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Documentation Index

Fetch the complete documentation index at: https://docs.praison.ai/llms.txt

Use this file to discover all available pages before exploring further.

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

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]
)
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]
)