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Convex Agents Rate Limiting

Controls message frequency and token usage to prevent abuse and manage API budgets. Use this to implement per-user limits, global caps, burst capacity, and token quota management.

SKILL.md

Full skill instructions

Purpose

Rate limiting protects against abuse, manages LLM costs, and ensures fair resource allocation. Covers message frequency limits and token usage quotas.

When to Use This Skill

  • Preventing rapid-fire message spam
  • Limiting total tokens per user
  • Implementing burst capacity
  • Global API limits to stay under provider quotas
  • Fair resource allocation in multi-user systems
  • Billing based on token usage

Configure Rate Limiter

import { RateLimiter, MINUTE, SECOND } from "@convex-dev/​rate-limiter";

export const rateLimiter = new RateLimiter(components.rateLimiter, {
  sendMessage: {
    kind: "fixed window",
    period: 5 * SECOND,
    rate: 1,
    capacity: 2,
  },
  globalSendMessage: {
    kind: "token bucket",
    period: MINUTE,
    rate: 1_000,
  },
  tokenUsagePerUser: {
    kind: "token bucket",
    period: MINUTE,
    rate: 2000,
    capacity: 10000,
  },
  globalTokenUsage: {
    kind: "token bucket",
    period: MINUTE,
    rate: 100_000,
  },
});

Check Message Rate Limit

export const sendMessage = mutation({
  args: { threadId: v.string(), message: v.string(), userId: v.string() },
  handler: async (ctx, { threadId, message, userId }) => {
    try {
      await rateLimiter.limit(ctx, "sendMessage", {
        key: userId,
        throws: true,
      });

      await rateLimiter.limit(ctx, "globalSendMessage", { throws: true });

      const { messageId } = await saveMessage(ctx, components.agent, {
        threadId,
        prompt: message,
      });

      return { success: true, messageId };
    } catch (error) {
      if (isRateLimitError(error)) {
        return {
          success: false,
          error: "Rate limit exceeded",
          retryAfter: error.data.retryAfter,
        };
      }
      throw error;
    }
  },
});

Check Token Usage

export const checkTokenUsage = action({
  args: { threadId: v.string(), question: v.string(), userId: v.string() },
  handler: async (ctx, { threadId, question, userId }) => {
    const estimatedTokens = await estimateTokens(ctx, threadId, question);

    try {
      await rateLimiter.check(ctx, "tokenUsagePerUser", {
        key: userId,
        count: estimatedTokens,
        throws: true,
      });

      // Proceed with generation
      const { thread } = await myAgent.continueThread(ctx, { threadId });
      const result = await thread.generateText({ prompt: question });

      return { success: true, response: result.text };
    } catch (error) {
      if (isRateLimitError(error)) {
        return {
          success: false,
          error: "Token limit exceeded",
          retryAfter: error.data.retryAfter,
        };
      }
      throw error;
    }
  },
});

async function estimateTokens(
  ctx: QueryCtx,
  threadId: string,
  question: string
): Promise<number> {
  const questionTokens = Math.ceil(question.length / 4);
  const responseTokens = Math.ceil(questionTokens * 3);
  return questionTokens + responseTokens;
}

Track Actual Usage

const myAgent = new Agent(components.agent, {
  name: "My Agent",
  languageModel: openai.chat("gpt-4o-mini"),
  usageHandler: async (ctx, { usage, userId }) => {
    if (!userId) return;

    await rateLimiter.limit(ctx, "tokenUsagePerUser", {
      key: userId,
      count: usage.totalTokens,
      reserve: true,
    });
  },
});

Client-Side Rate Limit Checking

import { useRateLimit } from "@convex-dev/​rate-limiter/​react";
import { isRateLimitError } from "@convex-dev/​rate-limiter";

function ChatInput() {
  const { status } = useRateLimit(api.rateLimiting.getRateLimit);

  if (status && !status.ok) {
    return (
      <div className="text-red-500">
        Rate limit exceeded. Retry after{" "}
        {new Date(status.retryAt).toLocaleTimeString()}
      </​div>
    );
  }

  return <input type="text" placeholder="Send a message..." />;
}

Key Principles

  • Fixed window for frequency: Use for simple X per period
  • Token bucket for capacity: Use for burst-friendly limits
  • Estimate before, track after: Prevent early, record actual usage
  • Global + per-user limits: Balance fair access with resource caps
  • Retryable errors: Clients can retry with backoff

Next Steps

  • See usage-tracking for billing based on token usage
  • See fundamentals for agent setup
  • See debugging for troubleshooting

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