Update app.py

app.py

@@ -45,7 +45,6 @@ retriever = vectorstore_persisted.as_retriever(
 
 
 # Prepare the logging functionality
-
 log_file = Path("logs/") / f"data_{uuid.uuid4()}.json"
 log_folder = log_file.parent
 
@@ -58,7 +57,6 @@ scheduler = CommitScheduler(
 )
 
 # Define the Q&A system message
-
 qna_system_message = """
 You are an AI assistant to help Finsights Grey Inc., an innovative financial technology firm, develop a Retrieval-Augmented Generation (RAG) system to automate the extraction, summarization, and analysis of information from 10-K reports. Your knowledge base was last updated in August 2023.
 
@@ -142,7 +140,6 @@ def predict(user_input,company):
 # Set-up the Gradio UI
 # Add text box and radio button to the interface
 # The radio button is used to select the company 10k report in which the context needs to be retrieved.
-
 with gr.Blocks() as demo:
     with gr.Row():
         question = gr.Textbox(label="Enter your question")
@@ -159,8 +156,7 @@ with gr.Blocks() as demo:
 
 demo.launch()
 # Create the interface
-# For the inputs parameter of Interface provide [textbox,company]
-
+# For the inputs parameter of Interface, provide [textbox, company]
 
 demo.queue()
 demo.launch(auth=("demouser", os.getenv('PASSWD')))