Update src/streamlit_app.py

src/streamlit_app.py

@@ -6,19 +6,23 @@ from PIL import Image
 from huggingface_hub import InferenceClient
 
 # -----------------------------------------------------------------------------
-# 1. SETUP & SECRETS
+# 0. AUTO-FIX FOR UPLOAD ERROR (RUNS FIRST)
 # -----------------------------------------------------------------------------
-st.set_page_config(page_title="SHINUI | Intelligent Care", page_icon="✨", layout="wide")
-
-# AUTO-FIX FOR 403 ERROR
 config_dir = ".streamlit"
 if not os.path.exists(config_dir):
     os.makedirs(config_dir)
 with open(os.path.join(config_dir, "config.toml"), "w") as f:
     f.write("[server]\nenableXsrfProtection=false\nenableCORS=false\nmaxUploadSize=200\n")
 
+# -----------------------------------------------------------------------------
+# 1. SETUP & CONFIGURATION
+# -----------------------------------------------------------------------------
+st.set_page_config(page_title="SHINUI | Intelligent Care", page_icon="✨", layout="wide")
+
 # RETRIEVE API KEY
+# Make sure "HF_TOKEN" is in your Space Settings -> Secrets
 HF_TOKEN = os.environ.get("HF_TOKEN")
+
 if not HF_TOKEN:
     st.error("⚠️ API Key missing! Please add 'HF_TOKEN' in Space Settings > Secrets.")
     st.stop()
@@ -27,174 +31,228 @@ if not HF_TOKEN:
 client = InferenceClient(token=HF_TOKEN)
 
 # -----------------------------------------------------------------------------
-# 2. THE "UNGATED" BRAIN LOGIC
+# 2. STATE MANAGEMENT (LOGIN & HISTORY)
+# -----------------------------------------------------------------------------
+if 'page' not in st.session_state: st.session_state.page = 'landing'
+if 'logged_in' not in st.session_state: st.session_state.logged_in = False
+if 'user_email' not in st.session_state: st.session_state.user_email = ""
+if 'history' not in st.session_state: st.session_state.history = []
+if 'result' not in st.session_state: st.session_state.result = None
+
+# -----------------------------------------------------------------------------
+# 3. THE BRAIN (Llama 3.2 Logic)
 # -----------------------------------------------------------------------------
 def get_ai_insight(input_type, content):
     """
-    Uses Open-Source, Non-Gated models to avoid permission errors.
+    Handles AI processing using Llama 3.2 Vision Instruct.
     """
-    # The "Brain" prompt that interprets the data
-    system_prompt = (
-        "You are SHINUI, an advanced medical AI. "
-        "Your goal is to analyze the user's input and provide clear, safe, and professional medical insights. "
-        "Structure your answer with: 'Analysis', 'Risk Level', and 'Recommended Action'. "
-        "Keep it concise and helpful."
-    )
+    prompt_base = "You are SHINUI, a professional medical AI assistant. Analyze the following input and provide a concise risk assessment and next steps."
 
     try:
-        final_text_input = ""
-
-        # A. VISION (Uses BLIP - Ungated)
+        # A. VISION (Llama 3.2 Vision)
         if input_type == "Image":
-            # 1. We use BLIP to "see" the image and describe it to text
-            # This model is open and requires no permissions.
-            image_description = client.image_to_text(
-                model="Salesforce/blip-image-captioning-large",
-                image=content
+            messages = [
+                {
+                    "role": "user", 
+                    "content": [
+                        {"type": "image"},
+                        {"type": "text", "text": prompt_base}
+                    ]
+                }
+            ]
+            # Pass image directly to the client
+            response = client.chat_completion(
+                model="meta-llama/Llama-3.2-11B-Vision-Instruct",
+                messages=messages,
+                max_tokens=500,
+                image=content # The PIL Image object
             )
-            # 2. We send that description to the LLM to "medicalize" it
-            final_text_input = f"I have an image that shows: '{image_description}'. Please analyze this medically."
+            return response.choices[0].message.content
 
-        # B. AUDIO (Uses Whisper - Ungated)
+        # B. AUDIO (Whisper -> Llama)
         elif input_type == "Audio":
-            # 1. Transcribe audio to text
+            # 1. Transcribe
             transcription = client.automatic_speech_recognition(
                 model="openai/whisper-large-v3-turbo",
                 audio=content
             ).text
-            final_text_input = f"The patient described their symptoms verbally: '{transcription}'. Analyze this."
+            
+            # 2. Analyze Text
+            messages = [{"role": "user", "content": f"{prompt_base} Patient speech: '{transcription}'"}]
+            analysis = client.chat_completion(
+                model="meta-llama/Llama-3.2-11B-Vision-Instruct",
+                messages=messages,
+                max_tokens=500
+            )
+            return f"**Transcript:** '{transcription}'\n\n**Analysis:** {analysis.choices[0].message.content}"
 
-        # C. TEXT (Direct)
+        # C. TEXT (Llama)
         elif input_type == "Text":
-            final_text_input = f"Patient notes: '{content}'. Analyze this."
-
-        # D. FINAL REASONING (Uses Zephyr - Ungated & Smart)
-        # Zephyr-7b-beta is free, open, and very good at following instructions.
-        messages = [
-            {"role": "system", "content": system_prompt},
-            {"role": "user", "content": final_text_input}
-        ]
-        
-        response = client.chat_completion(
-            model="HuggingFaceH4/zephyr-7b-beta",
-            messages=messages,
-            max_tokens=400
-        )
-        
-        return response.choices[0].message.content
+            messages = [{"role": "user", "content": f"{prompt_base} Patient notes: '{content}'"}]
+            response = client.chat_completion(
+                model="meta-llama/Llama-3.2-11B-Vision-Instruct",
+                messages=messages,
+                max_tokens=500
+            )
+            return response.choices[0].message.content
 
     except Exception as e:
         return f"⚠️ Analysis Error: {str(e)}"
 
 # -----------------------------------------------------------------------------
-# 3. VISUAL STYLING (TIVE.COM STYLE)
+# 4. UI STYLING (DARK THEME)
 # -----------------------------------------------------------------------------
-if 'history' not in st.session_state: st.session_state.history = []
-if 'result' not in st.session_state: st.session_state.result = None
-
 st.markdown("""
 <style>
     @import url('https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@300;400;600;800&display=swap');
-    
     .stApp {
         background-color: #020617;
         background-image: radial-gradient(circle at 50% 0%, #1e293b 0%, #020617 70%);
         font-family: 'Plus Jakarta Sans', sans-serif;
         color: #f8fafc;
     }
-    
-    /* Card Styling */
     .shinui-card {
-        background: rgba(30, 41, 59, 0.4);
-        border: 1px solid rgba(148, 163, 184, 0.1);
-        border-radius: 16px;
-        padding: 25px;
-        backdrop-filter: blur(12px);
-        margin-bottom: 20px;
+        background: rgba(30, 41, 59, 0.4); border: 1px solid rgba(148, 163, 184, 0.1);
+        border-radius: 16px; padding: 25px; backdrop-filter: blur(12px); margin-bottom: 20px;
     }
-    
-    /* Buttons */
     div.stButton > button {
-        background: #38bdf8;
-        color: #0f172a;
-        border: none;
-        font-weight: 700;
-        padding: 12px 20px;
-        border-radius: 8px;
-        width: 100%;
-        transition: all 0.3s;
-    }
-    div.stButton > button:hover {
-        background: #ffffff;
-        box-shadow: 0 0 20px rgba(56, 189, 248, 0.5);
+        background: #38bdf8; color: #0f172a; border: none; font-weight: 700;
+        padding: 12px 20px; border-radius: 8px; width: 100%; transition: all 0.3s;
     }
-
-    /* Headers */
-    h1, h2, h3 { color: white; font-weight: 700; }
-    
+    div.stButton > button:hover { background: #ffffff; box-shadow: 0 0 20px rgba(56, 189, 248, 0.5); }
     #MainMenu, footer, header {visibility: hidden;}
 </style>
 """, unsafe_allow_html=True)
 
 # -----------------------------------------------------------------------------
-# 4. APP UI
-# -----------------------------------------------------------------------------
-c1, c2 = st.columns([1, 8])
-with c1: st.markdown("### ✨ SHINUI")
-st.markdown("<hr style='border-color:rgba(255,255,255,0.1)'>", unsafe_allow_html=True)
-
-# Tabs
-t1, t2, t3 = st.tabs(["📷 Vision", "🎙️ Voice", "📝 Text"])
-
-# Tab 1: Vision
-with t1:
-    st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
-    img_file = st.file_uploader("Upload Scan / Image", type=['png','jpg','jpeg'])
-    if img_file and st.button("Analyze Visual", key="btn_img"):
-        image = Image.open(img_file)
-        with st.spinner("Processing Visual Data..."):
-            res = get_ai_insight("Image", image)
-            st.session_state.result = res
-            st.session_state.history.append(res)
-    st.markdown("</div>", unsafe_allow_html=True)
-
-# Tab 2: Voice
-with t2:
-    st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
-    # Uses new Streamlit Audio Input (Record directly in browser)
-    audio_input = st.audio_input("Record Symptoms")
-    if audio_input:
-        if st.button("Analyze Recording", key="btn_audio"):
-            with st.spinner("Transcribing & Analyzing..."):
-                # Read audio bytes
-                res = get_ai_insight("Audio", audio_input.read())
+# 5. HELPER FUNCTIONS
+# -----------------------------------------------------------------------------
+def nav_to(page):
+    st.session_state.page = page
+    st.rerun()
+
+def sign_out():
+    st.session_state.logged_in = False
+    st.session_state.history = []
+    st.session_state.result = None
+    st.session_state.user_email = ""
+    nav_to('landing')
+
+# -----------------------------------------------------------------------------
+# 6. PAGES
+# -----------------------------------------------------------------------------
+
+# --- LANDING ---
+def show_landing():
+    c1, c2 = st.columns([1, 8])
+    with c1: st.markdown("### ✨ SHINUI")
+    st.markdown("<br><br>", unsafe_allow_html=True)
+    
+    c1, c2 = st.columns([1.5, 1])
+    with c1:
+        st.markdown("""
+        <h1 style='font-size: 4rem; line-height: 1.1; margin-bottom: 20px;'>
+            Medical Intelligence.<br><span style='color:#38bdf8;'>Simplified.</span>
+        </h1>
+        <p style='font-size: 1.2rem; color: #94a3b8; margin-bottom: 40px;'>
+            SHINUI uses Llama 3.2 Vision AI to analyze medical data instantly.
+        </p>
+        """, unsafe_allow_html=True)
+        b1, b2 = st.columns([1, 2])
+        with b1: 
+            if st.button("Sign In"): nav_to('login')
+    
+    with c2:
+        st.markdown("""
+        <div class='shinui-card'>
+            <h3>🧬 Multimodal Brain</h3>
+            <p style='color:#94a3b8;'>Powered by Meta Llama 3.2 Vision.</p>
+        </div>
+        """, unsafe_allow_html=True)
+
+# --- LOGIN ---
+def show_login():
+    c1, c2, c3 = st.columns([1,1,1])
+    with c2:
+        st.markdown("<br><br>", unsafe_allow_html=True)
+        st.markdown("<div class='shinui-card' style='text-align:center;'><h2>Member Access</h2></div>", unsafe_allow_html=True)
+        email = st.text_input("Email")
+        password = st.text_input("Password", type="password")
+        if st.button("Authenticate"):
+            if email:
+                st.session_state.logged_in = True
+                st.session_state.user_email = email
+                nav_to('dashboard')
+        if st.button("Back"): nav_to('landing')
+
+# --- DASHBOARD ---
+def show_dashboard():
+    # SIDEBAR
+    with st.sidebar:
+        st.markdown(f"### 👤 {st.session_state.user_email}")
+        st.markdown("---")
+        st.write("HISTORY LOG")
+        if st.session_state.history:
+            for h in reversed(st.session_state.history):
+                st.markdown(f"<div style='font-size:0.8rem; padding:5px; border-left:2px solid #38bdf8; margin-bottom:5px;'>{h[:50]}...</div>", unsafe_allow_html=True)
+        else:
+            st.caption("No scans yet.")
+        st.markdown("---")
+        if st.button("Sign Out"): sign_out()
+
+    # MAIN UI
+    st.title("Diagnostic Interface")
+    t1, t2, t3 = st.tabs(["📷 Vision", "🎙️ Voice", "📝 Text"])
+
+    # TAB 1: VISION
+    with t1:
+        st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
+        img_file = st.file_uploader("Upload Scan", type=['png','jpg','jpeg'])
+        if img_file and st.button("Analyze Visual"):
+            image = Image.open(img_file)
+            with st.spinner("Processing Visual Data..."):
+                res = get_ai_insight("Image", image)
                 st.session_state.result = res
                 st.session_state.history.append(res)
-    st.markdown("</div>", unsafe_allow_html=True)
-
-# Tab 3: Text
-with t3:
-    st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
-    txt = st.text_area("Clinical Notes / Symptoms")
-    if txt and st.button("Analyze Notes", key="btn_txt"):
-        with st.spinner("Analyzing..."):
-            res = get_ai_insight("Text", txt)
-            st.session_state.result = res
-            st.session_state.history.append(res)
-    st.markdown("</div>", unsafe_allow_html=True)
-
-# -----------------------------------------------------------------------------
-# 5. RESULTS & HISTORY
-# -----------------------------------------------------------------------------
-if st.session_state.result:
-    st.markdown(f"""
-    <div class='shinui-card' style='border-left: 5px solid #38bdf8;'>
-        <h3 style='margin-top:0; color:#38bdf8;'>Analysis Result</h3>
-        <div style='white-space: pre-wrap; color: #e2e8f0; line-height: 1.6;'>{st.session_state.result}</div>
-    </div>
-    """, unsafe_allow_html=True)
-
-if st.session_state.history:
-    with st.expander("View Session History"):
-        for i, h in enumerate(reversed(st.session_state.history)):
-            st.markdown(f"**Scan {len(st.session_state.history)-i}:** {h[:100]}...")
+        st.markdown("</div>", unsafe_allow_html=True)
+
+    # TAB 2: VOICE
+    with t2:
+        st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
+        audio_input = st.audio_input("Record Symptoms")
+        if audio_input:
+            if st.button("Analyze Recording"):
+                with st.spinner("Transcribing & Analyzing..."):
+                    res = get_ai_insight("Audio", audio_input.read())
+                    st.session_state.result = res
+                    st.session_state.history.append(res)
+        st.markdown("</div>", unsafe_allow_html=True)
+
+    # TAB 3: TEXT
+    with t3:
+        st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
+        txt = st.text_area("Clinical Notes")
+        if txt and st.button("Analyze Notes"):
+            with st.spinner("Thinking..."):
+                res = get_ai_insight("Text", txt)
+                st.session_state.result = res
+                st.session_state.history.append(res)
+        st.markdown("</div>", unsafe_allow_html=True)
+
+    # RESULTS AREA
+    if st.session_state.result:
+        st.markdown(f"""
+        <div class='shinui-card' style='border-left: 5px solid #38bdf8;'>
+            <h3 style='margin-top:0; color:#38bdf8;'>Analysis Complete</h3>
+            <div style='white-space: pre-wrap; color: #e2e8f0; line-height: 1.6;'>{st.session_state.result}</div>
+        </div>
+        """, unsafe_allow_html=True)
+
+# -----------------------------------------------------------------------------
+# 7. ROUTER
+# -----------------------------------------------------------------------------
+if st.session_state.page == 'landing': show_landing()
+elif st.session_state.page == 'login': show_login()
+elif st.session_state.page == 'dashboard':
+    if st.session_state.logged_in: show_dashboard()
+    else: nav_to('login')