Hi,
I’m receiving this error when I try to query my index. I assume this is because I upserted the vectors to the index without any metadata. This is the code I used to insert data:
docs_chunks =
for i in range(0, len(docs), chunk_size):
chunk = docs[i:i + chunk_size]
docs_chunks.append(chunk)
vector_embeddings = embeddings.embed_documents(docs_chunks)
vectors = [(str(uuid.uuid4()), embedding) for embedding in vector_embeddings]
pinecone_index.upsert(vectors=vectors)
Is there any way to delete these existing documents, or update them to contain metadata? I did not document the indexes of the upserted documents anywhere.
If not, is there any other way to fix this error?
Hi @nu.cps.supplierdiver, and thanks for your question.
You’ll want to either:
- Re-upsert the vectors with metadata, or
- Delete the vectors and then re-upsert them with metadata if necessary.
1. Re-Upserting Vectors with Metadata:
If you need metadata, but forgot to add it during the initial upsert, you can simply upsert the vectors again with metadata included. Here’s an example of how to do that:
python
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# Assuming you have document embeddings and want to add metadata
vectors_with_metadata = [
(str(uuid.uuid4()), embedding, {"category": "example"}) # adding metadata
for embedding in vector_embeddings
]
# Upsert vectors with metadata
pinecone_index.upsert(vectors=vectors_with_metadata)
If you didn’t document the IDs of your previously upserted vectors, Pinecone does not automatically overwrite them. So, you’ll need to delete the old ones first.
2. Deleting Existing Vectors:
To clean up the old vectors, you can use Pinecone’s deletion API. If you don’t have the specific vector IDs, you can delete them based on filters (if you’re using Pod-based indexes) or clear the entire index:
Delete vectors by filter (e.g., based on metadata):
python
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pinecone_index.delete(filter={"category": "example"}) # filter by metadata category
Delete all vectors (clear the index):
python
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pinecone_index.delete(delete_all=True)
After deleting the vectors, you can re-upsert them with the appropriate metadata.
See Our guide to deleting data for more details on removing data from your index
Hope this helps!
Best,
Zack