

# .vectors.upsert algorithm
<a name="vectors-upsert"></a>

The `.vectors.upsert` algorithm is used to add a new embedding or update an existing one for a node.

**Important**  
Updates to vector embeddings are not ACID compliant. For details and best practices to minimize inconsistencies, see [Vector index transaction support](vector-index.md#vector-index-transaction-support).

## `.vectors.upsert`  syntax
<a name="vectors-upsert-syntax"></a>

```
CALL neptune.algo.vectors.upsert(
  "a target node (required)",
  [the embedding to upsert for the target node (required)]
)
YIELD node, embedding, success
RETURN node, embedding, success
```

## `.vectors.upsert`  input
<a name="vectors-upsert-inputs"></a>
+ **a target node**   *(required)*   –   *type:* `Node` or `NodeId`.

  The node for which you want to upsert an embedding.
+ **an embedding**   *(required)*   –   *type:* a list of floating-point values.

  The embedding that you want to upsert for the target node.

  If the node has an existing embedding, this must match the dimension of the existing one or an exception is thrown.

## `.vectors.upsert`  outputs
<a name="vectors-upsert-outputs"></a>

If the target node already has an existing embedding then `.vectors.upsert` replaces it with the one supplied. Otherwise `.vectors.upsert` adds the supplied embedding for the target node.
+ **node**   –   The target node.
+ **embedding**   –   The embedding that was supplied to be upserted.
+ **success**   –   A Boolean value: `true` indicates that the upsert succeded, and `false` that it failed.

## `.vectors.upsert`  query examples
<a name="vectors-upsert-query-example"></a>

```
CALL neptune.algo.vectors.upsert(
  "person933",
  [0.1, 0.2, 0.3, ..]
)
YIELD node, embedding, success
RETURN node, embedding, success
```

```
UNWIND [
  {id: "933", embedding: [1,2,3,4]}, 
  {id: "934", embedding: [-1,-2,-3,-4]}
] as entry 
MATCH (n:person) WHERE id(n)=entry.id WITH n, entry.embedding as embedding
CALL neptune.algo.vectors.upsert(n, embedding) 
YIELD success
RETURN n, embedding, success
```

## Sample  `.vectors.upsert`  output
<a name="vectors-upsert-sample-output"></a>

Here is an example of the output returned by `.vectors.upsert` when run against the sample Wikipedia dataset using the following query:

```
aws neptune-graph execute-query \
  --graph-identifier ${graphIdentifier} \
  --query-string "MATCH (n{\`~id\`:\"0\"})
                       CALL neptune.algo.vectors.get(n)
                       YIELD embedding AS vector
                       MATCH (m{`~id`: '1'})
                       CALL neptune.algo.vectors.upsert(m, vector)
                       YIELD node, embedding, success
                       RETURN node, embedding, success"
  --language open_cypher \
  /tmp/out.txt
{
  "results": [
    {
      "node": {
        "~id": "1",
        "~entityType": "node",
        "~labels": [],
        "~properties": {
          "title": "24-hour clock",
          "views": 2450.62548828125,
          "wiki_id": 9985,
          "paragraph_id": 1,
          "url": "https://simple.wikipedia.org/wiki?curid=9985",
          "langs": 30,
          "text": "A time in the 24-hour clock is written in the form hours:minutes (for example\\, 01:23)\\, or hours:minutes:seconds (01:23:45). Numbers under 10 have a zero in front (called a leading zero); e.g. 09:07. Under the 24-hour clock system\\, the day begins at midnight\\, 00:00\\, and the last minute of the day begins at 23:59 and ends at 24:00\\, which is identical to 00:00 of the following day. 12:00 can only be mid-day. Midnight is called 24:00 and is used to mean the end of the day and 00:00 is used to mean the beginning of the day. For example\\, you would say \"Tuesday at 24:00\" and \"Wednesday at 00:00\" to mean exactly the same time."
        }
      },
      "embedding": [
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  ]
}
```