YAML Agent

YAML data processing tools for AI agents.

from praisonaiagents import Agent
from praisonaiagents import read_yaml, write_yaml, validate_yaml

agent = Agent(
    name="YAMLAgent",
    tools=[read_yaml, write_yaml, validate_yaml],
)
agent.start("Validate and merge these two YAML configs")

The user describes a YAML change; the agent reads, validates, and updates structured config files.

Prerequisites

• Python 3.10 or higher
• PraisonAI Agents package installed
• PraisonAI Tools package installed
• pyyaml package installed
• Basic understanding of YAML format

YAML Tools

Use YAML Tools to process and manipulate YAML files with AI agents.

1. Install Dependencies

   First, install the required packages:

   pip install praisonaiagents praisonai-tools pyyaml
   
2. Import Components

   Import the necessary components:

   from praisonaiagents import Agent, Task, AgentTeam
   from praisonai_tools import read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml
   
3. Create Agent

   Create a YAML processing agent:

   yaml_agent = Agent(
       name="YAMLProcessor",
       role="YAML Processing Specialist",
       goal="Process YAML files efficiently and accurately.",
       backstory="Expert in YAML file manipulation and validation.",
       tools=[read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml],
       reflection=False
   )
   
4. Define Task

   Define the YAML processing task:

   yaml_task = Task(
       description="Parse and validate configuration files.",
       expected_output="Validated and processed YAML configurations.",
       agent=yaml_agent,
       name="yaml_processing"
   )
   
5. Run Agent

   Initialize and run the agent:

   agents = AgentTeam(
       agents=[yaml_agent],
       tasks=[yaml_task],
       process="sequential"
   )
   agents.start()
   

Understanding YAML Tools

What are YAML Tools?

YAML Tools provide YAML processing capabilities for AI agents:

• Reading YAML files
• Writing YAML data
• Validating YAML structure
• Merging YAML files
• Converting between formats

Key Components

YAML Agent

Create specialized YAML agents:

Agent(tools=[read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml])

YAML Task

Define YAML tasks:

Task(description="yaml_operation")

Process Types

Sequential or parallel processing:

process="sequential"

YAML Options

Customize YAML parameters:

safe_load=True, encoding="utf-8"

Available Functions

from praisonai_tools import read_yaml
from praisonai_tools import write_yaml
from praisonai_tools import validate_yaml
from praisonai_tools import merge_yaml
from praisonai_tools import convert_yaml

Examples

Basic YAML Processing Agent

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml

# Create YAML agent
yaml_agent = Agent(
    name="YAMLExpert",
    role="YAML Processing Specialist",
    goal="Process YAML files efficiently and accurately.",
    backstory="Expert in YAML file handling and validation.",
    tools=[read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml],
    reflection=False
)

# Define YAML task
yaml_task = Task(
    description="Parse and validate configuration files.",
    expected_output="Processed and validated YAML data.",
    agent=yaml_agent,
    name="config_processing"
)

# Run agent
agents = AgentTeam(
    agents=[yaml_agent],
    tasks=[yaml_task],
    process="sequential"
)
agents.start()

Advanced YAML Processing with Multiple Agents

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import read_yaml, write_yaml, convert_yaml, validate_yaml, merge_yaml

# Create YAML processing agent
processor_agent = Agent(
    name="Processor",
    role="YAML Processor",
    goal="Process YAML files systematically.",
    tools=[read_yaml, write_yaml, convert_yaml],
    reflection=False
)

# Create validation agent
validator_agent = Agent(
    name="Validator",
    role="Data Validator",
    goal="Validate YAML structure and content.",
    backstory="Expert in data validation and verification.",
    tools=[validate_yaml, merge_yaml],
    reflection=False
)

# Define tasks
processing_task = Task(
    description="Process and transform YAML configurations.",
    agent=processor_agent,
    name="yaml_processing"
)

validation_task = Task(
    description="Validate processed YAML data.",
    agent=validator_agent,
    name="data_validation"
)

# Run agents
agents = AgentTeam(
    agents=[processor_agent, validator_agent],
    tasks=[processing_task, validation_task],
    process="sequential"
)
agents.start()

Best Practices

Agent Configuration

Configure agents with clear YAML focus:

from praisonai_tools import read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml

Agent(
    name="YAMLProcessor",
    role="YAML Processing Specialist",
    goal="Process YAML files accurately and safely",
    tools=[read_yaml, write_yaml, validate_yaml, merge_yaml, convert_yaml]
)

Task Definition

Define specific YAML operations:

Task(
    description="Parse and validate deployment configurations",
    expected_output="Validated configuration set"
)

Common Patterns

YAML Processing Pipeline

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import read_yaml, write_yaml, convert_yaml, validate_yaml, merge_yaml

# Processing agent
processor = Agent(
    name="Processor",
    role="YAML Processor",
    tools=[read_yaml, write_yaml, convert_yaml]
)

# Validation agent
validator = Agent(
    name="Validator",
    role="Data Validator",
    tools=[validate_yaml, merge_yaml]
)

# Define tasks
process_task = Task(
    description="Process YAML files",
    agent=processor
)

validate_task = Task(
    description="Validate processed data",
    agent=validator
)

# Run workflow
agents = AgentTeam(
    agents=[processor, validator],
    tasks=[process_task, validate_task]
)

Related

Custom Tools

Build your own agent tools

Tools Overview

Browse PraisonAI tool documentation