Weaviate
Weaviate is an open-source vector search engine and database that enables efficient storage, retrieval, and management of high-dimensional data, often used in machine learning and AI applications.
Categories: Artificial Intelligence
Type: weaviate/v1
Connections
Version: 1
custom
Properties
| Name | Label | Type | Description | Required |
|---|---|---|---|---|
| url | Weaviate Url | STRING | The URL of the Weaviate instance. | true |
| apiKey | Weaviate API Key | STRING | The API key for the Weaviate API. | 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" : "weaviate/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" : "weaviate/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" : "weaviate/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" : "weaviate/v1/update"
}Output
This action does not produce any output.
How is this guide?
Last updated on