👐 Perform semantic search

Now let's run some vector search queries against our data present in MongoDB.

Fill in any <CODE_BLOCK_N> placeholders and run the cells under the Step 8: Perform semantic search on your data section in the notebook to run vector search queries against your data.

The answers for code blocks in this section are as follows:

CODE_BLOCK_9

Answer

get_embedding(user_query)

CODE_BLOCK_10

Answer

[
    {
        "$vectorSearch": {
            "index": ATLAS_VECTOR_SEARCH_INDEX_NAME,
            "queryVector": query_embedding,
            "path": "embedding",
            "numCandidates": 150,
            "limit": 5
        }
    },
    {
        "$project": {
            "_id": 0,
            "body": 1,
            "score": {"$meta": "vectorSearchScore"}
        }
    }
]

CODE_BLOCK_11

Answer

collection.aggregate(pipeline)