Genkit ↗

Documentation Index#

Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt Use this file to discover all available pages before exploring further.

export const PrimarySecondaryCTA = ({primaryLabel, primaryHref, primaryTarget, secondaryLabel, secondaryHref, secondaryTarget}) => {primaryLabel && primaryHref &&

  {primaryLabel}

<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
  <path d="M9.70492 6L8.29492 7.41L12.8749 12L8.29492 16.59L9.70492 18L15.7049 12L9.70492 6Z" fill="white" />
</svg>

{secondaryLabel && secondaryHref &&

    {secondaryLabel}
  
</a>

}

;

The Genkit Pinecone plugin empowers developers to reduce the complexity of integrating AI components through simple indexers, embedders and retrievers abstractions. Through the Genkit Pinecone plugin, developers can integrate AI models with their own custom logic and data to build AI features optimized for their businesses.

Additionally, developers can analyze unstructured text, generate creative content, select tasks, and send results back to their app as structured type-safe objects. The plugin provides a common format for content that supports combinations of text, data, and other media. Developers can use Genkit for models that perform any generative task (such as image generation), not just LLMs.