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Pinecone

Pinecone is a vector database designed for efficient similarity search and storage of high-dimensional data, commonly used in machine learning and AI applications.

Categories: Artificial Intelligence

Type: pinecone/v1


Connections

Version: 1

custom

Properties

NameLabelTypeDescriptionRequired
apiKeyPinecone API KeySTRINGThe API key for the Pinecone API.true
hostHostSTRINGUrl of the host.true

Actions

Delete Documents

Name: delete

Delete documents from the vector store by metadata

Properties

NameLabelTypeDescriptionRequired
metadataFilterMetadata FilterARRAY
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" : "pinecone/v1/delete"
}

Output

This action does not produce any output.

Load Documents

Name: load

Loads documents into the vector store using LLM embeddings.

Properties

NameLabelTypeDescriptionRequired
metadataFilterMetadata FilterARRAY
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" : "pinecone/v1/load"
}

Output

This action does not produce any output.

Search Documents

Name: search

Query documents from the vector store using LLM embeddings.

Properties

NameLabelTypeDescriptionRequired
queryQuerySTRINGThe query to be executed.true
metadataFilterMetadata FilterARRAY
Items [{}]
List of metadata key-value pairs to filter by. Entries within a group are ANDed; groups are ORed.false
topKTop KINTEGERThe top 'k' similar results to return.false
similarityThresholdSimilarity ThresholdNUMBERSimilarity 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" : "pinecone/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

NameLabelTypeDescriptionRequired
metadataFilterMetadata FilterARRAY
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" : "pinecone/v1/update"
}

Output

This action does not produce any output.

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