LLMConfig - AG2

LLMConfig

``autogen.LLMConfig [

LLMConfig(*configs, top_p=None, temperature=None, max_tokens=None, check_every_ms=None, allow_format_str_template=None, response_format=None, timeout=None, seed=None, cache_seed=None, parallel_tool_calls=None, tools=(), functions=(), routing_method=None, config_list=(), **kwargs)

Initializes the LLMConfig object.

PARAMETER DESCRIPTION
*configs A list of LLM configuration entries or dictionaries.
TYPE:ConfigItemDEFAULT:()
config_list A list of LLM configuration entries or dictionaries.
TYPE:`Iterable[ConfigItem]
temperature The sampling temperature for LLM generation.
TYPE:`float
check_every_ms The interval (in milliseconds) to check for updates
TYPE:`int
allow_format_str_template Whether to allow format string templates.
TYPE:`bool
response_format The format of the response (e.g., JSON, text).
TYPE:`str
timeout The timeout for LLM requests in seconds.
TYPE:`int
seed The random seed for reproducible results.
TYPE:`int
cache_seed The seed for caching LLM responses.
TYPE:`int
parallel_tool_calls Whether to enable parallel tool calls.
TYPE:`bool
tools A list of tools available for the LLM.
TYPE:Iterable[Any]DEFAULT:()
functions A list of functions available for the LLM.
TYPE:Iterable[Any]DEFAULT:()
max_tokens The maximum number of tokens to generate.
TYPE:`int
top_p The nucleus sampling probability.
TYPE:`float
routing_method The method used to route requests (e.g., fixed_order, round_robin).
TYPE:`Literal['fixed_order', 'round_robin']
**kwargs Additional keyword arguments for future extensions.
TYPE:AnyDEFAULT:{}

Examples:

# Example 1: create config from one model dictionary
config = LLMConfig({
    "model": "gpt-5-mini",
    "api_key": os.environ["OPENAI_API_KEY"],
})

# Example 2: create config from list of dictionaries
config = LLMConfig(
    {
        "model": "gpt-5-mini",
        "api_key": os.environ["OPENAI_API_KEY"],
    },
    {
        "model": "gpt-4",
        "api_key": os.environ["OPENAI_API_KEY"],
    },
)

# Example 3 (deprecated): create config from `kwargs` options
config = LLMConfig(
    model="gpt-5-mini",
    api_key=os.environ["OPENAI_API_KEY"],
)

# Example 4 (deprecated): create config from `config_list` dictionary
config = LLMConfig(
    config_list={
        "model": "gpt-5-mini",
        "api_key": os.environ["OPENAI_API_KEY"],
    }
)

# Example 5 (deprecated): create config from `config_list` list
config = LLMConfig(
    config_list=[
        {
            "model": "gpt-5-mini",
            "api_key": os.environ["OPENAI_API_KEY"],
        },
        {
            "model": "gpt-5",
            "api_key": os.environ["OPENAI_API_KEY"],
        },
    ]
)

``config_listinstance-attribute

config_list

``ensure_configclassmethod

ensure_config(config)

Transforms passed objects to LLMConfig object.

Method to use for Agent(llm_config={...}) cases.

LLMConfig.ensure_config(LLMConfig(...)) LLMConfig(...) LLMConfig.ensure_config(LLMConfigEntry(...)) LLMConfig(LLMConfigEntry(...)) LLMConfig.ensure_config({"model": "gpt-o3"}) LLMConfig(OpenAILLMConfigEntry(model="o3")) LLMConfig.ensure_config([{"model": "gpt-o3"}, ...]) LLMConfig(OpenAILLMConfigEntry(model="o3"), ...) (deprecated) LLMConfig.ensure_config({"config_list": [{ "model": "gpt-o3" }, ...]}) LLMConfig(OpenAILLMConfigEntry(model="o3"), ...)

``get_current_llm_configclassmethod

get_current_llm_config(llm_config=None)

``from_jsonclassmethod

from_json(*, env=None, path=None, file_location=None, filter_dict=None, **kwargs)

where

where(*, exclude=False, **kwargs)

model_dump

model_dump(*args, exclude_none=True, **kwargs)

model_dump_json

model_dump_json(*args, exclude_none=True, **kwargs)

model_validate

model_validate(*args, **kwargs)

model_validate_json

model_validate_json(*args, **kwargs)

model_validate_strings

model_validate_strings(*args, **kwargs)

get

get(key, default=None)

copy

copy()

deepcopy

deepcopy(memo=None)

items

items()

keys

keys()

values

values()