* fix(callbacks): allow MAX_CALLBACKS override via env var (#20778)
* fix(callbacks): allow MAX_CALLBACKS override via env var
- Move MAX_CALLBACKS from logging_callback_manager.py to constants.py
- Add LITELLM_MAX_CALLBACKS env var override (default: 30)
- Add troubleshooting doc explaining the limit and override
Fixes issue where large deployments with 60+ teams using guardrails
would hit the hardcoded MAX_CALLBACKS=30 limit and fail to start.
* docs: add max_callbacks to sidebar navigation
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Co-authored-by: shin-bot-litellm <shin-bot-litellm@users.noreply.github.com>
* fix callbacks issue
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Co-authored-by: shin-bot-litellm <shin-bot-litellm@berri.ai>
Co-authored-by: shin-bot-litellm <shin-bot-litellm@users.noreply.github.com>
* docs: add callback registration optimization to v1.81.9 release notes (#20681)
* docs: add callback registration optimization to v1.81.9 release notes
* Update v1.81.9.md
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Co-authored-by: Alexsander Hamir <alexsanderhamirgomesbaptista@gmail.com>
* Fix spend logs pickle error with Pydantic models
Replace copy.deepcopy() with Pydantic-safe serialization to avoid
"cannot pickle '_thread.RLock' object" errors when request/response
redaction is enabled.
Changes:
- Add _convert_to_json_serializable_dict() helper that uses
model_dump() for Pydantic models instead of pickle
- Replace copy.deepcopy() calls in request and response redaction
paths with the new helper function
- Recursively handles nested dicts, lists, and Pydantic models
Root cause: Pydantic v2 BaseModel instances contain internal
_thread.RLock objects for thread-safety. When copy.deepcopy()
attempts to pickle these objects, it fails because threading
primitives cannot be pickled.
Fixes#20647
* chore: remove unused copy import
Remove unused copy import that was causing lint failure. The copy.deepcopy()
calls were replaced with _convert_to_json_serializable_dict() helper function
in the previous commit, making the copy module no longer needed.
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Co-authored-by: ryan-crabbe <128659760+ryan-crabbe@users.noreply.github.com>
Co-authored-by: Alexsander Hamir <alexsanderhamirgomesbaptista@gmail.com>
* feat: add support for anthropic_messages call type in prompt caching
* test: move anthropic_messages prompt caching test to main router test file
* add tutorial on using claude code with prompt cache routing
* support policy mapping on team key level
* update document
* update document
* address comments
* update document
* add unit test for new feature
* add more test case
- Add paragraph on release validation, extensibility, and 100% coverage goal
- Include OOMs and CPU regressions as issues surfaced under sustained load
* fix: fix styling
* fix(custom_code_guardrail.py): add http support for custom code guardrails
allows users to call external guardrails on litellm with minimal code changes (no custom handlers)
Test guardrail integrations more easily
* feat(a2a/): add guardrails for agent interactions
allows the same guardrails for llm's to be applied to agents as well
* fix(a2a/): support passing guardrails to a2a from the UI
* style(code-editor): allow editing custom code guardrails on ui + add examples of pre/post calls for custom code guardrails
* feat(mcp/): support custom code guardrails for mcp calls
allows custom code guardrails to work on mcp input
* feat(chatui.tsx): support guardrails on mcp tool calls on playground
* [Feat] add ElevenLabs `eleven_v3` and `eleven_multilingual_v2` to model cost map
Register ElevenLabs TTS models for cost tracking:
- elevenlabs/eleven_v3: most expressive model, 70+ languages, audio tags
- elevenlabs/eleven_multilingual_v2: default TTS model, 29 languages
Also update ElevenLabs docs with supported models table and eleven_v3 audio tags example.
* docs: remove model-agnostic tip from ElevenLabs docs
* docs(web_search): clarify OpenAI search model requirements
- Add gpt-5-search-api to supported OpenAI search models
- Add warning that regular models (gpt-5, gpt-4.1) do NOT support web_search_options
- Add tip that web_search_options is optional for search models
* feat(models): add gpt-5-search-api pricing for OpenAI and Azure
Ishaan Jaff