Update app.py

app.py

@@ -412,7 +412,7 @@ def generate_prompt_with_history_langchain(prompt, history):
 def generate_auswahl(prompt, file, chatbot, history, rag_option, model_option, openai_api_key, k=3, top_p=0.6, temperature=0.5, max_new_tokens=4048, max_context_length_tokens=2048, repetition_penalty=1.3,):
         #kein Bild hochgeladen -> auf Text antworten...
         if (file == None):
-            result = generate_text(prompt, file, chatbot, history, rag_option, model_option, openai_api_key, k=3, top_p=0.6, temperature=0.5, max_new_tokens=4048, max_context_length_tokens=2048, repetition_penalty=1.3,)
+            result = generate_text(prompt, chatbot, history, rag_option, model_option, openai_api_key, k=3, top_p=0.6, temperature=0.5, max_new_tokens=4048, max_context_length_tokens=2048, repetition_penalty=1.3,)
             history = history + [(prompt, result)]
             #Antwort als Stream ausgeben... wenn Textantwort gefordert
         else:
@@ -465,7 +465,7 @@ def generate_text_zu_bild(file, prompt):
 ####################################################
 #aus einem Text-Prompt die Antwort von KI bekommen
 #mit oder ohne RAG möglich
-def generate_text (prompt, file, chatbot, history, rag_option, model_option, openai_api_key, k=3, top_p=0.6, temperature=0.5, max_new_tokens=4048, max_context_length_tokens=2048, repetition_penalty=1.3,):
+def generate_text (prompt, chatbot, history, rag_option, model_option, openai_api_key, k=3, top_p=0.6, temperature=0.5, max_new_tokens=4048, max_context_length_tokens=2048, repetition_penalty=1.3,):
     global splittet
     print(splittet)
 
@@ -479,7 +479,7 @@ def generate_text (prompt, file, chatbot, history, rag_option, model_option, ope
         raise gr.Error("Prompt ist erforderlich.")
         
     #Prompt an history anhängen und einen Text daraus machen
-    history_text_und_prompt = generate_prompt_with_history_openai(prompt, history)
+    history_text_und_prompt = generate_prompt_with_history(prompt, history)
     print("hist_text...................")
     print(history_text_und_prompt)
     #history für HuggingFace Models formatieren