Update app.py

app.py

@@ -1,74 +1,80 @@
 import streamlit as st
 
-# 1) Ensure DB tables exist
+# ──────────────────────────────────────────────────────────────────────────────
+# 1) Initialize DB (imports models under the hood, then create_all)
 from models.db import init_db
 init_db()
 
-# ————— First-Run Signup Flow —————
+# ──────────────────────────────────────────────────────────────────────────────
+# 2) First-run admin signup (before any queries to the user table)
 from repositories.user_repo import UserRepo
 from config.settings import settings
 
 repo = UserRepo(settings.database_url)
 if not repo.get_all_users():
     st.title("🚀 Welcome to Quantum Healthcare AI")
-    st.warning("No users exist yet. Please create the first admin account:")
+    st.warning("No users exist yet. Create the first admin account below:")
     new_user = st.text_input("Username")
     new_name = st.text_input("Full name")
     new_pw   = st.text_input("Password", type="password")
     if st.button("Create Admin User"):
         if new_user and new_name and new_pw:
             repo.add_user(new_user, new_name, new_pw)
-            st.success(f"Admin `{new_user}` created! Please refresh to log in.")
+            st.success(f"✅ Admin `{new_user}` created! Refresh the page to log in.")
         else:
             st.error("All fields are required.")
-    # Stop here until admin is created
     st.stop()
-# ————————————————————————————————
 
-# 2) Authentication (after at least one user exists)
+# ──────────────────────────────────────────────────────────────────────────────
+# 3) Authentication
 from services.auth import authenticator, require_login
 username = require_login()
 
-# 3) Core AI + Clinical NLP + Quantum
+# ──────────────────────────────────────────────────────────────────────────────
+# 4) Core services & repositories
 from agent.gemini_agent import chat_with_gemini
 from clinical_nlp.umls_bioportal import lookup_umls, lookup_bioportal
 from quantum.optimizer import optimize_treatment
 from repositories.chat_repo import ChatRepo
 
-# 4) Monitoring & Logging
+# ──────────────────────────────────────────────────────────────────────────────
+# 5) Logging & metrics
 from services.logger import logger
 from services.metrics import CHAT_COUNT, OPTIMIZE_COUNT
 
-# === UI Setup ===
-st.set_page_config(page_title="Quantum Health AI", layout="wide")
+# ──────────────────────────────────────────────────────────────────────────────
+# 6) UI Layout
+st.set_page_config(page_title="Quantum Healthcare AI", layout="wide")
 st.image("assets/logo.png", width=64)
-st.title(f"Welcome, {username}!")
+st.title(f"Hello, {username}!")
 
 tab1, tab2 = st.tabs(["🩺 Consult", "📊 Reports"])
 
 with tab1:
-    query = st.text_area("Describe symptoms or ask a medical question:", height=100)
+    query = st.text_area("Describe your symptoms or ask a clinical question:", height=100)
 
     if st.button("Ask Gemini"):
         CHAT_COUNT.inc()
-        with st.spinner("Consulting AI..."):
+        with st.spinner("🤖 Consulting Gemini..."):
             response = chat_with_gemini(username, query)
-            logger.info(f"[Chat] user={username} prompt={query}")
+            logger.info(f"[Chat] user={username} prompt={query!r}")
         st.markdown(f"**AI Response:** {response}")
         ChatRepo().save(user=username, prompt=query, response=response)
 
         with st.expander("🔎 UMLS Concept Lookup"):
-            st.write(lookup_umls(query) or "No UMLS concepts found.")
+            umls_results = lookup_umls(query)
+            st.write(umls_results or "No concepts found in UMLS.")
 
         with st.expander("🔬 BioPortal Concept Lookup"):
-            st.write(lookup_bioportal(query) or "No BioPortal matches found.")
+            bio_results = lookup_bioportal(query)
+            st.write(bio_results or "No matches found in BioPortal.")
 
-    if st.button("Quantum Optimize Care Plan"):
+    if st.button("🧬 Quantum Optimize Care Plan"):
         OPTIMIZE_COUNT.inc()
-        with st.spinner("Running quantum-inspired optimizer..."):
+        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.markdown("### Optimized Treatment Plan")
         st.json(plan)
 
 with tab2:
@@ -80,5 +86,6 @@ with tab2:
         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")