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Union[str, ChatModel, Literal["o1-pro", "o1-pro-2025-03-19", "o3-pro", 11 more]]
Literal["gpt-5.2", "gpt-5.2-2025-12-11", "gpt-5.2-chat-latest", 69 more]
Literal["o1-pro", "o1-pro-2025-03-19", "o3-pro", 11 more]
Literal["gpt-5.2", "gpt-5.2-2025-12-11", "gpt-5.2-chat-latest", 69 more]
class ComparisonFilter: …A filter used to compare a specified attribute key to a given value using a defined comparison operation.
A filter used to compare a specified attribute key to a given value using a defined comparison operation.
The key to compare against the value.
type: Literal["eq", "ne", "gt", 3 more]Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.
eq: equalsne: not equalgt: greater thangte: greater than or equallt: less thanlte: less than or equalin: innin: not in
Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.
eq: equalsne: not equalgt: greater thangte: greater than or equallt: less thanlte: less than or equalin: innin: not in
value: Union[str, float, bool, List[Union[str, float]]]The value to compare against the attribute key; supports string, number, or boolean types.
The value to compare against the attribute key; supports string, number, or boolean types.
List[Union[str, float]]
class CompoundFilter: …Combine multiple filters using and or or.
Combine multiple filters using and or or.
filters: List[Filter]Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.
Array of filters to combine. Items can be ComparisonFilter or CompoundFilter.
class ComparisonFilter: …A filter used to compare a specified attribute key to a given value using a defined comparison operation.
A filter used to compare a specified attribute key to a given value using a defined comparison operation.
The key to compare against the value.
type: Literal["eq", "ne", "gt", 3 more]Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.
eq: equalsne: not equalgt: greater thangte: greater than or equallt: less thanlte: less than or equalin: innin: not in
Specifies the comparison operator: eq, ne, gt, gte, lt, lte, in, nin.
eq: equalsne: not equalgt: greater thangte: greater than or equallt: less thanlte: less than or equalin: innin: not in
value: Union[str, float, bool, List[Union[str, float]]]The value to compare against the attribute key; supports string, number, or boolean types.
The value to compare against the attribute key; supports string, number, or boolean types.
List[Union[str, float]]
type: Literal["and", "or"]Type of operation: and or or.
Type of operation: and or or.
The input format for the custom tool. Default is unconstrained text.
The input format for the custom tool. Default is unconstrained text.
class Text: …Unconstrained free-form text.
Unconstrained free-form text.
Unconstrained text format. Always text.
class Grammar: …A grammar defined by the user.
A grammar defined by the user.
The grammar definition.
syntax: Literal["lark", "regex"]The syntax of the grammar definition. One of lark or regex.
The syntax of the grammar definition. One of lark or regex.
Grammar format. Always grammar.
class ErrorObject: …
class FunctionDefinition: …
The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
A description of what the function does, used by the model to choose when and how to call the function.
The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.
Omitting parameters defines a function with an empty parameter list.
Whether to enable strict schema adherence when generating the function call. If set to true, the model will follow the exact schema defined in the parameters field. Only a subset of JSON Schema is supported when strict is true. Learn more about Structured Outputs in the function calling guide.
The parameters the functions accepts, described as a JSON Schema object. See the guide for examples, and the JSON Schema reference for documentation about the format.
Omitting parameters defines a function with an empty parameter list.
Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
class Reasoning: …gpt-5 and o-series models only
Configuration options for
reasoning models.
gpt-5 and o-series models only
Configuration options for reasoning models.
Constrains effort on reasoning for
reasoning models.
Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing
reasoning effort can result in faster responses and fewer tokens used
on reasoning in a response.
gpt-5.1defaults tonone, which does not perform reasoning. The supported reasoning values forgpt-5.1arenone,low,medium, andhigh. Tool calls are supported for all reasoning values in gpt-5.1.- All models before
gpt-5.1default tomediumreasoning effort, and do not supportnone. - The
gpt-5-promodel defaults to (and only supports)highreasoning effort. xhighis supported for all models aftergpt-5.1-codex-max.
Deprecatedgenerate_summary: Optional[Literal["auto", "concise", "detailed"]]Deprecated: use summary instead.
A summary of the reasoning performed by the model. This can be
useful for debugging and understanding the model's reasoning process.
One of auto, concise, or detailed.
Deprecated: use summary instead.
A summary of the reasoning performed by the model. This can be
useful for debugging and understanding the model's reasoning process.
One of auto, concise, or detailed.
summary: Optional[Literal["auto", "concise", "detailed"]]A summary of the reasoning performed by the model. This can be
useful for debugging and understanding the model's reasoning process.
One of auto, concise, or detailed.
concise is supported for computer-use-preview models and all reasoning models after gpt-5.
A summary of the reasoning performed by the model. This can be
useful for debugging and understanding the model's reasoning process.
One of auto, concise, or detailed.
concise is supported for computer-use-preview models and all reasoning models after gpt-5.
Optional[Literal["none", "minimal", "low", 3 more]]Constrains effort on reasoning for
reasoning models.
Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing
reasoning effort can result in faster responses and fewer tokens used
on reasoning in a response.
gpt-5.1 defaults to none, which does not perform reasoning. The supported reasoning values for gpt-5.1 are none, low, medium, and high. Tool calls are supported for all reasoning values in gpt-5.1.- All models before
gpt-5.1 default to medium reasoning effort, and do not support none.
- The
gpt-5-pro model defaults to (and only supports) high reasoning effort.
xhigh is supported for all models after gpt-5.1-codex-max.
Constrains effort on reasoning for
reasoning models.
Currently supported values are none, minimal, low, medium, high, and xhigh. Reducing
reasoning effort can result in faster responses and fewer tokens used
on reasoning in a response.
gpt-5.1defaults tonone, which does not perform reasoning. The supported reasoning values forgpt-5.1arenone,low,medium, andhigh. Tool calls are supported for all reasoning values in gpt-5.1.- All models before
gpt-5.1default tomediumreasoning effort, and do not supportnone. - The
gpt-5-promodel defaults to (and only supports)highreasoning effort. xhighis supported for all models aftergpt-5.1-codex-max.
class ResponseFormatJSONObject: …JSON object response format. An older method of generating JSON responses.
Using json_schema is recommended for models that support it. Note that the
model will not generate JSON without a system or user message instructing it
to do so.
JSON object response format. An older method of generating JSON responses.
Using json_schema is recommended for models that support it. Note that the
model will not generate JSON without a system or user message instructing it
to do so.
The type of response format being defined. Always json_object.
class ResponseFormatJSONSchema: …JSON Schema response format. Used to generate structured JSON responses.
Learn more about Structured Outputs.
JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.
json_schema: JSONSchemaStructured Outputs configuration options, including a JSON Schema.
Structured Outputs configuration options, including a JSON Schema.
The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
A description of what the response format is for, used by the model to determine how to respond in the format.
The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.
Whether to enable strict schema adherence when generating the output.
If set to true, the model will always follow the exact schema defined
in the schema field. Only a subset of JSON Schema is supported when
strict is true. To learn more, read the Structured Outputs
guide.
The type of response format being defined. Always json_schema.
class ResponseFormatText: …Default response format. Used to generate text responses.
Default response format. Used to generate text responses.
The type of response format being defined. Always text.
class ResponseFormatTextGrammar: …A custom grammar for the model to follow when generating text.
Learn more in the custom grammars guide.
A custom grammar for the model to follow when generating text. Learn more in the custom grammars guide.
The custom grammar for the model to follow.
The type of response format being defined. Always grammar.
class ResponseFormatTextPython: …Configure the model to generate valid Python code. See the
custom grammars guide for more details.
Configure the model to generate valid Python code. See the custom grammars guide for more details.
The type of response format being defined. Always python.