S3 Vector Store

Amazon S3 Vector Store uses AWS S3 as a persistent storage backend for vector embeddings, enabling scalable and durable similarity search.

Categories: Artificial Intelligence

Type: s3VectorStore/v1

Connections

Version: 1

custom

Properties

Name	Label	Type	Description	Required
accessKeyId	Access Key ID	STRING	AWS access key ID for authentication.	true
secretAccessKey	Secret Access Key	STRING	AWS secret access key for authentication.	true
region	Region	STRING Options us-east-1, us-east-2, us-west-1, us-west-2, ca-central-1, ap-east-1, ap-south-1, ap-south-2, ap-northeast-3, ap-northeast-2, ap-southeast-1, ap-southeast-2, ap-southeast-3, ap-southeast-4, ap-northeast-1, me-south-1, me-central-1, eu-central-1, eu-central-2, eu-west-1, eu-west-2, eu-south-1, eu-south-2, eu-west-3, eu-north-1, af-south-1, sa-east-1, cn-north-1, cn-northwest-1	AWS region where the S3 bucket is located.	true
bucketName	Bucket Name	STRING	The name of the S3 bucket where the vector store data is persisted.	true
key	Key	STRING	The S3 object key (file path) used to store the vector store JSON data.	true

Actions

Delete Documents

Name: delete

Delete documents from the vector store by metadata

Properties

Name	Label	Type	Description	Required
metadataFilter	Metadata Filter	ARRAY Items [{}]	List of metadata key-value pairs to filter by. Entries within a group are ANDed; groups are ORed.	false

Example JSON Structure

{
  "label" : "Delete Documents",
  "name" : "delete",
  "parameters" : {
    "metadataFilter" : [ { } ]
  },
  "type" : "s3VectorStore/v1/delete"
}

Output

This action does not produce any output.

Load Documents

Name: load

Loads documents into the vector store using LLM embeddings.

Properties

Name	Label	Type	Description	Required
metadataFilter	Metadata Filter	ARRAY Items [{}]	List of metadata key-value pairs to filter by. Entries within a group are ANDed; groups are ORed.	false

Example JSON Structure

{
  "label" : "Load Documents",
  "name" : "load",
  "parameters" : {
    "metadataFilter" : [ { } ]
  },
  "type" : "s3VectorStore/v1/load"
}

Output

This action does not produce any output.

Search Documents

Name: search

Query documents from the vector store using LLM embeddings.

Properties

Name	Label	Type	Description	Required
query	Query	STRING	The query to be executed.	true
metadataFilter	Metadata Filter	ARRAY Items [{}]	List of metadata key-value pairs to filter by. Entries within a group are ANDed; groups are ORed.	false
topK	Top K	INTEGER	The top 'k' similar results to return.	false
similarityThreshold	Similarity Threshold	NUMBER	Similarity threshold score to filter the search response by. Only documents with similarity score equal or greater than the threshold will be returned. A threshold value of 0 means any similarity is accepted. A threshold value of 1 means an exact match is required.	false

Example JSON Structure

{
  "label" : "Search Documents",
  "name" : "search",
  "parameters" : {
    "query" : "",
    "metadataFilter" : [ { } ],
    "topK" : 1,
    "similarityThreshold" : 0.0
  },
  "type" : "s3VectorStore/v1/search"
}

Output

The output for this action is dynamic and may vary depending on the input parameters. To determine the exact structure of the output, you need to execute the action.

Update Documents

Name: update

Updates documents in the vector store by deleting existing ones matching the metadata filter and loading new ones using LLM embeddings.

Properties

Name	Label	Type	Description	Required
metadataFilter	Metadata Filter	ARRAY Items [{}]	List of metadata key-value pairs to filter by. Entries within a group are ANDed; groups are ORed.	false

Example JSON Structure

{
  "label" : "Update Documents",
  "name" : "update",
  "parameters" : {
    "metadataFilter" : [ { } ]
  },
  "type" : "s3VectorStore/v1/update"
}

Output

This action does not produce any output.

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