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fix(ci): unbreak realtime + bedrock batch tests (#27690)
* fix(tests): drop deprecated OpenAI-Beta realtime header
OpenAI deprecated the 'OpenAI-Beta: realtime=v1' header; the live
service now returns code 4000 invalid_beta with
"Unknown beta requested: 'realtime'.". Two integration tests in
tests/llm_translation/realtime/test_realtime_guardrails_openai.py
hardcoded the header and started failing across all PRs.
Library code is unaffected: the OpenAI realtime handler only
forwards 'OpenAI-Beta: realtime=v1' upstream when the proxy *client*
sends it (litellm/llms/openai/realtime/handler.py). Default proxy
behavior uses the GA protocol.
Connect to OpenAI without the deprecated header, and accept the GA
event name 'response.output_audio_transcript.delta' alongside the
beta-protocol name 'response.audio_transcript.delta' for the
transcript-delta assertion.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(logging): post_call tolerates non-JSON-serializable values
post_call() did json.dumps(original_response) without default=str, so
any provider passing a dict containing datetime/Decimal/etc. would
raise TypeError. Bedrock batch retrieval hits this with
get_model_invocation_job() responses that include datetime fields
(submitTime, lastModifiedTime, endTime), failing
tests/batches_tests/test_bedrock_files_and_batches.py::test_async_file_and_batch
across all PRs.
Pass default=str so non-serializable values fall back to str().
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(tests): mock boto3 in bedrock retrieve batch test
The test patched AsyncHTTPHandler.get, but the bedrock retrieve
handler uses boto3.client('bedrock').get_model_invocation_job
directly, so the real AWS call was being made on every run, failing
with AccessDeniedException because the hardcoded test ARN belongs to
a different AWS account.
- Mock boto3.client and BedrockBatchesConfig.get_credentials so the
test never touches AWS.
- Use status=Completed in the mock response so output_file_id is
populated (the handler intentionally leaves it None for
non-completed jobs).
- Assert the predicted per-job output object URI (matches what the
handler actually returns) instead of the bare output prefix.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* docs(tests): include GA event name in guardrail-block test docstring
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
This commit is contained in:
Mateo Wang
GitHub
parent
afbe864750
commit
6de00e24b4
4 changed files with 41 additions and 30 deletions
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@ -1212,7 +1212,7 @@ class Logging(LiteLLMLoggingBaseClass):
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# Log the exact result from the LLM API, for streaming - log the type of response received
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litellm.error_logs["POST_CALL"] = locals()
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if isinstance(original_response, dict):
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original_response = json.dumps(original_response)
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original_response = json.dumps(original_response, default=str)
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try:
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self.model_call_details["input"] = input
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self.model_call_details["api_key"] = api_key
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@ -157,16 +157,16 @@ async def test_bedrock_retrieve_batch():
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"""
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print("Testing bedrock batch retrieval")
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# Mock bedrock batch response
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mock_bedrock_response = {
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"jobArn": "arn:aws:bedrock:us-west-2:123456789012:model-invocation-job/test-job-123",
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"jobName": "test-job-123",
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"modelId": "us.anthropic.claude-haiku-4-5-20251001-v1:0",
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"roleArn": "arn:aws:iam::123456789012:role/service-role/AmazonBedrockExecutionRoleForAgents_TEST",
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"status": "InProgress",
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"message": "Job is in progress",
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"status": "Completed",
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"message": "",
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"submitTime": "2024-01-01T12:00:00Z",
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"lastModifiedTime": "2024-01-01T12:30:00Z",
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"endTime": "2024-01-01T13:00:00Z",
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"inputDataConfig": {
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"s3InputDataConfig": {"s3Uri": "s3://test-bucket/input/test-input.jsonl"}
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},
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@ -175,43 +175,38 @@ async def test_bedrock_retrieve_batch():
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},
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}
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# Mock the HTTP response
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mock_response = MagicMock()
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mock_response.json.return_value = mock_bedrock_response
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mock_response.status_code = 200
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mock_bedrock_client = MagicMock()
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mock_bedrock_client.get_model_invocation_job.return_value = mock_bedrock_response
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mock_creds = MagicMock(access_key="ak", secret_key="sk", token="tok")
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# Print the mock response to debug
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print("MOCK RESPONSE DATA:", mock_bedrock_response)
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with patch(
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"litellm.llms.custom_httpx.http_handler.AsyncHTTPHandler.get"
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) as mock_get:
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mock_response.raise_for_status.return_value = None
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mock_get.return_value = mock_response
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# Test retrieve batch
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with (
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patch("boto3.client", return_value=mock_bedrock_client),
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patch(
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"litellm.llms.bedrock.batches.transformation.BedrockBatchesConfig.get_credentials",
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return_value=mock_creds,
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),
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):
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batch_response = await litellm.aretrieve_batch(
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batch_id="arn:aws:bedrock:us-west-2:123456789012:model-invocation-job/test-job-123",
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custom_llm_provider="bedrock",
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model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
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)
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print("MOCKED BATCH RESPONSE=", batch_response)
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# Validate the response
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assert (
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batch_response.id
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== "arn:aws:bedrock:us-west-2:123456789012:model-invocation-job/test-job-123"
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)
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assert batch_response.object == "batch"
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assert (
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batch_response.status == "in_progress"
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) # Bedrock "InProgress" maps to "in_progress"
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assert batch_response.status == "completed"
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assert batch_response.endpoint == "/v1/chat/completions"
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# Validate input and output file IDs in the final transformed response
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assert batch_response.input_file_id == "s3://test-bucket/input/test-input.jsonl"
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assert batch_response.output_file_id == "s3://test-bucket/output/"
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# Bedrock returns only the output *prefix*; the handler predicts the
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# actual output object as <prefix>/<job-id>/<basename(input)>.out.
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assert (
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batch_response.output_file_id
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== "s3://test-bucket/output/test-job-123/test-input.jsonl.out"
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)
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def test_bedrock_batch_with_encryption_key_in_post_request():
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@ -104,7 +104,8 @@ async def test_text_message_blocked_by_guardrail_no_ai_response():
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Send a text message containing the blocked phrase.
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Guardrail must:
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- Send error event (guardrail_violation) to client.
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- Send response.audio_transcript.delta with the block message to client.
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- Send response.output_audio_transcript.delta (or beta-protocol
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response.audio_transcript.delta) with the block message to client.
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- NOT forward response.create to OpenAI (no AI response).
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"""
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import websockets
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@ -119,7 +120,6 @@ async def test_text_message_blocked_by_guardrail_no_ai_response():
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OPENAI_REALTIME_URL,
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additional_headers={
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"Authorization": f"Bearer {OPENAI_API_KEY}",
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"OpenAI-Beta": "realtime=v1",
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},
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) as backend_ws:
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streaming, input_queue = await _build_streaming(client_events, backend_ws)
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@ -182,7 +182,11 @@ async def test_text_message_blocked_by_guardrail_no_ai_response():
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transcript_deltas = [
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e
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for e in client_events
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if e.get("type") == "response.audio_transcript.delta"
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if e.get("type")
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in (
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"response.output_audio_transcript.delta",
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"response.audio_transcript.delta",
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)
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]
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assert (
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len(transcript_deltas) >= 1
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@ -298,7 +302,6 @@ async def test_clean_text_message_passes_through_to_openai():
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OPENAI_REALTIME_URL,
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additional_headers={
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"Authorization": f"Bearer {OPENAI_API_KEY}",
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"OpenAI-Beta": "realtime=v1",
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},
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) as backend_ws:
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streaming, input_queue = await _build_streaming(client_events, backend_ws)
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@ -36,6 +36,19 @@ def test_get_masked_api_base(logging_obj):
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assert type(masked_api_base) == str
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def test_post_call_serializes_dict_with_datetime(logging_obj):
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import datetime
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response = {
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"status": "InProgress",
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"submitTime": datetime.datetime(2026, 5, 11, 23, 49, 13, 132000),
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}
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logging_obj.post_call(original_response=response)
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serialized = logging_obj.model_call_details["original_response"]
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assert isinstance(serialized, str)
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assert "2026-05-11" in serialized
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def test_sentry_sample_rate():
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existing_sample_rate = os.getenv("SENTRY_API_SAMPLE_RATE")
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try:
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