Daita Documentation

#Installation

Install the Daita CLI with all dependencies:

bash

pip install daita-agents[cli]

Verify your installation:

bash

daita --version
# Output: Daita CLI v0.1.0

#Quick Start

Get started with a new project in under a minute:

bash

# Create a new project
daita init my-agent --type analysis
cd my-agent
 
# Set your API key
export OPENAI_API_KEY="your-key-here"
 
# Create your first agent
daita create agent data_processor
 
# Test it locally
daita test
 
# Deploy to production (requires DAITA_API_KEY)
daita push

#Command Structure

All Daita CLI commands follow a consistent pattern:

bash

daita [GLOBAL_OPTIONS] COMMAND [ARGUMENTS] [COMMAND_OPTIONS]

#Global Options

These options work with all commands:

Option	Short	Description
`--verbose`	`-v`	Enable detailed output for debugging
`--quiet`	`-q`	Suppress non-error messages
`--help`	`-h`	Show help information

Example usage:

bash

daita --verbose test my_agent
daita -v push production --force

#Core Commands

#Project Management

init - Initialize new Daita projects
status - Check project and deployment status

#Development

create - Generate agents, workflows, and components
test - Test agents and workflows with live reload

#Deployment

push - Deploy to environments (git-like)
logs - View deployment logs and monitor

#Utilities

utilities - Version information and documentation access

#Environment Setup

#Required Environment Variables

Configure these environment variables for full CLI functionality:

bash

# LLM Provider Keys (choose your provider)
export OPENAI_API_KEY="sk-your-openai-key"
export ANTHROPIC_API_KEY="sk-ant-your-anthropic-key"
export GOOGLE_API_KEY="your-google-key"
export XAI_API_KEY="xai-your-grok-key"
 
# Daita Platform (for cloud deployment features)
export DAITA_API_KEY="your-daita-api-key"

#Optional Configuration

Customize CLI behavior with these optional variables:

bash

# API endpoint (usually not needed)
export DAITA_API_ENDPOINT="https://api.daita-tech.io"
 
# Log level
export DAITA_LOG_LEVEL="INFO"            # DEBUG, INFO, WARNING, ERROR

#Project Context

Most CLI commands require you to be inside a Daita project directory. A Daita project is identified by the presence of a .daita/ folder and daita-project.yaml configuration file.

#Commands that require project context:

create - Create agents and workflows
test - Run tests locally
push - Deploy to cloud (requires DAITA_API_KEY)
status - Show project status
logs - View deployment logs (requires DAITA_API_KEY)
run - Execute agents/workflows remotely (requires DAITA_API_KEY)
deployments - Manage deployments (requires DAITA_API_KEY)
webhook - Webhook management (requires DAITA_API_KEY)

#Commands that work anywhere:

init - Initialize new projects
version - Show version info
docs - Open documentation

If you run a project-context command outside a Daita project, you'll see:

bash

❌ Not in a Daita project directory.
   Run 'daita init' to create a new project.

#Project Structure

A typical Daita project created by daita init looks like:

python

my-project/
├── .daita/                   # Daita metadata and cache
│   ├── cache/               # Local cache files
│   └── deployments.json    # Deployment history
├── agents/                  # AI agent definitions
│   ├── __init__.py
│   └── example_agent.py
├── workflows/               # Multi-agent workflows
│   ├── __init__.py
│   └── example_workflow.py
├── data/                    # Data files and samples
├── tests/                   # Test files
│   ├── __init__.py
│   ├── test_agents.py
│   └── test_workflows.py
├── daita-project.yaml       # Project configuration
├── requirements.txt         # Python dependencies
├── .gitignore              # Git ignore rules
└── README.md               # Project documentation

#Configuration File

The daita-project.yaml file controls your project settings:

yaml

name: my-project
version: 1.0.0
description: My AI agent project
created_at: '2025-01-15T10:00:00'
 
# Agent Definitions
agents:
  - name: data_processor
    display_name: "Data Processor"
    type: substrate
    created_at: '2025-01-15T10:00:00'
 
    # Optional: Retry configuration
    enable_retry: true
    retry_policy:
      max_retries: 3
      base_delay: 1.0
      max_delay: 60.0
      strategy: exponential
 
# Workflow Definitions
workflows:
  - name: data_pipeline
    display_name: "Data Pipeline"
    type: basic
    created_at: '2025-01-15T10:00:00'
 
# Webhook Configuration (optional)
agents:
  - name: github_agent
    webhooks:
      - slug: "github-push"
        field_mapping:
          "repository.name": "repo_name"
          "commits[0].message": "commit_message"
 
# Schedule Configuration (optional)
schedules:
  agents:
    data_processor:
      cron: "0 */6 * * *"
      enabled: true
      timezone: "UTC"

#Common Workflows

#Development Workflow

bash

# 1. Start a new project
daita init my-project --type analysis
cd my-project
 
# 2. Create components
daita create agent data_processor
daita create workflow data_pipeline
 
# 3. Develop with live testing
daita test --watch
 
# 4. Test specific components
daita test data_processor

#Deployment Workflow

bash

# 1. Ensure tests pass locally
daita test
 
# 2. Check project status
daita status
 
# 3. Deploy to production (requires DAITA_API_KEY)
daita push
 
# 4. Monitor deployment
daita logs --follow
 
# 5. Execute agent remotely
daita run data_processor --data input.json

#Debugging Workflow

bash

# 1. Run tests with verbose output
daita test --verbose
 
# 2. Check detailed status
daita status --verbose
 
# 3. Examine logs
daita logs --lines 100
 
# 4. Test with custom data
daita test my_agent --data debug_data.json
 
# 5. View execution history
daita executions --limit 20

#Error Handling

The CLI provides clear error messages and appropriate exit codes for automation:

#Exit Codes

0 - Success
1 - General error
2 - Invalid command usage
3 - Project context error
4 - Configuration error
5 - Deployment error

#Common Error Messages

Missing Dependencies:

bash

❌ Missing CLI dependencies. Install with:
   pip install PyYAML watchdog
   Or install all CLI dependencies with:
   pip install daita-agents[cli]

Invalid Project Configuration:

bash

❌ Error: Invalid project configuration
   Check your daita-project.yaml file for syntax errors

API Connection Issues:

bash

❌ Failed to fetch deployments: Network error
   Check your DAITA_API_KEY and network connection

#Dependencies

The CLI requires these Python packages (installed automatically):

#Core Dependencies

click - Command line interface framework
pydantic - Configuration validation
asyncio - Asynchronous operations

#Optional Dependencies (CLI extras)

PyYAML - YAML configuration parsing
watchdog - File watching for development
aiohttp - HTTP client for API calls

Install all dependencies:

bash

pip install daita-agents[cli]

#Getting Help

#Command Help

Get help for any command:

bash

daita --help                    # General help
daita init --help              # Command-specific help
daita create agent --help      # Subcommand help

#Verbose Output

Enable detailed output for debugging:

bash

daita --verbose test my_agent
daita -v push production

#Documentation

CLI Reference: Each command has detailed documentation
Online Docs: daita docs opens docs.daita-tech.io
Support: Get your DAITA_API_KEY at daita-tech.io

#Next Steps

Initialize a Project - Create your first Daita project
Create Components - Generate agents and workflows
Testing Guide - Test and debug your agents
Deployment Guide - Deploy to production environments
Monitoring Guide - Monitor deployments and debug issues
Utilities - Version and documentation utilities

#Tips and Best Practices

#Development Tips

Use watch mode: Develop with daita test --watch for immediate feedback
Start small: Begin with basic agents before building complex workflows
Test frequently: Run tests after each significant change
Use verbose mode: Enable --verbose for debugging issues

#Project Organization

Clear naming: Use descriptive names for agents and workflows
Modular design: Keep agents focused on single responsibilities
Documentation: Document your agents and workflows thoroughly
Version control: Use git for tracking changes and collaboration

#Deployment Best Practices

Test locally first: Always test with daita test before deploying
Monitor deployments: Watch logs during and after deployment with daita logs --follow
Use dry-run: Preview deployment changes with daita push --dry-run
Track deployments: Review deployment history with daita deployments list

#Troubleshooting

#Common Issues

Command not found

bash

# Ensure CLI is installed
pip install daita-agents[cli]

Permission denied

bash

# Check file permissions
ls -la daita-project.yaml

API key issues

bash

# Verify API key is set
echo $OPENAI_API_KEY

#Getting Support

Documentation: Use daita docs for comprehensive guides
GitHub Issues: Report bugs and request features
Community: Join discussions and get support from other users

CLI Overview

#Installation

#Quick Start

#Command Structure

#Global Options

#Core Commands

#Project Management

#Development

#Deployment

#Utilities

#Environment Setup

#Required Environment Variables

#Optional Configuration

#Project Context

#Commands that require project context:

#Commands that work anywhere:

#Project Structure

#Configuration File

#Common Workflows

#Development Workflow

#Deployment Workflow

#Debugging Workflow

#Error Handling

#Exit Codes

#Common Error Messages

#Dependencies

#Core Dependencies

#Optional Dependencies (CLI extras)

#Getting Help

#Command Help

#Verbose Output

#Documentation

#Next Steps

#Tips and Best Practices

#Development Tips

#Project Organization

#Deployment Best Practices

#Troubleshooting

#Common Issues

#Getting Support