The azure row of test_get_model_info_falls_back_from_dated_snapshot_to_undated_entry used gpt-5.6-luna-2026-07-09, which main's cost map carries as an exact azure key, so the lookup returned the dated key and the required misc test job failed on main. All three dated snapshot tests now use a 2099-01-01 snapshot date, so they keep exercising the strip path whatever real snapshots the map gains
DeepSeek charges half the listed rate outside 01:00-04:00 and 06:00-10:00 UTC
Monday to Friday, so every deepseek-flash, deepseek-v4-flash,
deepseek-v4-flash-vision-exp, and deepseek-v4-pro entry now carries an
off_peak_pricing block with those windows and the halved input, output, and
cache-hit rates. The generated cost map schema picks up the block, and the
regression tests pin the peak and off-peak cost of one call at fixed moments.
Fifty six of the deleted tests turn out to assert the output of litellm code rather than the catalog lookup itself, things like map_openai_params, get_supported_openai_params, should_fake_stream, transform_request bodies, cost_per_token arithmetic, get_llm_provider routing, and provider config dispatch. They only happen to read shipped entries as inputs, so they belong in the later rewrite that injects a local model_cost, not in this deletion
Each one is restored verbatim from origin/main along with the fixtures, helpers, constants and imports it needs, and tests/test_litellm/test_sambanova_model_metadata.py is restored wholesale
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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>
The Responses id security hook keeps the id a client addressed under
`_litellm_addressed_response_id` in the request body so internal retries can
re-authorize it. On a model without a native Responses config that body is
bridged into `completion()` kwargs, the key was treated as a provider param,
and providers rejected it, so every follow-up turn carrying
`previous_response_id` returned 400.
Register the key in `all_litellm_params` so it is dropped before any provider
request, and share one constant between the hook and the param list.
The deepgram/streaming/* rows added for the Deepgram WebSocket passthrough declare /v1/listen as their endpoint, so the registry validation test needs it in the enum, the same way /vertex_ai/live was added for that passthrough
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Keeps the original CustomStreamWrapper so response headers and the
correlation-context cleanup in __del__ are untouched when a deployment
hook rewrites the converted response. Covers the early-return branches
for real provider streams and unmapped call types
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
A pre-call deployment hook can turn a requested stream into a non-streaming provider call and the result is wrapped back into a fake stream. The async client wrapper treated that wrapper like a caller-requested stream and returned before async_post_call_success_deployment_hook, so SDK callers lost post-call deployment processing (including CustomGuardrail post_call enforcement) on converted streams. Run the hook on the complete ModelResponse behind the wrapper and rewrap a modified response so it reaches the emitted chunks.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
A deployment hook (Headroom, code interpreter, web search) can downgrade
kwargs["stream"] to False while the caller still expects to iterate the
result. The cache handler keyed stream replay and callback deferral off
the raw flag, so a cache hit returned a plain object to a caller that
iterates, and the Responses iterator never persisted the converted
stream in the first place. Key both off the conversion marker as well
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Deployment hooks such as Headroom downgrade stream=True to a non-streaming provider call and the agentic loop then hands back a CustomStreamWrapper (or MockResponsesAPIStreamingIterator for Responses). wrapper_async still saw kwargs["stream"] is False, so it took the non-streaming success path with a lazy stream object: no standard_logging_object was built, the proxy cost callback raised failed_tracking_spend, and the wrapper's own end-of-stream dispatch was deduped away. Treat a lazy stream result as streaming for logging regardless of the downgraded kwarg. Regression in v1.99.0 via #35017
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
num_retries_per_request has always capped the retries of one request with its fallback hops included. #40930 started reading the per-hop attempted_retries counter instead, and every fallback hop restarts that counter at zero, so a request could spend a fresh retry budget on each hop and the legacy fallback cap test started seeing the hop run.
Router.log_retry now also keeps request_retry_count on the request metadata, incremented on every retry and fallback hop and never truncated the way previous_models is, and max_retries_per_request_hit reads that count. The flat retry records, the litellm_metadata coverage and caps above four from #40930 stay as they are, and the legacy test goes back to its previous_models == 0 assertion.
get_litellm_params() keys such as model_alias_map, completion_call_id and
custom_prompt_dict were missing from all_litellm_params, so when a bridge
forwarded litellm_params as completion kwargs they were swept into extra_body
and OpenAI rejected the call with "Unknown parameter: 'model_alias_map'".
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
_client_async_logging_helper re-submitted logging_obj.success_handler to the
executor after _dispatch_success_logging had already done so, running the same
success pipeline twice per async request and racing on shared logging state.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
