Update app.py
Browse files
app.py
CHANGED
@@ -30,7 +30,7 @@ from mcp.alerts import check_alerts
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# Streamlit telemetry directory β /tmp
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os.environ.update({
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"STREAMLIT_DATA_DIR": "/tmp/.streamlit",
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"XDG_STATE_HOME"
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"STREAMLIT_BROWSER_GATHERUSAGESTATS": "false",
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})
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pathlib.Path("/tmp/.streamlit").mkdir(parents=True, exist_ok=True)
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@@ -55,7 +55,6 @@ def _pdf(papers: list[dict]) -> bytes:
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pdf.set_font("Helvetica", "B", 11)
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pdf.multi_cell(0, 7, _latin1_safe(f"{i}. {p.get('title','')}"))
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pdf.set_font("Helvetica", "", 9)
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# fixed string literal with explicit newlines
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body = (
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f"{p.get('authors','')}\n"
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f"{p.get('summary','')}\n"
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@@ -105,7 +104,7 @@ def render_ui():
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# Controls
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engine = st.radio("LLM engine", ["openai", "gemini"], horizontal=True)
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query
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# Alerts
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if get_workspace():
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@@ -140,7 +139,7 @@ def render_ui():
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# Tabs
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tabs = st.tabs(["Results", "Genes", "Trials", "Variants", "Graph", "Metrics", "Visuals"])
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# --- Results tab
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with tabs[0]:
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st.subheader("Literature")
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for i, p in enumerate(res['papers'], 1):
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@@ -167,7 +166,7 @@ def render_ui():
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st.subheader("AI summary")
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st.info(res['ai_summary'])
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# --- Genes tab
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with tabs[1]:
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st.header("Gene / Variant signals")
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valid_genes = [g for g in res['genes'] if isinstance(g, dict)]
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@@ -189,9 +188,11 @@ def render_ui():
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st.markdown("### DisGeNET links")
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st.json(gene_disease[:15])
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# --- Trials tab
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with tabs[2]:
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st.header("Clinical trials")
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trials = res['clinical_trials']
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if not trials:
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st.info("No trials returned (rate-limited or none found).")
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@@ -202,21 +203,23 @@ def render_ui():
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f"Phase {t.get('phase','?')} | Status {t.get('status','?')}"
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)
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# --- Variants tab
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with tabs[3]:
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st.header("Cancer variants (cBioPortal)")
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variants = res['variants']
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if not variants:
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st.info("No variants for this gene/profile.")
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else:
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st.json(variants[:30])
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# --- Graph tab
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with tabs[4]:
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nodes, edges, cfg = build_agraph(res['papers'], res['umls'], res['drug_safety'])
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agraph(nodes, edges, cfg)
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# --- Metrics tab
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with tabs[5]:
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G = build_nx([n.__dict__ for n in nodes], [e.__dict__ for e in edges])
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st.metric("Density", f"{get_density(G):.3f}")
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@@ -225,13 +228,13 @@ def render_ui():
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lab = next((n.label for n in nodes if n.id == nid), nid)
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st.write(f"- {lab} {sc:.3f}")
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# --- Visuals tab
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with tabs[6]:
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years = [p.get('published') for p in res['papers'] if p.get('published')]
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if years:
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st.plotly_chart(px.histogram(years, nbins=12, title="Publication Year"))
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# Follow-up QA (outside
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st.markdown("---")
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input_col, button_col = st.columns([4, 1])
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with input_col:
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# Streamlit telemetry directory β /tmp
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os.environ.update({
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"STREAMLIT_DATA_DIR": "/tmp/.streamlit",
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"XDG_STATE_HOME": "/tmp",
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"STREAMLIT_BROWSER_GATHERUSAGESTATS": "false",
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})
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pathlib.Path("/tmp/.streamlit").mkdir(parents=True, exist_ok=True)
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pdf.set_font("Helvetica", "B", 11)
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pdf.multi_cell(0, 7, _latin1_safe(f"{i}. {p.get('title','')}"))
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pdf.set_font("Helvetica", "", 9)
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body = (
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f"{p.get('authors','')}\n"
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f"{p.get('summary','')}\n"
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# Controls
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engine = st.radio("LLM engine", ["openai", "gemini"], horizontal=True)
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query = st.text_input("Enter biomedical question", placeholder="e.g. CRISPR glioblastoma therapy")
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# Alerts
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if get_workspace():
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# Tabs
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tabs = st.tabs(["Results", "Genes", "Trials", "Variants", "Graph", "Metrics", "Visuals"])
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# --- Results tab ---
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with tabs[0]:
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st.subheader("Literature")
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for i, p in enumerate(res['papers'], 1):
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st.subheader("AI summary")
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st.info(res['ai_summary'])
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# --- Genes tab ---
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with tabs[1]:
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st.header("Gene / Variant signals")
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valid_genes = [g for g in res['genes'] if isinstance(g, dict)]
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st.markdown("### DisGeNET links")
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st.json(gene_disease[:15])
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# --- Trials tab ---
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with tabs[2]:
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st.header("Clinical trials")
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# Debug: show raw response
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st.write("π Raw trials response:", res['clinical_trials'])
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trials = res['clinical_trials']
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if not trials:
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st.info("No trials returned (rate-limited or none found).")
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f"Phase {t.get('phase','?')} | Status {t.get('status','?')}"
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)
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# --- Variants tab ---
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with tabs[3]:
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st.header("Cancer variants (cBioPortal)")
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# Debug: show raw response
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st.write("π Raw variants response:", res['variants'])
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variants = res['variants']
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if not variants:
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st.info("No variants for this gene/profile.")
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else:
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st.json(variants[:30])
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# --- Graph tab ---
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with tabs[4]:
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nodes, edges, cfg = build_agraph(res['papers'], res['umls'], res['drug_safety'])
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agraph(nodes, edges, cfg)
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# --- Metrics tab ---
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with tabs[5]:
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G = build_nx([n.__dict__ for n in nodes], [e.__dict__ for e in edges])
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st.metric("Density", f"{get_density(G):.3f}")
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lab = next((n.label for n in nodes if n.id == nid), nid)
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st.write(f"- {lab} {sc:.3f}")
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# --- Visuals tab ---
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with tabs[6]:
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years = [p.get('published') for p in res['papers'] if p.get('published')]
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if years:
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st.plotly_chart(px.histogram(years, nbins=12, title="Publication Year"))
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# Follow-up QA (outside tabs)
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st.markdown("---")
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input_col, button_col = st.columns([4, 1])
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with input_col:
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