* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* ci: rename fork-flag to unit-flag now that it applies on every event
* test: move tests/test_litellm root and small trees into tests/unit
Pure renames, no content changes. Follow-up commits in this PR fix
references, merge the three files that already existed in tests/unit,
keep live-provider tests in tests/test_litellm and wire CI.
* test: carry tests/test_litellm conftest isolation into tests/unit
Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS,
proxy-URL and keychain env, and session-end client cleanup now reset for
unit tests too. The environment isolation owns its MonkeyPatch so a test's
own monkeypatch is undone before the model-cost teardown runs.
* test: merge, split and prune the moved root and small-tree tests
Merge batches/test_batch_utils.py and the chat_completions and messages
dispatch tests into the files that already existed in tests/unit. Keep
the live Gemini interactions tests, the async image-fetch format test and
the OpenAI embedding scorer test in tests/test_litellm since they need
real network or keys. Put test_router.py under tests/unit/test_router so
the existing package no longer shadows it. Delete eight tests the audit
found superseded by stronger ones kept in this move.
* ci: run the moved root and small-tree tests under their legacy flags
Add the misc and responses-caching-types flags to unit_selection.sh and
CircleCI, extend enterprise-routing and mcp-integration, and point the
legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest
and change classifier at the new paths.
* test: make the new tests/unit directories packages
tests/unit/test_package_layout.py requires every directory to carry an
__init__.py, and without one the moved and retained
test_litellm_responses_bridge.py modules collide on import.
* test: scope the unit socket block to tests/unit in shared sessions
The GHA shards collect the legacy test-path and the unit selection in one
pytest session. The unit conftest's loopback-only block leaked into legacy
modules that reach the network at import. The legacy conftest now lifts the
restriction at collect and setup time, and the unit conftest re-applies it
when collecting its own modules.
* test: give the shard-script tests their own GITHUB_OUTPUT
They only passed where the runner set it. The CircleCI unit job's env
allowlist drops it, so the script's redirect failed there.
* test: point the router and module-deletion checks at tests/unit
router_code_coverage and code_qa_check_tests only searched tests/test_litellm,
so the moved router tests no longer counted. The two silent-experiment tests
the audit deleted were the only direct callers of those methods; they are
replaced with tests that assert the forwarded shadow request and the
recursion guard.
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The openai/azure/compat image-edit funnel merged non_default_params and
extra_body straight into the multipart body, so a nested value (e.g.
extra_body={"metadata": {...}}) reached the httpx encoder and 500'd with
"Invalid type for value. Expected primitive type". Route the funnel through
a shared flattener that serializes nested values as OpenAI-SDK bracket fields
(key[subkey], lists as key[], bools lowercased, None/empty dropped), matching
the wire format of the rest of this fix.
POST /v1/videos without an input_reference file now goes out as
multipart/form-data the way the OpenAI SDK always sends it, instead of a
JSON body that OpenAI-compatible backends (SGLang Diffusion, vLLM-Omni)
reject; gemini, vertex, and runwayml keep their JSON bodies
/v1/images/edits on the openai/azure/openai-compatible path now forwards
unknown provider params (e.g. seed) and honors extra_body, matching
/v1/images/generations, and aimage_edit forwards
extra_headers/extra_query/extra_body instead of dropping them
Generic pass-through no longer downgrades a file-less multipart form to
application/x-www-form-urlencoded
* test: drop the cwd-relative sys.path.insert calls from the test suite
TQ003 stands at 1,077 across 1,058 files, and 1,015 of them are the same shape:
sys.path.insert(0, os.path.abspath("../..")) and its deeper siblings. The
argument resolves against the working directory rather than the file, so from
the repo root, where every job runs pytest, it inserts the directory two levels
above the checkout. It has never pointed at litellm. The package is installed
into the environment anyway, which is what actually makes the import work, and
what the rule's message has said all along.
Removing them leaves 1,634 imports of sys and os with no remaining reference,
and those go too, except where another test module imports the name back out of
the file. The rest of TQ003 is 62 call sites that resolve against __file__ or a
variable, which are a different question and are left alone.
Collection is identical either way: 45,871 tests and the same 51 pre-existing
collection errors before and after, and ruff reports no new undefined name.
* test: drop the duplicate imports the sys.path sweep exposed to F811
* test(pre-call-utils): restore the os import the new bedrock tests need
VertexAIImagenImageEditConfig.get_complete_url was resolving vertex_project
and vertex_location only from env vars and global settings, ignoring
litellm_params. Users supplying project/location exclusively via YAML
config would get a ValueError or wrong URL even after auth headers were fixed.
Mirrors the pattern already used by VertexAIGeminiImageEditConfig and
image_generation counterpart (safe_get_vertex_ai_project/location).
Also fixes api_key type hint in MockImageEditConfig (str -> Optional[str])
and adds a test covering get_complete_url credential resolution.
Made-with: Cursor
Adds three test cases to prevent regression of the Vertex AI image_edit
credentials bug:
1. test_validate_environment_signature_includes_litellm_params: ensures
all image-edit configs accept litellm_params (contract for the handler)
2. test_vertex_gemini_image_edit_reads_credentials_from_litellm_params:
verifies Gemini config reads from litellm_params first
3. test_vertex_imagen_image_edit_reads_credentials_from_litellm_params:
verifies Imagen config reads from litellm_params first
These tests catch if the fix is accidentally reverted or if new image-edit
configs are added without the litellm_params parameter.
Made-with: Cursor
When aimage_edit or image_edit was called with Vertex AI Gemini/Imagen models
via YAML-style config (vertex_project / vertex_credentials in proxy YAML),
the credentials were dropped during handler-to-config plumbing, causing
fallback to Application Default Credentials and DefaultCredentialsError.
Root cause: image_edit_handler and async_image_edit_handler did not pass
litellm_params to validate_environment, unlike image_generation_handler.
Fixes:
1. Widen BaseImageEditConfig.validate_environment signature to accept
litellm_params and api_base (optional kwargs).
2. Forward dict(litellm_params) and litellm_params.api_base from both
sync and async image_edit handlers to validate_environment.
3. Update VertexAIImagenImageEditConfig.validate_environment to read
vertex_ai_project/vertex_ai_credentials from litellm_params first,
matching Gemini config pattern (secondary latent bug fix).
4. Widen all image-edit config override signatures to match base.
Made-with: Cursor
* fix: Fixes https://github.com/BerriAI/litellm/issues/23185
* fix(responses/main.py): ensure litellm metadata custom cost works
* refactor: move all logging updates to a common function, to have just 1 place to update logging kwarg updates
image_edit was not forwarding model_info/metadata to the logging object,
so custom_pricing was never detected. After PR #20679 stripped custom
pricing fields from the shared backend key, image_edit cost became 0.
Fixes#22244
Fixes#22285 — extra_headers passed to litellm.image_generation() were
silently dropped on the openai/litellm_proxy/openai_compatible_providers
code path. The azure and azure_ai paths already forwarded them correctly.
