Agents模块

set_default_openai_key

set_default_openai_key(
    key: str, use_for_tracing: bool = True
) -> None

设置默认的OpenAI API密钥用于LLM请求（可选追踪）。只有在OPENAI_API_KEY环境变量未设置时才需要此操作。

如果提供，将使用此密钥而非OPENAI_API_KEY环境变量。

参数:

名称	类型	描述	默认值
`key`	`str`	使用的OpenAI密钥。	required
`use_for_tracing`	`bool`	是否也使用此密钥向OpenAI发送追踪数据。默认为True 如果设为False，您需要设置OPENAI_API_KEY环境变量或调用 set_tracing_export_api_key()函数并传入您想用于追踪的API密钥。	`True`

Source code in src/agents/__init__.py

def set_default_openai_key(key: str, use_for_tracing: bool = True) -> None:
    """Set the default OpenAI API key to use for LLM requests (and optionally tracing(). This is
    only necessary if the OPENAI_API_KEY environment variable is not already set.

    If provided, this key will be used instead of the OPENAI_API_KEY environment variable.

    Args:
        key: The OpenAI key to use.
        use_for_tracing: Whether to also use this key to send traces to OpenAI. Defaults to True
            If False, you'll either need to set the OPENAI_API_KEY environment variable or call
            set_tracing_export_api_key() with the API key you want to use for tracing.
    """
    _config.set_default_openai_key(key, use_for_tracing)

set_default_openai_client

set_default_openai_client(
    client: AsyncOpenAI, use_for_tracing: bool = True
) -> None

设置用于LLM请求和/或追踪的默认OpenAI客户端。如果提供，该客户端将替代默认的OpenAI客户端使用。

参数:

名称	类型	描述	默认值
`client`	`AsyncOpenAI`	要使用的OpenAI客户端。	required
`use_for_tracing`	`bool`	是否使用此客户端的API密钥上传追踪数据。如果设为False，您需要设置OPENAI_API_KEY环境变量，或者调用 set_tracing_export_api_key()函数并传入您想用于追踪的API密钥。	`True`

Source code in src/agents/__init__.py

def set_default_openai_client(client: AsyncOpenAI, use_for_tracing: bool = True) -> None:
    """Set the default OpenAI client to use for LLM requests and/or tracing. If provided, this
    client will be used instead of the default OpenAI client.

    Args:
        client: The OpenAI client to use.
        use_for_tracing: Whether to use the API key from this client for uploading traces. If False,
            you'll either need to set the OPENAI_API_KEY environment variable or call
            set_tracing_export_api_key() with the API key you want to use for tracing.
    """
    _config.set_default_openai_client(client, use_for_tracing)

set_default_openai_api

set_default_openai_api(
    api: Literal["chat_completions", "responses"],
) -> None

设置用于OpenAI LLM请求的默认API。默认情况下，我们将使用响应API，但您可以将其设置为使用聊天补全API。

Source code in src/agents/__init__.py

def set_default_openai_api(api: Literal["chat_completions", "responses"]) -> None:
    """Set the default API to use for OpenAI LLM requests. By default, we will use the responses API
    but you can set this to use the chat completions API instead.
    """
    _config.set_default_openai_api(api)

set_tracing_export_api_key

set_tracing_export_api_key(api_key: str) -> None

为后端导出器设置OpenAI API密钥。

Source code in src/agents/tracing/__init__.py

def set_tracing_export_api_key(api_key: str) -> None:
    """
    Set the OpenAI API key for the backend exporter.
    """
    default_exporter().set_api_key(api_key)

set_tracing_disabled

set_tracing_disabled(disabled: bool) -> None

设置是否全局禁用追踪。

Source code in src/agents/tracing/__init__.py

def set_tracing_disabled(disabled: bool) -> None:
    """
    Set whether tracing is globally disabled.
    """
    GLOBAL_TRACE_PROVIDER.set_disabled(disabled)

set_trace_processors

set_trace_processors(
    processors: list[TracingProcessor],
) -> None

设置跟踪处理器列表。这将替换当前的处理器列表。

Source code in src/agents/tracing/__init__.py

def set_trace_processors(processors: list[TracingProcessor]) -> None:
    """
    Set the list of trace processors. This will replace the current list of processors.
    """
    GLOBAL_TRACE_PROVIDER.set_processors(processors)

enable_verbose_stdout_logging

enable_verbose_stdout_logging()

启用详细日志输出到标准输出。这对调试很有帮助。

Source code in src/agents/__init__.py

def enable_verbose_stdout_logging():
    """Enables verbose logging to stdout. This is useful for debugging."""
    logger = logging.getLogger("openai.agents")
    logger.setLevel(logging.DEBUG)
    logger.addHandler(logging.StreamHandler(sys.stdout))