Update app.py

app.py

@@ -1,23 +1,23 @@
 import streamlit as st
 
-# 1) Initialize DB tables before anything else
+# 1) Ensure DB tables exist
 from models.db import init_db
 init_db()
 
-# 2) Authentication (after DB is ready)
+# 2) Auth
 from services.auth import authenticator, require_login
 
-# 3) Core services & repos
+# 3) Core AI + Clinical NLP + Quantum
 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 quantum.optimizer import optimize_treatment
 from repositories.chat_repo import ChatRepo
 
-# 4) Monitoring & logging
+# 4) Monitoring & Logging
 from services.logger import logger
 from services.metrics import CHAT_COUNT, OPTIMIZE_COUNT
 
-# === UI Setup ===
+# ——— UI ———
 username = require_login()
 st.set_page_config(page_title="Quantum Health AI", layout="wide")
 st.image("assets/logo.png", width=64)
@@ -26,42 +26,40 @@ st.title(f"Welcome, {username}!")
 tab1, tab2 = st.tabs(["🩺 Consult", "📊 Reports"])
 
 with tab1:
-    query = st.text_area("Enter clinical query or symptoms:", height=100)
+    query = st.text_area("Describe symptoms or enter a medical question:", height=100)
 
     if st.button("Ask Gemini"):
         CHAT_COUNT.inc()
         with st.spinner("Consulting AI..."):
             response = chat_with_gemini(username, query)
-            logger.info(f"User={username} Prompt={query}")
-        st.markdown(f"**AI:** {response}")
+            logger.info(f"[Chat] user={username} prompt={query}")
+        st.markdown(f"**AI Response:** {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("🔎 UMLS Concept Lookup"):
+            umls_res = lookup_umls(query)
+            st.write(umls_res or "No UMLS concepts found.")
 
-        with st.expander("🔬 BioPortal Lookup"):
-            bio_results = lookup_bioportal(query)
-            st.write(bio_results or "No BioPortal concepts found.")
+        with st.expander("🔬 BioPortal Concept Lookup"):
+            bio_res = lookup_bioportal(query)
+            st.write(bio_res or "No BioPortal matches found.")
 
-    if st.button("Quantum Optimize"):
+    if st.button("Quantum Optimize Care Plan"):
         OPTIMIZE_COUNT.inc()
-        with st.spinner("Running quantum optimizer..."):
-            plan = optimize_hubo({"query": query})
-            logger.info(f"Quantum plan for {username}: {plan}")
-        st.markdown("### 🧬 Optimized Care Plan")
+        with st.spinner("Running quantum-inspired optimizer..."):
+            plan = optimize_treatment(query)
+            logger.info(f"[Optimize] user={username} plan={plan}")
+        st.markdown("### 🧬 Optimized Treatment Plan")
         st.json(plan)
 
 with tab2:
-    st.header("Generate PDF Report")
+    st.header("Generate PDF Report of Recent Chats")
     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)
+        pdf_path = generate_pdf({"Recent Chats": recent})
+        with open(pdf_path, "rb") as f:
+            st.download_button("Download PDF", f, file_name=pdf_path)
 
 st.markdown("---")
-st.caption("Powered by Gemini LLM, UMLS, BioPortal & quantum-inspired optimization. For research use only.")
+st.caption("Powered by Gemini LLM • UMLS/BioPortal • Quantum-inspired optimization")