Update app.py

app.py

@@ -27,9 +27,6 @@ CHROMA_DIR = "docs/chroma/"
 
 MODEL_NAME = "gpt-4"
 
-VECTOR_DB = None
-QA_CHAIN = None
-
 def invoke(openai_api_key, youtube_url, process_video, prompt):
     openai.api_key = openai_api_key
     if (process_video):
@@ -38,12 +35,12 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
         docs = loader.load()
         text_splitter = RecursiveCharacterTextSplitter(chunk_size = 1500, chunk_overlap = 150)
         splits = text_splitter.split_documents(docs)
-        VECTOR_DB = Chroma.from_documents(documents = splits, embedding = OpenAIEmbeddings(), persist_directory = CHROMA_DIR)
-        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})
     else:
         print(222)
-    result = QA_CHAIN({"query": prompt})
+    vector_db = Chroma.from_documents(documents = splits, embedding = OpenAIEmbeddings(), persist_directory = CHROMA_DIR)
+    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})
+    result = qa_chain({"query": prompt})
     shutil.rmtree(YOUTUBE_DIR)
     #shutil.rmtree(CHROMA_DIR)
     return result["result"]