perplexity-rate-limits

Perplexity Rate Limits

Overview

Handle Perplexity Sonar API rate limits. Perplexity uses a leaky bucket algorithm: burst capacity is available, with tokens refilling continuously at your assigned rate. Rate limits are based on requests per minute (RPM).

Rate Limit Tiers

Rate limits apply per API key, not per model. Using sonar-pro counts against the same RPM as sonar.

Prerequisites

• PERPLEXITY_API_KEY set
• Understanding of HTTP 429 responses

Instructions

Step 1: Exponential Backoff with Jitter

async function withExponentialBackoff<T>(
  operation: () => Promise<T>,
  config = { maxRetries: 5, baseDelayMs: 1000, maxDelayMs: 30000, jitterMs: 500 }
): Promise<T> {
  for (let attempt = 0; attempt <= config.maxRetries; attempt++) {
    try {
      return await operation();
    } catch (error: any) {
      if (attempt === config.maxRetries) throw error;

      const status = error.status || error.response?.status;
      // Only retry on 429 (rate limit) and 5xx (server errors)
      if (status && status !== 429 && status < 500) throw error;

      const exponentialDelay = config.baseDelayMs * Math.pow(2, attempt);
      const jitter = Math.random() * config.jitterMs;
      const delay = Math.min(exponentialDelay + jitter, config.maxDelayMs);

      console.warn(`[Perplexity] ${status || "error"} — retry ${attempt + 1}/${config.maxRetries} in ${delay.toFixed(0)}ms`);
      await new Promise((r) => setTimeout(r, delay));
    }
  }
  throw new Error("Unreachable");
}

// Usage
const result = await withExponentialBackoff(() =>
  perplexity.chat.completions.create({
    model: "sonar",
    messages: [{ role: "user", content: "test query" }],
  })
);

Step 2: Queue-Based Rate Limiting

import PQueue from "p-queue";

// 50 RPM = ~0.83 req/sec. Set intervalCap=1, interval=1200ms for safety.
const perplexityQueue = new PQueue({
  concurrency: 3,
  interval: 1200,
  intervalCap: 1,
});

async function queuedSearch(query: string, model = "sonar") {
  return perplexityQueue.add(() =>
    withExponentialBackoff(() =>
      perplexity.chat.completions.create({
        model,
        messages: [{ role: "user", content: query }],
      })
    )
  );
}

// Batch queries are automatically rate-limited
const queries = ["query 1", "query 2", "query 3", "query 4", "query 5"];
const results = await Promise.all(queries.map((q) => queuedSearch(q)));

Step 3: Token Bucket Implementation (No Dependencies)

class TokenBucket {
  private tokens: number;
  private lastRefill: number;

  constructor(
    private maxTokens: number = 50,
    private refillRate: number = 50 / 60  // 50 per minute = 0.83/sec
  ) {
    this.tokens = maxTokens;
    this.lastRefill = Date.now();
  }

  async acquire(): Promise<void> {
    this.refill();
    if (this.tokens >= 1) {
      this.tokens -= 1;
      return;
    }
    // Wait until a token is available
    const waitMs = (1 / this.refillRate) * 1000;
    await new Promise((r) => setTimeout(r, waitMs));
    this.refill();
    this.tokens -= 1;
  }

  private refill() {
    const now = Date.now();
    const elapsed = (now - this.lastRefill) / 1000;
    this.tokens = Math.min(this.maxTokens, this.tokens + elapsed * this.refillRate);
    this.lastRefill = now;
  }

  get available(): number {
    this.refill();
    return Math.floor(this.tokens);
  }
}

const bucket = new TokenBucket(50, 50 / 60);

async function rateLimitedSearch(query: string) {
  await bucket.acquire();
  return perplexity.chat.completions.create({
    model: "sonar",
    messages: [{ role: "user", content: query }],
  });
}

Step 4: Python Rate Limiting

import time, asyncio
from collections import deque

class RateLimiter:
    def __init__(self, rpm: int = 50):
        self.rpm = rpm
        self.window = deque()

    def wait_if_needed(self):
        now = time.time()
        # Remove timestamps older than 60 seconds
        while self.window and self.window[0] < now - 60:
            self.window.popleft()
        if len(self.window) >= self.rpm:
            sleep_time = 60 - (now - self.window[0])
            time.sleep(max(0, sleep_time))
        self.window.append(time.time())

limiter = RateLimiter(rpm=50)

def rate_limited_search(client, query: str, model: str = "sonar"):
    limiter.wait_if_needed()
    return client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": query}],
    )

Error Handling

Output

• Automatic retry with exponential backoff and jitter
• Queue-based rate limiting for batch operations
• Token bucket for fine-grained control
• Python rate limiter for synchronous code

Resources

• Perplexity Rate Limits
• p-queue Documentation

Next Steps

For security configuration, see perplexity-security-basics.