In this Beta release, we are delighted to announce that the Instill VDP API has now achieved a state of stability and reliability. This marks a pivotal moment for Instill VDP, and we are committed to ensuring the continued robustness of our API.

We recognize the importance of a seamless transition for our users and pledge to avoid any disruptive or breaking changes. This commitment means that you can confidently build upon the current version of the Instill VDP API, knowing that your existing integrations and workflows will remain intact.

This achievement represents a major milestone in our journey to provide the best experience for our users. We understand the critical role that stability and consistency play in your development efforts, and we are excited to take this step forward together with you.

As we move forward, we will keep striving to enhance the features of Instill VDP, listening to your feedback, and working closely with our community to deliver even more value and innovation. Thank you for being part of this exciting journey with us.

Our Start operator now supports JSON inputs. 

Leveraging JSON as an input format enables the handling of semi-structured data

, providing a well-organized representation of information. This is especially valuable when working with a REST API connector as a payload or when utilizing the Pinecone connector to insert records that include metadata in the form of key-value pairs. 

Redis connector to facilitate chat history functionality

. Redis, a widely used in-memory data store, enables the efficient implementation of a chat history system. Messages from a given chat session, identified by a unique Session ID, can be stored consistently, complete with their associated roles like "system," "user," and "assistant." Moreover, you have the flexibility to configure the retrieval of the latest K messages and integrate them seamlessly with a Large Language Model (LLM), such as OpenAI's GPT models, allowing you to develop a chatbot with full control over your data.

 to enhance the efficiency and precision of your vector searches. With the ability to associate metadata key-value pairs with your vectors, you can now access not only the most similar records after your data has been indexed but also retrieve the associated metadata. Additionally, you can define filter expressions during queries, enabling you to refine your vector searches based on metadata. This functionality proves invaluable when dealing with extensive datasets where precision and efficiency in retrieval are paramount.

Unlock Instill VDP's full potential with Instill Hub!

, your go-to platform for all things Instill VDP! Here, you have the opportunity to explore and use pipelines that have been contributed by fellow members. These pipelines are designed to provide you with the most up-to-date and efficient AI capabilities. You can seamlessly trigger these pipelines for your projects, or if you're feeling creative, you can even clone them and customize them to suit your unique needs.

But that's not all – we strongly encourage you to share your pipelines with the Instill Hub community. By doing so, you'll be contributing to the growth and success of our platform, helping others in the community benefit from your expertise.

So, whether you're eager to explore, eager to contribute, or simply excited to learn from others, Instill Hub is here to foster a supportive and collaborative community around Instill VDP. Join 

 today and let's work together to make AI innovation accessible to everyone!

Instill AI changelog

Instill VDP, Now on Beta! 🦾