* test: move the unit half of 126 mixed legacy files into tests/unit
* test: restore litellm globals that moved tests set
* test: finalize migration test cleanup
* test: restore original bodies of moved legacy tests
The move into tests/unit had rewritten 612 test bodies, and some of the rewrites dropped assertions. Each moved test now carries its original body from the legacy file, with only the imports, helpers, fake provider credentials and monkeypatched env it needs to run under tests/unit
test_timeout_streaming goes back to tests/local_testing because it needs the fake OpenAI endpoint server. The image payload fixture moves with its only user, and two tests that leaked global state (a registered model cost entry and queued logging tasks) are now isolated
* test: drop module imports shadowed by restored local imports
* test: assert on LiteLLM output in no-assertion moved tests and isolate leaks
Twenty no-assertion candidates get one assertion on the value LiteLLM returns, with the original lines unchanged. Four tests go back to their legacy files because they only check types or imports, write into the working directory, or cannot assert without a body change
Two moved tests leaked globals into later tests in the same worker, so monkeypatch fixtures now restore the retry-after header parser and the end user cost tracking flags
* test: drain queued logging tasks before the Phoenix span test
The moved Phoenix test counted spans from logging tasks that earlier tests had queued, so the drain fixture moves to tests/unit/conftest.py and both it and the Datadog batch test use it. test_factory_function goes back to its legacy file because its returned wrapper calls the real Assistants API and cannot be asserted on without a body change
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Co-authored-by: yuneng <yuneng@berri.ai>
Regenerated every touched file from origin/main applying only the B1 test deletions and the unused import and helper cleanup they leave behind, without running the formatter across untouched code. CI only checks ruff format under litellm/, so the earlier reflows of test files were pure diff noise for reviewers
Also drops the tests/local_testing/test_prompt_caching.py entry from the caching-local shard in test-unit.yml since that file is deleted
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The repo rule is that a test must only fail when litellm code changes, never when a vendor updates a price, renames a field, or drops a model. These tests asserted shipped catalog entries directly, comparing lookup results to literals copied from model_prices_and_context_window.json or requiring named entries to exist or be absent, so every cost map sync could break them without any litellm code changing
Tests that exercise real litellm behavior with an injected local model_cost, invariants like backup parity, and assertions on non-lookup code paths are untouched
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* 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.
