Rate Limits

Rate limits protect the API from abuse and ensure fair usage across all users. The SolidRusT AI API enforces rate limits at the Artemis Gateway and PAM Platform levels.

Current Limits

The console is the source of truth. Artemis asks PAM to validate your key and reads X-Rate-Limit / X-Tier from that response. Docs do not own the numbers. If this page and the console disagree, the console wins.

See your live limits at console.solidrust.ai.

Token windows (model capacity, not billing) are documented under Models and Context Limits.

Rate Limit Headers

Every API response includes rate limit information in the headers:

HTTP/1.1 200 OK
X-RateLimit-Limit: 60
X-RateLimit-Remaining: 45
X-RateLimit-Reset: 1704067260
X-RateLimit-Window: 60

Header	Description
X-RateLimit-Limit	Maximum requests allowed in the current window
X-RateLimit-Remaining	Requests remaining in current window
X-RateLimit-Reset	Unix timestamp when the limit resets
X-RateLimit-Window	Window duration in seconds

Handling Rate Limits

HTTP 429 Response

When rate limited, you’ll receive HTTP 429 with this format:

{
  "error": {
    "message": "Rate limit exceeded. Please retry after 60 seconds.",
    "type": "rate_limit_error",
    "code": "rate_limit_exceeded"
  }
}

Retry-After Header

The response includes a Retry-After header indicating how long to wait:

HTTP/1.1 429 Too Many Requests
Retry-After: 30
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1704067260

Retry Strategies

Exponential Backoff (Recommended)

The best approach is exponential backoff with jitter:

import time
import random
from openai import OpenAI, RateLimitError

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.solidrust.ai/v1"
)

def make_request_with_retry(messages, max_retries=5, base_delay=1):
    """Make a request with exponential backoff retry logic."""
    for attempt in range(max_retries):
        try:
            return client.chat.completions.create(
                model="vllm-primary",
                messages=messages
            )
        except RateLimitError as e:
            if attempt == max_retries - 1:
                raise

            # Use Retry-After header if available
            retry_after = getattr(e, 'retry_after', None)
            if retry_after:
                wait_time = retry_after
            else:
                # Exponential backoff with jitter
                wait_time = (base_delay * (2 ** attempt)) + random.uniform(0, 1)

            print(f"Rate limited (attempt {attempt + 1}/{max_retries}), "
                  f"waiting {wait_time:.1f}s...")
            time.sleep(wait_time)

# Usage
response = make_request_with_retry([
    {"role": "user", "content": "Hello!"}
])

JavaScript/TypeScript

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'YOUR_API_KEY',
  baseURL: 'https://api.solidrust.ai/v1',
});

async function makeRequestWithRetry(messages, maxRetries = 5, baseDelay = 1000) {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await client.chat.completions.create({
        model: 'vllm-primary',
        messages,
      });
    } catch (error) {
      if (!(error instanceof OpenAI.RateLimitError)) {
        throw error;
      }

      if (attempt === maxRetries - 1) {
        throw error;
      }

      // Use Retry-After header if available
      const retryAfter = error.headers?.['retry-after'];
      const waitTime = retryAfter
        ? parseInt(retryAfter) * 1000
        : (baseDelay * Math.pow(2, attempt)) + Math.random() * 1000;

      console.log(`Rate limited (attempt ${attempt + 1}/${maxRetries}), ` +
                  `waiting ${(waitTime / 1000).toFixed(1)}s...`);
      await new Promise(resolve => setTimeout(resolve, waitTime));
    }
  }
}

// Usage
const response = await makeRequestWithRetry([
  { role: 'user', content: 'Hello!' }
]);

Request Queuing

For high-volume applications, implement a request queue:

import asyncio
from collections import deque
from datetime import datetime, timedelta

class RateLimitedQueue:
    def __init__(self, requests_per_minute=60):
        self.rpm = requests_per_minute
        self.request_times = deque(maxlen=requests_per_minute)

    async def wait_for_slot(self):
        """Wait until a rate limit slot is available."""
        while len(self.request_times) >= self.rpm:
            oldest = self.request_times[0]
            wait_until = oldest + timedelta(minutes=1)
            wait_seconds = (wait_until - datetime.now()).total_seconds()

            if wait_seconds > 0:
                await asyncio.sleep(wait_seconds)

            # Remove expired entries
            cutoff = datetime.now() - timedelta(minutes=1)
            while self.request_times and self.request_times[0] < cutoff:
                self.request_times.popleft()

    def record_request(self):
        """Record a successful request."""
        self.request_times.append(datetime.now())

# Usage
queue = RateLimitedQueue(requests_per_minute=60)

async def make_request(messages):
    await queue.wait_for_slot()
    response = await client.chat.completions.create(
        model="vllm-primary",
        messages=messages
    )
    queue.record_request()
    return response

Best Practices

Avoiding Rate Limits

1. Implement request queuing - Don’t burst requests
2. Use batch endpoints when processing multiple items
3. Cache responses when appropriate (especially for identical queries)
4. Monitor usage via response headers
5. Pre-fetch during low traffic if you have predictable workloads

Monitor Your Usage

Track rate limit headers to stay ahead of limits:

def make_request_with_monitoring(messages):
    response = client.chat.completions.create(
        model="vllm-primary",
        messages=messages
    )

    # Access rate limit headers from raw response
    remaining = response.response.headers.get('X-RateLimit-Remaining', 'unknown')
    limit = response.response.headers.get('X-RateLimit-Limit', 'unknown')

    if remaining != 'unknown' and int(remaining) < 10:
        print(f"Warning: Only {remaining}/{limit} requests remaining")

    return response

Requesting Higher Limits

Self-Service Upgrade

1. Log in to console.solidrust.ai
2. Navigate to Subscription > Upgrade Plan
3. Select your desired tier
4. Complete payment

Enterprise Limits

For custom enterprise limits:

• Email: support@solidrust.ai
• Subject: “Enterprise Rate Limit Request”
• Include:
  • Expected requests per minute/hour/day
  • Use case description
  • Current tier and account email

Related

• Error Handling - Complete error reference including 429 responses
• Authentication - API key management
• API Keys - How to generate and manage API keys