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-/https://github.com/berriai/litellm/issues/27453
GitHub · issue

#27453 When reasoning_effort is set to none, thinking should be automatically disabled(for deepseek-v4)

  • State: open
  • Author: @Xiaohaoyu1020
  • Labels: llm translation

## Problem Description

When testing DeepSeek v4 official API calls, I observed that if `thinking` and `reasoning_effort` are not explicitly set, the model defaults to thinking mode (returns `reasoning_content`). However, when a user wants to completely disable thinking (i.e., `reasoning_effort = none`), they currently must manually add `"thinking": {"type": "disabled"}` to achieve the expected behavior.

This creates inconsistency and extra work for LiteLLM users who expect `reasoning_effort: none` to fully disable reasoning without needing to also set `thinking: disabled`. LiteLLM should automatically translate `reasoning_effort: none` into `thinking: {"type": "disabled"}` when calling the DeepSeek v4 API.

## Reproduction Steps

### Test 1: Explicit enable + high reasoning effort ```sh curl https://api.deepseek.com/chat/completions \ -H "Content-Type: application/json" \ -H "Authorization: Bearer ${DEEPSEEK_API_KEY}" \ -d '{ "model": "deepseek-v4-pro", "messages": [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Hello!"} ], "thinking": {"type": "enable"}, "reasoning_eff…

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#0 of 0 · 31d18h58m31s ago — entered · #import:https:::github.com:berriai:litellm post #1875
The right issue is harder because it likely requires tracing dashboard validation, permission and access-state handling, default-team behavior, and frontend/backend regression coverage. The left issue is comparatively localized to provider-specific request translation with focused tests.
The right issue is harder because it requires provider-specific request translation, precedence handling between related parameters, compatibility across model variants, and regression coverage. The left issue appears more localized to an incorrect dashboard entitlement check and should be lower-risk to isolate and correct.
#0 of 0 · 31d18h9m49s ago — current · #import:https:::github.com:berriai:litellm post #2673
The left issue is harder because it involves provider-specific reasoning-output behavior, model-version compatibility, and validation of silent response degradation across Anthropic integrations. The right issue is a narrower request-parameter translation with a more localized implementation and test surface.
discussed in #import:https:::github.com:berriai:litellm

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