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Cap LLM call rate so agents stay within provider quotas and budget — safely, even when many agents share one limiter. 
from praisonaiagents import Agent, ExecutionConfig

agent = Agent(
    name="Researcher",
    instructions="Research topics concisely.",
    execution=ExecutionConfig(max_rpm=60),
)

agent.start("Summarise the latest Mars rover news")
The user runs agents at scale; the limiter queues or throttles LLM calls so quotas are not exceeded.
For bot/messaging rate limiting (Telegram, Discord, Slack), see Bot Rate Limiting. This page covers LLM API rate limiting.

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How It Works

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Quick Start

1

Simple Usage

Set max_rpm on execution config for a single agent:
from praisonaiagents import Agent, ExecutionConfig

agent = Agent(
    name="Researcher",
    instructions="You research topics on the web.",
    execution=ExecutionConfig(max_rpm=60),
)

agent.start("Summarise the latest Mars rover news")
2

With Configuration

Share one RateLimiter across multiple agents:
from praisonaiagents import Agent, AgentTeam, ExecutionConfig
from praisonaiagents.llm import RateLimiter

shared = RateLimiter(requests_per_minute=60, burst=5)

researcher = Agent(
    name="Researcher",
    instructions="Research topics",
    execution=ExecutionConfig(rate_limiter=shared),
)
writer = Agent(
    name="Writer",
    instructions="Write articles",
    execution=ExecutionConfig(rate_limiter=shared),
)

AgentTeam(agents=[researcher, writer]).start()

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How It Works

Token bucket algorithm: tokens refill at requests_per_minute / 60 per second; each LLM call consumes one token. Under contention, callers wait until a token is available. The limiter applies to both the initial LLM call and the follow-up after tool execution in streaming mode. The rate limiter applies to every LLM call the agent issues — single-shot, streaming, tool-iteration and reflection turns, sync and async — so a per-model token budget is never spent on a path that bypasses throttling.
StepWhat happens
RefillTokens regenerate on elapsed time
AcquireCaller reserves a token (thread-safe)
WaitSleeps or awaits when bucket is empty
ReleaseAutomatic — rolling window, no explicit release

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Configuration Options

OptionTypeDefaultDescription
max_rpmintNoneShorthand on ExecutionConfig
requests_per_minuteintNoneMax requests per rolling 60s window
tokens_per_minuteintNoneToken budget for TPM-quoted providers
burstint1Back-to-back requests before rate kicks in
max_retry_delayint120Max wait seconds when rate limited

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Best Practices

Low burst (1–5) smooths traffic; higher burst tolerates spiky demand.
Providers quote RPM and TPM — limiting only RPM can still trigger 429 errors.
agent.achat() calls acquire_async() automatically; avoid mixing sync and async limiters.

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CLI

praisonai "task" --rpm 60

Thread Safety

Thread-safe chat history and caches

Concurrency

Limit parallel agent runs