Update app.py

app.py

@@ -1,31 +1,31 @@
-import torch
-import torch.nn.functional as F
-from transformers import AutoTokenizer, AutoModel, AutoImageProcessor
-import gradio as gr
-import spaces
-
-processor = AutoImageProcessor.from_pretrained("nomic-ai/nomic-embed-vision-v1.5")
-vision_model = AutoModel.from_pretrained("nomic-ai/nomic-embed-vision-v1.5", trust_remote_code=True)
-
-@spaces.GPU
-def ImgEmbed(image):
-    print(image);
-    inputs = processor(image, return_tensors="pt")
-
-    img_emb = vision_model(**inputs).last_hidden_state
-    img_embeddings = F.normalize(img_emb[:, 0], p=2, dim=1)
-
-    return img_embeddings[0].tolist();
-
-
-
-with gr.Blocks() as demo:      
-       img = gr.Image();
-       out = gr.Text();
-       
-       btn = gr.Button("Get Embeddings")
-       btn.click(ImgEmbed, [img], [out])
-       
-       
-if __name__ == "__main__":
-    demo.launch(show_api=True)
+import torch
+import torch.nn.functional as F
+from transformers import AutoTokenizer, AutoModel, AutoImageProcessor
+import gradio as gr
+import spaces
+
+processor = AutoImageProcessor.from_pretrained("nomic-ai/nomic-embed-vision-v1.5")
+vision_model = AutoModel.from_pretrained("nomic-ai/nomic-embed-vision-v1.5", trust_remote_code=True)
+
+@spaces.GPU
+def ImgEmbed(image):
+    print(image);
+    inputs = processor(image, return_tensors="pt")
+
+    img_emb = vision_model(**inputs).last_hidden_state
+    img_embeddings = F.normalize(img_emb[:, 0], p=2, dim=1)
+
+    return img_embeddings[0].tolist();
+
+
+
+with gr.Blocks() as demo:      
+       img = gr.Image();
+       out = gr.Text();
+       
+       btn = gr.Button("Get Embeddings")
+       btn.click(ImgEmbed, [img], [out])
+       
+       
+if __name__ == "__main__":
+    demo.launch(show_api=True, mcp_server=True)