Update app.py

app.py

@@ -62,6 +62,7 @@ RAG_CHAIN_PROMPT = PromptTemplate(input_variables = ["context", "question"],
 HUGGINGFACEHUB_API_TOKEN = os.getenv("HF_ACCESS_READ")
 OAI_API_KEY=os.getenv("OPENAI_API_KEY")
 
+
 #Pfad, wo Docs/Bilder/Filme abgelegt werden können - lokal, also hier im HF Space (sonst auf eigenem Rechner)
 PATH_WORK = "."
 CHROMA_DIR  = "/chroma"
@@ -79,8 +80,11 @@ YOUTUBE_URL_2 = "https://www.youtube.com/watch?v=hdhZwyf24mE"
 #LLM Model mit dem gearbeitet wird
 #openai-------------------------------------
 #MODEL_NAME  = "gpt-3.5-turbo-16k"
-#MODEL_NAME  ="gpt-4"
-MODEL_NAME = "text-davinci-004"
+MODEL_NAME  ="gpt-4"
+#verfügbare Modelle anzeigen lassen
+openai_obj = OpenAI(api_key=OAI_API_KEY)
+model_list = openai_obj.list_models()
+print(model_list)
 
 #HuggingFace--------------------------------
 #repo_id = "meta-llama/Llama-2-13b-chat-hf"   
@@ -89,7 +93,7 @@ repo_id = "HuggingFaceH4/zephyr-7b-alpha"   #das Modell ist echt gut!!! Vom MIT
 #repo_id = "tiiuae/falcon-40b"  
 #repo_id = "Vicuna-33b"
 #repo_id = "alexkueck/ChatBotLI2Klein"
-#repo_id ="mistralai/Mistral-7B-v0.1"
+#repo_id = "mistralai/Mistral-7B-v0.1"
 #repo_id = "internlm/internlm-chat-7b"
 #repo_id = "Qwen/Qwen-7B"
 #repo_id = "Salesforce/xgen-7b-8k-base"