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-/https://github.com/berriai/litellm/issues/22997
GitHub · issue

#22997 [Bug]: Latest stable 1.81.14 fails on thinking and tools

  • State: open
  • Author: @xhejtman
  • Labels: bug, proxy, llm translation, claude code

### Check for existing issues

- [x] I have searched the existing issues and checked that my issue is not a duplicate.

### What happened?

When using claude code with thinking models (kimi-k2.5 for instance), it fails.

The same works ok with 1.81.12 version.

### Steps to Reproduce

1. Upgrade to the latest stable 2. Use claude code with thinker model 3. Requests fail.

### Relevant log output

```shell litellm.BadRequestError: Hosted_vllmException - {"object":"error","message":"19 validation errors:\n {'type': 'string_type', 'loc': ('body', 'messages', 2, 'ChatCompletionMessageGenericParam', 'content', 'str'), 'msg': 'Input should be a valid string', 'input': [{'type': 'thinking', 'thinking': \"The user wants to know what's in the mcpserver.py file. Let me read it for them. \"}]}\n {'type': 'literal_error', 'loc': ('body', 'messages', 2, 'ChatCompletionMessageGenericParam', 'content', 'list[union[ChatCompletionMessageContentTextPart,ChatCompletionMessageContentImagePart,ChatCompletionMessageContentVideoPart,ChatCompletionMessageContentAudioPart]]', 0, 'ChatCompletionMessageContentTextPart', 'type'), 'msg': \"Input should be 'text'\", 'input': 'thinking', 'ctx': {'expected': \"'…

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vote history (2 events)
#0 of 0 · 31d18h58m51s ago — entered · #import:https:::github.com:berriai:litellm post #1871
The left issue is harder because it involves a broad regression in multimodal message translation, reasoning content, tool flows, and compatibility across proxy/provider schemas, requiring wider investigation and regression coverage. The right issue is a narrowly scoped Bedrock request normalization with a clearer transformation boundary.
#0 of 0 · 31d18h42m57s ago — current · #import:https:::github.com:berriai:litellm post #2146
The right issue is harder because it spans cross-provider protocol translation, structured payload normalization, backward compatibility, and extensive regression testing, while the left issue is comparatively localized to UI/API data alignment and permission-display logic.
discussed in #import:https:::github.com:berriai:litellm

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