RapidCanvas Docs
  • Welcome
  • GETTING STARTED
    • Quick start guide
    • Introduction to RapidCanvas
    • RapidCanvas Concepts
    • Accessing the platform
  • BASIC
    • Projects
      • Projects Overview
        • Creating a project
        • Reviewing the Projects listing page
        • Duplicating a Project
        • Modifying the project settings
        • Deleting Project(s)
        • Configuring global variables at the project level
        • Working on a project
        • Generating the about content for the project
        • Generating AI snippets for each node on the Canvas
        • Marking & Unmarking a Project as Favorite
      • Canvas overview
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        • Viewing the run history of a specific scheduler
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      • Importing dataset(s) from the local system
      • Importing Text Files from the Local System
      • Connectors overview
      • Connect to external connectors
        • Importing data from Google Cloud Storage (GCS)
        • Importing data from Amazon S3
        • Importing data from Azure Blob
        • Importing data from Mongo DB
        • Importing data from Snowflake
        • Importing data from MySQL
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        • Importing data from Fivetran connectors
    • Workspaces
      • User roles and permissions
    • Artifacts & Models
      • Adding Artifacts at the Project Level
      • Adding Models at the Project Level
      • Creating an artifact at the workspace level
      • Managing artifacts at the workspace level
      • Managing Models at the Workspace Level
      • Prediction services
    • Environments Overview
      • Creating an environment
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      • Deleting an environment
      • Monitoring the resource utilization in an environment
  • ADVANCED
    • Starter Guide
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    • Setup and Installation
      • Installing and setting up the SDK
    • Helper Functions
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      • Introduction
      • Create a template
      • Code Snippets
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      • How to
        • How to Authenticate
        • Create a new project
        • Create a Custom Environment
        • Add a dataset
        • Add a recipe to the dataset
        • Manage cloud connection
        • Code recipes
        • Display a template on the UI
        • Create Global Variables
        • Scheduler
        • Create new scenarios
        • Create Template
        • Use a template in a flow notebook
      • Reference Implementations
        • DataApps
        • Artifacts
        • Connectors
        • Feature Store
        • ML model
        • ML Pipeline
        • Multiple Files
      • Sample Projects
        • Model build and predict
    • Rapid Rag
  • Additional Reading
    • Release Notes
      • May 14, 2025
      • April 21, 2025
      • April 01, 2025
      • Mar 18, 2025
      • Feb 27, 2025
      • Jan 27, 2025
      • Dec 26, 2024
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      • Sep 11, 2024
        • Aug 08, 2024
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      • Jan 16, 2024
      • Dec 12, 2023
      • Nov 07, 2023
      • Oct 25, 2023
      • Oct 01, 2024
    • Glossary
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On this page
  • New Features
  • Documents and PDFs as Input Options
  • New Features for Custom Model DataApps
  • Enhancements
  • New Option for Code Explanation in AskAI
  • Save Prediction Service Results and Add to Canvas
  • AI Guide Icon Update
  • Up and Down Arrow Navigation in Ask AI
  • Custom Environment Configuration with Flexible Resource Allocation
  • New Canvas Dataset Option in Prediction Service
  • Input Type Visibility on DataApp Cards
  • SQL-Based DataApp Enhancements
  • Copy table data in AskAI query response
  1. Additional Reading
  2. Release Notes

Sep 11, 2024

New Features

Documents and PDFs as Input Options

Custom Model DataApps now support Documents and PDFs as an input type, expanding the range of data sources. Users can upload documents in formats such as PDF, DOC, and DOCX directly into their DataApps. This feature is paired with the Ask AI tool, allowing users to easily query the document contents for fast information extraction, analysis, and text-based responses.

New Features for Custom Model DataApps

Response Caching:

A new option to enable response caching is now available. When activated, identical queries return the same response without regenerating results, reducing the processing time and improving efficiency.

Model Controls:

Model Controls allow users to provide specific context to guide the AI’s responses. This helps tailor AI-generated outputs more closely to individual use cases, ensuring more relevant and accurate results.

Enhanced Security Options for Data Inputs:

New security options are available for three input types: Project Canvas Datasets, Custom Uploaded Datasets, and SQL sources. Users now have more control over sensitive data by:

  • Sharing sample data for LLM code generation, or

  • Sharing only column names to protect data privacy.

These features offer increased flexibility and customization, helping users maximize the potential of their Custom Model DataApps while ensuring security and efficiency.

This update empowers users to work more seamlessly with different data formats and maintain better control over how their data is utilized, making it easier to create secure, tailored AI-driven insights.

Enhancements

Several key enhancements have been made to improve user experience, resource management, and the overall functionality of Custom Model DataApps:

New Option for Code Explanation in AskAI

Description:

A new feature has been introduced in AskAI that allows users to request explanations for code generated by the Large Language Model (LLM). This option provides detailed explanations of the code snippets produced by AskAI, helping users understand the logic and functionality of the generated code.

Benefits:

  • Enhanced Understanding: Users can gain a deeper insight into how the code works, facilitating better comprehension and learning.

  • Improved Debugging: By understanding the generated code, users can more easily identify and address any issues or make necessary adjustments.

  • Streamlined Workflow: The explanation feature aids in integrating generated code into larger projects more efficiently by providing clear, contextual information.

Save Prediction Service Results and Add to Canvas

Users can now Download as CSV or Add to Canvas after testing the prediction service on an uploaded dataset. This allows users to download the prediction results as a CSV file for further analysis or directly add the results to the canvas for seamless integration into ongoing projects.

AI Guide Icon Update

The AI Guide icon has been refreshed across multiple screens within the application to provide a more consistent and modern user interface experience.

Up and Down Arrow Navigation in Ask AI

Users can now navigate the chat window using Up and Down Arrows in both Ask AI and the AI Guide within DataApps, making it easier to scroll through and manage generated outputs during interaction.

Custom Environment Configuration with Flexible Resource Allocation

The custom environment configuration feature has been enhanced to provide users with greater control. Instead of selecting from predefined values, users can now specify custom resources such as CPU cores, memory, and disk space (within set limits). This allows for more flexibility when configuring environments for specific workloads.

New Canvas Dataset Option in Prediction Service

A new option now allows users to select datasets from the Canvas when testing prediction services. This enhancement adds flexibility, enabling users to work with both uploaded datasets and those directly available from the project canvas.

Input Type Visibility on DataApp Cards

The input type is now clearly visible on DataApp cards, making it easier to identify the type of data input being used within the app and improving the overall usability of the interface.

SQL-Based DataApp Enhancements

In SQL-based DataApps, the size of the connector table is now exposed, improving data management by providing better visibility into the datasets being used.

Copy table data in AskAI query response

  • Copy to Clipboard Option: Users can now copy dataset responses with a single click, enabling fast and seamless integration of AI-generated insights into other tools or workflows.

  • Enhanced Usability: This feature improves the ease of accessing and sharing data insights directly from the Ask AI interface, enhancing overall productivity.

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Last updated 3 months ago