trying

app.py

@@ -6,29 +6,27 @@ import gradio as gr
 from datasets import load_dataset
 from transformers import AutoModel
 
-# `LSH` and `Table` imports are necessary in order for the
-# `lsh.pickle` file to load successfully.
-from similarity_utils import LSH, BuildLSHTable, Table
 
 seed = 42
 
 # Only runs once when the script is first run.
-with open("lsh.pickle", "rb") as handle:
-    loaded_lsh = pickle.load(handle)
+with open("index.pickle", "rb") as handle:
+    index = pickle.load(handle)
 
 # Load model for computing embeddings.
-model_ckpt = "abhishek/autotrain-butterflies-new-17716425"
-model = AutoModel.from_pretrained(model_ckpt)
-lsh_builder = BuildLSHTable(model)
-lsh_builder.lsh = loaded_lsh
+feature_extractor = AutoFeatureExtractor.from_pretrained("abhishek/autotrain-butterflies-new-17716425")
+model = AutoModel.from_pretrained("abhishek/autotrain-butterflies-new-17716425")
 
 # Candidate images.
 dataset = load_dataset("huggan/inat_butterflies_top10k")
-candidate_dataset = dataset["train"].shuffle(seed=seed)
+candidate_dataset = dataset["train"]
 
 
 def query(image, top_k):
-    results = lsh_builder.query(image)
+    inputs = feature_extractor(image, return_tensors="pt")
+    model_output = model(**inputs)
+    embedding = model_output.pooler_output
+    results = index.query(embedding)
 
     # Should be a list of string file paths for gr.Gallery to work
     images = []