Pinecone

The Pinecone node in your workflow is used to query a Pinecone vector database for similar vectors based on a text query.

The Pinecone Node allows you to search a Pinecone vector database for vectors that are most similar to a given text input. It returns a list of similar vectors along with their metadata.

Required Inputs for the Pinecone Node

To use the Pinecone node, you need to provide the following input parameters:

1. Query (string, required): The text you want to search for similar vectors. For example, "AI marketing trends".

2. Number of Results (top_k) (integer, required): How many similar vectors you want to retrieve. The default is 5.

3. Index Name (string, required): The name of the Pinecone index you want to query.

4. Namespace (string, optional): An optional namespace within the Pinecone index to scope your query.

Output

• The node outputs a field called Results, which contains the similar vectors found in the database, along with their metadata.

Example Usage

• If you want to find the top 5 most similar vectors to the phrase "StackAI product launch" in your "company-updates" index, you would set:

  • Query: "StackAI product launch"

  • Number of Results: 5

  • Index Name: "company-updates"

  • Namespace: (leave blank or specify if needed)

The Pinecone node will then return the most relevant vectors, which you can use for recommendations, search, or further processing in your workflow.