Praison AI

YAML Agent

YAML data processing tools for AI agents.

python
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.

Diagram

Input

Agent

Tool

Output

Diagram
YAML AgentAgentUserYAML AgentAgentUserRequestProcess requestResultResponse

YAML Tools

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

  1. Install Dependencies

    First, install the required packages:

    bash
    pip install praisonaiagents praisonai-tools pyyaml
  2. Import Components

    Import the necessary components:

    python
    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:

    python
    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:

    python
    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:

    python
    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:

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

Define YAML tasks:

python
Task(description="yaml_operation")
 Process Types

Sequential or parallel processing:

python
process="sequential"
 YAML Options

Customize YAML parameters:

python
safe_load=True, encoding="utf-8"

Available Functions

python
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

python
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

python
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:

python
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:

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

Common Patterns

YAML Processing Pipeline

python
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