Daita Status

Display project status and deployment information, similar to `git status`. Shows your local project components, cloud deployment history, and any issues that need attention.

#Syntax

bash
daita status [OPTIONS]

#Options

OptionTypeDefaultDescription
--envstringNoneShow status for specific environment only
--verboseflagfalseShow detailed information (functions, etc.)

#Requirements

  • Must be run inside a Daita project directory (contains .daita/ folder)
  • DAITA_API_KEY environment variable for cloud deployment status (optional)

#Examples

#Basic Usage

bash
# Show project status and deployments
daita status
 
# Show status for specific environment
daita status --env staging
 
# Show detailed status with function list
daita status --env staging --verbose

#Status Output

#Basic Project Status

bash
$ daita status
 
📊 Project: my-ai-agents (v1.0.0)
📁 Location: /home/user/projects/my-ai-agents
 
🔧 Components:
   Agents (3):
 data_processor 'Data Processing Agent'
 sentiment_analyzer 'Sentiment Analysis'
 report_generator 'Report Generator'
 
   Workflows (2):
 data_pipeline 'Data Processing Pipeline'
 analysis_workflow 'Analysis Workflow'
 
☁️  Cloud Deployments (5):
 staging: v1.0.5 (2024-12-01 14:30) (current)
 staging: v1.0.4 (2024-11-30 16:20)
 staging: v1.0.3 (2024-11-29 10:15)
 staging: v1.0.2 (2024-11-28 12:00)
 staging: v1.0.1 (2024-11-27 09:30)
 
 No issues found
 
📋 Quick commands:
   daita create agent my_agent    # Create new agent (free)
   daita test                     # Test all components (free)
   daita test --watch             # Development mode (free)
   daita push staging             # Deploy to cloud
   daita logs staging             # View cloud logs

#Environment-Specific Status

bash
$ daita status --env staging
 
📊 Environment: staging
 Status: active
   Last deployed: 2024-12-01 14:30:45
   Version: 1.0.5

#With Verbose Flag

bash
$ daita status --env staging --verbose
 
📊 Environment: staging
 Status: active
   Last deployed: 2024-12-01 14:30:45
   Version: 1.0.5
   Functions: 5
 data_processor
 sentiment_analyzer
 report_generator
 data_pipeline
 analysis_workflow

#Project With Issues

bash
$ daita status
 
📊 Project: my-ai-agents (v1.0.0)
📁 Location: /home/user/projects/my-ai-agents
 
🔧 Components:
   Agents (2):
 sentiment_analyzer 'Sentiment Analysis'
 data_processor (file not found)
 
   Workflows (1):
 data_pipeline 'Data Processing Pipeline'
 
☁️  Cloud Deployments: Upgrade required
   Get your API key at daita-tech.io
   Local deployment history:
    No local deployment history
 
⚠️  Issues:
 Missing agent file: data_processor.py
 Missing requirements.txt
 No LLM API key found (set OPENAI_API_KEY, ANTHROPIC_API_KEY, etc.)
 
📋 Quick commands:
   daita create agent my_agent    # Create new agent (free)
   daita test                     # Test all components (free)
   daita test --watch             # Development mode (free)
 
    Ready for cloud deployment?
   Get your API key at daita-tech.io

#What Gets Shown

The status command displays:

  1. Project Information: Name, version, and location
  2. Components: Lists agents and workflows from daita-project.yaml (or filesystem if not in config)
  3. Cloud Deployments: Recent deployment history from the Daita API (requires DAITA_API_KEY)
  4. Issues: Missing files, missing API keys, configuration problems
  5. Quick Commands: Helpful commands based on your setup

#Status Indicators

#Component Status

  • - Component file exists
  • - Component file missing

#Deployment Status

  • (filled) - Active deployment
  • (empty) - Previous deployment

#Common Issues Detected

The status command checks for:

  • Missing component files: Agents or workflows defined in config but file doesn't exist
  • Missing configuration files: daita-project.yaml or requirements.txt
  • Missing API keys: No LLM provider API key set (OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY)

#Cloud vs Local Mode

#With DAITA_API_KEY Set

Shows cloud deployment history from the Daita platform API.

#Without DAITA_API_KEY

Shows message encouraging cloud deployment and displays local deployment history from .daita/deployments.json (if any).