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Mateo Wang
fec4ae69e0
Encode the 231-cell QA sweep (21 provider x model combos x 11 effort values) from #27039 / #27074 as an automated CircleCI-gated regression suite. Each cell hits the real provider endpoint, captures the outgoing wire body via a pre-call CustomLogger, and asserts: - thinking.type, output_config.effort, thinking.budget_tokens, max_tokens in the captured request body (regression signal for silent drops/strips in any provider transformation) - HTTP status (200 vs BadRequestError -> 400) returned by litellm (regression signal for clean-error vs leaked-500 mappings) The matrix is encoded as a small rule set keyed by (model_mode, effort) plus per-model xhigh/max capability overrides, then expanded across the five chat-completion routes (Anthropic direct, Azure AI Foundry, Vertex AI, Bedrock Converse, Bedrock Invoke /chat) and the Bedrock Invoke /v1/messages route. Cells skip at runtime when the route's provider env vars are absent, so PR builds without credentials no-op gracefully. Wired into CircleCI as the reasoning_effort_grid_v4_e2e job behind the existing main / litellm_* branch filter.
In total litellm runs 1000+ tests
[02/20/2025] Update:
To make it easier to contribute and map what behavior is tested,
we've started mapping the litellm directory in tests/test_litellm
This folder can only run mock tests.