Changes to be committed:

app.py

@@ -55,7 +55,7 @@ def image_to_image(prompt, image, dimension, flux_client):
     input_image=handle_file(padded_image_path),
     prompt=prompt,
     guidance_scale=2.5,
-    num_inference_steps=25,
+    steps=25,
     randomize_seed=True,
     api_name="/infer"
     )
@@ -68,7 +68,7 @@ def image_to_image(prompt, image, dimension, flux_client):
         pass
     return image[0]
 
-def image_to_video(prompt, image, ltx_client):
+def image_to_video(prompt, image, duration, ltx_client):
     result = ltx_client.predict(
         prompt=prompt,
         input_image_url=None,
@@ -80,13 +80,13 @@ def image_to_video(prompt, image, ltx_client):
     print(result)
     return result
 
-def personalized_video(prompt, image, dimension, request: gr.Request):
+def personalized_video(prompt, image, dimension, duration, request: gr.Request):
     x_ip_token = request.headers['x-ip-token']
     flux_client = Client("black-forest-labs/FLUX.1-Kontext-Dev", headers={"x-ip-token": x_ip_token})
     ltx_client = Client("KingNish/ltx-video-distilled", headers={"x-ip-token": x_ip_token})
     image = image_to_image(prompt, image, dimension, flux_client)
     yield image, None
-    video = image_to_video(prompt, image, ltx_client)
+    video = image_to_video(prompt, image, duration, ltx_client)
     yield image, video
 
 with gr.Blocks() as demo:
@@ -96,6 +96,7 @@ with gr.Blocks() as demo:
             input_image = gr.Image(label="Input Image", type="filepath")
             prompt = gr.Textbox(label="Prompt")
             dimension = gr.Radio(["Square (1024x1024)", "Portrait (768x1360)", "Landscape (1360x768)"], label="Dimension", value="Square (1024x1024)")
+            duration = gr.Slider(minimum=1, maximum=5, value=4, label="Video Duration")
             submit_button = gr.Button("Submit")
         with gr.Column():
             edited_image = gr.Image(label="Edited Image")