About 35,000 fixes ruff marks safe across 32 rules (UP006/UP045/UP007
modern annotations, UP032 f-strings, SIM114/SIM118, RET501, and
friends), removal of the 1,296 typing imports the rewrite orphaned, and
hand fixes for what the fixers could not see: five star-import
freeloaders of typing names, two F823 late-import annotations, the
/get/config/list introspection crash on types.UnionType, redundant
function-local RoleMappings imports in ui_sso.py that shadowed the
module-level name once the annotation lost its quotes, and one FURB168
tautology.
B009/B010/PIE804/RUF019 are excluded on purpose: their safe fixes
rewrite getattr/setattr/**-splat/key-in-dict escape hatches into forms
basedpyright then rejects (283 new errors measured), so their budgets
stay at base values.
ruff-strict-budget.json drops by 39,579 this commit (39,968 across the
branch) with 28 rules at an actual 0 and 9 more sharply down.
type-discipline-budget.json ratchets LIT002/LIT006/LIT009 down; LIT001
moves to the now-honest total: the checker matches the spelling `set`
but not the alias `Set`, so the 160 typing.Set annotations rewritten to
set[...] were always mutable-set annotations and only now count.
The repo linted at 120 (E501, isort) but ran ruff format at 88 via a
--line-length 88 override in the Makefile and CI, leaving the formatter
and the linter disagreeing on wrap width. Drop the override so ruff.toml's
line-length = 120 is the single source of truth and reformat the tree to
match.
* fix(main.py): fix async retryer
Fixes https://github.com/BerriAI/litellm/issues/12830
* fix(forward_clientside_headers_by_model_group.py): filter out 'content-type' from forwardable headers
clientside content-type != proxy content type, can cause requests to hang
* test(tests/): update tests
* feat: add Lambda AI provider support
Add support for Lambda AI (lambda.ai) as a new LLM provider in LiteLLM. Lambda AI provides access to a wide range of open-source models through their cloud GPU infrastructure.
Changes:
- Add Lambda AI provider implementation (OpenAI-compatible)
- Register 20 Lambda AI models with accurate pricing and 131k context windows
- Add comprehensive tests for Lambda AI integration
- Add detailed documentation with usage examples
- Use "lambda_ai" as provider name to avoid Python keyword conflict
Models include Llama 3.x, DeepSeek, Hermes, Qwen, and specialized models for coding and vision tasks.
* fix(tests): ensure lambda_ai_models list is repopulated after model cost reload
Updated test cases to clear and repopulate the lambda_ai_models list after reloading the model cost map. This ensures that the tests accurately reflect the current state of available models.
* feat: add Lambda AI chat configuration support
Added support for Lambda AI chat configuration in the ProviderConfigManager. This enhancement allows the integration of Lambda AI as a provider, expanding the capabilities of LiteLLM.
