Gateway Agent Defaults
Chat-optimised defaults for YAML agents behind the gateway
from praisonaiagents import Agent
agent = Agent(
name="chat-assistant",
instructions="You are a helpful assistant.",
reflect_on_output=False,
)
agent.start("Reply as fast as possible.")Gateway agents use chat-optimised defaults to ensure fast response times for interactive chat applications.
# gateway.yaml — fast by default (reflection=false)
agents:
assistant:
instructions: "You are a helpful AI assistant."
model: gpt-4o-miniThe user chats with the assistant; gateway defaults keep replies fast by disabling reflection on the agent path.
Quick Start
- Fast by default
Create a minimal
bot.yamlwith fast defaults:yaml agents: assistant: instructions: "You are a helpful AI assistant." model: gpt-4o-miniResponse latency: ~1.6 seconds on short prompts.
- Opt in to reflection
Add reflection for higher quality responses:
yaml agents: assistant: instructions: "You are a helpful AI assistant." model: gpt-4o-mini reflection: true # opt-in: enables self-critiqueResponse latency: ~12.3 seconds (8x slower for better quality).
How It Works
Gateway agents optimize for chat channel performance with different flow patterns:
| Mode | Reflection | Latency | Quality |
|---|---|---|---|
| Fast (default) | false | ~1.6s | Direct response |
| Quality (opt-in) | true | ~12.3s | Self-critiqued response |
Configuration Options
Gateway agents loaded from YAML use chat-optimised defaults:
| YAML key | Gateway default | SDK default | Why different |
|---|---|---|---|
reflection | false | false | Chat channels need sub-second replies |
tool_choice | null (auto) | null (auto) | Let LLM decide when to call tools |
allow_delegation | false | false | Prevents routing unless opted in |
Common Patterns
Plain Chat Assistant
agents:
assistant:
instructions: "You are a helpful AI assistant."
model: gpt-4o-mini
# reflection defaults to false - fast responsesHigh-Quality Q&A Bot
agents:
expert:
instructions: "You are an expert consultant. Think carefully before answering."
model: gpt-4o
reflection: true # opt-in for quality over speedMixed Agent Configuration
agents:
quickhelp:
instructions: "Handle basic questions quickly."
model: gpt-4o-mini
# reflection=false (default) - fast responses
research:
instructions: "Conduct thorough research and analysis."
model: gpt-4o
reflection: true # enable self-critique for researchBest Practices
Default is fast — only enable reflection when quality matters more than latency
Gateway agents default to reflection: false because chat applications prioritize response speed. Enable reflection only for agents handling complex analysis or research tasks.
Measure before opting in: reflection adds 1..max_reflect=3 extra LLM round-trips per message
Each reflection cycle requires additional API calls. For gpt-4o-mini, this increases latency from ~1.6s to ~12.3s. Test your specific use case to validate the quality improvement justifies the speed tradeoff.
Use reflection selectively per agent, not globally
Configure reflection per agent based on their role. Quick support agents should stay fast, while research or analysis agents benefit from reflection.
For background / long-form tasks use the Python SDK directly — it has different defaults suited to that use case
Gateway defaults optimize for interactive chat. For batch processing, long-running tasks, or non-interactive workflows, use the Python SDK directly where different performance characteristics apply.