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style(gemini): satisfy type-discipline gate on count_tokens request bodies

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Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
Devin AI 2026-09-23 12:57:06 +00:00
parent d9b612e1e2
commit 4e25825b91
3 changed files with 30 additions and 18 deletions
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10
litellm/llms/gemini/common_utils.py
View file

@ -511,11 +511,15 @@ class GoogleAIStudioTokenCounter(BaseTokenCounter):
"model": model_to_use,
"contents": payload.contents if payload is not None else contents,
**(
{"system_instruction": payload.system_instruction}
{"system_instruction": payload.system_instruction} # mutable-ok: kwargs dict for acount_tokens
if payload is not None and payload.system_instruction is not None
else {}
else {} # mutable-ok: kwargs dict for acount_tokens
),
**(
{"tools": payload.tools} # mutable-ok: kwargs dict for acount_tokens
if payload is not None and payload.tools is not None
else {} # mutable-ok: kwargs dict for acount_tokens
),
**({"tools": payload.tools} if payload is not None and payload.tools is not None else {}),
}
count_tokens_params_request.update(count_tokens_params)
try:

12
litellm/llms/gemini/count_tokens/handler.py
View file

@ -135,14 +135,16 @@ class GoogleAIStudioTokenCounter:
# Prepare request body - clean up contents to remove unsupported fields
cleaned_contents: Final = self._clean_contents_for_gemini_api(contents)
request_body: Final = (
{"contents": cleaned_contents}
{"contents": cleaned_contents} # mutable-ok: httpx json body takes a plain dict
if system_instruction is None and tools is None
else {
"generateContentRequest": {
else { # mutable-ok: httpx json body takes a plain dict
"generateContentRequest": { # mutable-ok: httpx json body takes a plain dict
"model": f"models/{model}",
"contents": cleaned_contents,
**({"systemInstruction": system_instruction} if system_instruction is not None else {}),
**({"tools": tools} if tools is not None else {}),
**( # mutable-ok: httpx json body takes a plain dict
{"systemInstruction": system_instruction} if system_instruction is not None else {}
),
**({"tools": tools} if tools is not None else {}), # mutable-ok: httpx json body takes a plain dict
}
}
)

26
litellm/llms/gemini/count_tokens/transformation.py
View file

@ -30,13 +30,13 @@ def build_count_tokens_payload(
system: object | None,
tools: Sequence[Mapping[str, object]] | None,
) -> GeminiCountTokensPayload:
anthropic_request: Final[AnthropicMessagesRequest] = cast(
AnthropicMessagesRequest, # cast-ok: untrusted client payload, adapter reads the anthropic-shape keys only
{
anthropic_request: Final[AnthropicMessagesRequest] = cast( # cast-ok: adapter reads only the keys supplied
AnthropicMessagesRequest,
{ # mutable-ok: transient request dict for the anthropic adapter
"model": model,
"messages": list(messages),
**({"system": system} if system else {}),
**({"tools": list(tools)} if tools else {}),
"messages": list(messages), # mutable-ok: adapter contract takes a list of messages
**({"system": system} if system else {}), # mutable-ok: transient request dict for the anthropic adapter
**({"tools": list(tools)} if tools else {}), # mutable-ok: transient request dict for the anthropic adapter
},
)
openai_request, _ = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai(
@ -44,7 +44,7 @@ def build_count_tokens_payload(
)
system_instruction, remaining_messages = _transform_system_message(
supports_system_message=True,
messages=list(openai_request["messages"]),
messages=list(openai_request["messages"]), # mutable-ok: helper pops the leading system message
)
contents: Final = _gemini_convert_messages_with_history(
messages=remaining_messages,
@ -52,10 +52,16 @@ def build_count_tokens_payload(
custom_llm_provider="gemini",
)
openai_tools: Final = openai_request.get("tools")
gemini_tools: Final = (
VertexGeminiConfig()._map_function(
value=[dict(tool) for tool in openai_tools], # mutable-ok: _map_function takes plain tool dicts
optional_params={}, # mutable-ok: _map_function signature takes a dict
)
if openai_tools
else None
)
return GeminiCountTokensPayload(
contents=contents,
system_instruction=system_instruction,
tools=VertexGeminiConfig()._map_function(value=[dict(tool) for tool in openai_tools], optional_params={})
if openai_tools
else None,
tools=gemini_tools,
)