* feat(gemini): add opt-in support for responseJsonSchema
Add support for Gemini's native responseJsonSchema parameter which uses
standard JSON Schema format instead of OpenAPI-style responseSchema.
Benefits of responseJsonSchema (Gemini 2.0+ only):
- Standard JSON Schema format (lowercase types)
- Supports additionalProperties for stricter validation
- Better compatibility with Pydantic's model_json_schema()
- No propertyOrdering required
Usage:
```python
response_format={
"type": "json_schema",
"json_schema": {"schema": {...}},
"use_json_schema": True # opt-in
}
```
This is backwards compatible - existing code continues to use
responseSchema by default.
Closes#16340
* docs: add documentation for use_json_schema parameter
Document the new use_json_schema option for Gemini 2.0+ models
in the JSON Mode documentation.
* refactor(gemini): use responseJsonSchema by default for Gemini 2.0+
Remove opt-in flag `use_json_schema` and automatically detect model version:
- Gemini 2.0+: uses responseJsonSchema (standard JSON Schema, supports additionalProperties)
- Gemini 1.5: uses responseSchema (OpenAPI format, legacy)
This follows LiteLLM's philosophy of abstracting provider differences -
users write the same code regardless of model version.
When extract_and_raise_litellm_exception tries to raise a LiteLLM exception
from an error string, it was always passing the response parameter. However,
some exceptions like APIConnectionError don't accept this parameter, causing
a TypeError.
This fix tries to raise the exception with the response parameter first,
and falls back to raising without it if a TypeError occurs.
This fixes the error:
TypeError: APIConnectionError.__init__() got an unexpected keyword argument 'response'
Which was occurring when Gemini returned UNEXPECTED_TOOL_CALL finish reason
and LiteLLM tried to convert the error to an APIConnectionError.
Fixes: cascading error when Gemini uses thinking feature (__thought__ tool calls)
* Update CLAUDE.md with qwen3 tool_calls bug fix instructions (#18922)
* fix(ollama): set finish_reason to "tool_calls" when tool_calls present
When qwen3 models return tool_calls through Ollama, the finish_reason
was incorrectly left as "stop" instead of being set to "tool_calls".
This caused clients to miss the tool_calls in the response.
Added _get_finish_reason helper method following OpenAI provider's
pattern, and fixed both streaming and non-streaming response paths.
Fixes: https://github.com/BerriAI/litellm/issues/18922
* fix(ollama): pass tools directly without model capability check
The previous code tried to check model capability via get_model_info()
which made network calls to localhost:11434. When Ollama is remote,
this fails and falls back to JSON format, breaking tool calling.
Ollama 0.4+ supports native tool calling - let Ollama handle
model capability detection instead of LiteLLM.
Fixes#18922
* fix(ollama): transform tool_calls response to OpenAI format
Ollama returns tool_calls with arguments as dict, but OpenAI format
requires arguments to be a JSON string. Also ensures 'type': 'function'
field is present.
Completes the fix for #18922
* fix(ollama): set finish_reason to "tool_calls" when tool_calls present
Fixes#18922
Two issues addressed:
1. Remove broken model capability check
- get_model_info() fails when Ollama runs on remote server
- Broken fallback triggered JSON prompt injection
- Now passes tools directly - Ollama 0.4+ handles detection
2. Set finish_reason correctly
- Was hardcoded to "stop" even with tool_calls present
- Clients use this to know how to process the response
- Now returns "tool_calls" when tool_calls are in response
Both streaming and non-streaming responses are fixed.
Tests:
- All 14 existing Ollama tests pass
- Added 3 focused tests for the fixes
Adds 'servers' field to OpenAPI schema when server_root_path is set, ensuring correct Swagger UI execute path for reverse proxies and subpath deployments. Includes tests to verify correct server URL handling for various root path formats.
- Add `should_wrap_with_default_message` parameter to GuardrailRaisedException
- Update Generic Guardrail API to use clean error messages without wrapper
- When should_wrap_with_default_message=False, exception shows the original
blocked_reason directly (e.g., "pii detected") instead of verbose format
- Update test to verify GuardrailRaisedException is raised with clean message
* 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.
