From d35bc3b28c4c4f0d2bf641e53d787d865fc13cef Mon Sep 17 00:00:00 2001 From: Derrick Mwiti <10187095+mwitiderrick@users.noreply.github.com> Date: Tue, 10 Jun 2025 11:40:10 +0300 Subject: [PATCH] Rename vectors --- .../using-multivector-representations.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/qdrant-landing/content/documentation/advanced-tutorials/using-multivector-representations.md b/qdrant-landing/content/documentation/advanced-tutorials/using-multivector-representations.md index 1cb8cfa8c..6275ba7f1 100644 --- a/qdrant-landing/content/documentation/advanced-tutorials/using-multivector-representations.md +++ b/qdrant-landing/content/documentation/advanced-tutorials/using-multivector-representations.md @@ -103,17 +103,17 @@ documents = [ ] query_text = "How does AI help in medicine?" -dense_doc_vectors = [ +dense_documents = [ models.Document(text=doc, model="BAAI/bge-small-en") for doc in documents ] -dense_query_vector = models.Document(text=query_text, model="BAAI/bge-small-en") +dense_query = models.Document(text=query_text, model="BAAI/bge-small-en") -colbert_doc_vectors = [ +colbert_documents = [ models.Document(text=doc, model="colbert-ir/colbertv2.0") for doc in documents ] -colbert_query_vector = models.Document(text=query_text, model="colbert-ir/colbertv2.0") +colbert_query = models.Document(text=query_text, model="colbert-ir/colbertv2.0") ``` @@ -149,8 +149,8 @@ points = [ models.PointStruct( id=i, vector={ - "dense": dense_vectors[i], - "colbert": colbert_vectors[i] + "dense": dense_documents[i], + "colbert": colbert_documents[i] }, payload={"text": documents[i]} ) for i in range(len(documents)) @@ -166,10 +166,10 @@ Now let’s run a search: results = client.query_points( collection_name="dense_multivector_demo", prefetch=models.Prefetch( - query=dense_query_vector, + query=dense_query, using="dense", ), - query=colbert_query_vector, + query=colbert_query, using="colbert", limit=3, with_payload=True