Update app.py
Browse files
app.py
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@@ -7,11 +7,13 @@ from fastapi.middleware.cors import CORSMiddleware
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from mcp.orchestrator import orchestrate_search, answer_ai_question
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from mcp.schemas import UnifiedSearchInput, UnifiedSearchResult
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from mcp.workspace import get_workspace, save_query
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from pathlib import Path
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import pandas as pd
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from fpdf import FPDF
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import asyncio
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import plotly.express as px
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ROOT_DIR = Path(__file__).resolve().parent
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LOGO_PATH = ROOT_DIR / "assets" / "logo.png"
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@@ -121,6 +123,13 @@ def render_ui():
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fig = px.histogram(pub_years, nbins=10, title="Publication Year Distribution")
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st.plotly_chart(fig)
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# Export as CSV
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if results["papers"]:
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df = pd.DataFrame(results["papers"])
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from mcp.orchestrator import orchestrate_search, answer_ai_question
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from mcp.schemas import UnifiedSearchInput, UnifiedSearchResult
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from mcp.workspace import get_workspace, save_query
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from mcp.knowledge_graph import build_knowledge_graph
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from pathlib import Path
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import pandas as pd
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from fpdf import FPDF
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import asyncio
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import plotly.express as px
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import streamlit.components.v1 as components
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ROOT_DIR = Path(__file__).resolve().parent
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LOGO_PATH = ROOT_DIR / "assets" / "logo.png"
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fig = px.histogram(pub_years, nbins=10, title="Publication Year Distribution")
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st.plotly_chart(fig)
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# --- INTERACTIVE KNOWLEDGE GRAPH ---
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st.markdown("### 🗺️ Knowledge Graph Explorer")
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kg_html_path = build_knowledge_graph(results["papers"], results["umls"], results["drug_safety"])
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with open(kg_html_path, 'r', encoding='utf-8') as f:
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kg_html = f.read()
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components.html(kg_html, height=600)
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# Export as CSV
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if results["papers"]:
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df = pd.DataFrame(results["papers"])
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