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Update app.py
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app.py
CHANGED
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@@ -22,31 +22,27 @@ if not openai_api_key or not tavily_api_key:
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# Define the asynchronous function to get the report and capture logs
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async def get_report(query: str, report_type: str, sources: list, report_source: str):
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f = io.StringIO()
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logs_container = st.empty()
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-
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with redirect_stdout(f):
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if report_source == 'local':
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os.environ['DOC_PATH'] = './uploads'
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researcher = GPTResearcher(query=query, report_type=report_type, report_source=report_source)
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else:
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researcher = GPTResearcher(query=query, report_type=report_type, source_urls=sources)
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# Start the research process
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await researcher.conduct_research()
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while True:
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logs = f.getvalue()
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await asyncio.sleep(1) # Wait for a second before the next update
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if "Finalized research step" in logs:
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break
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# Generate the final report
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report = await researcher.write_report()
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return report, f.getvalue()
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# Function to create PDF using fpdf with UTF-8 encoding
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class PDF(FPDF):
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def header(self):
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@@ -93,7 +89,6 @@ with st.expander("Why Use GPT Researcher?", expanded=False):
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- **Up-to-Date Information**: Unlike traditional LLMs, GPT Researcher avoids outdated information and minimizes the risk of hallucinations.
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- **Comprehensive Reports**: Capable of producing long, detailed research reports (2,000+ words).
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- **Reduced Misinformation**: By considering a wide range of sources, it minimizes the risks associated with limited or biased information.
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For more details, visit the [GPT Researcher GitHub repository](https://github.com/assafelovic/gpt-researcher).
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""")
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@@ -205,4 +200,4 @@ hide_streamlit_style = """
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footer {visibility: hidden;}
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</style>
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"""
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st.markdown(hide_streamlit_style, unsafe_allow_html=True)
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# Define the asynchronous function to get the report and capture logs
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async def get_report(query: str, report_type: str, sources: list, report_source: str):
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f = io.StringIO()
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logs_container = st.empty()
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with redirect_stdout(f):
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if report_source == 'local':
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# Set the DOC_PATH environment variable
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os.environ['DOC_PATH'] = './uploads'
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researcher = GPTResearcher(query=query, report_type=report_type, report_source=report_source)
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else:
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researcher = GPTResearcher(query=query, report_type=report_type, source_urls=sources)
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await researcher.conduct_research()
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while True:
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logs = f.getvalue()
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logs_container.text_area("Agent Logs", logs, height=200, key="realtime_logs_display")
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await asyncio.sleep(1) # Update every second
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if "Finalized research step" in logs:
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break
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report = await researcher.write_report()
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return report, f.getvalue()
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# Function to create PDF using fpdf with UTF-8 encoding
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class PDF(FPDF):
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def header(self):
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- **Up-to-Date Information**: Unlike traditional LLMs, GPT Researcher avoids outdated information and minimizes the risk of hallucinations.
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- **Comprehensive Reports**: Capable of producing long, detailed research reports (2,000+ words).
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- **Reduced Misinformation**: By considering a wide range of sources, it minimizes the risks associated with limited or biased information.
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For more details, visit the [GPT Researcher GitHub repository](https://github.com/assafelovic/gpt-researcher).
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""")
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footer {visibility: hidden;}
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</style>
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"""
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st.markdown(hide_streamlit_style, unsafe_allow_html=True)
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