Update app.py

app.py

@@ -9,14 +9,39 @@ import uuid
 tokenizer = GPT2Tokenizer.from_pretrained('gpt2')
 model = GPT2LMHeadModel.from_pretrained('gpt2')
 from datasets import load_dataset
+# Global dataset loading
+dataset = load_dataset("visionlab/block-towers-10k-3s-trajectory-scale1", split='train')
+
+# Preprocess dataset to build a lookup table for fast access
+# Simplified example: computing average positions (assuming a 2D grid for simplicity)
+lookup_table = {}
+grid_size = 1.0  # Adjust based on your dataset's scale and distribution
+for item in dataset:
+    for record in item['data']['trajectory']:
+        for position in record['data']:
+            xyz = position['xyz']
+            grid_key = (round(xyz[0]/grid_size), round(xyz[1]/grid_size), round(xyz[2]/grid_size))
+            if grid_key not in lookup_table:
+                lookup_table[grid_key] = xyz
+            else:
+                # Update this to handle multiple positions per grid cell if needed
+                pass
+
 class SecondLifeNavigator:
     def __init__(self):
-        self.dataset = self.load_dataset("visionlab/block-towers-10k-3s-trajectory-scale1", split='train')
-        self.position_lookup = self.preprocess_data()
-
-    def load_dataset(self, dataset_name, split='train'):
-        dataset = load_dataset(dataset_name, split=split)
-        return dataset
+        # Assume the dataset and lookup_table are ready to use
+        self.lookup_table = lookup_table
+    
+    def determine_action_sequence(self, current_xyz):
+        # Simplified nearest position lookup using the grid
+        grid_key = (round(current_xyz[0]/grid_size), round(current_xyz[1]/grid_size), round(current_xyz[2]/grid_size))
+        nearest_position = self.lookup_table.get(grid_key)
+        
+        if nearest_position:
+            action_sequence = f"Move to position {nearest_position[0]}, {nearest_position[1]}, {nearest_position[2]}"
+        else:
+            action_sequence = "No suitable position found."
+        return action_sequence
     
     def preprocess_data(self):
         # Initialize an empty dictionary for the lookup table