[feat] Add CentML as llm provider #11472
Closed
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Title
Add CentML provider support with granular function calling and JSON schema controls
Relevant issues
Pre-Submission checklist
Please complete all items before asking a LiteLLM maintainer to review your PR
tests/litellm/
directory, Adding at least 1 test is a hard requirement - see detailsmake test-unit
Local test screenshot
Type
🆕 New Feature
Changes
Core Provider Integration
CENTML = "centml"
toLlmProviders
enumCENTML_API_KEY
,CENTML_API_BASE
)Model Support & Capabilities Matrix
Granular Parameter Control
supports_function_calling
: Controlstools
,tool_choice
,function_call
parameterssupports_response_schema
: Controlsresponse_format
parameter independentlyCentmlConfig
class with intelligent parameter validation based on model capabilitiesHandler Implementation
CentmlChatCompletion
andCentmlTextCompletion
classes extending OpenAI handlersCentmlConfig
andCentmlTextCompletionConfig
Comprehensive Testing
tests/test_litellm/llms/centml/
:tests/local_testing/test_centml_integration.py
:Technical Implementation Details
centml/
prefix construction{"type": "text"}
default)This implementation enables developers to use CentML's inference platform through LiteLLM with full parameter validation, ensuring that unsupported features are properly blocked while supported features work seamlessly with the existing LiteLLM ecosystem.