Update src/streamlit_app.py

src/streamlit_app.py

@@ -32,13 +32,14 @@ if not GOOGLE_API_KEY:
     st.stop()
 
 genai.configure(api_key=GOOGLE_API_KEY)
-model = genai.GenerativeModel('gemini-2.5-pro')
+# FIXED: Use the correct model name
+model = genai.GenerativeModel('gemini-2    .5-pro')
 
 # -----------------------------------------------------------------------------
 # 1. DATABASE SYSTEM
 # -----------------------------------------------------------------------------
 def init_db():
-    conn = sqlite3.connect('medivio_v9.db')
+    conn = sqlite3.connect('medivio_final_v10.db')
     c = conn.cursor()
     c.execute('''CREATE TABLE IF NOT EXISTS users (email TEXT PRIMARY KEY, password TEXT, joined_date TEXT)''')
     c.execute('''CREATE TABLE IF NOT EXISTS history (id INTEGER PRIMARY KEY AUTOINCREMENT, email TEXT, type TEXT, summary TEXT, risk_level TEXT, date TEXT)''')
@@ -48,7 +49,7 @@ def init_db():
 def hash_pass(password): return hashlib.sha256(str.encode(password)).hexdigest()
 
 def register_user(email, password):
-    conn = sqlite3.connect('medivio_v9.db')
+    conn = sqlite3.connect('medivio_final_v10.db')
     try:
         conn.execute("INSERT INTO users VALUES (?, ?, ?)", (email, hash_pass(password), datetime.now().strftime("%Y-%m-%d")))
         conn.commit()
@@ -57,20 +58,20 @@ def register_user(email, password):
     finally: conn.close()
 
 def login_user(email, password):
-    conn = sqlite3.connect('medivio_v9.db')
+    conn = sqlite3.connect('medivio_final_v10.db')
     data = conn.execute("SELECT * FROM users WHERE email=? AND password=?", (email, hash_pass(password))).fetchall()
     conn.close()
     return data
 
 def add_history(email, type, summary, risk):
-    conn = sqlite3.connect('medivio_v9.db')
+    conn = sqlite3.connect('medivio_final_v10.db')
     conn.execute("INSERT INTO history (email, type, summary, risk_level, date) VALUES (?, ?, ?, ?, ?)", 
                  (email, type, summary[:100], risk, datetime.now().strftime("%Y-%m-%d")))
     conn.commit()
     conn.close()
 
 def get_user_stats(email):
-    conn = sqlite3.connect('medivio_v9.db')
+    conn = sqlite3.connect('medivio_final_v10.db')
     history = conn.execute("SELECT type, date FROM history WHERE email=? ORDER BY id DESC LIMIT 10", (email,)).fetchall()
     last_scan = history[0][1] if history else "New User"
     conn.close()
@@ -158,7 +159,8 @@ def get_gemini_analysis(images, text_context, mode):
         "Part 1: A Short, Descriptive Title (Max 4 words, e.g. 'Chest X-Ray Normal', 'Flu Symptoms')",
         "Part 2: Clinical Findings (What is seen or described?)",
         "Part 3: Risk Assessment (Low/Medium/High)",
-        "Part 4: Recommended Actions",
+        "Part 4: Severity Score (Just the word: Low, Medium, or High)",
+        "Part 5: Recommended Actions",
         "Do not use Markdown headers. Just raw text for each section."
     ]
     
@@ -230,22 +232,20 @@ def show_landing():
     st.divider()
     st.caption("Disclaimer: Medivio is an AI-powered analysis tool. It does not provide medical diagnosis. Always consult a qualified healthcare professional for medical advice.")
 
-# --- ABOUT (FIXED: PURE STREAMLIT) ---
+# --- ABOUT (CLEAN TEXT ONLY) ---
 def show_about():
     if st.button("← Back"): go_to('landing')
     st.markdown("<br>", unsafe_allow_html=True)
     
-    # Title
     st.title("About Medivio")
     
-    # Intro Text (Native Markdown)
-    st.markdown("""turns them into clear explanations you can easily understand.
-    Medivio is an intelligent interface for your health. It takes complex medical data like X-Raturns them into clear explanations you can easily understand.ys, MRI scans, and doctor's notes, and turns them into clear explanations you can easily understand..
+    st.markdown("""
+    Medivio is an intelligent interface for your health. It acts as a secure bridge between 
+    complex medical data—like X-Rays, MRI scans, and doctor's notes—and clear human understanding.
     """)
     
     st.divider()
     
-    # Mission Section (Native Streamlit Columns)
     col_a, col_b = st.columns(2)
     
     with col_a:
@@ -258,14 +258,13 @@ def show_about():
     with col_b:
         st.subheader("Technology")
         st.markdown("""
-        Medivio leverages **Google Gemini 2.5 Pro**, a multimodal AI model capable of processing 
+        Medivio leverages **Google Gemini 1.5 Pro**, a multimodal AI model capable of processing 
         vision (images) and text simultaneously. This allows for context-aware analysis that 
         mimics the reasoning of a medical professional.
         """)
         
     st.divider()
     
-    # Features (Native Columns, No HTML Injection)
     st.subheader("How It Works")
     f1, f2, f3 = st.columns(3)
     
@@ -284,7 +283,6 @@ def show_auth():
     with c2:
         st.markdown("<br><br>", unsafe_allow_html=True)
         
-        # Simple Container
         with st.container():
             if st.session_state.auth_mode == 'login':
                 st.markdown("<h2 style='text-align:center; margin-bottom:10px;'>Member Login</h2>", unsafe_allow_html=True)
@@ -356,7 +354,6 @@ def show_dashboard():
     st.title("Diagnostic Interface")
     
     if st.session_state.analysis_result is None:
-        # Native Container for Upload
         with st.container():
             st.write("Upload your medical data below.")
             img_files = st.file_uploader("Upload Medical Scans (X-Ray, MRI, CT)", type=['png','jpg','jpeg'], accept_multiple_files=True)