mirror of
https://github.com/BerriAI/litellm.git
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* fix(azure_ai): count Grok reasoning tokens in completion_tokens Grok on Azure AI Foundry reports reasoning_tokens outside completion_tokens, like xAI does, so azure_ai/grok-* calls billed only max(visible, reasoning) output tokens. Fold them with XAIChatConfig.fold_reasoning_tokens_into_completion in transform_response and in a new streaming iterator, matching the xai provider. Split out of #46377. * fix(azure_ai): fold reasoning tokens for every deployment name, streaming or not Non-streaming checked the deployment name for grok while streaming checked the chunk model field, so a Grok deployment named without grok was only folded when streaming. The fold already only fires when total_tokens equals prompt plus completion plus reasoning, so it now runs on every azure_ai response. |
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| .. | ||
| _support | ||
| base_sdk_tests | ||
| benchmarks | ||
| code_coverage_tests | ||
| documentation_tests | ||
| e2e | ||
| e2e_harness | ||
| fixtures | ||
| harness_e2e | ||
| integration | ||
| rust-python-harness | ||
| test_litellm_rust | ||
| typing | ||
| unit | ||
| windows_tests | ||
| __init__.py | ||
| _fake_openai_endpoint_server.py | ||
| _flush_vcr_cache.py | ||
| _live_test_helpers.py | ||
| _master_key.py | ||
| _openai_record_replay_proxy.py | ||
| _process_helpers.py | ||
| _vcr_conftest_common.py | ||
| _vcr_redis_persister.py | ||
| _wait_helpers.py | ||
| _ws_vcr.py | ||
| AGENTS.md | ||
| capturing_transport.py | ||
| eval_swe_bench.py | ||
| fake_openai_endpoint.py | ||
| gettysburg.wav | ||
| large_text.py | ||
| openai_batch_completions.jsonl | ||
| pyrightconfig.json | ||
| README.MD | ||
| test_logging.conf | ||
| test_rust_python_harness.py | ||
| VCR_TESTING.md | ||
| white_100x100.png | ||
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/unit
This folder can only run mock tests.