Skip to main content
Reflection makes agents review and refine their own answers, catching mistakes and improving quality automatically. 
from praisonaiagents import Agent

agent = Agent(
    name="Assistant",
    instructions="You are a precise technical writer.",
    reflection=True,
)

agent.start("Explain how TCP/IP handshakes work.")
The user asks a question; the agent drafts, self-reviews, and refines before returning the final answer.

​
Quick Start

1

Level 1 — Bool (simplest)

Turn on self-review with a single flag.
from praisonaiagents import Agent

agent = Agent(
    name="Writer",
    instructions="You are a technical writer.",
    reflection=True,
)
agent.start("Write clear documentation for a REST API authentication flow.")
2

Level 2 — Config class (tune iterations and LLM)

Use ReflectionConfig to control how many review passes run and which LLM critiques.
from praisonaiagents import Agent, ReflectionConfig

agent = Agent(
    name="Writer",
    instructions="You are a technical writer.",
    reflection=ReflectionConfig(
        min_iterations=1,
        max_iterations=3,
        llm="gpt-4o",
    ),
)
agent.start("Write a detailed security review of OAuth 2.0.")
3

Level 3 — Config with a custom review prompt

Pass a domain-specific prompt to steer what the self-review checks for.
from praisonaiagents import Agent, ReflectionConfig

agent = Agent(
    name="Reviewer",
    instructions="You are a code reviewer.",
    reflection=ReflectionConfig(
        max_iterations=2,
        prompt="Evaluate your response for: accuracy, completeness, and clarity. Improve if needed.",
    ),
)
agent.start("Review this Python function for bugs and performance issues.")

​
How It Works

PhaseWhat happens
1. DraftAgent generates initial response
2. EvaluateReflection checks quality against criteria
3. ImproveAgent rewrites based on self-critique
4. DeliverFinal polished response returned to user

​
Configuration Options

Full list of options, types, and defaults — ReflectionConfig
OptionTypeDefaultDescription
min_iterationsint1Minimum reflection passes (always runs at least once)
max_iterationsint3Maximum reflection passes
llmstr | NoneNoneLLM for reflection (defaults to agent’s LLM)
promptstr | NoneNoneCustom reflection evaluation prompt

​
Common Patterns

​
Pattern 1 — Quality-focused writing

from praisonaiagents import Agent, ReflectionConfig

agent = Agent(
    instructions="You are a professional copywriter.",
    reflection=ReflectionConfig(min_iterations=2, max_iterations=3),
)
response = agent.start("Write an engaging product description for a smart home speaker.")
print(response)

​
Pattern 2 — Factual accuracy check

from praisonaiagents import Agent, ReflectionConfig

agent = Agent(
    instructions="You are a fact-checking assistant.",
    reflection=ReflectionConfig(
        max_iterations=2,
        prompt="Check for factual inaccuracies, missing context, or ambiguous statements.",
    ),
)
agent.start("Summarize the key events of the Apollo 11 mission.")

​
Best Practices

Enable reflection for writing tasks, technical explanations, and any output where quality matters more than speed. Skip it for simple lookups, calculations, or real-time applications.
Each reflection pass costs an additional LLM call. Set max_iterations=1 for light review, 2 for thorough review, and only go to 3 for high-stakes content. The default is 3.
Default reflection uses general quality criteria. Pass a prompt tailored to your domain — e.g., “Check for HIPAA compliance language” for medical agents or “Verify all code is PEP 8 compliant” for coding agents.

Planning — plan before acting on complex requests

Self-Reflection Deep Dive — advanced reflection patterns