🌘w🌖

app.py

@@ -33,7 +33,7 @@ data.add_faiss_index("embedding")
 
 @spaces.GPU
 def search(query: str, k: int = TOP_K):
-    embedded_query = model.encode(query)
+    embedded_query = RAG.encode(query)
     scores, retrieved_examples = data.get_nearest_examples(
         "embedding", embedded_query, k=k
     )
@@ -101,7 +101,9 @@ def talk(message, history):
 TITLE = "RAG"
 
 DESCRIPTION = """
-## Resources used to build this project
+A rag pipeline with a chatbot feature
+
+Resources used to build this project : 
 * embedding model : https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1
 * dataset : https://huggingface.co/datasets/not-lain/wikipedia-small-3000-embedded (used mxbai-colbert-large-v1 to create the embedding column )
 * faiss docs : https://huggingface.co/docs/datasets/v2.18.0/en/package_reference/main_classes#datasets.Dataset.add_faiss_index