agentscope.models.openai_model module

Model wrapper for OpenAI models

class agentscope.models.openai_model.OpenAIWrapperBase(config_name: str, model_name: str | None = None, api_key: str | None = None, organization: str | None = None, client_args: dict | None = None, generate_args: dict | None = None, **kwargs: Any)[source]

Bases: ModelWrapperBase, ABC

The model wrapper for OpenAI API.

Response:

From https://platform.openai.com/docs/api-reference/chat/create

```json {

“id”: “chatcmpl-123”, “object”: “chat.completion”, “created”: 1677652288, “model”: “gpt-4o-mini”, “system_fingerprint”: “fp_44709d6fcb”, “choices”: [

{
“index”: 0, “message”: {

“role”: “assistant”, “content”: “Hello there, how may I assist you today?”,

}, “logprobs”: null, “finish_reason”: “stop”

}

], “usage”: {

“prompt_tokens”: 9, “completion_tokens”: 12, “total_tokens”: 21

}

Initialize the openai client.

Parameters:

config_name (str) – The name of the model config.
model_name (str, default None) – The name of the model to use in OpenAI API.
api_key (str, default None) – The API key for OpenAI API. If not specified, it will be read from the environment variable OPENAI_API_KEY.
organization (str, default None) – The organization ID for OpenAI API. If not specified, it will be read from the environment variable OPENAI_ORGANIZATION.
client_args (dict, default None) – The extra keyword arguments to initialize the OpenAI client.
generate_args (dict, default None) – The extra keyword arguments used in openai api generation, e.g. temperature, seed.

format(*args: Msg | Sequence[Msg]) → List[dict] | str[source]: Format the input string or dict into the format that the model API required.

class agentscope.models.openai_model.OpenAIChatWrapper(config_name: str, model_name: str | None = None, api_key: str | None = None, organization: str | None = None, client_args: dict | None = None, stream: bool = False, generate_args: dict | None = None, **kwargs: Any)[source]

Bases: OpenAIWrapperBase

The model wrapper for OpenAI’s chat API.

model_type: str = 'openai_chat': The type of the model wrapper, which is to identify the model wrapper class in model configuration.

deprecated_model_type: str = 'openai'

substrings_in_vision_models_names = ['gpt-4-turbo', 'vision', 'gpt-4o']: The substrings in the model names of vision models.

Initialize the openai client.

Parameters:

config_name (str) – The name of the model config.
model_name (str, default None) – The name of the model to use in OpenAI API.
api_key (str, default None) – The API key for OpenAI API. If not specified, it will be read from the environment variable OPENAI_API_KEY.
organization (str, default None) – The organization ID for OpenAI API. If not specified, it will be read from the environment variable OPENAI_ORGANIZATION.
client_args (dict, default None) – The extra keyword arguments to initialize the OpenAI client.
stream (bool, default False) – Whether to enable stream mode.
generate_args (dict, default None) – The extra keyword arguments used in openai api generation, e.g. temperature, seed.

static static_format(*args: Msg | Sequence[Msg], model_name: str) → List[dict][source]

A static version of the format method, which can be used without initializing the OpenAIChatWrapper object.

Parameters:

args (Union[Msg, Sequence[Msg]]) – The input arguments to be formatted, where each argument should be a Msg object, or a list of Msg objects. In distribution, placeholder is also allowed.
model_name (str) – The name of the model to use in OpenAI API.

Returns:

The formatted messages in the format that OpenAI Chat API required.

Return type:

List[dict]

format(*args: Msg | Sequence[Msg]) → List[dict][source]

Format the input string and dictionary into the format that OpenAI Chat API required.

Parameters:: args (Union[Msg, Sequence[Msg]]) – The input arguments to be formatted, where each argument should be a Msg object, or a list of Msg objects. In distribution, placeholder is also allowed.
Returns:: The formatted messages in the format that OpenAI Chat API required.
Return type:: List[dict]

config_name: str: The name of the model configuration.

model_name: str: The name of the model, which is used in model api calling.

class agentscope.models.openai_model.OpenAIDALLEWrapper(config_name: str, model_name: str | None = None, api_key: str | None = None, organization: str | None = None, client_args: dict | None = None, generate_args: dict | None = None, **kwargs: Any)[source]

Bases: OpenAIWrapperBase

The model wrapper for OpenAI’s DALL·E API.

Response:

Refer to https://platform.openai.com/docs/api-reference/images/create

```json {

“created”: 1589478378, “data”: [

{
“url”: “https://…”

}, {

“url”: “https://…”

}

]

model_type: str = 'openai_dall_e': The type of the model wrapper, which is to identify the model wrapper class in model configuration.

config_name: str: The name of the model configuration.

model_name: str: The name of the model, which is used in model api calling.

class agentscope.models.openai_model.OpenAIEmbeddingWrapper(config_name: str, model_name: str | None = None, api_key: str | None = None, organization: str | None = None, client_args: dict | None = None, generate_args: dict | None = None, **kwargs: Any)[source]

Bases: OpenAIWrapperBase

The model wrapper for OpenAI embedding API.

Response:

Refer to

https://platform.openai.com/docs/api-reference/embeddings/create

```json {

“object”: “list”, “data”: [

{
“object”: “embedding”, “embedding”: [

0.0023064255, -0.009327292, …. (1536 floats total for ada-002) -0.0028842222,

], “index”: 0

}

], “model”: “text-embedding-ada-002”, “usage”: {

“prompt_tokens”: 8, “total_tokens”: 8

}

model_type: str = 'openai_embedding': The type of the model wrapper, which is to identify the model wrapper class in model configuration.

config_name: str: The name of the model configuration.

model_name: str: The name of the model, which is used in model api calling.