Update app.py

app.py

@@ -1,18 +1,23 @@
 import streamlit as st
+
+# 1) Initialize DB tables before anything else
+from models.db import init_db
+init_db()
+
+# 2) Authentication (after DB is ready)
 from services.auth import authenticator, require_login
-from services.logger import logger
-from services.metrics import CHAT_COUNT, OPTIMIZE_COUNT
+
+# 3) Core services & repos
 from agent.gemini_agent import chat_with_gemini
 from clinical_nlp.umls_bioportal import lookup_umls, lookup_bioportal
 from quantum.bf_dcqo import optimize_hubo
-from services.pdf_report import generate_pdf
 from repositories.chat_repo import ChatRepo
 
-# Initialize DB
-from models.db import init_db
-init_db()
+# 4) Monitoring & logging
+from services.logger import logger
+from services.metrics import CHAT_COUNT, OPTIMIZE_COUNT
 
-# UI
+# === UI Setup ===
 username = require_login()
 st.set_page_config(page_title="Quantum Health AI", layout="wide")
 st.image("assets/logo.png", width=64)
@@ -21,30 +26,42 @@ st.title(f"Welcome, {username}!")
 tab1, tab2 = st.tabs(["🩺 Consult", "📊 Reports"])
 
 with tab1:
-    query = st.text_area("Enter clinical query or symptoms:")
+    query = st.text_area("Enter clinical query or symptoms:", height=100)
+
     if st.button("Ask Gemini"):
         CHAT_COUNT.inc()
         with st.spinner("Consulting AI..."):
             response = chat_with_gemini(username, query)
-        st.markdown(f"**AI**: {response}")
-        # save chat
-        ChatRepo().save(username, query, response)
-        # clinical NLP
-        with st.expander("UMLS Results"):
-            st.write(lookup_umls(query))
-        with st.expander("BioPortal Results"):
-            st.write(lookup_bioportal(query))
+            logger.info(f"User={username} Prompt={query}")
+        st.markdown(f"**AI:** {response}")
+        ChatRepo().save(user=username, prompt=query, response=response)
+
+        with st.expander("🔎 UMLS Lookup"):
+            umls_results = lookup_umls(query)
+            st.write(umls_results or "No UMLS concepts found.")
+
+        with st.expander("🔬 BioPortal Lookup"):
+            bio_results = lookup_bioportal(query)
+            st.write(bio_results or "No BioPortal concepts found.")
 
     if st.button("Quantum Optimize"):
         OPTIMIZE_COUNT.inc()
         with st.spinner("Running quantum optimizer..."):
-            result = optimize_hubo({"query":query})
-        st.json(result)
+            plan = optimize_hubo({"query": query})
+            logger.info(f"Quantum plan for {username}: {plan}")
+        st.markdown("### 🧬 Optimized Care Plan")
+        st.json(plan)
 
 with tab2:
-    if st.button("Generate PDF Report"):
-        # gather last 5 messages
-        pdf_data = {"Last Chats": ChatRepo().get_recent(username, limit=5)}
-        fname = generate_pdf(pdf_data)
-        st.success("Report Generated")
-        st.download_button("Download Report", data=open(fname,"rb"), file_name=fname)
+    st.header("Generate PDF Report")
+    if st.button("Download Last 5 Chats"):
+        # Fetch last 5 messages for this user
+        recent = ChatRepo().get_recent(user=username, limit=5)
+        report_data = {"Recent Chats": recent}
+        from services.pdf_report import generate_pdf
+        pdf_file = generate_pdf(report_data)
+        with open(pdf_file, "rb") as f:
+            st.download_button("Download Report", f, file_name=pdf_file)
+
+st.markdown("---")
+st.caption("Powered by Gemini LLM, UMLS, BioPortal & quantum-inspired optimization. For research use only.")