mod app

app.py

@@ -4,7 +4,12 @@ import numpy as np
 import pickle
 import json
 from sentence_transformers import SentenceTransformer
-from transformers import pipeline, RagTokenizer, RagRetriever, RagSequenceForGeneration
+from transformers import (
+    pipeline,
+    RagTokenizer,
+    RagRetriever,
+    RagSequenceForGeneration,
+)
 import torch
 
 # ========================
@@ -102,13 +107,11 @@ class CustomRagRetriever(RagRetriever):
         self.embed_model = embed_model      # Embedding model used for encoding queries
         self.n_docs = n_docs                # Number of top documents to retrieve
         self.tokenizer = tokenizer          # Save tokenizer for internal use if needed
-        # Call the base class constructor with the required arguments.
+        # Override init_retrieval to bypass loading default passages.
+        self.init_retrieval = lambda: None
+        # Call the parent constructor with the required arguments.
         super().__init__(config, question_encoder_tokenizer=tokenizer, generator_tokenizer=tokenizer)
     
-    def init_retrieval(self):
-        # Override to bypass loading the default DPR passages.
-        return
-
     def retrieve(self, query, n_docs=None):
         try:
             if n_docs is None: