Update app.py

app.py

@@ -6,8 +6,8 @@ import pdfplumber
 
 # Initialize RAG components
 tokenizer = RagTokenizer.from_pretrained("facebook/rag-sequence-nq")
-retriever = RagRetriever.from_pretrained("facebook/rag-sequence-nq")
-model = RagSequenceForGeneration.from_pretrained("facebook/rag-sequence-nq")
+retriever = RagRetriever.from_pretrained("facebook/wiki_dpr", use_dummy_dataset=True)  # Correct usage of dataset
+model = RagSequenceForGeneration.from_pretrained("facebook/rag-sequence-nq", retriever=retriever)
 
 # Extract text from PDF
 def extract_text_from_pdf(pdf_file):
@@ -54,7 +54,7 @@ if st.button("Get Response"):
             combined_context += "\n" + csv_data.to_string()
 
         # Generate response using RAG
-        inputs = tokenizer(user_input, combined_context, return_tensors="pt", truncation=True)
+        inputs = tokenizer(user_input, return_tensors="pt", truncation=True)
         with torch.no_grad():
             output = model.generate(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'])
         response = tokenizer.batch_decode(output, skip_special_tokens=True)[0]