A Conversational On-Chain Data Query Constructor

At KNN3 Network, we are committed to providing seamlessly integrated cross-platform data sources that optimize development efficiency. Our unwavering belief in the exceptional value of data fuels our continuous efforts to enhance the user experience, particularly for developers. Our goal is to enable them to effortlessly integrate data within minutes, freeing them to focus on their core tasks without any hindrance.

We are excited to introduce the latest advancements in K.Transformer, a conversational on-chain data query constructor designed to enhance the building experience of data-driven applications. Our aim is to foster a vibrant community and eagerly invite valuable user feedback to consistently improve and refine our offerings.

  1. ChatGPT-style SQL Query Constructor

    Intuitive

    K.Transformer offers an intuitive experience where natural language (NL) problems can be defined and narrowed down to the target. The goal-oriented chat agent ensures that data engineers can focus on problem-solving without any topic drifting.

    Progressive

    With the conversational-based SQL assistant, developers have the flexibility to interactively adjust and improve their SQL queries until they reach the perfect solution. This progressive approach allows for iterative refinement of queries.

    Reflective

    The seamless execution of SQL queries on the right side of the interface provides real-time feedback on the actual outcomes. Engineers can review this feedback to make further adjustments, ensuring optimal query performance and accuracy.

  1. SQL Modification & Parameterization

With our SQL solution, users are no longer burdened with the manual task of copying code. Instead, executing operations becomes a breeze as they can simply click the "run" button conveniently placed within the code interface. Users have the flexibility to directly modify parameters within the designated code lines, allowing them to customize and optimize their queries based on their specific requirements.

Users can use {{para_name}} as the placeholder of any value to parameterize the query.

  1. Favourite & Templates

To improve code preservation and organization, we have introduced a "Favorite" feature within our platform. This functionality empowers users to save and bookmark their preferred code snippets for future reference.

Users can conveniently assign custom names and descriptions (prompts) to the saved code, ensuring easy and quick access whenever needed. This feature enhances code management and facilitates efficient retrieval of specific snippets as per user preferences.

Once you have saved your preferred SQL query, utilizing it becomes seamless. Simply access the left menu and hover over the desired template to preview it. This action will provide you with the corresponding description and SQL code.

By clicking on the template, the SQL will automatically appear in the chat box, enabling you to conveniently edit and add any new requirements or demands.

We have provided a selection of pre-defined SQL templates for your convenience. By choosing a template, users can effortlessly populate the relevant content into the input field, ensuring a seamless interaction with our AI system.

  1. Mobile & PC Compatibility

We have improved our offering to deliver a smooth and consistent user experience across various devices, including both mobile and PC platforms. Our compatibility with multiple ports ensures that you can stay productive and connected without any limitations based on your preferred device. Enjoy the convenience of accessing our system anytime, anywhere, and make the most of our services without being restricted by device constraints.

Last updated