Batch logging - CoreWeave Docs

Access these through the tracing module:

from coreweave.forge.agentlens import tracing

log_turn

def log_turn(
    *,
    conversation_id: str,
    agent_name: str = '',
    conversation_name: str = '',
    model: str = '',
    agent_id: str = '',
    agent_description: str = '',
    agent_version: str = '',
    messages: Union[list[Message], None] = None,
    output_messages: Union[list[Message], None] = None,
    system_instructions: Union[list[str], None] = None,
    spans: Union[list[Union[LLM, Tool, SubAgent]], None] = None,
    started_at: Union[datetime, None] = None,
    ended_at: Union[datetime, None] = None,
    include_content: bool = True,
    continue_parent_trace: bool = False,
    attributes: Attributes = None,
) -> LogResult: ...

Imperatively emit one turn and its child spans to OTel. Use when context managers aren’t viable (stateless containers, callbacks, queue workers). Each child span passed in should have started_at / ended_at set; the emitted OTel span timestamps come from those fields. Falls back to the earliest/latest child timestamp, then now(), when the turn doesn’t supply its own. agent_id / agent_description / agent_version mirror the streaming path. attributes are stamped on every emitted span; the streaming path reads these from the active conversation instead. Use custom, non-semconv keys: a key that collides with a span’s own gen_ai.* / weave.* attribute is unsupported (which value wins is path-dependent). messages records the turn input and output_messages records the terminal agent response on the same invoke_agent span.

log_conversation

def log_conversation(
    *,
    turns: list[Turn],
    conversation_id: str = '',
    conversation_name: str = '',
    agent_name: str = '',
    model: str = '',
    agent_id: str = '',
    agent_description: str = '',
    agent_version: str = '',
    include_content: bool = True,
    continue_parent_trace: bool = False,
    attributes: Attributes = None,
) -> LogResult: ...

Imperatively emit a complete conversation. Each Turn’s .spans attribute provides its children. Auto-generates conversation_id if empty. By default each turn gets its own OTel trace. agent_name / model / agent_id / agent_description / agent_version are conversation-level defaults. A Turn’s own value wins; the conversation value only fills in when the Turn leaves it empty. The conversation’s continue_parent_trace applies to every turn and supersedes the per-Turn value. attributes are stamped on every emitted span. Use custom, non-semconv keys: a key that collides with a span’s own gen_ai.* / weave.* attribute is unsupported (which value wins is path-dependent).

LogResult

class LogResult(BaseModel): ...

Result of a batch log_* call. LogResult is a Pydantic model. Set any field below as a keyword argument when you construct it. Fields

Field	Type	Default
`conversation_id`	`str`	`''`
`trace_ids`	`list[str]`	`[]`
`root_span_ids`	`list[str]`	`[]`
`span_count`	`int`	`0`

​log_turn

​log_conversation

​LogResult

log_turn

log_conversation

LogResult