app.py

####################################################################################################
### PART 1: Imports & Basic Utilities
####################################################################################################
import sys
from pathlib import Path
import uuid
import tempfile
import subprocess
import torch
import torch.nn.functional as F
import torchaudio
import os
from typing import Any
import time
from contextlib import contextmanager
from gradio.helpers import create_examples 

@contextmanager
def timer(name: str):
    start = time.time()
    print(f"{name}...")
    yield
    print(f"  -> {name} completed in {time.time() - start:.2f} sec")

def _coerce_audio_path(audio_path: Any) -> str:
    # Common Gradio case: tuple where first item is the filepath
    if isinstance(audio_path, tuple) and len(audio_path) > 0:
        audio_path = audio_path[0]

    # Some gradio versions pass a dict-like object
    if isinstance(audio_path, dict):
        # common keys: "name", "path"
        audio_path = audio_path.get("name") or audio_path.get("path")

    # pathlib.Path etc.
    if not isinstance(audio_path, (str, bytes, os.PathLike)):
        raise TypeError(f"audio_path must be a path-like, got {type(audio_path)}: {audio_path}")

    return os.fspath(audio_path)


####################################################################################################
### PART 2: Audio Extraction & Matching Utilities
####################################################################################################
def extract_audio_wav_ffmpeg(video_path: str, target_sr: int = 48000) -> str | None:
    """
    Extract audio from a video into a temp WAV (mono, target_sr).
    Returns path, or None if the video has no audio stream.
    """
    out_path = tempfile.NamedTemporaryFile(suffix=".wav", delete=False).name

    # Check if there's an audio stream
    probe_cmd = [
        "ffprobe", "-v", "error",
        "-select_streams", "a:0",
        "-show_entries", "stream=codec_type",
        "-of", "default=nw=1:nk=1",
        video_path,
    ]
    try:
        out = subprocess.check_output(probe_cmd).decode("utf-8").strip()
        if not out:
            return None
    except subprocess.CalledProcessError:
        return None

    # Extract + resample + mono
    cmd = [
        "ffmpeg", "-y", "-v", "error",
        "-i", video_path,
        "-vn",
        "-ac", "1",
        "-ar", str(int(target_sr)),
        "-c:a", "pcm_s16le",
        out_path
    ]
    subprocess.check_call(cmd)
    return out_path

def match_audio_to_duration(
    audio_path: str,
    target_seconds: float,
    target_sr: int = 48000,
    to_mono: bool = True,
    pad_mode: str = "silence",  # "silence" | "repeat"
    device: str = "cuda",
):
    """
    Load audio, resample, (optionally) mono, then trim/pad to exactly target_seconds.
    Returns: (waveform[T] or [1,T], sr)
    """
    audio_path = _coerce_audio_path(audio_path)

    wav, sr = torchaudio.load(audio_path)  # [C, T] float32 CPU

    # Resample to target_sr (recommended so duration math is stable)
    if sr != target_sr:
        wav = torchaudio.functional.resample(wav, sr, target_sr)
        sr = target_sr

    # Mono (common expectation; if your model supports stereo, set to_mono=False)
    if to_mono and wav.shape[0] > 1:
        wav = wav.mean(dim=0, keepdim=True)  # [1, T]

    # Exact target length in samples
    target_len = int(round(target_seconds * sr))
    cur_len = wav.shape[-1]

    if cur_len > target_len:
        wav = wav[..., :target_len]
    elif cur_len < target_len:
        pad_len = target_len - cur_len
        if pad_mode == "repeat" and cur_len > 0:
            # Repeat then cut to exact length
            reps = (target_len + cur_len - 1) // cur_len
            wav = wav.repeat(1, reps)[..., :target_len]
        else:
            # Silence pad
            wav = F.pad(wav, (0, pad_len))

    # move to device
    wav = wav.to(device, non_blocking=True)
    return wav, sr

def sh(cmd): subprocess.check_call(cmd, shell=True)


####################################################################################################
### PART 3: LTX Pipeline Imports & Constants
####################################################################################################
# Add packages to Python path
current_dir = Path(__file__).parent
sys.path.insert(0, str(current_dir / "packages" / "ltx-pipelines" / "src"))
sys.path.insert(0, str(current_dir / "packages" / "ltx-core" / "src"))

import spaces
import flash_attn_interface
import time
import gradio as gr
import numpy as np
import random
import torch
from typing import Optional
from pathlib import Path
import torchaudio
from huggingface_hub import hf_hub_download, snapshot_download
from ltx_pipelines.distilled import DistilledPipeline
from ltx_core.model.video_vae import TilingConfig
from ltx_core.model.audio_vae.ops import AudioProcessor
from ltx_core.loader.primitives import LoraPathStrengthAndSDOps
from ltx_core.loader.sd_ops import LTXV_LORA_COMFY_RENAMING_MAP
from ltx_pipelines.utils.constants import (
    DEFAULT_SEED,
    DEFAULT_1_STAGE_HEIGHT,
    DEFAULT_1_STAGE_WIDTH ,
    DEFAULT_NUM_FRAMES,
    DEFAULT_FRAME_RATE,
    DEFAULT_LORA_STRENGTH,
)
from ltx_core.loader.single_gpu_model_builder import enable_only_lora
from ltx_core.model.audio_vae import decode_audio
from ltx_core.model.audio_vae import encode_audio
from PIL import Image

MAX_SEED = np.iinfo(np.int32).max
# Import from public LTX-2 package
# Install with: pip install git+https://github.com/Lightricks/LTX-2.git
from ltx_pipelines.utils import ModelLedger
from ltx_pipelines.utils.helpers import generate_enhanced_prompt
import imageio
import cv2

# HuggingFace Hub defaults
DEFAULT_REPO_ID = "Lightricks/LTX-2"
DEFAULT_GEMMA_REPO_ID = "unsloth/gemma-3-12b-it-qat-bnb-4bit"
DEFAULT_CHECKPOINT_FILENAME = "ltx-2-19b-dev.safetensors"


####################################################################################################
### PART 4: Download Helpers
####################################################################################################
def get_hub_or_local_checkpoint(repo_id: str, filename: str):
    """Download from HuggingFace Hub."""
    print(f"Downloading {filename} from {repo_id}...")
    ckpt_path = hf_hub_download(repo_id=repo_id, filename=filename)
    print(f"Downloaded to {ckpt_path}")
    return ckpt_path

def download_gemma_model(repo_id: str):
    """Download the full Gemma model directory."""
    print(f"Downloading Gemma model from {repo_id}...")
    local_dir = snapshot_download(repo_id=repo_id)
    print(f"Gemma model downloaded to {local_dir}")
    return local_dir


####################################################################################################
### PART 5: Text Encoder Initialization
####################################################################################################
# Initialize model ledger and text encoder at startup (load once, keep in memory)
print("=" * 80)
print("Loading Gemma Text Encoder...")
print("=" * 80)

checkpoint_path = get_hub_or_local_checkpoint(DEFAULT_REPO_ID, DEFAULT_CHECKPOINT_FILENAME)
gemma_local_path = download_gemma_model(DEFAULT_GEMMA_REPO_ID)
device = "cuda"

print(f"Initializing text encoder with:")
print(f"  checkpoint_path={checkpoint_path}")
print(f"  gemma_root={gemma_local_path}")
print(f"  device={device}")

model_ledger = ModelLedger(
    dtype=torch.bfloat16,
    device=device,
    checkpoint_path=checkpoint_path,
    gemma_root_path=DEFAULT_GEMMA_REPO_ID,
    local_files_only=False
)

# Load text encoder once and keep it in memory
text_encoder = model_ledger.text_encoder()

print("=" * 80)
print("Text encoder loaded and ready!")
print("=" * 80)

def on_lora_change(selected: str):
    # Only Detailer might need handling, but we simplified motion control out
    needs_video = selected in {"Detailer"} 
    return (
        selected,
        gr.update(visible=not needs_video, value=None if needs_video else None),
        gr.update(visible=needs_video, value=None if not needs_video else None),
    )


####################################################################################################
### PART 6: Video/Frame Utilities
####################################################################################################
def load_video_frames(video_path: str):
    """Return list of frames as numpy arrays (H,W,3) uint8."""
    frames = []
    with imageio.get_reader(video_path) as reader:
        for frame in reader:
            frames.append(frame)
    return frames

def write_video_mp4(frames_float_01, fps: float, out_path: str):
    """Write frames in float [0..1] to mp4 as uint8."""
    frames_uint8 = [(f * 255).astype(np.uint8) for f in frames_float_01]

    # PyAV backend doesn't support `quality=...`
    with imageio.get_writer(out_path, fps=fps, macro_block_size=1) as writer:
        for fr in frames_uint8:
            writer.append_data(fr)
    return out_path

import json

def probe_video_duration_seconds(video_path: str) -> float:
    """Return duration in seconds using ffprobe."""
    cmd = [
        "ffprobe", "-v", "error",
        "-select_streams", "v:0",
        "-show_entries", "format=duration",
        "-of", "json",
        video_path,
    ]
    out = subprocess.check_output(cmd).decode("utf-8")
    data = json.loads(out)
    dur = float(data["format"]["duration"])
    return dur


####################################################################################################
### PART 7: FFmpeg Utils & Frame Prep
####################################################################################################
def trim_video_to_seconds_ffmpeg(video_path: str, target_seconds: float, fps: float = None) -> str:
    """
    Trim video to [0, target_seconds]. Re-encode for accuracy & compatibility.
    If fps is provided, also normalize fps.
    Returns new temp mp4 path.
    """
    target_seconds = max(0.01, float(target_seconds))

    out_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name

    vf = []
    if fps is not None:
        vf.append(f"fps={float(fps)}")
    vf_str = ",".join(vf) if vf else None

    cmd = ["ffmpeg", "-y", "-v", "error"]

    # Accurate trim: use -t and re-encode.
    cmd += ["-i", video_path, "-t", f"{target_seconds:.6f}"]

    if vf_str:
        cmd += ["-vf", vf_str]

    # Safe default encode
    cmd += [
        "-c:v", "libx264", "-pix_fmt", "yuv420p", "-preset", "veryfast", "-crf", "18",
        "-an",  # conditioning video doesn't need audio
        out_path
    ]

    subprocess.check_call(cmd)
    return out_path

def extract_first_frame_png(video_path: str) -> str:
    """Extract first frame as png; returns png path."""
    out_path = tempfile.NamedTemporaryFile(suffix=".png", delete=False).name
    cmd = [
        "ffmpeg", "-y", "-v", "error",
        "-i", video_path,
        "-frames:v", "1",
        out_path
    ]
    subprocess.check_call(cmd)
    return out_path

def _coerce_video_path(video_path: Any) -> str:
    if isinstance(video_path, tuple) and len(video_path) > 0:
        video_path = video_path[0]
    if isinstance(video_path, dict):
        video_path = video_path.get("name") or video_path.get("path")
    if not isinstance(video_path, (str, bytes, os.PathLike)):
        raise TypeError(f"video_path must be a path-like, got {type(video_path)}: {video_path}")
    return os.fspath(video_path)


####################################################################################################
### PART 8: Prompt Encoding Logic
####################################################################################################
def encode_text_simple(text_encoder, prompt: str):
    """Simple text encoding without using pipeline_utils."""
    v_context, a_context, _ = text_encoder(prompt)
    return v_context, a_context

@spaces.GPU()
def encode_prompt(
    prompt: str,
    enhance_prompt: bool = True,
    input_image=None,   # this is now filepath (string) or None
    seed: int = 42,
    negative_prompt: str = ""
):
    start_time = time.time()
    try:
        final_prompt = prompt
        if enhance_prompt:
            final_prompt = generate_enhanced_prompt(
                text_encoder=text_encoder,
                prompt=prompt,
                image_path=input_image if input_image is not None else None,
                seed=seed,
            )

        with torch.inference_mode():
            video_context, audio_context = encode_text_simple(text_encoder, final_prompt)

        video_context_negative = None
        audio_context_negative = None
        if negative_prompt:
            video_context_negative, audio_context_negative = encode_text_simple(text_encoder, negative_prompt)

        # IMPORTANT: return tensors directly (no torch.save)
        embedding_data = {
            "video_context": video_context.detach().cpu(),
            "audio_context": audio_context.detach().cpu(),
            "prompt": final_prompt,
            "original_prompt": prompt,
        }
        if video_context_negative is not None:
            embedding_data["video_context_negative"] = video_context_negative
            embedding_data["audio_context_negative"] = audio_context_negative
            embedding_data["negative_prompt"] = negative_prompt

        elapsed_time = time.time() - start_time
        if torch.cuda.is_available():
            allocated = torch.cuda.memory_allocated() / 1024**3
            peak = torch.cuda.max_memory_allocated() / 1024**3
            status = f"✓ Encoded in {elapsed_time:.2f}s | VRAM: {allocated:.2f}GB allocated, {peak:.2f}GB peak"
        else:
            status = f"✓ Encoded in {elapsed_time:.2f}s (CPU mode)"

        return embedding_data, final_prompt, status

    except Exception as e:
        import traceback
        error_msg = f"Error: {str(e)}\n{traceback.format_exc()}"
        print(error_msg)
        return None, prompt, error_msg

# Default prompt from docstring example
DEFAULT_PROMPT = "An astronaut hatches from a fragile egg on the surface of the Moon, the shell cracking and peeling apart in gentle low-gravity motion. Fine lunar dust lifts and drifts outward with each movement, floating in slow arcs before settling back onto the ground. The astronaut pushes free in a deliberate, weightless motion, small fragments of the egg tumbling and spinning through the air. In the background, the deep darkness of space subtly shifts as stars glide with the camera's movement, emphasizing vast depth and scale. The camera performs a smooth, cinematic slow push-in, with natural parallax between the foreground dust, the astronaut, and the distant starfield. Ultra-realistic detail, physically accurate low-gravity motion, cinematic lighting, and a breath-taking, movie-like shot."


####################################################################################################
### PART 9: Pipeline Constants & Checkpoint Paths
####################################################################################################
# HuggingFace Hub defaults
DEFAULT_REPO_ID = "Lightricks/LTX-2"
DEFAULT_CHECKPOINT_FILENAME = "ltx-2-19b-dev.safetensors"
DEFAULT_DISTILLED_LORA_FILENAME = "ltx-2-19b-distilled-lora-384.safetensors"
DEFAULT_SPATIAL_UPSAMPLER_FILENAME = "ltx-2-spatial-upscaler-x2-1.0.safetensors"

def get_hub_or_local_checkpoint_pipeline(repo_id: Optional[str] = None, filename: Optional[str] = None):
    """Download from HuggingFace Hub or use local checkpoint."""
    if repo_id is None and filename is None:
        raise ValueError("Please supply at least one of `repo_id` or `filename`")

    if repo_id is not None:
        if filename is None:
            raise ValueError("If repo_id is specified, filename must also be specified.")
        print(f"Downloading {filename} from {repo_id}...")
        ckpt_path = hf_hub_download(repo_id=repo_id, filename=filename)
        print(f"Downloaded to {ckpt_path}")
    else:
        ckpt_path = filename

    return ckpt_path


# Initialize pipeline at startup
print("=" * 80)
print("Loading LTX-2 Distilled pipeline...")
print("=" * 80)

checkpoint_path = get_hub_or_local_checkpoint_pipeline(DEFAULT_REPO_ID, DEFAULT_CHECKPOINT_FILENAME)
spatial_upsampler_path = get_hub_or_local_checkpoint_pipeline(DEFAULT_REPO_ID, DEFAULT_SPATIAL_UPSAMPLER_FILENAME)

print(f"Initializing pipeline with:")
print(f"  checkpoint_path={checkpoint_path}")
print(f"  spatial_upsampler_path={spatial_upsampler_path}")

distilled_lora_path = get_hub_or_local_checkpoint_pipeline(
    DEFAULT_REPO_ID,
    DEFAULT_DISTILLED_LORA_FILENAME,
)

static_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Static",
    "ltx-2-19b-lora-camera-control-static.safetensors",
)
dolly_in_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-In",
    "ltx-2-19b-lora-camera-control-dolly-in.safetensors",
)
dolly_out_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Out",
    "ltx-2-19b-lora-camera-control-dolly-out.safetensors",
)
dolly_left_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Left",
    "ltx-2-19b-lora-camera-control-dolly-left.safetensors",
)
dolly_right_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Right",
    "ltx-2-19b-lora-camera-control-dolly-right.safetensors",
)
jib_down_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Down",
    "ltx-2-19b-lora-camera-control-jib-down.safetensors",
)
jib_up_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up",
    "ltx-2-19b-lora-camera-control-jib-up.safetensors",
)

detailer_lora_path = get_hub_or_local_checkpoint_pipeline(
    "Lightricks/LTX-2-19b-IC-LoRA-Detailer",
    "ltx-2-19b-ic-lora-detailer.safetensors",
)


####################################################################################################
### PART 10: LoRA Setup & Configuration
####################################################################################################
# Load distilled LoRA as a regular LoRA
loras = [
    # --- fused / base behavior ---
    LoraPathStrengthAndSDOps(
        path=distilled_lora_path,
        strength=0.6,
        sd_ops=LTXV_LORA_COMFY_RENAMING_MAP,
    ),
    LoraPathStrengthAndSDOps(static_lora_path,      DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(detailer_lora_path,    DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(dolly_in_lora_path,    DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(dolly_out_lora_path,   DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(dolly_left_lora_path,  DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(dolly_right_lora_path, DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(jib_down_lora_path,    DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
    LoraPathStrengthAndSDOps(jib_up_lora_path,      DEFAULT_LORA_STRENGTH, LTXV_LORA_COMFY_RENAMING_MAP),
]

# Runtime-toggle LoRAs (exclude fused distilled at index 0)
VISIBLE_RUNTIME_LORA_CHOICES = [
    ("No LoRA", -1),
    ("Static", 0),
    ("Detailer", 1),
    ("Zoom In", 2),
    ("Zoom Out", 3),
    ("Slide Left", 4),
    ("Slide Right", 5),
    ("Slide Down", 6),
    ("Slide Up", 7),
]

RUNTIME_LORA_CHOICES = [
    ("No LoRA", -1),
    ("Static", 0),
    ("Detailer", 1),
    ("Zoom In", 2),
    ("Zoom Out", 3),
    ("Slide Left", 4),
    ("Slide Right", 5),
    ("Slide Down", 6),
    ("Slide Up", 7),
]


####################################################################################################
### PART 11: Pipeline Initialization
####################################################################################################
# Initialize pipeline WITHOUT text encoder (gemma_root=None)
# Text encoding will be done by external space
pipeline = DistilledPipeline(
    device=torch.device("cuda"),
    checkpoint_path=checkpoint_path,
    spatial_upsampler_path=spatial_upsampler_path,
    gemma_root=None,  # No text encoder in this space
    loras=loras,
    fp8transformer=False,
    local_files_only=False,
)

pipeline._video_encoder = pipeline.model_ledger.video_encoder()
pipeline._transformer = pipeline.model_ledger.transformer()

print("=" * 80)
print("Pipeline fully loaded and ready!")
print("=" * 80)


####################################################################################################
### PART 12: Custom Component - RadioAnimated
####################################################################################################
class RadioAnimated(gr.HTML):
    """
    Animated segmented radio (like iOS pill selector).
    Outputs: selected option string, e.g. "768x512"
    """
    def __init__(self, choices, value=None, **kwargs):
        if not choices or len(choices) < 2:
            raise ValueError("RadioAnimated requires at least 2 choices.")
        if value is None:
            value = choices[0]

        uid = uuid.uuid4().hex[:8]  # unique per instance
        group_name = f"ra-{uid}"

        inputs_html = "\n".join(
            f"""
            <input class="ra-input" type="radio" name="{group_name}" id="{group_name}-{i}" value="{c}">
            <label class="ra-label" for="{group_name}-{i}">{c}</label>
            """
            for i, c in enumerate(choices)
        )

        # NOTE: use classes instead of duplicate IDs
        html_template = f"""
        <div class="ra-wrap" data-ra="{uid}">
          <div class="ra-inner">
            <div class="ra-highlight"></div>
            {inputs_html}
          </div>
        </div>
        """

        js_on_load = r"""
        (() => {
            const wrap = element.querySelector('.ra-wrap');
            const inner = element.querySelector('.ra-inner');
            const highlight = element.querySelector('.ra-highlight');
            const inputs = Array.from(element.querySelectorAll('.ra-input'));
            const labels = Array.from(element.querySelectorAll('.ra-label'));

            if (!inputs.length || !labels.length) return;

            const choices = inputs.map(i => i.value);
            const PAD = 6; // must match .ra-inner padding and .ra-highlight top/left

            let currentIdx = 0;

            function setHighlightByIndex(idx) {
                currentIdx = idx;

                const lbl = labels[idx];
                if (!lbl) return;

                const innerRect = inner.getBoundingClientRect();
                const lblRect = lbl.getBoundingClientRect();

                // width matches the label exactly
                highlight.style.width = `${lblRect.width}px`;

                // highlight has left: 6px, so subtract PAD to align
                const x = (lblRect.left - innerRect.left - PAD);
                highlight.style.transform = `translateX(${x}px)`;
            }

            function setCheckedByValue(val, shouldTrigger=false) {
                const idx = Math.max(0, choices.indexOf(val));
                inputs.forEach((inp, i) => { inp.checked = (i === idx); });

                // Wait a frame in case fonts/layout settle (prevents rare drift)
                requestAnimationFrame(() => setHighlightByIndex(idx));

                props.value = choices[idx];
                if (shouldTrigger) trigger('change', props.value);
            }

            // Init
            setCheckedByValue(props.value ?? choices[0], false);

            // Input handlers
            inputs.forEach((inp) => {
                inp.addEventListener('change', () => setCheckedByValue(inp.value, true));
            });

            // Recalc on resize (important in Gradio layouts)
            window.addEventListener('resize', () => setHighlightByIndex(currentIdx));

            // sync from Python (Examples / backend updates)
            let last = props.value;
            const syncFromProps = () => {
              if (props.value !== last) {
                last = props.value;
                setCheckedByValue(last, false);
              }
              requestAnimationFrame(syncFromProps);
            };
            requestAnimationFrame(syncFromProps);

        })();

        """

        super().__init__(
            value=value,
            html_template=html_template,
            js_on_load=js_on_load,
            **kwargs
        )


####################################################################################################
### PART 13: Custom Component - PromptBox
####################################################################################################
class PromptBox(gr.HTML):
    """
    Prompt textarea with an internal footer slot (.ds-footer) where we can inject dropdowns.
    """
    def __init__(self, value="", placeholder="دستور ساخت ویدیو را اینجا بنویسید...", **kwargs):
        uid = uuid.uuid4().hex[:8]

        html_template = f"""
        <div class="ds-card" data-ds="{uid}">
          <div class="ds-top">
            <textarea class="ds-textarea" rows="3" placeholder="{placeholder}"></textarea>

            <!-- footer slot -->
            <div class="ds-footer" aria-label="prompt-footer"></div>
          </div>
        </div>
        """

        js_on_load = r"""
        (() => {
          const textarea = element.querySelector(".ds-textarea");
          if (!textarea) return;
        
          const autosize = () => {
            textarea.style.height = "0px";
            textarea.style.height = Math.min(textarea.scrollHeight, 240) + "px";
          };
        
          const setValue = (v, triggerChange=false) => {
            const val = (v ?? "");
            if (textarea.value !== val) textarea.value = val;
            autosize();
            props.value = textarea.value;
            if (triggerChange) trigger("change", props.value);
          };
        
          setValue(props.value, false);
        
          textarea.addEventListener("input", () => {
            autosize();
            props.value = textarea.value;
            trigger("change", props.value);
          });
        
          // ✅ Focus-on-load (robust)
          const shouldAutoFocus = () => {
            // don’t steal focus if user already clicked/typed somewhere
            const ae = document.activeElement;
            if (ae && ae !== document.body && ae !== document.documentElement) return false;
            // don’t auto-focus on small screens (optional; avoids mobile keyboard pop)
            if (window.matchMedia && window.matchMedia("(max-width: 768px)").matches) return false;
            return true;
          };
        
          const focusWithRetry = (tries = 30) => {
            if (!shouldAutoFocus()) return;
            // only focus if still not focused
            if (document.activeElement !== textarea) textarea.focus({ preventScroll: true });
            if (document.activeElement === textarea) return;
            if (tries > 0) requestAnimationFrame(() => focusWithRetry(tries - 1));
          };
        
          // wait a tick so Gradio/layout settles
          requestAnimationFrame(() => focusWithRetry());
        
          // keep your sync loop
          let last = props.value;
          const syncFromProps = () => {
            if (props.value !== last) {
              last = props.value;
              setValue(last, false);
            }
            requestAnimationFrame(syncFromProps);
          };
          requestAnimationFrame(syncFromProps);
        })();

        """

        super().__init__(value=value, html_template=html_template, js_on_load=js_on_load, **kwargs)


####################################################################################################
### PART 14: Custom Component - CameraDropdown
####################################################################################################
class CameraDropdown(gr.HTML):
    """
    Custom dropdown (More-style) with optional icons per item.
    Outputs: selected option string, e.g. "16:9"
    """
    def __init__(self, choices, value="None", title="Dropdown", **kwargs):
        if not choices:
            raise ValueError("CameraDropdown requires choices.")

        # Normalize choices -> list of dicts: {label, value, icon(optional)}
        norm = []
        for c in choices:
            if isinstance(c, dict):
                label = str(c.get("label", c.get("value", "")))
                val = str(c.get("value", label))
                icon = c.get("icon", None)  # emoji or svg/html
                norm.append({"label": label, "value": val, "icon": icon})
            else:
                s = str(c)
                norm.append({"label": s, "value": s, "icon": None})

        uid = uuid.uuid4().hex[:8]

        def render_item(item):
            icon_html = ""
            if item["icon"]:
                icon_html = f'<span class="cd-icn">{item["icon"]}</span>'
            return (
                f'<button type="button" class="cd-item" '
                f'data-value="{item["value"]}">'
                f'{icon_html}<span class="cd-label">{item["label"]}</span>'
                f'</button>'
            )

        items_html = "\n".join(render_item(item) for item in norm)

        html_template = f"""
        <div class="cd-wrap" data-cd="{uid}">
            <button type="button" class="cd-trigger" aria-haspopup="menu" aria-expanded="false">
              <span class="cd-trigger-icon"></span>
              <span class="cd-trigger-text"></span>
              <span class="cd-caret">▾</span>
            </button>

          <div class="cd-menu" role="menu" aria-hidden="true">
            <div class="cd-title">{title}</div>
            <div class="cd-items">
              {items_html}
            </div>
          </div>
        </div>
        """

        # Pass a mapping value->label so the trigger can show label text
        # (and still output value to Python)
        value_to_label = {it["value"]: it["label"] for it in norm}
        value_to_icon = {it["value"]: (it["icon"] or "") for it in norm}

        js_on_load = r"""
        (() => {
          const wrap = element.querySelector(".cd-wrap");
          const trigger = element.querySelector(".cd-trigger");
          const triggerIcon = element.querySelector(".cd-trigger-icon");
          const triggerText = element.querySelector(".cd-trigger-text");
          const menu = element.querySelector(".cd-menu");
          const items = Array.from(element.querySelectorAll(".cd-item"));
          if (!wrap || !trigger || !menu || !items.length) return;

          const valueToLabel = __VALUE_TO_LABEL__;
          const valueToIcon  = __VALUE_TO_ICON__;
        
          const safeLabel = (v) => (valueToLabel && valueToLabel[v]) ? valueToLabel[v] : (v ?? "None");
          const safeIcon  = (v) => (valueToIcon  && valueToIcon[v])  ? valueToIcon[v]  : "";


          function closeMenu() {
            menu.classList.remove("open");
            trigger.setAttribute("aria-expanded", "false");
            menu.setAttribute("aria-hidden", "true");
          }

          function openMenu() {
            menu.classList.add("open");
            trigger.setAttribute("aria-expanded", "true");
            menu.setAttribute("aria-hidden", "false");
          }

          function setValue(val, shouldTrigger = false) {
            const v = (val ?? "None");
            props.value = v;

            // Trigger shows LABEL only (icons stay in menu)
            triggerText.textContent = safeLabel(v);
            if (triggerIcon) {
              triggerIcon.innerHTML = safeIcon(v);
              triggerIcon.style.display = safeIcon(v) ? "inline-flex" : "none";
            }


            items.forEach(btn => {
              btn.dataset.selected = (btn.dataset.value === v) ? "true" : "false";
            });

            if (shouldTrigger) trigger("change", props.value);
          }

          trigger.addEventListener("pointerdown", (e) => {
            e.preventDefault();
            e.stopPropagation();
            if (menu.classList.contains("open")) closeMenu();
            else openMenu();
          });

          document.addEventListener("pointerdown", (e) => {
            if (!wrap.contains(e.target)) closeMenu();
          }, true);

          document.addEventListener("keydown", (e) => {
            if (e.key === "Escape") closeMenu();
          });

          wrap.addEventListener("focusout", (e) => {
            if (!wrap.contains(e.relatedTarget)) closeMenu();
          });

          items.forEach((btn) => {
            btn.addEventListener("pointerdown", (e) => {
              e.preventDefault();
              e.stopPropagation();
              closeMenu();
              setValue(btn.dataset.value, true);
            });
          });

          // init
          setValue((props.value ?? "None"), false);

          // sync from Python
          let last = props.value;
          const syncFromProps = () => {
            if (props.value !== last) {
              last = props.value;
              setValue(last, false);
            }
            requestAnimationFrame(syncFromProps);
          };
          requestAnimationFrame(syncFromProps);
        })();
        """

        # Inject mapping into JS safely
        import json
        js_on_load = js_on_load.replace("__VALUE_TO_LABEL__", json.dumps(value_to_label))
        js_on_load = js_on_load.replace("__VALUE_TO_ICON__", json.dumps(value_to_icon))

        super().__init__(
            value=value,
            html_template=html_template,
            js_on_load=js_on_load,
            **kwargs
        )


####################################################################################################
### PART 15: Custom Component - PresetGallery
####################################################################################################
class PresetGallery(gr.HTML):
    """
    Clickable image presets -> outputs selected index (int as string, then cast in python)
    """
    def __init__(self, items, title="Click an Example", **kwargs):
        """
        items: list[dict] with keys:
          - thumb: str (path to image file, e.g. "supergirl.png")
          - label: str (optional)
        """
        uid = uuid.uuid4().hex[:8]

        cards_html = []
        for i, it in enumerate(items):
            thumb = it["thumb"]
            label = it.get("label", "")
            cards_html.append(f"""
              <button type="button" class="pg-card" data-idx="{i}" aria-label="{label}">
                <img class="pg-img" src="gradio_api/file={thumb}" alt="{label}">
              </button>
            """)

        html_template = f"""
        <style>
        .pg-modal-overlay-custom {{
            position: fixed; top: 0; left: 0; right: 0; bottom: 0;
            background: rgba(0,0,0,0.6); display: none;
            align-items: center; justify-content: center; z-index: 999999;
            backdrop-filter: blur(2px);
        }}
        .pg-modal-custom {{
            background: #2b2b2b; padding: 24px; border-radius: 16px;
            border: 1px solid rgba(255,255,255,0.12); color: rgba(255,255,255,0.9);
            text-align: center; font-family: ui-sans-serif, system-ui, -apple-system, sans-serif; 
            min-width: 320px; box-shadow: 0 10px 30px rgba(0,0,0,0.5);
            direction: rtl;
        }}
        .pg-modal-custom p {{
            font-size: 16px; margin: 0 0 20px 0; font-weight: 600;
        }}
        .pg-modal-btns-custom {{
            display: flex; gap: 12px; justify-content: center;
        }}
        .pg-modal-btns-custom button {{
            padding: 10px 24px; border: none; border-radius: 10px; cursor: pointer; 
            font-weight: 700; font-size: 14px; font-family: inherit; transition: opacity 0.2s;
        }}
        .pg-modal-btns-custom button:hover {{
            opacity: 0.8;
        }}
        .pg-btn-confirm-custom {{ 
            background: #4b2ab5; color: white; 
        }}
        .pg-btn-cancel-custom {{ 
            background: transparent; color: rgba(255,255,255,0.7); 
            border: 1px solid rgba(255,255,255,0.2) !important;
        }}
        </style>

        <div class="pg-wrap" data-pg="{uid}">
          <div class="pg-title">
            <div class="pg-h1">{title}</div>
          </div>
          <div class="pg-grid">
            {''.join(cards_html)}
          </div>
          
          <!-- پیام تاییدی (Modal) اضافه شده -->
          <div class="pg-modal-overlay-custom">
            <div class="pg-modal-custom">
              <p>آیا می‌خواهید نمونه به بالا اضافه بشه؟</p>
              <div class="pg-modal-btns-custom">
                <button class="pg-btn-confirm-custom">تایید</button>
                <button class="pg-btn-cancel-custom">انصراف</button>
              </div>
            </div>
          </div>
        </div>
        """

        # --- JAVASCRIPT LOGIC UPDATED ---
        # Logic updated to show confirmation prompt before triggering action
        js_on_load = r"""
        (() => {
          const wrap = element.querySelector(".pg-wrap");
          const cards = Array.from(element.querySelectorAll(".pg-card"));
          const modalOverlay = element.querySelector(".pg-modal-overlay-custom");
          const btnConfirm = element.querySelector(".pg-btn-confirm-custom");
          const btnCancel = element.querySelector(".pg-btn-cancel-custom");
          
          if (!wrap || !cards.length || !modalOverlay) return;
        
          function setDim(activeIdx) {
            cards.forEach((c, i) => {
              // Dim cards that are not the active one.
              c.dataset.dim = (activeIdx !== null && i !== activeIdx) ? "true" : "false";
              // Set the active state for the clicked card.
              c.dataset.active = (i === activeIdx) ? "true" : "false";
            });
          }
        
          let lastSent = null;
          let lock = false;
          let pendingIdxNumber = null;
          
          // Action for "تایید"
          btnConfirm.addEventListener("pointerdown", (e) => {
              e.preventDefault();
              e.stopPropagation();
              modalOverlay.style.display = "none"; // Hide Modal
              
              if (pendingIdxNumber !== null) {
                  const idxString = String(pendingIdxNumber);
                  
                  // 1. Update visual state immediately on confirmed click.
                  setDim(pendingIdxNumber);
                  
                  // 2. Only update Python backend if the value has actually changed.
                  if (idxString !== lastSent) {
                      lastSent = idxString;
                      // ✅ Set props.value to send data to Python.
                      props.value = idxString;
                  }
                  
                  pendingIdxNumber = null;
              }
          });
          
          // Action for "انصراف"
          btnCancel.addEventListener("pointerdown", (e) => {
              e.preventDefault();
              e.stopPropagation();
              modalOverlay.style.display = "none"; // Hide Modal
              pendingIdxNumber = null;
          });

          // Close modal if clicked directly on background overlay
          modalOverlay.addEventListener("pointerdown", (e) => {
              if (e.target === modalOverlay) {
                  e.preventDefault();
                  e.stopPropagation();
                  modalOverlay.style.display = "none";
                  pendingIdxNumber = null;
              }
          });
        
          cards.forEach((card) => {
            card.addEventListener("pointerdown", (e) => {
              e.preventDefault();
              e.stopPropagation();
        
              if (lock) return;
              lock = true;
              setTimeout(() => (lock = false), 250);
        
              // Save clicked index and display modal
              pendingIdxNumber = Number(card.dataset.idx);
              modalOverlay.style.display = "flex";
              
            }, { passive: false });
          });
        
          // Initially, no card is selected.
          setDim(null);
        })();
        """

        super().__init__(value="", html_template=html_template, js_on_load=js_on_load, **kwargs)


####################################################################################################
### PART 16: Custom Component - AudioDropUpload (FIXED)
####################################################################################################
class AudioDropUpload(gr.HTML):
    """
    Custom audio drop/click UI that proxies file into a hidden gr.Audio component.
    IMPORTANT:
    - Pass target_audio_elem_id = elem_id of your hidden gr.Audio.
    - The hidden gr.Audio must be type="filepath" (or whatever you need).
    """
    def __init__(self, target_audio_elem_id: str, value=None, **kwargs):
        uid = uuid.uuid4().hex[:8]

        html_template = f"""
        <div class="aud-wrap" data-aud="{uid}">
          <div class="aud-drop" role="button" tabindex="0" aria-label="بارگذاری صدا">
            <div><strong>(اختیاری) فایل صوتی را اینجا بکشید و رها کنید</strong></div>
            <div class="aud-hint">…یا برای انتخاب کلیک کنید</div>
          </div>
          <div class="aud-row" aria-live="polite">
            <audio class="aud-player" controls></audio>
            <button class="aud-remove" type="button" aria-label="حذف صدا">
              <svg width="16" height="16" viewBox="0 0 24 24" aria-hidden="true" focusable="false">
                <path d="M18 6L6 18M6 6l12 12"
                      stroke="currentColor"
                      stroke-width="2.25"
                      stroke-linecap="round"/>
              </svg>
            </button>
          </div>
          <div class="aud-filelabel"></div>
        </div>
        """

        # JS:
        # - finds the hidden gr.Audio upload <input type=file> inside the component with elem_id=target_audio_elem_id
        # - sets the selected file onto it (DataTransfer) and dispatches change
        js_on_load = """
        (() => {
          // Helper: access Gradio shadow DOM safely
          function grRoot() {
            const ga = document.querySelector("gradio-app");
            return (ga && ga.shadowRoot) ? ga.shadowRoot : document;
          }
          const root = grRoot();
          const wrap = element.querySelector(".aud-wrap");
          const drop = element.querySelector(".aud-drop");
          const row  = element.querySelector(".aud-row");
          const player = element.querySelector(".aud-player");
          const removeBtn = element.querySelector(".aud-remove");
          const label = element.querySelector(".aud-filelabel");
          const TARGET_ID = "__TARGET_ID__";
          let currentUrl = null;
          function findHiddenAudioFileInput() {
            const host = root.querySelector("#" + CSS.escape(TARGET_ID));
            if (!host) return null;
            // Gradio's Audio component contains an <input type=file> for upload.
            // This selector works in most Gradio 3/4 themes.
            const inp = host.querySelector('input[type="file"]');
            return inp;
          }
          function showDrop() {
            drop.style.display = "";
            row.style.display = "none";
            label.style.display = "none";
            label.textContent = "";
          }
          function showPlayer(filename) {
            drop.style.display = "none";
            row.style.display = "flex";
            if (filename) {
              label.textContent = "فایل بارگذاری شده: " + filename;
              label.style.display = "block";
            }
          }
          function clearPreview() {
            player.pause();
            player.removeAttribute("src");
            player.load();
            if (currentUrl) {
              URL.revokeObjectURL(currentUrl);
              currentUrl = null;
            }
          }
          function clearHiddenGradioAudio() {
            const fileInput = findHiddenAudioFileInput();
            if (!fileInput) return;
            // Clear file input (works by replacing its files with empty DataTransfer)
            fileInput.value = "";
            const dt = new DataTransfer();
            fileInput.files = dt.files;
            fileInput.dispatchEvent(new Event("input",  { bubbles: true }));
            fileInput.dispatchEvent(new Event("change", { bubbles: true }));
          }
          function clearAll() {
            clearPreview();
          
            // Attempt DOM clear (still useful)
            clearHiddenGradioAudio();
          
            // Tell Gradio/Python explicitly to clear backend state
            props.value = "__CLEAR__";
            trigger("change", props.value);
          
            showDrop();
          }

          function loadFileToPreview(file) {
            if (!file) return;
            if (!file.type || !file.type.startsWith("audio/")) {
              alert("لطفا یک فایل صوتی انتخاب کنید.");
              return;
            }
            clearPreview();
            currentUrl = URL.createObjectURL(file);
            player.src = currentUrl;
            showPlayer(file.name);

          }
          function pushFileIntoHiddenGradioAudio(file) {
            const fileInput = findHiddenAudioFileInput();
            if (!fileInput) {
              console.warn("Could not find hidden gr.File input. Check elem_id:", TARGET_ID);
              return;
            }
          
            // Hard reset (important for re-selecting same file)
            fileInput.value = "";
          
            const dt = new DataTransfer();
            dt.items.add(file);
            fileInput.files = dt.files;
          
            // Trigger Gradio listeners
            fileInput.dispatchEvent(new Event("input",  { bubbles: true }));
            fileInput.dispatchEvent(new Event("change", { bubbles: true }));
          }

          function handleFile(file) {
            loadFileToPreview(file);
            pushFileIntoHiddenGradioAudio(file);
          }
          // Click-to-browse uses a *local* ephemeral input (not Gradio’s),
          // then we forward to hidden gr.Audio.
          const localPicker = document.createElement("input");
          localPicker.type = "file";
          localPicker.accept = "audio/*";
          localPicker.style.display = "none";
          wrap.appendChild(localPicker);
          localPicker.addEventListener("change", () => {
            const f = localPicker.files && localPicker.files[0];
            if (f) handleFile(f);
            localPicker.value = "";
          });
          drop.addEventListener("click", () => localPicker.click());
          drop.addEventListener("keydown", (e) => {
            if (e.key === "Enter" || e.key === " ") {
              e.preventDefault();
              localPicker.click();
            }
          });
          removeBtn.addEventListener("click", clearAll);
          // Drag & drop
          ["dragenter","dragover","dragleave","drop"].forEach(evt => {
            drop.addEventListener(evt, (e) => {
              e.preventDefault();
              e.stopPropagation();
            });
          });
          drop.addEventListener("dragover", () => drop.classList.add("dragover"));
          drop.addEventListener("dragleave", () => drop.classList.remove("dragover"));
          drop.addEventListener("drop", (e) => {
            drop.classList.remove("dragover");
            const f = e.dataTransfer.files && e.dataTransfer.files[0];
            if (f) handleFile(f);
          });
          // init
          showDrop();

          function setPreviewFromPath(path) {
            if (path === "__CLEAR__") path = null;
            
            if (!path) {
              clearPreview();
              showDrop();
              return;
            }
          
            // If path already looks like a URL, use it directly
            // otherwise serve it through Gradio's file route.
            let url = path;
            if (!/^https?:\/\//.test(path) && !path.startsWith("gradio_api/file=") && !path.startsWith("/file=")) {
              url = "gradio_api/file=" + path;
            }
          
            clearPreview();
            player.src = url;
            showPlayer(path.split("/").pop());
          }
          
          // ---- sync from Python (Examples / backend updates) ----
          let last = props.value;
          const syncFromProps = () => {
            const v = props.value;
          
            if (v !== last) {
              last = v;
              if (!v || v === "__CLEAR__") setPreviewFromPath(null);
              else setPreviewFromPath(String(v));
            }
            requestAnimationFrame(syncFromProps);
          };
          requestAnimationFrame(syncFromProps);


        })();
        """
        js_on_load = js_on_load.replace("__TARGET_ID__", target_audio_elem_id)
        
        super().__init__(
            value=value,
            html_template=html_template,
            js_on_load=js_on_load,
            **kwargs
        )


####################################################################################################
### PART 17: Wrapper Functions (Resolution, Duration, Examples)
####################################################################################################
def generate_video_example(first_frame, prompt, camera_lora, resolution, radioanimated_mode, input_video, input_audio, end_frame, progress=gr.Progress(track_tqdm=True)):

    w, h = apply_resolution(resolution)
    
    # We pass input_video (from example) to generate_video, though the logic inside generate_video 
    # might ignore it since we removed the Motion Control block.
    # We keep the argument in this function signature to align with the examples_list columns.
    
    # Default duration for examples
    duration_s = 5

    with timer(f'generating with LoRA:{camera_lora} in {w}x{h}'):
        output_video = generate_video(
            first_frame,
            end_frame,
            prompt,
            10,
            input_video, 
            radioanimated_mode,
            True,                    
            42,                      
            True,                    
            h,  
            w,   
            camera_lora,     
            input_audio,
            progress
        )
    return output_video

def get_duration(
    first_frame,
    end_frame,
    prompt,
    duration,
    input_video,
    radioanimated_mode,
    enhance_prompt,
    seed,
    randomize_seed,
    height,
    width,
    camera_lora,
    audio_path,
    progress
):
    extra_time = 0

    if audio_path is not None:
        extra_time += 10

    if input_video is not None:
        extra_time += 60

    if duration <= 3:
        return 60 + extra_time
    elif duration <= 5:
        return 80 + extra_time
    elif duration <= 10:
        return 120 + extra_time
    else:
        return 180 + extra_time


####################################################################################################
### PART 18: Main Generation Function (Modified)
####################################################################################################
@spaces.GPU(duration=get_duration)
def generate_video(
    first_frame,
    end_frame,
    prompt: str,
    duration: float,
    input_video = None,
    generation_mode = "تبدیل تصویر به ویدیو", # Default changed to Persian
    enhance_prompt: bool = True,
    seed: int = 42,
    randomize_seed: bool = True,
    height: int = DEFAULT_1_STAGE_HEIGHT,
    width: int = DEFAULT_1_STAGE_WIDTH,
    camera_lora: str = "No LoRA", 
    audio_path = None,
    progress=gr.Progress(track_tqdm=True),
):
    """
    Generate a short cinematic video from a text prompt and optional input image using the LTX-2 distilled pipeline.
    """

    # Removed the 15s warning check since 15s option is removed from UI

    if audio_path is None:
        print(f'generating with duration:{duration} and LoRA:{camera_lora} in {width}x{height}')
    else:
        print(f'generating with duration:{duration} and audio in {width}x{height}')

    # Randomize seed if checkbox is enabled
    current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)

    # Calculate num_frames from duration (using fixed 24 fps)
    frame_rate = 24.0
    num_frames = int(duration * frame_rate) + 1  # +1 to ensure we meet the duration
    video_seconds = int(duration)

    with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
        output_path = tmpfile.name


    images = []
    videos = []

    # Removed Motion Control block

    if first_frame is not None:
        images = []
        images.append((first_frame, 0, 1.0))

    # Updated logic for Persian string
    if generation_mode == "ویدیو با دو تصویر":
      if end_frame is not None:
          end_idx = max(0, num_frames - 1)
          images.append((end_frame, end_idx, 0.5))

    embeddings, final_prompt, status = encode_prompt(
        prompt=prompt,
        enhance_prompt=enhance_prompt,
        input_image=first_frame,
        seed=current_seed,
        negative_prompt="",
    )
    
    video_context = embeddings["video_context"].to("cuda", non_blocking=True)
    audio_context = embeddings["audio_context"].to("cuda", non_blocking=True)
    print("✓ Embeddings loaded successfully")


    # free prompt enhancer / encoder temps ASAP
    del embeddings, final_prompt, status
    torch.cuda.empty_cache()

    # ✅ if user provided audio, use a neutral audio_context
    n_audio_context = None

    if audio_path is not None:
        with torch.inference_mode():
            _, n_audio_context = encode_text_simple(text_encoder, "")  # returns tensors on GPU already
            del audio_context
            audio_context = n_audio_context

        if len(videos) == 0:
            camera_lora = "Static"

    torch.cuda.empty_cache()

    # Map dropdown name -> adapter index
    name_to_idx = {name: idx for name, idx in RUNTIME_LORA_CHOICES}
    selected_idx = name_to_idx.get(camera_lora, -1)

    enable_only_lora(pipeline._transformer, selected_idx)
    torch.cuda.empty_cache()

    # True video duration in seconds based on your rounding
    video_seconds = (num_frames - 1) / frame_rate

    if audio_path is not None:
        input_waveform, input_waveform_sample_rate = match_audio_to_duration(
            audio_path=audio_path,
            target_seconds=video_seconds,
            target_sr=48000,     # pick what your model expects; 48k is common for AV models
            to_mono=True,        # set False if your model wants stereo
            pad_mode="silence",  # or "repeat" if you prefer looping over silence
            device="cuda",
        )
    else:
        input_waveform = None
        input_waveform_sample_rate = None

    with timer(f'generating with LoRA:{camera_lora} in {width}x{height}'):
        with torch.inference_mode():
            pipeline(
                prompt=prompt,
                output_path=str(output_path),
                seed=current_seed,
                height=height,
                width=width,
                num_frames=num_frames,
                frame_rate=frame_rate,
                images=images,
                video_conditioning=videos,
                tiling_config=TilingConfig.default(),
                video_context=video_context,
                audio_context=audio_context,
                input_waveform=input_waveform,
                input_waveform_sample_rate=input_waveform_sample_rate, 
            )
    del video_context, audio_context
    torch.cuda.empty_cache()
    print("successful generation")

    return str(output_path)


def apply_resolution(resolution: str):

    if resolution == "16:9":
        w, h = 768, 512
    elif resolution == "1:1":
        w, h = 512, 512
    elif resolution == "9:16":
        w, h = 512, 768
        
    return int(w), int(h)

def apply_duration(duration: str):
    duration_s = int(duration[:-1])
    return duration_s

def on_mode_change(selected: str):
    is_motion = False # Removed Motion Control
    # Updated logic for Persian string
    is_interpolate = (selected == "ویدیو با دو تصویر")

    return (gr.update(visible=is_motion), gr.update(visible=is_interpolate))


####################################################################################################
### PART 19: CSS Styles
####################################################################################################
css = """

    /* Make the row behave nicely */
    #controls-row {
    display: none !important;
    align-items: center;
    gap: 12px;
    flex-wrap: nowrap; /* or wrap if you prefer on small screens */
    }

    /* Stop these components from stretching */
    #controls-row > * {
    flex: 0 0 auto !important;
    width: auto !important;
    min-width: 0 !important;
    }

    
    #col-container {
        margin: 0 auto;
        max-width: 1600px;
    }
    #modal-container {
    width: 100vw;            /* Take full viewport width */
    height: 100vh;           /* Take full viewport height (optional) */
    display: flex;           
    justify-content: center; /* Center content horizontally */
    align-items: center;     /* Center content vertically if desired */
    }
    #modal-content {
    width: 100%;
    max-width: 700px;         /* Limit content width */
    margin: 0 auto;
    border-radius: 8px;
    padding: 1.5rem;
    }
    #step-column {
        padding: 10px;
        border-radius: 8px;
        box-shadow: var(--card-shadow);
        margin: 10px;
    }
    #col-showcase {
        margin: 0 auto;
        max-width: 1100px;
    }
    .button-gradient {
        background: linear-gradient(45deg, rgb(255, 65, 108), rgb(255, 75, 43), rgb(255, 155, 0), rgb(255, 65, 108)) 0% 0% / 400% 400%;
        border: none;
        padding: 14px 28px;
        font-size: 16px;
        font-weight: bold;
        color: white;
        border-radius: 10px;
        cursor: pointer;
        transition: 0.3s ease-in-out;
        animation: 2s linear 0s infinite normal none running gradientAnimation;
        box-shadow: rgba(255, 65, 108, 0.6) 0px 4px 10px;
    }
    .toggle-container {
    display: inline-flex;
    background-color: #ffd6ff;  /* light pink background */
    border-radius: 9999px;
    padding: 4px;
    position: relative;
    width: fit-content;
    font-family: sans-serif;
    }
    .toggle-container input[type="radio"] {
    display: none;
    }
    .toggle-container label {
    position: relative;
    z-index: 2;
    flex: 1;
    text-align: center;
    font-weight: 700;
    color: #4b2ab5; /* dark purple text for unselected */
    padding: 6px 22px;
    border-radius: 9999px;
    cursor: pointer;
    transition: color 0.25s ease;
    }
    /* Moving highlight */
    .toggle-highlight {
    position: absolute;
    top: 4px;
    left: 4px;
    width: calc(50% - 4px);
    height: calc(100% - 8px);
    background-color: #4b2ab5; /* dark purple background */
    border-radius: 9999px;
    transition: transform 0.25s ease;
    z-index: 1;
    }
    /* When "True" is checked */
    #true:checked ~ label[for="true"] {
    color: #ffd6ff; /* light pink text */
    }
    /* When "False" is checked */
    #false:checked ~ label[for="false"] {
    color: #ffd6ff; /* light pink text */
    }
    /* Move highlight to right side when False is checked */
    #false:checked ~ .toggle-highlight {
    transform: translateX(100%);
    }

    /* Center items inside that row */
    #mode-row{
      justify-content: center !important;
      align-items: center !important;
    }
    
    /* Center the mode row contents */
    #mode-row {
      display: flex !important;
      justify-content: center !important;
      align-items: center !important;
      width: 100% !important;
    }
    
    /* Stop Gradio from making children stretch */
    #mode-row > * {
      flex: 0 0 auto !important;
      width: auto !important;
      min-width: 0 !important;
    }
    
    /* Specifically ensure the HTML component wrapper doesn't take full width */
    #mode-row .gr-html,
    #mode-row .gradio-html,
    #mode-row .prose,
    #mode-row .block {
      width: auto !important;
      flex: 0 0 auto !important;
      display: inline-block !important;
    }
    
    /* Center the pill itself */
    #radioanimated_mode {
      display: inline-flex !important;
      justify-content: center !important;
      width: auto !important;
    }

    """

css += """
    .cd-trigger-icon{
      color: rgba(255,255,255,0.9);
      display: inline-flex;
      align-items: center;
      justify-content: center;
      width: 18px;
      height: 18px;
    }
    .cd-trigger-icon svg {
      width: 18px;
      height: 18px;
      display: block;
    }
    """


css += """
    /* ---- radioanimated ---- */
    .ra-wrap{
      width: fit-content;
    }
    .ra-inner{
      position: relative;
      display: inline-flex;
      align-items: center;
      gap: 0;
      padding: 6px;
      background: #0b0b0b;
      border-radius: 9999px;
      overflow: hidden;
      user-select: none;
    }
    .ra-input{
      display: none;
    }
    .ra-label{
      position: relative;
      z-index: 2;
      padding: 10px 18px;
      font-family: ui-sans-serif, system-ui, -apple-system, Segoe UI, Roboto, Arial;
      font-size: 14px;
      font-weight: 600;
      color: rgba(255,255,255,0.7);
      cursor: pointer;
      transition: color 180ms ease;
      white-space: nowrap;
    }
    .ra-highlight{
      position: absolute;
      z-index: 1;
      top: 6px;
      left: 6px;
      height: calc(100% - 12px);
      border-radius: 9999px;
      background: #8bff97; /* green knob */
      transition: transform 200ms ease, width 200ms ease;
    }
    /* selected label becomes darker like your screenshot */
    .ra-input:checked + .ra-label{
      color: rgba(0,0,0,0.75);
    }
    """

css += """
.cd-icn svg{
  width: 18px;
  height: 18px;
  display: block;
}
.cd-icn svg *{
  stroke: rgba(255,255,255,0.9);
}
"""


css += """
    /* --- prompt box --- */
    .ds-prompt{
      width: 100%;
      max-width: 720px;
      margin-top: 3px;
    }
    
    .ds-textarea{
      width: 100%;
      box-sizing: border-box;
      background: #2b2b2b;
      color: rgba(255,255,255,0.9);
      border: 1px solid rgba(255,255,255,0.12);
      border-radius: 14px;
      padding: 14px 16px;
      outline: none;
      font-family: ui-sans-serif, system-ui, -apple-system, Segoe UI, Roboto, Arial;
      font-size: 15px;
      line-height: 1.35;
      resize: none;
      min-height: 210px;
      max-height: 210px;
      overflow-y: auto;
    
      /* IMPORTANT: space for the footer controls */
      padding-bottom: 72px;
    }


    .ds-card{
      width: 100%;
      max-width: 720px;
      margin: 0 auto;
    }
    .ds-top{
      position: relative;
    }
    
    /* Make room for footer inside textarea */
    .ds-textarea{
      padding-bottom: 72px;
    }
    
    /* Footer positioning */
    .ds-footer{
      position: absolute;
      right: 12px;
      bottom: 10px;
      display: flex;
      gap: 8px;
      align-items: center;
      justify-content: flex-end;
      z-index: 3;
    }
    
    /* Smaller pill buttons inside footer */
    .ds-footer .cd-trigger{
      min-height: 32px;
      padding: 6px 10px;
      font-size: 12px;
      gap: 6px;
      border-radius: 9999px;
    }
    .ds-footer .cd-trigger-icon,
    .ds-footer .cd-icn{
      width: 14px;
      height: 14px;
    }
    .ds-footer .cd-trigger-icon svg,
    .ds-footer .cd-icn svg{
      width: 14px;
      height: 14px;
    }
    .ds-footer .cd-caret{
      font-size: 11px;
    }
    
    /* Bottom safe area bar (optional but looks nicer) */
    .ds-top::after{
      content: "";
      position: absolute;
      left: 1px;
      right: 1px;
      bottom: 1px;
      height: 56px;
      background: #2b2b2b;
      border-bottom-left-radius: 13px;
      border-bottom-right-radius: 13px;
      pointer-events: none;
      z-index: 2;
    }

    """

css += """
    /* ---- camera dropdown ---- */

    /* 1) Fix overlap: make the Gradio HTML block shrink-to-fit when it contains a CameraDropdown.
    Gradio uses .gr-html for HTML components in most versions; older themes sometimes use .gradio-html.
    This keeps your big header HTML unaffected because it doesn't contain .cd-wrap.
    */

    /* 2) Actual dropdown layout */
    .cd-wrap{
    position: relative;
    display: inline-block;
    }

    /* 3) Match RadioAnimated pill size/feel */
    .cd-trigger{
    margin-top: 2px;
    display: inline-flex;
    align-items: center;
    justify-content: center;
    gap: 10px;

    border: none;

    box-sizing: border-box;
    padding: 10px 18px;
    min-height: 52px;
    line-height: 1.2;

    border-radius: 9999px;
    background: #0b0b0b;

    font-family: ui-sans-serif, system-ui, -apple-system, Segoe UI, Roboto, Arial;
    font-size: 14px;

    /* ✅ match .ra-label exactly */
    color: rgba(255,255,255,0.7) !important;
    font-weight: 600 !important;

    cursor: pointer;
    user-select: none;
    white-space: nowrap;
    }

    /* Ensure inner spans match too */
    .cd-trigger .cd-trigger-text,
    .cd-trigger .cd-caret{
    color: rgba(255,255,255,0.7) !important;
    }

    /* keep caret styling */
    .cd-caret{
    opacity: 0.8;
    font-weight: 900;
    }

    /* 4) Ensure menu overlays neighbors and isn't clipped */
    /* Move dropdown a tiny bit up (closer to the trigger) */
    .cd-menu{
      position: absolute;
      top: calc(100% + 4px);   /* was +10px */
      left: 0;
    
      min-width: 240px;
      background: #2b2b2b;
      border: 1px solid rgba(255,255,255,0.14);
      border-radius: 14px;
      box-shadow: 0 18px 40px rgba(0,0,0,0.35);
      padding: 10px;
    
      opacity: 0;
      transform: translateY(-6px);
      pointer-events: none;
      transition: opacity 160ms ease, transform 160ms ease;
    
      z-index: 9999;
    }

    .cd-title{
      font-size: 12px;
      font-weight: 600;
      text-transform: uppercase;
      letter-spacing: 0.04em;
    
      color: rgba(255,255,255,0.45); /* 👈 muted grey */
      margin-bottom: 6px;
      padding: 0 6px;
      pointer-events: none; /* title is non-interactive */
    }
    
        
    .cd-menu.open{
      opacity: 1;
      transform: translateY(0);
      pointer-events: auto;
    }
    
    .cd-items{
      display: flex;
      flex-direction: column;
      gap: 0px; /* tighter, more like a native menu */
    }
    
    /* Items: NO "boxed" buttons by default */
    .cd-item{
      width: 100%;
      text-align: left;
      border: none;
      background: transparent;          /* ✅ removes box look */
      color: rgba(255,255,255,0.92);
      padding: 8px 34px 8px 12px;     /* right padding leaves room for tick */
      border-radius: 10px;             /* only matters on hover */
      cursor: pointer;
    
      font-size: 14px;
      font-weight: 700;
    
      position: relative;
      transition: background 120ms ease;
    }
    
    /* “Box effect” only on hover (not always) */
    .cd-item:hover{
      background: rgba(255,255,255,0.08);
    }
    
    /* Tick on the right ONLY on hover */
    .cd-item::after{
      content: "✓";
      position: absolute;
      right: 12px;
      top: 50%;
      transform: translateY(-50%);
      opacity: 0;                      /* hidden by default */
      transition: opacity 120ms ease;
      color: rgba(255,255,255,0.9);
      font-weight: 900;
    }
    
    /* show tick ONLY for selected item */
    .cd-item[data-selected="true"]::after{
      opacity: 1;
    }
    
    /* keep hover box effect, but no tick change */
    .cd-item:hover{
      background: rgba(255,255,255,0.08);
    }

    
    /* Kill any old “selected” styling just in case */
    .cd-item.selected{
      background: transparent !important;
      border: none !important;
    }


    """

css += """
/* icons in dropdown items */
.cd-item{
  display: flex;
  align-items: center;
  gap: 10px;
}
.cd-icn{
  display: inline-flex;
  align-items: center;
  justify-content: center;
  width: 18px;
  height: 18px;
  flex: 0 0 18px;
}
.cd-label{
  flex: 1;
}

/* =========================
   FIX: prompt border + scrollbar bleed
   ========================= */

/* Put the border + background on the wrapper, not the textarea */
.ds-top{
  position: relative;
  background: #2b2b2b;
  border: 1px solid rgba(255,255,255,0.12);
  border-radius: 14px;
  overflow: hidden; /* ensures the footer bar is clipped to rounded corners */
}

/* Make textarea "transparent" so wrapper owns the border/background */
.ds-textarea{
  background: transparent !important;
  border: none !important;
  border-radius: 0 !important; /* wrapper handles radius */
  outline: none;

  /* keep your spacing */
  padding: 14px 16px;
  padding-bottom: 72px; /* room for footer */
  width: 100%;
  box-sizing: border-box;

  /* keep scroll behavior */
  overflow-y: auto;

  /* prevent scrollbar bleed by hiding native scrollbar */
  scrollbar-width: none;          /* Firefox */
}
.ds-textarea::-webkit-scrollbar{  /* Chrome/Safari */
  width: 0;
  height: 0;
}

/* Safe-area bar: now it matches perfectly because it's inside the same bordered wrapper */
.ds-top::after{
  content: "";
  position: absolute;
  left: 0;
  right: 0;
  bottom: 0;
  height: 56px;
  background: #2b2b2b;
  pointer-events: none;
  z-index: 2;
}

/* Footer above the bar */
.ds-footer{
  position: absolute;
  right: 12px;
  bottom: 10px;
  display: flex;
  gap: 8px;
  align-items: center;
  justify-content: flex-end;
  z-index: 3;
}

/* Ensure textarea content sits below overlays */
.ds-textarea{
  position: relative;
  z-index: 1;
}

/* ===== FIX dropdown menu being clipped/behind ===== */

/* Let the dropdown menu escape the prompt wrapper */
.ds-top{
  overflow: visible !important;  /* IMPORTANT: do not clip the menu */
}

/* Keep the rounded "safe area" look without clipping the menu */
.ds-top::after{
  left: 0 !important;
  right: 0 !important;
  bottom: 0 !important;
  border-bottom-left-radius: 14px !important;
  border-bottom-right-radius: 14px !important;
}

/* Ensure the footer stays above the safe-area bar */
.ds-footer{
  z-index: 20 !important;
}

/* Make sure the opened menu is above EVERYTHING */
.ds-footer .cd-menu{
  z-index: 999999 !important;
}

/* Sometimes Gradio/columns/cards create stacking contexts;
   force the whole prompt card above nearby panels */
.ds-card{
  position: relative;
  z-index: 50;
}

/* --- Fix focus highlight shape (make it match rounded container) --- */

/* Kill any theme focus ring on the textarea itself */
.ds-textarea:focus,
.ds-textarea:focus-visible{
  outline: none !important;
  box-shadow: none !important;
}

/* Optional: if some themes apply it even when not focused */
.ds-textarea{
  outline: none !important;
}

/* Apply the focus ring to the rounded wrapper instead */
.ds-top:focus-within{
  border-color: rgba(255,255,255,0.22) !important;
  box-shadow: 0 0 0 3px rgba(255,255,255,0.06) !important;
  border-radius: 14px !important;
}

/* If you see any tiny square corners, ensure the wrapper clips its own shadow properly */
.ds-top{
  border-radius: 14px !important;
}

/* =========================
   CameraDropdown: force readable menu text in BOTH themes
   ========================= */

/* Menu surface */
.cd-menu{
  background: #2b2b2b !important;
  border: 1px solid rgba(255,255,255,0.14) !important;
}

/* Title */
.cd-title{
  color: rgba(255,255,255,0.55) !important;
}

/* Items + all descendants (fixes spans / inherited theme colors) */
.cd-item,
.cd-item *{
  color: rgba(255,255,255,0.92) !important;
}

/* Hover state */
.cd-item:hover{
  background: rgba(255,255,255,0.10) !important;
}

/* Checkmark */
.cd-item::after{
  color: rgba(255,255,255,0.92) !important;
}

/* (Optional) make sure the trigger stays readable too */
.cd-trigger,
.cd-trigger *{
  color: rgba(255,255,255,0.75) !important;
}

/* ---- preset gallery ---- */
.pg-wrap{
  width: 100%;
  max-width: 1100px;
  margin: 18px auto 0 auto;
}
.pg-title{
  text-align: center;
  margin-bottom: 14px;
}
.pg-h1{
  font-size: 34px;
  font-weight: 800;
  line-height: 1.1;

  /* ✅ theme-aware */
  color: var(--body-text-color);
}
.pg-h2{
  font-size: 14px;
  font-weight: 600;
  color: var(--body-text-color-subdued);
  margin-top: 6px;
}

.pg-grid{
  display: grid;
  grid-template-columns: repeat(3, minmax(0, 1fr)); /* 3 per row */
  gap: 18px;
}

.pg-card{
  border: none;
  background: transparent;
  padding: 0;
  cursor: pointer;
  border-radius: 12px;
  overflow: hidden;
  position: relative;
  transform: translateZ(0);
}

.pg-img{
  width: 100%;
  height: 220px;              /* adjust to match your look */
  object-fit: cover;
  display: block;
  border-radius: 12px;
  transition: transform 160ms ease, filter 160ms ease, opacity 160ms ease;
}

/* hover: slight zoom on hovered card */
.pg-card:hover .pg-img{
  transform: scale(1.02);
}

/* dim others while hovering */
.pg-card[data-dim="true"] .pg-img{
  opacity: 0.35;
  filter: saturate(0.9);
}

/* keep hovered/active crisp */
.pg-card[data-active="true"] .pg-img{
  opacity: 1.0;
  filter: none;
}


"""


css += """
/* ---- AudioDropUpload ---- */
.aud-wrap{
  width: 100%;
  max-width: 720px;
}
.aud-drop{
  border: 2px dashed var(--body-text-color-subdued);
  border-radius: 16px;
  padding: 18px;
  text-align: center;
  cursor: pointer;
  user-select: none;
  color: var(--body-text-color);
  background: var(--block-background-fill);
}
.aud-drop.dragover{
  border-color: rgba(255,255,255,0.35);
  background: rgba(255,255,255,0.06);
}
.aud-hint{
  color: var(--body-text-color-subdued);
  font-size: 0.95rem;
  margin-top: 6px;
}
/* pill row like your other controls */
.aud-row{
  display: none;
  align-items: center;
  gap: 10px;
  background: #0b0b0b;
  border-radius: 9999px;
  padding: 8px 10px;
}
.aud-player{
  flex: 1;
  width: 100%;
  height: 34px;
  border-radius: 9999px;
}
.aud-remove{
  appearance: none;
  border: none;
  background: transparent;
  color: rgba(255,255,255);
  cursor: pointer;
  width: 36px;
  height: 36px;
  border-radius: 9999px;
  display: inline-flex;
  align-items: center;
  justify-content: center;
  padding: 0;
  transition: background 120ms ease, color 120ms ease, opacity 120ms ease;
  opacity: 0.9;
  flex: 0 0 auto;
}
.aud-remove:hover{
  background: rgba(255,255,255,0.08);
  color: rgb(255,255,255);
  opacity: 1;
}
.aud-filelabel{
  margin: 10px 6px 0;
  color: var(--body-text-color-subdued);
  font-size: 0.95rem;
  display: none;
}
#audio_input_hidden { display: none !important; }
"""

# Hiding Gradio Footer, Branding and Settings
css += """
footer {
    display: none !important;
}
.gradio-container footer {
    display: none !important;
}
div.footer {
    display: none !important;
}
.flagging {
    display: none !important;
}
/* Hide the 'Use via API' link if visible */
.api-logo, .built-with {
    display: none !important;
}
"""


def apply_example(idx: str):
    idx = int(idx)

    # Read the example row from your list
    img, prompt_txt, cam, res, mode, vid, aud, end_img = examples_list[idx]

    img_path = img if img else None
    vid_path = vid if vid else None
    aud_path = aud if aud else None

    input_image_update = img_path
    prompt_update = prompt_txt
    camera_update = cam
    resolution_update = res
    mode_update = mode
    video_update = gr.update(value=vid_path, visible=(mode == "Motion Control"))
    audio_update = aud_path
    end_image = end_img

    return (
        input_image_update,
        prompt_update,
        camera_update,
        resolution_update,
        mode_update,
        video_update,
        audio_update,
        audio_update,
        end_image,
    )


####################################################################################################
### PART 20: Gradio UI Layout & Launch (CPU-OPTIMIZED & GPU-GENERATION SPLIT)
####################################################################################################
import requests
import time

# JS Function to handle download request via PostMessage
js_download_video = """
async (video) => {
    if (!video) { 
        alert("لطفاً ابتدا ویدیو را تولید کنید."); 
        return; 
    }
    
    let fileUrl = "";
    
    // پیدا کردن لینک فایل از داخل ساختار پیچیده خروجی گاردریو نسخه 4
    if (typeof video === 'string') {
        fileUrl = video;
    } else if (video && video.video && typeof video.video.url === 'string') {
        fileUrl = video.video.url;
    } else if (video && video.video && typeof video.video.path === 'string') {
        fileUrl = video.video.path;
    } else if (video && typeof video.url === 'string') {
        fileUrl = video.url;
    } else if (video && typeof video.path === 'string') {
        fileUrl = video.path;
    }

    if (!fileUrl) {
        alert("خطا: مسیر ویدیو یافت نشد.");
        return;
    }

    if (fileUrl && !fileUrl.startsWith('http') && !fileUrl.startsWith('blob:')) { 
        let cleanPath = fileUrl.startsWith('/') ? fileUrl.substring(1) : fileUrl;
        
        // اطمینان از قرار گرفتن کلمه file= برای گاردریو
        if (!cleanPath.startsWith('gradio_api/') && !cleanPath.startsWith('file=')) {
            cleanPath = 'file=' + cleanPath;
        }
        
        fileUrl = window.location.origin + "/" + cleanPath;
    }
    
    if (fileUrl) {
        console.log("Sending download request for:", fileUrl);
        window.parent.postMessage({ type: 'DOWNLOAD_REQUEST', url: fileUrl }, '*');
    }
}
"""

def enhance_prompt_on_cpu(image_path: str, prompt: str, mode: str):
    """
    این تابع روی CPU اجرا می‌شود و هیچ سهمیه‌ای از GPU کم نمی‌کند.
    """
    if mode not in ['تبدیل تصویر به ویدیو', 'ویدیو با دو تصویر'] or not image_path:
        return prompt

    print("Running prompt enhancement on CPU...")
    url = 'https://ezmarynoori-vidtolani.hf.space/api/enhance-animation-prompt'
    try:
        with open(image_path, 'rb') as f:
            files = {'image': f}
            data = {'prompt': prompt, 'is_extension': 'false'}
            response = requests.post(url, files=files, data=data, timeout=60)
            
            if response.status_code == 200:
                result = response.json()
                enhanced = result.get("animation_prompt", prompt)
                print(f"Success! Enhanced prompt: {enhanced[:50]}...")
                return enhanced
            else:
                print(f"API Error {response.status_code}: {response.text}")
                return prompt
    except Exception as e:
        print(f"CPU Enhancement failed (using original): {e}")
        return prompt

def apply_example(idx: str):
    idx = int(idx)
    img, prompt_txt, cam, res, mode, vid, aud, end_img, dur = examples_list[idx]
    return (
        img or None, prompt_txt, cam, dur, res, mode,
        gr.update(value=vid or None, visible=(mode == "Motion Control")),
        aud or None, aud or None, end_img or None,
        gr.update(value=None), gr.update(visible=False)
    )

# تعریف متغیرهای متنی برای دکمه‌ها با استایل‌های داخلی (کوچک کردن کلمه پیشفرض)
ENHANCE_YES_TEXT = "دستور بهینه شود <span style='font-size: 0.75em; font-weight: normal; opacity: 0.75;'>(پیشفرض)</span> ✨"
ENHANCE_NO_TEXT = "دستور بهینه نشود ✋"

# --- توابع کنترل کننده (بدون وابستگی محلی) ---

def ui_lock_and_enhance(first_frame, prompt, mode, enhance_toggle, audio_input, duration):
    """
    مرحله ۱: قفل کردن UI و بررسی اینکه آیا پرامپت نیاز به بهینه‌سازی دارد یا خیر
    """
    # بررسی محدودیت زمانی برای فایل صوتی
    if audio_input is not None and float(duration) > 5.0:
        raise gr.Error("در صورت وجود همزمان فایل صوتی امکان ساخت فقط تا پنج ثانیه امکان پذیر است")

    if enhance_toggle == ENHANCE_YES_TEXT:
        yield (
            gr.Button(value="⏳ در حال بهینه سازی پرامپت (CPU)...", interactive=False),
            gr.update(), 
            gr.update(), 
            None 
        )
        
        enhanced = enhance_prompt_on_cpu(first_frame, prompt, mode)
        
        yield (
            gr.Button(value="🚀 در حال ساخت ویدیو (GPU)...", interactive=False),
            gr.update(value=enhanced), 
            enhanced, 
            None
        )
    else:
        # اگر کاربر نخواست پرامپت بهینه شود، مستقیما به مرحله تولید می‌رویم
        yield (
            gr.Button(value="🚀 در حال ساخت ویدیو (GPU)...", interactive=False),
            gr.update(value=prompt), 
            prompt, 
            None
        )

@spaces.GPU(duration=get_duration)
def ui_generate_video(
    first_frame, end_frame, enhanced_prompt, duration, input_video,
    radioanimated_mode, enhance_toggle, seed, randomize_seed,
    height, width, camera_lora, audio_input, progress=gr.Progress(track_tqdm=True)
):
    """
    مرحله ۲: ساخت ویدیو با استفاده از GPU
    """
    # بررسی مجدد محدودیت زمانی برای اطمینان در مرحله ساخت
    if audio_input is not None and float(duration) > 5.0:
        raise gr.Error("در صورت وجود همزمان فایل صوتی امکان ساخت فقط تا پنج ثانیه امکان پذیر است")

    video_path = generate_video(
        first_frame, end_frame, enhanced_prompt, duration, input_video,
        radioanimated_mode, False, seed, randomize_seed,
        height, width, camera_lora, audio_input, progress
    )
    return (
        gr.Button(value="🤩 ساخت ویدیو", interactive=True),
        video_path,
        gr.Button(visible=True)
    )


# کدهای جاوااسکریپت قدرتمند برای بازکردن قفل دکمه هنگام خطا
relocate_js = r"""
(() => { 
    function getGradioRoot() {
        const app = document.querySelector('gradio-app');
        return app && app.shadowRoot ? app.shadowRoot : document;
    }

    function moveIntoFooter() { 
        const root = getGradioRoot();
        const p = root.querySelector("#prompt_ui");
        const f = p ? p.querySelector(".ds-footer") : null; 
        if (!f) return false; 
        
        const d = root.querySelector("#duration_ui .cd-wrap");
        const r = root.querySelector("#resolution_ui .cd-wrap");
        const c = root.querySelector("#camera_ui .cd-wrap"); 
        if (!d || !r || !c) return false; 
        
        f.appendChild(d); f.appendChild(r); f.appendChild(c); 
        return true; 
    } 
    
    function checkAndReset(mutations) {
        let errorFound = false;
        
        // بررسی افزوده شدن Toast ها
        if (mutations) {
            mutations.forEach(m => {
                m.addedNodes.forEach(node => {
                    if (node.nodeType === 1) {
                        const txt = (node.textContent || "").toLowerCase();
                        if (txt.includes("quota") || txt.includes("exceeded") || txt.includes("error") || txt.includes("خطا") || txt.includes("فایل صوتی")) {
                            errorFound = true;
                        }
                        if (node.classList && node.classList.contains("toast-wrap")) {
                            errorFound = true; 
                        }
                    }
                });
            });
        }

        // بررسی متون در کل صفحه (حتی مواردی که توسط کد شما مخفی شده‌اند)
        const root = getGradioRoot();
        const fullText = ((document.body.textContent || "") + " " + (root.textContent || "")).toLowerCase();
        if (fullText.includes("exceeded your gpu quota") || fullText.includes("gpu quota")) {
            errorFound = true;
        }

        if (errorFound && !window._resetFiredBtn) {
            window._resetFiredBtn = true;
            console.log("Error or Quota detected! Forcing reset...");
            
            // کلیک کردن دکمه مخفی پایتون که صف رو دور می‌زند
            const rb = root.querySelector('#reset_btn');
            if (rb) {
                const btn = rb.tagName === 'BUTTON' ? rb : rb.querySelector('button');
                if (btn) btn.click();
            }
            
            // باز کردن فیزیکی قفل دکمه تولید (احتیاط ثانویه)
            const gbWrap = root.querySelector('#generate_btn');
            if (gbWrap) {
                const gb = gbWrap.tagName === 'BUTTON' ? gbWrap : gbWrap.querySelector('button');
                if (gb) {
                    gb.innerText = "🤩 ساخت ویدیو";
                    gb.disabled = false;
                    gb.classList.remove("disabled"); 
                    gb.style.pointerEvents = "auto";
                }
            }
            
            // جلوگیری از کلیک مکرر به مدت ۵ ثانیه
            setTimeout(() => { window._resetFiredBtn = false; }, 5000);
        }
    }

    function setupErrorObserver() {
        const observer = new MutationObserver(checkAndReset);
        observer.observe(document.body, { childList: true, subtree: true });
        
        const root = getGradioRoot();
        if (root !== document) {
            observer.observe(root, { childList: true, subtree: true });
        }
        
        // اسکن دائمی صفحه هر 1 ثانیه به عنوان روش تضمینی
        setInterval(() => checkAndReset(), 1000);
    }
    
    const tick = () => { 
        if (!moveIntoFooter()) requestAnimationFrame(tick); 
        else setupErrorObserver(); 
    }; 
    requestAnimationFrame(tick); 
})();
"""

with gr.Blocks(title="LTX-2 Video Distilled 🎥🔈") as demo:
    
    # مخفی کردن فیزیکی دکمه ریست بدون استفاده از visible=False
    gr.HTML("<style>#reset_btn { display: none !important; }</style>")
    
    gr.HTML(
        """
        <div style="text-align: center; padding: 20px;">
            <h1 style="font-size: 28px; font-weight: bold; margin-bottom: 10px; color: var(--body-text-color);">
                ساخت ویدیو با هوش مصنوعی
            </h1>
            <p style="font-size: 18px; color: var(--body-text-color-subdued); margin: 0;">
                با پشتیبانی از صدا و دو تصویر
            </p>
        </div>
        """
    )
    
    with gr.Column(elem_id="col-container"):
        with gr.Row(elem_id="mode-row"):
            radioanimated_mode = RadioAnimated(choices=["تبدیل تصویر به ویدیو", "ویدیو با دو تصویر"], value="تبدیل تصویر به ویدیو", elem_id="radioanimated_mode")
        with gr.Row():
            with gr.Column(elem_id="step-column"):
                with gr.Row():
                    first_frame = gr.Image(label="تصویر اول (برای بهینه‌سازی پرامپت الزامی است)", type="filepath", height=256)
                    end_frame = gr.Image(label="تصویر آخر (اختیاری)", type="filepath", height=256, visible=False)
                    input_video = gr.Video(label="Motion Reference Video", height=256, visible=False)
                
                relocate = gr.HTML(value="", html_template="<div></div>", js_on_load=relocate_js)
                
                prompt_ui = PromptBox(value="این تصویر را با حرکت سینمایی و انیمیشن روان زنده کن", elem_id="prompt_ui")
                audio_input = gr.File(label="Audio (Optional)", file_types=["audio"], type="filepath", elem_id="audio_input_hidden")
                audio_ui = AudioDropUpload(target_audio_elem_id="audio_input_hidden", elem_id="audio_ui")
                prompt = gr.Textbox(label="Prompt", value="این تصویر را با حرکت سینمایی و انیمیشن روان زنده کن", lines=3, max_lines=3, visible=False)
                
                with gr.Accordion("تنظیمات پیشرفته", open=False, visible=False):
                    seed = gr.Slider(label="سید (Seed)", minimum=0, maximum=MAX_SEED, value=DEFAULT_SEED, step=1)
                    randomize_seed = gr.Checkbox(label="استفاده از سید تصادفی", value=True)
            
            with gr.Column(elem_id="step-column"):
                output_video = gr.Video(label="ویدیوی ساخته شده", autoplay=True, height=512, interactive=False)
                with gr.Row():
                    download_btn = gr.Button("📥 دانلود ویدیو", variant="secondary", size="sm", scale=0, visible=False)
                with gr.Row(elem_id="controls-row"):
                    duration_ui = CameraDropdown(choices=["3s", "5s", "8s", "10s"], value="5s", title="مدت زمان ویدیو", elem_id="duration_ui")
                    duration = gr.Slider(label="Duration (seconds)", minimum=1.0, maximum=10.0, value=5.0, step=0.1, visible=False)
                    ICON_16_9, ICON_1_1, ICON_9_16 = ("<svg viewBox='0 0 24 24' fill='none' aria-hidden='true'><rect x='3' y='7' width='18' height='10' rx='2' stroke='currentColor' stroke-width='2'/></svg>", "<svg viewBox='0 0 24 24' fill='none' aria-hidden='true'><rect x='6' y='6' width='12' height='12' rx='2' stroke='currentColor' stroke-width='2'/></svg>", "<svg viewBox='0 0 24 24' fill='none' aria-hidden='true'><rect x='7' y='3' width='10' height='18' rx='2' stroke='currentColor' stroke-width='2'/></svg>")
                    resolution_ui = CameraDropdown(choices=[{"label": "16:9", "value": "16:9", "icon": ICON_16_9}, {"label": "1:1", "value": "1:1", "icon": ICON_1_1}, {"label": "9:16", "value": "9:16", "icon": ICON_9_16}], value="16:9", title="ابعاد تصویر", elem_id="resolution_ui")
                    width = gr.Number(label="Width", value=DEFAULT_1_STAGE_WIDTH, precision=0, visible=False)
                    height = gr.Number(label="Height", value=DEFAULT_1_STAGE_HEIGHT, precision=0, visible=False)
                    
                    camera_choices_fa = [
                        {"label": "بدون افکت", "value": "No LoRA"},
                        {"label": "ثابت", "value": "Static"},
                        {"label": "جزئیات بیشتر", "value": "Detailer"},
                        {"label": "زوم به داخل", "value": "Zoom In"},
                        {"label": "زوم به بیرون", "value": "Zoom Out"},
                        {"label": "حرکت به چپ", "value": "Slide Left"},
                        {"label": "حرکت به راست", "value": "Slide Right"},
                        {"label": "حرکت به پایین", "value": "Slide Down"},
                        {"label": "حرکت به بالا", "value": "Slide Up"},
                    ]
                    camera_ui = CameraDropdown(choices=camera_choices_fa, value="No LoRA", title="افکت دوربین (LoRA)", elem_id="camera_ui")
                    camera_lora = gr.Dropdown(label="Camera Control LoRA", choices=[(c["label"], c["value"]) for c in camera_choices_fa], value="No LoRA", visible=False)
                
                # استایل‌های بهینه‌شده برای کوچکتر کردن دکمه‌ها و قرار دادن در مرکز صفحه
                gr.HTML("""
                <style>
                #enhance-toggle-col {
                    display: flex !important;
                    flex-direction: column !important;
                    align-items: center !important;
                    justify-content: center !important;
                    margin: 15px auto !important;
                    width: 100% !important;
                    text-align: center !important;
                }
                #enhance_toggle {
                    display: flex !important;
                    justify-content: center !important;
                    align-items: center !important;
                    width: 100% !important;
                }
                #enhance_toggle .ra-wrap {
                    margin: 0 auto !important;
                }
                /* استایل برای کوچکتر کردن سایز دکمه‌های RadioAnimated به طور خاص */
                #enhance_toggle .ra-label {
                    padding: 7px 12px !important;
                    font-size: 12.5px !important;
                }
                .enhance-helper-text {
                    font-size: 11px; /* متن راهنما نیز کمی کوچکتر شد */
                    color: rgba(255, 255, 255, 0.55);
                    text-align: center;
                    margin-top: 8px;
                    margin-left: auto;
                    margin-right: auto;
                    max-width: 90%;
                    line-height: 1.5;
                }
                </style>
                """)

                # افزودن سوییچ پرامپت با متون سفارشی
                with gr.Column(elem_id="enhance-toggle-col"):
                    enhance_toggle = RadioAnimated(
                        choices=[ENHANCE_YES_TEXT, ENHANCE_NO_TEXT], 
                        value=ENHANCE_YES_TEXT, 
                        elem_id="enhance_toggle"
                    )
                    gr.HTML('<div class="enhance-helper-text">بهترین حالت برای درک بهتر دستور و ساخت ویدیو بر اساس پرامپت شما، بهتره حالت روی «بهینه شود» باشه.</div>')

                generate_btn = gr.Button("🤩 ساخت ویدیو", variant="primary", elem_classes="button-gradient", elem_id="generate_btn")
                
                reset_btn = gr.Button("Reset", elem_id="reset_btn")

    # اتصال رویدادها
    camera_ui.change(fn=lambda x: x, inputs=camera_ui, outputs=camera_lora, api_visibility="private")
    radioanimated_mode.change(fn=on_mode_change, inputs=radioanimated_mode, outputs=[input_video, end_frame], api_visibility="private")
    duration_ui.change(fn=apply_duration, inputs=duration_ui, outputs=[duration], api_visibility="private")
    resolution_ui.change(fn=apply_resolution, inputs=resolution_ui, outputs=[width, height], api_visibility="private")
    prompt_ui.change(fn=lambda x: x, inputs=prompt_ui, outputs=prompt, api_visibility="private")
    audio_ui.change(fn=lambda v: None if v == "__CLEAR__" or not v else gr.update(), inputs=audio_ui, outputs=audio_input, api_visibility="private")
    download_btn.click(fn=None, inputs=[output_video], js=js_download_video)
    
    reset_btn.click(
        fn=lambda: gr.Button(value="🤩 ساخت ویدیو", interactive=True),
        inputs=[],
        outputs=[generate_btn],
        api_visibility="private",
        queue=False 
    )
    
    # زنجیره اصلی ساخت ویدیو
    generate_btn.click(
        fn=ui_lock_and_enhance,
        inputs=[first_frame, prompt, radioanimated_mode, enhance_toggle, audio_input, duration],
        outputs=[generate_btn, prompt_ui, prompt, output_video]
    ).then(
        fn=ui_generate_video,
        inputs=[
            first_frame, end_frame, prompt, 
            duration, input_video, radioanimated_mode, enhance_toggle, 
            seed, randomize_seed, height, width, camera_lora, audio_input
        ],
        outputs=[generate_btn, output_video, download_btn]
    )

    # منطق نمونه ها همراه با زمان
    examples_list = [
        ["examples/supergirl-2.png", "A fuzzy puppet superhero character resembling a female puppet with blonde hair and a blue superhero suit sleeping in bed and just waking up, she gradually gets up, rubbing her eyes and looking at her dog that just popped on the bed. the scene feels chaotic, comedic, and emotional with expressive puppet reactions, cinematic lighting, smooth camera motion, shallow depth of field, and high-quality puppet-style animation", "Static", "16:9", "تبدیل تصویر به ویدیو", None, "examples/supergirl.m4a", None, "5s"],
        ["examples/frame3.png", "انار خوردن یک خانم با لباس سفید و گفتن وای چقدر خوشمزه است به فارسی . حتما به فارسی باید بگوید", "Static", "16:9", "ویدیو با دو تصویر", None, None, "examples/frame4.png", "10s"],
        ["examples/supergirl.png", "A fuzzy puppet superhero character resembling a female puppet with blonde hair and a blue superhero suit stands inside an icy cave made of frozen walls and icicles, she looks panicked and frantic, rapidly turning her head left and right and scanning the cave while waving her arms and shouting angrily and desperately, mouthing the words “where the hell is my dog,” her movements exaggerated and puppet-like with high energy and urgency, suddenly a second puppet dog bursts into frame from the side, jumping up excitedly and tackling her affectionately while licking her face repeatedly, she freezes in surprise and then breaks into relief and laughter as the dog continues licking her, the scene feels chaotic, comedic, and emotional with expressive puppet reactions, cinematic lighting, smooth camera motion, shallow depth of field, and high-quality puppet-style animation", "No LoRA", "16:9", "تبدیل تصویر به ویدیو", None, None, None, "5s"],
        ["examples/highland.png", "Realistic POV selfie-style video in a snowy, foggy field. Two shaggy Highland cows with long curved horns stand ahead. The camera is handheld and slightly shaky. The woman filming talks nervously and excitedly in a vlog tone: \"Oh my god guys… look how big those horns are… I’m kinda scared.\" The cow on the left walks toward the camera in a cute, bouncy, hopping way, curious and gentle. Snow crunches under its hooves, breath visible in the cold air. The horns look massive from the POV. As the cow gets very close, its wet nose with slight dripping fills part of the frame. She laughs nervously but reaches out and pets the cow. The cow makes deep, soft, interesting mooing and snorting sounds, calm and friendly. Ultra-realistic, natural lighting, immersive audio, documentary-style realism.", "No LoRA", "16:9", "تبدیل تصویر به ویدیو", None, None, None, "5s"],
        ["examples/wednesday.png", "A cinematic dolly out of Wednesday Addams frozen mid-dance on a dark, blue-lit ballroom floor as students move indistinctly behind her, their footsteps and muffled music reduced to a distant, underwater thrum; the audio foregrounds her steady breathing and the faint rustle of fabric as she slowly raises one arm, never breaking eye contact with the camera, then after a deliberately long silence she speaks in a flat, dry, perfectly controlled voice, “I don’t dance… I vibe code,” each word crisp and unemotional, followed by an abrupt cutoff of her voice as the background sound swells slightly, reinforcing the deadpan humor, with precise lip sync, minimal facial movement, stark gothic lighting, and cinematic realism.", "Zoom Out", "16:9", "تبدیل تصویر به ویدیو", None, None, None, "5s"],
        ["examples/astronaut.png", "An astronaut hatches from a fragile egg on the surface of the Moon, the shell cracking and peeling apart in gentle low-gravity motion. Fine lunar dust lifts and drifts outward with each movement, floating in slow arcs before settling back onto the ground. The astronaut pushes free in a deliberate, weightless motion, small fragments of the egg tumbling and spinning through the air. In the background, the deep darkness of space subtly shifts as stars glide with the camera's movement, emphasizing vast depth and scale. The camera performs a smooth, cinematic slow push-in, with natural parallax between the foreground dust, the astronaut, and the distant starfield. Ultra-realistic detail, physically accurate low-gravity motion, cinematic lighting, and a breath-taking, movie-like shot.", "Static", "1:1", "تبدیل تصویر به ویدیو", None, None, None, "5s"],
    ]

    preset_gallery = PresetGallery(
        items=[{"thumb": "examples/supergirl-2.png", "label": "تصویر و صدا به ویدیو"}, {"thumb": "examples/frame3.png", "label": "تصویر اول و آخر"}, {"thumb": "examples/supergirl.png", "label": "تصویر به ویدیو (عروسک)"}, {"thumb": "examples/highland.png", "label": "تصویر به ویدیو (گاو)"}, {"thumb": "examples/wednesday.png", "label": "تصویر به ویدیو (ونزدی)"}, {"thumb": "examples/astronaut.png", "label": "تصویر به ویدیو (فضانورد)"}],
        title="نمونه ها",
    )

    preset_gallery.change(
        fn=apply_example,
        inputs=preset_gallery,
        outputs=[first_frame, prompt_ui, camera_ui, duration_ui, resolution_ui, radioanimated_mode, input_video, audio_input, audio_ui, end_frame, output_video, download_btn],
        api_visibility="private",
    )

if __name__ == "__main__":
    demo.launch(ssr_mode=False, mcp_server=True, css=css, allowed_paths=["./examples"])