Update app.py

app.py

@@ -13,6 +13,11 @@ import tempfile
 from typing import Optional, Tuple, Any
 from groq import Groq
 
+# =========================================================
+# CUDA BACKEND FIX
+# =========================================================
+# Fix for cusolver error
+torch.backends.cuda.preferred_linalg_library("cusolver")
 
 # =========================================================
 # API CONFIGURATION
@@ -36,7 +41,7 @@ pipe = WanPipeline.from_pretrained(
 
 MAX_SEED = np.iinfo(np.int32).max
 FIXED_FPS = 24
-MIN_FRAMES = 8
+MIN_FRAMES = 9  # Must be (4k + 1) format: 9, 13, 17, 21, 25, ...
 MAX_FRAMES = 81
 
 # =========================================================
@@ -70,7 +75,7 @@ Enhanced: "A fluffy orange tabby cat playfully batting at a dangling yarn ball,
 def enhance_prompt(prompt: str) -> str:
     """Enhance the user prompt using Groq LLM API."""
     if not GROQ_API_KEY:
-        return prompt + " (API key not configured - using original prompt)"
+        return prompt
     
     try:
         client = Groq(api_key=GROQ_API_KEY)
@@ -110,8 +115,18 @@ def enhance_prompt(prompt: str) -> str:
 # HELPER FUNCTIONS
 # =========================================================
 def get_num_frames(duration_seconds: float) -> int:
-    """Calculate number of frames based on duration."""
-    return max(MIN_FRAMES, min(MAX_FRAMES, int(duration_seconds * FIXED_FPS)))
+    """
+    Calculate number of frames based on duration.
+    num_frames - 1 must be divisible by 4, so num_frames must be 4k + 1
+    Valid values: 5, 9, 13, 17, 21, 25, 29, 33, 37, 41, 45, 49, 53, 57, 61, 65, 69, 73, 77, 81
+    """
+    raw_frames = int(duration_seconds * FIXED_FPS)
+    # Round to nearest valid frame count (4k + 1)
+    k = round((raw_frames - 1) / 4)
+    num_frames = 4 * k + 1
+    # Clamp to valid range
+    num_frames = max(MIN_FRAMES, min(MAX_FRAMES, num_frames))
+    return num_frames
 
 
 # =========================================================
@@ -146,8 +161,11 @@ def generate_video(
     current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)
     generator = torch.Generator(device=device).manual_seed(current_seed)
     
-    # Calculate frames
+    # Calculate frames (must be 4k + 1)
     num_frames = get_num_frames(duration_seconds)
+    actual_duration = num_frames / FIXED_FPS
+    
+    print(f"Generating video with {num_frames} frames ({actual_duration:.2f}s)")
     
     # Generate video
     output_frames = pipe(
@@ -170,7 +188,7 @@ def generate_video(
     info_log = f"""✅ VIDEO GENERATION COMPLETE!
 {'=' * 50}
 🎬 Video Info:
-   • Duration: {duration_seconds:.1f} seconds
+   • Duration: {actual_duration:.2f} seconds
    • Total Frames: {num_frames}
    • FPS: {FIXED_FPS}
    • Resolution: {width} x {height}
@@ -590,10 +608,10 @@ with gr.Blocks() as demo:
             
             duration_slider = gr.Slider(
                 label="⏱️ Duration (seconds)",
-                minimum=1.0,
-                maximum=4.0,
+                minimum=0.5,
+                maximum=3.5,
                 step=0.5,
-                value=3.0
+                value=2.0
             )
             
             generate_btn = gr.Button(