Update app.py

app.py

@@ -1,9 +1,7 @@
 import gradio as gr
-import spaces
 import torch
 from transformers import AutoTokenizer, AutoModel
 import plotly.graph_objects as go
-import numpy as np
 
 model_name = "mistralai/Mistral-7B-v0.1"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -13,44 +11,44 @@ model = None
 if tokenizer.pad_token is None:
     tokenizer.pad_token = tokenizer.eos_token
 
-@spaces.GPU
 def get_embedding(text):
     global model
     if model is None:
-        model = AutoModel.from_pretrained(model_name).cuda()
-        model.resize_token_embeddings(len(tokenizer))
+        model = AutoModel.from_pretrained(model_name, device_map="auto", torch_dtype=torch.float16)
     
-    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512).to('cuda')
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512).to(model.device)
     with torch.no_grad():
         outputs = model(**inputs)
-    return outputs.last_hidden_state.mean(dim=1).squeeze().cpu().numpy()
+    return outputs.last_hidden_state.mean(dim=1).squeeze().cpu()
 
 def reduce_to_3d(embedding):
     return embedding[:3]
 
-@spaces.GPU
 def compare_embeddings(text_input):
-    texts = [t.strip() for t in text_input.split('\n') if t.strip()]
-    embeddings = [get_embedding(text) for text in texts]
-    embeddings_3d = [reduce_to_3d(emb) for emb in embeddings]
-    
-    fig = go.Figure()
+    try:
+        texts = [t.strip() for t in text_input.split('\n') if t.strip()]
+        embeddings = [get_embedding(text) for text in texts]
+        embeddings_3d = [reduce_to_3d(emb) for emb in embeddings]
+        
+        fig = go.Figure()
 
-    # Add origin point (black)
-    fig.add_trace(go.Scatter3d(x=[0], y=[0], z=[0], mode='markers', name='Origin',
-                               marker=dict(size=5, color='black')))
+        # Add origin point (black)
+        fig.add_trace(go.Scatter3d(x=[0], y=[0], z=[0], mode='markers', name='Origin',
+                                   marker=dict(size=5, color='black')))
 
-    # Add lines and points for each text embedding
-    colors = ['red', 'blue', 'green', 'purple', 'orange', 'cyan', 'magenta', 'yellow']
-    for i, emb in enumerate(embeddings_3d):
-        color = colors[i % len(colors)]
-        fig.add_trace(go.Scatter3d(x=[0, emb[0]], y=[0, emb[1]], z=[0, emb[2]], 
-                                   mode='lines+markers', name=f'Text {i+1}',
-                                   line=dict(color=color), marker=dict(color=color)))
+        # Add lines and points for each text embedding
+        colors = ['red', 'blue', 'green', 'purple', 'orange', 'cyan', 'magenta', 'yellow']
+        for i, emb in enumerate(embeddings_3d):
+            color = colors[i % len(colors)]
+            fig.add_trace(go.Scatter3d(x=[0, emb[0].item()], y=[0, emb[1].item()], z=[0, emb[2].item()], 
+                                       mode='lines+markers', name=f'Text {i+1}',
+                                       line=dict(color=color), marker=dict(color=color)))
 
-    fig.update_layout(scene=dict(xaxis_title='X', yaxis_title='Y', zaxis_title='Z'))
-    
-    return fig
+        fig.update_layout(scene=dict(xaxis_title='X', yaxis_title='Y', zaxis_title='Z'))
+        
+        return fig
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
 
 iface = gr.Interface(
     fn=compare_embeddings,
@@ -63,4 +61,5 @@ iface = gr.Interface(
     allow_flagging="never"
 )
 
-iface.launch()
+if __name__ == "__main__":
+    iface.launch()