Update app.py

app.py

@@ -20,7 +20,7 @@ COMFY = Path("/app/ComfyUI")
 MODELS = COMFY / "models"
 OUTPUT = COMFY / "output"
 
-# ✅ Manifest สำหรับตรวจสอบว่าโมเดลครบ (Dockerfile ดาวน์โหลดไว้แล้วตอน Build)
+# ✅ Manifest สำหรับตรวจสอบว่าโมเดลครบ
 DOWNLOAD_MANIFEST = [
  {
  "file": "10Eros_v1-Q3_K_M.gguf",
@@ -60,7 +60,6 @@ DOWNLOAD_MANIFEST = [
 ]
 
 def _check_models(progress_cb=None):
- """ตรวจสอบว่าโมเดลที่ Docker ดาวน์โหลดไว้ครบหรือไม่"""
  if progress_cb:
   progress_cb(0.0, desc="Verifying models...")
  missing = []
@@ -208,8 +207,6 @@ NODE_LABELS = {
  "21": "Preprocessing image",
  "22": "I2V conditioning",
  "30": "Applying user LoRA",
- "40": "Encoding prompt",
- "41": "Encoding negative",
 }
 
 _comfy_proc = None
@@ -273,7 +270,6 @@ def _is_ic_lora(lora_path: str) -> bool:
   return False
  if lora_path in _ic_lora_cache:
   return _ic_lora_cache[lora_path]
-
  result = _detect_ic_lora(lora_path)
  _ic_lora_cache[lora_path] = result
  return result
@@ -281,14 +277,12 @@ def _is_ic_lora(lora_path: str) -> bool:
 def _detect_ic_lora(lora_path: str) -> bool:
  if re.search(r"ic[-_]?lora", lora_path, re.IGNORECASE):
   return True
-
  local = MODELS / "loras" / lora_path
  if local.exists():
   try:
    return _check_safetensors_header(str(local))
   except Exception:
    return False
-
  if "/" in lora_path:
   parts = lora_path.split("/")
   if len(parts) >= 3:
@@ -333,23 +327,33 @@ def _download_user_lora(repo_id: str, filename: str) -> str | None:
   return None
 
 def _build_workflow(prompt: str, steps: int, duration_sec: float, seed: int,
- img_name: str | None = None, user_lora: str | None = None,
- lora_strength: float = 0.6, vid_w: int | None = None,
- vid_h: int | None = None, enable_audio: bool = True) -> dict:
+                    img_name: str | None = None, user_lora: str | None = None,
+                    lora_strength: float = 0.6, vid_w: int | None = None,
+                    vid_h: int | None = None, enable_audio: bool = True) -> dict:
  wf = json.loads(json.dumps(WORKFLOW_TEMPLATE))
  wf["40"]["inputs"]["text"] = prompt
- frames = max(9, int(duration_sec * 24) + 1)
+ 
+ # 🔧 FIX 1: LTX Video ต้องการจำนวนเฟรมเป็นสูตร 8 * N + 1 เสมอ (เช่น 9, 17, 25, 33, 41, 49)
+ # หากคำนวณได้ค่าอื่น ระบบจะบีบอัด Latent แล้วทำให้มิติเวลา (T) กลายเป็น 0 และเกิด Error
+ raw_frames = int(float(duration_sec) * 24) + 1
+ frames = ((raw_frames - 1) // 8) * 8 + 1
+ frames = max(9, frames) # กำหนดขั้นต่ำที่ 9 เฟรม
+ print(f"[workflow] Calculated valid frames: {frames} (for {duration_sec}s duration)", flush=True)
+ 
  wf["5"]["inputs"]["length"] = frames
+ 
+ # 🔧 FIX 2: ไม่ลบ Node สร้าง Audio Latent (50, 51, 52, 53) ออกทั้งหมด
+ # เพราะโมเดล AV ต้องการโครงสร้าง Latent ที่ครบถ้วน หากขาดไปจะทำให้มิติ T=0 และ Crash
+ # แต่เราจะลบเฉพาะ Node Decode เสียง (54) ออกเพื่อประหยัดเวลา CPU ~4 ชั่วโมง
  if not enable_audio:
-  for n in ["49", "50", "51", "52", "53", "54"]:
-   wf.pop(n, None)
-  wf["11"]["inputs"]["latent_image"] = ["5", 0]
-  wf["13"]["inputs"]["samples"] = ["11", 0]
+  wf.pop("54", None) # ลบเฉพาะส่วน Decode เสียง
  else:
   wf["50"]["inputs"]["frames_number"] = frames
+
  if vid_w and vid_h:
   wf["5"]["inputs"]["width"] = vid_w
   wf["5"]["inputs"]["height"] = vid_h
+  
  wf["8"]["inputs"]["steps"] = steps
  wf["10"]["inputs"]["noise_seed"] = seed
 
@@ -563,7 +567,7 @@ def generate(prompt, duration_sec, steps, seed, image_path=None,
 
  if progress:
   progress(0.0, desc="Checking models...")
- _check_models(progress) # ✅ เปลี่ยนจาก _download_models เป็น _check_models
+ _check_models(progress)
 
  if progress:
   progress(0.15, desc="Starting ComfyUI...")
@@ -659,6 +663,7 @@ def generate(prompt, duration_sec, steps, seed, image_path=None,
   print(f"[output] mp4 conversion failed: {e}, returning webp", flush=True)
   out_path = out_dir / "output.webp"
   shutil.copy2(result, out_path)
+  
  elapsed = status_lines[0].split(":")[0] if ":" in status_lines[0] else "?"
  lora_info = f" | LoRA: {user_lora_file}" if user_lora_file else ""
  return str(out_path), f"Done {elapsed} | {mode} | {steps} steps | {duration_sec}s | seed {int(seed)}{lora_info}"
@@ -676,17 +681,14 @@ import gradio as gr
 import random
 
 _all_lora_choices = []
-
 _lora_state = {"mode": "search"}
 
 def _on_lora_interact(value):
  if not value or len(value) < 2:
   repos = _search_hf_loras("ltx 2.3 lora")
   return gr.update(choices=repos, value=None)
-
  if value.endswith(".safetensors"):
   return gr.update(value=value)
-
  if "/" in value:
   parts = value.split("/")
   if len(parts) >= 2:
@@ -702,7 +704,6 @@ def _on_lora_interact(value):
    if len(choices) == 1:
     return gr.update(choices=choices, value=choices[0])
    return gr.update(choices=choices, value=None)
-
  repos = _search_hf_loras(value)
  return gr.update(choices=repos, value=None)
 
@@ -760,10 +761,8 @@ with gr.Blocks(title="LTX 2.3 CPU") as demo:
   global _all_lora_choices
   selected = list(selected_values) if selected_values else []
   print(f"[lora] pick: {selected}", flush=True)
-
   valid = [v for v in selected if "/" in v]
   search_terms = [v for v in selected if "/" not in v and v.strip()]
-
   if search_terms:
    query = " ".join(search_terms)
    repos = _search_hf_loras(query)
@@ -781,7 +780,6 @@ with gr.Blocks(title="LTX 2.3 CPU") as demo:
      _all_lora_choices.append(r)
    print(f"[lora] search '{query}': {len(resolved)} new, {len(_all_lora_choices)} total", flush=True)
    return gr.update(choices=_all_lora_choices, value=valid[:9])
-
   if len(valid) > 9:
    valid = valid[:9]
   return gr.update(choices=_all_lora_choices, value=valid)
@@ -850,7 +848,6 @@ with gr.Blocks(title="LTX 2.3 CPU") as demo:
   fn=_gen,
   inputs=[prompt_in, image_in, lora_picker, lora_strength, audio_in, duration_in, steps_in, seed_in],
   outputs=[video_out, status_out],
-  #api_name="generate",
   api_name="predict",
  )
  gr.Button(visible=False).click(fn=health, outputs=[gr.Textbox(visible=False)], api_name="health")