Create app.py

app.py

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+import streamlit as st
+from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration
+
+# Load RAG components
+tokenizer = RagTokenizer.from_pretrained("facebook/rag-sequence-nq")
+retriever = RagRetriever.from_pretrained("facebook/rag-sequence-nq", use_dummy_dataset=True)
+rag_model = RagSequenceForGeneration.from_pretrained("facebook/rag-sequence-nq", retriever=retriever)
+
+# Streamlit UI
+st.title("RAG-based Q&A")
+
+query = st.text_input("Enter your question:")
+
+if st.button("Generate Answer"):
+    if query:
+        # Process the input query and generate a response
+        inputs = tokenizer(query, return_tensors="pt")
+        outputs = rag_model.generate(**inputs)
+        response = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+        st.write(f"Answer: {response[0]}")
+    else:
+        st.write("Please enter a question to get an answer.")