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fix(cost-map): add azure_ai/claude-mythos-5-1 entry

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`azure_ai/claude-mythos-5-1` had no entry in the model cost map, so the
provider lookup rejected it (the bare `claude-mythos-5-1` belongs to the
`anthropic` provider). `cost_per_token()` raised `ModelNotMappedError` and the
proxy recorded zero spend for a model that actually bills.

Add the dedicated `azure_ai/` entry, reusing Anthropic's published per-model
token rates (per the Microsoft Foundry docs: Foundry uses Anthropic's published
rates), and mirroring the existing `azure_ai/claude-*` layout.

Add a regression test that resolves the entry via `get_model_info` and asserts
non-zero input/output costs from `cost_per_token` (no credentials needed).

Fixes #49865
This commit is contained in:
AaronG 2026-11-04 08:04:15 +08:00
parent baddc67041
commit d652ee3677
2 changed files with 70 additions and 1 deletions
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34
model_prices_and_context_window.json
View file

@ -3833,7 +3833,39 @@
"prompt_cache_min_tokens": 4096,
"source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule"
},
"azure_ai/claude-opus-4-5": {
"azure_ai/claude-mythos-5-1": {
"litellm_provider": "azure_ai",
"mode": "chat",
"max_input_tokens": 1000000,
"max_output_tokens": 128000,
"input_cost_per_token": 1e-05,
"output_cost_per_token": 5e-05,
"input_cost_per_token_batches": 5e-06,
"output_cost_per_token_batches": 2.5e-05,
"cache_creation_input_token_cost": 1.25e-05,
"cache_creation_input_token_cost_above_1hr": 2e-05,
"cache_creation_input_token_cost_batches": 6.25e-06,
"cache_read_input_token_cost": 2.5e-07,
"cache_read_input_token_cost_batches": 1.25e-07,
"prompt_cache_min_tokens": 512,
"supports_function_calling": true,
"supports_vision": true,
"supports_pdf_input": true,
"supports_prompt_caching": true,
"supports_reasoning": true,
"supports_response_schema": true,
"supports_tool_choice": true,
"supports_computer_use": true,
"supports_assistant_prefill": false,
"supports_sampling_params": false,
"supports_adaptive_thinking": true,
"supports_xhigh_reasoning_effort": true,
"supports_max_reasoning_effort": true,
"supports_output_config": true,
"supports_native_structured_output": true,
"source": "https://platform.claude.com/docs/en/about-claude/pricing"
},
"azure_ai/claude-opus-4-5": {
"deprecation_date": "2026-11-24",
"cache_creation_input_token_cost": 6.25e-06,
"cache_creation_input_token_cost_above_1hr": 1e-05,

37
tests/unit_tests/test_azure_ai_mythos_cost_map.py Normal file
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@ -0,0 +1,37 @@
"""
Regression test for https://github.com/BerriAI/litellm/issues/49865
`azure_ai/claude-mythos-5-1` had no entry in the model cost map. The bare
`claude-mythos-5-1` entry belongs to the `anthropic` provider and is rejected by
the azure_ai provider lookup, so `cost_per_token()` raised `ModelNotMappedError`
and the proxy recorded zero spend for a model that actually bills.
This test asserts the dedicated azure_ai entry resolves and returns non-zero
input/output costs, mirroring the issue's reproduction (no credentials needed).
"""
import pytest
from litellm import cost_per_token, get_model_info
def test_azure_ai_claude_mythos_5_1_get_model_info():
info = get_model_info("claude-mythos-5-1", custom_llm_provider="azure_ai")
assert info["litellm_provider"] == "azure_ai"
assert info["input_cost_per_token"] > 0
assert info["output_cost_per_token"] > 0
def test_azure_ai_claude_mythos_5_1_cost_per_token():
spend = cost_per_token(
model="claude-mythos-5-1",
custom_llm_provider="azure_ai",
prompt_tokens=1271,
completion_tokens=389,
)
try:
prompt_cost, completion_cost = spend
except (TypeError, ValueError):
prompt_cost = spend["prompt_cost"]
completion_cost = spend["completion_cost"]
assert prompt_cost > 0
assert completion_cost > 0