File size: 11,167 Bytes
f51cd44 e621b51 37b828a e621b51 37b828a f51cd44 6ee6fcd 37b828a 6ee6fcd 37b828a e621b51 9f8ae5f 37b828a 9f8ae5f 37b828a 9f8ae5f 37b828a e621b51 37b828a 6ee6fcd d2d8662 9f8ae5f 37b828a 6ee6fcd 37b828a 0ad7393 e621b51 37b828a e621b51 37b828a e621b51 37b828a e621b51 37b828a e621b51 37b828a 6ee6fcd 0ad7393 6ee6fcd d2d8662 6ee6fcd 9f8ae5f 6ee6fcd 9f8ae5f 6ee6fcd 9f8ae5f 6ee6fcd 37b828a 9f8ae5f 37b828a 9f8ae5f 37b828a 9f8ae5f d2d8662 9f8ae5f 37b828a 9f8ae5f 0ad7393 d2d8662 37b828a d2d8662 0ad7393 37b828a 0ad7393 d2d8662 9f8ae5f 37b828a 9f8ae5f d2d8662 9f8ae5f 37b828a d2d8662 9f8ae5f 0ad7393 9f8ae5f 0ad7393 9f8ae5f 37b828a 9f8ae5f d2d8662 9f8ae5f 0ad7393 9f8ae5f 37b828a 9f8ae5f 0ad7393 9f8ae5f 0ad7393 d2d8662 0ad7393 d2d8662 0ad7393 37b828a d2d8662 9f8ae5f d2d8662 9f8ae5f d2d8662 9f8ae5f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 |
import streamlit as st
import os
import torch
from PIL import Image
from transformers import AutoModelForCausalLM, AutoProcessor
# -----------------------------------------------------------------------------
# 0. AUTO-FIX FOR UPLOAD ERROR (RUNS INSTANTLY)
# -----------------------------------------------------------------------------
# This creates the config.toml automatically so uploads work.
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 & MODEL LOADING (AarambhAI Gemma)
# -----------------------------------------------------------------------------
st.set_page_config(page_title="SHINUI | Gemma AI", page_icon="✨", layout="wide")
@st.cache_resource
def load_model():
model_id = "AarambhAI/gemma-like-multimodal-speech-vision-text"
# Load Processor and Model
# We use trust_remote_code=True because this is a custom architecture
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.float32, # float32 is safer for CPU
device_map="auto",
trust_remote_code=True
)
return model, processor
# Load Model on App Start
try:
with st.spinner("Initializing Gemma Multimodal Model..."):
model, processor = load_model()
MODEL_LOADED = True
except Exception as e:
st.error(f"⚠️ Model Load Error: {e}")
MODEL_LOADED = False
# -----------------------------------------------------------------------------
# 2. STATE MANAGEMENT
# -----------------------------------------------------------------------------
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 (Gemma Logic)
# -----------------------------------------------------------------------------
def get_gemma_insight(input_type, content):
if not MODEL_LOADED:
return "Error: Model not loaded."
try:
# A. VISION ANALYSIS
if input_type == "Image":
text_prompt = "Analyze this medical image and list observations."
# Gemma format input
inputs = processor(text=text_prompt, images=content, return_tensors="pt")
# Generate
with torch.no_grad():
output = model.generate(**inputs, max_new_tokens=200)
return processor.batch_decode(output, skip_special_tokens=True)[0]
# B. TEXT ANALYSIS
elif input_type == "Text":
text_prompt = f"Medical analysis for: {content}"
inputs = processor(text=text_prompt, return_tensors="pt")
with torch.no_grad():
output = model.generate(**inputs, max_new_tokens=200)
return processor.batch_decode(output, skip_special_tokens=True)[0]
except Exception as e:
return f"⚠️ Processing Error: {str(e)}"
# -----------------------------------------------------------------------------
# 4. UI STYLING (Clean Dark Theme)
# -----------------------------------------------------------------------------
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;
}
.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;
}
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); }
#MainMenu, footer, header {visibility: hidden;}
</style>
""", unsafe_allow_html=True)
# -----------------------------------------------------------------------------
# 5. NAVIGATION
# -----------------------------------------------------------------------------
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;'>Runs Locally.</span>
</h1>
<p style='font-size: 1.2rem; color: #94a3b8; margin-bottom: 40px;'>
SHINUI runs the specialized Gemma Multimodal model for secure analysis.
</p>
""", unsafe_allow_html=True)
b1, b2 = st.columns([1, 2])
with b1:
if st.button("Sign In"): nav_to('login')
with b2:
if st.button("About SHINUI"): nav_to('about')
with c2:
st.markdown("""
<div class='shinui-card'>
<h3>🧬 Gemma Multimodal</h3>
<p style='color:#94a3b8;'>Vision, Text & Speech capable.</p>
</div>
""", unsafe_allow_html=True)
# --- ABOUT ---
def show_about():
if st.button("← Back Home"): nav_to('landing')
st.markdown("<br>", unsafe_allow_html=True)
st.markdown("""
<div class='shinui-card'>
<h2 style='color:#38bdf8'>About SHINUI</h2>
<p style='font-size:1.1rem; line-height:1.6'>
SHINUI utilizes the <b>AarambhAI Gemma-like Multimodal</b> model.
This model is unique because it understands images, text, and speech natively in a single architecture.
</p>
<hr style='border-color:#333'>
<h3>Capabilities</h3>
<ul>
<li><b>Visual Diagnostics:</b> Reads medical images.</li>
<li><b>Clinical Text:</b> Analyzes symptoms and notes.</li>
</ul>
</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():
with st.sidebar:
st.markdown(f"### 👤 {st.session_state.user_email}")
if st.button("About System"): nav_to('about_internal')
st.markdown("---")
st.write("HISTORY")
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()
st.title("Gemma Interface")
t1, t2 = st.tabs(["📷 Image Scan", "📝 Text Analysis"])
# TAB 1: IMAGE
with t1:
st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
img_file = st.file_uploader("Upload Medical Image", type=['png','jpg','jpeg'])
if img_file and st.button("Analyze Visual"):
if not MODEL_LOADED:
st.error("Model failed to load (Check Space Logs).")
else:
image = Image.open(img_file)
st.image(image, width=300)
with st.spinner("Gemma Processing..."):
res = get_gemma_insight("Image", image)
st.session_state.result = res
st.session_state.history.append(f"Image: {res[:30]}...")
st.markdown("</div>", unsafe_allow_html=True)
# TAB 2: TEXT
with t2:
st.markdown("<div class='shinui-card'>", unsafe_allow_html=True)
txt = st.text_area("Clinical Notes / Symptoms")
if txt and st.button("Analyze Notes"):
if not MODEL_LOADED:
st.error("Model failed to load.")
else:
with st.spinner("Gemma Processing..."):
res = get_gemma_insight("Text", txt)
st.session_state.result = res
st.session_state.history.append(f"Text: {res[:30]}...")
st.markdown("</div>", unsafe_allow_html=True)
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)
# --- INTERNAL ABOUT ---
def show_about_internal():
with st.sidebar:
if st.button("← Back"): nav_to('dashboard')
st.markdown("""
<div class='shinui-card'>
<h2 style='color:#38bdf8'>System Status</h2>
<p><b>Model:</b> AarambhAI Gemma-like Multimodal</p>
<p><b>Backend:</b> Local Transformers</p>
</div>
""", unsafe_allow_html=True)
# -----------------------------------------------------------------------------
# 7. 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')
elif st.session_state.page == 'about_internal':
if st.session_state.logged_in: show_about_internal()
else: nav_to('login') |