Update app.py

app.py

@@ -25,19 +25,21 @@ QA_CHAIN_PROMPT = PromptTemplate(input_variables = ["context", "question"], temp
 YOUTUBE_DIR = "docs/youtube/" 
 CHROMA_DIR = "docs/chroma/"
 
-def invoke(openai_api_key, youtube_url, prompt, process_video):
+MODEL_NAME = "gpt-4"
+
+def invoke(openai_api_key, youtube_url, process_video, prompt):
     openai.api_key = openai_api_key
-    print(process_video)
-    if (os.path.isdir(CHROMA_DIR) == False):
+    if (process_video):
         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)
         vectordb = Chroma.from_documents(documents = splits, embedding = OpenAIEmbeddings(), persist_directory = CHROMA_DIR)
-        llm = ChatOpenAI(model_name = "gpt-4", temperature = 0)
+        llm = ChatOpenAI(model_name = MODEL_NAME, 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(222)
+    else:
+        print(222)
     result = qa_chain({"query": prompt})
     shutil.rmtree(YOUTUBE_DIR)
     #shutil.rmtree(CHROMA_DIR)
@@ -52,7 +54,7 @@ description = """The app demonstrates how to use a <strong>Large Language Model<
 
 gr.close_all()
 demo = gr.Interface(fn=invoke, 
-                    inputs = [gr.Textbox(label = "OpenAI API Key", value = "sk-", lines = 1), gr.Textbox(label = "YouTube URL", value = "https://www.youtube.com/watch?v=--khbXchTeE", lines = 1), gr.Textbox(label = "Prompt", value = "GPT-4 human level performance", lines = 1), gr.Radio(["Yes", "No"], label="Process Video")],
+                    inputs = [gr.Textbox(label = "OpenAI API Key", value = "sk-", lines = 1), gr.Textbox(label = "YouTube URL", value = "https://www.youtube.com/watch?v=--khbXchTeE", lines = 1), gr.Radio(["Yes", "No"], label="Process Video", value = "Yes"), gr.Textbox(label = "Prompt", value = "GPT-4 human level performance", lines = 1)],
                     outputs = [gr.Textbox(label = "Completion", lines = 1)],
                     title = "Generative AI - LLM & RAG",
                     description = description)