Create app.py

app.py

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+import gradio as gr
+from openai import OpenAI
+import os
+
+# Liste der verfügbaren Modelle
+MODELS = [
+    "llama3-70b-8192",
+    "llama3-8b-8192",
+    "qwen-qwq-32b",
+    "mistral-saba-24b",
+    "qwen-2.5-coder-32b",
+    "qwen-2.5-32b",
+    "deepseek-r1-distill-qwen-32b",
+    "deepseek-r1-distill-llama-70b-specdec",
+    "deepseek-r1-distill-llama-70b",
+    "llama-3.2-3b-preview",
+    "llama-3.2-11b-vision-preview"
+]
+
+def predict(model, input_text):
+    # Initialisiere den Groq Client
+    client = OpenAI(
+        base_url="https://api.groq.com/openai/v1",
+        api_key=os.environ.get("GROQ_API_KEY"),
+    )
+
+    # Sende Anfrage an die Groq API
+    completion = client.chat.completions.create(
+        model=model,
+        messages=[
+            {
+                "role": "user",
+                "content": input_text
+            }
+        ],
+        temperature=0.5,
+        max_tokens=1024,
+        top_p=1,
+        stream=False,
+        stop=None,
+    )
+
+    return completion.choices[0].message.content
+
+# Erstelle die Gradio Oberfläche
+with gr.Blocks() as demo:
+    gr.Markdown("# Groq API Chat Interface")
+    
+    with gr.Row():
+        model_dropdown = gr.Dropdown(
+            choices=MODELS,
+            value=MODELS[0],
+            label="Wähle ein Modell"
+        )
+    
+    with gr.Row():
+        input_text = gr.Textbox(
+            label="Eingabe",
+            placeholder="Gib deine Nachricht hier ein..."
+        )
+    
+    output_text = gr.Textbox(label="Antwort", interactive=False)
+    
+    submit_btn = gr.Button("Absenden")
+    submit_btn.click(
+        fn=predict,
+        inputs=[model_dropdown, input_text],
+        outputs=output_text
+    )
+
+if __name__ == "__main__":
+    demo.launch()