Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,345 +1,200 @@
 import streamlit as st
+import os
 import time
 from datetime import datetime
+from PIL import Image
+from huggingface_hub import InferenceClient
 
 # -----------------------------------------------------------------------------
-# 1. APP CONFIGURATION
+# 1. SETUP & SECRETS
 # -----------------------------------------------------------------------------
-st.set_page_config(
-    page_title="SHINUI | Intelligent Health AI",
-    page_icon="✨",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
+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")
+
+# RETRIEVE API KEY
+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()
+
+# INITIALIZE CLIENT
+client = InferenceClient(token=HF_TOKEN)
 
 # -----------------------------------------------------------------------------
-# 2. SESSION STATE INITIALIZATION
+# 2. THE "UNGATED" BRAIN LOGIC
 # -----------------------------------------------------------------------------
-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
+def get_ai_insight(input_type, content):
+    """
+    Uses Open-Source, Non-Gated models to avoid permission errors.
+    """
+    # 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."
+    )
+
+    try:
+        final_text_input = ""
+
+        # A. VISION (Uses BLIP - Ungated)
+        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
+            )
+            # 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."
+
+        # B. AUDIO (Uses Whisper - Ungated)
+        elif input_type == "Audio":
+            # 1. Transcribe audio to text
+            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."
+
+        # C. TEXT (Direct)
+        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
+
+    except Exception as e:
+        return f"⚠️ Analysis Error: {str(e)}"
 
 # -----------------------------------------------------------------------------
-# 3. VISUAL STYLING (PREMIUM DARK MODE + ANIMATIONS)
+# 3. VISUAL STYLING (TIVE.COM STYLE)
 # -----------------------------------------------------------------------------
+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');
-
-    /* GLOBAL THEME */
+    
     .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;
     }
-
-    /* ANIMATIONS */
-    @keyframes slideUp {
-        0% { opacity: 0; transform: translateY(20px); }
-        100% { opacity: 1; transform: translateY(0); }
-    }
-    .animate-slide-up {
-        animation: slideUp 0.6s cubic-bezier(0.16, 1, 0.3, 1) forwards;
-    }
-
-    /* CARDS */
+    
+    /* 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);
-        transition: all 0.3s ease;
         margin-bottom: 20px;
     }
-    .shinui-card:hover {
-        transform: translateY(-3px);
-        border-color: #38bdf8;
-        background: rgba(30, 41, 59, 0.6);
-        box-shadow: 0 10px 30px -10px rgba(0, 0, 0, 0.5);
-    }
-
-    /* BUTTONS */
+    
+    /* Buttons */
     div.stButton > button {
-        background: linear-gradient(135deg, #38bdf8 0%, #0ea5e9 100%);
-        color: white;
+        background: #38bdf8;
+        color: #0f172a;
         border: none;
-        font-weight: 600;
-        padding: 12px 24px;
+        font-weight: 700;
+        padding: 12px 20px;
         border-radius: 8px;
-        transition: all 0.2s;
         width: 100%;
+        transition: all 0.3s;
     }
     div.stButton > button:hover {
-        transform: scale(1.02);
-        box-shadow: 0 0 15px rgba(56, 189, 248, 0.4);
+        background: #ffffff;
+        box-shadow: 0 0 20px rgba(56, 189, 248, 0.5);
     }
 
-    /* TEXT GRADIENTS */
-    .highlight {
-        background: linear-gradient(90deg, #38bdf8, #a855f7);
-        -webkit-background-clip: text;
-        -webkit-text-fill-color: transparent;
-        font-weight: 800;
-    }
+    /* Headers */
+    h1, h2, h3 { color: white; font-weight: 700; }
     
-    /* HIDE DEFAULT UI */
     #MainMenu, footer, header {visibility: hidden;}
 </style>
 """, unsafe_allow_html=True)
 
 # -----------------------------------------------------------------------------
-# 4. LOGIC FUNCTIONS
+# 4. APP UI
 # -----------------------------------------------------------------------------
-def nav_to(page):
-    st.session_state.page = page
-    st.rerun()
-
-def sign_out():
-    """Securely clears session and redirects."""
-    st.session_state.logged_in = False
-    st.session_state.history = []
-    st.session_state.result = None
-    st.session_state.user_email = ""
-    nav_to('landing')
-
-def process_analysis(input_type, content_name):
-    """
-    Simulates the high-end analysis without crashing the server.
-    It adapts the response based on the input type.
-    """
-    with st.spinner(f"SHINUI Neural Engine processing {input_type}..."):
-        time.sleep(2) # Cinematic delay for UI feel
-        
-        # Intelligent Mock Responses
-        if input_type == "Image":
-            summary = "Visual Scan: Detected pill bottle label with clear text indicators."
-            action = "Check dosage instructions."
-        elif input_type == "Audio":
-            summary = "Vocal Analysis: Voice biomarkers indicate mild respiratory stress."
-            action = "Monitor breathing patterns."
-        elif input_type == "Text":
-            summary = "Symptom NLP: Description matches common seasonal allergic reaction."
-            action = "Consult pharmacist for antihistamines."
-        elif input_type == "Face Scan":
-            summary = "Dermatological Scan: No critical irregularities detected on skin surface."
-            action = "Routine hydration recommended."
-        else:
-            summary = "Analysis complete."
-            action = "Review details."
-
-        return {
-            "summary": summary,
-            "risk": "Low to Moderate",
-            "details": "The input data has been processed against our medical database. No immediate emergency flags were triggered.",
-            "action": action,
-            "date": datetime.now().strftime("%Y-%m-%d %H:%M")
-        }
+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())
+                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. PAGES
+# 5. RESULTS & HISTORY
 # -----------------------------------------------------------------------------
-
-# --- LANDING PAGE ---
-def show_landing():
-    c1, c2 = st.columns([1, 8])
-    with c1:
-        st.markdown("<h3 style='margin:0; color:#38bdf8;'>SHINUI</h3>", unsafe_allow_html=True)
-    
-    st.markdown("<br><br>", unsafe_allow_html=True)
-    
-    col1, col2 = st.columns([1.5, 1])
-    with col1:
-        st.markdown('<div class="animate-slide-up">', unsafe_allow_html=True)
-        st.markdown(f"""
-        <h1 style='font-size: 4.5rem; line-height: 1.1; margin-bottom: 20px;'>
-            Medical Intelligence.<br>
-            <span class='highlight'>Simplified.</span>
-        </h1>
-        <p style='font-size: 1.2rem; color: #94a3b8; margin-bottom: 40px; max-width:90%;'>
-            SHINUI bridges the gap between complex medical data and human understanding.
-            Upload images, speak your symptoms, or scan documents for instant clarity.
-        </p>
-        """, unsafe_allow_html=True)
-        
-        b1, b2 = st.columns([1, 2])
-        with b1:
-            if st.button("Start Analysis"):
-                nav_to('login')
-        with b2:
-            if st.button("About Tool"):
-                nav_to('about')
-        st.markdown('</div>', unsafe_allow_html=True)
-
-    with col2:
-        st.markdown('<div class="animate-slide-up" style="animation-delay: 0.2s;">', unsafe_allow_html=True)
-        st.markdown("""
-        <div class="shinui-card">
-            <h3>🧬 Multimodal Engine</h3>
-            <p style="color:#94a3b8; font-size:0.9rem;">Processing Video, Audio, and Text simultaneously.</p>
-        </div>
-        <div class="shinui-card">
-            <h3>🔒 Privacy First</h3>
-            <p style="color:#94a3b8; font-size:0.9rem;">Session-based data handling. No permanent storage.</p>
-        </div>
-        """, unsafe_allow_html=True)
-        st.markdown('</div>', unsafe_allow_html=True)
-
-# --- ABOUT PAGE ---
-def show_about():
-    if st.button("← Back"): nav_to('landing')
-    st.markdown("<br>", unsafe_allow_html=True)
-    st.markdown("""
-    <div class="shinui-card animate-slide-up">
-        <h2 class="highlight">About SHINUI</h2>
-        <p style="font-size: 1.1rem; line-height: 1.8; color: #cbd5e1;">
-            SHINUI is a dedicated AI health assistant designed to clarify medical confusion.
-            It is not a replacement for a doctor, but a tool to help you organize, understand, and
-            prepare for professional medical consultations.
-        </p>
-        <h4 style="margin-top:20px; color:white;">Our Mission</h4>
-        <p style="color: #94a3b8;">To empower patients with knowledge through accessible technology, ensuring that medical data—whether handwritten notes, complex scans, or confusing labels—becomes clear, actionable information.</p>
+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)
 
-# --- LOGIN PAGE ---
-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>Secure Access</h2>
-            <p style="color:#94a3b8;">Sign in to access the Neural Engine.</p>
-        </div>
-        """, unsafe_allow_html=True)
-        
-        email = st.text_input("Email Identity")
-        password = st.text_input("Passkey", 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("Cancel"): nav_to('landing')
-
-# --- DASHBOARD ---
-def show_dashboard():
-    # Sidebar Logic
-    with st.sidebar:
-        st.markdown(f"### 👤 {st.session_state.user_email}")
-        st.markdown("---")
-        st.markdown("#### Recent Scans")
-        if st.session_state.history:
-            for item in reversed(st.session_state.history):
-                st.markdown(f"""
-                <div style="font-size:0.8rem; padding:10px; border-left:2px solid #38bdf8; margin-bottom:5px; background:rgba(255,255,255,0.03);">
-                    <div style="color:white;">{item['summary']}</div>
-                    <div style="color:#64748b; font-size:0.7rem;">{item['date']}</div>
-                </div>
-                """, unsafe_allow_html=True)
-        else:
-            st.caption("No history found.")
-        
-        st.markdown("---")
-        if st.button("Sign Out"): sign_out()
-
-    # Main Content
-    st.title("Neural Diagnostic Interface")
-    
-    # TABS
-    t1, t2, t3, t4 = st.tabs(["📷 Image/Video", "🎙️ Audio/Speech", "📝 Text Input", "👤 Face Scan"])
-    
-    input_data = None
-    input_type = None
-
-    # Tab 1: Image
-    with t1:
-        st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
-        st.write("Upload Medical Imaging or Video.")
-        f = st.file_uploader("Select File", type=['png','jpg','jpeg', 'mp4'], label_visibility="collapsed", key="img_uploader")
-        if f and st.button("Analyze Image"):
-            input_data = f.name
-            input_type = "Image"
-        st.markdown("</div>", unsafe_allow_html=True)
-
-    # Tab 2: Audio (Using File Uploader for stability, or native input if available)
-    with t2:
-        st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
-        st.write("Record or Upload audio description.")
-        # We use file uploader to be safe on older streamlit versions, works 100%
-        audio_file = st.file_uploader("Upload Audio", type=['wav','mp3'], label_visibility="collapsed", key="audio_uploader")
-        if audio_file and st.button("Process Audio"):
-            input_data = "Audio File"
-            input_type = "Audio"
-        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("Describe symptoms...", height=100)
-        if txt and st.button("Analyze Text"):
-            input_data = txt
-            input_type = "Text"
-        st.markdown("</div>", unsafe_allow_html=True)
-
-    # Tab 4: Face
-    with t4:
-        st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
-        cam = st.camera_input("Face Scan")
-        if cam:
-            input_data = "Face Data"
-            input_type = "Face Scan"
-            # Trigger immediately on photo take if you prefer, or add button
-            # We will trigger via button to be consistent
-            if st.button("Analyze Face"):
-               pass 
-        st.markdown("</div>", unsafe_allow_html=True)
-
-    # PROCESSING LOGIC
-    # We check if a button set input_data OR if cam was used
-    if input_data and input_type:
-        res = process_analysis(input_type, input_data)
-        st.session_state.result = res
-        # Add to history
-        st.session_state.history.append({
-            "date": res['date'],
-            "summary": res['summary']
-        })
-        st.rerun() # Refresh to show results
-
-    # RESULTS DISPLAY
-    if st.session_state.result:
-        r = st.session_state.result
-        st.markdown("<br>", unsafe_allow_html=True)
-        st.markdown(f"""
-        <div class="shinui-card animate-slide-up" style="border-top: 4px solid #38bdf8;">
-            <h3 style="margin-top:0;">Analysis Complete</h3>
-            <p style="font-size:1.2rem; color: white;">{r['summary']}</p>
-            <p style="color:#94a3b8;">{r['details']}</p>
-            <hr style="border-color:rgba(255,255,255,0.1);">
-            <div style="display:flex; justify-content:space-between;">
-                <div><b>Risk:</b> {r['risk']}</div>
-                <div><b>Action:</b> {r['action']}</div>
-            </div>
-        </div>
-        """, unsafe_allow_html=True)
-        
-        if st.button("Clear Results"):
-            st.session_state.result = None
-            st.rerun()
-
-# -----------------------------------------------------------------------------
-# 6. ROUTER
-# -----------------------------------------------------------------------------
-if st.session_state.page == 'landing': show_landing()
-elif st.session_state.page == 'about': show_about()
-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')
+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]}...")