Update app.py

app.py

@@ -19,12 +19,10 @@ load_dotenv()
 
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
-print(OPENAI_API_KEY)
-
-text_splitter = CharacterTextSplitter(separator = "\n", chunk_size=1000, chunk_overlap=200, length_function = len)
-embeddings = OpenAIEmbeddings(api_key=OPENAI_API_KEY)
-retrieval_qa_chat_prompt = hub.pull("langchain-ai/retrieval-qa-chat")
-llm = ChatOpenAI(api_key=OPENAI_API_KEY)
+# text_splitter = CharacterTextSplitter(separator = "\n", chunk_size=1000, chunk_overlap=200, length_function = len)
+# embeddings = OpenAIEmbeddings(api_key=OPENAI_API_KEY)
+# retrieval_qa_chat_prompt = hub.pull("langchain-ai/retrieval-qa-chat")
+# llm = ChatOpenAI(api_key=OPENAI_API_KEY)
 
 vectordb_path = "./vector_db"
 
@@ -114,7 +112,7 @@ def dbcreate():
 import gradio as gr
 chatbot = gr.Chatbot(avatar_images=["user.png", "bot.jpg"], height=600)
 clear_but = gr.Button(value="Clear Chat")
-demo = gr.ChatInterface(fn=search, title="Mediate.com Chatbot Prototype", multimodal=False, retry_btn=None, undo_btn=None, clear_btn=clear_but, chatbot=chatbot)
+demo = gr.ChatInterface(fn="", title="Mediate.com Chatbot Prototype", multimodal=False, retry_btn=None, undo_btn=None, clear_btn=clear_but, chatbot=chatbot)
 
 if __name__ == "__main__":
     demo.launch(debug=True)