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chore(typing): clear fresh tech debt from the Aug 24 window
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Browse source 
type the strategy-router health check params instead of a bare dict, annotate
the new interactions usage locals Final, drop a reportUnnecessaryIsInstance
suppression by narrowing the grounding tool list before iterating it, and delete
the duplicated file-id decode comment

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
Devin AI 2026-08-25 07:58:20 +00:00
parent 41acaf4183
commit 442175c4dc
6 changed files with 34 additions and 37 deletions
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12
basedpyright-code-budget.json
View file

@ -1,6 +1,6 @@
{
"reportAny": {
"limit": 19945
"limit": 19936
},
"reportArgumentType": {
"limit": 2566
@ -24,7 +24,7 @@
"limit": 19
},
"reportExplicitAny": {
"limit": 6048
"limit": 6047
},
"reportFunctionMemberAccess": {
"limit": 7
@ -57,7 +57,7 @@
"limit": 5663
},
"reportMissingTypeArgument": {
"limit": 15545
"limit": 15536
},
"reportMissingTypeStubs": {
"limit": 40
@ -105,13 +105,13 @@
"limit": 109
},
"reportUnknownMemberType": {
"limit": 38998
"limit": 38990
},
"reportUnknownParameterType": {
"limit": 19876
"limit": 19868
},
"reportUnknownVariableType": {
"limit": 30554
"limit": 30540
},
"reportUnnecessaryCast": {
"limit": 117

37
litellm/litellm_core_utils/llm_cost_calc/usage_object_transformation.py
View file

@ -1,6 +1,6 @@
from collections.abc import Mapping, Sequence
from types import MappingProxyType
from typing import Any
from typing import Any, Final
from litellm.types.utils import (
CompletionTokensDetailsWrapper,
@ -39,7 +39,7 @@ class TranscriptionUsageObjectTransformation:
return None
_INTERACTIONS_MODALITY_FIELDS: Mapping[str, str] = MappingProxyType(
_INTERACTIONS_MODALITY_FIELDS: Final[Mapping[str, str]] = MappingProxyType(
{
"text": "text_tokens",
"audio": "audio_tokens",
@ -59,7 +59,7 @@ def _token_count(value: object) -> int:
def _modality_token_sums(entries: Sequence[Mapping[str, Any]]) -> Mapping[str, int]:
fields = frozenset(field for entry in entries if (field := _modality_field(entry)) is not None)
fields: Final = frozenset(field for entry in entries if (field := _modality_field(entry)) is not None)
return MappingProxyType(
{
field: sum(_token_count(entry.get("tokens")) for entry in entries if _modality_field(entry) == field)
@ -69,10 +69,13 @@ def _modality_token_sums(entries: Sequence[Mapping[str, Any]]) -> Mapping[str, i
def _google_search_query_count(usage_object: Mapping[str, Any]) -> int:
entries: Final = usage_object.get("grounding_tool_count")
if not isinstance(entries, Sequence):
return 0
return sum(
_token_count(entry.get("count"))
for entry in tuple(usage_object.get("grounding_tool_count") or ())
if isinstance(entry, Mapping) and entry.get("type") == "google_search" # pyright: ignore[reportUnnecessaryIsInstance] # provider JSON, not the empty tuple inferred from `or ()`
for entry in entries
if isinstance(entry, Mapping) and entry.get("type") == "google_search"
)
@ -112,30 +115,30 @@ class InteractionsUsageObjectTransformation:
@staticmethod
def transform_interactions_usage_object(usage_object: Mapping[str, Any]) -> Usage:
input_entries = tuple(usage_object.get("input_tokens_by_modality") or ()) + tuple(
input_entries: Final = tuple(usage_object.get("input_tokens_by_modality") or ()) + tuple(
usage_object.get("tool_use_tokens_by_modality") or ()
)
cached_sums = _modality_token_sums(tuple(usage_object.get("cached_tokens_by_modality") or ()))
output_sums = _modality_token_sums(tuple(usage_object.get("output_tokens_by_modality") or ()))
cached_sums: Final = _modality_token_sums(tuple(usage_object.get("cached_tokens_by_modality") or ()))
output_sums: Final = _modality_token_sums(tuple(usage_object.get("output_tokens_by_modality") or ()))
total_cached_tokens = _token_count(usage_object.get("total_cached_tokens"))
input_sums = _subtract_cached_from_input(
total_cached_tokens: Final = _token_count(usage_object.get("total_cached_tokens"))
input_sums: Final = _subtract_cached_from_input(
input_sums=_modality_token_sums(input_entries),
cached_sums=cached_sums,
total_cached_tokens=total_cached_tokens,
)
reasoning_tokens = _token_count(usage_object.get("total_reasoning_tokens")) or _token_count(
reasoning_tokens: Final = _token_count(usage_object.get("total_reasoning_tokens")) or _token_count(
usage_object.get("total_thought_tokens")
)
prompt_tokens = _token_count(usage_object.get("total_input_tokens")) + _token_count(
prompt_tokens: Final = _token_count(usage_object.get("total_input_tokens")) + _token_count(
usage_object.get("total_tool_use_tokens")
)
completion_tokens = _token_count(usage_object.get("total_output_tokens")) + reasoning_tokens
total_tokens = _token_count(usage_object.get("total_tokens")) or (prompt_tokens + completion_tokens)
completion_tokens: Final = _token_count(usage_object.get("total_output_tokens")) + reasoning_tokens
total_tokens: Final = _token_count(usage_object.get("total_tokens")) or (prompt_tokens + completion_tokens)
web_search_requests = _google_search_query_count(usage_object)
prompt_tokens_details = (
web_search_requests: Final = _google_search_query_count(usage_object)
prompt_tokens_details: Final = (
PromptTokensDetailsWrapper(
cached_tokens=total_cached_tokens or None,
web_search_requests=web_search_requests or None,
@ -144,7 +147,7 @@ class InteractionsUsageObjectTransformation:
if input_sums or total_cached_tokens or web_search_requests
else None
)
completion_tokens_details = (
completion_tokens_details: Final = (
CompletionTokensDetailsWrapper(
reasoning_tokens=reasoning_tokens or None,
**output_sums,

6
litellm/litellm_core_utils/prompt_templates/common_utils.py
View file

@ -511,9 +511,6 @@ def update_messages_with_model_file_ids(
if "llm_output_file_id," in unified_file_id:
provider_file_id = unified_file_id.split("llm_output_file_id,")[1].split(";")[0]
if not provider_file_id and is_model_embedded_id(file_id):
# `litellm:<raw_id>;model,<m>` encoding from the
# x-litellm-model upload path. Strip the wrapper
# so the provider sees its own ID.
provider_file_id = get_original_file_id(file_id)
file_object_file_field["file_id"] = provider_file_id or file_id
if format:
@ -588,9 +585,6 @@ def update_responses_input_with_model_file_ids(
updated_content_item["file_id"] = provider_file_id
updated_content.append(updated_content_item)
elif is_model_embedded_id(file_id):
# `litellm:<raw_id>;model,<m>` encoding from the
# x-litellm-model upload path. Strip the wrapper
# so the provider sees its own ID.
updated_content_item = content_item.copy()
updated_content_item["file_id"] = get_original_file_id(file_id)
updated_content.append(updated_content_item)

2
litellm/proxy/health_check.py
View file

@ -183,7 +183,7 @@ async def run_with_timeout(task, timeout):
return {"error": "Timeout exceeded", "exception": timeout_exception}
def _is_strategy_router_deployment(litellm_params: dict) -> bool:
def _is_strategy_router_deployment(litellm_params: Mapping[str, object]) -> bool:
"""True for strategy-router deployments."""
model: Final[object] = litellm_params.get("model", "")
return isinstance(model, str) and classify_strategy_router_model(model) is not None

8
ruff-strict-budget.json
View file

@ -12,10 +12,10 @@
"limit": 2016
},
"ANN202": {
"limit": 850
"limit": 849
},
"ANN204": {
"limit": 709
"limit": 708
},
"ANN205": {
"limit": 112
@ -24,7 +24,7 @@
"limit": 133
},
"ANN401": {
"limit": 1185
"limit": 1183
},
"ASYNC230": {
"limit": 11
@ -231,7 +231,7 @@
"limit": 5
},
"TID251": {
"limit": 1210
"limit": 1209
},
"TRY002": {
"limit": 524

6
type-discipline-budget.json
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@ -1,9 +1,9 @@
{
"LIT001": {
"limit": 22795
"limit": 22788
},
"LIT002": {
"limit": 26872
"limit": 26871
},
"LIT003": {
"limit": 269
@ -27,7 +27,7 @@
"limit": 0
},
"LIT010": {
"limit": 16672
"limit": 16657
},
"LIT011": {
"limit": 5588