Update app.py

app.py

@@ -140,6 +140,11 @@ def clear_all(history):
     # Den "content" auswählen, da dort die Antwort der Ki enthalten ist
     result = data['choices'][0]['message']['content']
 
+    #Alternatives Model umd schlagworte zu finden
+    """
+    llm =  HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 128})
+    result = process_chatverlauf_hf(prompt,llm)
+    """
     #chat hinzufügen zu den chatverläufen und in GUI anzeigen
     id_neu = str(len(chats)+1) + "_" + result
     #chats ist ein dictionary
@@ -438,7 +443,7 @@ def generate_text (prompt, chatbot, history, rag_option, model_option, openai_ap
         else:
             #oder an Hugging Face --------------------------
             print("HF Anfrage.......................")
-            llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 1024}) 
+            llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 128}) 
             #llm = HuggingFaceChain(model=MODEL_NAME_HF, model_kwargs={"temperature": 0.5, "max_length": 128}) 
             #llm = HuggingFaceHub(url_??? = "https://wdgsjd6zf201mufn.us-east-1.aws.endpoints.huggingface.cloud", model_kwargs={"temperature": 0.5, "max_length": 64}) 
             #llm = HuggingFaceTextGenInference( inference_server_url="http://localhost:8010/", max_new_tokens=max_new_tokens,top_k=10,top_p=top_p,typical_p=0.95,temperature=temperature,repetition_penalty=repetition_penalty,)