agentlab.llm.chat_api

Functions

`handle_error`(error, itr, ...)
`make_assistant_message`(content)
`make_system_message`(content)
`make_user_message`(content)

Classes

`AzureChatModel`(model_name[, api_key, ...])
`AzureModelArgs`(model_name[, ...])	Serializable object for instantiating a generic chat model with an Azure model.
`ChatModel`(model_name[, api_key, ...])
`ChatModelArgs`(model_name[, ...])	Object added for backward compatibility with the old ChatModelArgs.
`CheatMiniWoBLLM`([wait_time])	For unit-testing purposes only.
`CheatMiniWoBLLMArgs`([wait_time])
`HuggingFaceURLChatModel`(model_name, ...[, ...])
`OpenAIChatModel`(model_name[, api_key, ...])
`OpenAIModelArgs`(model_name[, ...])	Serializable object for instantiating a generic chat model with an OpenAI model.
`OpenRouterChatModel`(model_name[, api_key, ...])
`OpenRouterModelArgs`(model_name[, ...])	Serializable object for instantiating a generic chat model with an OpenAI model.
`SelfHostedModelArgs`(model_name[, ...])	Serializable object for instantiating a generic chat model with a self-hosted model.

Exceptions

`OpenRouterError`
`RetryError`

class agentlab.llm.chat_api.AzureChatModel(model_name, api_key=None, deployment_name=None, temperature=0.5, max_tokens=100, max_retry=4, min_retry_wait_time=60): Bases: ChatModel

class agentlab.llm.chat_api.AzureModelArgs(model_name: str, max_total_tokens: int = None, max_input_tokens: int = None, max_new_tokens: int = None, temperature: float = 0.1, vision_support: bool = False, deployment_name: str = None)

Bases: BaseModelArgs

Serializable object for instantiating a generic chat model with an Azure model.

deployment_name: str = None

make_model()

class agentlab.llm.chat_api.ChatModel(model_name, api_key=None, temperature=0.5, max_tokens=100, max_retry=4, min_retry_wait_time=60, api_key_env_var=None, client_class=<class 'openai.OpenAI'>, client_args=None, pricing_func=None)

Bases: AbstractChatModel

get_stats()

class agentlab.llm.chat_api.ChatModelArgs(model_name: str, max_total_tokens: int = None, max_input_tokens: int = None, max_new_tokens: int = None, temperature: float = 0.1, vision_support: bool = False, model_path: str = None, model_url: str = None, model_size: str = None, training_total_tokens: int = None, hf_hosted: bool = False, is_model_operational: str = False, sliding_window: bool = False, n_retry_server: int = 4, infer_tokens_length: bool = False, shard_support: bool = True, extra_tgi_args: dict = None, tgi_image: str = None, info: dict = None)

Bases: BaseModelArgs

Object added for backward compatibility with the old ChatModelArgs.

extra_tgi_args: dict = None

hf_hosted: bool = False

infer_tokens_length: bool = False

info: dict = None

is_model_operational: str = False

make_model()

model_path: str = None

model_size: str = None

model_url: str = None

n_retry_server: int = 4

shard_support: bool = True

sliding_window: bool = False

tgi_image: str = None

training_total_tokens: int = None

vision_support: bool = False

class agentlab.llm.chat_api.CheatMiniWoBLLM(wait_time=0)

Bases: AbstractChatModel

For unit-testing purposes only. It only work with miniwob.click-test task.

class agentlab.llm.chat_api.CheatMiniWoBLLMArgs(wait_time: int = 0)

Bases: object

close_server()

make_model()

max_input_tokens = 8000

max_new_tokens = 128

max_total_tokens = 10240

model_name = 'test/cheat_miniwob_click_test'

prepare_server()

wait_time: int = 0

class agentlab.llm.chat_api.HuggingFaceURLChatModel(model_name: str, base_model_name: str, model_url: str, token: str | None = None, temperature: int | None = 0.1, max_new_tokens: int | None = 512, n_retry_server: int | None = 4): Bases: HFBaseChatModel

class agentlab.llm.chat_api.OpenAIChatModel(model_name, api_key=None, temperature=0.5, max_tokens=100, max_retry=4, min_retry_wait_time=60): Bases: ChatModel

class agentlab.llm.chat_api.OpenAIModelArgs(model_name: str, max_total_tokens: int = None, max_input_tokens: int = None, max_new_tokens: int = None, temperature: float = 0.1, vision_support: bool = False)

Bases: BaseModelArgs

Serializable object for instantiating a generic chat model with an OpenAI model.

make_model()

class agentlab.llm.chat_api.OpenRouterChatModel(model_name, api_key=None, temperature=0.5, max_tokens=100, max_retry=4, min_retry_wait_time=60): Bases: ChatModel

exception agentlab.llm.chat_api.OpenRouterError: Bases: OpenAIError

class agentlab.llm.chat_api.OpenRouterModelArgs(model_name: str, max_total_tokens: int = None, max_input_tokens: int = None, max_new_tokens: int = None, temperature: float = 0.1, vision_support: bool = False)

Bases: BaseModelArgs

Serializable object for instantiating a generic chat model with an OpenAI model.

make_model()

exception agentlab.llm.chat_api.RetryError: Bases: Exception

class agentlab.llm.chat_api.SelfHostedModelArgs(model_name: str, max_total_tokens: int = None, max_input_tokens: int = None, max_new_tokens: int = None, temperature: float = 0.1, vision_support: bool = False, model_url: str = None, token: str = None, backend: str = 'huggingface', n_retry_server: int = 4)

Bases: BaseModelArgs

Serializable object for instantiating a generic chat model with a self-hosted model.

backend: str = 'huggingface'

make_model()

model_url: str = None

n_retry_server: int = 4

token: str = None

agentlab.llm.chat_api.handle_error(error, itr, min_retry_wait_time, max_retry)

agentlab.llm.chat_api.make_assistant_message(content: str) → dict

agentlab.llm.chat_api.make_system_message(content: str) → dict

agentlab.llm.chat_api.make_user_message(content: str) → dict