Spaces:
Running
Running
File size: 2,394 Bytes
c0a2f04 a1d082f 5654a6b dbcc073 5654a6b c0a2f04 5654a6b dbcc073 187985b dbcc073 c0a2f04 dbcc073 5654a6b 07df051 dbcc073 f32cee6 07df051 e1ecda6 187985b 5654a6b e1ecda6 07df051 527848d c0a2f04 187985b c0a2f04 e1ecda6 04d19e0 c0a2f04 04d19e0 187985b c0a2f04 5229ff8 c0a2f04 187985b 5654a6b 187985b f32cee6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
import streamlit as st
from gpt_researcher import GPTResearcher
import asyncio
import nest_asyncio
import os
from contextlib import contextmanager
from io import StringIO
import sys
# 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"
# Function to handle asynchronous calls
def run_async(coroutine):
loop = asyncio.get_event_loop()
return loop.run_until_complete(coroutine)
# Define the asynchronous function to fetch the report
async 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.
"""
try:
researcher = GPTResearcher(
query=query, report_type=report_type, report_source="local"
)
await researcher.conduct_research()
return await researcher.write_report()
except Exception as e:
return f"Error during research: {str(e)}"
# Streamlit interface
st.title("Google Leak Reporting Tool")
# User input for the query using a text area
query = st.text_area(
"Enter your research query:",
"Extract all the information about how the ranking for internal links works.",
height=150, # Adjustable height
)
# Start the report generation process
if st.button("Generate Report"):
if not query:
st.warning("Please enter a query to generate a report.")
else:
with st.spinner("Generating report..."):
report = run_async(fetch_report(query, REPORT_TYPE))
# Display the report or error message
if report and not report.startswith("Error"):
st.success("Report generated successfully!")
st.write(report) # Display the report in the app
# Create a download button for the report
st.download_button(
label="Download Report as Text File",
data=report,
file_name="research_report.txt",
mime="text/plain",
)
else:
st.error(report) # Show the error message if any |