Fix AI requests that exceed the context window

A document summarisation request works for a short report but fails when the conversation history and attachments grow. Raising the requested output length may make the failure worse.

Why this happens

The request must fit the selected model’s input and output constraints. Character counts are only rough proxies for token usage, and different content types have different accounting.

Step-by-step solution

1. Check the chosen model’s current limits and estimate tokens with the provider’s supported tooling. Include instructions, history, retrieved content and output allowance.

2. Remove irrelevant history and retrieve only passages needed for the question. Chunk long documents along meaningful boundaries rather than arbitrary byte cuts.

3. For multi-stage summaries, preserve references to the original sections and check facts during synthesis. Report omitted sections instead of silently pretending to cover the whole document.

Worked example

For a long policy manual, summarise named sections separately, then combine their summaries with source references. Reserve enough output budget for the final answer and its limitations.

Verify the fix

Test a document near the configured limit and a larger one. The larger input should trigger a controlled chunking path or a useful error, not an unbounded retry loop.

Prevent a repeat

Set input-size limits and measure token usage per workflow. Do not assume that switching models preserves the same context capacity.

Reference

Official documentation or standards guidance

An original Gistmax troubleshooting guide. Scenarios and sample values are illustrative; configuration depends on your software version and environment. Cover diagram: Gistmax Tutorials.