Async Self-Reflection

Self-reflection now works in async agents using the unified dispatch path

Self-reflection enables agents to evaluate and improve their responses in async execution, bringing full feature parity with sync agents.

import asyncio
from praisonaiagents import Agent

agent = Agent(
    name="Writer",
    instructions="Write concise product blurbs.",
    self_reflect=True,
    min_reflect=1,
    max_reflect=3,
)

async def main():
    await agent.achat("Write a one-line blurb for a smart mug.")

asyncio.run(main())

The user asks for copy; the agent drafts, self-reflects, and improves the answer before replying.

Quick Start

1. Basic Async Reflection

   Enable reflection in async agents with simple boolean flag:

   import asyncio
   from praisonaiagents import Agent
   
   agent = Agent(
       name="Writer",
       instructions="Write concise product blurbs.",
       self_reflect=True,
       min_reflect=1,
       max_reflect=3,
   )
   
   async def main():
       result = await agent.achat("Write a one-line blurb for a smart mug.")
       print(result)
   
   asyncio.run(main())

2. Custom Reflection Criteria

   Configure reflection with custom criteria for async agents:

   import asyncio
   from praisonaiagents import Agent, ReflectionConfig
   
   agent = Agent(
       name="Technical Writer",
       instructions="Create technical documentation.",
       self_reflect=ReflectionConfig(
           min_reflect=2,
           max_reflect=5,
           criteria="Is the response clear, accurate, and complete?"
       )
   )
   
   async def main():
       result = await agent.achat("Explain async/await in Python.")
       print(result)
   
   asyncio.run(main())

How It Works

Self-reflection in async agents follows the same process as sync agents:

Feature Parity

Prior to PR #1704, async agents had limited reflection support:

Configuration Options

All reflection configuration options work identically in async agents:

Best Practices

Related