# Pinecone

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.