mirror of
https://github.com/BerriAI/litellm.git
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603d3358d6
Pulls in the detect-changes CI action and the test-unit job timeout bump, which clears the red lint and code-quality checks on this PR The merged, tightened lint budgets flag this PR's own code, so this merge also makes video_reference_to_id a pure function instead of a helper that mutates its input dict, and rewrites the form-body regression test to call the video_edit and video_extension handlers directly rather than patching an internal class method. Adds pure-logic unit tests for video_reference_to_id
208 lines
7 KiB
Python
208 lines
7 KiB
Python
"""
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Pure-logic contract tests for litellm/proxy/video_endpoints/utils.py
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Four helpers the video proxy endpoints lean on:
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- extract_model_from_target_model_names: first model from a comma string / list
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- video_reference_to_id: normalize a video reference (dict / bare id / JSON string) to an id
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- get_custom_provider_from_data: provider precedence (top-level > extra_body)
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- encode_character_id_in_response: re-encode a response id in place
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Every test asserts the exact result (or identity), so a mutation that flips a
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branch, drops a strip/filter, or changes precedence fails. The only collaborator
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is encode_character_id_with_provider, which runs for real; encoding assertions
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are checked by the genuine decode round-trip.
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"""
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import pytest
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from litellm.proxy.video_endpoints.utils import (
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encode_character_id_in_response,
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extract_model_from_target_model_names,
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get_custom_provider_from_data,
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video_reference_to_id,
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)
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from litellm.types.videos.utils import (
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decode_character_id_with_provider,
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encode_character_id_with_provider,
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)
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# =========================================================================== #
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# extract_model_from_target_model_names
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# =========================================================================== #
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@pytest.mark.parametrize(
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"value,expected",
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[
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("m1,m2,m3", "m1"),
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(" a , b ", "a"), # leading/trailing whitespace stripped
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(",, m1 ,,", "m1"), # empty tokens filtered out
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("solo", "solo"), # single token, no comma
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("", None), # empty string -> no tokens
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(" , , ", None), # only separators/whitespace -> no tokens
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(["x", "y"], "x"), # list -> first element
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([], None), # empty list
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],
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)
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def test_extract_model__str_and_list(value, expected):
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assert extract_model_from_target_model_names(value) == expected
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@pytest.mark.parametrize("value", [None, 123, {"a": 1}, 4.5])
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def test_extract_model__non_str_non_list_is_none(value):
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assert extract_model_from_target_model_names(value) is None
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# =========================================================================== #
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# video_reference_to_id
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# =========================================================================== #
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@pytest.mark.parametrize(
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"video_ref,expected",
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[
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({"id": "video_123"}, "video_123"), # dict reference -> its id
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({"id": ""}, ""), # dict with empty id
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({}, ""), # dict missing id -> default empty
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({"other": "x"}, ""), # dict without id key
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("video_123", "video_123"), # bare id string (not valid JSON) -> itself
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('{"id": "video_9"}', "video_9"), # JSON-encoded dict -> its id
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('{"other": 1}', ""), # JSON-encoded dict without id -> empty
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("[1, 2]", "[1, 2]"), # JSON parses to non-dict -> original string
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(None, ""), # non-str, non-dict
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(123, ""), # non-str, non-dict
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(["video_123"], ""), # list is neither dict nor str
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],
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)
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def test_video_reference_to_id(video_ref, expected):
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assert video_reference_to_id(video_ref) == expected
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# =========================================================================== #
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# get_custom_provider_from_data
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# =========================================================================== #
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def test_provider__top_level_wins_over_extra_body():
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data = {
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"custom_llm_provider": "azure",
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"extra_body": {"custom_llm_provider": "openai"},
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}
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assert get_custom_provider_from_data(data) == "azure"
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@pytest.mark.parametrize("falsy", ["", None])
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def test_provider__falsy_top_level_falls_through_to_extra_body(falsy):
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data = {
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"custom_llm_provider": falsy,
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"extra_body": {"custom_llm_provider": "vertex_ai"},
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}
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assert get_custom_provider_from_data(data) == "vertex_ai"
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def test_provider__from_extra_body_dict():
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assert (
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get_custom_provider_from_data(
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{"extra_body": {"custom_llm_provider": "bedrock"}}
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)
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== "bedrock"
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)
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def test_provider__from_extra_body_json_string():
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data = {"extra_body": '{"custom_llm_provider": "gemini"}'}
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assert get_custom_provider_from_data(data) == "gemini"
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def test_provider__invalid_json_string_is_none():
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assert get_custom_provider_from_data({"extra_body": "not-json{"}) is None
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def test_provider__json_string_parsing_to_non_dict_is_none():
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# parses to a list, not a dict -> no provider extracted.
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assert get_custom_provider_from_data({"extra_body": "[1, 2]"}) is None
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def test_provider__extra_body_provider_not_a_string_is_none():
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assert (
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get_custom_provider_from_data({"extra_body": {"custom_llm_provider": 123}})
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is None
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)
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@pytest.mark.parametrize(
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"data",
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[
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{},
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{"extra_body": {}},
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{"extra_body": 5}, # non-dict, non-str
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{"extra_body": {"other": "x"}}, # dict without provider key
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],
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)
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def test_provider__no_provider_anywhere_is_none(data):
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assert get_custom_provider_from_data(data) is None
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# =========================================================================== #
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# encode_character_id_in_response
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# =========================================================================== #
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class _Resp:
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"""Minimal response object exposing an `id` attribute."""
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def test_encode__dict_with_id_mutates_in_place_and_preserves_other_keys():
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response = {"id": "char_raw", "object": "character", "name": "hero"}
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out = encode_character_id_in_response(response, "azure", "model-1")
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assert out is response # same dict, mutated in place
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assert out["object"] == "character" and out["name"] == "hero"
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assert out["id"] == encode_character_id_with_provider(
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"char_raw", "azure", "model-1"
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)
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decoded = decode_character_id_with_provider(out["id"])
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assert decoded["custom_llm_provider"] == "azure"
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assert decoded["model_id"] == "model-1"
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assert decoded["character_id"] == "char_raw"
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@pytest.mark.parametrize("response", [{}, {"id": ""}, {"id": None}])
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def test_encode__dict_without_usable_id_unchanged(response):
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snapshot = dict(response)
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out = encode_character_id_in_response(response, "azure", "model-1")
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assert out == snapshot
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def test_encode__object_with_str_id():
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resp = _Resp()
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resp.id = "char_raw"
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out = encode_character_id_in_response(resp, "openai", None)
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assert out is resp
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assert resp.id == encode_character_id_with_provider("char_raw", "openai", None)
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decoded = decode_character_id_with_provider(resp.id)
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assert decoded["custom_llm_provider"] == "openai"
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assert decoded["character_id"] == "char_raw"
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@pytest.mark.parametrize("bad_id", [None, 123, ""])
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def test_encode__object_non_str_or_empty_id_unchanged(bad_id):
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resp = _Resp()
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resp.id = bad_id
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out = encode_character_id_in_response(resp, "azure", "model-1")
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assert out is resp
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assert resp.id == bad_id # untouched
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def test_encode__object_without_id_attr_returned_unchanged():
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resp = _Resp()
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out = encode_character_id_in_response(resp, "azure", "model-1")
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assert out is resp
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assert not hasattr(resp, "id")
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