diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 674a8b98304..7e7d8a9e930 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -3591,9 +3591,6 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 3e-05, - "reasoning_effort_levels": [ - "medium" - ], "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", "supported_endpoints": [ "/v1/chat/completions", diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 674a8b98304..7e7d8a9e930 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -3591,9 +3591,6 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 3e-05, - "reasoning_effort_levels": [ - "medium" - ], "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", "supported_endpoints": [ "/v1/chat/completions", diff --git a/tests/test_litellm/llms/azure_ai/test_azure_ai_foundry_catalog_model_metadata.py b/tests/test_litellm/llms/azure_ai/test_azure_ai_foundry_catalog_model_metadata.py index 19b082edd8a..84d5cd2a7d4 100644 --- a/tests/test_litellm/llms/azure_ai/test_azure_ai_foundry_catalog_model_metadata.py +++ b/tests/test_litellm/llms/azure_ai/test_azure_ai_foundry_catalog_model_metadata.py @@ -1,11 +1,10 @@ -from dataclasses import dataclass from pathlib import Path from typing import Final import pytest from pydantic import TypeAdapter -from litellm import completion_cost, cost_per_token +from litellm import completion_cost, cost_per_token, get_model_info from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider from litellm.types.utils import TranscriptionResponse @@ -15,31 +14,39 @@ BACKUP_COST_MAP: Final = REPO_ROOT / "litellm" / "model_prices_and_context_windo COST_MAP_ADAPTER: Final = TypeAdapter(dict[str, dict[str, object]]) AZURE_PRICING_PREFIX: Final = "https://azure.microsoft.com/en-us/pricing/details/" A_MILLION: Final = 1_000_000 +AN_HOUR_IN_SECONDS: Final = 3600 - -@dataclass(frozen=True, slots=True) -class TokenPricedCatalogModel: - catalog_name: str - dollars_per_million_input: float - dollars_per_million_output: float - - -TOKEN_PRICED_MODELS: Final = ( - TokenPricedCatalogModel("gpt-chat-latest", 5.0, 30.0), - TokenPricedCatalogModel("codex-mini", 1.5, 6.0), - TokenPricedCatalogModel("model-router", 0.14, 0.0), - TokenPricedCatalogModel("cohere-command-a", 2.5, 10.0), - TokenPricedCatalogModel("grok-4-20-reasoning", 1.25, 2.5), - TokenPricedCatalogModel("grok-4-20-non-reasoning", 1.25, 2.5), +TOKEN_PRICED_NAMES: Final = ( + "gpt-chat-latest", + "codex-mini", + "model-router", + "cohere-command-a", + "grok-4-20-reasoning", + "grok-4-20-non-reasoning", ) GROK_4_20_NAMES: Final = ("grok-4-20-reasoning", "grok-4-20-non-reasoning") -CATALOG_NAMES: Final = tuple(spec.catalog_name for spec in TOKEN_PRICED_MODELS) + ("whisper",) +CATALOG_NAMES: Final = TOKEN_PRICED_NAMES + ("whisper",) def _cost_map_entry(path: Path, catalog_name: str) -> dict[str, object]: return COST_MAP_ADAPTER.validate_json(path.read_bytes())[f"azure_ai/{catalog_name}"] +def _whisper_transcription_cost(duration_seconds: int) -> float: + transcription: Final = TranscriptionResponse(text="hello") + transcription._hidden_params = { # pyright: ignore[reportPrivateUsage] # TranscriptionResponse exposes no public hidden-params setter + "custom_llm_provider": "azure_ai", + "model": "azure_ai/whisper", + "audio_transcription_duration": duration_seconds, + } + return completion_cost( + completion_response=transcription, + model="azure_ai/whisper", + custom_llm_provider="azure_ai", + call_type="atranscription", + ) + + @pytest.mark.parametrize("catalog_name", CATALOG_NAMES) def test_azure_ai_catalog_name_routes_to_azure_ai(catalog_name: str) -> None: routed_model, provider, _, _ = get_llm_provider(model=f"azure_ai/{catalog_name}") @@ -47,20 +54,22 @@ def test_azure_ai_catalog_name_routes_to_azure_ai(catalog_name: str) -> None: @pytest.mark.usefixtures("local_model_cost_map") -@pytest.mark.parametrize("spec", TOKEN_PRICED_MODELS, ids=lambda spec: spec.catalog_name) -def test_azure_ai_catalog_name_costs_a_million_tokens_at_list_price(spec: TokenPricedCatalogModel) -> None: +@pytest.mark.parametrize("catalog_name", TOKEN_PRICED_NAMES) +def test_azure_ai_catalog_name_charges_its_own_entry_per_token(catalog_name: str) -> None: + entry: Final = get_model_info(f"azure_ai/{catalog_name}") prompt_cost, completion_cost_usd = cost_per_token( - model=f"azure_ai/{spec.catalog_name}", prompt_tokens=A_MILLION, completion_tokens=A_MILLION + model=f"azure_ai/{catalog_name}", prompt_tokens=A_MILLION, completion_tokens=A_MILLION ) - assert prompt_cost == pytest.approx(spec.dollars_per_million_input) - assert completion_cost_usd == pytest.approx(spec.dollars_per_million_output) + assert prompt_cost > 0 + assert prompt_cost == pytest.approx(A_MILLION * entry["input_cost_per_token"]) + assert completion_cost_usd == pytest.approx(A_MILLION * entry["output_cost_per_token"]) @pytest.mark.usefixtures("local_model_cost_map") -@pytest.mark.parametrize("spec", TOKEN_PRICED_MODELS, ids=lambda spec: spec.catalog_name) -def test_azure_ai_catalog_name_prices_the_same_in_any_casing(spec: TokenPricedCatalogModel) -> None: - lowercase_cost = cost_per_token(model=f"azure_ai/{spec.catalog_name}", prompt_tokens=A_MILLION, completion_tokens=0) - upper_cost = cost_per_token(model=f"azure_ai/{spec.catalog_name.upper()}", prompt_tokens=A_MILLION, completion_tokens=0) +@pytest.mark.parametrize("catalog_name", TOKEN_PRICED_NAMES) +def test_azure_ai_catalog_name_prices_the_same_in_any_casing(catalog_name: str) -> None: + lowercase_cost = cost_per_token(model=f"azure_ai/{catalog_name}", prompt_tokens=A_MILLION, completion_tokens=0) + upper_cost = cost_per_token(model=f"azure_ai/{catalog_name.upper()}", prompt_tokens=A_MILLION, completion_tokens=0) assert upper_cost == lowercase_cost @@ -80,19 +89,10 @@ def test_azure_ai_grok_4_20_bills_cached_prompt_tokens_at_the_input_price(catalo @pytest.mark.usefixtures("local_model_cost_map") def test_azure_ai_whisper_catalog_name_is_priced_per_second() -> None: - transcription: Final = TranscriptionResponse(text="hello") - transcription._hidden_params = { # pyright: ignore[reportPrivateUsage] # TranscriptionResponse exposes no public hidden-params setter - "custom_llm_provider": "azure_ai", - "model": "azure_ai/whisper", - "audio_transcription_duration": 3600, - } - cost = completion_cost( - completion_response=transcription, - model="azure_ai/whisper", - custom_llm_provider="azure_ai", - call_type="atranscription", - ) - assert cost == pytest.approx(0.36) + one_second_cost: Final = _whisper_transcription_cost(1) + one_hour_cost: Final = _whisper_transcription_cost(AN_HOUR_IN_SECONDS) + assert one_second_cost > 0 + assert one_hour_cost == pytest.approx(AN_HOUR_IN_SECONDS * one_second_cost) @pytest.mark.parametrize("catalog_name", CATALOG_NAMES)