Update app.py

app.py

@@ -11,6 +11,7 @@ from langchain.document_loaders.blob_loaders.youtube_audio import YoutubeAudioLo
 from langchain.document_loaders.generic import GenericLoader
 from langchain.document_loaders.parsers import OpenAIWhisperParser
 from langchain.schema import AIMessage, HumanMessage
+from langchain.llms import HuggingFaceHub
 
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.prompts import PromptTemplate
@@ -73,9 +74,13 @@ YOUTUBE_URL_3 = "https://www.youtube.com/watch?v=vw-KWfKwvTQ"
 
 ################################################
 #LLM Model mit dem gearbeitet wird
+#openai
 MODEL_NAME  = "gpt-3.5-turbo-16k"
 #MODEL_NAME  ="gpt-4"
 
+#HuggingFace
+repo_id = "google/flan-t5-xxl"  
+
 
 ################################################
 #HF Hub Zugriff ermöglichen
@@ -225,7 +230,7 @@ def invoke (prompt, history, openai_api_key, rag_option, temperature=0.9, max_ne
     global splittet
 
     #Prompt an history anhängen und einen Text daraus machen
-    history_text_und_prompt = generate_prompt_with_history(prompt, history)
+    #history_text_und_prompt = generate_prompt_with_history(prompt, history)
     
     #history für HuggingFace Models formatieren
     #history_text_und_prompt = generate_prompt_with_history_hf(prompt, history)
@@ -234,7 +239,7 @@ def invoke (prompt, history, openai_api_key, rag_option, temperature=0.9, max_ne
     #history_text_und_prompt = generate_prompt_with_history_openai(prompt, history)
 
     #history für Langchain formatieren
-    #history_text_und_prompt = generate_prompt_with_history_langchain(prompt, history)
+    history_text_und_prompt = generate_prompt_with_history_langchain(prompt, history)
     
     if (openai_api_key == "" or openai_api_key == "sk-"):
         #raise gr.Error("OpenAI API Key is required.")
@@ -245,10 +250,14 @@ def invoke (prompt, history, openai_api_key, rag_option, temperature=0.9, max_ne
     if (prompt == ""):
         raise gr.Error("Prompt ist erforderlich.")
     try:
+        ###########################
+        #LLM auswählen (OpenAI oder HF)
+        ###########################
         #Anfrage an OpenAI
-        llm = ChatOpenAI(model_name = MODEL_NAME, 
-                         openai_api_key = openai_api_key, 
-                         temperature = 0)
+        #llm = ChatOpenAI(model_name = MODEL_NAME,  openai_api_key = openai_api_key, temperature = 0)
+        #oder an Hugging Face
+        #llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 64})
+        
         #zusätzliche Dokumenten Splits aus DB zum Prompt hinzufügen (aus VektorDB - Chroma oder Mongo DB)
         if (rag_option == "Chroma"):
             #muss nur einmal ausgeführt werden...