Update app.py

app.py

@@ -2,6 +2,7 @@ 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"]
@@ -10,36 +11,29 @@ 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'] = './'  # Path to the folder with documents
+
 # Constants
-REPORT_TYPE = "research_report"  # Fixed report type
-PREDEFINED_SOURCES = [
-    "https://hexdocs.pm/google_api_content_warehouse/",
-    "https://ipullrank.com/google-algo-leak",
-    "https://sparktoro.com/blog/an-anonymous-source-shared-thousands-of-leaked-google-search-api-documents-with-me-everyone-in-seo-should-see-them/"]
+REPORT_TYPE = "research_report"
+DOCUMENT_FILE = 'removed_code.txt'  # Name of the document file
+
+# Function to handle asynchronous calls
+def run_async(coroutine):
+    loop = asyncio.get_event_loop()
+    return loop.run_until_complete(coroutine)
 
-async def fetch_report(query, report_type, sources):
+# Define the asynchronous function to fetch the report
+async def fetch_report(query, report_type):
     """
-    Fetch a research report based on the provided query, report type, and sources.
-    This function assumes that `GPTResearcher` has methods to conduct research and write a report.
+    Fetch a research report based on the provided query and report type.
+    Research is conducted on a local document specified by DOCUMENT_FILE.
     """
-    # Initialize the researcher with required parameters
-    researcher = GPTResearcher(query=query, report_type=report_type, source_urls=sources)
-    
-    # Conduct research
+    researcher = GPTResearcher(query=query, report_type=report_type, report_source='local')
     await researcher.conduct_research()
-    
-    # Write the report after research has been conducted
     report = await researcher.write_report()
-    
-    # Return the completed report
     return report
 
-
-# Function to handle asynchronous calls
-def run_async(coroutine):
-    loop = asyncio.get_event_loop()
-    return loop.run_until_complete(coroutine)
-
 # Streamlit interface
 st.title("Google Leak Reporting Tool")
 
@@ -55,8 +49,8 @@ if st.button("Generate Report"):
         st.warning("Please enter a query to generate a report.")
     else:
         with st.spinner("Generating report..."):
-            # Fetch the report asynchronously using predefined sources and fixed report type
-            fetch_report_coroutine = fetch_report(query, REPORT_TYPE, PREDEFINED_SOURCES)
+            # Fetch the report asynchronously using the local document
+            fetch_report_coroutine = fetch_report(query, REPORT_TYPE)
             report = run_async(fetch_report_coroutine)
             st.success("Report generated successfully!")
-            st.write(report)
+            st.write(report)