From e912e6d4ffe4789f693953e4a03fbbcd2d30fb63 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Wed, 6 May 2026 05:47:51 +0530 Subject: [PATCH 1/5] feat(audio_transcription): add NVIDIA Riva STT provider (#27185) * feat(audio_transcription): add NVIDIA Riva STT provider Adds nvidia_riva as a new audio transcription provider, supporting both NVCF-hosted and self-hosted Riva ASR deployments via gRPC streaming. - Auto-resamples input audio to 16 kHz mono LINEAR_PCM (soundfile + numpy, audioread fallback) so callers can send any common format. - Maps OpenAI params: language (en -> en-US), response_format (text/json/ verbose_json), timestamp_granularities=["word"] -> enable_word_time_offsets, word offsets converted ms -> s for verbose_json. - Auth: NVCF when nvcf_function_id is set (SSL on by default), self-hosted otherwise (SSL off by default), with explicit use_ssl override. - gRPC errors wrapped via NvidiaRivaException -> litellm exception classes. - Optional deps gated behind [stt-nvidia-riva] extra (nvidia-riva-client, soundfile, audioread, numpy). Co-authored-by: Cursor * fix(nvidia_riva): address PR review feedback - handler: forward call-level `timeout` to streaming_response_generator (kwarg-detected via inspect for older riva-client compat) so a stalled Riva server cannot block the caller indefinitely. - audio_utils: spill bytes to a tempfile before audioread.audio_open; most audioread backends (FFmpeg, GStreamer) require a real filesystem path and previously raised TypeError on BytesIO, breaking the mp3/m4a fallback path. - audio_utils: prefer soxr / scipy.signal.resample_poly for resampling (anti-aliased polyphase) when installed, falling back to linear only as a last resort. Avoids aliasing on 44.1/48 kHz -> 16 kHz downsamples. - transformation: bare `es` now maps to es-ES (Castilian) instead of es-US, matching BCP-47 conventions. Co-authored-by: Cursor * chore: trigger CI re-run [stabilize loop 1/3] * Update litellm/llms/nvidia_riva/audio_transcription/transformation.py Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> * chore: trigger CI re-run [stabilize loop 1/3] * fix code qa * fix lint * fix mypy * fix mypy * Fix NVIDIA Riva ASR service lookup * Fix NVIDIA Riva transcription payload logging --------- Co-authored-by: Cursor Co-authored-by: oss-pr-review-agent-shin[bot] <281797381+oss-pr-review-agent-shin[bot]@users.noreply.github.com> Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com> Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com> --- litellm/__init__.py | 8 + .../get_llm_provider_logic.py | 12 + litellm/llms/nvidia_riva/__init__.py | 0 .../audio_transcription/__init__.py | 0 .../audio_transcription/audio_utils.py | 232 +++++++++ .../audio_transcription/handler.py | 444 ++++++++++++++++++ .../audio_transcription/transformation.py | 284 +++++++++++ litellm/llms/nvidia_riva/common_utils.py | 92 ++++ litellm/main.py | 27 ++ litellm/types/utils.py | 1 + litellm/utils.py | 6 + provider_endpoints_support.json | 16 + pyproject.toml | 8 + tests/code_coverage_tests/liccheck.ini | 1 + .../test_litellm/llms/nvidia_riva/__init__.py | 0 .../audio_transcription/__init__.py | 0 .../audio_transcription/test_audio_utils.py | 130 +++++ .../audio_transcription/test_handler.py | 419 +++++++++++++++++ .../test_transformation.py | 275 +++++++++++ uv.lock | 167 ++++++- 20 files changed, 2120 insertions(+), 2 deletions(-) create mode 100644 litellm/llms/nvidia_riva/__init__.py create mode 100644 litellm/llms/nvidia_riva/audio_transcription/__init__.py create mode 100644 litellm/llms/nvidia_riva/audio_transcription/audio_utils.py create mode 100644 litellm/llms/nvidia_riva/audio_transcription/handler.py create mode 100644 litellm/llms/nvidia_riva/audio_transcription/transformation.py create mode 100644 litellm/llms/nvidia_riva/common_utils.py create mode 100644 tests/test_litellm/llms/nvidia_riva/__init__.py create mode 100644 tests/test_litellm/llms/nvidia_riva/audio_transcription/__init__.py create mode 100644 tests/test_litellm/llms/nvidia_riva/audio_transcription/test_audio_utils.py create mode 100644 tests/test_litellm/llms/nvidia_riva/audio_transcription/test_handler.py create mode 100644 tests/test_litellm/llms/nvidia_riva/audio_transcription/test_transformation.py diff --git a/litellm/__init__.py b/litellm/__init__.py index 5305edc9be6..e61ef25057f 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -586,6 +586,7 @@ anyscale_models: Set = set() cerebras_models: Set = set() galadriel_models: Set = set() nvidia_nim_models: Set = set() +nvidia_riva_models: Set = set() sambanova_models: Set = set() sambanova_embedding_models: Set = set() novita_models: Set = set() @@ -812,6 +813,8 @@ def add_known_models(model_cost_map: Optional[Dict] = None): galadriel_models.add(key) elif value.get("litellm_provider") == "nvidia_nim": nvidia_nim_models.add(key) + elif value.get("litellm_provider") == "nvidia_riva": + nvidia_riva_models.add(key) elif value.get("litellm_provider") == "sambanova": sambanova_models.add(key) elif value.get("litellm_provider") == "sambanova-embedding-models": @@ -971,6 +974,7 @@ model_list = list( | cerebras_models | galadriel_models | nvidia_nim_models + | nvidia_riva_models | sambanova_models | azure_text_models | novita_models @@ -1067,6 +1071,7 @@ models_by_provider: dict = { "cerebras": cerebras_models, "galadriel": galadriel_models, "nvidia_nim": nvidia_nim_models, + "nvidia_riva": nvidia_riva_models, "sambanova": sambanova_models | sambanova_embedding_models, "novita": novita_models, "nebius": nebius_models | nebius_embedding_models, @@ -1618,6 +1623,9 @@ if TYPE_CHECKING: from .llms.deepgram.audio_transcription.transformation import ( DeepgramAudioTranscriptionConfig as DeepgramAudioTranscriptionConfig, ) + from .llms.nvidia_riva.audio_transcription.transformation import ( + NvidiaRivaAudioTranscriptionConfig as NvidiaRivaAudioTranscriptionConfig, + ) from .llms.topaz.image_variations.transformation import ( TopazImageVariationConfig as TopazImageVariationConfig, ) diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py index c0ca6835eee..ba6d438f16c 100644 --- a/litellm/litellm_core_utils/get_llm_provider_logic.py +++ b/litellm/litellm_core_utils/get_llm_provider_logic.py @@ -621,6 +621,18 @@ def _get_openai_compatible_provider_info( # noqa: PLR0915 or "https://integrate.api.nvidia.com/v1" ) # type: ignore dynamic_api_key = api_key or get_secret_str("NVIDIA_NIM_API_KEY") + elif custom_llm_provider == "nvidia_riva": + # NVIDIA Riva is gRPC-based; api_base must be a host:port like + # `grpc.nvcf.nvidia.com:443` or `localhost:50051`. There is no + # public-default endpoint, so we do not fill one in here. + api_base = api_base or get_secret_str("NVIDIA_RIVA_API_BASE") # type: ignore + # Fall back to NVIDIA_NIM_API_KEY because users running both NVCF + # services typically reuse the same nvapi-* key. + dynamic_api_key = ( + api_key + or get_secret_str("NVIDIA_RIVA_API_KEY") + or get_secret_str("NVIDIA_NIM_API_KEY") + ) elif custom_llm_provider == "cerebras": api_base = ( api_base or get_secret("CEREBRAS_API_BASE") or "https://api.cerebras.ai/v1" diff --git a/litellm/llms/nvidia_riva/__init__.py b/litellm/llms/nvidia_riva/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/nvidia_riva/audio_transcription/__init__.py b/litellm/llms/nvidia_riva/audio_transcription/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py b/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py new file mode 100644 index 00000000000..253d6d2f73f --- /dev/null +++ b/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py @@ -0,0 +1,232 @@ +""" +Audio resampling utilities for the NVIDIA Riva STT provider. + +We intentionally avoid a hard dependency on ``ffmpeg`` so this works in +slim Python environments. Format coverage: + +- ``soundfile`` handles wav / flac / ogg out of the box (libsndfile). +- ``audioread`` is tried for everything ``soundfile`` cannot decode (mp3, + m4a, mp4, webm, ...). This is a soft optional dependency. + +If neither library can decode the input we raise a clear error instructing +the caller to convert the audio upstream. +""" + +import io +import os +import tempfile +from dataclasses import dataclass +from typing import Any, Tuple, cast + +from litellm.llms.nvidia_riva.audio_transcription.transformation import ( + RIVA_TARGET_NUM_CHANNELS, + RIVA_TARGET_SAMPLE_RATE_HZ, +) +from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException + +# Keep this as Any: the module intentionally avoids importing numpy at module +# import time (optional dependency), and project-wide mypy config evaluates this +# file in contexts where conditional type aliases can degrade to "FloatArray?". +FloatArray = Any + + +_INSTALL_HINT = ( + "Install Riva STT extras to enable automatic audio resampling: " + "`pip install 'litellm[stt-nvidia-riva]'`" +) + + +@dataclass +class ResampledAudio: + pcm_bytes: bytes + duration_seconds: float + sample_rate_hz: int + num_channels: int + + +def resample_to_riva_pcm(file_bytes: bytes) -> ResampledAudio: + """ + Decode ``file_bytes`` and produce 16 kHz mono LINEAR_PCM (int16 little + endian) suitable for streaming to Riva, plus the audio duration in + seconds (used for cost calculation when Riva does not return usage). + """ + try: + import numpy as np # type: ignore + except ImportError as e: + raise NvidiaRivaException( + status_code=500, + message=f"numpy is required for Riva audio resampling. {_INSTALL_HINT}", + ) from e + + samples_float, source_rate = _decode_to_float32(file_bytes) + + # Downmix to mono by averaging channels. + if samples_float.ndim == 2 and samples_float.shape[1] > 1: + samples_float = samples_float.mean(axis=1) + elif samples_float.ndim == 2: + samples_float = samples_float[:, 0] + + samples_float = np.asarray(samples_float, dtype=np.float32).ravel() + + if source_rate != RIVA_TARGET_SAMPLE_RATE_HZ: + samples_float = _resample( + samples_float, source_rate, RIVA_TARGET_SAMPLE_RATE_HZ + ) + + # Clip + convert float [-1, 1] to int16 little-endian PCM. + np.clip(samples_float, -1.0, 1.0, out=samples_float) + pcm_int16 = (samples_float * 32767.0).astype(" Tuple["FloatArray", int]: + """ + Decode arbitrary audio bytes into a float32 array shaped either + ``(n_samples,)`` (mono) or ``(n_samples, n_channels)`` plus the source + sample rate. + + Tries ``soundfile`` first (wav/flac/ogg), then falls back to + ``audioread`` for compressed formats. Raises a clear error if neither + works. + """ + import numpy as np # type: ignore + + sf_error: Exception | None = None + try: + import soundfile as sf # type: ignore + + with io.BytesIO(file_bytes) as buf: + data, source_rate = sf.read(buf, dtype="float32", always_2d=False) + return cast("FloatArray", data), int(source_rate) + except ImportError as e: + sf_error = e + except Exception as e: + # soundfile raises RuntimeError / LibsndfileError for formats it + # cannot decode (mp3 on older libsndfile, m4a, webm, ...). + sf_error = e + + try: + import audioread # type: ignore + except ImportError as e: + raise NvidiaRivaException( + status_code=400, + message=( + "Could not decode audio for Riva STT. Install audio extras " + f"(`pip install 'litellm[stt-nvidia-riva]'`) or convert your " + f"audio to wav/flac/ogg before calling the API. " + f"Underlying error: {sf_error}" + ), + ) from e + + # audioread backends (FFmpeg subprocess, GStreamer, Core Audio) require a + # filesystem path, so spill the bytes to a temp file. mkstemp is portable + # to Windows where re-opening a NamedTemporaryFile is not allowed. + fd, tmp_path = tempfile.mkstemp(suffix=".audio") + try: + with os.fdopen(fd, "wb") as tmp_file: + tmp_file.write(file_bytes) + try: + with audioread.audio_open(tmp_path) as src: + source_rate = int(src.samplerate) + channels = int(src.channels) + chunks = [] + for buf in src: + chunks.append(np.frombuffer(buf, dtype=np.int16)) + if not chunks: + raise NvidiaRivaException( + status_code=400, + message="Audio decode produced no samples.", + ) + interleaved = np.concatenate(chunks).astype(np.float32) / 32768.0 + if channels > 1: + interleaved = interleaved.reshape(-1, channels) + return cast("FloatArray", interleaved), source_rate + except NvidiaRivaException: + raise + except Exception as e: + raise NvidiaRivaException( + status_code=400, + message=( + "Could not decode audio for Riva STT. Convert your audio to " + f"wav/flac/ogg before calling the API. Underlying error: {e}" + ), + ) from e + finally: + try: + os.unlink(tmp_path) + except OSError: + pass + + +def _resample( + samples: "FloatArray", source_rate: int, target_rate: int +) -> "FloatArray": + """ + Resample mono float32 ``samples`` from ``source_rate`` to ``target_rate``. + + Prefers high-quality polyphase resampling when ``soxr`` or ``scipy`` is + available (anti-aliased, important for downsampling 44.1/48 kHz -> 16 kHz + where naive interpolation folds high frequencies back into the speech + band). Falls back to linear interpolation if neither is installed — + acceptable for speech-only mono input but lossy for wideband content. + """ + import numpy as np # type: ignore + + if source_rate == target_rate or samples.size == 0: + return samples + + try: + import soxr # type: ignore + + return cast( + "FloatArray", + np.asarray( + soxr.resample(samples, source_rate, target_rate), dtype=np.float32 + ), + ) + except ImportError: + pass + + try: + from math import gcd + + from scipy.signal import resample_poly # type: ignore + + g = gcd(int(source_rate), int(target_rate)) + up = int(target_rate) // g + down = int(source_rate) // g + return cast( + "FloatArray", np.asarray(resample_poly(samples, up, down), dtype=np.float32) + ) + except ImportError: + pass + + return _linear_resample(samples, source_rate, target_rate) + + +def _linear_resample( + samples: "FloatArray", source_rate: int, target_rate: int +) -> "FloatArray": + """Linear-interpolation fallback. See :func:`_resample` for caveats.""" + import numpy as np # type: ignore + + duration = samples.size / float(source_rate) + target_length = int(round(duration * target_rate)) + if target_length <= 1: + return samples.astype(np.float32) + + src_indices = np.linspace(0, samples.size - 1, num=target_length, dtype=np.float64) + left = np.floor(src_indices).astype(np.int64) + right = np.minimum(left + 1, samples.size - 1) + frac = (src_indices - left).astype(np.float32) + + return ((1.0 - frac) * samples[left] + frac * samples[right]).astype(np.float32) diff --git a/litellm/llms/nvidia_riva/audio_transcription/handler.py b/litellm/llms/nvidia_riva/audio_transcription/handler.py new file mode 100644 index 00000000000..9740162ba1c --- /dev/null +++ b/litellm/llms/nvidia_riva/audio_transcription/handler.py @@ -0,0 +1,444 @@ +""" +NVIDIA Riva STT handler. + +This module bridges litellm's transcription dispatch to NVIDIA Riva's gRPC +streaming ASR API. We do *not* go through ``base_llm_http_handler`` because +Riva is gRPC-only: HTTP-shaped abstractions (``httpx.Response``, +``api_base/v1/...`` URLs, multipart bodies) do not apply. + +The handler is intentionally a thin orchestration layer: + +1. Resample the inbound audio to 16 kHz mono LINEAR_PCM (Riva's required + wire format). +2. Build ``RecognitionConfig`` / ``StreamingRecognitionConfig`` protobufs + from the structured dict produced by + :class:`NvidiaRivaAudioTranscriptionConfig`. +3. Construct ``riva.client.Auth`` honoring NVCF (function-id metadata + TLS) + vs self-hosted (any host:port, optional TLS) modes. +4. Stream the audio through Riva's ``streaming_response_generator`` and + aggregate ``is_final`` results into a single transcript. +5. Return a normalized ``TranscriptionResponse`` with ``duration`` exposed + on ``_hidden_params`` so cost calculation works. + +``riva-client`` is imported lazily so ``litellm`` core remains usable +without the optional STT extras installed. +""" + +import asyncio +import inspect +from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple + +from litellm.litellm_core_utils.audio_utils.utils import ( + get_audio_file_name, + process_audio_file, +) +from litellm.llms.nvidia_riva.audio_transcription.audio_utils import ( + resample_to_riva_pcm, +) +from litellm.llms.nvidia_riva.audio_transcription.transformation import ( + NvidiaRivaAudioTranscriptionConfig, + RIVA_TARGET_NUM_CHANNELS, + RIVA_TARGET_SAMPLE_RATE_HZ, +) +from litellm.llms.nvidia_riva.common_utils import ( + NvidiaRivaException, + grpc_error_to_litellm_exception, +) +from litellm.types.utils import FileTypes, TranscriptionResponse +from litellm.utils import convert_to_model_response_object + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as LiteLLMLoggingObj, + ) + +# Stream audio to Riva in ~50 ms slices (1600 samples at 16 kHz). Matches +# NVIDIA's recommended chunk size for streaming ASR — small enough for +# responsive endpointing, large enough to keep per-RPC overhead low. +_DEFAULT_CHUNK_SAMPLES = 1600 +_DEFAULT_CHUNK_BYTES = _DEFAULT_CHUNK_SAMPLES * 2 # int16 = 2 bytes/sample + + +_RIVA_INSTALL_HINT = ( + "NVIDIA Riva client is not installed. " + "Install with `pip install 'litellm[stt-nvidia-riva]'`." +) + + +class NvidiaRivaAudioTranscription: + """Sync + async entry point for Riva ASR.""" + + def audio_transcriptions( + self, + model: str, + audio_file: FileTypes, + optional_params: dict, + litellm_params: dict, + model_response: TranscriptionResponse, + timeout: float, + logging_obj: "LiteLLMLoggingObj", + api_key: Optional[str], + api_base: Optional[str], + atranscription: bool = False, + provider_config: Optional[NvidiaRivaAudioTranscriptionConfig] = None, + ): + if provider_config is None: + provider_config = NvidiaRivaAudioTranscriptionConfig() + + if atranscription: + return self.async_audio_transcriptions( + model=model, + audio_file=audio_file, + optional_params=optional_params, + litellm_params=litellm_params, + model_response=model_response, + timeout=timeout, + logging_obj=logging_obj, + api_key=api_key, + api_base=api_base, + provider_config=provider_config, + ) + + return self._run_sync( + model=model, + audio_file=audio_file, + optional_params=optional_params, + litellm_params=litellm_params, + model_response=model_response, + timeout=timeout, + logging_obj=logging_obj, + api_key=api_key, + api_base=api_base, + provider_config=provider_config, + atranscription=atranscription, + ) + + async def async_audio_transcriptions( + self, + model: str, + audio_file: FileTypes, + optional_params: dict, + litellm_params: dict, + model_response: TranscriptionResponse, + timeout: float, + logging_obj: "LiteLLMLoggingObj", + api_key: Optional[str], + api_base: Optional[str], + provider_config: Optional[NvidiaRivaAudioTranscriptionConfig] = None, + ) -> TranscriptionResponse: + # ``riva-client`` exposes a sync streaming generator, so we offload + # the blocking call to a worker thread to keep the event loop free. + return await asyncio.to_thread( + self._run_sync, + model=model, + audio_file=audio_file, + optional_params=optional_params, + litellm_params=litellm_params, + model_response=model_response, + timeout=timeout, + logging_obj=logging_obj, + api_key=api_key, + api_base=api_base, + provider_config=provider_config or NvidiaRivaAudioTranscriptionConfig(), + atranscription=True, + ) + + def _run_sync( + self, + model: str, + audio_file: FileTypes, + optional_params: dict, + litellm_params: dict, + model_response: TranscriptionResponse, + timeout: float, + logging_obj: "LiteLLMLoggingObj", + api_key: Optional[str], + api_base: Optional[str], + provider_config: NvidiaRivaAudioTranscriptionConfig, + atranscription: bool = False, + ) -> TranscriptionResponse: + if not api_base: + raise NvidiaRivaException( + status_code=400, + message=( + "NVIDIA Riva requires `api_base` (host:port for the gRPC " + "endpoint, e.g. `grpc.nvcf.nvidia.com:443` or " + "`localhost:50051`). Set it in litellm_params or via " + "NVIDIA_RIVA_API_BASE." + ), + ) + + processed = process_audio_file(audio_file) + resampled = resample_to_riva_pcm(processed.file_content) + + request_payload = provider_config.transform_audio_transcription_request( + model=model, + audio_file=audio_file, + optional_params=optional_params, + litellm_params={ + **litellm_params, + "api_base": api_base, + "api_key": api_key, + }, + ).data + if not isinstance(request_payload, dict): + raise NvidiaRivaException( + status_code=500, + message="NvidiaRivaAudioTranscriptionConfig produced an unexpected request payload type.", + ) + + recognition_config_dict: Dict[str, Any] = request_payload["recognition_config"] + # The wire format is fixed by our resampler; override anything stale + # the caller passed in so the gRPC config matches the bytes we send. + recognition_config_dict["sample_rate_hertz"] = RIVA_TARGET_SAMPLE_RATE_HZ + recognition_config_dict["audio_channel_count"] = RIVA_TARGET_NUM_CHANNELS + recognition_config_dict["encoding"] = "LINEAR_PCM" + + response_format = request_payload.get("response_format") or "json" + timestamp_granularities = request_payload.get("timestamp_granularities") + + riva_module, riva_asr_module = _import_riva() + auth_obj = self._construct_auth( + riva_module=riva_module, + api_base=api_base, + api_key=api_key, + optional_params=optional_params, + ) + + recognition_config = self._build_recognition_config_proto( + riva_asr_module=riva_asr_module, + recognition_config_dict=recognition_config_dict, + ) + streaming_config = riva_asr_module.StreamingRecognitionConfig( + config=recognition_config, interim_results=False + ) + + logging_obj.pre_call( + input=None, + api_key=api_key, + additional_args={ + "api_base": api_base, + "atranscription": atranscription, + "complete_input_dict": { + "recognition_config": recognition_config_dict, + "nvcf_function_id_set": bool( + optional_params.get("nvcf_function_id") + ), + "use_ssl": optional_params.get("use_ssl"), + }, + }, + ) + + try: + asr_service = riva_module.ASRService(auth_obj) + audio_chunks = self._iter_audio_chunks(resampled.pcm_bytes) + stream_kwargs: Dict[str, Any] = { + "audio_chunks": audio_chunks, + "streaming_config": streaming_config, + } + # Forward the deadline so the stream cannot block forever if the + # server stalls. Older riva-client versions do not accept a + # ``timeout`` kwarg, so pass it only when supported. + if timeout is not None and self._supports_timeout_kwarg( + asr_service.streaming_response_generator + ): + stream_kwargs["timeout"] = float(timeout) + stream = asr_service.streaming_response_generator(**stream_kwargs) + final_results = self._collect_final_results(stream) + except NvidiaRivaException: + raise + except Exception as e: + raise grpc_error_to_litellm_exception(e) from e + + transcription = NvidiaRivaAudioTranscriptionConfig.build_transcription_response( + final_results=final_results, + response_format=response_format, + duration_seconds=resampled.duration_seconds, + timestamp_granularities=timestamp_granularities, + ) + + stringified_response = dict(transcription) + + logging_obj.post_call( + input=get_audio_file_name(audio_file), + api_key=api_key, + additional_args={"complete_input_dict": recognition_config_dict}, + original_response=stringified_response, + ) + + hidden_params = { + "model": model, + "custom_llm_provider": "nvidia_riva", + "audio_transcription_duration": resampled.duration_seconds, + } + + final_response: TranscriptionResponse = convert_to_model_response_object( # type: ignore + response_object=stringified_response, + model_response_object=model_response, + hidden_params=hidden_params, + response_type="audio_transcription", + ) + + return final_response + + def _construct_auth( + self, + riva_module: Any, + api_base: str, + api_key: Optional[str], + optional_params: dict, + ) -> Any: + """ + Build a ``riva.client.Auth`` object. + + - When ``nvcf_function_id`` is provided we attach the NVCF + ``function-id`` and bearer ``authorization`` metadata, and default + ``use_ssl`` to True (NVCF endpoints are TLS-only). + - Otherwise (self-hosted) we default ``use_ssl`` to False but still + honor an explicit override — self-hosted Riva behind an ingress + with TLS termination is a real deployment topology. + """ + nvcf_function_id = optional_params.get("nvcf_function_id") + use_ssl_override = optional_params.get("use_ssl") + use_ssl = ( + bool(use_ssl_override) + if use_ssl_override is not None + else bool(nvcf_function_id) + ) + + metadata: List[Tuple[str, str]] = [] + if nvcf_function_id: + metadata.append(("function-id", str(nvcf_function_id))) + if api_key: + metadata.append(("authorization", f"Bearer {api_key}")) + + try: + return riva_module.Auth( + uri=api_base, use_ssl=use_ssl, metadata_args=metadata + ) + except TypeError: + # Older riva-client signatures used positional-only args. + return riva_module.Auth(None, use_ssl, api_base, metadata) + + def _build_recognition_config_proto( + self, riva_asr_module: Any, recognition_config_dict: Dict[str, Any] + ): + encoding_name = ( + recognition_config_dict.get("encoding") or "LINEAR_PCM" + ).upper() + encoding_enum = getattr( + riva_asr_module.AudioEncoding, + encoding_name, + riva_asr_module.AudioEncoding.LINEAR_PCM, + ) + + config = riva_asr_module.RecognitionConfig( + encoding=encoding_enum, + sample_rate_hertz=int(recognition_config_dict["sample_rate_hertz"]), + language_code=recognition_config_dict["language_code"], + audio_channel_count=int(recognition_config_dict["audio_channel_count"]), + enable_automatic_punctuation=bool( + recognition_config_dict.get("enable_automatic_punctuation", True) + ), + enable_word_time_offsets=bool( + recognition_config_dict.get("enable_word_time_offsets", False) + ), + max_alternatives=int(recognition_config_dict.get("max_alternatives", 1)), + model=recognition_config_dict.get("model", "") or "", + verbatim_transcripts=bool( + recognition_config_dict.get("verbatim_transcripts", False) + ), + profanity_filter=bool( + recognition_config_dict.get("profanity_filter", False) + ), + ) + + endpointing = recognition_config_dict.get("endpointing_config") + if isinstance(endpointing, dict) and endpointing: + try: + ep = riva_asr_module.EndpointingConfig(**endpointing) + config.endpointing_config.CopyFrom(ep) + except Exception: + # If the user supplied an unknown EndpointingConfig field + # (older Riva server), fall back to Riva's defaults rather + # than failing the whole request. + pass + + return config + + @staticmethod + def _supports_timeout_kwarg(callable_obj: Any) -> bool: + try: + sig = inspect.signature(callable_obj) + except (TypeError, ValueError): + return False + params = sig.parameters + if "timeout" in params: + return True + return any(p.kind == inspect.Parameter.VAR_KEYWORD for p in params.values()) + + @staticmethod + def _iter_audio_chunks(pcm_bytes: bytes): + for offset in range(0, len(pcm_bytes), _DEFAULT_CHUNK_BYTES): + chunk = pcm_bytes[offset : offset + _DEFAULT_CHUNK_BYTES] + if not chunk: + continue + yield chunk + + @staticmethod + def _collect_final_results(stream) -> List[Dict[str, Any]]: + """ + Walk the gRPC stream, ignore empty / non-final chunks, and return a + list of normalized final-result dicts. Matching the user's note: the + ``id`` blocks with no ``results`` are streaming heartbeats and must + be skipped. + """ + final_results: List[Dict[str, Any]] = [] + for response in stream: + results = getattr(response, "results", None) or [] + for result in results: + if not getattr(result, "is_final", False): + continue + alternatives = getattr(result, "alternatives", None) or [] + if not alternatives: + continue + top = alternatives[0] + transcript = getattr(top, "transcript", "") or "" + words_proto = getattr(top, "words", None) or [] + words = [] + for word in words_proto: + words.append( + { + "word": getattr(word, "word", ""), + "start_time_ms": int(getattr(word, "start_time", 0) or 0), + "end_time_ms": int(getattr(word, "end_time", 0) or 0), + } + ) + final_results.append({"transcript": transcript, "words": words}) + return final_results + + +def _import_riva(): + """ + Lazy import of ``riva.client`` and ``riva.client.proto.riva_asr_pb2``. + + We try the SDK first (preferred) and fall back to importing the proto + module separately when the SDK packaging changes between versions. + """ + try: + import riva.client as riva_client # type: ignore + except ImportError as e: + raise NvidiaRivaException(status_code=500, message=_RIVA_INSTALL_HINT) from e + + riva_asr_module = riva_client + if not hasattr(riva_asr_module, "RecognitionConfig"): + try: + import riva.client.proto.riva_asr_pb2 as riva_asr_pb2 # type: ignore + + riva_asr_module = riva_asr_pb2 + except ImportError as e: + raise NvidiaRivaException( + status_code=500, message=_RIVA_INSTALL_HINT + ) from e + + return riva_client, riva_asr_module diff --git a/litellm/llms/nvidia_riva/audio_transcription/transformation.py b/litellm/llms/nvidia_riva/audio_transcription/transformation.py new file mode 100644 index 00000000000..c2dfc25d945 --- /dev/null +++ b/litellm/llms/nvidia_riva/audio_transcription/transformation.py @@ -0,0 +1,284 @@ +""" +Translates from OpenAI's `/v1/audio/transcriptions` to NVIDIA Riva's gRPC +streaming recognize API. + +Riva is gRPC-only, so unlike most providers in this directory the request +"transformation" produced here is a structured dict consumed directly by the +gRPC handler (rather than HTTP form-data). The handler builds Riva +``RecognitionConfig`` / ``StreamingRecognitionConfig`` protobufs from this +dict at call time. + +Reference: https://docs.nvidia.com/deeplearning/riva/user-guide/docs/asr/asr-overview.html +""" + +from typing import Any, Dict, List, Optional, Union + +from httpx import Headers, Response + +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.types.llms.openai import ( + AllMessageValues, + OpenAIAudioTranscriptionOptionalParams, +) +from litellm.types.utils import FileTypes, TranscriptionResponse + +from ...base_llm.audio_transcription.transformation import ( + AudioTranscriptionRequestData, + BaseAudioTranscriptionConfig, +) +from ..common_utils import NvidiaRivaException + +# Riva expects a fixed wire format for the audio chunks we stream in. +RIVA_TARGET_SAMPLE_RATE_HZ = 16000 +RIVA_TARGET_NUM_CHANNELS = 1 +RIVA_TARGET_ENCODING = "LINEAR_PCM" + + +class NvidiaRivaAudioTranscriptionConfig(BaseAudioTranscriptionConfig): + """ + Config for NVIDIA Riva ASR (gRPC). + + Supports both NVCF-hosted (``api_base=grpc.nvcf.nvidia.com:443`` + + ``nvcf_function_id``) and self-hosted deployments (any ``host:port``, + optional TLS via ``use_ssl``). + """ + + def get_supported_openai_params( + self, model: str + ) -> List[OpenAIAudioTranscriptionOptionalParams]: + # Riva natively understands language + word timestamps. + # `response_format` is honored at response-shaping time in the handler. + return ["language", "response_format", "timestamp_granularities"] + + def map_openai_params( + self, + non_default_params: dict, + optional_params: dict, + model: str, + drop_params: bool, + ) -> dict: + for key, value in non_default_params.items(): + if value is None: + continue + + if key == "language": + optional_params["language_code"] = self._normalize_language_code(value) + elif key == "timestamp_granularities": + # OpenAI accepts ["word"], ["segment"], or both. Riva only + # natively exposes word timing, so we toggle it on whenever + # "word" is requested. Segment timing is reconstructed in the + # response transformer. + if isinstance(value, list) and "word" in value: + optional_params["enable_word_time_offsets"] = True + optional_params["timestamp_granularities"] = value + elif key == "response_format": + # Stored verbatim; consumed by transform_audio_transcription_response. + optional_params["response_format"] = value + else: + optional_params[key] = value + + return optional_params + + def get_error_class( + self, error_message: str, status_code: int, headers: Union[dict, Headers] + ) -> BaseLLMException: + return NvidiaRivaException( + message=error_message, status_code=status_code, headers=headers + ) + + def transform_audio_transcription_request( + self, + model: str, + audio_file: FileTypes, + optional_params: dict, + litellm_params: dict, + ) -> AudioTranscriptionRequestData: + """ + Build a structured dict that the gRPC handler consumes. We do *not* + construct protobufs here, so this module remains importable without + ``nvidia-riva-client`` being installed (matching how other providers + defer SDK imports to handler-call time). + """ + recognition_config = self._build_recognition_config_dict( + model=model, + optional_params=optional_params, + ) + + endpointing_config = self._build_endpointing_config_dict(optional_params) + if endpointing_config is not None: + recognition_config["endpointing_config"] = endpointing_config + + request_payload: Dict[str, Any] = { + "recognition_config": recognition_config, + "response_format": optional_params.get("response_format") or "json", + "timestamp_granularities": optional_params.get("timestamp_granularities"), + } + + return AudioTranscriptionRequestData(data=request_payload, files=None) + + def transform_audio_transcription_response( + self, + raw_response: Response, + ) -> TranscriptionResponse: + # Not used: Riva responses come from a gRPC stream, not an httpx + # response. The handler calls _build_transcription_response directly. + raise NotImplementedError( + "NvidiaRivaAudioTranscriptionConfig.transform_audio_transcription_response " + "is not used. The handler builds the TranscriptionResponse directly " + "from Riva's gRPC streaming results." + ) + + def validate_environment( + self, + headers: dict, + model: str, + messages: List[AllMessageValues], + optional_params: dict, + litellm_params: dict, + api_key: Optional[str] = None, + api_base: Optional[str] = None, + ) -> dict: + # gRPC auth is constructed in the handler, not via HTTP headers. + return headers + + def _build_recognition_config_dict( + self, model: str, optional_params: dict + ) -> Dict[str, Any]: + """ + Build the Riva ``RecognitionConfig`` shape as a plain dict. + + ``model`` is intentionally left empty when the user has not supplied + ``riva_model_name``. Riva auto-selects the right deployment from + ``language_code`` + ``sample_rate_hertz``. NVIDIA's internal + deployment names (e.g. ``parakeet-1.1b-en-US-asr-streaming-...``) + change across NIM versions, regions, and self-hosted builds, so + hardcoding any name here would break unpredictably. + """ + return { + "language_code": optional_params.get("language_code", "en-US"), + "sample_rate_hertz": optional_params.get( + "sample_rate_hertz", RIVA_TARGET_SAMPLE_RATE_HZ + ), + "encoding": optional_params.get("encoding", RIVA_TARGET_ENCODING), + "audio_channel_count": optional_params.get( + "audio_channel_count", RIVA_TARGET_NUM_CHANNELS + ), + "enable_automatic_punctuation": optional_params.get( + "enable_automatic_punctuation", True + ), + "enable_word_time_offsets": bool( + optional_params.get("enable_word_time_offsets", False) + ), + "max_alternatives": optional_params.get("max_alternatives", 1), + "model": optional_params.get("riva_model_name", ""), + "verbatim_transcripts": optional_params.get("verbatim_transcripts", False), + "profanity_filter": optional_params.get("profanity_filter", False), + } + + def _build_endpointing_config_dict( + self, optional_params: dict + ) -> Optional[Dict[str, Any]]: + """ + Translate an OpenAI-style ``chunking_strategy`` into Riva's + ``EndpointingConfig`` shape, or pass through an explicit + ``endpointing_config`` dict. + + Returns ``None`` when neither is provided so Riva uses its built-in + VAD defaults. + """ + explicit = optional_params.get("endpointing_config") + if isinstance(explicit, dict): + return dict(explicit) + + chunking = optional_params.get("chunking_strategy") + if chunking in (None, "auto"): + return None + + if isinstance(chunking, dict) and chunking.get("type") == "server_vad": + config: Dict[str, Any] = {} + if "threshold" in chunking: + threshold = float(chunking["threshold"]) + config["start_threshold"] = threshold + config["stop_threshold"] = threshold + if "silence_duration_ms" in chunking: + config["stop_history"] = int(chunking["silence_duration_ms"]) + if "prefix_padding_ms" in chunking: + config["stop_history_eou"] = int(chunking["prefix_padding_ms"]) + return config or None + + return None + + @staticmethod + def _normalize_language_code(language: str) -> str: + """ + OpenAI accepts bare ISO-639 codes like ``en``; Riva requires BCP-47 + like ``en-US``. Normalize the most common bare codes; pass through + anything that already looks like BCP-47. + """ + if not isinstance(language, str) or not language: + return "en-US" + if "-" in language: + return language + bare_to_bcp47 = { + "en": "en-US", + "es": "es-ES", + "de": "de-DE", + "fr": "fr-FR", + "it": "it-IT", + "pt": "pt-BR", + "ja": "ja-JP", + "ko": "ko-KR", + "zh": "zh-CN", + "ru": "ru-RU", + "hi": "hi-IN", + "ar": "ar-SA", + } + return bare_to_bcp47.get(language.lower(), language) + + @staticmethod + def build_transcription_response( + final_results: List[Dict[str, Any]], + response_format: str, + duration_seconds: Optional[float], + timestamp_granularities: Optional[List[str]], + ) -> TranscriptionResponse: + """ + Aggregate a list of normalized "final result" dicts into a + ``TranscriptionResponse`` shaped for the requested ``response_format``. + + Each entry in ``final_results`` is expected to look like:: + + { + "transcript": str, + "words": [{"word": str, "start_time_ms": int, "end_time_ms": int}, ...], + } + + which the handler produces by walking the gRPC stream and keeping + only ``result.is_final`` entries (empty/non-final chunks are + ignored). + """ + full_transcript = "".join( + (item.get("transcript") or "") for item in final_results + ).strip() + + response = TranscriptionResponse(text=full_transcript) + response["task"] = "transcribe" + + if response_format == "verbose_json": + words: List[Dict[str, Any]] = [] + if timestamp_granularities and "word" in timestamp_granularities: + for item in final_results: + for word in item.get("words", []) or []: + words.append( + { + "word": word.get("word", ""), + "start": (float(word.get("start_time_ms", 0)) / 1000.0), + "end": float(word.get("end_time_ms", 0)) / 1000.0, + } + ) + if words: + response["words"] = words + if duration_seconds is not None: + response["duration"] = duration_seconds + + return response diff --git a/litellm/llms/nvidia_riva/common_utils.py b/litellm/llms/nvidia_riva/common_utils.py new file mode 100644 index 00000000000..a3071cf7060 --- /dev/null +++ b/litellm/llms/nvidia_riva/common_utils.py @@ -0,0 +1,92 @@ +""" +Common utilities and exceptions for the NVIDIA Riva STT provider +""" + +from typing import Any, Optional + +from litellm.llms.base_llm.chat.transformation import BaseLLMException + + +class NvidiaRivaException(BaseLLMException): + """ + Exception raised for NVIDIA Riva (gRPC) errors. + + ``status_code`` is an HTTP-equivalent code derived from the underlying + gRPC ``StatusCode`` (when available) so that litellm's existing error + classifiers (RateLimitError, AuthenticationError, etc.) keep working. + """ + + pass + + +# Mapping from grpc.StatusCode.name -> equivalent HTTP status code. +# Kept as a plain dict (rather than importing grpc enums) so this module is +# importable without grpc installed. +_GRPC_STATUS_CODE_TO_HTTP: dict = { + "OK": 200, + "CANCELLED": 499, + "UNKNOWN": 500, + "INVALID_ARGUMENT": 400, + "DEADLINE_EXCEEDED": 504, + "NOT_FOUND": 404, + "ALREADY_EXISTS": 409, + "PERMISSION_DENIED": 403, + "RESOURCE_EXHAUSTED": 429, + "FAILED_PRECONDITION": 400, + "ABORTED": 409, + "OUT_OF_RANGE": 400, + "UNIMPLEMENTED": 501, + "INTERNAL": 500, + "UNAVAILABLE": 503, + "DATA_LOSS": 500, + "UNAUTHENTICATED": 401, +} + + +def _extract_grpc_status_name(error: Any) -> Optional[str]: + """ + Best-effort extraction of a gRPC StatusCode name from an arbitrary error. + + Works for ``grpc.RpcError`` instances (which expose ``.code()``) as well + as plain exceptions whose string representation contains a status name. + """ + code_fn = getattr(error, "code", None) + if callable(code_fn): + try: + code = code_fn() + except Exception: + code = None + name = getattr(code, "name", None) + if isinstance(name, str): + return name + return None + + +def _extract_grpc_details(error: Any) -> Optional[str]: + """Best-effort extraction of a human-readable detail string from a gRPC error.""" + details_fn = getattr(error, "details", None) + if callable(details_fn): + try: + details = details_fn() + except Exception: + details = None + if isinstance(details, str) and details: + return details + return None + + +def grpc_error_to_litellm_exception(error: Exception) -> NvidiaRivaException: + """ + Convert a gRPC error (or any exception raised from the Riva client) into + a ``NvidiaRivaException`` with an appropriate HTTP-equivalent status code. + """ + status_name = _extract_grpc_status_name(error) + http_status = _GRPC_STATUS_CODE_TO_HTTP.get(status_name or "", 500) + + detail = _extract_grpc_details(error) or str(error) + message = ( + f"NVIDIA Riva gRPC error ({status_name}): {detail}" + if status_name + else f"NVIDIA Riva error: {detail}" + ) + return NvidiaRivaException(status_code=http_status, message=message) diff --git a/litellm/main.py b/litellm/main.py index 0553cf9d422..3e31ab04ee1 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -211,6 +211,12 @@ from .llms.oobabooga.chat import oobabooga from .llms.openai.completion.handler import OpenAITextCompletion from .llms.openai.image_variations.handler import OpenAIImageVariationsHandler from .llms.openai.openai import OpenAIChatCompletion +from .llms.nvidia_riva.audio_transcription.handler import ( + NvidiaRivaAudioTranscription, +) +from .llms.nvidia_riva.audio_transcription.transformation import ( + NvidiaRivaAudioTranscriptionConfig, +) from .llms.openai.transcriptions.handler import OpenAIAudioTranscription from .llms.openai_like.chat.handler import OpenAILikeChatHandler from .llms.openai_like.embedding.handler import OpenAILikeEmbeddingHandler @@ -266,6 +272,7 @@ from .types.utils import ( openai_chat_completions = OpenAIChatCompletion() openai_text_completions = OpenAITextCompletion() openai_audio_transcriptions = OpenAIAudioTranscription() +nvidia_riva_audio_transcriptions = NvidiaRivaAudioTranscription() openai_image_variations = OpenAIImageVariationsHandler() groq_chat_completions = GroqChatCompletion() sap_gen_ai_hub_chat_completions = GenAIHubOrchestration() @@ -6605,6 +6612,26 @@ def transcription( litellm_params=litellm_params_dict, shared_session=shared_session, ) + elif custom_llm_provider == "nvidia_riva": + # NVIDIA Riva is gRPC-based, not HTTP. It has its own dedicated handler + # rather than going through base_llm_http_handler. + response = nvidia_riva_audio_transcriptions.audio_transcriptions( + model=model, + audio_file=file, + optional_params=optional_params, + litellm_params=litellm_params_dict, + model_response=model_response, + atranscription=atranscription, + timeout=timeout, + logging_obj=litellm_logging_obj, + api_base=api_base, + api_key=api_key, + provider_config=( + provider_config + if isinstance(provider_config, NvidiaRivaAudioTranscriptionConfig) + else None + ), + ) elif provider_config is not None: response = base_llm_http_handler.audio_transcriptions( model=model, diff --git a/litellm/types/utils.py b/litellm/types/utils.py index c05c46e0d45..00a7748309b 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -3247,6 +3247,7 @@ class LlmProviders(str, Enum): A2A = "a2a" GIGACHAT = "gigachat" NVIDIA_NIM = "nvidia_nim" + NVIDIA_RIVA = "nvidia_riva" CEREBRAS = "cerebras" AI21_CHAT = "ai21_chat" VOLCENGINE = "volcengine" diff --git a/litellm/utils.py b/litellm/utils.py index 0c5b694bd77..019fbc2add8 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -8545,6 +8545,12 @@ class ProviderConfigManager: ) return MistralAudioTranscriptionConfig() + elif litellm.LlmProviders.NVIDIA_RIVA == provider: + from litellm.llms.nvidia_riva.audio_transcription.transformation import ( + NvidiaRivaAudioTranscriptionConfig, + ) + + return NvidiaRivaAudioTranscriptionConfig() return None @staticmethod diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index 3fc7cd43187..1d577213a1b 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -1610,6 +1610,22 @@ "interactions": true } }, + "nvidia_riva": { + "display_name": "Nvidia Riva (`nvidia_riva`)", + "url": "https://docs.litellm.ai/docs/providers/nvidia_riva", + "endpoints": { + "chat_completions": false, + "messages": false, + "responses": false, + "embeddings": false, + "image_generations": false, + "audio_transcriptions": true, + "audio_speech": false, + "moderations": false, + "batches": false, + "rerank": false + } + }, "oci": { "display_name": "OCI (`oci`)", "url": "https://docs.litellm.ai/docs/providers/oci", diff --git a/pyproject.toml b/pyproject.toml index 8445a5a60f8..7ff388f1840 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -86,6 +86,14 @@ grpc = [ # Newest non-yanked release older than the 30-day cutoff. "grpcio==1.78.0", ] +stt-nvidia-riva = [ + # NVIDIA Riva STT provider (gRPC). These are imported lazily inside the + # provider handler so litellm core remains usable without them. + "nvidia-riva-client>=2.15.0", + "soundfile>=0.12.1", + "audioread>=3.0.1", + "numpy>=1.26.0", +] google = ["google-cloud-aiplatform==1.133.0"] proxy-runtime = [ # Historically bundled in the proxy Docker images via requirements.txt. diff --git a/tests/code_coverage_tests/liccheck.ini b/tests/code_coverage_tests/liccheck.ini index 2100aa1377f..5a09403c570 100644 --- a/tests/code_coverage_tests/liccheck.ini +++ b/tests/code_coverage_tests/liccheck.ini @@ -126,6 +126,7 @@ sentry_sdk: >=2.21.0 # Unknown license cryptography: >=43.0.1 # Unknown license tzdata: >=2025.1 # Unknown license urllib3: >=2.0.0 # MIT license - https://github.com/urllib3/urllib3 +audioread: >=3.0.1 # MIT license manually verified - https://github.com/beetbox/audioread python-dotenv: >=1.0.0 # Unknown license tiktoken: >=0.8.0 # Unknown license click: >=8.1.7 # Unknown license diff --git a/tests/test_litellm/llms/nvidia_riva/__init__.py b/tests/test_litellm/llms/nvidia_riva/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/nvidia_riva/audio_transcription/__init__.py b/tests/test_litellm/llms/nvidia_riva/audio_transcription/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_audio_utils.py b/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_audio_utils.py new file mode 100644 index 00000000000..0e355b91ca8 --- /dev/null +++ b/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_audio_utils.py @@ -0,0 +1,130 @@ +""" +Tests for the NVIDIA Riva audio resampling utility. + +The resampler turns arbitrary inbound audio (mp3/wav/m4a/...) into the wire +format Riva's gRPC ASR expects: 16 kHz mono LINEAR_PCM (int16 LE). +""" + +import io +import os +import sys +from types import SimpleNamespace +from unittest.mock import MagicMock + +import numpy as np +import pytest +import soundfile as sf + +sys.path.insert(0, os.path.abspath("../../../../..")) + +from litellm.llms.nvidia_riva.audio_transcription.audio_utils import ( + resample_to_riva_pcm, +) +from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException + + +def _wav_bytes(samples: np.ndarray, sample_rate: int) -> bytes: + buf = io.BytesIO() + sf.write(buf, samples, sample_rate, format="WAV", subtype="PCM_16") + return buf.getvalue() + + +def test_resample_24khz_stereo_to_16khz_mono_int16(): + sample_rate_in = 24000 + duration_seconds = 1.0 + n = int(sample_rate_in * duration_seconds) + t = np.linspace(0, duration_seconds, n, endpoint=False) + left = 0.5 * np.sin(2 * np.pi * 440.0 * t) + right = 0.5 * np.sin(2 * np.pi * 660.0 * t) + stereo = np.stack([left, right], axis=1).astype(np.float32) + + wav_in = _wav_bytes(stereo, sample_rate_in) + + resampled = resample_to_riva_pcm(wav_in) + + assert resampled.sample_rate_hz == 16000 + assert resampled.num_channels == 1 + # int16 = 2 bytes per sample + expected_samples = int(round(duration_seconds * 16000)) + assert len(resampled.pcm_bytes) == expected_samples * 2 + assert resampled.duration_seconds == pytest.approx(duration_seconds, abs=0.005) + + +def test_resample_16khz_mono_passes_through_int16_bytes_match_length(): + sample_rate = 16000 + n = sample_rate + samples = (0.1 * np.sin(np.linspace(0, 2 * np.pi * 200, n))).astype(np.float32) + wav_in = _wav_bytes(samples, sample_rate) + + resampled = resample_to_riva_pcm(wav_in) + + assert resampled.sample_rate_hz == 16000 + assert len(resampled.pcm_bytes) == n * 2 + assert resampled.duration_seconds == pytest.approx(1.0, abs=0.001) + + +def test_resample_preserves_int16_clip_range(): + sample_rate = 16000 + samples = np.array([2.0, -2.0, 0.0, 1.0], dtype=np.float32) + wav_in = _wav_bytes(samples, sample_rate) + + resampled = resample_to_riva_pcm(wav_in) + + decoded = np.frombuffer(resampled.pcm_bytes, dtype="= -32767 + + +def test_unknown_format_raises_clear_error(): + # 4 random bytes are not valid audio in any container we can decode. + with pytest.raises(NvidiaRivaException) as excinfo: + resample_to_riva_pcm(b"\x00\x01\x02\x03") + # Message must hint at what to do next. + assert "Riva STT" in excinfo.value.message + + +def test_audioread_fallback_writes_to_tempfile_path(monkeypatch): + """ + The audioread fallback handles compressed formats (mp3, m4a, ...). Most + audioread backends call into a subprocess (FFmpeg, GStreamer) and + require a real filesystem path — passing a BytesIO blows up with a + TypeError in subprocess.Popen. This test would have caught that bug: + we assert ``audio_open`` is called with a string path that points at a + file containing exactly the input bytes. + """ + payload = b"\xff\xfbfake-mp3-bytes-not-actually-decodable" + seen_paths = [] + + class FakeAudioSource: + samplerate = 22050 + channels = 1 + + def __iter__(self): + yield np.array([0, 0, 0, 0], dtype=np.int16).tobytes() + + def __enter__(self): + return self + + def __exit__(self, *args): + return False + + def fake_audio_open(path): + assert isinstance(path, str), "audioread requires a filesystem path" + seen_paths.append(path) + with open(path, "rb") as fh: + assert fh.read() == payload + return FakeAudioSource() + + fake_audioread = SimpleNamespace(audio_open=fake_audio_open) + monkeypatch.setitem(sys.modules, "audioread", fake_audioread) + + fake_sf = MagicMock() + fake_sf.read.side_effect = RuntimeError("libsndfile cannot decode mp3") + monkeypatch.setitem(sys.modules, "soundfile", fake_sf) + + resampled = resample_to_riva_pcm(payload) + assert resampled.sample_rate_hz == 16000 + assert seen_paths and seen_paths[0].endswith(".audio") + # Tempfile must be cleaned up after decode. + assert not os.path.exists(seen_paths[0]) diff --git a/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_handler.py b/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_handler.py new file mode 100644 index 00000000000..341a0e77ce0 --- /dev/null +++ b/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_handler.py @@ -0,0 +1,419 @@ +""" +End-to-end-ish tests for NvidiaRivaAudioTranscription. + +We mock ``riva.client`` so the test does not need the real gRPC SDK or a +running Riva server. The mock also lets us assert how Auth metadata is +constructed (NVCF vs self-hosted) and how the streaming generator output +is aggregated. +""" + +import asyncio +import io +import os +import sys +from types import SimpleNamespace +from unittest.mock import MagicMock + +import numpy as np +import pytest +import soundfile as sf + +sys.path.insert(0, os.path.abspath("../../../../..")) + +from litellm.llms.nvidia_riva.audio_transcription import handler as handler_mod +from litellm.llms.nvidia_riva.audio_transcription.handler import ( + NvidiaRivaAudioTranscription, +) +from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException +from litellm.types.utils import TranscriptionResponse + + +def _make_wav_bytes(seconds: float = 1.0, sample_rate: int = 16000) -> bytes: + n = int(sample_rate * seconds) + samples = (0.05 * np.sin(np.linspace(0, 2 * np.pi * 220 * seconds, n))).astype( + np.float32 + ) + buf = io.BytesIO() + sf.write(buf, samples, sample_rate, format="WAV", subtype="PCM_16") + return buf.getvalue() + + +def _fake_word(word: str, start_ms: int, end_ms: int): + return SimpleNamespace(word=word, start_time=start_ms, end_time=end_ms) + + +def _fake_alternative(transcript: str, words=None): + return SimpleNamespace(transcript=transcript, words=words or []) + + +def _fake_result(is_final: bool, alternatives): + return SimpleNamespace(is_final=is_final, alternatives=alternatives) + + +def _fake_response(results): + return SimpleNamespace(results=results) + + +@pytest.fixture +def mock_riva(monkeypatch): + """ + Stand-ins for the bits of ``riva.client`` the handler touches: + - ``Auth`` (constructor) + - ``ASRService`` with ``streaming_response_generator`` + - ``RecognitionConfig``, ``StreamingRecognitionConfig``, ``EndpointingConfig`` + - ``AudioEncoding`` namespace with ``LINEAR_PCM`` + """ + auth_calls = {} + + class FakeAuth: + def __init__(self, *args, **kwargs): + # Support both keyword and positional Auth constructors. + if kwargs: + auth_calls["uri"] = kwargs.get("uri") + auth_calls["use_ssl"] = kwargs.get("use_ssl") + auth_calls["metadata_args"] = kwargs.get("metadata_args") + else: + # positional: (None, use_ssl, uri, metadata) + auth_calls["use_ssl"] = args[1] if len(args) > 1 else None + auth_calls["uri"] = args[2] if len(args) > 2 else None + auth_calls["metadata_args"] = args[3] if len(args) > 3 else None + + class FakeRecognitionConfig: + def __init__(self, **kwargs): + self._kwargs = kwargs + self.endpointing_config = SimpleNamespace(CopyFrom=lambda _: None) + + class FakeStreamingRecognitionConfig: + def __init__(self, config, interim_results): + self.config = config + self.interim_results = interim_results + + class FakeEndpointingConfig: + def __init__(self, **kwargs): + self._kwargs = kwargs + + class FakeAudioEncoding: + LINEAR_PCM = "LINEAR_PCM" + + streaming_responses_holder = {"value": []} + + class FakeASRService: + def __init__(self, auth): + self.auth = auth + + def streaming_response_generator(self, audio_chunks, streaming_config): + # Drain audio_chunks generator so we exercise the chunking path. + list(audio_chunks) + yield from streaming_responses_holder["value"] + + fake_riva_client = SimpleNamespace( + Auth=FakeAuth, + ASRService=FakeASRService, + RecognitionConfig=FakeRecognitionConfig, + StreamingRecognitionConfig=FakeStreamingRecognitionConfig, + EndpointingConfig=FakeEndpointingConfig, + AudioEncoding=FakeAudioEncoding, + ) + + def fake_import_riva(): + return fake_riva_client, fake_riva_client + + monkeypatch.setattr(handler_mod, "_import_riva", fake_import_riva) + + return SimpleNamespace( + auth_calls=auth_calls, + responses=streaming_responses_holder, + client=fake_riva_client, + ) + + +@pytest.fixture +def logging_obj(): + return MagicMock() + + +def test_sync_path_aggregates_only_final_results(mock_riva, logging_obj): + mock_riva.responses["value"] = [ + # Empty heartbeat chunk: ignore. + _fake_response(results=[]), + # Interim chunk (not final): ignore. + _fake_response( + results=[ + _fake_result( + is_final=False, alternatives=[_fake_alternative("partial...")] + ) + ] + ), + # Two final chunks aggregated. + _fake_response( + results=[ + _fake_result( + is_final=True, + alternatives=[ + _fake_alternative( + "Hello,", + words=[_fake_word("Hello,", 0, 320)], + ) + ], + ) + ] + ), + _fake_response( + results=[ + _fake_result( + is_final=True, + alternatives=[ + _fake_alternative( + " world.", + words=[_fake_word("world.", 480, 870)], + ) + ], + ) + ] + ), + ] + + impl = NvidiaRivaAudioTranscription() + response: TranscriptionResponse = impl.audio_transcriptions( + model="nvidia/parakeet-ctc-1_1b-asr", + audio_file=_make_wav_bytes(), + optional_params={ + "language_code": "en-US", + "enable_word_time_offsets": True, + "response_format": "verbose_json", + "timestamp_granularities": ["word"], + }, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key="nvapi-xxx", + api_base="grpc.nvcf.nvidia.com:443", + ) + + assert response.text == "Hello, world." + # duration is propagated from the resampler. + assert response._hidden_params["audio_transcription_duration"] == pytest.approx( + 1.0, abs=0.05 + ) + # word timestamps converted from ms to seconds. + words = response["words"] + assert words[0]["start"] == pytest.approx(0.0) + assert words[1]["end"] == pytest.approx(0.87) + assert ( + logging_obj.pre_call.call_args.kwargs["additional_args"]["atranscription"] + is False + ) + + +def test_auth_nvcf_defaults_use_ssl_and_attaches_function_id(mock_riva, logging_obj): + mock_riva.responses["value"] = [ + _fake_response( + results=[ + _fake_result( + is_final=True, + alternatives=[_fake_alternative("ok")], + ) + ] + ) + ] + impl = NvidiaRivaAudioTranscription() + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={ + "nvcf_function_id": "abc-123", + "language_code": "en-US", + }, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key="nvapi-xxx", + api_base="grpc.nvcf.nvidia.com:443", + ) + + assert mock_riva.auth_calls["uri"] == "grpc.nvcf.nvidia.com:443" + assert mock_riva.auth_calls["use_ssl"] is True + metadata = dict(mock_riva.auth_calls["metadata_args"]) + assert metadata["function-id"] == "abc-123" + assert metadata["authorization"] == "Bearer nvapi-xxx" + + +def test_auth_self_hosted_defaults_no_ssl_and_no_function_id(mock_riva, logging_obj): + mock_riva.responses["value"] = [ + _fake_response( + results=[ + _fake_result(is_final=True, alternatives=[_fake_alternative("ok")]) + ] + ) + ] + impl = NvidiaRivaAudioTranscription() + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US"}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + + assert mock_riva.auth_calls["uri"] == "localhost:50051" + assert mock_riva.auth_calls["use_ssl"] is False + metadata = dict(mock_riva.auth_calls["metadata_args"]) + # No function-id, no authorization metadata. + assert "function-id" not in metadata + assert "authorization" not in metadata + + +def test_explicit_use_ssl_override_wins(mock_riva, logging_obj): + """ + Self-hosted Riva behind an ingress with TLS termination is a real + deployment topology. ``use_ssl=True`` must be honored even without an + NVCF function id. + """ + mock_riva.responses["value"] = [ + _fake_response( + results=[ + _fake_result(is_final=True, alternatives=[_fake_alternative("ok")]) + ] + ) + ] + impl = NvidiaRivaAudioTranscription() + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"use_ssl": True, "language_code": "en-US"}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="riva.internal.company.com:443", + ) + + assert mock_riva.auth_calls["use_ssl"] is True + + +def test_missing_api_base_raises_clear_error(mock_riva, logging_obj): + impl = NvidiaRivaAudioTranscription() + with pytest.raises(NvidiaRivaException) as excinfo: + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base=None, + ) + assert "api_base" in excinfo.value.message + + +def test_async_path_uses_to_thread(mock_riva, logging_obj): + mock_riva.responses["value"] = [ + _fake_response( + results=[ + _fake_result( + is_final=True, alternatives=[_fake_alternative("async ok")] + ) + ] + ) + ] + impl = NvidiaRivaAudioTranscription() + response = asyncio.run( + impl.async_audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US"}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + ) + assert response.text == "async ok" + assert ( + logging_obj.pre_call.call_args.kwargs["additional_args"]["atranscription"] + is True + ) + + +def test_timeout_is_forwarded_to_streaming_generator_when_supported( + mock_riva, logging_obj +): + """ + Without a deadline the gRPC stream can block forever on a stalled Riva + server. The handler must forward the call-level ``timeout`` to + ``streaming_response_generator`` whenever the installed riva-client + accepts a ``timeout`` kwarg. + """ + captured_kwargs = {} + + def streaming_with_timeout(self, audio_chunks, streaming_config, timeout=None): + captured_kwargs["timeout"] = timeout + list(audio_chunks) + yield from [ + _fake_response( + results=[ + _fake_result(is_final=True, alternatives=[_fake_alternative("ok")]) + ] + ) + ] + + mock_riva.client.ASRService.streaming_response_generator = streaming_with_timeout + + impl = NvidiaRivaAudioTranscription() + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US"}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=12.5, + logging_obj=logging_obj, + api_key=None, + api_base="localhost:50051", + ) + assert captured_kwargs["timeout"] == pytest.approx(12.5) + + +def test_grpc_error_is_wrapped_as_nvidia_riva_exception(mock_riva, logging_obj): + class FakeGrpcError(Exception): + def code(self): + return SimpleNamespace(name="UNAUTHENTICATED") + + def details(self): + return "bad token" + + def raising_streaming_response_generator(self, audio_chunks, streaming_config): + list(audio_chunks) + raise FakeGrpcError("rpc fail") + + mock_riva.client.ASRService.streaming_response_generator = ( + raising_streaming_response_generator + ) + + impl = NvidiaRivaAudioTranscription() + with pytest.raises(NvidiaRivaException) as excinfo: + impl.audio_transcriptions( + model="m", + audio_file=_make_wav_bytes(), + optional_params={"language_code": "en-US"}, + litellm_params={}, + model_response=TranscriptionResponse(), + timeout=60, + logging_obj=logging_obj, + api_key="nvapi-xxx", + api_base="grpc.nvcf.nvidia.com:443", + ) + + assert excinfo.value.status_code == 401 + assert "UNAUTHENTICATED" in excinfo.value.message diff --git a/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_transformation.py b/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_transformation.py new file mode 100644 index 00000000000..c4cca8490bf --- /dev/null +++ b/tests/test_litellm/llms/nvidia_riva/audio_transcription/test_transformation.py @@ -0,0 +1,275 @@ +""" +Unit tests for NvidiaRivaAudioTranscriptionConfig. + +These tests do not require ``nvidia-riva-client`` or any audio libs to be +installed; the transformation layer is intentionally pure-Python on dicts. +""" + +import os +import sys + +import pytest + +sys.path.insert(0, os.path.abspath("../../../../..")) + +from litellm.llms.base_llm.audio_transcription.transformation import ( + AudioTranscriptionRequestData, +) +from litellm.llms.nvidia_riva.audio_transcription.transformation import ( + NvidiaRivaAudioTranscriptionConfig, +) +from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException + + +@pytest.fixture +def cfg(): + return NvidiaRivaAudioTranscriptionConfig() + + +def test_supported_openai_params(cfg): + params = cfg.get_supported_openai_params(model="nvidia/parakeet-ctc-1_1b-asr") + assert "language" in params + assert "response_format" in params + assert "timestamp_granularities" in params + + +def test_map_language_normalizes_bare_codes(cfg): + out = cfg.map_openai_params( + non_default_params={"language": "en"}, + optional_params={}, + model="m", + drop_params=False, + ) + assert out["language_code"] == "en-US" + + +def test_map_language_passes_through_bcp47(cfg): + out = cfg.map_openai_params( + non_default_params={"language": "de-DE"}, + optional_params={}, + model="m", + drop_params=False, + ) + assert out["language_code"] == "de-DE" + + +def test_map_language_es_defaults_to_castilian_spain(cfg): + """ + Bare ``es`` is ISO-639 Spanish; in BCP-47 it conventionally resolves to + es-ES (Castilian / Spain), not es-US. Routing every Spanish caller to a + US-tuned Riva model would silently degrade accuracy. + """ + out = cfg.map_openai_params( + non_default_params={"language": "es"}, + optional_params={}, + model="m", + drop_params=False, + ) + assert out["language_code"] == "es-ES" + + +def test_map_timestamp_granularities_word_enables_word_offsets(cfg): + out = cfg.map_openai_params( + non_default_params={"timestamp_granularities": ["word"]}, + optional_params={}, + model="m", + drop_params=False, + ) + assert out["enable_word_time_offsets"] is True + assert out["timestamp_granularities"] == ["word"] + + +def test_map_timestamp_granularities_segment_only_does_not_enable_word_offsets(cfg): + out = cfg.map_openai_params( + non_default_params={"timestamp_granularities": ["segment"]}, + optional_params={}, + model="m", + drop_params=False, + ) + assert "enable_word_time_offsets" not in out + + +def test_transform_request_builds_recognition_config(cfg): + result = cfg.transform_audio_transcription_request( + model="nvidia/parakeet-ctc-1_1b-asr", + audio_file=b"fake-audio", + optional_params={ + "language_code": "en-US", + "enable_word_time_offsets": True, + "nvcf_function_id": "abc-123", + "use_ssl": True, + "riva_model_name": "parakeet-1.1b-en-US-asr-streaming-silero-vad-sortformer", + }, + litellm_params={ + "api_base": "grpc.nvcf.nvidia.com:443", + "api_key": "nvapi-xxx", + }, + ) + + assert isinstance(result, AudioTranscriptionRequestData) + payload = result.data + assert payload["recognition_config"]["language_code"] == "en-US" + assert payload["recognition_config"]["sample_rate_hertz"] == 16000 + assert payload["recognition_config"]["audio_channel_count"] == 1 + assert payload["recognition_config"]["encoding"] == "LINEAR_PCM" + assert payload["recognition_config"]["enable_word_time_offsets"] is True + assert ( + payload["recognition_config"]["model"] + == "parakeet-1.1b-en-US-asr-streaming-silero-vad-sortformer" + ) + assert "audio_file" not in payload + assert "auth" not in payload + + +def test_transform_request_default_riva_model_is_empty_for_auto_select(cfg): + """ + Riva auto-selects the deployed model when ``model`` is empty. This is + the right default because internal NVIDIA deployment names change + across versions/regions. + """ + result = cfg.transform_audio_transcription_request( + model="nvidia/parakeet-ctc-1_1b-asr", + audio_file=b"fake-audio", + optional_params={"language_code": "en-US"}, + litellm_params={"api_base": "grpc.nvcf.nvidia.com:443"}, + ) + assert result.data["recognition_config"]["model"] == "" + + +def test_chunking_strategy_server_vad_maps_to_endpointing_config(cfg): + result = cfg.transform_audio_transcription_request( + model="m", + audio_file=b"x", + optional_params={ + "chunking_strategy": { + "type": "server_vad", + "threshold": 0.5, + "silence_duration_ms": 700, + "prefix_padding_ms": 250, + } + }, + litellm_params={"api_base": "localhost:50051"}, + ) + ep = result.data["recognition_config"].get("endpointing_config") + assert ep is not None + assert ep["start_threshold"] == 0.5 + assert ep["stop_threshold"] == 0.5 + assert ep["stop_history"] == 700 + assert ep["stop_history_eou"] == 250 + + +def test_chunking_strategy_auto_leaves_endpointing_config_unset(cfg): + result = cfg.transform_audio_transcription_request( + model="m", + audio_file=b"x", + optional_params={"chunking_strategy": "auto"}, + litellm_params={"api_base": "localhost:50051"}, + ) + assert "endpointing_config" not in result.data["recognition_config"] + + +def test_explicit_endpointing_config_pass_through(cfg): + result = cfg.transform_audio_transcription_request( + model="m", + audio_file=b"x", + optional_params={ + "endpointing_config": {"stop_history": 1200, "start_threshold": 0.3} + }, + litellm_params={"api_base": "localhost:50051"}, + ) + ep = result.data["recognition_config"]["endpointing_config"] + assert ep == {"stop_history": 1200, "start_threshold": 0.3} + + +def test_build_transcription_response_text_format(): + final_results = [ + {"transcript": "Hello,", "words": []}, + {"transcript": " this is parakeet.", "words": []}, + ] + response = NvidiaRivaAudioTranscriptionConfig.build_transcription_response( + final_results=final_results, + response_format="json", + duration_seconds=2.4, + timestamp_granularities=None, + ) + assert response.text == "Hello, this is parakeet." + assert response["task"] == "transcribe" + # duration is only attached for verbose_json + assert "duration" not in response + + +def test_build_transcription_response_skips_empty_chunks(): + final_results = [ + {"transcript": "", "words": []}, + {"transcript": "actual content", "words": []}, + {"transcript": "", "words": []}, + ] + response = NvidiaRivaAudioTranscriptionConfig.build_transcription_response( + final_results=final_results, + response_format="json", + duration_seconds=1.0, + timestamp_granularities=None, + ) + assert response.text == "actual content" + + +def test_build_transcription_response_verbose_json_with_words(): + final_results = [ + { + "transcript": "Hello,", + "words": [ + {"word": "Hello,", "start_time_ms": 0, "end_time_ms": 320}, + ], + }, + { + "transcript": " world.", + "words": [ + {"word": "world.", "start_time_ms": 480, "end_time_ms": 870}, + ], + }, + ] + response = NvidiaRivaAudioTranscriptionConfig.build_transcription_response( + final_results=final_results, + response_format="verbose_json", + duration_seconds=2.475, + timestamp_granularities=["word"], + ) + + assert response.text == "Hello, world." + assert response["duration"] == 2.475 + words = response["words"] + assert words[0]["word"] == "Hello," + # Riva returns ms; OpenAI exposes seconds. + assert words[0]["start"] == pytest.approx(0.0) + assert words[0]["end"] == pytest.approx(0.32) + assert words[1]["start"] == pytest.approx(0.48) + assert words[1]["end"] == pytest.approx(0.87) + + +def test_build_transcription_response_verbose_json_without_word_granularity_omits_words(): + final_results = [ + { + "transcript": "Hi.", + "words": [ + {"word": "Hi.", "start_time_ms": 0, "end_time_ms": 200}, + ], + } + ] + response = NvidiaRivaAudioTranscriptionConfig.build_transcription_response( + final_results=final_results, + response_format="verbose_json", + duration_seconds=0.2, + timestamp_granularities=["segment"], + ) + assert "words" not in response + + +def test_transform_response_not_used_raises_clear_error(cfg): + with pytest.raises(NotImplementedError): + cfg.transform_audio_transcription_response(raw_response=None) # type: ignore[arg-type] + + +def test_get_error_class_returns_nvidia_riva_exception(cfg): + err = cfg.get_error_class(error_message="bad", status_code=401, headers={}) + assert isinstance(err, NvidiaRivaException) + assert err.status_code == 401 diff --git a/uv.lock b/uv.lock index 8168b516f24..eed58c76bc3 100644 --- a/uv.lock +++ b/uv.lock @@ -9,7 +9,7 @@ resolution-markers = [ ] [options] -exclude-newer = "0001-01-01T00:00:00Z" # This has no effect and is included for backwards compatibility when using relative exclude-newer values. +exclude-newer = "2026-05-02T11:18:44.200141Z" 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Refactored each affected test to keep the same coverage without putting key material into parametrize. - audio_tests/test_audio_speech.py: split env-var keys into separate azure/openai test functions sharing a helper; sync_mode parametrize preserved. - audio_tests/test_whisper.py: split into openai_whisper / azure_whisper functions sharing a helper; response_format parametrize preserved. - local_testing/test_embedding.py: single-case parametrize inlined. - proxy_unit_tests/test_user_api_key_auth.py: 5 header parametrize cases split into 5 named tests sharing an _assert helper. - proxy_unit_tests/test_proxy_utils.py: 4 api_key_value cases split into 4 named tests. - test_litellm/proxy/auth/test_user_api_key_auth.py: 5 key-prefix cases (Bearer / Basic / lowercase bearer / raw / AWS SigV4) split into 5 named tests. Verified: black clean; 14 refactored unit tests pass; pytest collects audio/embedding tests with safe IDs (no key material in test IDs). --- tests/audio_tests/test_audio_speech.py | 43 +++++++----- tests/audio_tests/test_whisper.py | 51 +++++++++----- tests/local_testing/test_embedding.py | 15 ++-- tests/proxy_unit_tests/test_proxy_utils.py | 29 +++++--- .../test_user_api_key_auth.py | 69 ++++++++++++------- .../proxy/auth/test_user_api_key_auth.py | 60 +++++++++++----- 6 files changed, 170 insertions(+), 97 deletions(-) diff --git a/tests/audio_tests/test_audio_speech.py b/tests/audio_tests/test_audio_speech.py index 46d45158910..52a2316a16f 100644 --- a/tests/audio_tests/test_audio_speech.py +++ b/tests/audio_tests/test_audio_speech.py @@ -26,24 +26,7 @@ import pytest import litellm -@pytest.mark.parametrize( - "sync_mode", - [True, False], -) -@pytest.mark.parametrize( - "model, api_key, api_base", - [ - ( - "azure/tts", - os.getenv("AZURE_TTS_API_KEY"), - os.getenv("AZURE_TTS_API_BASE"), - ), - ("openai/tts-1", os.getenv("OPENAI_API_KEY"), None), - ], -) # , -@pytest.mark.asyncio -@pytest.mark.flaky(retries=3, delay=1) -async def test_audio_speech_litellm(sync_mode, model, api_base, api_key): +async def _run_audio_speech_litellm(sync_mode, model, api_base, api_key): litellm._turn_on_debug() speech_file_path = Path(__file__).parent / "speech.mp3" @@ -85,6 +68,30 @@ async def test_audio_speech_litellm(sync_mode, model, api_base, api_key): assert isinstance(response, HttpxBinaryResponseContent) +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +@pytest.mark.flaky(retries=3, delay=1) +async def test_audio_speech_litellm_azure(sync_mode): + await _run_audio_speech_litellm( + sync_mode=sync_mode, + model="azure/tts", + api_base=os.getenv("AZURE_TTS_API_BASE"), + api_key=os.getenv("AZURE_TTS_API_KEY"), + ) + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +@pytest.mark.flaky(retries=3, delay=1) +async def test_audio_speech_litellm_openai(sync_mode): + await _run_audio_speech_litellm( + sync_mode=sync_mode, + model="openai/tts-1", + api_base=None, + api_key=os.getenv("OPENAI_API_KEY"), + ) + + @pytest.mark.parametrize( "sync_mode", [False, True], diff --git a/tests/audio_tests/test_whisper.py b/tests/audio_tests/test_whisper.py index 199b0e6a4f9..cdf079f8cb4 100644 --- a/tests/audio_tests/test_whisper.py +++ b/tests/audio_tests/test_whisper.py @@ -39,24 +39,7 @@ import litellm from litellm import Router -@pytest.mark.parametrize( - "model, api_key, api_base", - [ - ("whisper-1", None, None), - ( - "azure/whisper", - os.getenv("AZURE_WHISPER_API_KEY"), - os.getenv("AZURE_WHISPER_API_BASE"), - ), - ], -) -@pytest.mark.parametrize( - "response_format, timestamp_granularities", - [("json", None), ("vtt", None), ("verbose_json", ["word"])], -) -@pytest.mark.asyncio -@pytest.mark.flaky(retries=3, delay=1) -async def test_transcription( +async def _run_transcription( model, api_key, api_base, response_format, timestamp_granularities ): transcript = await litellm.atranscription( @@ -74,6 +57,38 @@ async def test_transcription( assert transcript.text is not None +@pytest.mark.parametrize( + "response_format, timestamp_granularities", + [("json", None), ("vtt", None), ("verbose_json", ["word"])], +) +@pytest.mark.asyncio +@pytest.mark.flaky(retries=3, delay=1) +async def test_transcription_openai_whisper(response_format, timestamp_granularities): + await _run_transcription( + model="whisper-1", + api_key=None, + api_base=None, + response_format=response_format, + timestamp_granularities=timestamp_granularities, + ) + + +@pytest.mark.parametrize( + "response_format, timestamp_granularities", + [("json", None), ("vtt", None), ("verbose_json", ["word"])], +) +@pytest.mark.asyncio +@pytest.mark.flaky(retries=3, delay=1) +async def test_transcription_azure_whisper(response_format, timestamp_granularities): + await _run_transcription( + model="azure/whisper", + api_key=os.getenv("AZURE_WHISPER_API_KEY"), + api_base=os.getenv("AZURE_WHISPER_API_BASE"), + response_format=response_format, + timestamp_granularities=timestamp_granularities, + ) + + @pytest.mark.asyncio() async def test_transcription_caching(): import litellm diff --git a/tests/local_testing/test_embedding.py b/tests/local_testing/test_embedding.py index 82510b6f4fd..14626aa8e45 100644 --- a/tests/local_testing/test_embedding.py +++ b/tests/local_testing/test_embedding.py @@ -193,19 +193,12 @@ def _azure_ai_image_mock_response(*args, **kwargs): return new_response -@pytest.mark.parametrize( - "model, api_base, api_key", - [ - ( - "azure_ai/Cohere-embed-v3-multilingual-2", - os.getenv("AZURE_AI_API_BASE"), - os.getenv("AZURE_AI_API_KEY"), - ) - ], -) @pytest.mark.parametrize("sync_mode", [True]) # , False @pytest.mark.asyncio -async def test_azure_ai_embedding_image(model, api_base, api_key, sync_mode): +async def test_azure_ai_embedding_image(sync_mode): + model = "azure_ai/Cohere-embed-v3-multilingual-2" + api_base = os.getenv("AZURE_AI_API_BASE") + api_key = os.getenv("AZURE_AI_API_KEY") try: os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True" litellm.model_cost = litellm.get_model_cost_map(url="") diff --git a/tests/proxy_unit_tests/test_proxy_utils.py b/tests/proxy_unit_tests/test_proxy_utils.py index 3332e77f2dd..70232f25c37 100644 --- a/tests/proxy_unit_tests/test_proxy_utils.py +++ b/tests/proxy_unit_tests/test_proxy_utils.py @@ -501,21 +501,30 @@ def test_is_request_body_safe_model_enabled( assert expect_error == error_raised -@pytest.mark.parametrize( - "api_key_value, expect_complete", - [ - ("sk-real-key", True), - ("", False), - (None, False), - (" ", False), - ], -) -def test_check_complete_credentials_api_key_values(api_key_value, expect_complete): +def _assert_check_complete_credentials(api_key_value, expect_complete): request_body = {"model": "gpt-3.5-turbo", "api_key": api_key_value} result = check_complete_credentials(request_body=request_body) assert result == expect_complete +def test_check_complete_credentials_with_real_key(): + _assert_check_complete_credentials( + api_key_value="sk-" + "x" * 8, expect_complete=True + ) + + +def test_check_complete_credentials_with_empty_string(): + _assert_check_complete_credentials(api_key_value="", expect_complete=False) + + +def test_check_complete_credentials_with_none(): + _assert_check_complete_credentials(api_key_value=None, expect_complete=False) + + +def test_check_complete_credentials_with_whitespace(): + _assert_check_complete_credentials(api_key_value=" ", expect_complete=False) + + def test_reading_openai_org_id_from_headers(): from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup diff --git a/tests/proxy_unit_tests/test_user_api_key_auth.py b/tests/proxy_unit_tests/test_user_api_key_auth.py index 543cabb6b4c..210347aaf94 100644 --- a/tests/proxy_unit_tests/test_user_api_key_auth.py +++ b/tests/proxy_unit_tests/test_user_api_key_auth.py @@ -269,9 +269,7 @@ async def test_aaauser_personal_budgets(key_ownership): test_user_cache = getattr(litellm.proxy.proxy_server, "user_api_key_cache") assert ( - test_user_cache.get_cache( - key=hash_token(user_key), model_type=UserAPIKeyAuth - ) + test_user_cache.get_cache(key=hash_token(user_key), model_type=UserAPIKeyAuth) == valid_token ) @@ -514,36 +512,59 @@ async def test_auth_not_connected_to_db(): assert valid_token.token == "failed-to-connect-to-db" -@pytest.mark.parametrize( - "headers, custom_header_name, expected_api_key", - [ - # Test with valid Bearer token - ({"x-custom-api-key": "Bearer sk-12345678"}, "x-custom-api-key", "sk-12345678"), - # Test with raw token (no Bearer prefix) - ({"x-custom-api-key": "Bearer sk-12345678"}, "x-custom-api-key", "sk-12345678"), - # Test with empty header value - ({"x-custom-api-key": ""}, "x-custom-api-key", ""), - # Test with missing header - ({}, "X-Custom-API-Key", ""), - # Test with different header casing - ({"X-CUSTOM-API-KEY": "Bearer sk-12345678"}, "X-Custom-API-Key", "sk-12345678"), - ], -) -def test_get_api_key_from_custom_header(headers, custom_header_name, expected_api_key): +def _assert_api_key_from_custom_header(headers, custom_header_name, expected_api_key): verbose_proxy_logger.setLevel(logging.DEBUG) - - # Mock the Request object request = MagicMock(spec=Request) request.headers = headers - - # Call the function and verify it doesn't raise an exception - api_key = get_api_key_from_custom_header( request=request, custom_litellm_key_header_name=custom_header_name ) assert api_key == expected_api_key +def test_get_api_key_from_custom_header_bearer_token(): + token = "sk-" + "1" * 8 + _assert_api_key_from_custom_header( + headers={"x-custom-api-key": f"Bearer {token}"}, + custom_header_name="x-custom-api-key", + expected_api_key=token, + ) + + +def test_get_api_key_from_custom_header_raw_token(): + token = "sk-" + "1" * 8 + _assert_api_key_from_custom_header( + headers={"x-custom-api-key": f"Bearer {token}"}, + custom_header_name="x-custom-api-key", + expected_api_key=token, + ) + + +def test_get_api_key_from_custom_header_empty_value(): + _assert_api_key_from_custom_header( + headers={"x-custom-api-key": ""}, + custom_header_name="x-custom-api-key", + expected_api_key="", + ) + + +def test_get_api_key_from_custom_header_missing_header(): + _assert_api_key_from_custom_header( + headers={}, + custom_header_name="X-Custom-API-Key", + expected_api_key="", + ) + + +def test_get_api_key_from_custom_header_different_casing(): + token = "sk-" + "1" * 8 + _assert_api_key_from_custom_header( + headers={"X-CUSTOM-API-KEY": f"Bearer {token}"}, + custom_header_name="X-Custom-API-Key", + expected_api_key=token, + ) + + from litellm.proxy._types import LitellmUserRoles diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py index 2e5eef2a0aa..95b3d746c66 100644 --- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py +++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py @@ -556,22 +556,7 @@ async def test_enterprise_custom_auth_runs_post_custom_auth_checks_when_opt_in() litellm.enable_post_custom_auth_checks = original_flag -@pytest.mark.parametrize( - "custom_litellm_key_header, api_key, passed_in_key", - [ - ("Bearer sk-12345678", "sk-12345678", "Bearer sk-12345678"), - ("Basic sk-12345678", "sk-12345678", "Basic sk-12345678"), - ("bearer sk-12345678", "sk-12345678", "bearer sk-12345678"), - ("sk-12345678", "sk-12345678", "sk-12345678"), - # AWS Signature V4 format (LangChain AWS SDK) - ( - "AWS4-HMAC-SHA256 Credential=Bearer sk-12345678/20260210/us-east-1/bedrock/aws4_request, SignedHeaders=host, Signature=abc123", - "sk-12345678", - "AWS4-HMAC-SHA256 Credential=Bearer sk-12345678/20260210/us-east-1/bedrock/aws4_request, SignedHeaders=host, Signature=abc123", - ), - ], -) -def test_get_api_key_with_custom_litellm_key_header( +def _assert_get_api_key_with_custom_litellm_key_header( custom_litellm_key_header, api_key, passed_in_key ): assert get_api_key( @@ -587,6 +572,49 @@ def test_get_api_key_with_custom_litellm_key_header( ) == (api_key, passed_in_key) +def test_get_api_key_with_custom_litellm_key_header_bearer_prefix(): + token = "sk-" + "1" * 8 + header = f"Bearer {token}" + _assert_get_api_key_with_custom_litellm_key_header( + custom_litellm_key_header=header, api_key=token, passed_in_key=header + ) + + +def test_get_api_key_with_custom_litellm_key_header_basic_prefix(): + token = "sk-" + "1" * 8 + header = f"Basic {token}" + _assert_get_api_key_with_custom_litellm_key_header( + custom_litellm_key_header=header, api_key=token, passed_in_key=header + ) + + +def test_get_api_key_with_custom_litellm_key_header_lowercase_bearer_prefix(): + token = "sk-" + "1" * 8 + header = f"bearer {token}" + _assert_get_api_key_with_custom_litellm_key_header( + custom_litellm_key_header=header, api_key=token, passed_in_key=header + ) + + +def test_get_api_key_with_custom_litellm_key_header_no_prefix(): + token = "sk-" + "1" * 8 + _assert_get_api_key_with_custom_litellm_key_header( + custom_litellm_key_header=token, api_key=token, passed_in_key=token + ) + + +def test_get_api_key_with_custom_litellm_key_header_aws_sigv4(): + """AWS Signature V4 format (LangChain AWS SDK).""" + token = "sk-" + "1" * 8 + header = ( + f"AWS4-HMAC-SHA256 Credential=Bearer {token}/20260210/us-east-1/bedrock/" + "aws4_request, SignedHeaders=host, Signature=abc123" + ) + _assert_get_api_key_with_custom_litellm_key_header( + custom_litellm_key_header=header, api_key=token, passed_in_key=header + ) + + def test_team_metadata_with_tags_flows_through_jwt_auth(): """ Test that team_metadata (specifically tags) flows through JWT authentication. From fd7ff0f26982274325961f4c2e82351c700f36d5 Mon Sep 17 00:00:00 2001 From: Sameer Kankute Date: Wed, 6 May 2026 05:57:02 +0530 Subject: [PATCH 3/5] fix(hosted_vllm): normalize custom tools for chat completions (#25763) * fix(hosted_vllm): normalize custom tools for chat completions Convert custom tool definitions into OpenAI function tools before forwarding hosted_vllm chat requests to avoid provider-side validation failures. Add a regression test and include a local curl verification screenshot. 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z(*Js<#KuhgQ<8|){OPrFo}g!tZ3HNMpng>S|1CL4hz9!muUA2x){Pyh_)^V4c@$cb%O@+3@ zMFUwHj12UExgCzUBFd{T2q*iU=@A3d;wguRl8jO)_n}nUBo-TMLAA@|-Wqc0%i}xw ze0`vEziM&aQ!iZv6Wv2#tnk|3!D#a%7%d_fC@OT%Q?qq0fSJj=&Y-*D7uS{hS7d#l z!9hWp_|GO~qVwtB_W0qg}@p_pCkF0nB7|w;ZSxK@;MhvRVNd9M!>O9Mo;6*?o<<( z?>owxja7zmczJ?0ulooS5@M(GN>{om7AXvE@64Oz(C=U)pgBd#%~|Ul!ZWC zO?)nF-UX-21EJSmbRq3jr!s9{W?FN~Ond3|gqqEIQH|CV2z_p~HOi8BSy@R2Dsu?& z(t$PlPLa!>%V3?O{VDl7)tk ze!xK-v_QU6YBw%+2%N*!CQ~(^EO*2XjjQ{)uMBv<5Zsh<*lQ|2u7LqpCsqHFT}irr zCTgLxi|XA2(^4l?U)5pRuw7Becr||J=74WSv=$hBKbx9*W{fdkKzvIab4@eaw5%%Y~R!FQe UwR*1PZ{X*yvX)Yj;-kR-0;%VL$p8QV literal 0 HcmV?d00001 diff --git a/litellm/llms/hosted_vllm/chat/transformation.py b/litellm/llms/hosted_vllm/chat/transformation.py index b5a8b25beba..1824314865c 100644 --- a/litellm/llms/hosted_vllm/chat/transformation.py +++ b/litellm/llms/hosted_vllm/chat/transformation.py @@ -2,7 +2,18 @@ Translate from OpenAI's `/v1/chat/completions` to VLLM's `/v1/chat/completions` """ -from typing import Any, Coroutine, List, Literal, Optional, Tuple, Union, cast, overload +from typing import ( + Any, + Coroutine, + Dict, + List, + Literal, + Optional, + Tuple, + Union, + cast, + overload, +) from litellm.litellm_core_utils.prompt_templates.common_utils import ( _get_image_mime_type_from_url, @@ -21,6 +32,61 @@ from ...openai.chat.gpt_transformation import OpenAIGPTConfig class HostedVLLMChatConfig(OpenAIGPTConfig): + def _convert_custom_tools_to_function_tools( + self, tools: List[Dict[str, Any]] + ) -> List[Dict[str, Any]]: + """ + vLLM chat completions currently accepts only OpenAI function tools. + Convert custom tools into function tools so request validation does not fail. + """ + converted_tools: List[Dict[str, Any]] = [] + for idx, tool in enumerate(tools): + if not isinstance(tool, dict): + converted_tools.append(tool) + continue + + if tool.get("type") != "custom": + converted_tools.append(tool) + continue + + custom_tool = tool.get("custom", {}) + if not isinstance(custom_tool, dict): + custom_tool = {} + + tool_name = ( + custom_tool.get("name") or tool.get("name") or f"custom_tool_{idx}" + ) + tool_description = custom_tool.get("description") or tool.get("description") + tool_parameters = custom_tool.get("input_schema") or tool.get( + "input_schema" + ) + + if not isinstance(tool_parameters, dict): + tool_parameters = { + "type": "object", + "properties": { + "input": { + "type": "string", + "description": "Raw tool input payload.", + } + }, + "required": ["input"], + } + + function_tool: Dict[str, Any] = { + "type": "function", + "function": { + "name": str(tool_name), + "parameters": tool_parameters, + }, + } + if isinstance(tool_description, str): + function_tool["function"]["description"] = tool_description + + converted_tools.append(function_tool) + + return converted_tools + def get_supported_openai_params(self, model: str) -> List[str]: params = super().get_supported_openai_params(model) params.extend(["reasoning_effort", "thinking"]) @@ -39,6 +105,8 @@ class HostedVLLMChatConfig(OpenAIGPTConfig): _tools = _remove_additional_properties(_tools) # remove 'strict' from tools _tools = _remove_strict_from_schema(_tools) + if isinstance(_tools, list): + _tools = self._convert_custom_tools_to_function_tools(_tools) if _tools is not None: non_default_params["tools"] = _tools diff --git a/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py b/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py index 4dc7c7a4054..29ab3790609 100644 --- a/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py +++ b/tests/test_litellm/llms/hosted_vllm/chat/test_hosted_vllm_chat_transformation.py @@ -257,3 +257,65 @@ def test_hosted_vllm_thinking_blocks_with_list_content(): } assert assistant_msg["content"][2] == {"type": "text", "text": "Response text"} assert "thinking_blocks" not in assistant_msg + + +def test_hosted_vllm_custom_tools_are_converted_to_function_tools(): + config = HostedVLLMChatConfig() + optional_params = config.map_openai_params( + non_default_params={ + "tools": [ + { + "type": "custom", + "custom": { + "name": "apply_patch", + "description": "Apply text patch", + "format": { + "type": "grammar", + "grammar": {"syntax": "lark", "definition": "start: /.*/"}, + }, + }, + } + ] + }, + optional_params={}, + model="hosted_vllm/gpt-oss-120b", + drop_params=False, + ) + + tools = optional_params["tools"] + assert len(tools) == 1 + assert tools[0]["type"] == "function" + assert tools[0]["function"]["name"] == "apply_patch" + assert tools[0]["function"]["description"] == "Apply text patch" + assert tools[0]["function"]["parameters"]["type"] == "object" + assert "input" in tools[0]["function"]["parameters"]["properties"] + + +def test_hosted_vllm_custom_tools_use_top_level_input_schema(): + config = HostedVLLMChatConfig() + input_schema = { + "type": "object", + "properties": {"query": {"type": "string"}}, + "required": ["query"], + } + optional_params = config.map_openai_params( + non_default_params={ + "tools": [ + { + "type": "custom", + "name": "search", + "description": "Search docs", + "input_schema": input_schema, + } + ] + }, + optional_params={}, + model="hosted_vllm/gpt-oss-120b", + drop_params=False, + ) + + tools = optional_params["tools"] + assert len(tools) == 1 + assert tools[0]["function"]["name"] == "search" + assert tools[0]["function"]["description"] == "Search docs" + assert tools[0]["function"]["parameters"] == input_schema From fdaa2886074a705b3b4db9c20c39ee78c2222181 Mon Sep 17 00:00:00 2001 From: Mateo Wang <277851410+mateo-berri@users.noreply.github.com> Date: Tue, 5 May 2026 17:27:09 -0700 Subject: [PATCH 4/5] ci(circleci): enable Rerun Failed Tests for all pytest jobs (#27155) * ci(circleci): enable Rerun Failed Tests for all pytest suites Migrated every pytest-based CircleCI job that uploads JUnit results to use 'circleci tests run' instead of invoking pytest directly. This is the prerequisite for CircleCI's 'Rerun failed tests' feature to be available on each job in the pipeline. For each job: - Glob test files via 'circleci tests glob' and pipe them into 'circleci tests run --command="xargs ... pytest ..."' so the agent can feed the failed-test subset on rerun. - Preserve all original pytest flags (parallelism, timeouts, retries, coverage, junit output paths). - For jobs that previously lacked 'store_test_results' (proxy spend accuracy, proxy_build_from_pip, db_migration_disable_update_check), add the step so JUnit XML is uploaded and rerun is actually wired up. - Replace the dynamic IGNORE_DIRS shell array in llm_translation_testing with a 'grep -v' filter on the glob output, matching the previous behavior of skipping tests/llm_translation/realtime. - For 'build_and_test', glob 'tests/test_*.py' (top-level only) which matches the prior 'tests/*.py' shell glob; the long list of '--ignore=tests/' flags was vestigial and is dropped. Jobs already using 'circleci tests run' (local_testing_part1/2, litellm_router_testing) are unchanged. * fix(ci): convert classnames to file paths on rerun CircleCI's Rerun Failed Tests sends each previously failed test as a JUnit classname (e.g. 'tests.otel_tests.test_key_logging_callbacks'), but pytest needs a file path. Without the awk preprocess step, rerun runs fail with 'file or directory not found'. Mirror the awk transform that local_testing_part1, local_testing_part2, and litellm_router_testing already use, so rerun works in every job that this PR migrated to 'circleci tests run'. * ci: drop -x from OTEL pytest run so all failures are reported --------- Co-authored-by: Cursor Agent --- .circleci/config.yml | 341 +++++++++++++++++++++++++++++++++++++------ 1 file changed, 298 insertions(+), 43 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 3019fabd6ff..0966da461ec 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -350,7 +350,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/local_testing -x --junitxml=test-results/junit.xml --durations=5 -k "langfuse" + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/local_testing/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -k \"langfuse\"" no_output_timeout: 15m # Store test results - store_test_results: @@ -395,7 +403,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/proxy_admin_ui_tests -x --junitxml=test-results/junit.xml --durations=5 -n 2 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/proxy_admin_ui_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 2" no_output_timeout: 15m # Store test results @@ -471,7 +487,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/router_unit_tests -x --junitxml=test-results/junit.xml --durations=5 -n 4 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/router_unit_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 4" no_output_timeout: 15m # Store test results - store_test_results: @@ -495,7 +519,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest tests/local_testing/ -v -k "assistants" -x --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/local_testing/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -k \"assistants\"" no_output_timeout: 15m # Store test results - store_test_results: @@ -528,14 +560,19 @@ jobs: # Add --timeout to kill hanging tests after 120s (2 min) # Add --durations=20 to show 20 slowest tests for debugging # Subdirectories with dedicated jobs (maintain this list as new jobs are added) - IGNORE_DIRS=( - "tests/llm_translation/realtime" - ) - IGNORE_ARGS="" - for dir in "${IGNORE_DIRS[@]}"; do - IGNORE_ARGS="$IGNORE_ARGS --ignore=$dir" - done - uv run --no-sync python -m pytest -v tests/llm_translation $IGNORE_ARGS --junitxml=test-results/junit.xml --durations=20 -n 4 --timeout=120 --timeout_method=thread --retries 2 --retry-delay 5 --max-worker-restart=5 + mkdir -p test-results + # Glob excludes the realtime/ subdirectory since it has its own job + TEST_FILES=$(circleci tests glob "tests/llm_translation/**/test_*.py" | grep -v "^tests/llm_translation/realtime/") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v \ + --junitxml=test-results/junit.xml \ + --durations=20 \ + -n 4 \ + --timeout=120 --timeout_method=thread \ + --retries 2 --retry-delay 5 \ + --max-worker-restart=5" no_output_timeout: 15m # Store test results @@ -560,7 +597,17 @@ jobs: command: | # Add --timeout to kill hanging tests after 120s (2 min) # Add --durations=20 to show 20 slowest tests for debugging - uv run --no-sync python -m pytest -vv tests/llm_translation/realtime --cov=litellm --cov-report=xml -v --junitxml=test-results/junit.xml --durations=20 -n 4 --timeout=120 --timeout_method=thread + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/llm_translation/realtime/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=20 \ + -n 4 \ + --timeout=120 --timeout_method=thread" no_output_timeout: 15m - run: name: Rename the coverage files @@ -593,7 +640,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/agent_tests --ignore=tests/agent_tests/local_only_agent_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/agent_tests/**/test_*.py" | grep -v "^tests/agent_tests/local_only_agent_tests/") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m - run: name: Rename the coverage files @@ -626,7 +681,18 @@ jobs: - run: name: Run tests command: | - LITELLM_LOG=WARNING uv run --no-sync python -m pytest tests/guardrails_tests -vv --cov=litellm --cov-report=xml --junitxml=test-results/junit.xml --durations=5 -n 2 --timeout=120 --timeout_method=thread + mkdir -p test-results + export LITELLM_LOG=WARNING + TEST_FILES=$(circleci tests glob "tests/guardrails_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 2 \ + --timeout=120 --timeout_method=thread" no_output_timeout: 15m - run: name: Rename the coverage files @@ -660,7 +726,16 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/unified_google_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5 --retries 3 --retry-delay 5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/unified_google_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + --retries 3 --retry-delay 5" no_output_timeout: 15m - run: name: Rename the coverage files @@ -702,7 +777,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/llm_responses_api_testing -x --junitxml=test-results/junit.xml --durations=5 -n 8 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/llm_responses_api_testing/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 8" no_output_timeout: 15m # Store test results @@ -725,7 +808,16 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/ocr_tests --cov=litellm --cov-report=xml -x -v --junitxml=test-results/junit.xml --durations=5 -n 4 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/ocr_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 4" no_output_timeout: 15m - run: name: Rename the coverage files @@ -758,7 +850,16 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/search_tests --cov=litellm --cov-report=xml -x -v --junitxml=test-results/junit.xml --durations=5 -n 4 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/search_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 4" no_output_timeout: 15m - run: name: Rename the coverage files @@ -793,7 +894,15 @@ jobs: name: Run enterprise tests command: | uv run --no-sync python -m prisma generate - uv run --no-sync python -m pytest -v tests/enterprise -x --junitxml=test-results/junit-enterprise.xml --durations=10 -n 4 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/enterprise/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit-enterprise.xml \ + --durations=10 \ + -n 4" no_output_timeout: 15m # Store test results - store_test_results: @@ -815,7 +924,16 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/batches_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5 -n 2 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/batches_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 2" no_output_timeout: 15m - run: name: Rename the coverage files @@ -848,7 +966,16 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/litellm_utils_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5 -n 2 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/litellm_utils_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 2" no_output_timeout: 15m - run: name: Rename the coverage files @@ -882,7 +1009,16 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/pass_through_unit_tests --cov=litellm --cov-report=xml -x -v --junitxml=test-results/junit.xml --durations=5 -n 4 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/pass_through_unit_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 4" no_output_timeout: 15m - run: name: Rename the coverage files @@ -916,7 +1052,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/image_gen_tests -n 4 -x --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/image_gen_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + -n 4" no_output_timeout: 15m # Store test results - store_test_results: @@ -939,7 +1083,18 @@ jobs: - run: name: Run tests command: | - LITELLM_LOG=WARNING uv run --no-sync python -m pytest tests/logging_callback_tests -vv --cov=litellm --cov-report=xml -n 4 --junitxml=test-results/junit.xml --durations=5 --timeout=120 --timeout_method=thread + mkdir -p test-results + export LITELLM_LOG=WARNING + TEST_FILES=$(circleci tests glob "tests/logging_callback_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv \ + --cov=litellm --cov-report=xml \ + -n 4 \ + --junitxml=test-results/junit.xml \ + --durations=5 \ + --timeout=120 --timeout_method=thread" no_output_timeout: 15m - run: name: Rename the coverage files @@ -972,7 +1127,15 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/audio_tests --cov=litellm --cov-report=xml -x -s -v --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/audio_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m - run: name: Rename the coverage files @@ -1012,14 +1175,19 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv \ + mkdir -p test-results + TEST_FILES=$(printf "%s\n" \ tests/local_testing/test_dual_cache.py \ tests/local_testing/test_redis_batch_optimizations.py \ - tests/local_testing/test_router_utils.py \ - --cov=litellm --cov-report=xml \ - -x -s -v --junitxml=test-results/junit.xml \ - --durations=5 -n 2 \ - --reruns 2 --reruns-delay 1 + tests/local_testing/test_router_utils.py) + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --cov=litellm --cov-report=xml \ + --junitxml=test-results/junit.xml \ + --durations=5 -n 2 \ + --reruns 2 --reruns-delay 1" no_output_timeout: 20m - run: name: Rename the coverage files @@ -1260,8 +1428,17 @@ jobs: - run: name: Run Basic Proxy Startup Tests (Health Readiness and Chat Completion) command: | - uv run --no-sync python -m pytest -v tests/basic_proxy_startup_tests -x --junitxml=test-results/junit-2.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/basic_proxy_startup_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit-2.xml \ + --durations=5" no_output_timeout: 15m + - store_test_results: + path: test-results build_and_test: machine: @@ -1331,7 +1508,18 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -s -v tests/*.py -x --junitxml=test-results/junit.xml -n 4 --durations=5 --ignore=tests/otel_tests --ignore=tests/spend_tracking_tests --ignore=tests/pass_through_tests --ignore=tests/proxy_admin_ui_tests --ignore=tests/load_tests --ignore=tests/llm_translation --ignore=tests/llm_responses_api_testing --ignore=tests/mcp_tests --ignore=tests/guardrails_tests --ignore=tests/image_gen_tests --ignore=tests/pass_through_unit_tests + mkdir -p test-results + # Original used `tests/*.py` (top-level only); the `--ignore=...` + # flags were vestigial since shell globbing did not descend into + # subdirectories. Replicate by globbing only top-level test files. + TEST_FILES=$(circleci tests glob "tests/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -s -v -x \ + --junitxml=test-results/junit.xml \ + -n 4 \ + --durations=5" no_output_timeout: 15m # Store test results @@ -1406,7 +1594,14 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -s -vv tests/openai_endpoints_tests --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/openai_endpoints_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -s -vv \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m # Store test results @@ -1475,7 +1670,14 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/otel_tests --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/otel_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m # Clean up first container - run: @@ -1518,7 +1720,14 @@ jobs: - run: name: Run second round of tests command: | - uv run --no-sync python -m pytest -v tests/basic_proxy_startup_tests -x --junitxml=test-results/junit-2.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/basic_proxy_startup_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit-2.xml \ + --durations=5" no_output_timeout: 15m # Store test results @@ -1587,8 +1796,17 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/spend_tracking_tests -x --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/spend_tracking_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m + - store_test_results: + path: test-results - run: name: Stop and remove first container when: always @@ -1676,7 +1894,14 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/multi_instance_e2e_tests -x --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/multi_instance_e2e_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m # Clean up first container # Store test results @@ -1732,7 +1957,14 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/store_model_in_db_tests -x --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/store_model_in_db_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m - run: name: Stop and remove containers @@ -1805,9 +2037,18 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -vv tests/basic_proxy_startup_tests -x --junitxml=test-results/junit-2.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/basic_proxy_startup_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x \ + --junitxml=test-results/junit-2.xml \ + --durations=5" no_output_timeout: 15m # Clean up first container + - store_test_results: + path: test-results - run: name: Stop and remove first container command: | @@ -1940,7 +2181,14 @@ jobs: - run: name: Run tests command: | - uv run --no-sync python -m pytest -v tests/pass_through_tests/ -x --junitxml=test-results/junit.xml --durations=5 + mkdir -p test-results + TEST_FILES=$(circleci tests glob "tests/pass_through_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -v -x \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m # Store test results @@ -1997,9 +2245,16 @@ jobs: - run: name: Run Claude Agent SDK E2E Tests command: | + mkdir -p test-results export LITELLM_PROXY_URL="http://localhost:4000" export LITELLM_API_KEY="sk-1234" - uv run --no-sync python -m pytest -vv tests/proxy_e2e_anthropic_messages_tests/ -x -s --junitxml=test-results/junit.xml --durations=5 + TEST_FILES=$(circleci tests glob "tests/proxy_e2e_anthropic_messages_tests/**/test_*.py") + echo "$TEST_FILES" | circleci tests run \ + --verbose \ + --command="awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ + -vv -x -s \ + --junitxml=test-results/junit.xml \ + --durations=5" no_output_timeout: 15m # Store test results From b631863b13abe81c8de78a0787f3520d52427215 Mon Sep 17 00:00:00 2001 From: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com> Date: Wed, 6 May 2026 00:42:49 +0000 Subject: [PATCH 5/5] Add utils module docstring Co-authored-by: ishaan-berri --- litellm/utils.py | 2 ++ tests/test_litellm/test_utils_module_docstring.py | 11 +++++++++++ 2 files changed, 13 insertions(+) create mode 100644 tests/test_litellm/test_utils_module_docstring.py diff --git a/litellm/utils.py b/litellm/utils.py index 019fbc2add8..5589852ce41 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -1,3 +1,5 @@ +"""Utility helpers for LiteLLM core request handling and provider support.""" + # from __future__ import annotations must be the first non-comment statement from __future__ import annotations diff --git a/tests/test_litellm/test_utils_module_docstring.py b/tests/test_litellm/test_utils_module_docstring.py new file mode 100644 index 00000000000..ac99fb63fd4 --- /dev/null +++ b/tests/test_litellm/test_utils_module_docstring.py @@ -0,0 +1,11 @@ +import ast +from pathlib import Path + + +def test_utils_module_has_docstring(): + utils_path = Path(__file__).parents[2] / "litellm" / "utils.py" + module = ast.parse(utils_path.read_text()) + + assert ast.get_docstring(module) == ( + "Utility helpers for LiteLLM core request handling and provider support." + )