Update app.py

app.py

@@ -24,26 +24,25 @@ custom_css = """
 
 # Verwende die integrierten Embeddings von ChromaDB
 embedding_function = embedding_functions.DefaultEmbeddingFunction()
+client = Client("Qwen/Qwen2.5-72B-Instruct")
 
 def update(json):
-    url = 'https://api.groq.com/openai/v1/chat/completions'
-    options = {
-        'method': 'POST',
-        'headers': {
-            'Authorization': f"{groq}",
-            'Content-Type': 'application/json'
-        },
-        'body': json.dumps({
-            'messages': [{'role': 'user', 'content': json}],
-            'model': 'mixtral-8x7b-32768'
-        })
-    }
-
-    response = requests.post(url, headers=options['headers'], json=options['body'])
-    data = response.json()
-    response_content = data['choices'][0]['message']['content']
+
+    client = groq.Client(api_key=f"{groq}")
     
-client = Client("Qwen/Qwen2.5-72B-Instruct")
+    try:
+        # Use Llama 3 70B powered by Groq for text generation
+        completion = client.chat.completions.create(
+            model="llama3-70b-8192",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": f"{json}"}
+            ],
+        )
+        return completion.choices[0].message.content
+    except Exception as e:
+        return f"Error in response generation: {str(e)}"
+
 
 #def text_to_speech(text):
     #engine = pyttsx3.init()
@@ -59,7 +58,7 @@ def transcribe_audio(audio):
         audio_data = recognizer.record(source)
         try:
             text = recognizer.recognize_google(audio_data, language="de-DE")
-            #result = update(text)
+            result = update(text)
             #return result
             result = client.predict(
                 query=text,