OpenAI Context Length Exceeded Fix

Context length errors happen when the request input, instructions, tools and expected output exceed the model context window.

Symptoms

  • The API rejects a large request before generating output.
  • Long chat history works until one extra message is added.
  • A coding agent sends full files or logs into one request.

Likely causes

  • Prompt, conversation history or pasted logs are too large.
  • The request includes unnecessary tool schemas or repeated context.
  • The selected model has a smaller context window than expected.

Fix steps

  1. Remove duplicate context and irrelevant logs.
  2. Summarize earlier conversation history before sending it again.
  3. Split large files or tasks into smaller requests.
  4. Check the selected model family and token limits.

Verify the fix

  • Run the same request with a shorter input.
  • Log approximate input size before sending.
  • Keep a minimal failing payload for comparison.

FAQ

Can max tokens fix context length?

Lowering output tokens can help only if total input plus output budget fits the model window.

Should I paste complete repositories into one request?

No. Send the smallest files and context needed for the current task.

Related tools and guides

OpenAI OpenAI API Request Checker

Statically inspect an OpenAI API request body for common JSON and parameter mistakes before sending it to the API.

 JSON JSON Validator and Formatter

Validate JSON, format it for reading, or minify it for compact API payloads without sending data to an external API.

 Prompt AI Prompt Debugger

Analyze coding-agent prompts for missing context, vague goals, unsafe instructions, unclear outputs and weak verification steps.

 OpenAI Debug OpenAI API Request JSON Before Sending

Most API request bugs are easier to fix before the request is sent. Start with valid JSON, then check model-family parameters and only then debug application code.

Last updated: May 18, 2026