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litellm/tests/unit/llms/deepgram/test_deepgram_common_utils.py
yuneng-jiang 5e6dc89ba1
test: move tests/test_litellm/llms into tests/unit/llms (#43191) 
* ci: run the unit_selection.sh shard files on every event instead of only fork pull requests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* ci: rename fork-flag to unit-flag now that it applies on every event

* test: move tests/test_litellm root and small trees into tests/unit

Pure renames, no content changes. Follow-up commits in this PR fix
references, merge the three files that already existed in tests/unit,
keep live-provider tests in tests/test_litellm and wire CI.

* test: carry tests/test_litellm conftest isolation into tests/unit

Callback lists, routing fallbacks, cached HTTP clients, logger state, AWS,
proxy-URL and keychain env, and session-end client cleanup now reset for
unit tests too. The environment isolation owns its MonkeyPatch so a test's
own monkeypatch is undone before the model-cost teardown runs.

* test: merge, split and prune the moved root and small-tree tests

Merge batches/test_batch_utils.py and the chat_completions and messages
dispatch tests into the files that already existed in tests/unit. Keep
the live Gemini interactions tests, the async image-fetch format test and
the OpenAI embedding scorer test in tests/test_litellm since they need
real network or keys. Put test_router.py under tests/unit/test_router so
the existing package no longer shadows it. Delete eight tests the audit
found superseded by stronger ones kept in this move.

* ci: run the moved root and small-tree tests under their legacy flags

Add the misc and responses-caching-types flags to unit_selection.sh and
CircleCI, extend enterprise-routing and mcp-integration, and point the
legacy GHA shards, Makefile, redis-compat workflow, merge smoke manifest
and change classifier at the new paths.

* test: make the new tests/unit directories packages

tests/unit/test_package_layout.py requires every directory to carry an
__init__.py, and without one the moved and retained
test_litellm_responses_bridge.py modules collide on import.

* test: scope the unit socket block to tests/unit in shared sessions

The GHA shards collect the legacy test-path and the unit selection in one
pytest session. The unit conftest's loopback-only block leaked into legacy
modules that reach the network at import. The legacy conftest now lifts the
restriction at collect and setup time, and the unit conftest re-applies it
when collecting its own modules.

* test: move tests/test_litellm/llms into tests/unit/llms

Rename-only. Moves the provider tests and the fine-tuning fixtures they
load, mirroring the old paths. Follow-up commits merge, split and wire them.

* test: merge, split and prune the moved llms tests

Merges the Databricks chat transformation tests into the existing unit
file, keeps the tests that need real keys or the network in
tests/test_litellm, deletes the audited tests a stronger unit test
already covers, and points imports at tests.unit.llms.

* ci: run the moved llms tests under their legacy flags

The Vertex AI and All Other Providers shards keep their legacy test-path
for the retained files and add the llm-vertex-ai and llm-other-providers
unit selections. CircleCI gets matching unit jobs.

* test: make the tests/unit/llms directories packages

Adds __init__.py to the moved dirs and drops the legacy ones whose
directories no longer hold tests.

* test: drop script runners and path hacks the llms split left dangling

The __main__ runners in the split openai_like files and the Databricks e2e
runner called tests that now live in the other half of the split or were
deleted. The retained legacy halves also no longer need sys.path edits.

* test: give the shard-script tests their own GITHUB_OUTPUT

They only passed where the runner set it. The CircleCI unit job's env
allowlist drops it, so the script's redirect failed there.

* test: point the router and module-deletion checks at tests/unit

router_code_coverage and code_qa_check_tests only searched tests/test_litellm,
so the moved router tests no longer counted. The two silent-experiment tests
the audit deleted were the only direct callers of those methods; they are
replaced with tests that assert the forwarded shadow request and the
recursion guard.

* test: keep the Databricks manual e2e runner and fix the SageMaker Nova run path

The Databricks e2e file is a manual script whose main() calls the tests
that were pruned, so pruning them broke the documented run. It is back to
its main version. The SageMaker Nova docstring now points at the file's
real location in tests/local_testing.

* test: keep the job's UNIT_FLAG out of the shard-script tests

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-09-25 12:43:23 -07:00

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import math
from collections.abc import Mapping, Sequence
from typing import Final
from urllib.parse import parse_qs, urlparse
import pytest
import litellm
from litellm.llms.deepgram.common_utils import (
deepgram_listen_addon_pricing_models,
deepgram_listen_audio_seconds,
deepgram_listen_callback_params,
deepgram_listen_channel_count,
deepgram_listen_is_priced,
deepgram_listen_model,
deepgram_listen_pricing_model,
deepgram_listen_registry_key,
deepgram_listen_requested_model,
deepgram_listen_transcript,
deepgram_listen_websocket_target,
)
NOVA_3_URL: Final = "wss://api.deepgram.com/v1/listen?model=nova-3&encoding=linear16&sample_rate=16000"
def _results(
start: object,
duration: object,
transcript: str = "",
is_final: object = True,
channel_index: object = (0, 1),
) -> dict[str, object]:
return {
"type": "Results",
"start": start,
"duration": duration,
"is_final": is_final,
"channel_index": list(channel_index) if isinstance(channel_index, tuple) else channel_index,
"channel": {"alternatives": [{"transcript": transcript, "confidence": 0.9}]},
}
def _metadata(duration: object, channels: object = 1) -> dict[str, object]:
return {"type": "Metadata", "request_id": "req-1", "duration": duration, "channels": channels}
@pytest.mark.parametrize(
("api_base", "query_string", "expected"),
[
pytest.param(
None,
"model=nova-3&encoding=linear16",
"wss://api.deepgram.com/v1/listen?model=nova-3&encoding=linear16",
id="default",
),
pytest.param(
None,
"encoding=linear16&sample_rate=16000",
"wss://api.deepgram.com/v1/listen?encoding=linear16&sample_rate=16000&model=nova-3",
id="model added when missing",
),
pytest.param(
None,
"model=&encoding=linear16",
"wss://api.deepgram.com/v1/listen?encoding=linear16&model=nova-3",
id="empty model replaced",
),
pytest.param(
"http://localhost:9000/v1/",
"model=nova-2",
"ws://localhost:9000/v1/listen?model=nova-2",
id="custom base becomes ws",
),
pytest.param(
"wss://dg.internal/v1",
"model=nova-3&keywords=a&keywords=b",
"wss://dg.internal/v1/listen?model=nova-3&keywords=a&keywords=b",
id="repeated keys preserved",
),
pytest.param(
None,
"model=nova-2&encoding=linear16&model=nova-3",
"wss://api.deepgram.com/v1/listen?model=nova-2&encoding=linear16",
id="only the authorized first model reaches deepgram",
),
pytest.param(
None,
"language=en&model=nova-3&language=multi",
"wss://api.deepgram.com/v1/listen?language=en&model=nova-3",
id="only the priced first language reaches deepgram",
),
pytest.param(
None,
"model=&model=nova-2",
"wss://api.deepgram.com/v1/listen?model=nova-3",
id="blank first model is the default, later models dropped",
),
],
)
def test_deepgram_listen_websocket_target(api_base: str | None, query_string: str, expected: str):
assert deepgram_listen_websocket_target(api_base=api_base, query_string=query_string) == expected
@pytest.mark.parametrize(
("query_string", "expected"),
[
pytest.param("model=nova-3&encoding=linear16", (), id="no callback"),
pytest.param("model=nova-3&callback=https%3A%2F%2Fevil.example%2Fsink", ("callback",), id="callback"),
pytest.param(
"callback_method=put&model=nova-3&callback=wss%3A%2F%2Fevil.example",
("callback", "callback_method"),
id="callback and method",
),
pytest.param("model=nova-3&callback_method=put", ("callback_method",), id="method alone"),
pytest.param("model=nova-3&callbacks=x&my_callback=y", (), id="only exact names match"),
],
)
def test_deepgram_listen_callback_params(query_string: str, expected: tuple[str, ...]):
assert deepgram_listen_callback_params(query_string) == expected
@pytest.mark.parametrize(
("frames", "expected_seconds"),
[
pytest.param((_results(0.0, 2.0), _results(2.0, 3.5), _metadata(6.25)), 6.25, id="metadata wins"),
pytest.param((_metadata(4.0), _results(0.0, 9.0), _metadata(5.5)), 5.5, id="last metadata wins"),
pytest.param((_results(0.0, 2.0), _results(2.0, 3.5), _results(1.0, 1.0)), 5.5, id="furthest results end"),
pytest.param((_results(0.0, 0.0), _metadata(0.0)), 0.0, id="zero metadata is a real zero"),
pytest.param(
(_metadata(0.0), _results(0.0, 2.0), _results(2.0, 3.5)),
5.5,
id="handshake metadata zero does not hide streamed results",
),
pytest.param((_metadata(0.0), _results(0.0, 2.0), _metadata(0.0)), 2.0, id="only zero metadata frames"),
pytest.param((_results(0.0, 1.5), _metadata("6.25")), 1.5, id="string metadata is ignored"),
pytest.param((_results(0.0, 1.5), _metadata(True)), 1.5, id="boolean metadata is ignored"),
pytest.param((_results(0.0, 1.5), _metadata(-3.0)), 1.5, id="negative metadata is ignored"),
pytest.param((_results(0.0, 1.5), _metadata(math.nan), _metadata(math.inf)), 1.5, id="nan/inf ignored"),
pytest.param((_results("0", 2.0), _results(0.0, None), _results(0.0, 0.75)), 0.75, id="malformed results"),
pytest.param(({"type": "SpeechStarted", "timestamp": 3.0}, {"type": "UtteranceEnd"}), 0.0, id="no usage"),
pytest.param((), 0.0, id="no frames"),
],
)
def test_deepgram_listen_audio_seconds(frames: Sequence[Mapping[str, object]], expected_seconds: float):
assert deepgram_listen_audio_seconds(frames) == expected_seconds
@pytest.mark.parametrize(
("frames", "upstream_url", "expected_channels"),
[
pytest.param((_results(0.0, 2.0), _metadata(6.25)), NOVA_3_URL, 1, id="mono"),
pytest.param((_results(0.0, 2.0, channel_index=(0, 2)), _metadata(6.25, 2)), NOVA_3_URL, 2, id="stereo"),
pytest.param((_metadata(1.0, 3), _metadata(1.0, 5)), NOVA_3_URL, 5, id="last metadata wins"),
pytest.param(
(_metadata(1.0, 20), _results(0.0, 1.0, channel_index=(1, 2))),
NOVA_3_URL,
20,
id="metadata beats channel_index",
),
pytest.param(
(_results(0.0, 1.0, channel_index=(0, 2)), _results(0.0, 1.0, channel_index=(3, 4))),
NOVA_3_URL,
4,
id="widest channel_index without metadata",
),
pytest.param(
(_results(0.0, 1.0, channel_index=(0, 2)),),
f"{NOVA_3_URL}&channels=7&multichannel=true",
2,
id="frames beat the declared query",
),
pytest.param((), f"{NOVA_3_URL}&channels=7&multichannel=true", 7, id="declared query when no frames"),
pytest.param((), f"{NOVA_3_URL}&channels=0", 1, id="zero declared channels"),
pytest.param((), f"{NOVA_3_URL}&channels=-2", 1, id="negative declared channels"),
pytest.param((), f"{NOVA_3_URL}&channels=two", 1, id="non numeric declared channels"),
pytest.param((), NOVA_3_URL, 1, id="nothing declared"),
pytest.param((_metadata(1.0, "2"), _metadata(1.0, True), _metadata(1.0, 0)), NOVA_3_URL, 1, id="bad metadata"),
pytest.param((_metadata(1.0, 3), _metadata(1.0, True)), NOVA_3_URL, 3, id="boolean does not shadow a count"),
pytest.param((_metadata(1.0, 2.0), _metadata(1.0, -1)), NOVA_3_URL, 1, id="float and negative metadata"),
pytest.param(
(_metadata(1.0, 2), {**_results(0.0, 1.0), "channels": 9}, {"type": "UtteranceEnd", "channels": 11}),
NOVA_3_URL,
2,
id="channels on non metadata frames ignored",
),
pytest.param(
(
_results(0.0, 1.0, channel_index=[0]),
_results(0.0, 1.0, channel_index=(0, "2")),
_results(0.0, 1.0, channel_index=(0, 0)),
),
NOVA_3_URL,
1,
id="bad channel_index",
),
],
)
def test_deepgram_listen_channel_count(
frames: Sequence[Mapping[str, object]], upstream_url: str, expected_channels: int
):
assert deepgram_listen_channel_count(frames, upstream_url) == expected_channels
def test_deepgram_listen_transcript_joins_final_results_only():
frames = (
_results(0.0, 1.0, "hello wor", is_final=False),
_results(0.0, 1.5, "hello world"),
_results(1.5, 0.5, "", is_final=True),
_results(2.0, 1.0, "how are you", is_final="yes"),
{"type": "Results", "start": 3.0, "duration": 1.0, "is_final": True, "channel": {"alternatives": []}},
_results(4.0, 1.0, "goodbye"),
_metadata(5.0),
)
assert deepgram_listen_transcript(frames) == "hello world goodbye"
@pytest.mark.parametrize(
("upstream_url", "expected_model"),
[
(NOVA_3_URL, "nova-3"),
("wss://api.deepgram.com/v1/listen?encoding=linear16&model=nova-2-medical", "nova-2-medical"),
("wss://api.deepgram.com/v1/listen?model=nova-3&model=nova-2", "nova-3"),
("wss://api.deepgram.com/v1/listen?encoding=linear16", litellm.constants.DEEPGRAM_LISTEN_DEFAULT_MODEL),
],
)
def test_deepgram_listen_model_comes_from_the_upstream_query(upstream_url: str, expected_model: str):
assert deepgram_listen_model(upstream_url) == expected_model
@pytest.mark.parametrize(
"query_string",
[
"model=nova-2&language=en",
"language=en",
"model=&language=en",
"",
"model=nova-3-medical",
"model=nova-2&model=nova-3",
"model=&model=nova-3-medical",
],
)
def test_requested_model_is_the_only_model_the_upstream_target_carries(query_string: str):
"""Authorization runs against ``deepgram_listen_requested_model``; the upstream URL is built separately, so the
two must always agree or a key could be authorized for one model and reach another. Deepgram reads the last
repeated ``model``, so the target must carry exactly one."""
target: Final = deepgram_listen_websocket_target(None, query_string)
assert parse_qs(urlparse(target).query)["model"] == [deepgram_listen_requested_model(query_string)]
assert deepgram_listen_requested_model(query_string) == deepgram_listen_model(target)
@pytest.mark.parametrize(
("upstream_url", "expected"),
[
pytest.param(NOVA_3_URL, "streaming/nova-3", id="monolingual"),
pytest.param(f"{NOVA_3_URL}&language=en", "streaming/nova-3", id="explicit language"),
pytest.param(f"{NOVA_3_URL}&language=multi", "streaming/nova-3-multilingual", id="multilingual"),
pytest.param(f"{NOVA_3_URL}&language=MULTI", "streaming/nova-3-multilingual", id="multilingual any case"),
pytest.param(
"wss://api.deepgram.com/v1/listen?model=nova-2&language=multi",
"streaming/nova-2-multilingual",
id="other model",
),
pytest.param("wss://api.deepgram.com/v1/listen?encoding=linear16", "streaming/nova-3", id="default model"),
],
)
def test_deepgram_listen_pricing_model_is_the_streaming_entry_never_the_prerecorded_one(
upstream_url: str, expected: str
):
assert deepgram_listen_pricing_model(upstream_url) == expected
assert deepgram_listen_registry_key(upstream_url) == f"deepgram/{expected}"
NOVA_2_URL: Final = "wss://api.deepgram.com/v1/listen?model=nova-2"
@pytest.mark.usefixtures("local_model_cost_map")
@pytest.mark.parametrize(
("upstream_url", "extra_rows", "expected"),
[
pytest.param(NOVA_3_URL, (), True, id="streaming entry present"),
pytest.param(f"{NOVA_3_URL}&language=multi", (), True, id="multilingual entry present"),
pytest.param(NOVA_2_URL, (), False, id="only the pre-recorded entry"),
pytest.param(f"{NOVA_2_URL}&language=multi", ("deepgram/streaming/nova-2",), False, id="needs multilingual"),
pytest.param("wss://api.deepgram.com/v1/listen?model=nova-99-unmapped", (), False, id="nothing priced"),
pytest.param(NOVA_2_URL, ("deepgram/streaming/nova-2",), True, id="operator-supplied streaming entry"),
pytest.param(NOVA_2_URL, ("streaming/nova-2",), False, id="a row under another key is not the entry"),
],
)
def test_deepgram_listen_is_priced(
monkeypatch: pytest.MonkeyPatch, upstream_url: str, extra_rows: tuple[str, ...], expected: bool
):
"""The bundled map prices only nova-3 for streaming; nova-2 has a pre-recorded row, which must never count."""
monkeypatch.delitem(litellm.model_cost, "deepgram/streaming/nova-2", raising=False)
assert "deepgram/nova-2" in litellm.model_cost
for row in extra_rows:
monkeypatch.setitem(litellm.model_cost, row, dict(litellm.model_cost["deepgram/streaming/nova-3"]))
assert deepgram_listen_is_priced(upstream_url) is expected
@pytest.mark.parametrize(
("upstream_url", "expected"),
[
pytest.param(NOVA_3_URL, (), id="no add-ons"),
pytest.param(f"{NOVA_3_URL}&redact=pci", ("streaming/redact",), id="redact"),
pytest.param(f"{NOVA_3_URL}&redact=pci&redact=ssn", ("streaming/redact",), id="repeated redact once"),
pytest.param(f"{NOVA_3_URL}&keyterm=a&keyterm=b", ("streaming/keyterm",), id="keyterm"),
pytest.param(f"{NOVA_3_URL}&detect_entities=true", ("streaming/detect_entities",), id="detect_entities"),
pytest.param(f"{NOVA_3_URL}&diarize=true", ("streaming/diarize",), id="diarize"),
pytest.param(f"{NOVA_3_URL}&diarize_model=v1", ("streaming/diarize",), id="diarize_model"),
pytest.param(f"{NOVA_3_URL}&diarize=true&diarize_model=latest", ("streaming/diarize",), id="diarize both once"),
pytest.param(f"{NOVA_3_URL}&detect_entities=false&diarize=FALSE&redact=", (), id="disabled"),
pytest.param(
f"{NOVA_3_URL}&detect_entities=false&detect_entities=true",
("streaming/detect_entities",),
id="any enabling value wins",
),
pytest.param(
f"{NOVA_3_URL}&diarize=true&redact=pci&keyterm=x&detect_entities=true",
("streaming/detect_entities", "streaming/diarize", "streaming/keyterm", "streaming/redact"),
id="all, sorted",
),
],
)
def test_deepgram_listen_addon_pricing_models(upstream_url: str, expected: tuple[str, ...]):
assert deepgram_listen_addon_pricing_models(upstream_url) == expected
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