app-mixtral-plain.py

import gradio as gr
import os
from huggingface_hub import InferenceClient

# Load token and model
HF_TOKEN = os.getenv("tomoniaccess")
client = InferenceClient(
    model="mistralai/Mixtral-8x7B-Instruct-v0.1",
    token=HF_TOKEN
)

conversation_history = []
model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"

def query_mixtral(messages, max_tokens=200, temperature=1.0, top_p=0.9):
    """Query Mixtral-8x7B model via Hugging Face InferenceClient"""
    try:
        response = client.chat_completion(
            messages=messages,
            max_tokens=max_tokens,
            temperature=temperature,
            top_p=top_p,
            stream=False
        )
        return response.choices[0].message.content
    except Exception as e:
        raise Exception(f"InferenceClient Error: {str(e)}")

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_text = query_mixtral(messages, max_tokens, temperature, top_p)
    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:
        test_messages = [
            {"role": "system", "content": "Du bist ein hilfsbereit Assistent."},
            {"role": "user", "content": "Hallo"}
        ]
        
        response = query_mixtral(test_messages, max_tokens=10)
        return f"✅ API Verbindung erfolgreich: {response[:50]}..."
    except Exception as e:
        return f"❌ API Error: {str(e)}"

# UI
with gr.Blocks(title="Mixtral Depression Training Simulator") as demo:
    gr.Markdown("## 🧠 Depression Training Simulator (Mixtral-8x7B)")
    gr.Markdown("**Übe realistische Gespräche mit einem 16-jährigen Teenager mit Depressionen.**")
    gr.Markdown("*Powered by Mixtral-8x7B-Instruct-v0.1*")

    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(0.1, 2.0, value=0.7, step=0.1, label="Kreativität (Temperature)")
            top_p = gr.Slider(0.1, 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")
            
            gr.Markdown("### 📋 Setup")
            gr.Markdown("""
            **Benötigt:**
            - `tomoniaccess` Umgebungsvariable mit HF Token
            - `pip install huggingface_hub gradio`
            """)

        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__":
    print("🚀 Mixtral Depression Training Simulator")
    print(f"📊 Model: {model_name}")
    
    if not HF_TOKEN:
        print("❌ FEHLER: tomoniaccess Umgebungsvariable ist nicht gesetzt!")
        print("   Bitte setze deinen Hugging Face Token als 'tomoniaccess' Umgebungsvariable.")
    else:
        print("✅ Hugging Face API Token gefunden")
    
    print("\n📦 Benötigte Pakete:")
    print("pip install huggingface_hub gradio")
    
    demo.launch(share=False)