Update rag_pipeline.py

rag_pipeline.py

@@ -2,18 +2,17 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from sentence_transformers import SentenceTransformer, models
 import numpy as np
 import torch
-import time
 
 class RAGPipeline:
     def __init__(self):
-        print("[RAG] تحميل النماذج العربية...")
+        print("[RAG] تحميل النماذج...")
 
         word_embedding_model = models.Transformer('asafaya/bert-base-arabic')
         pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension())
         self.embedder = SentenceTransformer(modules=[word_embedding_model, pooling_model])
 
-        self.tokenizer = AutoTokenizer.from_pretrained("google/mt5-small")
-        self.model = AutoModelForSeq2SeqLM.from_pretrained("google/mt5-small")
+        self.tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
+        self.model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
 
         self.index = None
         self.chunks = []