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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/ably/docs/llms.txt

Use this file to discover all available pages before exploring further.

LLM token streaming introduces high-rate or bursty traffic patterns to your application, with some models outputting upwards of 150 distinct events (that is, tokens or response deltas) per second. Output rates can vary unpredictably over the lifetime of a response stream, and you have limited control over third-party model behaviour. AI Transport provides functionality to help you stay within your rate limits while delivering a great experience to your users. Ably’s limits divide into two categories:
  1. Limits relating to usage across an account, such as the total number of messages sent in a month, or the aggregate instantaneous message rate across all connections and channels
  2. Limits relating to the capacity of a single resource, such as a connection or a channel
Limits in the first category exist to provide protection in the case of accidental spikes or deliberate abuse. Provided that your package is sized correctly for your use-case, these limits should not be hit as a result of valid traffic. The limits in the second category, however, cannot be increased arbitrarily and exist to protect the integrity of the service. The limits associated with individual connections or channels can be relevant to LLM token streaming use-cases. The following sections discuss these limits in particular.

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Message-per-response

The message-per-response pattern includes automatic rate limit protection. AI Transport prevents a single response stream from reaching the message rate limit for a connection by rolling up multiple appends into a single published message:
  1. Your agent streams tokens to the channel at the model’s output rate
  2. Ably publishes the first token immediately, then automatically rolls up subsequent tokens on receipt
  3. Clients receive the same content, delivered in fewer discrete messages
By default, Ably delivers a single response stream at 25 messages per second or the model output rate, whichever is lower. This means you can publish two simultaneous response streams on the same channel or connection with any Ably package, because each stream uses half of the connection inbound message rate. Ably charges for the number of published messages, not for the number of streamed tokens.

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Configure rollup behaviour

Ably concatenates all appends for a single response that are received during the rollup window into one published message. You can specify the rollup window for a particular connection by setting the appendRollupWindow transport parameter. This allows you to determine how much of the connection message rate can be consumed by a single response stream and control your consumption costs.
appendRollupWindowMaximum message rate for a single response
0msModel output rate
20ms50 messages/s
40ms (default)25 messages/s
100ms10 messages/s
500ms (max)2 messages/s
The following example code demonstrates establishing a connection to Ably with appendRollupWindow set to 100ms:

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Message-per-token

The message-per-token pattern requires you to manage rate limits directly. Each token publishes as a separate message, so high-speed model output can cause per-connection or per-channel rate limits to be hit, as well as consuming overall message allowances quickly. To stay within limits:
  • Calculate your headroom by comparing your model’s peak output rate against your package’s connection inbound message rate
  • Account for concurrency by multiplying peak rates by the maximum number of simultaneous streams your application supports
  • If required, batch tokens in your agent before publishing to the SDK, reducing message count while maintaining delivery speed
  • Enable server-side batching to reduce the number of messages delivered to your subscribers
If your application requires higher message rates than your current package allows, contact Ably to discuss options.

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