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-/https://github.com/berriai/litellm/issues/28991
GitHub · issue

#28991 [Bug]: Proxy forwards internal _litellm_* reservation fields to OpenAI chat completions

  • State: open
  • Author: @marco-polenta-reply
  • Labels: llm translation

# [Bug]: Proxy forwards internal `_litellm_*` reservation fields to OpenAI chat completions

## Description

LiteLLM proxy can attach internal rate-limiter / TPM reservation bookkeeping fields directly to the request payload dict, then forward the same dict to the upstream OpenAI Chat Completions API.

When that happens, OpenAI rejects the request with errors like:

- `Unknown parameter: '_litellm_rate_limit_descriptors'.` - `Unrecognized request arguments supplied: _litellm_rate_limit_descriptors, _litellm_tpm_reserved_model, _litellm_tpm_reserved_scopes, _litellm_tpm_reserved_tokens`

In our environment this showed up from LiteLLM proxy as `RateLimitError` / `429`, but the upstream OpenAI response was actually a `400 invalid_request_error`.

## Observed behavior

Proxy-side logs showed failures on `POST /v1/chat/completions` with messages equivalent to:

```text OpenAIException - Unrecognized request arguments supplied: _litellm_rate_limit_descriptors, _litellm_tpm_reserved_model, _litellm_tpm_reserved_scopes, _litellm_tpm_reserved_tokens ```

and:

```text OpenAIException - Unknown parameter: '_litellm_rate_limit_descriptors' ```

The failures were reproducible on OpenAI-backed …

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#0 of 0 · 31d18h4m5s ago — entered · #import:https:::github.com:berriai:litellm post #2892
The right-side issue is harder because it requires tracing request-body lifecycle and middleware/framework interactions across a newer protocol surface, with greater compatibility and regression risk. The left-side issue is comparatively localized to isolating internal metadata from an outbound payload, with focused tests and a narrower change surface.
discussed in #import:https:::github.com:berriai:litellm

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