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NirantK
2023-10-17 11:10:58 +05:30
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qdrant-landing/content/articles/fastembed.md
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@@ -180,7 +180,7 @@ client.add(
Behind the scenes, Qdrant is using FastEmbed to make the text embedding, generate ids if they’re missing and then adding them to the index with metadata.
INDEX TIME: Sequence Diagram for Qdrant and FastEmbed
![INDEX TIME: Sequence Diagram for Qdrant and FastEmbed](/articles_data/fastembed/image2.png)
### Performing Queries
@@ -196,7 +196,7 @@ print(search_result)
Behind the scenes, we first convert the query_text to the embedding and use that to query the vector index.
QUERY TIME: Sequence Diagram for Qdrant and FastEmbed integration
![QUERY TIME: Sequence Diagram for Qdrant and FastEmbed integration](/articles_data/fastembed/image2.png)
By following these steps, you effectively utilize the combined capabilities of FastEmbed and Qdrant, thereby streamlining your embedding generation and retrieval tasks.