Update app.py

app.py

@@ -1,8 +1,9 @@
 #!/usr/bin/env python3
 # MedGenesis AI · CPU-only Streamlit app (OpenAI / Gemini)
 
-# ── Streamlit telemetry dir fix ───────────────────────────────────────
 import os, pathlib
+
+# ── Streamlit telemetry dir fix ───────────────────────────────────────
 os.environ["STREAMLIT_DATA_DIR"] = "/tmp/.streamlit"
 os.environ["XDG_STATE_HOME"] = "/tmp"
 os.environ["STREAMLIT_BROWSER_GATHERUSAGESTATS"] = "false"
@@ -14,7 +15,7 @@ from pathlib import Path
 import streamlit as st
 import pandas as pd
 import plotly.express as px
-from fpdf import FPDF          # classic FPDF → Latin-1 only
+from fpdf import FPDF
 from streamlit_agraph import agraph
 
 # ── Internal helpers ────────────────────────────────────────────────
@@ -29,7 +30,6 @@ LOGO = ROOT / "assets" / "logo.png"
 
 # ── PDF export helper (UTF-8 → Latin-1 “safe”) ──────────────────────
 def _latin1_safe(txt: str) -> str:
-    """Return text that FPDF(latin-1) can embed; replace unknown chars."""
     return txt.encode("latin-1", "replace").decode("latin-1")
 
 def _pdf(papers):
@@ -71,7 +71,6 @@ def render_ui():
     st.set_page_config("MedGenesis AI", layout="wide")
     _workspace_sidebar()
 
-    # Header
     c1, c2 = st.columns([0.15, 0.85])
     with c1:
         if LOGO.exists():
@@ -81,8 +80,7 @@ def render_ui():
         st.caption("Multi-source biomedical assistant · OpenAI / Gemini")
 
     llm   = st.radio("LLM engine", ["openai", "gemini"], horizontal=True)
-    query = st.text_input("Enter biomedical question",
-                          placeholder="e.g. CRISPR glioblastoma therapy")
+    query = st.text_input("Enter biomedical question", placeholder="e.g. CRISPR glioblastoma therapy")
 
     # Alert check
     if get_workspace():
@@ -102,10 +100,8 @@ def render_ui():
             res = asyncio.run(orchestrate_search(query, llm=llm))
         st.success(f"Completed with **{res['llm_used'].title()}**")
 
-        tabs = st.tabs(["Results", "Genes", "Trials", "Graph",
-                        "Metrics", "Visuals"])
+        tabs = st.tabs(["Results", "Genes", "Trials", "Graph", "Metrics", "Visuals"])
 
-        # Results
         with tabs[0]:
             for i, p in enumerate(res["papers"], 1):
                 st.markdown(f"**{i}. [{p['title']}]({p['link']})**  *{p['authors']}*")
@@ -113,12 +109,9 @@ def render_ui():
 
             col1, col2 = st.columns(2)
             with col1:
-                st.download_button("CSV",
-                                   pd.DataFrame(res["papers"]).to_csv(index=False),
-                                   "papers.csv", "text/csv")
+                st.download_button("CSV", pd.DataFrame(res["papers"]).to_csv(index=False), "papers.csv", "text/csv")
             with col2:
-                st.download_button("PDF", _pdf(res["papers"]),
-                                   "papers.pdf", "application/pdf")
+                st.download_button("PDF", _pdf(res["papers"]), "papers.pdf", "application/pdf")
 
             if st.button("💾 Save"):
                 save_query(query, res)
@@ -136,12 +129,10 @@ def render_ui():
             st.subheader("AI summary")
             st.info(res["ai_summary"])
 
-        # Genes
         with tabs[1]:
             st.header("Gene / Variant signals")
             for g in res["genes"]:
-                st.write(f"- **{g.get('name', g.get('geneid'))}** "
-                         f"{g.get('description', '')}")
+                st.write(f"- **{g.get('name', g.get('geneid'))}** {g.get('description', '')}")
             if res["gene_disease"]:
                 st.markdown("### DisGeNET links")
                 st.json(res["gene_disease"][:15])
@@ -151,21 +142,16 @@ def render_ui():
                     if d:
                         st.write("-", d)
 
-        # Trials
         with tabs[2]:
             st.header("Clinical trials")
             if not res["clinical_trials"]:
                 st.info("No trials (rate-limited or none found).")
             for t in res["clinical_trials"]:
                 st.markdown(f"**{t['NCTId'][0]}** – {t['BriefTitle'][0]}")
-                st.write(f"Phase {t.get('Phase', [''])[0]} "
-                         f"| Status {t['OverallStatus'][0]}")
+                st.write(f"Phase {t.get('Phase',[''])[0]} | Status {t['OverallStatus'][0]}")
 
-        # Graph
         with tabs[3]:
-            nodes, edges, cfg = build_agraph(res["papers"],
-                                             res["umls"],
-                                             res["drug_safety"])
+            nodes, edges, cfg = build_agraph(res["papers"], res["umls"], res["drug_safety"])
             hl = st.text_input("Highlight node:", key="hl")
             if hl:
                 pat = re.compile(re.escape(hl), re.I)
@@ -173,31 +159,29 @@ def render_ui():
                     n.color = "#f1c40f" if pat.search(n.label) else "#d3d3d3"
             agraph(nodes, edges, cfg)
 
-        # Metrics
         with tabs[4]:
-            G = build_nx([n.__dict__ for n in nodes],
-                         [e.__dict__ for e in edges])
+            G = build_nx([n.__dict__ for n in nodes], [e.__dict__ for e in edges])
             st.metric("Density", f"{get_density(G):.3f}")
             st.markdown("**Top hubs**")
             for nid, sc in get_top_hubs(G):
                 lab = next((n.label for n in nodes if n.id == nid), nid)
                 st.write(f"- {lab}  {sc:.3f}")
 
-        # Visuals
         with tabs[5]:
             years = [p["published"] for p in res["papers"] if p.get("published")]
             if years:
-                st.plotly_chart(px.histogram(years, nbins=12,
-                                             title="Publication Year"))
+                st.plotly_chart(px.histogram(years, nbins=12, title="Publication Year"))
 
-        # Follow-up Q-A
+        # ── Follow-up Q-A (fixed) ───────────────────────────────────────
         st.markdown("---")
-        follow = st.text_input("Ask follow-up:")
+        follow = st.text_input("Ask follow-up question:", key="followup_input")  # ✅ UPDATED
         if st.button("Ask AI"):
-            ans = asyncio.run(answer_ai_question(follow,
-                                                 context=query,
-                                                 llm=llm))
-            st.write(ans["answer"])
+            if follow.strip():  # ✅ UPDATED
+                with st.spinner("Generating AI response..."):
+                    ans = asyncio.run(answer_ai_question(follow, context=query, llm=llm))
+                st.write(ans["answer"])
+            else:
+                st.warning("Please type a follow-up question before submitting.")  # ✅ UPDATED
 
     else:
         st.info("Enter a question and press **Run Search 🚀**")