Create app.py

app.py

@@ -0,0 +1,39 @@
+import streamlit as st
+import replicate
+
+# Set the replicate API token
+import os
+os.environ["REPLICATE_API_TOKEN"] = "r8_JSR8xlRoCk6cmq3qEOOThVTn3dAgdPq1bWXdj"
+
+def run_replicate_model(input_params):
+    output = replicate.run(
+        "stability-ai/stable-video-diffusion:3f0457e4619daac51203dedb472816fd4af51f3149fa7a9e0b5ffcf1b8172438",
+        input=input_params
+    )
+    return output
+
+st.title("Stable Video Diffusion")
+st.write("Fill in the input parameters and click on the button to run the Stable Video Diffusion model.")
+
+cond_aug = st.number_input("Conditioning Augmentation", value=0.02)
+decoding_t = st.number_input("Decoding Time", value=7)
+input_image = st.text_input("Input Image URL", "https://example.com/s-widua-icjKmXvsO7U-unsplash.jpg")
+video_length = st.selectbox("Video Length", ["14_frames_with_svd", "other_options"])
+sizing_strategy = st.selectbox("Sizing Strategy", ["maintain_aspect_ratio", "other_options"])
+motion_bucket_id = st.number_input("Motion Bucket ID", value=127)
+frames_per_second = st.number_input("Frames Per Second", value=6)
+
+input_params = {
+    "cond_aug": cond_aug,
+    "decoding_t": decoding_t,
+    "input_image": input_image,
+    "video_length": video_length,
+    "sizing_strategy": sizing_strategy,
+    "motion_bucket_id": motion_bucket_id,
+    "frames_per_second": frames_per_second
+}
+
+if st.button("Run Model"):
+    output_result = run_replicate_model(input_params)
+    st.write("Output:")
+    st.code(output_result, language="json")