kandinskytest

app.py

@@ -1,24 +1,24 @@
 import gradio as gr
 from transformers import pipeline
 from spaces import GPU  # Import the GPU decorator for ZeroGPU
+from PIL import Image
 
-# Decorate the function to indicate it needs GPU resources
+# Use @GPU to allocate a GPU when running the video generation function
 @GPU
-def generate_text(prompt):
-    # Load the model within the function so that it only runs on GPU when the function is called
-    model = pipeline("text-generation", model="EleutherAI/gpt-neo-125M", device=0)
-
-    return model(prompt, max_length=200, temperature=0.7, top_p=0.9, stop=["."])[0]["generated_text"]
-
-
+def generate_video(prompt):
+    # Load the Kandinsky video model
+    video_model = pipeline("video-generation", model="ai-forever/KandinskyVideo_1_1", device=0)
+    # Generate video based on the prompt
+    video = video_model(prompt)
+    return video  # Ensure this returns the video file or frames
 
 # Create the Gradio interface
 interface = gr.Interface(
-    fn=generate_text,
+    fn=generate_video,
     inputs=gr.Textbox(label="Enter your prompt here"),
-    outputs=gr.Textbox(label="Generated Text"),
-    title="AI Text Generator",
-    description="This app generates text based on your input prompt. Try it out!",
+    outputs="video",
+    title="AI Video Generator",
+    description="This app generates a short video based on your input prompt using KandinskyVideo_1_1.",
     theme="dark"
 )
 

requirements.txt

@@ -1,2 +1,4 @@
 gradio
-transformers==4.31.0
+transformers
+torch
+Pillow