feat: add InsufficientQuotaError for insufficient_quota 429 responses

What this error means

RateLimitError raised for both temporary rate limits AND quota exhaustion (insufficient_quota 429s), requiring different handling strategies is a OpenAI API failure pattern reported for developers trying to distinguish between temporary rate limits (retry-after delay) and quota exhaustion (insufficient_quota) in openai api 429 responses for proper error handling. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub PR openai/openai-python#3042 — Users cannot distinguish temporary rate limits from permanent quota exhaustion because both raise generic RateLimitError. Needs InsufficientQuotaError subclass. Commercial impact on paid API users who may be blocked indefinitely after quota max-out.

Common causes

• GitHub PR openai/openai-python#3042 — Users cannot distinguish temporary rate limits from permanent quota exhaustion because both raise generic RateLimitError. Needs InsufficientQuotaError subclass. Commercial impact on paid API users who may be blocked indefinitely after quota max-out.

Quick fixes

1. Confirm the exact error signature matches RateLimitError raised for both temporary rate limits AND quota exhaustion (insufficient_quota 429s), requiring different handling strategies.
2. Check the OpenAI API account, local tool state, and provider configuration involved in the failing workflow.
3. Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.

Platform/tool-specific checks

• Verify the command, editor, extension, or API client that produced the error.
• Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
• Avoid deleting credentials, local model data, or project settings until the failing scope is clear.

Step-by-step troubleshooting

1. Capture the exact error message and the command, editor action, or request that triggered it.
2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
3. Review the source evidence below and compare it with your environment.
4. Apply one change at a time and rerun the smallest failing action.
5. Keep the working fix documented for the team or deployment environment.

How to prevent it

• Keep provider/tool configuration documented.
• Record non-secret diagnostics such as tool version, provider name, model name, and command path.
• Add a lightweight check before CI or production workflows depend on the tool.

Sources checked

• https://github.com/openai/openai-python/pull/3042

Evidence note: GitHub PR openai/openai-python#3042 — Users cannot distinguish temporary rate limits from permanent quota exhaustion because both raise generic RateLimitError. Needs InsufficientQuotaError subclass. Commercial impact on paid API users who may be blocked indefinitely after quota max-out.

Related errors

• OpenAI API

FAQ

What should I check first?

Start with the exact RateLimitError raised for both temporary rate limits AND quota exhaustion (insufficient_quota 429s), requiring different handling strategies text and the smallest action that reproduces it.

Can I ignore this error?

No. Treat it as a failed OpenAI API workflow until the root cause is understood.

Is this guaranteed to have one fix?

No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.

How do I know the fix worked?

Rerun the same command, editor action, or request. The fix is working when that action completes without RateLimitError raised for both temporary rate limits AND quota exhaustion (insufficient_quota 429s), requiring different handling strategies.