Update app.py

app.py

@@ -31,10 +31,8 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
     openai.api_key = openai_api_key
     if (process_video):
         if (os.path.isdir(CHROMA_DIR)):
-            print(os.listdir(CHROMA_DIR))
             shutil.rmtree(CHROMA_DIR)
         if (os.path.isdir(YOUTUBE_DIR)):
-            print(os.listdir(YOUTUBE_DIR))
             shutil.rmtree(YOUTUBE_DIR)
         loader = GenericLoader(YoutubeAudioLoader([youtube_url], YOUTUBE_DIR), OpenAIWhisperParser())
         docs = loader.load()
@@ -42,10 +40,6 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
         splits = text_splitter.split_documents(docs)
         vector_db = Chroma.from_documents(documents = splits, embedding = OpenAIEmbeddings(), persist_directory = CHROMA_DIR)
     else:
-        if (os.path.isdir(CHROMA_DIR)):
-            print(os.listdir(CHROMA_DIR))
-        if (os.path.isdir(YOUTUBE_DIR)):
-            print(os.listdir(YOUTUBE_DIR))
         vector_db = Chroma(persist_directory = CHROMA_DIR, embedding_function = OpenAIEmbeddings())
     llm = ChatOpenAI(model_name = MODEL_NAME, temperature = 0)
     qa_chain = RetrievalQA.from_chain_type(llm, retriever = vector_db.as_retriever(), return_source_documents = True, chain_type_kwargs = {"prompt": QA_CHAIN_PROMPT})
@@ -56,9 +50,8 @@ description = """<strong>Overview:</strong> The app demonstrates how to use a <s
                  (RAG) on external data (YouTube videos in this case, but could be PDFs, URLs, databases, etc.)\n\n
                  <strong>Instructions:</strong> Enter an OpenAI API key, YouTube URL, and prompt to perform semantic search, sentiment analysis, summarization, 
                  translation, etc. "Process Video" specifies whether or not to perform speech-to-text processing. To ask multiple questions related to the same video, 
-                 typically set it to "True" the first time and then to "False". Note that persistence is not guaranteed in the Hugging Face free tier 
-                 (the plan is to migrate to AWS S3). The example is a 3:12 min. video about GPT-4 and takes about 20 sec. to process. Try different prompts, for example 
-                 "what is gpt-4, answer in german" or "write a poem about gpt-4".\n\n
+                 typically set it to "True" the first run and then to "False". The example is a 3:12 min. video about GPT-4 and takes about 20 sec. to process. 
+                 Try different prompts, for example "what is gpt-4, answer in german" or "write a poem about gpt-4".\n\n
                  <strong>Technology:</strong> <a href='https://www.gradio.app/'>Gradio</a> UI using <a href='https://platform.openai.com/'>OpenAI</a> API 
                  via AI-first <a href='https://www.langchain.com/'>LangChain</a> toolkit with <a href='https://openai.com/research/whisper'>Whisper</a> (speech-to-text) 
                  and <a href='https://openai.com/research/gpt-4'>GPT-4</a> (LLM) foundation models as well as AI-native