diff --git a/common/llms.py b/common/llms.py
index 49ec697..62f341e 100644
--- a/common/llms.py
+++ b/common/llms.py
@@ -107,12 +107,12 @@ def postprocess_new(
 
             records.append(
                 {
-                    "generated_text": text[prompt_length:],
                     "usage": {
                         "completion_tokens": len(sequence) - prompt_tokens,
                         "prompt_tokens": prompt_tokens,
                         "total_tokens": len(sequence),
                     },
+                    "generated_text": text[prompt_length:],
                 }
             )
 
diff --git a/retro/sadtalker.py b/retro/sadtalker.py
index e725bdd..bba2cba 100644
--- a/retro/sadtalker.py
+++ b/retro/sadtalker.py
@@ -83,6 +83,7 @@ class SadtalkerInput(BaseModel):
     still: bool = (
         False  # can crop back to the original videos for the full body aniamtion
     )
+    max_frames: typing.Optional[int] = None
 
 
 try:
@@ -291,6 +292,7 @@ def sadtalker(
             background_enhancer=inputs.background_enhancer,
             preprocess=pipeline.preprocess,
             img_size=pipeline.size,
+            max_frames=inputs.max_frames,
         )
 
         with open(result_path, "rb") as f:
@@ -315,6 +317,7 @@ def animate_from_coeff_generate(
     background_enhancer,
     preprocess,
     img_size,
+    max_frames,
 ):
 
     source_image = x["source_image"].type(torch.FloatTensor)
@@ -392,7 +395,7 @@ def animate_from_coeff_generate(
         roll_c_seq,
     ):
         for out_image in batch:
-            if out_meta.num_frames >= frame_num:
+            if max_frames and out_meta.num_frames > max_frames:
                 break
             out_image = img_as_ubyte(
                 out_image.data.cpu().numpy().transpose([1, 2, 0]).astype(np.float32)
diff --git a/retro/wav2lip.py b/retro/wav2lip.py
index 60afa49..eda45b5 100644
--- a/retro/wav2lip.py
+++ b/retro/wav2lip.py
@@ -82,6 +82,7 @@ class Wav2LipInputs(BaseModel):
         default=480,
     )
     batch_size: int = 256
+    max_frames: typing.Optional[int] = None
 
 
 @app.task(name="wav2lip")
@@ -173,6 +174,8 @@ def main(model, detector, outfile: str, inputs: Wav2LipInputs):
 
     mel_chunks = get_mel_chunks(inputs.audio, fps)
     for idx in tqdm(range(0, len(mel_chunks), inputs.batch_size)):
+        if inputs.max_frames and idx >= inputs.max_frames:
+            break
         if is_static:
             frame_batch = [frame.copy()] * inputs.batch_size
         else: