Adds litellm/litellm_core_utils/aws_partition.py mapping a region to its
AWS partition (aws, aws-cn, aws-us-gov, and the iso partitions), its DNS
suffix, and its ARN prefix, and uses it at every AWS host and ARN build
site: bedrock (runtime, agent, agentcore, legacy client, batches, files,
realtime), sagemaker, polly, secrets manager, s3 log uploads, bedrock
passthrough routes, and rag ingestion. ARN detection now accepts
arn:aws-cn: and arn:aws-us-gov: prefixes.
STS region resolution now falls back to the configured aws_region_name
after the aws_sts_endpoint host and the AWS_REGION/AWS_DEFAULT_REGION env
vars, so cn and gov role assumption no longer silently signs against
us-west-2.
A partition sweep test walks every endpoint builder with cn regions and
asserts no amazonaws.com host or arn:aws: prefix comes out, plus an AST
guard that fails on any new f-string hardcoding either literal.
* 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
Caller-supplied bedrock_tags land as AWS resource tags under the proxy's
AWS identity, letting an authenticated caller forge ownership or
cost-allocation labels. Add bedrock_tags to _BANNED_REQUEST_BODY_PARAMS
so per-request tags need general_settings.allow_client_side_credentials
or configurable_clientside_auth_params on the deployment, matching the
aws_bedrock_project_id precedent. Deployment-level bedrock_tags in
litellm_params are unaffected.
Also stop an explicit empty bedrock_tags list in litellm_params from
falling through to optional_params
* test(batches): add 1:1 test file scaffold for batches component paths
Co-authored-by: Cursor <cursoragent@cursor.com>
* Add harness test for create batch endpoint
* Add retrieve endpoint harness tests
* Add list endpoint harness tests
* Add cancel endpoint harness tests
* Add cancel endpoint harness tests
* Add test for litellm/batches/main.py
* Add test for litellm/tests/test_litellm/batches/test_batch_utils.py
* Add handler and transformation tests for all providers
* Fix: run batches tests in cicd
* fix(tests): remove azure/__init__.py that shadowed azure namespace package
Adding __init__.py to tests/test_litellm/llms/azure/ caused pytest to
insert tests/test_litellm/llms/ into sys.path[0], making our empty
azure/ dir shadow the real azure-identity namespace package. Any test
that patched azure.identity.* would then fail with AttributeError.
* style(tests): apply ruff format to test_batch_utils.py
Base migrated the formatter from black to ruff format (#31317); reformat the
batches scaffold test file to match.
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(bedrock): sanitize batch metadata to prevent Pydantic ValidationError
Proxy guardrail hooks (Model Armor, OpenAI Moderations) and internal
processing inject non-string values (dicts, floats) into the request
metadata. When the Bedrock batch handler passes this metadata directly
to LiteLLMBatch (which inherits OpenAI's Batch Pydantic model with
metadata: Dict[str, str]), Pydantic raises a ValidationError. This
causes the router retry loop to re-submit the same Bedrock job
multiple times before ultimately failing.
Add _get_openai_compatible_batch_metadata() that serializes non-string
values to JSON strings via safe_dumps, skips None values and internal
logging keys, ensuring the response object always validates.
* test(bedrock): add tests for batch metadata sanitization
Covers _get_openai_compatible_batch_metadata: string passthrough, dict/float
serialization, None/internal key exclusion, and LiteLLMBatch compatibility.
---------
Co-authored-by: Noah Nistler <60981020+noahnistler@users.noreply.github.com>
* feat(bedrock): support retrieve for model-invocation-job batch ARNs
`bedrock.retrieve_batch` previously only handled `:async-invoke/` ARNs
(Twelve Labs Marengo embeddings). The `:model-invocation-job/` ARNs
returned by `CreateModelInvocationJob` (the bulk batch inference API
behind `bedrock.create_batch`) fell through and returned a misleading
data-plane error, leaving created jobs unretrievable through the
LiteLLM batches API.
The two ARN families live on different AWS service endpoints
(`bedrock-runtime` data plane vs `bedrock` control plane), so they need
distinct handlers. This adds:
* `BedrockBatchesHandler._handle_model_invocation_job_status` — calls
the control plane via boto3 (`bedrock:GetModelInvocationJob`),
reusing `BaseAWSLLM.get_credentials` for credential resolution so
model_list / env / role-assumption configs continue to apply. The
response is reshaped into a `LiteLLMBatch` with the same status
mapping `transform_create_batch_response` already uses.
* Output-file-URI prediction. Bedrock surfaces the user-supplied
`s3OutputDataConfig.s3Uri` *prefix* in `GetModelInvocationJob`, but
results actually land at `<prefix>/<job-id>/<basename(input)>.out`.
We compute that single-file URI client-side and surface it as
`output_file_id`, so OpenAI-style `client.files.content(...)` works
without an extra `ListObjectsV2` round-trip. The bare prefix stays
in metadata for callers that want the manifest.
* Dispatch in `litellm/batches/main.py` for the new ARN family,
alongside the existing async-invoke branch.
* Unit tests covering ARN parsing, output-URI prediction (incl. edge
cases), the full status mapping, region resolution precedence, and
failure-message propagation.
Note: `request_counts` is intentionally `(0, 0, 0)` —
`GetModelInvocationJob` does not report per-record counts; getting
accurate numbers requires parsing `manifest.json.out` from the output
S3 prefix, which is left to callers.
Made-with: Cursor
* fix(bedrock): address PR feedback on model-invocation-job retrieve
Addresses Greptile P2 findings on #26834:
1. Use the bare job id (not the full ARN) when constructing the
`api_base` URL for `pre_call` logging. Passing the full ARN double-
counts the `model-invocation-job/` segment and embeds colons in the
path, producing misleading log lines.
2. Drop the `or output_prefix` fallback when `_predict_output_file_uri`
returns None. A bare prefix is not a downloadable object and surfacing
it as `output_file_id` re-creates the very NoSuchKey bug this handler
exists to fix. The bare prefix is still preserved in
`metadata["output_s3_uri"]` for callers that want to do their own S3
listing or read `manifest.json.out`.
`metadata["output_file_uri"]` uses "" rather than None to satisfy the
OpenAI Batch metadata schema (`dict[str, str]`); callers should branch
on the typed `output_file_id` field instead.
Also expands test coverage on the new code path:
- new "stay None" regression test for the prediction-fail case
- pre_call/post_call logging hook assertions (incl. the bare-id URL)
- explicit cancelled_at / expired_at coverage
- _to_epoch type-handling matrix and the boto3 ImportError branch
- defensive _extract_region_from_bedrock_arn exception path
- empty-basename case for _predict_output_file_uri
Patch coverage on the changed lines is now 100% (the only remaining
uncovered lines in the file belong to the pre-existing
`_handle_async_invoke_status` method, which this PR does not touch).
Made-with: Cursor
* test(bedrock): cover retrieve_batch dispatch for both ARN families
Codecov flagged 8 uncovered lines on `litellm/batches/main.py` after
this PR refactored the Bedrock dispatch into a single guard with two
sub-branches (`async-invoke` + `model-invocation-job`). Existing tests
exercised the handlers directly but not the dispatch in `main.py`.
Adds `tests/test_litellm/batches/test_retrieve_batch_bedrock_dispatch.py`
with 6 mocked tests that exercise `litellm.retrieve_batch` end-to-end
for the dispatch logic:
- async-invoke ARN routes to `_handle_async_invoke_status`
- async-invoke ARN with no region falls back to "us-east-1" (preserves
prior behavior on this branch)
- model-invocation-job ARN routes to the new
`_handle_model_invocation_job_status` handler
- model-invocation-job ARN with no region forwards None (so the new
handler can sniff region from the ARN itself, rather than getting
silently routed to us-east-1)
- unrelated bedrock ARN family falls through to the generic
provider-config retrieve path (neither special handler invoked)
- non-bedrock batch ids skip the bedrock dispatch entirely
Both handlers are mocked at the import site so the tests don't hit
AWS — the focus here is purely the new dispatch logic in main.py.
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(bedrock): move retrieve_batch dispatch test to tests/test_litellm/
The dispatch test landed under `tests/test_litellm/batches/`, a new
directory that no upstream `test-unit-*.yml` workflow's `test-path`
allow-list includes. As a result, the test was never executed in CI
and codecov reported `litellm/batches/main.py` patch coverage at
11.11% (8 lines uncovered) — the lines belonging to this PR's
dispatch refactor itself.
Move the file up one level so it matches the
`tests/test_litellm/test_*.py` glob that `test-unit-misc.yml`
already runs, and adjust `sys.path.insert` for the new depth.
The companion handler tests under
`tests/test_litellm/llms/bedrock/batches/test_handler.py` are
unaffected — they're picked up by the `llms` directory in
`test-unit-llm-providers.yml`.
Made-with: Cursor
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
