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propagate to tool calls

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This commit is contained in:
Chester Curme 2025-03-17 14:12:31 -04:00
parent 192035f8c0
commit f333720aad
1 changed files with 36 additions and 2 deletions
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38
libs/partners/openai/langchain_openai/chat_models/base.py
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@ -490,6 +490,15 @@ class BaseChatOpenAI(BaseChatModel):
.. versionadded:: 0.2.14 .. versionadded:: 0.2.14
""" """
reasoning_summary: Optional[str] = None
"""Generate a summary of the reasoning performed by the model (Responses API).
Reasoning models only, like OpenAI o1 and o3-mini.
Currently supported values are ``"concise"`` or ``"detailed"``.
.. versionadded:: 0.3.9
"""
tiktoken_model_name: Optional[str] = None tiktoken_model_name: Optional[str] = None
"""The model name to pass to tiktoken when using this class. """The model name to pass to tiktoken when using this class.
Tiktoken is used to count the number of tokens in documents to constrain Tiktoken is used to count the number of tokens in documents to constrain
@ -541,6 +550,13 @@ class BaseChatOpenAI(BaseChatModel):
If not specified then will be inferred based on invocation params. If not specified then will be inferred based on invocation params.
.. versionadded:: 0.3.9
"""
truncation: Optional[str] = None
"""Truncation strategy (Responses API). Can be ``"auto"`` or ``"disabled"``
(default). If ``"auto"``, model may drop input items from the middle of the
message sequence to fit the context window.
.. versionadded:: 0.3.9 .. versionadded:: 0.3.9
""" """
@ -652,6 +668,8 @@ class BaseChatOpenAI(BaseChatModel):
"n": self.n, "n": self.n,
"temperature": self.temperature, "temperature": self.temperature,
"reasoning_effort": self.reasoning_effort, "reasoning_effort": self.reasoning_effort,
"reasoning_summary": self.reasoning_summary,
"truncation": self.truncation,
} }
params = { params = {
@ -2877,8 +2895,13 @@ def _construct_responses_api_payload(
for legacy_token_param in ["max_tokens", "max_completion_tokens"]: for legacy_token_param in ["max_tokens", "max_completion_tokens"]:
if legacy_token_param in payload: if legacy_token_param in payload:
payload["max_output_tokens"] = payload.pop(legacy_token_param) payload["max_output_tokens"] = payload.pop(legacy_token_param)
if "reasoning_effort" in payload: if "reasoning_effort" in payload or "reasoning_summary" in payload:
payload["reasoning"] = {"effort": payload.pop("reasoning_effort")} reasoning = {}
if "reasoning_effort" in payload:
reasoning["effort"] = payload.pop("reasoning_effort")
if "reasoning_summary" in payload:
reasoning["generate_summary"] = payload.pop("reasoning_summary")
payload["reasoning"] = reasoning
payload["input"] = _construct_responses_api_input(messages) payload["input"] = _construct_responses_api_input(messages)
if tools := payload.pop("tools", None): if tools := payload.pop("tools", None):
@ -3127,6 +3150,17 @@ def _construct_lc_result_from_responses_api(
if _FUNCTION_CALL_IDS_MAP_KEY not in additional_kwargs: if _FUNCTION_CALL_IDS_MAP_KEY not in additional_kwargs:
additional_kwargs[_FUNCTION_CALL_IDS_MAP_KEY] = {} additional_kwargs[_FUNCTION_CALL_IDS_MAP_KEY] = {}
additional_kwargs[_FUNCTION_CALL_IDS_MAP_KEY][output.call_id] = output.id additional_kwargs[_FUNCTION_CALL_IDS_MAP_KEY][output.call_id] = output.id
elif output.type == "computer_call":
tool_call = {
"type": "tool_call",
"name": output.type,
"args": output.action.model_dump(),
"id": output.call_id,
}
tool_calls.append(tool_call)
if _FUNCTION_CALL_IDS_MAP_KEY not in additional_kwargs:
additional_kwargs[_FUNCTION_CALL_IDS_MAP_KEY] = {}
additional_kwargs[_FUNCTION_CALL_IDS_MAP_KEY][output.call_id] = output.id
elif output.type == "reasoning": elif output.type == "reasoning":
additional_kwargs["reasoning"] = output.model_dump( additional_kwargs["reasoning"] = output.model_dump(
exclude_none=True, mode="json" exclude_none=True, mode="json"