* fix(text_completion): support token IDs (list of integers) as prompt
Add support for passing token IDs (list of integers) to the text_completion
endpoint for OpenAI-compatible providers (openai, azure, vllm, etc.).
Fixes#17118
* test(text_completion): replace live test with mock test for token IDs
Move token IDs test from local_testing to test_litellm with mocks
per PR review feedback.
* feat(bedrock): add OpenAI-compatible service_tier parameter translation
Translates OpenAI's service_tier parameter (string) to Bedrock's
serviceTier format (object with type field).
* docs(bedrock): add OpenAI-compatible service_tier parameter documentation
Document the automatic translation from OpenAI-style service_tier
parameter to Bedrock's native serviceTier format.
* feat(bedrock): add service_tier to response when present
According to OpenAI's API documentation, when service_tier is sent in the
request, it should be returned in the response. This commit implements
this behavior for Bedrock Converse API to maintain compatibility with
OpenAI's API.
Changes:
- Added serviceTier field to ConverseResponseBlock type definition
- Moved ServiceTierBlock definition before ConverseResponseBlock to fix
type reference order
- Added response transformation to map Bedrock serviceTier (object) to
OpenAI service_tier (string format)
- Added 4 new tests for response transformation with service_tier
The service_tier is only added to the response when present in Bedrock's
response, maintaining backward compatibility.
Fixes#18137
Similar to the fix for web_search_tool_result (#17746, #17798), this PR
preserves web_fetch_tool_result blocks in multi-turn conversations.
Changes:
- Add handling for web_fetch_tool_result in transformation.py (non-streaming)
- Add capture of web_fetch_tool_result in handler.py (streaming)
- Fix streaming tool arguments bug where empty input {} was prepended to
actual arguments by using empty string instead of str({})
- Add unit tests for web_fetch_tool_result handling
* fix(generic-guardrail-api): fix SerializationIterator error on multimodal requests
When sending multimodal messages (with images) through the Generic Guardrail API,
the `model_dump()` call fails with "Object of type SerializationIterator is not
JSON serializable" error.
Root cause: The `ChatCompletionAssistantMessage` type defines `content` as an
`Iterable` (not just `List`), and Pydantic's `model_dump()` creates a
`SerializationIterator` for iterables which is not JSON serializable.
Fix: Use `model_dump(mode="json")` which properly converts all iterables to
lists and ensures all complex objects are JSON serializable.
* fix(guardrails): pass tools (function definitions) to guardrail inputs
The unified guardrail handler was not passing the `tools` parameter
(function definitions) from the request to the guardrail inputs.
This meant guardrails could not inspect or validate tool definitions.
Added extraction of `data.get("tools")` and inclusion in the
GenericGuardrailAPIInputs passed to `apply_guardrail()`.
* test(guardrails): add tests for tools passed to guardrail
Added tests verifying that tools (function definitions) are correctly
passed to guardrails in the unified guardrail handler:
- test_tools_passed_to_guardrail
- test_multiple_tools_passed_to_guardrail
- test_no_tools_in_request
- test_tools_and_tool_calls_both_passed
* fix(azure): add logprobs support for Azure OpenAI GPT-5 models
Azure OpenAI GPT-5 models (including gpt-5.2) support logprobs
parameters, unlike OpenAI's GPT-5 reasoning models. This fix
overrides the parent class restriction to enable logprobs for Azure.
Changes:
- Override get_supported_openai_params() in AzureOpenAIGPT5Config
- Add "logprobs" and "top_logprobs" to supported params
- Add comprehensive tests for logprobs functionality
Testing:
- Verified with direct Azure API calls to gpt-5.2
- API version: 2025-01-01-preview
- Successfully returns logprobs data
Related: #7974, #4022
* refactor: restrict logprobs support to gpt-5.2 only
Only gpt-5.2 has been verified to support logprobs on Azure.
Other gpt-5 variants (gpt-5, gpt-5.1) have not been tested.
Changes:
- Add conditional check for is_model_gpt_5_2_model()
- Update tests to be specific to gpt-5.2
- Add negative tests for gpt-5 and gpt-5.1
- Update documentation to reflect gpt-5.2 specificity
Added XIAOMI_MIMO to the LlmProviders enum in types/utils.py.
The provider was already configured in providers.json but was
missing from the enum, causing "Unsupported provider" errors
when using it in Router/Proxy configurations.
Also added comprehensive unit tests to prevent regression.
2026-01-08 23:45:57 +05:30
Ishaan JaffGitHubCopilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
