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fix(health.md): add rerank model health check information (#7295)
* fix(health.md): add rerank model health check information * build(model_prices_and_context_window.json): add gemini 2.0 for google ai studio - pricing + commercial rate limits * build(model_prices_and_context_window.json): add gemini-2.0 supports audio output = true * docs(team_model_add.md): clarify allowing teams to add models is an enterprise feature * fix(o1_transformation.py): add support for 'n', 'response_format' and 'stop' params for o1 and 'stream_options' param for o1-mini * build(model_prices_and_context_window.json): add 'supports_system_message' to supporting openai models needed as o1-preview, and o1-mini models don't support 'system message * fix(o1_transformation.py): translate system message based on if o1 model supports it * fix(o1_transformation.py): return 'stream' param support if o1-mini/o1-preview o1 currently doesn't support streaming, but the other model versions do Fixes https://github.com/BerriAI/litellm/issues/7292 * fix(o1_transformation.py): return tool calling/response_format in supported params if model map says so Fixes https://github.com/BerriAI/litellm/issues/7292 * fix: fix linting errors * fix: update '_transform_messages' * fix(o1_transformation.py): fix provider passed for supported param checks * test(base_llm_unit_tests.py): skip test if api takes >5s to respond * fix(utils.py): return false in 'supports_factory' if can't find value * fix(o1_transformation.py): always return stream + stream_options as supported params + handle stream options being passed in for azure o1 * feat(openai.py): support stream faking natively in openai handler Allows o1 calls to be faked for just the "o1" model, allows native streaming for o1-mini, o1-preview Fixes https://github.com/BerriAI/litellm/issues/7292 * fix(openai.py): use inference param instead of original optional param
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@ -130,11 +130,6 @@ class ReplicateConfig(BaseConfig):
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return split_model[1]
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return model
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def _transform_messages(
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self, messages: List[AllMessageValues]
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) -> List[AllMessageValues]:
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return messages
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def get_error_class(
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self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
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) -> BaseLLMException:
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