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docs(embeddings): use current query_points API in OpenAI example #2455

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docs(embeddings): use current query_points API in OpenAI example #2455

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4 changes: 2 additions & 2 deletions qdrant-landing/content/documentation/embeddings/openai.md
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Expand Up @@ -80,9 +80,9 @@ client.upsert(collection_name, points)
Once the documents are indexed, you can search for the most relevant documents using the same model.

```python
client.search(
client.query_points(
collection_name=collection_name,
query_vector=openai_client.embeddings.create(
query=openai_client.embeddings.create(
input=["What is the best to use for vector search scaling?"],
model=embedding_model,
)
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