Commit Graph
109 Commits
Author SHA1 Message Date
yuneng-jiangandGitHub 16bd81985d Merge pull request #27795 from BerriAI/litellm_vcr-cache-observability-and-fixes-c5bc
test(vcr): classify cache verdicts, surface cost leaks, and fix the two biggest leakers
2026-05-14 13:51:16 -07:00
b593b88ec6 Ishaan - May 13th Staging LiteLLM (#27877)
* fix: strip Gemini thought-signature from tool_use.id in non-streaming path; example websearch config (#27873)

- adapters/transformation.py: mirror the streaming path and strip the
  `__thought__<b64>` suffix off `tool_call.id` before building the
  AnthropicResponseContentBlockToolUse. Base64's `+ / =` characters
  violate Anthropic's `^[a-zA-Z0-9_-]+$` tool_use.id pattern, so when a
  conversation that flowed through Gemini is later replayed to an
  Anthropic-native provider (Bedrock or Anthropic API) the request 400s.
- example_config_yaml/websearch_interception_config.yaml: register the
  interceptor under `callbacks:` not `success_callback:`. `success_callback`
  does not run pre-request hooks, so the tool-conversion step never fires
  on `/v1/messages` and the raw `web_search_20250305` tool is forwarded
  to Bedrock, which 400s.
- adds a unit test pinning the non-streaming strip behavior and the
  surviving `^[a-zA-Z0-9_-]+$` shape of the resulting id.

Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com>

* Fix/azure image edit auth header (#27863)

* fix(azure/image_edit): use api-key header instead of Authorization Bearer

Delegate `AzureImageEditConfig.validate_environment` to
`BaseAzureLLM._base_validate_azure_environment` so the image-edit route
follows the same auth resolution as every other Azure provider:

- prefer the Azure-native `api-key` header when an API key is available
- fall back to `Authorization: Bearer <azure_ad_token>` only for AAD auth

The previous implementation unconditionally set
`Authorization: Bearer <api_key>`, which is the OpenAI-direct convention
and is rejected by Azure OpenAI / APIM-fronted deployments with
`401 Access denied due to missing subscription key`.

Adds regression tests covering api_key kwarg, litellm_params.api_key, and
the AAD-token fallback path.

Co-authored-by: Cursor <cursoragent@cursor.com>

* docs(azure/image_edit): pin api-key precedence semantics + add regression test

Address review feedback that the move to
``BaseAzureLLM._base_validate_azure_environment`` changed the relative
priority of the positional ``api_key`` kwarg vs. ``litellm_params["api_key"]``.

The new behavior — ``litellm_params["api_key"]`` wins, positional only fills
in when ``litellm_params["api_key"]`` is empty — is intentional and matches
every other Azure ``validate_environment``: ``AzureVideosConfig`` uses the
exact same merge logic, while ``AzureVectorStoresConfig`` and
``AzureResponsesAPIConfig`` don't accept a positional ``api_key`` at all.
The old ``or`` chain (positional wins) was the outlier and was part of the
same OpenAI-vs-Azure convention drift that produced the original
``Authorization: Bearer`` bug.

The only production caller (``llm_http_handler.image_edit``) sources both
values from the same ``litellm_params.api_key``, so this change is
behaviorally a no-op there. Document the precedence in the docstring and
lock it in with an explicit test so future refactors can't quietly
re-invert it.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: Adam Kirstein <adam.kirstein@disney.com>
Co-authored-by: Cursor <cursoragent@cursor.com>

* test(azure/image_edit): expect api-key header instead of Authorization Bearer

PR #27863 fixed Azure image edit to use the Azure-native api-key header
instead of OpenAI's Authorization: Bearer convention, but did not update
test_azure_image_edit_litellm_sdk to match. The test still asserted
'Authorization' in headers, which now fails since the new code routes
through BaseAzureLLM._base_validate_azure_environment and emits
api-key when an api_key is provided.

Update the assertion to pin the correct Azure behavior: api-key header
present with the resolved key, and no Authorization header.

---------

Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com>
Co-authored-by: Adam Kirstein <107421694+justalittleadam@users.noreply.github.com>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: Adam Kirstein <adam.kirstein@disney.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
2026-05-13 16:37:15 -07:00
Cursor AgentandMateo Wang b13ae8de50 fix(image_edits): drop _RewindableImage to prevent infinite multipart upload
The _RewindableImage(BytesIO) wrapper auto-rewound on every read after
EOF, which made the OpenAI SDK's multipart upload writer read the same
bytes forever instead of seeing EOF. Workers OOM'd / SIGKILL'd:

    [gw0] node down: Not properly terminated
    replacing crashed worker gw0
    ...
    worker 'gw1' crashed while running
        'tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditGPTImage1::test_openai_image_edit_litellm_sdk[False]'

The auto-rewind was added defensively for parametrized + flaky-retried
tests, but BaseLLMImageEditTest::test_openai_image_edit_litellm_sdk
already calls get_base_image_edit_call_args() once per invocation and
that helper now constructs fresh streams via _make_test_images(), so
rewinding inside the stream is unnecessary. Replace with plain BytesIO
seeded with the cached image bytes.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-13 01:04:31 +00:00
Cursor AgentandMateo Wang 656377bb3d test(image_edits): regenerate fixtures per call instead of holding open module-level file handles
Module-level

    TEST_IMAGES = [
        open(os.path.join(pwd, 'ishaan_github.png'), 'rb'),
        open(os.path.join(pwd, 'litellm_site.png'), 'rb'),
    ]
    SINGLE_TEST_IMAGE = open(...)

opens the file once at import. After the first multipart upload, the
file pointer is at EOF, so every subsequent test in the same xdist
worker sends an empty multipart body. That non-determinism (a) blows
the recorded cassette past MAX_EPISODES_PER_CASSETTE (50) so
_RedisPersister.save_cassette refuses to save it, and (b) re-bills the
live image edit endpoint on every CI run.

Recent CI runs confirm the leak: tests/image_gen_tests/test_image_edits.py
shows six tests parking at 51-52 cassette entries
(TestOpenAIImageEditGPTImage1::test_openai_image_edit_litellm_sdk[False],
TestOpenAIImageEditDallE2::..., test_openai_image_edit_with_bytesio,
test_openai_image_edit_litellm_router, test_multiple_vs_single_image_edit[False],
test_multiple_image_edit_with_different_formats).

Replace the module-level file handles with _make_test_images() /
_make_single_test_image() factories that return fresh _RewindableImage
(BytesIO subclass) objects whose pointer always starts at 0. The image
bytes are read once at import into module-level constants
(_ISHAAN_GITHUB_BYTES, _LITELLM_SITE_BYTES), so disk I/O cost is
unchanged.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-13 00:32:23 +00:00
Cursor AgentandMateo Wang b637d9f64a test(vcr): classify cache verdicts, detect live calls, surface cost leaks
Convert the per-test VCR verdict line from a single 'NOOP / HIT / MISS /
PARTIAL' tag into a classified outcome that distinguishes the cases that
silently bill the live API on every CI run from the ones that don't:

  HIT                         pure replay
  PARTIAL                     mixed replay + new recordings
  MISS:RECORDED               new cassette saved to Redis (cached next run)
  MISS:OVERFLOW               cassette > MAX_EPISODES_PER_CASSETTE; persister
                              refused to save; re-bills every run
  MISS:NOT_PERSISTED          test failed; save_cassette skipped; re-bills
  NOOP                        VCR-marked but no HTTP traffic (mocked elsewhere)
  UNMARKED:LIVE_CALL          test bypassed VCR AND opened a TCP connection
                              to a known LLM provider host -> wasted spend
  UNMARKED:NO_TRAFFIC         test bypassed VCR but didn't call out

The UNMARKED:LIVE_CALL signal is what converts 'this test probably hits
live' into 'this test connected to api.openai.com'. We install a
socket.connect / socket.create_connection wrapper for the duration of
each non-VCR-marked test and record any outbound TCP to a known LLM
provider hostname. The probe sits below the httpx layer so vcrpy and
respx (which both patch above the socket) are unaffected.

Replace the file-level _RESPX_CONFLICTING_FILES blacklists in the
llm_translation and local_testing conftests with per-item respx
detection in apply_vcr_auto_marker_to_items. A test now skips VCR when
it actually carries @pytest.mark.respx or has respx_mock in its fixture
chain - not just because some other test in the same file imports
MockRouter. Items skipped by skip_files are split into respx_conflict
(real conflict, the module wires up respx) vs file_opt_out (dead skip-
list entry whose module never touches respx) so the session summary
makes pruning obvious.

Stabilize the AWS SigV4 fingerprint: the Authorization header on
Bedrock requests rotates its Credential date and Signature on every
call, which previously pushed every Bedrock test past the 50-episode
overflow threshold. Extract the access-key id only
('aws-sigv4:AKIA...') so two requests with the same identity match.

Always emit verdict logging when VCR is active (set
LITELLM_VCR_VERBOSE=0 to opt back into the legacy quiet mode). Add a
session-end classification summary that lists overflow tests, unmarked
live-call tests, and the skip-reason breakdown.

Wire the live-call probe + summary hook into every test directory that
already uses the Redis-backed VCR cache (audio_tests, guardrails_tests,
image_gen_tests, litellm_utils_tests, llm_responses_api_testing,
llm_translation, local_testing, logging_callback_tests, ocr_tests,
pass_through_unit_tests, router_unit_tests, search_tests,
unified_google_tests).

Add tests/llm_translation/test_vcr_classification.py covering the
verdict classifier, skip-reason tagging, AWS SigV4 fingerprint stability,
live-host classification, and session summary rendering.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-13 00:31:47 +00:00
Yuneng Jiang 945b10ded4 fix(tests): drop dall-e-only test classes; route live image tests via gpt-image-1
Second wave of failures from the 2026-05-12 DALL-E shutdown:
- tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditDallE2
  and tests/image_gen_tests/test_image_generation.py::TestOpenAIDalle3
  are explicitly named for the deprecated models and can't pass; remove.
  gpt-image-1 coverage already exists in sibling classes.
- tests/local_testing/test_router.py image gen tests use dall-e-3 only
  as a routing example; swap to gpt-image-1.
- tests/local_testing/test_custom_callback_input.py image_generation
  success/failure paths swapped to gpt-image-1.
2026-05-12 16:16:59 -07:00
7e13256fee test: add 24hr Redis-backed VCR cache to additional test suites (#27159)
* test: add 24hr Redis-backed VCR cache to additional test suites

Extracts the existing llm_translation VCR plumbing into a reusable helper
(tests/_vcr_conftest_common.py) and wires it into the conftest.py files
of the test directories listed in LIT-2787:

  audio_tests, batches_tests, guardrails_tests, image_gen_tests,
  litellm_utils_tests, local_testing, logging_callback_tests,
  pass_through_unit_tests, router_unit_tests, unified_google_tests

The same helper is also adopted by the pre-existing llm_translation and
llm_responses_api_testing conftests to remove the copy-pasted VCR setup.

Each consuming conftest:
- registers the Redis persister via pytest_recording_configure
- auto-marks collected tests with pytest.mark.vcr (skipping respx-using
  files where applicable, since respx and vcrpy both patch httpx)
- gates cassette writes on test success via _vcr_outcome_gate

The cache is opt-in via CASSETTE_REDIS_URL; when unset, VCR is disabled
and tests hit live providers as before. LITELLM_VCR_DISABLE=1 still
forces a bypass for ad-hoc local runs.

Test directories that run LiteLLM proxy in Docker (build_and_test,
proxy_logging_guardrails_model_info_tests, proxy_store_model_in_db_tests)
are intentionally not included: VCR.py patches the in-process httpx
transport and cannot intercept calls made from inside a Docker container.
The installing_litellm_on_python* jobs make no LLM calls and don't
benefit from caching.

https://linear.app/litellm-ai/issue/LIT-2787/add-24hr-caching-to-additional-test-suites

* test(vcr): add safe-body matcher to handle JSONL and binary request bodies

vcrpy's stock body matcher inspects Content-Type and unconditionally
runs json.loads on application/json bodies. JSON Lines payloads (used
by the Bedrock batch S3 PUT and other upload paths) crash that with
json.JSONDecodeError: Extra data, before the matcher can return
'not a match'.

This was the root cause of the batches_testing CI job failing on
test_async_create_file once VCR auto-marking was applied to the
batches_tests directory.

Add a conservative byte-equality body matcher and use it in place of
'body' in the shared match_on tuple. The matcher is strictly more
conservative than vcrpy's default — the only thing it gives up is
'different JSON key order is treated as the same body', which doesn't
apply to deterministic litellm-built request payloads. It can never
produce a false positive that the default would have rejected, so
there is no cross-contamination risk.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): exclude tests that VCR replay actively breaks

A few tests are incompatible with cassette replay and were failing on
the latest CI run after VCR auto-marking was extended to local_testing
and logging_callback_tests:

- test_amazing_s3_logs.py (logging_callback_tests): the test asserts on
  a per-run response_id that should round-trip through a real S3
  PUT/LIST. vcrpy's boto3 stub intercepts the PUT and the LIST replays
  stale keys, so the freshly-generated id is never found.
- test_async_embedding_azure (logging_callback_tests) and
  test_amazing_sync_embedding (local_testing): the failure branches
  deliberately pass api_key='my-bad-key' to assert that the failure
  callback fires. We scrub auth headers from cassettes (so the bad-key
  request matches the prior good-key request), and vcrpy replays the
  recorded 200 — the failure callback never fires.
- test_assistants.py (local_testing): the OpenAI Assistants polling
  APIs mint fresh thread/run IDs every recording session and then poll
  until status=='completed'. Replays of those polled GETs can never
  match a freshly-generated run id, so every CI run effectively
  re-records and the suite blows past the 15m no_output_timeout.

Skip these from VCR auto-marking so they continue to hit live providers
as they did before this change. The remaining tests in each directory
still get cached.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): expand skip lists for second batch of incompatible tests

Followup to the previous commit. After re-running CI on the rebuilt
branch, three more tests surfaced as VCR-replay-incompatible:

- litellm_utils_testing :: test_get_valid_models_from_dynamic_api_key
  Calls GET /v1/models with api_key='123' to assert the result is empty.
  We scrub auth headers, so the bad-key request matches the prior
  good-key cassette and replays the recorded model list.
- litellm_utils_testing :: test_litellm_overhead.py
  Measures litellm_overhead_time_ms as a percentage of total wall-clock
  time. With cached responses the upstream 'network' time collapses to
  microseconds, blowing past the 40%% threshold the test asserts on.
  Skip the whole file (every parametrization is at risk).
- local_testing_part1 :: test_async_custom_handler_completion and
  test_async_custom_handler_embedding
  Same bad-key failure-callback pattern as the already-skipped
  test_amazing_sync_embedding.
- litellm_router_testing :: test_router_caching.py
  Asserts on litellm's own router-level response cache by comparing
  response1.id to response2.id across repeat upstream calls (test
  bypasses litellm cache via ttl=0 and expects upstream to return a
  *new* id). With VCR replay both upstream calls return the same
  cassette body, so the ids are identical. Skip the whole file.
- logging_callback_tests :: test_async_chat_azure (preemptive)
  Same shape as already-skipped test_async_embedding_azure; was masked
  by upstream OpenAI rate-limit failures on baseline.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): use item.path and tighten matcher docstring

- Replace pytest's deprecated item.fspath with item.path in
  apply_vcr_auto_marker_to_items so we don't emit deprecation
  warnings under pytest 8.
- Clarify _safe_body_matcher docstring to reflect actual behavior
  (direct == first, then UTF-8 bytes comparison, no repr fallback).

Addresses Greptile review feedback on PR #27159.

* test(vcr): swallow all RedisError on cassette save/load

Cassette persistence is strictly best-effort: any Redis-side failure
(connection blip, timeout, OutOfMemoryError when the maxmemory cap is
hit, READONLY replicas, etc.) should degrade to 'test passed but
cassette not cached' rather than fail the test on teardown.

Previously the persister only caught ConnectionError and TimeoutError,
so OutOfMemoryError — which Redis Cloud raises when the cassette cache
hits its memory cap and there are no evictable keys — propagated out of
vcrpy's autouse fixture and ERRORed otherwise-passing tests on
teardown. This caused the litellm_utils_testing CircleCI job to fail on
the latest commit's run, even though the underlying test was a unit
test that used mock_response and produced no real upstream traffic
(the cassette was dirtied by a background langfuse callback). The
rerun only succeeded because Redis evictions happened to free enough
room before the SET — i.e. it was timing-dependent flakiness.

Catch redis.exceptions.RedisError (the common base of all server- and
client-side Redis exceptions) on both save and load, and parametrize
the regression tests across ConnectionError, TimeoutError, and
OutOfMemoryError to pin the new behavior.

* test(vcr): surface cassette-cache failures with warnings + session banner

When the persister silently swallows a Redis OOM (or any RedisError) on
save/load there is otherwise no visible signal that the cache is
degraded — tests pass, the cassette just isn't persisted, and the next
session still hits the same Redis at the same near-cap memory.

Add three layers of observability so that failure mode is loud:

1. Per-process health counters ("save_failures", "load_failures", and
   the last error string for each), exposed via cassette_cache_health()
   and reset via reset_cassette_cache_health(). The persister
   increments these in addition to logging.

2. VCRCassetteCacheWarning (UserWarning subclass) emitted via
   warnings.warn() inside the persister's except block. Pytest's
   built-in warnings summary at session end automatically lists every
   such warning, so the failure is visible in CI logs without any
   conftest-level wiring.

3. Session-end banner via emit_cassette_cache_session_banner() and a
   stderr-fallback atexit handler registered from
   register_persister_if_enabled(). Two states:
     - red "VCR CASSETTE CACHE DEGRADED" when save_failures or
       load_failures > 0
     - yellow "VCR CASSETTE CACHE NEAR CAPACITY" (no failures, but
       used_memory >= 85% of maxmemory) so the next session knows
       the Redis is approaching OOM before any SET actually fails

Capacity comes from a best-effort INFO memory probe
(cassette_cache_capacity_snapshot) that returns None on any failure or
when maxmemory is uncapped. The atexit handler skips xdist workers so
only the controller emits.

Tests: parametrize the existing save/load swallow-error tests across
ConnectionError/TimeoutError/OutOfMemoryError, add direct tests for
the health counters and warning emission, and a new
test_vcr_conftest_common_banner.py covering banner output for every
state (silent/red/yellow/disabled/xdist-worker).

* test(vcr): bucket cassettes by API key fingerprint, drop bad-key skips

Tests that deliberately call an LLM API with a bad key (e.g. to assert
that the failure callback fires, or that check_valid_key returns False)
were being silently served the prior good-key cassette: we scrub the
real Authorization / x-api-key header from the cassette before storing
it, so a follow-up bad-key call is byte-identical to the good-key call
under the existing match_on tuple.

Add a 'key_fingerprint' custom matcher that distinguishes requests by
the SHA-256 of their API-key headers. The fingerprint is stamped into
a synthetic 'x-litellm-key-fp' header by a new before_record_request
hook, which then strips the real auth headers (we have to do the
scrubbing here instead of via vcrpy's filter_headers knob, because
filter_headers runs *first* and would erase the value we want to hash).

Bad-key requests now get a different cassette bucket than good-key
requests, so vcrpy will not replay a recorded 200 in place of the
expected 401. The fingerprint is a one-way hash of the secret, so
cassettes never contain the key.

This permanently removes the 'bad-key' category of skips:

- tests/local_testing: dropped ::test_amazing_sync_embedding,
  ::test_async_custom_handler_completion,
  ::test_async_custom_handler_embedding
- tests/logging_callback_tests: dropped ::test_async_chat_azure,
  ::test_async_embedding_azure
- tests/litellm_utils_tests: dropped
  ::test_get_valid_models_from_dynamic_api_key

Coverage: 7 new unit tests in tests/test_litellm/test_vcr_safe_body_matcher.py
covering header stripping, fingerprint determinism, no-auth bucketing,
good-vs-bad key discrimination, x-api-key (Anthropic/Azure) discrimination,
and idempotence under replay.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): drop redundant comments and docstrings

Trim narration of code that is already self-evident from function and
variable names. Keep the two genuinely non-obvious bits:

- ordering constraint between filter_headers and before_record_request,
  which would invite a maintainer to re-introduce the bug if removed
- the per-directory _VCR_INCOMPATIBLE_FILES rationale, since 'why
  exactly is this skipped' is not knowable from the test name alone

Also drop the 40-line commented-out drop-in conftest snippet at the
bottom of _vcr_conftest_common.py — the consuming conftests are the
canonical reference.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): make _before_record_request idempotent

vcrpy invokes before_record_request more than once per request:
can_play_response_for calls it, then __contains__ /
_responses (reached via play_response) call it again on the
result. The second invocation sees a request whose auth headers we
already stripped, so a naive recompute yields "no-key" and
overwrites the real fingerprint stored in the header.

This makes can_play_response_for and play_response disagree on
matchability — the former says "yes, we have a stored response for
this" (matching no-key to no-key) and the latter throws
UnhandledHTTPRequestError because it computes a fresh real
fingerprint that doesn't match the stored no-key.

In CI this manifested as ~30 failing tests across guardrails_testing,
audio_testing, batches_testing, image_gen_testing, llm_responses_api,
litellm_router_unit_testing, etc. Skip the recompute when the header
is already set, so re-applying the hook is a no-op.

Adds a regression test that fires the hook twice on the same dict and
asserts the fingerprint stays put.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

* test(vcr): drop more redundant docstrings and headers

* test(vcr): enable 24hr cache for ocr_tests and search_tests

These two directories were the only non-dockerized test suites in the
build_and_test workflow that make live LLM/provider API calls but were
not VCR-enabled by this PR. Together they account for 96 tests:

- tests/ocr_tests/ (31): Mistral OCR, Azure AI OCR, Azure Document
  Intelligence, Vertex AI OCR. Pure-unit tests inside the same files
  (e.g. TestAzureDocumentIntelligencePagesParam) make no HTTP calls
  and become benign VCR NOOPs.
- tests/search_tests/ (65): Brave, DataForSEO, DuckDuckGo, Exa,
  Firecrawl, Google PSE, Linkup, Parallel.ai, Perplexity, SearchAPI,
  Searxng, Serper, Tavily.

Both directories use the canonical minimal conftest pattern from
tests/audio_tests/conftest.py with no skip lists. None of the test
files use respx, none assert on per-call upstream non-determinism
(no response1.id != response2.id, no overhead-as-fraction-of-total,
no live polling), so the default match_on tuple should cache cleanly.
If a flake surfaces during the first cassette-recording CI run, we
can add a targeted skip the same way we did for the other dirs.

Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
2026-05-05 15:13:31 -07:00
Sameer KankuteandCursor c53c71ad66 test(image_gen): align Azure image gen fixture with body omitting model
Expected JSON matches deployment-scoped Azure POST (#26316).

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-04 18:09:30 +05:30
Sameer KankuteandCursor 41ac026fc1 test(image_gen): expect no model in Azure image edit multipart (#26316)
Align test_azure_image_edit_litellm_sdk with deployment-scoped Azure edits.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-05-04 12:20:29 +05:30
Ishaan Jaffer e8461b5b97 style: run black formatter on files from main merge 2026-04-17 13:02:59 -07:00
Krrish Dholakia c7e2bfc577 fix: cleanup tests 2026-03-30 16:24:35 -07:00
Krrish Dholakia 7b532fda66 test: cleanup tests 2026-03-30 16:20:01 -07:00
Ishaan Jaffer 899b5710d1 TestAzureAIFlux2ImageEdit 2026-03-30 16:15:03 -07:00
Krrish Dholakia 1fb677702d test: update to new vertex ai keys 2026-03-28 20:19:05 -07:00
Krrish Dholakia bc829d51f2 test: test 2026-03-28 19:17:38 -07:00
Cursor Agentandyuneng-jiang 49dc391a46 fix(ci): remove unused is_expired variable (ruff F841) and handle ModelDeprecated in image gen test
- Remove dead code: is_expired was assigned but never used in
  mcp_management_endpoints.py (the raw expires_at timestamp is passed
  directly to the client per existing comment)
- Handle Azure DALL-E 3 ModelDeprecated (HTTP 410) error gracefully in
  base_image_generation_test.py so CI doesn't fail on deprecated model
  deployments

Co-authored-by: yuneng-jiang <yuneng-jiang@users.noreply.github.com>
2026-03-12 01:27:42 +00:00
Sameer Kankute a8301d5614 Fix: varaitions endpoint geting 401 2026-03-09 12:51:21 +05:30
Ishaan JaffandGitHub a30b71c946 fix(tests): generate square PNG in image_url fixture for DALL-E 2 variation test (#23073)
DALL-E 2 create_variation requires a square PNG. The old fixture fetched
the LiteLLM logo from S3 which is non-square, causing API rejections.
Replace with a programmatically-generated 1024x1024 RGBA PNG via Pillow.
2026-03-07 16:58:27 -08:00
Ishaan JaffandGitHub 66c822435e fix(ci): image variation openai sdk 2.24.0 compat + swap bedrock nova-premier to nova-pro (#23066)
* fix(ci): fix image variation test for openai sdk 2.24.0 and swap nova-premier to nova-pro

image_gen_tests: openai==2.24.0 (bumped Feb 25) requires BytesIO objects to have
a .name attribute for MIME type detection in multipart uploads. Add .name to the
fixture so create_variation works. Also guard with OPENAI_API_KEY skipif.

proxy_e2e_anthropic_messages_tests: nova-premier requires provisioned throughput
not available via standard on-demand cross-region inference on the CI account.
Swap to nova-pro which uses standard inference profiles.

* fix: remove skipif, keep only .name fix for openai sdk compat
2026-03-07 16:41:54 -08:00
Alexsander HamirandGitHub ebce0e5f8c [Release - 02/10/2026] v1.81.10-nightly 2026-02-10 16:26:30 -08:00
Sameer Kankute caab7821bd Fix: imagegeneration@006 has been deprecated 2026-01-22 18:24:59 +05:30
Ishaan Jaffer 58e6ef7d93 TestAzureAIFlux2ImageEdit 2026-01-08 18:23:05 +05:30
Ishaan JaffandGitHub 929af510fa [Feat] New provider - Add Azure BFL FLux for image edits (#18766)
* add azure_ai/flux.2-pro

* get_flux2_image_generation_url

* azure_client_params

* docs

* add Image Editing

* add azure ai image edits

* AzureFoundryFlux2ImageEditConfig

* TestAzureAIFlux2ImageEdit
2026-01-07 23:28:39 +05:30
Ishaan Jaffer 45f840d274 test_azure_image_edit_cost_tracking 2026-01-07 15:12:51 +05:30
Ishaan Jaffer ee2b51b2d0 test_openai_image_edit_cost_tracking 2026-01-07 14:36:50 +05:30
Ishaan Jaffer 7d28485cb5 test_amazon_titan_image_gen 2025-12-20 15:16:55 +05:30
Ishaan Jaffer 627d615322 test_amazon_titan_image_gen 2025-12-20 14:36:50 +05:30
Sameer Kankute b0a219b718 fix lint error 2025-12-19 23:45:37 +05:30
Sameer Kankute b849f51e58 Add support for stability model in image edit 2025-12-19 23:03:17 +05:30
Alexsander HamirandGitHub 0c48826cdc Revert "[Fix] CI/CD - local_testing & mapped tests (#18222)" (#18223)
This reverts commit dc7f500c47.
2025-12-18 14:46:09 -08:00
Alexsander HamirandGitHub dc7f500c47 [Fix] CI/CD - local_testing & mapped tests (#18222) 2025-12-18 14:34:48 -08:00
Sameer Kankute 085b07cdde Add test for handling gaurdrails param 2025-12-17 14:12:27 +05:30
Ishaan Jaffer efa9f69991 TestRunwaymlImageGeneration 2025-12-13 17:21:20 -08:00
Ishaan Jaffer 2fd8621b38 test recraft 2025-12-13 16:10:34 -08:00
Ishaan Jaffer 050264f7d7 test_recraft_image_edit_api 2025-12-13 16:09:52 -08:00
Ishaan Jaffer 0346d1ea23 fix 2025-11-26 17:11:33 -08:00
Sameer KankuteandGitHub 3249f6dd2d Merge pull request #17070 from BerriAI/litellm_add_vertex_ai_image_support
Add vertex ai image gen support for both gemini and imagen models
2025-11-26 00:04:03 +05:30
Sameer Kankute 883cfaeeaf Add tests 2025-11-25 13:32:13 +05:30
Dmitrii KomarovandGitHub 046b7efbbe Make Bedrock image generation more consistent (#17021) 2025-11-24 20:58:01 -08:00
Ishaan Jaffer 8b8b31ecd8 fix img gen 2025-11-21 17:18:48 -08:00
Ishaan Jaffer 69da15e65e test_fal_ai_image_generation_basic 2025-11-21 16:23:41 -08:00
a2e3b942dc Vector store files Stable Release (#16643)
* Add support for vector store files endpoints (#16490)

* Add base code for vector store integration

* fix azure related tests and linting error

* fix mypy errors

* Add vector store files documentation

* fix mapped tests

* Add bytedance and ideogram support in fal ai (#16636)

* Add fal ai flux pro v1.1 support (#16578)

* Add fal ai flux pro v1.1 support

* Add tests and docs

---------

Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
2025-11-15 13:00:33 -08:00
Sameer KankuteandGitHub 13993d6ea3 Add fal-ai/flux/schnell support (#16580) 2025-11-13 22:31:31 -08:00
Ishaan JaffandGitHub b30439257b [Feat] Add RunwayML Img Gen API support (#16557)
* TestRunwaymlImageGeneration

* fix RUNWAYML

* rename

* fix rename

* get_runwayml_image_generation_config

* get_runwayml_image_generation_config

* TestRunwaymlImageGeneration

* add RUNWAYML_POLLING_TIMEOUT

* fix rnwayml transform img gen

* runwayml_image_cost_calculator

* runwayml_image_cost_calculator

* docs runwayml

* fix runwayML polling

* test_get_first_default_fallback
2025-11-12 18:20:14 -08:00
Krish DholakiaandGitHub 06906534b3 feat(audio_transcriptions/): calculate duration of audio file for cost calculation + feat (image_generations): cost tracking accuracy improved with output_format, quality, size values fixed per openai model
* feat(audio_transcriptions/): calculate duration of audio file for cost calculation

Fixes https://github.com/BerriAI/litellm/issues/11846

Closes https://github.com/BerriAI/litellm/issues/14605

* fix(cost_calculator.py): correctly use base model, when set

Fixes issue where azure base model was being ignored

* feat(cost_calculator.py): fix default cost tracking quality param for image generation

* feat(image_generations/): return output_format, quality, size

aligns response to openai spec and improves cost tracking accuracy

* fix(cost_calculator.py): refactor cost calculation for image generation to use image response instead of hidden params

* build: update build

* fix: fix cost calculation

* build: update poetry lock

* fix: fix ruff checks

* fix: fix aembedding

* fix: fix ruff errors

* fix: modify to catch errors

* fix: test

* fix: loosen test to handle openai lib out of sync

* fix: fix base models

* fix: fix usage object
2025-11-08 16:24:31 -08:00
Krish DholakiaandGitHub 202eaeb1a2 Revert "(feat) Audio transcription - cost tracking + (feat) image generation …" (#16409)
This reverts commit c96da44265.
2025-11-08 15:38:16 -08:00
Krish DholakiaandGitHub c96da44265 (feat) Audio transcription - cost tracking + (feat) image generation - accurate cost tracking based on output_format/quality/size
* feat(audio_transcriptions/): calculate duration of audio file for cost calculation

Fixes https://github.com/BerriAI/litellm/issues/11846

Closes https://github.com/BerriAI/litellm/issues/14605

* fix(cost_calculator.py): correctly use base model, when set

Fixes issue where azure base model was being ignored

* feat(cost_calculator.py): fix default cost tracking quality param for image generation

* feat(image_generations/): return output_format, quality, size

aligns response to openai spec and improves cost tracking accuracy

* fix(cost_calculator.py): refactor cost calculation for image generation to use image response instead of hidden params

* build: update build

* fix: fix cost calculation

* build: update poetry lock

* fix: fix ruff checks

* fix: fix aembedding

* fix: fix ruff errors

* fix: modify to catch errors

* fix: test

* fix: loosen test to handle openai lib out of sync
2025-11-08 15:30:46 -08:00
Ishaan Jaffer 044e26081d test_get_request_body_nova_canvas_inference_profile_arn 2025-10-29 18:30:59 -07:00
Ishaan JaffandGitHub 99feefd614 [Feat] Add FAL AI Image Generations on LiteLLM (#16067)
* add fal-ai provider

* fix image_generation_handler

* init FalAIImageGenerationConfig

* init cost_calculator

* init FAL AI

* TestFAL_AI_ImageGeneration

* fix load_custom_provider_entrypoints

* TestFAL_AI_ImageGeneration

* add imagen4 transform FAL AI

* add FAL AI imagen 4 transform

* BaseImageGenTest

* test_fal_ai_image_generation_basic

* add BRIA + Recraft img gen

* add recraft + BRIA

* test_fal_ai_image_generation_basic

* tests for flux PRO v11

* Add FAL AI SD

* test FAL AI SD

* docs FAL AI

* docs fal ai

* Using Model-Specific Parameters

* add fal ai model prices

* add fall_ai JPG logo

* ui fixes FAL AI

* fix linting

* fix linting

* fix bedrock test_get_request_body_stability3

* test_custom_llm_provider_entrypoint
2025-10-29 13:10:51 -07:00
Ishaan Jaffer 3bd42b7ccf test_image_generation_azure_dall_e_3 2025-10-25 15:47:40 -07:00