Update app.py

app.py

@@ -25,23 +25,22 @@ QA_CHAIN_PROMPT = PromptTemplate(input_variables = ["context", "question"], temp
 YOUTUBE_DIR = "docs/youtube/" 
 CHROMA_DIR = "docs/chroma/"
 
+shutil.rmtree(CHROMA_DIR)
+
 def invoke(openai_api_key, youtube_url, prompt):
     openai.api_key = openai_api_key
-    global qa_chain
     if (os.path.isdir(CHROMA_DIR) == False):
-        print(1)
-        #youtube_dir = "docs/youtube/"
+        print(111)
         loader = GenericLoader(YoutubeAudioLoader([youtube_url], YOUTUBE_DIR), OpenAIWhisperParser())
         docs = loader.load()
         text_splitter = RecursiveCharacterTextSplitter(chunk_size = 1500, chunk_overlap = 150)
         splits = text_splitter.split_documents(docs)
-        #chroma_dir = "docs/chroma/"
         vectordb = Chroma.from_documents(documents = splits, embedding = OpenAIEmbeddings(), persist_directory = CHROMA_DIR)
         llm = ChatOpenAI(model_name = "gpt-4", temperature = 0)
         qa_chain = RetrievalQA.from_chain_type(llm, retriever = vectordb.as_retriever(), return_source_documents = True, chain_type_kwargs = {"prompt": QA_CHAIN_PROMPT})
-    print(2)
+    print(222)
     result = qa_chain({"query": prompt})
-    #shutil.rmtree(YOUTUBE_DIR)
+    shutil.rmtree(YOUTUBE_DIR)
     #shutil.rmtree(CHROMA_DIR)
     return result["result"]