mirror of
https://github.com/BerriAI/litellm.git
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276 lines
11 KiB
Python
276 lines
11 KiB
Python
from __future__ import annotations
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import importlib.util
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import json
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import re
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from pathlib import Path
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from types import MappingProxyType
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from typing import Final
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import jsonschema
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import pytest
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from litellm.llms.openai.chat.gpt_5_transformation import is_gpt_reasoning_series_name
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from litellm.router_utils.reasoning_effort_capability import resolve_supported_reasoning_efforts
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REPO_ROOT = Path(__file__).parents[2]
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GENERATOR_PATH = REPO_ROOT / "ci_cd" / "generate_model_prices_schema.py"
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PRICES_PATH = REPO_ROOT / "model_prices_and_context_window.json"
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BACKUP_PRICES_PATH = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json"
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SCHEMA_PATH = REPO_ROOT / "model_prices_and_context_window.schema.json"
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def build_validator(schema: dict) -> jsonschema.Draft202012Validator:
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return jsonschema.Draft202012Validator(schema, format_checker=jsonschema.Draft202012Validator.FORMAT_CHECKER)
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def load_generator():
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spec = importlib.util.spec_from_file_location("generate_model_prices_schema", GENERATOR_PATH)
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assert spec is not None and spec.loader is not None
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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return module
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@pytest.fixture(scope="module")
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def committed_schema() -> dict:
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return json.loads(SCHEMA_PATH.read_text())
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@pytest.fixture(scope="module")
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def prices() -> dict:
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return json.loads(PRICES_PATH.read_text())
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def test_committed_schema_matches_generator_output(prices: dict, committed_schema: dict):
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generator = load_generator()
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regenerated = json.loads(generator.render(generator.build_schema(prices)))
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assert regenerated == committed_schema, (
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"model_prices_and_context_window.schema.json is out of sync; "
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"run `python ci_cd/generate_model_prices_schema.py` and commit the result"
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)
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def test_prices_file_validates_against_committed_schema(prices: dict, committed_schema: dict):
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validator = build_validator(committed_schema)
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errors = [
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f"{'.'.join(str(part) for part in error.absolute_path)}: {error.message}"
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for error in validator.iter_errors(prices)
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]
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assert errors == []
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@pytest.mark.parametrize(
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"entry",
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[
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{"litellm_provider": "openai", "mode": "chat", "input_cost_per_token": "0.01"},
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{"litellm_provider": "openai", "mode": "chat", "input_cost_per_token": -1},
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{"litellm_provider": "openai", "mode": "not_a_real_mode"},
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{"mode": "chat"},
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{"litellm_provider": "openai", "deprecation_date": "June 2026"},
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{"litellm_provider": "openai", "deprecation_date": "2026-99-99"},
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{"litellm_provider": "openai", "deprecation_date": "2026-13-01"},
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{"litellm_provider": "openai", "deprecation_date": "2026-01-32"},
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{"litellm_provider": "openai", "deprecation_date": "2026-01-00"},
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{"litellm_provider": "openai", "deprecation_date": "2026-02-31"},
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{"litellm_provider": "openai", "supported_modalities": ["smell"]},
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{"litellm_provider": "openai", "supports_vision": "yes"},
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{"litellm_provider": "openai", "max_tokens": 8191.5},
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{"litellm_provider": "openai", "tiered_pricing": [{"unknown_tier_field": 1}]},
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],
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ids=[
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"cost_as_string",
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"negative_cost",
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"unknown_mode",
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"missing_provider",
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"non_iso_deprecation_date",
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"impossible_month_and_day",
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"month_out_of_range",
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"day_out_of_range",
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"day_zero",
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"calendar_impossible_day",
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"unknown_modality",
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"boolean_flag_as_string",
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"fractional_max_tokens",
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"unknown_tiered_pricing_field",
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],
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)
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def test_schema_rejects_malformed_entries(committed_schema: dict, entry: dict):
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validator = build_validator(committed_schema)
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assert not validator.is_valid({"some-model": entry})
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def test_schema_accepts_minimal_and_unknown_optional_fields(committed_schema: dict):
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validator = build_validator(committed_schema)
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assert validator.is_valid({"some-model": {"litellm_provider": "openai"}})
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assert validator.is_valid({"some-model": {"litellm_provider": "openai", "brand_new_field": {"nested": True}}})
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def test_schema_accepts_cache_creation_cost_inside_a_pricing_tier(committed_schema: dict):
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validator = build_validator(committed_schema)
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entry = {
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"litellm_provider": "dashscope",
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"mode": "chat",
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"tiered_pricing": [
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{
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"range": [0, 256000],
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"input_cost_per_token": 3.25e-07,
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"output_cost_per_token": 1.95e-06,
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"cache_creation_input_token_cost": 4.063e-07,
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"cache_read_input_token_cost": 3.25e-08,
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}
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],
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}
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assert validator.is_valid({"some-model": entry})
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def find_duplicate_keys(path: Path) -> list[str]:
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duplicates: list[str] = []
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def record_duplicates(pairs):
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seen: set[str] = set()
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for key, _ in pairs:
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if key in seen:
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duplicates.append(key)
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seen.add(key)
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return dict(pairs)
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json.loads(path.read_text(), object_pairs_hook=record_duplicates)
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return duplicates
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@pytest.mark.parametrize("path", (PRICES_PATH, BACKUP_PRICES_PATH), ids=("main", "backup"))
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def test_price_map_has_no_duplicate_keys(path: Path):
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assert find_duplicate_keys(path) == [], (
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f"{path.name} defines the same key twice; JSON parsers keep only the last "
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"occurrence, so the earlier entry's fields are silently dropped. This is what "
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"a clean text merge of two branches that both added a model looks like: "
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"deduplicate the keys into one entry"
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)
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DATED_VARIANT = re.compile(r"^(.*?)-(\d{4}-\d{2}-\d{2})$")
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SERVICE_TIER_SUFFIXES = ("_flex", "_priority")
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def tier_anchor(tier_key: str) -> str:
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matched = next(suffix for suffix in SERVICE_TIER_SUFFIXES if tier_key.endswith(suffix))
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return tier_key[: -len(matched)]
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def test_dated_variants_carry_base_alias_service_tier_pricing(prices: dict):
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drifted = [
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f"{name}: missing {tier_key}={base[tier_key]} (base alias {match.group(1)})"
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for name, entry in prices.items()
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if isinstance(entry, dict)
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for match in [DATED_VARIANT.match(name)]
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if match is not None
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for base in [prices.get(match.group(1))]
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if isinstance(base, dict)
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for tier_key in base
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if tier_key.endswith(SERVICE_TIER_SUFFIXES)
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and tier_anchor(tier_key) in base
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and entry.get(tier_anchor(tier_key)) == base[tier_anchor(tier_key)]
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and entry.get(tier_key) != base[tier_key]
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]
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assert drifted == [], (
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"dated model variants are missing flex/priority pricing their base alias has; "
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"sync the tier keys so service-tier requests against pinned snapshots are not "
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"billed at standard rates:\n" + "\n".join(drifted)
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)
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OPENAI_REASONING_FAMILY_MARKERS = ("codex", "deep-research", "chat-latest")
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def is_openai_o_series(name: str) -> bool:
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return len(name) > 1 and name[0] == "o" and name[1].isdigit()
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def is_openai_reasoning_family(name: str) -> bool:
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base = name.split("/")[-1].removeprefix("ft:")
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if "search-api" in base:
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return False
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return (
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is_openai_o_series(base)
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or is_gpt_reasoning_series_name(base)
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or any(marker in base for marker in OPENAI_REASONING_FAMILY_MARKERS)
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)
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def test_openai_reasoning_family_entries_carry_supports_reasoning(prices: dict):
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unflagged = [
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name
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for name, entry in prices.items()
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if isinstance(entry, dict)
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and entry.get("litellm_provider") == "openai"
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and is_openai_reasoning_family(name)
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and entry.get("supports_reasoning") is not True
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]
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assert unflagged == [], (
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"OpenAI o-series, gpt-5+, codex, deep-research, and chat-latest models are reasoning "
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"models, and the Responses API drops the `reasoning` param for any mapped OpenAI model "
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"whose entry lacks supports_reasoning; flag these entries:\n" + "\n".join(unflagged)
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)
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def test_chat_latest_declares_the_one_effort_openai_accepts(prices: dict):
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"""OpenAI rejects every reasoning.effort on chat-latest except medium, and a reasoning entry
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with no declared levels resolves to None, which lets /model_group/info and the dashboard offer
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levels the upstream will 400 on."""
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assert resolve_supported_reasoning_efforts(prices["chat-latest"], deployment_is_mapped=True) == ("medium",)
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@pytest.mark.parametrize("key", ["azure/gpt-chat-latest", "azure/chat-latest", "azure/us/gpt-chat-latest"])
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def test_azure_gpt_chat_latest_declares_the_one_effort_azure_accepts(prices: dict, key: str):
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"""Azure answers every reasoning_effort on a gpt-chat-latest deployment except medium with
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"Unsupported value ... Supported values are: 'medium'", the same fixed level OpenAI's chat-latest
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carries, so the Foundry product name and the OpenAI API name both declare that one level."""
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assert resolve_supported_reasoning_efforts(prices[key], deployment_is_mapped=True) == ("medium",)
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BEDROCK_OPENAI_GPT_MARKERS: Final = ("openai.gpt-5.4", "openai.gpt-5.5", "openai.gpt-5.6", "openai.gpt-6-astra")
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BEDROCK_PROVIDERS: Final = frozenset(("bedrock", "bedrock_converse", "bedrock_mantle"))
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BEDROCK_ROW_PREFIXES: Final = ("bedrock_mantle/", "us.", "global.")
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GPT_5_4_BEDROCK_LADDER: Final = ("none", "low", "medium", "high", "xhigh")
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GPT_5_6_BEDROCK_LADDER: Final = ("none", "low", "medium", "high", "xhigh", "max")
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GPT_6_ASTRA_BEDROCK_LADDER: Final = ("low", "medium", "high", "xhigh", "max")
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BEDROCK_OPENAI_GPT_LADDERS: Final = MappingProxyType(
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{
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"bedrock_mantle/openai.gpt-5.4": GPT_5_4_BEDROCK_LADDER,
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"bedrock_mantle/openai.gpt-5.5": GPT_5_4_BEDROCK_LADDER,
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**{
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f"{prefix}openai.gpt-5.6-{variant}": GPT_5_6_BEDROCK_LADDER
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for prefix in BEDROCK_ROW_PREFIXES
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for variant in ("luna", "sol", "terra")
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},
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**{f"{prefix}openai.gpt-6-astra": GPT_6_ASTRA_BEDROCK_LADDER for prefix in BEDROCK_ROW_PREFIXES},
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}
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)
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@pytest.mark.parametrize(
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("name", "ladder"), tuple(BEDROCK_OPENAI_GPT_LADDERS.items()), ids=tuple(BEDROCK_OPENAI_GPT_LADDERS)
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)
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def test_bedrock_openai_gpt_rows_advertise_the_ladder_bedrock_accepts(prices: dict, name: str, ladder: tuple[str, ...]):
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"""Each ladder is the set of levels Bedrock answered 200 to for that row through the proxy on
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2026-09-11 (PR #40740): the Mantle rows go out over its Responses endpoint and the Converse rows
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over inference profiles. Bedrock differs from the direct OpenAI rows in two places, gpt-5.6 and
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gpt-6-astra take max there, and gpt-6-astra refuses none; minimal is refused on every row.
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xhigh and max are opt-in for the resolver, so a row missing either flag silently drops that
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level from every group it belongs to."""
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assert resolve_supported_reasoning_efforts(prices[name], deployment_is_mapped=True) == ladder
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def test_every_bedrock_openai_gpt_row_advertises_xhigh(prices: dict):
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"""The GovCloud and gpt-5.6-cyber rows cannot be called from our account, so they carry the
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family's xhigh flag rather than a measured ladder."""
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missing: Final = [
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name
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for name, entry in prices.items()
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if isinstance(entry, dict)
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and entry.get("litellm_provider") in BEDROCK_PROVIDERS
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and any(marker in name for marker in BEDROCK_OPENAI_GPT_MARKERS)
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and "xhigh" not in (resolve_supported_reasoning_efforts(entry, deployment_is_mapped=True) or ())
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]
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assert missing == []
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