Update app.py

app.py

@@ -17,20 +17,6 @@ os.environ.setdefault("LLM_PROVIDER", "openai")
 os.environ.setdefault("EMBEDDING_PROVIDER", "openai")
 os.environ.setdefault("EMBEDDING_MODEL", "text-embedding-3-small")
 
-# ---------- tiny version printer (optional) ----------
-def get_version(pkg, module=None):
-    try:
-        v = getattr(module, "__version__", None) if module else None
-        v = v or importlib.metadata.version(pkg)
-        print(f"{pkg} version: {v}")
-    except Exception:
-        pass
-
-get_version("streamlit", st)
-get_version("gpt_researcher")
-get_version("nest_asyncio", nest_asyncio)
-get_version("fpdf")
-
 # ---------- streamlit base ----------
 st.set_page_config(layout="wide")
 nest_asyncio.apply()
@@ -46,7 +32,6 @@ class PDF(FPDF):
     def header(self):
         self.set_font("Arial", "B", 12)
         self.cell(0, 10, "Research Report", 0, 1, "C")
-
     def footer(self):
         self.set_y(-15)
         self.set_font("Arial", "I", 8)
@@ -59,11 +44,10 @@ def create_pdf_bytes(report_text: str) -> bytes:
     pdf.set_font("Arial", size=12)
     for line in report_text.split("\n"):
         pdf.multi_cell(0, 10, line.encode("latin-1", "replace").decode("latin-1"))
-    # dest='S' returns str; encode for bytes
     return pdf.output(dest="S").encode("latin-1")
 
-# ---------- live research with streaming logs ----------
-async def run_research_streaming(query: str, report_type: str, sources: list, report_source: str, doc_dir: str, logs_box):
+# ---------- live research with streaming logs (single placeholder, no keys) ----------
+async def run_research_streaming(query: str, report_type: str, sources: list, report_source: str, doc_dir: str, logs_placeholder):
     buf = io.StringIO()
 
     # Build researcher
@@ -73,30 +57,21 @@ async def run_research_streaming(query: str, report_type: str, sources: list, re
     else:
         researcher = GPTResearcher(query=query, report_type=report_type, source_urls=sources)
 
-    # Run and stream logs every second while the task is pending
+    # Create an initial visible block for logs (single widget, then we just overwrite it)
+    logs_placeholder.code("Starting…")
+
     with redirect_stdout(buf), redirect_stderr(buf):
         task = asyncio.create_task(researcher.conduct_research())
 
         while not task.done():
             logs = buf.getvalue()
-            # update the single stable widget for logs
-            logs_box.text_area(
-                "Agent Logs (live)",
-                value=logs if logs else "Starting…",
-                height=240,
-                key="live_logs_box",
-            )
+            logs_placeholder.code(logs if logs else "Starting…")
             await asyncio.sleep(1)
 
-        # ensure any final prints are captured
+        # ensure final prints are shown
         await task
         final_logs = buf.getvalue()
-        logs_box.text_area(
-            "Agent Logs (live)",
-            value=final_logs,
-            height=240,
-            key="live_logs_box",
-        )
+        logs_placeholder.code(final_logs if final_logs else "Done.")
 
         # Now write the report
         report = await researcher.write_report()
@@ -106,16 +81,16 @@ async def run_research_streaming(query: str, report_type: str, sources: list, re
 # ---------- UI ----------
 st.title("GPT Researcher")
 st.markdown("""
-GPT Researcher is an autonomous agent designed for comprehensive online research tasks. It pulls information from the web or uploaded documents to create detailed, factual, research reports.
+GPT Researcher is an autonomous agent designed for comprehensive online research tasks. It pulls information from the web or uploaded documents to create detailed, factual research reports.
 """)
 
 with st.expander("Why Use GPT Researcher?", expanded=False):
     st.markdown("""
-- **Objective and Unbiased**: Delivers accurate, factual information.
-- **Time-Efficient**: Reduces manual research time.
-- **Up-to-Date**: Minimizes outdated info and hallucinations.
-- **Comprehensive**: Produces long, detailed reports (2,000+ words).
-- **Reduced Misinformation**: Considers multiple sources.
+- **Objective & Unbiased**  
+- **Time-Efficient**  
+- **Up-to-Date**  
+- **Comprehensive (2,000+ words)**  
+- **Reduced Misinformation**  
     """)
 
 st.markdown(
@@ -136,11 +111,11 @@ final_query = f"{user_query} Current Date is {datetime.now().strftime('%B %Y')}"
 st.sidebar.title("Research Settings")
 with st.sidebar.expander("How to Use", expanded=False):
     st.markdown("""
-1. **Select Research Type**: Web or Document Research.
-2. **Enter Research Query**.
-3. **Choose Report Type**.
-4. **Provide Sources or Upload Files**.
-5. **Run Research** — watch live logs and download the PDF.
+1. **Select Research Type** (Web/Document).  
+2. **Enter Research Query**.  
+3. **Choose Report Type**.  
+4. **Add URLs or Upload Files**.  
+5. **Run Research** — watch live logs, then download the PDF.
     """)
 
 research_type = st.sidebar.selectbox("Select research type:", ["Web Research", "Document Research"])
@@ -163,11 +138,9 @@ else:
 
 run_clicked = st.sidebar.button("Run Research")
 
-# live logs placeholder (single stable widget)
+# stable placeholders
 st.markdown("### Agent Logs")
 logs_placeholder = st.empty()
-
-# output placeholders
 report_placeholder = st.empty()
 download_placeholder = st.empty()
 
@@ -184,11 +157,11 @@ if run_clicked:
                     final_query, report_type, sources, src, UPLOAD_DIR, logs_placeholder
                 )
             )
-            # Save to session_state for persistence across reruns
+            # persist
             st.session_state.report = report
             st.session_state.logs = logs
 
-# Display results if we have them (e.g., after rerun)
+# Render results if available (e.g., after rerun)
 if "report" in st.session_state:
     report_placeholder.markdown("### Research Report")
     report_placeholder.markdown(st.session_state.report)
@@ -200,17 +173,11 @@ if "report" in st.session_state:
         data=pdf_bytes,
         file_name=f"report_{timestamp}.pdf",
         mime="application/pdf",
-        key="dl_pdf_btn",
     )
 
-# If logs exist from a previous run, keep them visible
+# Keep last logs visible after run / rerun
 if "logs" in st.session_state:
-    logs_placeholder.text_area(
-        "Agent Logs (live)",
-        value=st.session_state.logs,
-        height=240,
-        key="live_logs_box",
-    )
+    logs_placeholder.code(st.session_state.logs)
 
 # Hide Streamlit chrome
 st.markdown("""