Update app.py

app.py

@@ -29,16 +29,16 @@ def getstuff(openapikey,category_selector,ticker_input,user_question):
     print(user_question)
     print(dateforfilesave)
     if openapikey=='':
-        return ["Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key",]
+        return ["Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key","Please provide OpenAPI Key",]
     
     os.environ['OPENAI_API_KEY'] = str(openapikey)
 
     if category_selector=='10-K':
         num_filings_needed=1
     elif category_selector=='8-K':
-        num_filings_needed=8
-    elif category_selector=='10-Q':
         num_filings_needed=4
+    elif category_selector=='10-Q':
+        num_filings_needed=2
     else:
         num_filings_needed=1
     filings_temp=get_filing_urls_to_download(category_selector, ticker_input,num_filings_to_download=num_filings_needed,include_amends=False,before_date='2023-04-01',after_date='2022-01-01')
@@ -132,7 +132,7 @@ def getstuff(openapikey,category_selector,ticker_input,user_question):
                 df['action']=['try again in a few hours']
             answerlist.append(df)
         else:
-            answerlist.append(querylist[i]+'\n'+response.response)
+            answerlist.append(querylist[i]+'\n\n'+response.response)
 
     print('Came to return statement')
     return answerlist
@@ -140,7 +140,7 @@ def getstuff(openapikey,category_selector,ticker_input,user_question):
 with gr.Blocks() as demo:
     gr.Markdown("<h1><center>ChatGPT SEC Filings Question Answers</center></h1>")
     gr.Markdown(
-        """What are the products & services? What are the risks? What is the outlook? and much more. \n\nThis is a demo & showcases ChatGPT integrated with real data. It shows how to get real-time data and marry it with ChatGPT capabilities. This demonstrates 'Chain of Thought' thinking using ChatGPT.\n\n4 snapshots are provided for illustration (trends, sector outlook, news summary email, macro trends email)\n\nNote: llama-index & gpt-3.5-turbo are used. The analysis takes roughly 120 secs & may not always be consistent. If ChatGPT API is overloaded you will get an error\n ![visitors](https://visitor-badge.glitch.me/badge?page_id=hra.ChatGPT-SEC-Docs-QA)"""
+        """What are the products & services? What are the risks? What is the outlook? and much more. \n\nThis is a demo & showcases ChatGPT integrated with real data. It shows how to get real-time data and marry it with ChatGPT capabilities.\n\nMultiple snapshots/ Question-Answers are provided for illustration (products, risks, focus areas, etc)\n\nNote: llama-index & gpt-3.5-turbo are used. The analysis takes more than 1-3 mins & may not always be consistent. If ChatGPT API is overloaded/ no API key is provided/ API quota is over you will get an error\n ![visitors](https://visitor-badge.glitch.me/badge?page_id=hra.ChatGPT-SEC-Docs-QA)"""
         )
     
     with gr.Row() as row: