Update app.py

app.py

@@ -1,45 +1,36 @@
 import streamlit as st
 from gpt_researcher import GPTResearcher
-import asyncio
-import nest_asyncio
 import os
 
 # Access secrets
 openai_api_key = st.secrets["OPENAI_API_KEY"]
 tavily_api_key = st.secrets["TAVILY_API_KEY"]
 
-# Apply the asyncio patch from nest_asyncio if required
-nest_asyncio.apply()
-
 # Set the document path environment variable
 os.environ["DOC_PATH"] = "./local"  # Path to the folder with documents
 
 # Constants
 REPORT_TYPE = "research_report"
 
-
-# Define the asynchronous function to fetch the report
-async def fetch_report(query, report_type):
+# Define the function to fetch the report
+def fetch_report(query, report_type):
     """
     Fetch a research report based on the provided query and report type.
-    Research is conducted on a local document related to Google Search Algorithm Leak.
+    Research is conducted on a local document.
     """
     try:
         researcher = GPTResearcher(
             query=query, report_type=report_type, report_source="local"
         )
-        await researcher.conduct_research()
-        return await researcher.write_report()
+        researcher.conduct_research()
+        return researcher.write_report()
     except Exception as e:
         return f"Error during research: {str(e)}"
 
-
-# Function to run the asynchronous function in a separate thread
-def run_async(coroutine):
-    loop = asyncio.new_event_loop()
-    asyncio.set_event_loop(loop)
-    return loop.run_until_complete(coroutine)
-
+# Cache the report generation function to avoid redundant computations
+@st.cache(suppress_st_warning=True, show_spinner=False)
+def cached_fetch_report(query, report_type):
+    return fetch_report(query, report_type)
 
 # Streamlit interface
 st.title("Google Leak Reporting Tool")
@@ -57,10 +48,7 @@ if st.button("Generate Report"):
         st.warning("Please enter a query to generate a report.")
     else:
         with st.spinner("Generating report..."):
-            # Submit the task to the ThreadPoolExecutor
-            future = executor.submit(run_async, fetch_report(query, REPORT_TYPE))
-            # Wait for the result
-            report = future.result()
+            report = cached_fetch_report(query, REPORT_TYPE)
             # Display the report or error message
             if report and not report.startswith("Error"):
                 st.success("Report generated successfully!")
@@ -73,4 +61,4 @@ if st.button("Generate Report"):
                     mime="text/plain",
                 )
             else:
-                st.error(report)  # Show the error message if any
+                st.error(report)  # Show the error message if any