Configuration Reference

Complete configuration guide for PraisonAI agents, tasks, memory, and more

Configuration Reference

This section provides comprehensive documentation for all configuration options in PraisonAI. Each component has its own detailed configuration guide with examples, best practices, and advanced options.

Configuration Categories

Agent Configuration

Complete guide to agent parameters including max_iter, max_retry_limit, context_length, and markdown options

Task Configuration

Task parameters including task_type, condition, next_tasks, and is_start options

Memory Configuration

Memory system configuration including graph store, quality scores, and embedder options

LLM Configuration

LLM settings including retry logic, timeouts, and custom headers

Tool Configuration

Tool timeout settings and performance tuning options

Handoff Configuration

Handoff filters and advanced delegation settings

Guardrail Configuration

Custom validation rules and guardrail settings

Best Practices

Configuration best practices and common patterns

CLI Configuration

Layered, project-aware defaults for the praisonai CLI (~/.praisonai/config.yaml)

Single-Source Config

Now also the single source of truth for mcp servers and permissions policy — model, MCP, and permissions in one file.

Quick Reference

Essential Configuration Parameters

Component	Parameter	Type	Description
Agent	`max_iter`	int	Maximum iterations for task completion
Agent	`max_retry_limit`	int	Max retries for retryable tool and guardrail failures (`1 + limit` total attempts)
Agent	`retry_initial_delay`	float	First retry delay in seconds (exponential backoff)
Agent	`retry_backoff_factor`	float	Backoff multiplier per retry attempt
Agent	`retry_jitter`	float	Jitter fraction added to each retry delay
Task	`task_type`	str	Type of task execution
Memory	`quality_threshold`	float	Minimum quality score for memory retrieval
LLM	`timeout`	int	Request timeout in seconds
Tool	`execution_timeout`	int	Tool execution timeout

Environment Variables

PraisonAI supports configuration through environment variables for sensitive settings:

bash

# LLM Configuration
export OPENAI_API_KEY="your-api-key"
export OPENAI_MODEL="gpt-4o"

# Memory Configuration
export PRAISONAI_MEMORY_PROVIDER="rag"
export PRAISONAI_DB_PATH="/path/to/db"

# Performance Settings
export PRAISONAI_MAX_WORKERS=4
export PRAISONAI_TIMEOUT=300

Configuration Files

PraisonAI supports YAML configuration files for complex setups:

yaml

# config.yaml
agents:
  default:
    max_iter: 15
    max_retry_limit: 3
    context_length: 128000
    markdown: true

memory:
  provider: rag
  quality_threshold: 0.7
  graph_enabled: true

llm:
  timeout: 60
  max_retries: 3
  temperature: 0.7

Getting Started

Start with the Agent Configuration to set up your agents
Configure Tasks for your workflow
Set up Memory for persistent storage
Fine-tune LLM settings for optimal performance

Need Help?

Check our Best Practices guide
See Examples for real-world configurations
Visit our GitHub for issues and discussions