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4e19127350
* fix(pricing): add undated azure aliases for gpt-audio-mini and gpt-realtime-mini Azure deployments are commonly created against the undated model name, and the cost-tracking docs say to set base_model to azure/<model> — but only the dated -2025-10-06 entries existed for these two models (the openai provider has undated aliases for both). base_model: azure/gpt-audio-mini therefore resolved to nothing and, depending on the fallback path, text tokens billed at $0 while audio tokens billed fine. Mirror the -2025-10-06 entries as undated aliases, exactly like the undated openai entries mirror their newest dated variant. Fixes #33170 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * test(pricing): assert undated azure audio aliases exactly mirror their dated entries Review follow-up: COST_FIELDS missed realtime-specific cost keys (cache_creation_input_audio_token_cost, cache_read_input_token_cost, input_cost_per_image). Full-entry equality catches drift on every field. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(pricing): mirror updated mode=realtime on the undated gpt-realtime-mini alias Upstream changed the dated entry's mode from chat to realtime after this branch was cut; the undated alias must stay a byte-for-byte mirror. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * fix(pricing): mirror the new deprecation_date onto the undated gpt-audio-mini alias * test(pricing): use shared local_model_cost_map fixture so get_model_info's lru_cache never crosses maps --------- Co-authored-by: Mihidum Hettiyahandi <55163074+mihidumh@users.noreply.github.com> Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
import json
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import typing
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from pathlib import Path
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import pytest
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import litellm
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from litellm.types.utils import ModelInfoBase
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REALTIME_ONLY_GPT_MODELS = (
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"azure/gpt-realtime-2025-08-28",
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"azure/gpt-realtime-1.5-2026-02-23",
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"azure/gpt-realtime-mini",
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"azure/gpt-realtime-mini-2025-10-06",
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"gpt-realtime",
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"gpt-realtime-1.5",
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"gpt-realtime-2",
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"gpt-realtime-2.1",
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"gpt-realtime-2.1-mini",
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"gpt-realtime-mini",
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"gpt-realtime-2025-08-28",
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"gpt-realtime-mini-2025-10-06",
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"gpt-realtime-mini-2025-12-15",
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)
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REALTIME_ONLY_GPT_MODELS_WITHOUT_ENDPOINTS = (
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"azure/eu/gpt-4o-mini-realtime-preview-2024-12-17",
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"azure/eu/gpt-4o-realtime-preview-2024-10-01",
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"azure/eu/gpt-4o-realtime-preview-2024-12-17",
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"azure/gpt-4o-mini-realtime-preview-2024-12-17",
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"azure/gpt-4o-realtime-preview-2024-10-01",
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"azure/gpt-4o-realtime-preview-2024-12-17",
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"azure/us/gpt-4o-mini-realtime-preview-2024-12-17",
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"azure/us/gpt-4o-realtime-preview-2024-10-01",
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"azure/us/gpt-4o-realtime-preview-2024-12-17",
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"gpt-4o-mini-realtime-preview",
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"gpt-4o-mini-realtime-preview-2024-12-17",
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"gpt-4o-realtime-preview",
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"gpt-4o-realtime-preview-2024-12-17",
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"gpt-4o-realtime-preview-2025-06-03",
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)
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ALL_REALTIME_ONLY_GPT_MODELS = REALTIME_ONLY_GPT_MODELS + REALTIME_ONLY_GPT_MODELS_WITHOUT_ENDPOINTS
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def _load_cost_map() -> dict:
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json_path = Path(__file__).parents[2] / "model_prices_and_context_window.json"
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with open(json_path) as f:
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return json.load(f)
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def test_realtime_is_a_valid_mode_literal():
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hints = typing.get_type_hints(ModelInfoBase, include_extras=False)
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assert "realtime" in typing.get_args(hints["mode"])
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@pytest.mark.parametrize("model", REALTIME_ONLY_GPT_MODELS)
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def test_realtime_only_gpt_models_are_mode_realtime(model):
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"""These models only serve /v1/realtime and are rejected by /v1/chat/completions
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("This is not a chat model ..."), so they must not be tagged mode=chat."""
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info = _load_cost_map()[model]
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assert info["supported_endpoints"] == ["/v1/realtime"]
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assert info["mode"] == "realtime"
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@pytest.mark.parametrize("model", REALTIME_ONLY_GPT_MODELS_WITHOUT_ENDPOINTS)
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def test_realtime_only_gpt_4o_models_are_mode_realtime(model):
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"""gpt-4o(-mini)-realtime-preview are realtime-only and must not be mode=chat."""
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assert _load_cost_map()[model]["mode"] == "realtime"
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def test_get_model_info_reports_realtime_mode(monkeypatch):
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"""get_model_info must resolve the retag against the bundled cost map, not the
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hosted map fetched from main, which lags this repo until the next promotion."""
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monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
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monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
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litellm.get_model_info.cache_clear()
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try:
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assert litellm.get_model_info("gpt-realtime-mini")["mode"] == "realtime"
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finally:
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litellm.get_model_info.cache_clear()
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def test_backup_matches_main_for_realtime_models():
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repo_root = Path(__file__).parents[2]
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with open(repo_root / "model_prices_and_context_window.json") as f:
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main_cost = json.load(f)
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with open(repo_root / "litellm" / "model_prices_and_context_window_backup.json") as f:
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backup_cost = json.load(f)
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for model in ALL_REALTIME_ONLY_GPT_MODELS:
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assert backup_cost.get(model) == main_cost.get(model)
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