# Zerve User Documentation ## Zerve User Documentation - [Welcome to Zerve](https://docs.zerve.ai/guide/welcome-to-zerve.md): Zerve is an AI-native, code-based environment built for visual data exploration and production-ready results. - [How to Get Started ?](https://docs.zerve.ai/guide/how-to-get-started.md): There are many ways in which you can get started. Let us see them below. - [Organization Controls](https://docs.zerve.ai/guide/organization-controls.md): Zerve provides organization control settings to create workspaces, manage cloud configurations, create, edit and manage roles. - [Creating Organization](https://docs.zerve.ai/guide/organization-controls/creating-organization.md): You can create an organization by clicking on the arrow next to your username on the top left as shown in the picture below. - [Working with Folders](https://docs.zerve.ai/guide/organization-controls/working-with-folders.md): Folders in Zerve AI are essential for organizing, managing, and collaborating on projects efficiently. - [Creating Folders](https://docs.zerve.ai/guide/organization-controls/working-with-folders/creating-folders.md) - [Creating a Canvas](https://docs.zerve.ai/guide/organization-controls/working-with-folders/creating-a-canvas.md) - [Members](https://docs.zerve.ai/guide/organization-controls/members.md) - [Navigating from Notebook](https://docs.zerve.ai/guide/notebook-view/navigating-from-notebook.md): The canvas view in the my canvases section can be adjusted according to the user's preference. The different views are show below: - [Files](https://docs.zerve.ai/guide/notebook-view/files.md) - [Storing Files](https://docs.zerve.ai/guide/notebook-view/files/storing-files.md): Canvas file system is a dynamic environment to store files of any type with a specified size limit. - [Import Files](https://docs.zerve.ai/guide/notebook-view/files/import-files.md): Once the file is uploaded, it can be accessed in the Python or R blocks, and the files can be of any type. - [Download Files](https://docs.zerve.ai/guide/notebook-view/files/download-files.md): The files can also be seamlessly downloaded into file system from Python or R blocks. - [Deleting Files](https://docs.zerve.ai/guide/notebook-view/files/deleting-files.md): The zerve's canvas offers different ways to delete a file from file system - [Files in Folder](https://docs.zerve.ai/guide/notebook-view/files/files-in-folder.md) - [Installing Packages](https://docs.zerve.ai/guide/notebook-view/installing-packages.md): User can install Python, Linux and R packages by using the Environment feature. - [Global Imports](https://docs.zerve.ai/guide/notebook-view/global-imports.md): Imports done under each code block will work only inside it. Users can add a package or function to Global Imports section to make it available across all the blocks in the canvas. - [Blocks](https://docs.zerve.ai/guide/notebook-view/blocks.md) - [Block types](https://docs.zerve.ai/guide/notebook-view/blocks/block-types.md) - [Python](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/python.md) - [Query](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/query.md) - [R](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/r.md) - [Markdown](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/markdown.md) - [Gen AI](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/gen-ai.md) - [UI Blocks (Input and Output)](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/ui-blocks-input-and-output.md): These blocks help the user to create an application in the canvas - [Aggregator](https://docs.zerve.ai/guide/notebook-view/blocks/block-types/aggregator.md) - [Output and Variable](https://docs.zerve.ai/guide/notebook-view/blocks/output-and-variable.md) - [Block level Security](https://docs.zerve.ai/guide/notebook-view/blocks/block-level-security.md) - [Language Interoperability](https://docs.zerve.ai/guide/notebook-view/blocks/language-interoperability.md): This functionality of Zerve allows users to share the data between two programming languages - [Compute Settings](https://docs.zerve.ai/guide/notebook-view/blocks/compute-settings.md) - [Compute Types](https://docs.zerve.ai/guide/notebook-view/blocks/compute-settings/compute-types.md) - [Setting Compute Type](https://docs.zerve.ai/guide/notebook-view/blocks/compute-settings/setting-compute-type.md) - [Deployment](https://docs.zerve.ai/guide/notebook-view/deployment.md) - [Streamlit Deployment](https://docs.zerve.ai/guide/notebook-view/deployment/streamlit-deployment.md): You can deploy Streamlit apps from Zerve notebooks directly - [Fast API](https://docs.zerve.ai/guide/notebook-view/deployment/fast-api.md): You can deploy via Fast API in Zerve - [Download Deployment](https://docs.zerve.ai/guide/notebook-view/deployment/download-deployment.md) - [API Methods](https://docs.zerve.ai/guide/notebook-view/deployment/api-methods.md) - [Scheduled Jobs](https://docs.zerve.ai/guide/notebook-view/scheduled-jobs.md): Each notebook in Zerve has an inbuilt scheduler as part of it. This can be used to run analytics workflows that need to be run at scheduled intervals - hourly/daily/weekly/custom (cron string) - [Report](https://docs.zerve.ai/guide/notebook-view/report.md) - [How Zerve Works](https://docs.zerve.ai/guide/notebook-view/how-zerve-works.md) - [Assets](https://docs.zerve.ai/guide/notebook-view/assets.md) - [Functions & Classes](https://docs.zerve.ai/guide/notebook-view/assets/functions-and-classes.md): "Functions & Classes" are reusable code snippets that encapsulate specific logic or operations or classes. This provides code modularity, readability, and reduces duplication. - [Constants & Secrets](https://docs.zerve.ai/guide/notebook-view/assets/constants-and-secrets.md): "Constants" are used for unchanging data in code to enhance readability and maintainability, "Secrets" refer to sensitive information that should be protected and not exposed in your code. - [Connections](https://docs.zerve.ai/guide/notebook-view/assets/connections.md): Zerve offers support to integrate with popular database solutions which can be queried directly from canvas and can be used across different blocks/languages. - [Data Discovery](https://docs.zerve.ai/guide/notebook-view/data-discovery.md) - [AI Agent](https://docs.zerve.ai/guide/notebook-view/ai-agent.md) - [Chat](https://docs.zerve.ai/guide/notebook-view/ai-agent/chat.md) - [Search](https://docs.zerve.ai/guide/notebook-view/ai-agent/search.md): Agent can search the internet for you based on your input - [Code](https://docs.zerve.ai/guide/notebook-view/ai-agent/code.md) - [Best Practices](https://docs.zerve.ai/guide/notebook-view/ai-agent/best-practices.md) - [Fleets](https://docs.zerve.ai/guide/notebook-view/fleets.md): Fleets is Zerve's built-in feature for parallel processing. With a single line of code, users can parallelize code to run across multiple blocks. - [Navigating Your Canvas](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas.md): This section is for exploring different functionalities of canvas - [Creating a Canvas](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/creating-a-canvas.md) - [My Canvases](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/my-canvases.md): The canvas view in the my canvases section can be adjusted according to the user's preference. The different views are show below: - [Edit and Sort](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/edit-and-sort.md) - [Shared with me](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/shared-with-me.md) - [Starred](https://docs.zerve.ai/guide/canvas-view/navigating-your-canvas/starred.md) - [Layers Overview](https://docs.zerve.ai/guide/canvas-view/layers-overview.md): Layers are used for arranging blocks as individual workflows. Each canvas can be set up to contain multiple workflows of same/different types for different parts of a data science problem. - [Development](https://docs.zerve.ai/guide/canvas-view/layers-overview/development.md): The IDE Layer. Development layer is similar to any scripting environment - Jupyter or datascience Coding IDE - but better. - [Deployment](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment.md): API builder allows developers to define endpoints, map data structures, set up authentication and authorization mechanisms, and generate documentation for their APIs. - [Create Deployment](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment/create-deployment.md): There are 3 components to setup a deployment in Zerve - API Controller, API Route and the code blocks to execute as part of the deployment. - [Download Deployment](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment/download-deployment.md) - [API Methods](https://docs.zerve.ai/guide/canvas-view/layers-overview/deployment/api-methods.md) - [Scheduled Jobs](https://docs.zerve.ai/guide/canvas-view/layers-overview/scheduled-jobs.md): Each canvas in Zerve has an inbuilt scheduler as part of it. This can be used to run analytics workflows that need to be run at scheduled intervals - hourly/daily/weekly/custom (cron string) - [Files](https://docs.zerve.ai/guide/canvas-view/files.md): File system is the storage space for all the files required to create, run and execute the canvas. - [Storing Files](https://docs.zerve.ai/guide/canvas-view/files/storing-files.md): Canvas file system is a dynamic environment to store files of any type with a specified size limit. - [Import Files](https://docs.zerve.ai/guide/canvas-view/files/import-files.md): Once the file is uploaded, it can be accessed in the Python or R blocks, and the files can be of any type. - [Download Files](https://docs.zerve.ai/guide/canvas-view/files/download-files.md): The files can also be seamlessly downloaded into file system from Python or R blocks. - [Deleting Files](https://docs.zerve.ai/guide/canvas-view/files/deleting-files.md): The zerve's canvas offers different ways to delete a file from file system - [Files in Folder](https://docs.zerve.ai/guide/canvas-view/files/files-in-folder.md) - [Installing Packages](https://docs.zerve.ai/guide/canvas-view/installing-packages.md): User can install Python, Linux and R packages by using the Environment feature. - [Requirements](https://docs.zerve.ai/guide/canvas-view/installing-packages/requirements.md): By default, zerve canvas run in containers with Python 3.11.1, and a number of pre-installed packages. The user has the option to add new packages, new python versions, etc. from the requirements tab. - [Global Imports](https://docs.zerve.ai/guide/canvas-view/global-imports.md): Imports done under each code block will work only inside it. Users can add a package or function to Global Imports section to make it available across all the blocks in the canvas. - [Blocks and Connections](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections.md) - [Block types](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types.md) - [Python](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/python.md) - [Query](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/query.md) - [R](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/r.md) - [Markdown](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/markdown.md) - [Gen AI](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/gen-ai.md): GenAI blocks can be used to connect to LLMs on Bedrock/OpenAI making it suitable for various applications, including text generation, summarization, translation, text to image, and more. - [R Markdown](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/r-markdown.md): Zerve’s R Markdown block enables users to integrate and execute R code within their analytics environment, facilitating the creation and publication of dynamic, interactive reports. - [UI Blocks (Input and Output)](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/ui-blocks-input-and-output.md): These blocks help the user to create an application in the canvas - [Aggregator](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/aggregator.md) - [Logic Gate](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-types/logic-gate.md) - [Code and Variable Mode](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/code-and-variable-mode.md) - [Block level Security](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/block-level-security.md) - [Language Interoperability](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/language-interoperability.md): This functionality of Zerve allows users to share the data between two programming languages - [Compute Settings](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/compute-settings.md) - [Lambda vs Fargate vs GPU](https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/compute-settings/lambda-vs-fargate-vs-gpu.md) - [How Zerve Works](https://docs.zerve.ai/guide/canvas-view/how-zerve-works.md) - [Assets](https://docs.zerve.ai/guide/canvas-view/assets.md): Assets are used for storing functions, queries, constants, secrets, and connections for seamless development. - [Functions & Classes](https://docs.zerve.ai/guide/canvas-view/assets/functions-and-classes.md): "Functions & Classes" are reusable code snippets that encapsulate specific logic or operations or classes. This provides code modularity, readability, and reduces duplication. - [Constants & Secrets](https://docs.zerve.ai/guide/canvas-view/assets/constants-and-secrets.md): "Constants" are used for unchanging data in code to enhance readability and maintainability, "Secrets" refer to sensitive information that should be protected and not exposed in your code. - [Connections](https://docs.zerve.ai/guide/canvas-view/assets/connections.md): Zerve offers support to integrate with popular database solutions which can be queried directly from canvas and can be used across different blocks/languages. - [AI Agent](https://docs.zerve.ai/guide/canvas-view/ai-agent.md) - [Chat](https://docs.zerve.ai/guide/canvas-view/ai-agent/chat.md) - [Search](https://docs.zerve.ai/guide/canvas-view/ai-agent/search.md): Agent can search the internet for you based on your input - [Code](https://docs.zerve.ai/guide/canvas-view/ai-agent/code.md) - [Best Practices](https://docs.zerve.ai/guide/canvas-view/ai-agent/best-practices.md) - [Fleets](https://docs.zerve.ai/guide/canvas-view/fleets.md): Fleets is Zerve's built-in feature for parallel processing. With a single line of code, users can parallelize code to run across multiple blocks. - [Hosted Apps](https://docs.zerve.ai/guide/hosted-apps.md): Zerve's Hosted App feature is designed to streamline and enhance the deployment and management of web applications. This include benefits such as Ease of Deployment, Scalability, friendly interface. - [Source Control (Git)](https://docs.zerve.ai/guide/source-control-git.md): Zerve provides integration or linkage with Git repositories. This section guides you through setting up Git integration with supported platforms. - [Install Github (Cloud) App](https://docs.zerve.ai/guide/source-control-git/install-github-cloud-app.md): Follow the installation steps described here if you are integrating Zerve with your Github Cloud Repositories. - [Install Github Enterprise (GHES) App](https://docs.zerve.ai/guide/source-control-git/install-github-enterprise-ghes-app.md): Follow the installation steps here if you are integrating Zerve with a self hosted Github Enterprise Server account. This integration is only supported for Zerve organizations. - [Install Bitbucket OAuth Consumer](https://docs.zerve.ai/guide/source-control-git/install-bitbucket-oauth-consumer.md): This type of integration should be installed if you wish to grant the Zerve application permissions that are associated with a Bitbucket User account. - [Install Bitbucket Cloud Connect App](https://docs.zerve.ai/guide/source-control-git/install-bitbucket-cloud-connect-app.md): This type of integration should be installed if you wish to grant the Zerve application permissions to access all repositories in a Bitbucket Workspace. - [Install Azure Devops Repos App](https://docs.zerve.ai/guide/source-control-git/install-azure-devops-repos-app.md): Follow the installation steps described here if you are integrating Zerve with your Azure Devops Repositories. - [Canvas Source Control Features](https://docs.zerve.ai/guide/source-control-git/canvas-source-control-features.md): This page covers how Zerve integrates Git-based source control directly into the canvas environment, including committing code, viewing history and managing branches. - [Integrations](https://docs.zerve.ai/guide/integrations.md): Cloud and Database integrations. - [Cloud](https://docs.zerve.ai/guide/integrations/cloud.md): Bring your own cloud - Data stays in your environment - Safe and Secure - [AWS Self Hosting](https://docs.zerve.ai/guide/integrations/cloud/aws-self-hosting.md): Create a workspace using the AWS Quick Start - [AWS CloudFormation](https://docs.zerve.ai/guide/integrations/cloud/aws-cloudformation.md) - [GCP Self Hosting (GKE)](https://docs.zerve.ai/guide/integrations/cloud/gcp-self-hosting-gke.md) - [Azure Self Hosting](https://docs.zerve.ai/guide/integrations/cloud/azure-self-hosting.md): This section explains how to setup and create resources for self-hosting Zerve on a pre-existing AKS cluster in Azure. - [Database Connections](https://docs.zerve.ai/guide/integrations/database-connections.md) - [MySQL](https://docs.zerve.ai/guide/integrations/database-connections/mysql.md): Zerve connects directly to MySQL databases, helping you build better and faster data science workflows - [PostgreSQL](https://docs.zerve.ai/guide/integrations/database-connections/postgresql.md): Zerve's connections feature lets you easily integrate PostgreSQL databases. - [MariaDB](https://docs.zerve.ai/guide/integrations/database-connections/mariadb.md): Zerve provides a secure, direct connection to MariaDB, enabling comprehensive data analysis without the complexity of multiple tools or data movement. - [Snowflake](https://docs.zerve.ai/guide/integrations/database-connections/snowflake.md): Zerve enables direct, protected access to Snowflake data, eliminating the need to switch between platforms or move data around. - [Weaviate](https://docs.zerve.ai/guide/integrations/database-connections/weaviate.md): Weaviate connection provides native support to write and query vector database using GraphQL. - [Settings](https://docs.zerve.ai/guide/settings.md) - [User Settings](https://docs.zerve.ai/guide/settings/user-settings.md): Customize your Zerve experience with user settings. - [Agent Skills](https://docs.zerve.ai/guide/settings/agent-skills.md): Prepackaged and repeatable best practices & tools for your agent - [Shortcuts](https://docs.zerve.ai/guide/shortcuts.md): Zerve canvas comes with a host of shortcuts to improve developer/data scientist productivity and efficiency. The table below gives the comprehensive list of shortcuts available in Zerve. - [Collaboration](https://docs.zerve.ai/guide/collaboration.md): Zerve allows the team work by enabling collaboration between team members - [Sharing](https://docs.zerve.ai/guide/collaboration/sharing.md): Collaboration in real time is one of the core principles of how Zerve works. Users can easily share their canvas with others in the organization to collaborate, get feedback, and showcase their work. - [Real-time collaboration](https://docs.zerve.ai/guide/collaboration/real-time-collaboration.md): Zerve's real time collaboration allows multiple individuals or teams to work together simultaneously on a project or task, regardless of their physical locations. - [Comments](https://docs.zerve.ai/guide/collaboration/comments.md): Google doc style comments feature to truly collaborate and work with team members. Comment, Edit, Resolve options to work productively within a team. - [Additional Resources/Policies](https://docs.zerve.ai/guide/additional-resources-policies.md) - [End User License Agreement](https://docs.zerve.ai/guide/additional-resources-policies/end-user-license-agreement.md) - [Cookie Policy](https://docs.zerve.ai/guide/additional-resources-policies/cookie-policy.md) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on a page URL with the `ask` query parameter: ``` GET https://docs.zerve.ai/guide/welcome-to-zerve.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.