Paradime Help Docs
Get Started
  • 🚀Introduction
  • 📃Guides
    • Paradime 101
      • Getting Started with your Paradime Workspace
        • Creating a Workspace
        • Setting Up Data Warehouse Connections
        • Managing workspace configurations
        • Managing Users in the Workspace
      • Getting Started with the Paradime IDE
        • Setting Up a dbt™ Project
        • Creating a dbt™ Model
        • Data Exploration in the Code IDE
        • DinoAI: Accelerating Your Analytics Engineering Workflow
          • DinoAI Agent
            • Creating dbt Sources from Data Warehouse
            • Generating Base Models
            • Building Intermediate/Marts Models
            • Documentation Generation
            • Data Pipeline Configuration
            • Using .dinorules to Tailor Your AI Experience
          • Accelerating GitOps
          • Accelerating Data Governance
          • Accelerating dbt™ Development
        • Utilizing Advanced Developer Features
          • Visualize Data Lineage
          • Auto-generated Data Documentation
          • Enforce SQL and YAML Best Practices
          • Working with CSV Files
      • Managing dbt™ Schedules with Bolt
        • Creating Bolt Schedules
        • Understanding schedule types and triggers
        • Viewing Run History and Analytics
        • Setting Up Notifications
        • Debugging Failed Runs
    • Migrating from dbt™ cloud to Paradime
  • 🔍Concepts
    • Working with Git
      • Git Lite
      • Git Advanced
      • Read Only Branches
      • Delete Branches
      • Merge Conflicts
      • Configuring Signed Commits on Paradime with SSH Keys
      • GitHub Branch Protection Guide: Preventing Direct Commits to Main
    • dbt™ fundamentals
      • Getting started with dbt™
        • Introduction
        • Project Strucuture
        • Working with Sources
        • Testing Data Quality
        • Models and Transformations
      • Configuring your dbt™ Project
        • Setting up your dbt_project.yml
        • Defining Your Sources in sources.yml
        • Testing Source Freshness
        • Unit Testing
        • Working with Tags
        • Managing Seeds
        • Environment Management
        • Variables and Parameters
        • Macros
        • Custom Tests
        • Hooks & Operational Tasks
        • Packages
      • Model Materializations
        • Table Materialization
        • View​ Materialization
        • Incremental Materialization
          • Using Merge for Incremental Models
          • Using Delete+Insert for Incremental Models
          • Using Append for Incremental Models
          • Using Microbatch for Incremental Models
        • Ephemeral Materialization
        • Snapshots
      • Running dbt™
        • Mastering the dbt™ CLI
          • Commands
          • Methods
          • Selector Methods
          • Graph Operators
    • Paradime fundamentals
      • Global Search
        • Paradime Apps Navigation
        • Invite users to your workspace
        • Search and preview Bolt schedules status
      • Using --defer in Paradime
      • Workspaces and data mesh
    • Data Warehouse essentials
      • BigQuery Multi-Project Service Account
  • 📖Documentation
    • DinoAI
      • Agent Mode
        • Use Cases
          • Creating Sources from your Warehouse
          • Generating dbt™ models
          • Fixing Errors with Jira
          • Researching with Perplexity
          • Providing Additional Context Using PDFs
      • Context
        • File Context
        • Directory Context
      • Tools and Features
        • Warehouse Tool
        • File System Tool
        • PDF Tool
        • Jira Tool
        • Perplexity Tool
        • Terminal Tool
        • Coming Soon Tools...
      • .dinorules
      • Ask Mode
      • Version Control
      • Production Pipelines
      • Data Documentation
    • Code IDE
      • User interface
        • Autocompletion
        • Context Menu
        • Flexible layout
        • "Peek" and "Go To" Definition
        • IDE preferences
        • Shortcuts
      • Left Panel
        • DinoAI Coplot
        • Search, Find, and Replace
        • Git Lite
        • Bookmarks
      • Command Panel
        • Data Explorer
        • Lineage
        • Catalog
        • Lint
      • Terminal
        • Running dbt™
        • Paradime CLI
      • Additional Features
        • Scratchpad
    • Bolt
      • Creating Schedules
        • 1. Schedule Settings
        • 2. Command Settings
          • dbt™ Commands
          • Python Scripts
          • Elementary Commands
          • Lightdash Commands
          • Tableau Workbook Refresh
          • Power BI Dataset Refresh
          • Paradime Bolt Schedule Toggle Commands
          • Monte Carlo Commands
        • 3. Trigger Types
        • 4. Notification Settings
        • Templates
          • Run and Test all your dbt™ Models
          • Snapshot Source Data Freshness
          • Build and Test Models with New Source Data
          • Test Code Changes On Pull Requests
          • Re-executes the last dbt™ command from the point of failure
          • Deploy Code Changes On Merge
          • Create Jira Tickets
          • Trigger Census Syncs
          • Trigger Hex Projects
          • Create Linear Issues
          • Create New Relic Incidents
          • Create Azure DevOps Items
        • Schedules as Code
      • Managing Schedules
        • Schedule Configurations
        • Viewing Run Log History
        • Analyzing Individual Run Details
          • Configuring Source Freshness
      • Bolt API
      • Special Environment Variables
        • Audit environment variables
        • Runtime environment variables
      • Integrations
        • Reverse ETL
          • Hightouch
        • Orchestration
          • Airflow
          • Azure Data Factory (ADF)
      • CI/CD
        • Turbo CI
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
          • Paradime Turbo CI Schema Cleanup
        • Continuous Deployment with Bolt
          • GitHub Native Continuous Deployment
          • Using Azure Pipelines
          • Using BitBucket Pipelines
          • Using GitLab Pipelines
        • Column-Level Lineage Diff
          • dbt™ mesh
          • Looker
          • Tableau
          • Thoughtspot
    • Radar
      • Get Started
      • Cost Management
        • Snowflake Cost Optimization
        • Snowflake Cost Monitoring
        • BigQuery Cost Monitoring
      • dbt™ Monitoring
        • Schedules Dashboard
        • Models Dashboard
        • Sources Dashboard
        • Tests Dashboard
      • Team Efficiency Tracking
      • Real-time Alerting
      • Looker Monitoring
    • Data Catalog
      • Data Assets
        • Looker assets
        • Tableau assets
        • Power BI assets
        • Sigma assets
        • ThoughtSpot assets
        • Fivetran assets
        • dbt™️ assets
      • Lineage
        • Search and Discovery
        • Filters and Nodes interaction
        • Nodes navigation
        • Canvas interactions
        • Compare Lineage version
    • Integrations
      • Dashboards
        • Sigma
        • ThoughtSpot (Beta)
        • Lightdash
        • Tableau
        • Looker
        • Power BI
        • Streamlit
      • Code IDE
        • Cube CLI
        • dbt™️ generator
        • Prettier
        • Harlequin
        • SQLFluff
        • Rainbow CSV
        • Mermaid
          • Architecture Diagrams
          • Block Diagrams Documentation
          • Class Diagrams
          • Entity Relationship Diagrams
          • Gantt Diagrams
          • GitGraph Diagrams
          • Mindmaps
          • Pie Chart Diagrams
          • Quadrant Charts
          • Requirement Diagrams
          • Sankey Diagrams
          • Sequence Diagrams
          • State Diagrams
          • Timeline Diagrams
          • User Journey Diagrams
          • XY Chart
          • ZenUML
        • pre-commit
          • Paradime Setup and Configuration
          • dbt™️-checkpoint hooks
            • dbt™️ Model checks
            • dbt™️ Script checks
            • dbt™️ Source checks
            • dbt™️ Macro checks
            • dbt™️ Modifiers
            • dbt™️ commands
            • dbt™️ checks
          • SQLFluff hooks
          • Prettier hooks
      • Observability
        • Elementary Data
          • Anomaly Detection Tests
            • Anomaly tests parameters
            • Volume anomalies
            • Freshness anomalies
            • Event freshness anomalies
            • Dimension anomalies
            • All columns anomalies
            • Column anomalies
          • Schema Tests
            • Schema changes
            • Schema changes from baseline
          • Sending alerts
            • Slack alerts
            • Microsoft Teams alerts
            • Alerts Configuration and Customization
          • Generate observability report
          • CLI commands and usage
        • Monte Carlo
      • Storage
        • Amazon S3
        • Snowflake Storage
      • Reverse ETL
        • Hightouch
      • CI/CD
        • GitHub
        • Spectacles
      • Notifications
        • Microsoft Teams
        • Slack
      • ETL
        • Fivetran
    • Security
      • Single Sign On (SSO)
        • Okta SSO
        • Azure AD SSO
        • Google SAML SSO
        • Google Workspace SSO
        • JumpCloud SSO
      • Audit Logs
      • Security model
      • Privacy model
      • FAQs
      • Trust Center
      • Security
    • Settings
      • Workspaces
      • Git Repositories
        • Importing a repository
          • Azure DevOps
          • BitBucket
          • GitHub
          • GitLab
        • Update connected git repository
      • Connections
        • Code IDE environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Scheduler environment
          • Amazon Athena
          • BigQuery
          • Clickhouse
          • Databricks
          • Dremio
          • DuckDB
          • Firebolt
          • Microsoft Fabric
          • Microsoft SQL Server
          • MotherDuck
          • PostgreSQL
          • Redshift
          • Snowflake
          • Starburst/Trino
        • Manage connections
          • Set alternative default connection
          • Delete connections
        • Cost connection
          • BigQuery cost connection
          • Snowflake cost connection
        • Connection Security
          • AWS PrivateLink
            • Snowflake PrivateLink
            • Redshift PrivateLink
          • BigQuery OAuth
          • Snowflake OAuth
        • Optional connection attributes
      • Notifications
      • dbt™
        • Upgrade dbt Core™ version
      • Users
        • Invite users
        • Manage Users
        • Enable Auto-join
        • Users and licences
        • Default Roles and Permissions
        • Role-based access control
      • Environment Variables
        • Bolt Schedules Environment Variables
        • Code IDE Environment Variables
  • 💻Developers
    • GraphQL API
      • Authentication
      • Examples
        • Audit Logs API
        • Bolt API
        • User Management API
        • Workspace Management API
    • Python SDK
      • Getting Started
      • Modules
        • Audit Log
        • Bolt
        • Lineage Diff
        • Custom Integration
        • User Management
        • Workspace Management
    • Paradime CLI
      • Getting Started
      • Bolt CLI
    • Webhooks
      • Getting Started
      • Custom Webhook Guides
        • Create an Azure DevOps Work item when a Bolt run complete with errors
        • Create a Linear Issue when a Bolt run complete with errors
        • Create a Jira Issue when a Bolt run complete with errors
        • Trigger a Slack notification when a Bolt run is overrunning
    • Virtual Environments
      • Using Poetry
      • Troubleshooting
    • API Keys
    • IP Restrictions in Paradime
    • Company & Workspace token
  • 🙌Best Practices
    • Data Mesh Setup
      • Configure Project dependencies
      • Model access
      • Model groups
  • ‼️Troubleshooting
    • Errors
    • Error List
    • Restart Code IDE
  • 🔗Other Links
    • Terms of Service
    • Privacy Policy
    • Paradime Blog
Powered by GitBook
On this page
  • Capabilities
  • Using the Terminal Tool
  • Example Use Cases
  • Working with Error Messages
  • Integration with Other Tools

Was this helpful?

  1. Documentation
  2. DinoAI
  3. Tools and Features

Terminal Tool

The Terminal Tool enables DinoAI to suggest and execute terminal commands, helping you with Git operations, dbt runs, and other command-line tasks directly from your DinoAI interface.

With the Terminal Tool, DinoAI can help you navigate Git workflows, execute dbt commands, and troubleshoot issues by analyzing command outputs - all without leaving your development environment.

Capabilities

Capability
What It Does

Execute Git Commands

Create branches, commit changes, and manage Git workflows

Run dbt Operations

Execute dbt commands to build, test, and verify models

Debug Errors

Analyze command outputs to identify and fix issues

Using the Terminal Tool

  1. Open DinoAI and describe what you're trying to accomplish

  2. DinoAI suggests a terminal command based on your goal

  3. Review the suggested command carefully

  4. Approve the command execution if it looks correct

  5. DinoAI runs the command in your terminal and analyzes the output

  6. If errors occur, DinoAI suggests fixes based on the error messages


Example Use Cases

Summarizing Documentation

  • Prompt: "I need to create a branch to fix the issue described in JIRA-123"

  • Result: DinoAI suggests and runs the Git command to create a properly named branch (e.g., git checkout -b fix/JIRA-123-description)

Extracting Information

  • Prompt: "Can you fix the failing model in our production pipeline?"

  • Result: DinoAI identifies the failing model, suggests edits, runs 'dbt run' to test the fix, and helps resolve any compilation or runtime errors

Extracting Information

  • Prompt: "I've fixed the issue, can you commit and push my changes?"

  • Result: DinoAI creates a descriptive commit message, commits the changes, and pushes to the remote repository

Always review suggested commands before execution. While DinoAI is designed to be helpful, you should verify that the commands won't have unintended consequences.


Working with Error Messages

One of the most powerful features of the Terminal Tool is its ability to understand and resolve errors:

  1. When a command fails, DinoAI analyzes the error output

  2. DinoAI suggests fixes based on the specific error message

  3. After applying fixes, DinoAI can re-run the command to verify the solution


Integration with Other Tools

The Terminal Tool works seamlessly with other DinoAI tools:

  • Jira Tool: Execute workflows based on Jira ticket requirements

  • File System Tool: Make changes to files and then commit them with proper Git commands

  • Warehouse Tool: Run dbt commands to test models created based on warehouse metadata


Best Practices

  1. Be specific about your goals - Tell DinoAI what you're trying to accomplish, not just what command you want to run

  2. Review before executing - Always check suggested commands before approving them

  3. Use for workflows - The Terminal Tool is most powerful when automating multi-step workflows

  4. Leverage for debugging - Let DinoAI help identify issues in command outputs and suggest fixes

PreviousPerplexity ToolNextComing Soon Tools...

Last updated 23 days ago

Was this helpful?

📖