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-/https://github.com/berriai/litellm/issues/32613
GitHub · issue

#32613 [Feature]: Add support fort Kimi-K2.7-Code in Azure

  • State: open
  • Author: @emerzon
  • Labels: enhancement

### Check for existing issues

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

### The Feature

Add support for Kimi K2.7 Code in Azure: https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-kimi-k2-7-code-in-microsoft-foundry/4532286

### Motivation, pitch

Support for new model

### What part of LiteLLM is this about?

Proxy

### LiteLLM is hiring a founding backend engineer, are you interested in joining us and shipping to all our users?

No

### Twitter / LinkedIn details

_No response_

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vote history (3 events)
#0 of 0 · 31d19h7m5s ago — entered · #import:https:::github.com:berriai:litellm post #1776
-/https://github.com/berriai/litellm/issues/289024:3-/https://github.com/berriai/litellm/issues/32613⭐
The right issue is harder because it requires coordinated frontend and backend changes around secret redaction, update semantics, persistence safety, and regression coverage. The left issue is comparatively contained to Azure model integration, configuration, and compatibility tests.
#0 of 0 · 31d19h6m5s ago · #import:https:::github.com:berriai:litellm post #1778
-/https://github.com/berriai/litellm/issues/344514:1-/https://github.com/berriai/litellm/issues/32613⭐
Security work carries substantially higher engineering risk due to exploit validation, remediation across authentication and request-routing boundaries, regression testing, and coordinated disclosure. The model-integration request is narrower, largely involving provider configuration, capability mapping, and targeted tests.
#0 of 0 · 31d18h30m48s ago — current · #import:https:::github.com:berriai:litellm post #2373
-/https://github.com/berriai/litellm/issues/307303:1-/https://github.com/berriai/litellm/issues/32613⭐
The guardrail defect is harder because it requires safely reconciling verdict and redaction semantics, defining fail-open versus fail-closed behavior, and adding regression coverage for malformed or incomplete detector output. The Azure model addition is comparatively scoped to provider integration, capability metadata, and compatibility tests.
discussed in #import:https:::github.com:berriai:litellm

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