Update app.py

app.py

@@ -27,11 +27,8 @@ _ = load_dotenv(find_dotenv())
   #api_key=os.getenv("OPENAI_API_KEY"),  
 #)
 
-
-
-
-
-#openai.api_key = os.getenv["OPENAI_API_KEY"]
+#nur bei ersten Anfrage splitten der Dokumente
+splitted = False
 
 #Für MongoDB statt Chroma als Vektorstore
 #MONGODB_URI = os.environ["MONGODB_ATLAS_CLUSTER_URI"]
@@ -63,9 +60,11 @@ YOUTUBE_URL_1 = "https://www.youtube.com/watch?v=--khbXchTeE"
 YOUTUBE_URL_2 = "https://www.youtube.com/watch?v=hdhZwyf24mE"
 YOUTUBE_URL_3 = "https://www.youtube.com/watch?v=vw-KWfKwvTQ"
 
-MODEL_NAME  = "gpt-3.5-turbo-16k"
+#MODEL_NAME  = "gpt-3.5-turbo-16k"
+MODEL_NAME  ="gpt-4"
 
 def document_loading_splitting():
+    global splittet = True
     # Document loading
     docs = []
     # Load PDF
@@ -127,6 +126,8 @@ def rag_chain(llm, prompt, db):
     return result["result"]
 
 def invoke(openai_api_key, rag_option, prompt):
+    global splittet
+    
     if (openai_api_key == "" or openai_api_key == "sk-"):
         #raise gr.Error("OpenAI API Key is required.")
         openai_api_key= OAI_API_KEY
@@ -140,8 +141,9 @@ def invoke(openai_api_key, rag_option, prompt):
                          temperature = 0)
         if (rag_option == "Chroma"):
             #muss nur einmal ausgeführt werden... 
-            #splits = document_loading_splitting()
-            #document_storage_chroma(splits)
+            if not splittet:
+                splits = document_loading_splitting()
+                document_storage_chroma(splits)
             db = document_retrieval_chroma(llm, prompt)
             result = rag_chain(llm, prompt, db)
         elif (rag_option == "MongoDB"):