Redis

Redis is an open-source, in-memory data structure store used as a database, cache, and message broker, known for its high performance and support for various data structures like strings, hashes, lists, sets, and more.

Categories: Artificial Intelligence

Type: redis/v1

Connections

Version: 1

custom

Properties

Name	Label	Type	Description	Required
publicEndpoint	Public Endpoint	STRING		true
username	Username	STRING		true
password	Password	STRING		true
initializeSchema	Initialize Schema	BOOLEAN Options true, false	Whether to initialize the schema.	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" : "redis/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" : "redis/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" : "redis/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" : "redis/v1/update"
}

Output

This action does not produce any output.

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