Class swarmauri_standard.llms.OpenAIReasonModel.OpenAIReasonModel
swarmauri_standard.llms.OpenAIReasonModel.OpenAIReasonModel
OpenAIReasonModel(**data)
Bases: LLMBase
OpenAIReasonModel class for interacting with the OpenAI Reasoning Model language models API. This class provides synchronous and asynchronous methods to send conversation data to the model, receive predictions, and stream responses.
ATTRIBUTE | DESCRIPTION |
---|---|
api_key |
API key for authenticating requests to the Groq API.
TYPE:
|
allowed_models |
List of allowed model names that can be used.
TYPE:
|
name |
The default model name to use for predictions.
TYPE:
|
type |
The type identifier for this class.
TYPE:
|
timeout |
Timeout duration for API requests.
TYPE:
|
_BASE_URL |
Base URL for the OpenAI API.
TYPE:
|
_headers |
Headers for API requests.
TYPE:
|
Provider resources: https://platform.openai.com/docs/models
Initialize the OpenAIModel class with the provided data.
PARAMETER | DESCRIPTION |
---|---|
**data
|
Arbitrary keyword arguments containing initialization data.
TYPE:
|
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
api_key
instance-attribute
api_key
allowed_models
class-attribute
instance-attribute
allowed_models = [
"o3-deep-research-2025-06-26",
"o4-mini-deep-research-2025-06-26",
"o3-pro-2025-06-10",
"o3-2025-04-16",
"o4-mini-2025-04-16",
"o1-pro-2025-03-19",
"o1-mini",
"o1",
"o1-2024-12-17",
"o1-mini-2024-09-12",
"o3-mini",
"o3-mini-2025-01-31",
]
name
class-attribute
instance-attribute
name = 'o1-mini'
type
class-attribute
instance-attribute
type = 'OpenAIReasonModel'
timeout
class-attribute
instance-attribute
timeout = 600.0
model_config
class-attribute
instance-attribute
model_config = ConfigDict(
extra="allow", arbitrary_types_allowed=True
)
id
class-attribute
instance-attribute
id = Field(default_factory=generate_id)
members
class-attribute
instance-attribute
members = None
owners
class-attribute
instance-attribute
owners = None
host
class-attribute
instance-attribute
host = None
default_logger
class-attribute
default_logger = None
logger
class-attribute
instance-attribute
logger = None
version
class-attribute
instance-attribute
version = '0.1.0'
include_usage
class-attribute
instance-attribute
include_usage = True
BASE_URL
class-attribute
instance-attribute
BASE_URL = None
predict
predict(
conversation,
max_completion_tokens=256,
enable_json=False,
stop=None,
)
Generates a response from the model based on the given conversation.
PARAMETER | DESCRIPTION |
---|---|
conversation
|
Conversation object with message history.
TYPE:
|
max_completion_tokens
|
Maximum tokens for the model's response.
TYPE:
|
enable_json
|
Whether to format the response as JSON.
TYPE:
|
stop
|
List of stop sequences for response termination.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
Conversation
|
Updated conversation with the model's response.
TYPE:
|
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
apredict
async
apredict(
conversation,
max_completion_tokens=256,
enable_json=False,
stop=None,
)
Async method to generate a response from the model based on the given conversation.
PARAMETER | DESCRIPTION |
---|---|
conversation
|
Conversation object with message history.
TYPE:
|
max_completion_tokens
|
Maximum tokens for the model's response.
TYPE:
|
enable_json
|
Whether to format the response as JSON.
TYPE:
|
stop
|
List of stop sequences for response termination.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
Conversation
|
Updated conversation with the model's response.
TYPE:
|
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
get_allowed_models
get_allowed_models()
Queries the LLMProvider API endpoint to retrieve the list of allowed models.
RETURNS | DESCRIPTION |
---|---|
List[str]
|
List[str]: List of allowed model names. |
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
stream
stream(
conversation,
max_completion_tokens=256,
enable_json=False,
stop=None,
)
Not implemented.
PARAMETER | DESCRIPTION |
---|---|
conversation
|
Conversation object with message history.
TYPE:
|
max_completion_tokens
|
Maximum tokens for the model's response.
TYPE:
|
enable_json
|
Whether to format the response as JSON.
TYPE:
|
stop
|
List of stop sequences for response termination.
TYPE:
|
RAISES | DESCRIPTION |
---|---|
NotImplementedError
|
This method is not implemented. |
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
astream
async
astream(
conversation,
max_completion_tokens=256,
enable_json=False,
stop=None,
)
Not implemented.
PARAMETER | DESCRIPTION |
---|---|
conversation
|
Conversation object with message history.
TYPE:
|
max_completion_tokens
|
Maximum tokens for the model's response.
TYPE:
|
enable_json
|
Whether to format the response as JSON.
TYPE:
|
stop
|
List of stop sequences for response termination.
TYPE:
|
RAISES | DESCRIPTION |
---|---|
NotImplementedError
|
This method is not implemented. |
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
batch
batch(
conversations,
max_completion_tokens=256,
enable_json=False,
stop=None,
)
Not implemented.
PARAMETER | DESCRIPTION |
---|---|
conversations
|
List of conversations to process.
TYPE:
|
max_completion_tokens
|
Maximum tokens for the model's response.
TYPE:
|
enable_json
|
Whether to format the response as JSON.
TYPE:
|
stop
|
List of stop sequences for response termination.
TYPE:
|
RAISES | DESCRIPTION |
---|---|
NotImplementedError
|
This method is not implemented. |
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
abatch
async
abatch(
conversations,
max_completion_tokens=256,
enable_json=False,
stop=None,
)
Not implemented.
PARAMETER | DESCRIPTION |
---|---|
conversations
|
List of conversations to process.
TYPE:
|
max_completion_tokens
|
Maximum tokens for the model's response.
TYPE:
|
enable_json
|
Whether to format the response as JSON.
TYPE:
|
stop
|
List of stop sequences for response termination.
TYPE:
|
RAISES | DESCRIPTION |
---|---|
NotImplementedError
|
This method is not implemented. |
Source code in swarmauri_standard/llms/OpenAIReasonModel.py
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|
register_model
classmethod
register_model()
Decorator to register a base model in the unified registry.
RETURNS | DESCRIPTION |
---|---|
Callable
|
A decorator function that registers the model class.
TYPE:
|
Source code in swarmauri_base/DynamicBase.py
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|
register_type
classmethod
register_type(resource_type=None, type_name=None)
Decorator to register a subtype under one or more base models in the unified registry.
PARAMETER | DESCRIPTION |
---|---|
resource_type
|
The base model(s) under which to register the subtype. If None, all direct base classes (except DynamicBase) are used.
TYPE:
|
type_name
|
An optional custom type name for the subtype.
TYPE:
|
RETURNS | DESCRIPTION |
---|---|
Callable
|
A decorator function that registers the subtype.
TYPE:
|
Source code in swarmauri_base/DynamicBase.py
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|
model_validate_toml
classmethod
model_validate_toml(toml_data)
Validate a model from a TOML string.
Source code in swarmauri_base/TomlMixin.py
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|
model_dump_toml
model_dump_toml(
fields_to_exclude=None, api_key_placeholder=None
)
Return a TOML representation of the model.
Source code in swarmauri_base/TomlMixin.py
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|
model_validate_yaml
classmethod
model_validate_yaml(yaml_data)
Validate a model from a YAML string.
Source code in swarmauri_base/YamlMixin.py
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|
model_dump_yaml
model_dump_yaml(
fields_to_exclude=None, api_key_placeholder=None
)
Return a YAML representation of the model.
Source code in swarmauri_base/YamlMixin.py
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|
model_post_init
model_post_init(logger=None)
Assign a logger instance after model initialization.
Source code in swarmauri_base/LoggerMixin.py
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|
add_allowed_model
add_allowed_model(model)
Add a new model to the list of allowed models.
RAISES | DESCRIPTION |
---|---|
ValueError
|
If the model is already in the allowed models list. |
Source code in swarmauri_base/llms/LLMBase.py
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|
remove_allowed_model
remove_allowed_model(model)
Remove a model from the list of allowed models.
RAISES | DESCRIPTION |
---|---|
ValueError
|
If the model is not in the allowed models list. |
Source code in swarmauri_base/llms/LLMBase.py
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|