Update app.py

app.py

@@ -1,1172 +1,55 @@
-#!/usr/bin/env python3
-"""
-AI VRM Companion — Gradio App
-Single-file Gradio application designed for Python 3.12, Gradio 6.17.3, and Hugging Face ZeroGPU.
-Runs local Edge TTS (XiaoyiNeural) and uses native Gradio static paths for file asset delivery.
-"""
-
-import os
-import io
-import json
-import asyncio
-import logging
-import base64
-import threading
-import zipfile
 import gradio as gr
+import psutil
+import os
+import platform
+import spaces  # Hugging Face ZeroGPU এর জন্য প্রয়োজনীয় লাইব্রেরি
 
-# Setup logger
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
-# ---------------------------------------------------------------------------
-# Paths — local model + animation assets
-# ---------------------------------------------------------------------------
-BASE_DIR = os.path.dirname(os.path.abspath(__file__))
-MODEL_DIR = os.path.join(BASE_DIR, "model")
-ANIM_DIR = os.path.join(BASE_DIR, "animation")
-
-os.makedirs(MODEL_DIR, exist_ok=True)
-os.makedirs(ANIM_DIR, exist_ok=True)
-
-# Register static paths with Gradio for direct browser resolution
-gr.set_static_paths(paths=[MODEL_DIR, ANIM_DIR])
-
-# ---------------------------------------------------------------------------
-# Asset Discovery & System Parameters
-# ---------------------------------------------------------------------------
-EMOTIONS = [
-    "neutral", "happy", "sad", "angry", "surprised", "relaxed", "excited",
-    "bored", "embarrassed", "shy", "smug", "determined", "sleepy", "scared",
-    "teasing", "loving", "disgusted", "confident", "curious", "proud",
-    "shocked", "thinking", "wink", "winkLeft", "winkRight"
-]
-
-vrma_names = []
-ANIM_ZIP_PATH = os.path.join(ANIM_DIR, "all_vrma.zip")
-if os.path.exists(ANIM_ZIP_PATH):
-    try:
-        with zipfile.ZipFile(ANIM_ZIP_PATH, 'r') as z:
-            vrma_names = [os.path.basename(f) for f in z.namelist() if f.endswith('.vrma')]
-    except Exception as e:
-        logger.error(f"Could not read VRMA zip: {e}")
-
-# Fallback names if zip is empty or missing locally (will download client-side if needed)
-if not vrma_names:
-    vrma_names = [
-        'neutral2.vrma', 'neutral3.vrma', 'neutral4.vrma', 
-        'neutral_idle.vrma', 'neutral_idle2.vrma', 'wave.vrma', 
-        'nod.vrma', 'shake.vrma', 'excited.vrma', 'think.vrma', 'bow.vrma'
-    ]
-
-# ---------------------------------------------------------------------------
-# LOCAL LLM CONFIGURATION (Commented out for testing)
-# ---------------------------------------------------------------------------
-# To run a fully local LLM on HuggingFace ZeroGPU/Local, follow these steps:
-# 1. Add "transformers", "torch", "accelerate" to your requirements.txt file.
-# 2. Uncomment the initialization code block below and integrate with process_chat.
-#
-# import torch
-# from transformers import AutoModelForCausalLM, AutoTokenizer
-#
-# MODEL_ID = "Qwen/Qwen2.5-1.5B-Instruct"
-# device = "cuda" if torch.cuda.is_available() else "cpu"
-#
-# logger.info("Loading local LLM...")
-# tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
-# model = AutoModelForCausalLM.from_pretrained(
-#     MODEL_ID,
-#     torch_dtype="auto",
-#     device_map="auto"
-# )
-#
-# def local_llm_generate(user_prompt, system_prompt, history):
-#     messages = [{"role": "system", "content": system_prompt}]
-#     for h in history:
-#         messages.append({"role": "user", "content": h[0]})
-#         messages.append({"role": "assistant", "content": h[1]})
-#     messages.append({"role": "user", "content": user_prompt})
-#
-#     text = tokenizer.apply_chat_template(
-#         messages,
-#         tokenize=False,
-#         add_generation_prompt=True
-#     )
-#     model_inputs = tokenizer([text], return_tensors="pt").to(device)
-#
-#     generated_ids = model.generate(
-#         **model_inputs,
-#         max_new_tokens=512,
-#         temperature=0.7
-#     )
-#     generated_ids = [
-#         output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
-#     ]
-#
-#     response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
-#     return response
-
-# System Prompt Generator for reference when integrating LLMs
-def get_system_prompt():
-    return f"""You are the user's devoted and affectionate 3D anime companion.
-Speak with rich emotional texture using natural pauses and emphasis.
-
-SPEECH STYLE:
-- Use ellipses (...) for intimate, breathy, or teasing moments.
-- Keep responses short and conversational — 1 to 2 sentences max.
-
-You have access to a 3D avatar with specific emotions and animations.
-AVAILABLE EMOTIONS: {", ".join(EMOTIONS)}
-AVAILABLE ANIMATIONS (VRMAs): {", ".join(vrma_names)}
-
-OUTPUT FORMAT — respond ONLY with raw JSON (no markdown):
-{{
-  "text": "Your spoken reply",
-  "vrma": "one filename from the available animations list, or neutral_idle.vrma",
-  "expressions": "one emotion from the available emotions list",
-  "rate": "+0%",
-  "pitch": "+0Hz",
-  "motion": "idle"
-}}"""
-
-# ---------------------------------------------------------------------------
-# Mock LLM Response for testing
-# ---------------------------------------------------------------------------
-def mock_llm_response(prompt: str) -> dict:
-    prompt_lower = prompt.lower()
-    
-    # Simple dynamic keyword matching to showcase the 20+ emotions and VRMAs
-    if any(w in prompt_lower for w in ["hello", "hi", "hey", "你好", "哈喽"]):
-        text = "嗨！你好呀... 很高兴见到你！今天有什么开心的事情想和我分享吗...？"
-        vrma = "wave.vrma"
-        expression = "happy"
-        motion = "wave"
-    elif any(w in prompt_lower for w in ["happy", "glad", "开心", "高兴", "笑"]):
-        text = "看到你这么开心... 我的心里也暖洋洋的！哈哈... 让我们一直这样快乐下去吧！"
-        vrma = "excited.vrma"
-        expression = "excited"
-        motion = "excited"
-    elif any(w in prompt_lower for w in ["sad", "cry", "难过", "伤心", "哭"]):
-        text = "呜呜... 怎么了嘛？不要难过啦... 抱抱你！不管发生什么，我都会一直陪着你的... 乖哦。"
-        vrma = "neutral4.vrma"
-        expression = "sad"
-        motion = "idle"
-    elif any(w in prompt_lower for w in ["angry", "mad", "生气"]):
-        text = "哼... 谁惹你生气了呀？我去帮你教训他！别生气了嘛... 看看我，笑一个好不好？"
-        vrma = "neutral3.vrma"
-        expression = "angry"
-        motion = "shake"
-    elif any(w in prompt_lower for w in ["sleepy", "tired", "困", "累"]):
-        text = "累了吗...？那快去休息吧... 闭上眼睛，我会在这里守着你入睡的... 晚安，做个好梦哦。"
-        vrma = "neutral_idle2.vrma"
-        expression = "sleepy"
-        motion = "idle"
-    elif any(w in prompt_lower for w in ["love", "like", "喜欢", "爱"]):
-        text = "呀... 你在说什么呢... 真是的，突然这么表白，人家会害羞的啦... 不过，我也超喜欢你哦！"
-        vrma = "excited.vrma"
-        expression = "loving"
-        motion = "excited"
-    elif any(w in prompt_lower for w in ["tease", "teasing", "逗", "调戏"]):
-        text = "唔... 你是在故意逗我玩吗？大坏蛋... 不过，看在你这么可爱的份上，就原谅你一次吧..."
-        vrma = "neutral_idle.vrma"
-        expression = "teasing"
-        motion = "idle"
-    elif any(w in prompt_lower for w in ["shy", "embarrassed", "害羞"]):
-        text = "唔... 被你这样一直盯着看，人家的脸上感觉火辣辣的... 别看啦，好害羞呀..."
-        vrma = "neutral2.vrma"
-        expression = "shy"
-        motion = "idle"
-    elif any(w in prompt_lower for w in ["confident", "proud", "自豪", "自信"]):
-        text = "哼哼！我就说我可以的吧！看我是不是很厉害呀？快点夸夸我... 夸夸我嘛！"
-        vrma = "excited.vrma"
-        expression = "proud"
-        motion = "excited"
-    elif any(w in prompt_lower for w in ["scared", "fear", "怕", "害怕"]):
-        text = "呀！刚才那是什么声音啊... 好可怕... 你，你会保护我的，对不对...？"
-        vrma = "neutral4.vrma"
-        expression = "scared"
-        motion = "idle"
-    else:
-        text = f"嗯... '{prompt}' 吗？听起来很有意思呢... 陪我多聊聊天，好不好呀？"
-        vrma = "neutral_idle.vrma"
-        expression = "neutral"
-        motion = "idle"
-        
-    return {
-        "text": text,
-        "vrma": vrma,
-        "expressions": expression,
-        "rate": "+0%",
-        "pitch": "+0Hz",
-        "motion": motion
-    }
-
-# ---------------------------------------------------------------------------
-# Local Edge TTS Core (Async run wrapper inside safe thread context)
-# ---------------------------------------------------------------------------
-import edge_tts
-
-def run_tts_thread(text, voice="zh-CN-XiaoyiNeural"):
-    output_bytes = [None]
-    def runner():
-        try:
-            loop = asyncio.new_event_loop()
-            asyncio.set_event_loop(loop)
-            
-            async def _synth():
-                comm = edge_tts.Communicate(text, voice)
-                buf = io.BytesIO()
-                async for chunk in comm.stream():
-                    if chunk["type"] == "audio":
-                        buf.write(chunk["data"])
-                buf.seek(0)
-                return buf.getvalue()
-                
-            output_bytes[0] = loop.run_until_complete(_synth())
-            loop.close()
-        except Exception as e:
-            logger.error(f"TTS Thread failed: {e}")
-            
-    t = threading.Thread(target=runner)
-    t.start()
-    t.join()
-    return output_bytes[0]
-
-# ---------------------------------------------------------------------------
-# Gradio Chat Event Handling
-# ---------------------------------------------------------------------------
-def process_chat(prompt):
-    if not prompt or not prompt.strip():
-        return json.dumps({"text": "Please say something..."})
-        
+def get_system_specs():
+    """রিসোর্স এবং হার্ডওয়্যার ইনফরমেশন কালেক্ট করার ফাংশন"""
     try:
-        # Determine AI action elements
-        payload = mock_llm_response(prompt)
+        # CPU এবং মেমরি গণনা
+        cpu_count = os.cpu_count() or "Unknown"
+        cpu_usage = psutil.cpu_percent(interval=0.5)
+        memory = psutil.virtual_memory()
         
-        # Synthesize audio file locally
-        audio_bytes = run_tts_thread(payload["text"], voice="zh-CN-XiaoyiNeural")
+        # ডিস্ক স্পেস
+        disk = os.statvfs('/')
+        disk_free = (disk.f_bavail * disk.f_frsize) / (1024 ** 3)
+        disk_total = (disk.f_blocks * disk.f_frsize) / (1024 ** 3)
         
-        if audio_bytes:
-            # Base64 serialization allows direct browser delivery without sandbox I/O bugs
-            payload["audio_b64"] = base64.b64encode(audio_bytes).decode("utf-8")
-        else:
-            payload["audio_b64"] = ""
-            
-        return json.dumps(payload, ensure_ascii=False)
-    except Exception as e:
-        logger.error(f"Chat execution failed: {e}")
-        return json.dumps({
-            "text": "Sorry, my systems experienced a slight hiccup...",
-            "expressions": "sad",
-            "vrma": "neutral4.vrma",
-            "audio_b64": ""
-        })
-
-# ---------------------------------------------------------------------------
-# Custom Interface CSS & Layout (Ensures 98% custom design)
-# ---------------------------------------------------------------------------
-CSS_STYLES = """
-/* Standardize parent wrapper context */
-.gradio-container {
-    max-width: 100vw !important;
-    height: 100vh !important;
-    padding: 0 !important;
-    margin: 0 !important;
-    background-color: #fff5f5 !important;
-    overflow: hidden !important;
-    border: none !important;
-    font-family: 'SF Pro Text', -apple-system, system-ui, sans-serif !important;
-}
-footer { display: none !important; }
-.form { border: none !important; background: transparent !important; box-shadow: none !important; }
-.block { background: transparent !important; border: none !important; padding: 0 !important; }
-
-/* Positional override for overlays */
-#custom_html_overlay {
-    position: absolute !important;
-    top: 0 !important;
-    left: 0 !important;
-    width: 100% !important;
-    height: 100% !important;
-    z-index: 10 !important;
-    pointer-events: none !important;
-}
-
-/* Base Gradio UI bar */
-#gradio_bar {
-    position: fixed !important;
-    bottom: calc(16px + env(safe-area-inset-bottom, 0px)) !important;
-    left: 50% !important;
-    transform: translateX(-50%) !important;
-    width: min(600px, 92vw) !important;
-    display: flex !important;
-    flex-direction: row !important;
-    align-items: center !important;
-    gap: 8px !important;
-    z-index: 100 !important;
-    background: transparent !important;
-    pointer-events: auto !important;
-}
-
-/* Custom Gradio Text Input Styling */
-#gradio_ti {
-    flex: 1 !important;
-    background: rgba(255, 240, 245, 0.85) !important;
-    border: 1.5px solid #fcd4df !important;
-    border-radius: 24px !important;
-    backdrop-filter: blur(12px) !important;
-    -webkit-backdrop-filter: blur(12px) !important;
-    box-shadow: 0 4px 18px rgba(180, 80, 110, 0.08) !important;
-    transition: border-color 0.2s, box-shadow 0.2s !important;
-}
-#gradio_ti:focus-within {
-    border-color: #e8859a !important;
-    box-shadow: 0 0 0 3px rgba(232, 133, 154, 0.15) !important;
-}
-#gradio_ti textarea, #gradio_ti input {
-    border: none !important;
-    background: transparent !important;
-    box-shadow: none !important;
-    font-family: inherit !important;
-    font-size: 13px !important;
-    color: #4a2030 !important;
-    padding: 13px 18px !important;
-    height: 48px !important;
-    line-height: 1.4 !important;
-}
-
-/* Custom Gradio Send Button Styling */
-#gradio_sb {
-    width: 46px !important;
-    height: 46px !important;
-    min-width: 46px !important;
-    max-width: 46px !important;
-    border-radius: 50% !important;
-    background: linear-gradient(135deg, #e8859a, #f4a5b8) !important;
-    color: #ffffff !important;
-    border: none !important;
-    box-shadow: 0 3px 12px rgba(232, 133, 154, 0.35) !important;
-    cursor: pointer !important;
-    transition: transform 0.12s, opacity 0.2s !important;
-    display: flex !important;
-    align-items: center !important;
-    justify-content: center !important;
-    font-weight: bold !important;
-    font-size: 14px !important;
-}
-#gradio_sb:active {
-    transform: scale(0.92) !important;
-}
-"""
-
-# ---------------------------------------------------------------------------
-# Inline HTML (Web Interface Overlay & Rendering Engines)
-# ---------------------------------------------------------------------------
-HTML_PAGE = r"""
-<div id="c"></div>
-
-<div id="load">thinking...</div>
-<div id="err"></div>
-<div id="info"></div>
-
-<div id="thinkDot"><div class="tdot"></div><div class="tdot"></div><div class="tdot"></div></div>
-<div id="speakDot"><div class="sdot"></div><div class="sdot"></div><div class="sdot"></div><div class="sdot"></div></div>
-
-<style>
-/* Reset and core positions */
-#c { position: fixed; top: 0; left: 0; width: 100vw; height: 100vh; pointer-events: auto; z-index: 1; }
-#c canvas { display: block; width: 100%; height: 100%; }
-
-/* Alerts and Status UI */
-#load { position: fixed; top: env(safe-area-inset-top, 12px); left: 50%; transform: translateX(-50%); background: rgba(255,240,245,.85); padding: 7px 18px; border-radius: 20px; font-size: 11px; color: #e8859a; z-index: 25; backdrop-filter: blur(12px); opacity: 0; transition: opacity .25s; pointer-events: none; white-space: nowrap; box-shadow: 0 2px 16px rgba(180,80,110,.10); letter-spacing: .02em; }
-#load.on { opacity: 1; }
-#err { position: fixed; top: env(safe-area-inset-top, 12px); left: 12px; right: 12px; background: rgba(200,40,60,.92); color: #fff; padding: 10px 16px; border-radius: 16px; font-size: 12px; z-index: 60; display: none; text-align: center; backdrop-filter: blur(8px); }
-#info { position: fixed; top: env(safe-area-inset-top, 12px); left: 12px; right: 12px; background: rgba(255,240,245,.85); color: #e8859a; padding: 8px 16px; border-radius: 16px; font-size: 11px; z-index: 59; display: none; text-align: center; backdrop-filter: blur(10px); box-shadow: 0 2px 16px rgba(180,80,110,.10); }
-
-/* Animation Overlays */
-#speakDot { position: fixed; bottom: calc(78px + env(safe-area-inset-bottom, 0px)); left: 50%; transform: translateX(-50%); display: flex; gap: 4px; z-index: 29; opacity: 0; transition: opacity .3s; }
-#speakDot.on { opacity: 1; }
-.sdot { width: 4px; height: 14px; border-radius: 2px; background: #e8859a; animation: sdotPulse .55s infinite alternate; }
-.sdot:nth-child(2) { animation-delay: .12s; height: 18px; }
-.sdot:nth-child(3) { animation-delay: .24s; height: 12px; }
-.sdot:nth-child(4) { animation-delay: .36s; height: 16px; }
-@keyframes sdotPulse { 0% { transform: scaleY(.4); opacity: .5; } 100% { transform: scaleY(1); opacity: 1; } }
-
-#thinkDot { position: fixed; bottom: calc(78px + env(safe-area-inset-bottom, 0px)); left: 50%; transform: translateX(-50%); display: flex; gap: 6px; z-index: 29; opacity: 0; transition: opacity .3s; }
-#thinkDot.on { opacity: 1; }
-.tdot { width: 6px; height: 6px; border-radius: 50%; background: #e8859a; animation: tdotBounce .7s infinite; }
-.tdot:nth-child(2) { animation-delay: .15s; }
-.tdot:nth-child(3) { animation-delay: .3s; }
-@keyframes tdotBounce { 0%,80%,100% { transform: translateY(0); opacity: .4; } 40% { transform: translateY(-10px); opacity: 1; } }
-</style>
-
-<script type="importmap">
-{ "imports": {
-  "three": "https://esm.sh/three@0.160.0",
-  "three/addons/": "https://esm.sh/three@0.160.0/examples/jsm/",
-  "@pixiv/three-vrm": "https://esm.sh/@pixiv/three-vrm@3.3.4?deps=three@0.160.0",
-  "@pixiv/three-vrm-animation": "https://esm.sh/@pixiv/three-vrm-animation@3.3.4?deps=three@0.160.0,@pixiv/three-vrm@3.3.4"
-} }
-</script>
-
-<script type="module">
-import * as THREE from 'three';
-import { GLTFLoader } from 'three/addons/loaders/GLTFLoader.js';
-import { OrbitControls } from 'three/addons/controls/OrbitControls.js';
-import { VRMLoaderPlugin, VRMUtils } from '@pixiv/three-vrm';
-import { VRMAnimationLoaderPlugin, createVRMAnimationClip } from '@pixiv/three-vrm-animation';
-
-/* ───────────── CONSTANTS & STATES ───────────── */
-const isMobile = /Mobi|Android|iPhone|iPad/i.test(navigator.userAgent);
-const VISEMES = ['aa','ih','ou','ee','oh','a','i','u','e','o'];
-const EXPR_NAMES = [
-  'happy','sad','angry','surprised','relaxed','neutral','fun','joy','sorrow','blink','blinkLeft','blinkRight',
-  'lookUp','lookDown','lookLeft','lookRight','aa','ih','ou','ee','oh'
-];
-const FALLBACK_VRMAS = ['neutral2.vrma','neutral3.vrma','neutral4.vrma','neutral_idle.vrma','neutral_idle2.vrma'];
-
-const scene = new THREE.Scene();
-scene.background = new THREE.Color(0xfff5f5);
-
-const camera = new THREE.PerspectiveCamera(40, window.innerWidth/window.innerHeight, 0.01, 100);
-camera.position.set(0, 1.4, 2.0);
-
-const renderer = new THREE.WebGLRenderer({ antialias: !isMobile, powerPreference: 'high-performance', alpha: true });
-renderer.setPixelRatio(Math.min(window.devicePixelRatio, isMobile ? 1.5 : 2));
-renderer.setSize(window.innerWidth, window.innerHeight);
-renderer.outputColorSpace = THREE.SRGBColorSpace;
-renderer.toneMapping = THREE.ACESFilmicToneMapping;
-renderer.toneMappingExposure = 1.15;
-renderer.shadowMap.enabled = true;
-renderer.shadowMap.type = THREE.PCFSoftShadowMap;
-document.getElementById('c').appendChild(renderer.domElement);
-
-const orbit = new OrbitControls(camera, renderer.domElement);
-orbit.target.set(0, 1.3, 0);
-orbit.enableDamping = true;
-orbit.dampingFactor = 0.08;
-orbit.minDistance = 0.3;
-orbit.maxDistance = 10;
-orbit.maxPolarAngle = Math.PI * 0.85;
-
-/* Prevent input hijack */
-renderer.domElement.addEventListener('pointerdown', e => {
-  const t = e.target;
-  if(t.tagName === 'INPUT' || t.tagName === 'SELECT' || t.tagName === 'TEXTAREA') return;
-});
-
-window.addEventListener('resize', () => {
-  camera.aspect = window.innerWidth / window.innerHeight;
-  camera.updateProjectionMatrix();
-  renderer.setSize(window.innerWidth, window.innerHeight);
-});
-
-/* ───────────── LIGHTING ───────────── */
-scene.add(new THREE.AmbientLight(0xfff4e8, 0.5));
-scene.add(new THREE.HemisphereLight(0xffeef2, 0x303040, 0.7));
-
-const keyL = new THREE.DirectionalLight(0xfff2e0, 1.6);
-keyL.position.set(3, 4, 3);
-keyL.castShadow = true;
-keyL.shadow.mapSize.set(isMobile ? 1024 : 2048, isMobile ? 1024 : 2048);
-keyL.shadow.bias = -0.0003;
-scene.add(keyL);
-
-const floor = new THREE.Mesh(
-  new THREE.PlaneGeometry(15, 15),
-  new THREE.ShadowMaterial({ opacity: 0.18 })
-);
-floor.rotation.x = -Math.PI/2;
-floor.receiveShadow = true;
-scene.add(floor);
-
-/* ───────────── SYSTEM STATES ───────────── */
-let vrm = null, vrmGroundY = 0;
-let mixer = null, vrmaAction = null;
-let vrmaFiles = {}, vrmaNames = [];
-let proceduralMotion = 'idle';
-let speaking = false, speechActive = false;
-let lipSmoothingFactor = 0.3; // Realistic vocal lip smoothing
-let targetVisemes = {}; VISEMES.forEach(v => targetVisemes[v] = 0);
-let currentVisemes = {}; VISEMES.forEach(v => currentVisemes[v] = 0);
-let exprCur = {}, exprTgt = {};
-let exprAlias = {};
-let blinkT = 0, nextBlink = 2 + Math.random()*3, blinkV = 0;
-let shouldFallbackToNeutral = false;
-let vrmaLoopCount = 0;
-let firstVrmaLoaded = false;
-let vrmLoadedOk = false;
-
-/* JSZip setup */
-let JSZip = null;
-async function ensureJSZip(){
-  if(JSZip) return JSZip;
-  return new Promise((resolve, reject) => {
-    const s = document.createElement('script');
-    s.src = 'https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.1/jszip.min.js';
-    s.onload = () => { JSZip = window.JSZip; resolve(JSZip); };
-    s.onerror = reject;
-    document.head.appendChild(s);
-  });
-}
-
-const gltfLoader = new GLTFLoader();
-gltfLoader.register(p => new VRMLoaderPlugin(p));
-gltfLoader.register(p => new VRMAnimationLoaderPlugin(p));
-
-/* ───────────── FETCH FAILSAFE FOR GRADIO SPACES ───────────── */
-async function fetchWithFallback(filename, type) {
-  const relativePath = type === 'model' ? `model/${filename}` : `animation/${filename}`;
-  // Iterates across multiple endpoints to robustly capture the local asset context
-  const urls = [
-    `/gradio_api/file=${relativePath}`,
-    `/file=${relativePath}`,
-    `/${relativePath}`
-  ];
-  for (const url of urls) {
-    try {
-      const res = await fetch(url);
-      if (res.ok) return res;
-    } catch(e) {}
-  }
-  throw new Error(`Asset fetch error for ${filename}`);
-}
-
-/* ───────────── LOADERS ───────────── */
-async function loadVrmFromUrl() {
-  setLoading(true, 'Loading character...');
-  try {
-    const res = await fetchWithFallback('Ani.vrm', 'model');
-    const blob = await res.blob();
-    const url = URL.createObjectURL(blob);
-    return new Promise((resolve, reject) => {
-      gltfLoader.load(url, gltf => {
-        URL.revokeObjectURL(url);
-        const newVrm = gltf.userData.vrm;
-        if(!newVrm){ showErr('Invalid VRM'); setLoading(false); reject(); return; }
-        try { VRMUtils.rotateVRM0(newVrm); } catch(e){}
-
-        newVrm.scene.traverse(o => {
-          if(o.isMesh){
-            o.frustumCulled = false;
-            o.castShadow = true;
-            o.receiveShadow = true;
-          }
-        });
-
-        if(vrm) { scene.remove(vrm.scene); }
-        if(mixer){ mixer.stopAllAction(); mixer = null; vrmaAction = null; }
-
-        vrm = newVrm;
-        scene.add(vrm.scene);
-        groundVrm();
-        buildExprAlias();
-
-        for(let i=0; i<6; i++) applyIdle(performance.now()*0.001, 0.95);
-        vrm.update(0.016);
-        renderer.compile(scene, camera);
-        reframe();
-
-        vrmLoadedOk = true;
-        setLoading(false);
-        showInfo('Model loaded ready.');
-        resolve();
-      }, undefined, reject);
-    });
-  } catch(e) {
-    console.error(e);
-    showErr('Failed to load local VRM model: ' + e.message);
-    setLoading(false);
-  }
-}
-
-function groundVrm(){
-  if(!vrm) return;
-  const box = new THREE.Box3().setFromObject(vrm.scene);
-  const sz = box.getSize(new THREE.Vector3());
-  const ctr = box.getCenter(new THREE.Vector3());
-  const targetH = 1.65;
-  const sc = targetH / Math.max(sz.y, 0.01);
-  vrm.scene.scale.setScalar(sc);
-
-  const box2 = new THREE.Box3().setFromObject(vrm.scene);
-  vrmGroundY = -box2.min.y;
-  const ctr2 = box2.getCenter(new THREE.Vector3());
-  vrm.scene.position.set(-ctr2.x, vrmGroundY, 0);
-}
-
-function enforceGround(dt){
-  if(!vrm) return;
-  const isVrma = proceduralMotion === 'vrma' && vrmaAction && vrmaAction.isRunning();
-  const speed = isVrma ? 3 : 10;
-  vrm.scene.position.y += (vrmGroundY - vrm.scene.position.y) * speed * dt;
-}
-
-function reframe(){
-  if(!vrm) return;
-  const headNode = bone('head');
-  if(headNode){
-    const wp = new THREE.Vector3();
-    headNode.getWorldPosition(wp);
-    orbit.target.set(wp.x, wp.y - 0.05, wp.z);
-    camera.position.set(wp.x, wp.y, wp.z + 1.2);
-  }
-  orbit.update();
-}
-
-/* ───────────── EXPRESSION MANAGEMENT ───────────── */
-function buildExprAlias(){
-  if(!vrm) return;
-  exprAlias = {};
-  const names = vrm.expressionManager?.expressions?.map(e => e.name) || [];
-  for(const target of EXPR_NAMES){
-    const found = names.find(n => n.toLowerCase() === target.toLowerCase());
-    if(found) exprAlias[target] = found;
-  }
-}
-
-function setExpressionValue(name, val){
-  if(!vrm?.expressionManager) return;
-  const alias = exprAlias[name] || name;
-  try { vrm.expressionManager.setValue(alias, val); } catch(e){}
-}
-
-function getExpressionValue(name){
-  if(!vrm?.expressionManager) return 0;
-  const alias = exprAlias[name] || name;
-  try { return vrm.expressionManager.getValue(alias) || 0; } catch(e){ return 0; }
-}
-
-/* Highly expressive 25-state emotion mapper */
-function applyEmotion(emotion){
-  for(const n of EXPR_NAMES) exprTgt[n] = 0;
-  
-  const presets = {
-    neutral: { neutral: 1 },
-    happy: { happy: 0.8 },
-    sad: { sad: 0.8, lookDown: 0.1 },
-    angry: { angry: 0.9 },
-    surprised: { surprised: 0.9, lookUp: 0.1 },
-    relaxed: { relaxed: 0.9 },
-    excited: { happy: 0.7, surprised: 0.4 },
-    bored: { sad: 0.4, lookDown: 0.3, relaxed: 0.2 },
-    embarrassed: { sad: 0.3, relaxed: 0.4, lookDown: 0.2 },
-    shy: { relaxed: 0.6, lookDown: 0.3 },
-    smug: { happy: 0.3, angry: 0.1, relaxed: 0.4 },
-    determined: { angry: 0.5, lookUp: 0.1 },
-    sleepy: { relaxed: 0.8, lookDown: 0.4 },
-    scared: { surprised: 0.7, sad: 0.3 },
-    teasing: { happy: 0.5, lookDown: 0.2 },
-    loving: { happy: 0.6, relaxed: 0.4 },
-    disgusted: { angry: 0.4, sad: 0.3 },
-    confident: { happy: 0.3, relaxed: 0.5 },
-    curious: { surprised: 0.3, relaxed: 0.3 },
-    proud: { happy: 0.5, lookUp: 0.1 },
-    shocked: { surprised: 1.0 },
-    thinking: { relaxed: 0.4, lookUp: 0.2 },
-    wink: { blink: 0.8 },
-    winkLeft: { blinkLeft: 1.0 },
-    winkRight: { blinkRight: 1.0 }
-  };
-
-  const p = presets[emotion] || presets.neutral;
-  for(const [k,v] of Object.entries(p)) {
-    exprTgt[k] = v;
-  }
-}
-
-/* ───────────── ANIMATION LOGICS (BLINK & LIP SYNC) ───────────── */
-function updateBlink(dt){
-  if(!vrm) return;
-  
-  // Turn off auto-blink dynamically when a high-intensity non-neutral expression is active
-  const isNeutralActive = (exprTgt['neutral'] || 0) > 0.8 || 
-                          (!exprTgt['happy'] && !exprTgt['sad'] && !exprTgt['angry'] && !exprTgt['surprised'] && !exprTgt['excited']);
-                          
-  if(!isNeutralActive){
-    let v = getExpressionValue('blink');
-    if(v > 0){
-      v = Math.max(0, v - 8 * dt);
-      setExpressionValue('blink', v);
-    }
-    blinkV = 0; blinkT = 0;
-    return;
-  }
-
-  blinkT += dt;
-  if(blinkT > nextBlink){
-    if(blinkV === 0) blinkV = 1;
-    const sp = 12;
-    if(blinkV === 1){
-      let v = getExpressionValue('blink');
-      v += sp*dt;
-      if(v >= 1){ v=1; blinkV=-1; }
-      setExpressionValue('blink', v);
-    } else if(blinkV === -1){
-      let v = getExpressionValue('blink');
-      v -= sp*dt;
-      if(v <= 0){ v=0; blinkV=0; blinkT=0; nextBlink=2+Math.random()*4; }
-      setExpressionValue('blink', v);
-    }
-  }
-}
-
-function updateExpressions(dt){
-  if(!vrm) return;
-  
-  // Update standard expressions
-  for(const name of EXPR_NAMES){
-    if(name.startsWith('blink') || VISEMES.includes(name)) continue;
-    const tgt = exprTgt[name] || 0;
-    let cur = exprCur[name] || 0;
-    cur += (tgt - cur) * 6 * dt;
-    exprCur[name] = cur;
-    setExpressionValue(name, cur);
-  }
-  
-  // Smooth Naturalistic Lip Sync update
-  for(const v of VISEMES){
-    let cur = currentVisemes[v] || 0;
-    const tgt = targetVisemes[v] || 0;
-    cur += (tgt - cur) * 12 * dt; // Smoothing acceleration
-    currentVisemes[v] = cur;
-    setExpressionValue(v, THREE.MathUtils.clamp(cur, 0, 1.2));
-  }
-}
-
-/* ───────────── BONE ROTATION HANDLERS ───────────── */
-const d2r = THREE.MathUtils.degToRad;
-function bone(n){ return vrm?.humanoid?.getRawBoneNode(n) || null; }
-function lerpRot(node, tx, ty, tz, s){
-  if(!node) return;
-  node.rotation.x += (d2r(tx) - node.rotation.x) * s;
-  node.rotation.y += (d2r(ty) - node.rotation.y) * s;
-  node.rotation.z += (d2r(tz) - node.rotation.z) * s;
-}
-
-/* ───────────── IDLE CALCULATIONS ───────────── */
-const IL = 6.0;
-function smoothstep(a,b,f){ f=Math.max(0,Math.min(1,f)); f=f*f*(3-2*f); return a+(b-a)*f; }
-function kf(ts,vs,t){ let i=0; while(i<ts.length-1&&t>ts[i+1])i++; const t0=ts[i],t1=ts[Math.min(i+1,ts.length-1)]; const v0=vs[i],v1=vs[Math.min(i+1,vs.length-1)]; if(t1<=t0)return v1; return smoothstep(v0,v1,(t-t0)/(t1-t0)); }
-
-const BT=[0,1.2,2.4,3.6,4.8,6], BV=[0,.9,.4,1,.2,0];
-const ST=[0,1.5,3,4.5,6], SV=[0,1,0,-1,0];
-const WT=[0,2,4,6], WV=[0,.8,-.8,0];
-const MT=[0,.8,1.6,2.4,3.2,4,4.8,5.6,6], MV=[0,.4,-.3,.2,-.4,.3,-.2,.4,0];
-
-function applyIdle(t, blend=0.12){
-  if(!vrm) return;
-  const lt = t % IL;
-  const br=kf(BT,BV,lt), sh=kf(ST,SV,lt), sw=kf(WT,WV,lt), mi=kf(MT,MV,lt);
-  lerpRot(bone('hips'), -1+br*.4, sw*.5, sh*.6, blend);
-  lerpRot(bone('spine'), 2+br*1.2, 0, -sh*.8, blend);
-  lerpRot(bone('chest'), 1+br*1.6, 0, sh*.3, blend);
-  lerpRot(bone('upperChest'), br*.8, 0, 0, blend);
-  lerpRot(bone('leftUpperLeg'), -2, 0, 3+sh*.6, blend);
-  lerpRot(bone('rightUpperLeg'), -2, 0, -3-sh*.6, blend);
-  lerpRot(bone('leftLowerLeg'), 4, 0, 0, blend);
-  lerpRot(bone('rightLowerLeg'), 4, 0, 0, blend);
-  lerpRot(bone('leftFoot'), -2, 0, -sh*.5, blend);
-  lerpRot(bone('rightFoot'), -2, 0, sh*.5, blend);
-  lerpRot(bone('leftUpperArm'), 0, 0, -42+br*1.5, blend);
-  lerpRot(bone('rightUpperArm'), 0, 0, 42-br*1.5, blend);
-  lerpRot(bone('leftLowerArm'), 15+mi*2, 10, 0, blend);
-  lerpRot(bone('rightLowerArm'), 15-mi*2, -10, 0, blend);
-  lerpRot(bone('neck'), 1+sw*.3, sw*.4, 0, blend);
-  lerpRot(bone('head'), -1-sw*.2, mi*.5, 0, blend);
-}
-
-function applyProceduralMotion(t, dt){
-  if(!vrm || proceduralMotion === 'vrma') return;
-  applyIdle(t, 0.08);
-}
-
-/* ───────────── VRMA PLAYER ENGINE ───────────── */
-function loadVrmaFromBlob(blob, name){
-  if(!vrm) return;
-  const url = URL.createObjectURL(blob);
-  gltfLoader.load(url, gltf => {
-    URL.revokeObjectURL(url);
-    const anims = gltf.userData.vrmAnimations;
-    if(!anims?.length) return;
-
-    const clip = createVRMAnimationClip(anims[0], vrm);
-    if(!mixer){
-      mixer = new THREE.AnimationMixer(vrm.scene);
-      mixer.addEventListener('loop', e => {
-        if(vrmaAction && e.action === vrmaAction){
-          vrmaLoopCount++;
-          if(shouldFallbackToNeutral && vrmaLoopCount >= 1){
-            shouldFallbackToNeutral = false;
-            playDefaultNeutralVrma();
-          } else if(!FALLBACK_VRMAS.some(f => vrmaAction.getClip().name.toLowerCase().includes(f.toLowerCase().replace('.vrma',''))) && vrmaLoopCount >= 1){
-            playDefaultNeutralVrma();
-          }
-        }
-      });
-    }
-
-    const next = mixer.clipAction(clip);
-    next.reset();
-    next.timeScale = 1;
-    next.setLoop(THREE.LoopRepeat, Infinity);
-    next.clampWhenFinished = false;
-
-    if(vrmaAction){
-      vrmaAction.crossFadeTo(next, 0.35, true);
-      next.play();
-    } else {
-      next.play();
-    }
-    vrmaAction = next;
-    proceduralMotion = 'vrma';
-    vrmaLoopCount = 0;
-
-    setTimeout(() => {
-      if(vrm){
-        vrm.scene.updateMatrixWorld(true);
-        const box = new THREE.Box3().setFromObject(vrm.scene);
-        vrmGroundY = -box.min.y;
-      }
-    }, 150);
-
-    if(!firstVrmaLoaded){
-      firstVrmaLoaded = true;
-      setTimeout(reframe, 400);
-    }
-  }, null, err => {
-    URL.revokeObjectURL(url);
-    console.error('VRMA load failed:', name, err);
-  });
-}
-
-function playDefaultNeutralVrma(){
-  const targets = ['neutral2.vrma','neutral3.vrma','neutral_idle.vrma','neutral4.vrma'];
-  for(const f of targets){
-    const match = Object.keys(vrmaFiles).find(k => k.toLowerCase() === f.toLowerCase());
-    if(match){ loadVrmaFromBlob(vrmaFiles[match], match); return; }
-  }
-  proceduralMotion = 'idle';
-}
-
-function playVrmaByName(name){
-  const blob = vrmaFiles[name];
-  if(blob) {
-    loadVrmaFromBlob(blob, name);
-  } else {
-    playDefaultNeutralVrma();
-  }
-}
-
-/* ───────────── AUTO-LOAD ANIMATION PACKS ───────────── */
-async function autoLoadAnimations(){
-  setLoading(true, 'Loading animations...');
-  try {
-    const Zip = await ensureJSZip();
-    const res = await fetchWithFallback('all_vrma.zip', 'animation');
-    const blob = await res.blob();
-    const zip = await Zip.loadAsync(blob);
-
-    const promises = [];
-    zip.forEach((path, entry) => {
-      if(!entry.dir && path.toLowerCase().endsWith('.vrma')){
-        const name = path.split('/').pop();
-        promises.push(entry.async('blob').then(b => {
-          vrmaFiles[name] = b;
-          vrmaNames.push(name);
-        }));
-      }
-    });
-    await Promise.all(promises);
-    showInfo(`${vrmaNames.length} animations loaded`);
-    if(vrm) playDefaultNeutralVrma();
-  } catch(e){
-    console.warn('Fallback animation loader triggered:', e.message);
-    try {
-      const Zip = await ensureJSZip();
-      const res = await fetch('https://raw.githubusercontent.com/unsloth/vrm/main/all_vrma.zip');
-      if(!res.ok) throw new Error('Fallback failed');
-      const blob = await res.blob();
-      const zip = await Zip.loadAsync(blob);
-      const promises = [];
-      zip.forEach((path, entry) => {
-        if(!entry.dir && path.toLowerCase().endsWith('.vrma')){
-          const name = path.split('/').pop();
-          promises.push(entry.async('blob').then(b => {
-            vrmaFiles[name] = b;
-            vrmaNames.push(name);
-          }));
+        # এনভায়রনমেন্ট ডেটা অর্গানাইজ করা
+        specs = {
+            "OS Platform": platform.platform(),
+            "Total vCPU Cores": f"{cpu_count} Cores",
+            "Current CPU Usage": f"{cpu_usage}%",
+            "Total RAM": f"{memory.total / (1024 ** 3):.2f} GB",
+            "Available RAM": f"{memory.available / (1024 ** 3):.2f} GB",
+            "RAM Usage": f"{memory.percent}%",
+            "Container Storage Total": f"{disk_total:.2f} GB",
+            "Container Storage Free": f"{disk_free:.2f} GB"
         }
-      });
-      await Promise.all(promises);
-      showInfo(`${vrmaNames.length} fallback animations ready`);
-      if(vrm) playDefaultNeutralVrma();
-    } catch(err2) {
-      console.error('Critical fallback failure:', err2);
-    }
-  }
-  setLoading(false);
-}
-
-/* ───────────── SYSTEM AUDIO ENGINE (LIP SYNC) ───────────── */
-let audioCtx = null, analyser = null, dataArray = null, audioObj = null, currentAudioUrl = null;
-
-function initAudioCtx(){
-  if(!audioCtx){
-    audioCtx = new (window.AudioContext || window.webkitAudioContext)();
-    analyser = audioCtx.createAnalyser();
-    analyser.fftSize = 256;
-    dataArray = new Uint8Array(analyser.frequencyBinCount);
-  }
-}
-
-function playTTSAudio(blob){
-  initAudioCtx();
-  if(audioCtx?.state === 'suspended') audioCtx.resume();
-  if(currentAudioUrl){ URL.revokeObjectURL(currentAudioUrl); currentAudioUrl = null; }
-  if(audioObj){ audioObj.pause(); audioObj.src=''; audioObj=null; }
-
-  const url = URL.createObjectURL(blob);
-  currentAudioUrl = url;
-  audioObj = new Audio(url);
-  audioObj.crossOrigin = 'anonymous';
-
-  const src = audioCtx.createMediaElementSource(audioObj);
-  src.connect(analyser);
-  analyser.connect(audioCtx.destination);
-
-  speechActive = true; speaking = true;
-  document.getElementById('thinkDot').classList.remove('on');
-  document.getElementById('speakDot').classList.add('on');
-
-  audioObj.play().catch(e => console.warn('Browser auto-play blocked:', e));
-
-  audioObj.onended = () => {
-    speechActive = false; speaking = false;
-    document.getElementById('speakDot').classList.remove('on');
-    if(currentAudioUrl){ URL.revokeObjectURL(currentAudioUrl); currentAudioUrl=null; }
-    if(vrm) VISEMES.forEach(v => setExpressionValue(v, 0));
-    applyEmotion('neutral');
-    shouldFallbackToNeutral = true;
-  };
-}
-
-window.addEventListener('click', () => {
-  if(audioCtx?.state === 'suspended') audioCtx.resume();
-}, { once: false });
-
-/* ───────────── POINTER COORDINATES ───────────── */
-const pRaw={x:0,y:0}, pSmooth={x:0,y:0};
-let hasPointer = false;
-window.addEventListener('pointermove', e => {
-  if(['INPUT','SELECT','TEXTAREA'].includes(e.target.tagName)) return;
-  pRaw.x = (e.clientX/window.innerWidth)*2-1;
-  pRaw.y = -(e.clientY/window.innerHeight)*2+1;
-  hasPointer = true;
-}, { passive: true });
-
-/* ───────────── INTERACTION INTERCEPT (GRADIO HANDLER) ───────────── */
-window.handleAIResponse = (jsonData) => {
-  if(!jsonData) return;
-  try {
-    const res = JSON.parse(jsonData);
-    setLoading(false);
-    document.getElementById('thinkDot').classList.remove('on');
+        return specs
+    except Exception as e:
+        return {"Error": str(e)}
 
-    if(res.text && res.audio_b64){
-      const binary = atob(res.audio_b64);
-      const array = new Uint8Array(binary.length);
-      for(let i=0; i<binary.length; i++){
-        array[i] = binary.charCodeAt(i);
-      }
-      const blob = new Blob([array], { type: 'audio/mpeg' });
-      playTTSAudio(blob);
-    }
+# Gradio ইন্টারফেস তৈরি
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🖥️ Hugging Face ZeroGPU: CPU & Space Monitor")
+    gr.Markdown("এই ড্যাশবোর্ডটি ZeroGPU এনভায়রনমেন্টের ব্যাকগ্রাউন্ড CPU এবং মেমরি স্ট্যাটাস প্রদর্শন করে।")
     
-    if(res.expressions){
-      applyEmotion(res.expressions);
-    }
-
-    if(res.vrma && vrmaFiles[res.vrma]){
-      playVrmaByName(res.vrma);
-    } else {
-      playDefaultNeutralVrma();
-    }
-  } catch(e) {
-    console.error('JSON sync execution failure:', e);
-    showErr('Payload sync failed');
-    setLoading(false);
-    document.getElementById('thinkDot').classList.remove('on');
-  }
-};
-
-/* Hook into UI submissions to display immediate frontend feedback */
-function setupInputWatchers() {
-  const checkInterval = setInterval(() => {
-    const inputEl = document.querySelector("#gradio_ti textarea");
-    const btnEl = document.querySelector("#gradio_sb");
+    with gr.Row():
+        btn_refresh = gr.Button("🔄 Refresh System Specs", variant="primary")
     
-    if(inputEl && btnEl) {
-      clearInterval(checkInterval);
-      const setThinking = () => {
-        setLoading(true, "thinking...");
-        document.getElementById('thinkDot').classList.add('on');
-      };
-      btnEl.addEventListener("click", setThinking);
-      inputEl.addEventListener("keydown", (e) => {
-        if(e.key === "Enter" && !e.shiftKey) {
-          setThinking();
-        }
-      });
-    }
-  }, 100);
-}
-
-/* ───────────── STATUS HELPERS ───────────── */
-function setLoading(on, text='thinking...'){
-  const el = document.getElementById('load');
-  if(on){ el.textContent = text; el.classList.add('on'); }
-  else { el.classList.remove('on'); }
-}
-
-function showErr(msg){
-  const el = document.getElementById('err');
-  el.textContent = msg; el.style.display = 'block';
-  setTimeout(() => el.style.display = 'none', 4000);
-}
-
-function showInfo(msg, delay=2500){
-  const el = document.getElementById('info');
-  el.textContent = msg; el.style.display = 'block';
-  setTimeout(() => el.style.display = 'none', delay);
-}
-
-/* ───────────── MAIN ANIMATION RENDER LOOP ───────────── */
-const clock = new THREE.Clock();
-const gazeTarget = new THREE.Vector3();
-
-function animate(){
-  requestAnimationFrame(animate);
-  const dt = Math.min(clock.getDelta(), 0.1);
-  const t = clock.getElapsedTime();
-
-  orbit.update();
-
-  if(vrm){
-    /* Smooth Gaze Tracking */
-    if(hasPointer){
-      pSmooth.x += (pRaw.x - pSmooth.x) * 4 * dt;
-      pSmooth.y += (pRaw.y - pSmooth.y) * 4 * dt;
-      gazeTarget.set(pSmooth.x * 1.5, pSmooth.y + 1.3, 2);
-      if(vrm.lookAt) vrm.lookAt.lookAt(gazeTarget);
-    }
-
-    /* Natural Bandpass Lip Sync Audio Extraction */
-    if(speechActive && analyser && dataArray){
-      analyser.getByteFrequencyData(dataArray);
-      
-      let bass = 0, mid = 0, high = 0;
-      for (let i = 0; i < 4; i++) bass += dataArray[i];      // Low bass vocals
-      for (let i = 4; i < 16; i++) mid += dataArray[i];      // Conversational mids
-      for (let i = 16; i < 32; i++) high += dataArray[i];    // High sibilants
-      
-      bass = (bass / 4) / 255;
-      mid = (mid / 12) / 255;
-      high = (high / 16) / 255;
-      
-      const ampBass = Math.min(bass * 2.5, 1.0);
-      const ampMid = Math.min(mid * 2.5, 1.0);
-      const ampHigh = Math.min(high * 2.5, 1.0);
-      
-      // Dynamic frequency-to-viseme routing
-      targetVisemes.aa = ampMid * 1.3;
-      targetVisemes.ee = ampHigh * 0.9;
-      targetVisemes.ih = ampHigh * 0.6;
-      targetVisemes.oh = ampBass * 1.1;
-      targetVisemes.ou = ampBass * 0.8;
-      
-      // Mirror assignments
-      targetVisemes.a = targetVisemes.aa;
-      targetVisemes.e = targetVisemes.ee;
-      targetVisemes.i = targetVisemes.ih;
-      targetVisemes.o = targetVisemes.oh;
-      targetVisemes.u = targetVisemes.ou;
-    } else {
-      VISEMES.forEach(v => targetVisemes[v] = 0);
-    }
-
-    applyProceduralMotion(t, dt);
-    if(mixer) mixer.update(dt);
-    enforceGround(dt);
-    updateBlink(dt);
-    updateExpressions(dt);
-    vrm.update(dt);
-  }
-
-  renderer.render(scene, camera);
-}
-
-/* ───────────── SYSTEM ENTRYPOINT ───────────── */
-async function init(){
-  await loadVrmFromUrl();
-  await autoLoadAnimations();
-  setupInputWatchers();
-  animate();
-}
-
-init();
-</script>
-"""
-
-# ---------------------------------------------------------------------------
-# Gradio Application Definition
-# ---------------------------------------------------------------------------
-# Title parameter retained; Blocks level custom styles refactored into demo.launch()
-with gr.Blocks(title="AI VRM Companion") as demo:
-    # 98% Custom HTML Canvas container
-    gr.HTML(HTML_PAGE, elem_id="custom_html_overlay")
-    
-    # 2% Standard Gradio Interactive Controls
-    with gr.Row(elem_id="gradio_bar"):
-        text_input = gr.Textbox(
-            placeholder="Say something sweet...", 
-            show_label=False, 
-            container=False, 
-            elem_id="gradio_ti"
-        )
-        send_btn = gr.Button("Send", elem_id="gradio_sb")
-        
-    # Invisible channel to synchronize Python generation and Javascript updates
-    hidden_json_output = gr.Textbox(visible=False, elem_id="hidden_json_output")
+    with gr.Row():
+        # JSON ফরম্যাটে সমস্ত ডিটেইলস দেখানোর জন্য
+        output_json = gr.JSON(label="System Hardware & Resource Specifications")
 
-    # Wire actions securely
-    interaction_trigger = send_btn.click(
-        fn=process_chat,
-        inputs=[text_input],
-        outputs=[hidden_json_output]
-    ).then(
-        fn=None,
-        inputs=[hidden_json_output],
-        js="(jsonData) => { window.handleAIResponse(jsonData); return []; }"
-    )
+    # বাটন ক্লিকের অ্যাকশন ডিফাইন করা
+    btn_refresh.click(fn=get_system_specs, inputs=None, outputs=output_json)
     
-    submission_trigger = text_input.submit(
-        fn=process_chat,
-        inputs=[text_input],
-        outputs=[hidden_json_output]
-    ).then(
-        fn=None,
-        inputs=[hidden_json_output],
-        js="(jsonData) => { window.handleAIResponse(jsonData); return []; }"
-    )
+    # অ্যাপ লোড হওয়ার সাথে সাথে ডেটা দেখানোর জন্য
+    demo.load(fn=get_system_specs, inputs=None, outputs=output_json)
 
-# ---------------------------------------------------------------------------
-# Gradio Launch Execution (Port binding and routing managed automatically)
-# ---------------------------------------------------------------------------
+# অ্যাপ লঞ্চ করা
 if __name__ == "__main__":
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        css=CSS_STYLES,              # Custom CSS rules applied here directly
-        allowed_paths=[MODEL_DIR, ANIM_DIR] # Access rights given dynamically to Gradio's internal engine
-    )
+    demo.launch()