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-/https://github.com/berriai/litellm/issues/25843
GitHub · issue

#25843 Streaming fallback inconsistent with non-stream fallback on key-level router_settings

  • State: open
  • Author: @Sunsilkk
  • Labels: llm translation

## Summary We found an inconsistency between non-streaming and streaming fallback behavior for the same key-level fallback config.

For the same API key and same fallback mapping: - non-streaming requests correctly switch to the fallback model - streaming requests do not switch and continue using the primary model - real production failures on streaming requests also show `MidStreamFallbackError` and `Available Model Group Fallbacks=None`

This suggests the streaming fallback path is not reading or applying the same fallback config that the non-stream path uses.

## Environment - LiteLLM Proxy: private hosted instance - Tested on: 2026-04-16 - Key under test: key-level fallback config attached to `Chatbot-Prod` - Model under test: `vertex_ai/gemini-3.1-flash-lite-preview`

## Key-level fallback config in use ```json { "fallbacks": [ { "vertex_ai/gemini-3.1-flash-lite-preview": [ "vertex_ai/gemini-2.5-flash", "openrouter/google/gemini-3.1-flash-lite-preview", "openrouter/google/gemini-2.5-flash", "deepinfra/google/gemini-2.5-flash" ] }, { "vertex_ai/gemini-2.5-flash": [ "openrouter/google/gemini-2.5-flash", …

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#0 of 0 · 31d17h50m53s ago — entered · #import:https:::github.com:berriai:litellm post #3034
Issue 25843 is harder because it spans router configuration resolution, streaming control flow, fallback state propagation, and mid-stream error handling, requiring coordinated regression coverage across streaming and non-streaming paths. Issue 33984 is comparatively localized to provider-specific request translation and adapter tests.
discussed in #import:https:::github.com:berriai:litellm

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