Create App.py

App.py

@@ -0,0 +1,69 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+"""
+For more information on `huggingface_hub` Inference API support, please check the docs:
+https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("damo-vilab/modelscope-text-to-video-synthesis")
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+    
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+    
+    messages.append({"role": "user", "content": message})
+
+    # NOTE: Video models don't usually use "streaming" generation, so we'll just call once
+    payload = {
+        "inputs": message,
+        "parameters": {
+            "max_new_tokens": max_tokens,
+            "temperature": temperature,
+            "top_p": top_p,
+        }
+    }
+
+    # Post directly to the model
+    response = client.post(json=payload)
+
+    video_url = response.get("video", None)
+
+    if video_url:
+        yield video_url
+    else:
+        yield "Failed to generate video."
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs:
+https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are generating a creative video.", label="System message"),
+        gr.Slider(minimum=1, maximum=1000, value=250, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=2.0, value=1.0, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.9,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
+
+if __name__ == "__main__":
+    demo.launch()