response_text = "Entschuldigung, da ist ein Fehler aufgetreten."
+    
+    response_text = response_text.strip()
+    
+    chat_display = f"**Du:** {user_input}\n**Assistant:** {response_text}\n\n"
+    
+    return "", response_text, chat_display, ""
+
+def reset_conversation():
+    return "Neues Gespräch gestartet.", "", ""
+
+with gr.Blocks(title="Depression Training Simulator", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🧠 Depression Training Simulator")
+    gr.Markdown("**Übe realistische Gespräche mit depressiven Jugendlichen und erhalte Feedback**")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            # Parameter
+            gr.Markdown("### ⚙️ Einstellungen")
+            max_tokens = gr.Slider(50, 150, value=80, step=10, label="Antwortlänge")
+            temperature = gr.Slider(0.5, 1.2, value=0.9, step=0.1, label="Variabilität")
+            top_p = gr.Slider(0.7, 1.0, value=0.95, step=0.05, label="Fokus")
+            
+            # Actions
+            gr.Markdown("### 🔄 Aktionen")
+            reset_btn = gr.Button("Neues Gespräch", variant="secondary")
+            
+        with gr.Column(scale=2):
+            # Chat Interface
+            gr.Markdown("### 💬 Gespräch")
+            
+            user_input = gr.Textbox(
+                label="Deine Nachricht", 
+                placeholder="Beginne das Gespräch...",
+                lines=2
+            )
+            send_btn = gr.Button("📨 Senden", variant="primary")
+            
+            bot_response = gr.Textbox(
+                label="Antwort", 
+                interactive=False,
+                lines=3
+            )
+            
+            chat_history = gr.Textbox(
+                label="Gesprächsverlauf", 
+                interactive=False,
+                lines=12
+            )
+            
+            # Feedback Panel (empty, no persona feedback)
+            with gr.Accordion("📈 Trainer-Feedback", open=True):
+                feedback_display = gr.Markdown("Starte ein Gespräch, um Feedback zu erhalten.")
+    
+    # Event Bindings
+    send_btn.click(
+        fn=enhanced_chat_response,
+        inputs=[user_input, max_tokens, temperature, top_p],
+        outputs=[user_input, bot_response, chat_history, feedback_display]
+    )
+    
+    user_input.submit(
+        fn=enhanced_chat_response,
+        inputs=[user_input, max_tokens, temperature, top_p],
+        outputs=[user_input, bot_response, chat_history, feedback_display]
+    )
+    
+    reset_btn.click(
+        fn=reset_conversation,
+        outputs=[bot_response, chat_history, feedback_display]
+    )
+
+if __name__ == "__main__":
+    demo.launch(share=True, debug=True)