* feat(azure): decouple deployment ID from model name via base_model
Azure OpenAI deployments have arbitrary names (deployment IDs) that may
not match the underlying model. Previously, model-type detection
(o-series, gpt-5, etc.) relied on substring matching against the
deployment name, causing misrouted configs and rejected params when
deployment names were non-standard (e.g. 'my-deployment-id' for gpt-5.2).
This change extends the existing base_model field to drive model-type
detection, config selection, supported param resolution, and param
mapping throughout the Azure call path:
- _get_azure_config() uses base_model for is_o_series/is_gpt_5 checks
- get_provider_chat_config() threads base_model for Azure
- get_supported_openai_params() accepts and uses base_model
- get_optional_params() accepts base_model and passes it to all Azure
config method calls (get_supported_openai_params, map_openai_params)
- azure.py completion handler uses base_model for GPT-5 detection
- Config internal methods (e.g. is_model_gpt_5_2_model) now receive
base_model so features like logprobs are correctly enabled
Fully backward compatible - when base_model is unset, behavior is
identical. Existing o_series/ and gpt5_series/ prefix workarounds
continue to work.
Usage in proxy config:
model_list:
- model_name: my-gpt5
litellm_params:
model: azure/my-deployment-id
model_info:
base_model: azure/gpt-5.2
Fixes: non-standard deployment names like 'prefix-gpt-5.2' rejecting
logprobs/top_logprobs despite the underlying model supporting them.
* Addressing Greptile comments.
1c80fa9c3b