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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) |