inspect_ai.event

Transcript events.

Core Events

ModelEvent

Call to a language model.

class ModelEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['model']: Event type.
model str: Model name.
role str | None: Model role.
input list[ChatMessage]: Model input (list of messages).
input_refs list[tuple[int, int]] | None: Message pool references for input. Each element is a (start, end_exclusive) range.
tools list[ToolInfo]: Tools available to the model.
tool_choice ToolChoice: Directive to the model which tools to prefer.
config GenerateConfig: Generate config used for call to model.
output ModelOutput: Output from model.
retries int | None: Retries for the model API request.
error str | None: Error which occurred during model call.
traceback str | None: Error traceback (plain text).
traceback_ansi str | None: Error traceback with ANSI color codes for display.
cache Literal['read', 'write'] | None: Was this a cache read or write.
call ModelCall | None: Raw call made to model API.
completed UtcDatetime | None: Time that model call completed (see timestamp for started)
working_time float | None: working time for model call that succeeded (i.e. was not retried).

ToolEvent

Call to a tool.

Source

class ToolEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['tool']: Event type.
type Literal['function']: Type of tool call (currently only ‘function’)
id str: Unique identifier for tool call.
function str: Function called.
arguments dict[str, JsonValue]: Arguments to function.
view ToolCallContent | None: Custom view of tool call input.
result ToolResult: Function return value.
truncated tuple[int, int] | None: Bytes truncated (from,to) if truncation occurred
error ToolCallError | None: Error that occurred during tool call.
completed UtcDatetime | None: Time that tool call completed (see timestamp for started)
working_time float | None: Working time for tool call (i.e. time not spent waiting on semaphores).
agent str | None: Name of agent if the tool call was an agent handoff.
agent_span_id str | None: Span ID of the agent span, if this tool call spawned an agent.
failed bool | None: Did the tool call fail with a hard error?.
message_id str | None: Id of ChatMessageTool associated with this event.
cancelled bool: Was the task cancelled?

BranchEvent

Marks where a branched trajectory’s unique content begins.

Emitted at the point where a branch transitions from replaying its parent’s prefix to live execution. Events before this in the trajectory’s span are replay-phase re-execution; events after are the branch’s genuine new content.

Source

class BranchEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['branch']: Event type.
from_anchor str: Anchor at the branch point (matches an AnchorEvent.anchor_id in the parent).

CompactionEvent

Compaction of conversation history.

Source

class CompactionEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['compaction']: Event type.
type Literal['summary', 'edit', 'trim']: Compaction type.
tokens_before int | None: Tokens before compaction.
tokens_after int | None: Tokens after compaction.
source str | None: Compaction source (e.g. ‘inspect’, ‘claude_code’, etc.)

ApprovalEvent

Tool approval.

Source

class ApprovalEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['approval']: Event type
message str: Message generated by model along with tool call.
call ToolCall: Tool call being approved.
view ToolCallView | None: View presented for approval.
approver str: Aprover name.
decision Literal['approve', 'modify', 'reject', 'escalate', 'terminate']: Decision of approver.
modified ToolCall | None: Modified tool call for decision ‘modify’.
explanation str | None: Explanation for decision.

SandboxEvent

Sandbox execution or I/O

Source

class SandboxEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['sandbox']: Event type
action Literal['exec', 'read_file', 'write_file']: Sandbox action
cmd str | None: Command (for exec)
options dict[str, JsonValue] | None: Options (for exec)
file str | None: File (for read_file and write_file)
input str | None: Input (for cmd and write_file). Truncated to 100 lines.
result int | None: Result (for exec)
output str | None: Output (for exec and read_file). Truncated to 100 lines.
completed UtcDatetime | None: Time that sandbox action completed (see timestamp for started)

InfoEvent

Event with custom info/data.

Source

class InfoEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['info']: Event type.
source str | None: Optional source for info event.
data JsonValue: Data provided with event.

ScoreEvent

Event with score.

Can be the final score for a Sample, or can be an intermediate score resulting from a call to score.

Source

class ScoreEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['score']: Event type.
score Score: Score value.
target str | list[str] | None: “Sample target.
intermediate bool: Was this an intermediate scoring?
scorer str | None: Name of the scorer that produced this score (unique within the task).
scorer_args dict[str, Any] | None: Arguments the scorer was instantiated with (None for scores set directly by a solver via state.scores).
model_usage dict[str, ModelUsage] | None: Cumulative model usage at the time of this score.
role_usage dict[str, ModelUsage] | None: Cumulative model usage by role at the time of this score.

LoggerEvent

Log message recorded with Python logger.

Source

class LoggerEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['logger']: Event type.
message LoggingMessage: Logging message

ErrorEvent

Event with sample error.

Source

class ErrorEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['error']: Event type.
error EvalError: Sample error

SpanBeginEvent

Mark the beginning of a transcript span.

Source

class SpanBeginEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['span_begin']: Event type.
id str: Unique identifier for span.
parent_id str | None: Identifier for parent span.
type str | None: Optional ‘type’ field for span.
name str: Span name.

SpanEndEvent

Mark the end of a transcript span.

Source

class SpanEndEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['span_end']: Event type.
id str: Unique identifier for span.

Event Tree

event_tree

Build a tree representation of a sequence of events.

Organize events heirarchially into event spans.

Source

def event_tree(events: Sequence[Event]) -> EventTree

events Sequence[Event]: Sequence of Event.

event_tree_walk

Walk an event tree yielding nodes matching a filter.

Source

def event_tree_walk(
    tree: EventTree,
    filter: type[T]
    | tuple[type[T], ...]
    | Callable[[EventTreeNode], bool]
    | None = None,
) -> Iterable[T] | Iterable[EventTreeNode]

tree EventTree: Event tree to walk.
filter type[T] | tuple[type[T], ...] | Callable[[EventTreeNode], bool] | None: A type, tuple of types (passed to isinstance), a predicate function, or None to yield all nodes.

event_sequence

Flatten a span forest back into a properly ordered seqeunce.

Source

def event_sequence(tree: EventTree | EventTreeSpan) -> Iterable[Event]

tree EventTree | EventTreeSpan: Event tree or EventTreeSpan.

EventTree

Tree of events (has invividual events and event spans).

Source

EventTree: TypeAlias = list[EventTreeNode]

EventTreeSpan

Event tree node representing a span of events.

Source

@dataclass
class EventTreeSpan

Attributes

id str: Span id.
parent_id str | None: Parent span id.
type str | None: Optional ‘type’ field for span.
name str: Span name.
begin SpanBeginEvent: Span begin event.
end SpanEndEvent | None: Span end event (if any).
children list[EventTreeNode]: Children in the span.

EventTreeNode

Node in an event tree.

Source

EventTreeNode: TypeAlias = Union["EventTreeSpan", Event]

Timeline

timeline_build

Build a Timeline from a flat event list.

Transforms a flat event stream into a hierarchical Timeline tree with agent-centric interpretation. The pipeline has two phases:

Phase 1 — Structure extraction:

Uses event_tree() to parse span_begin/span_end events into a tree, then looks for top-level phase spans (“init”, “solvers”, “scorers”):

If present, partitions events into init (setup), agent (solvers), and scoring sections.
If absent, treats the entire event stream as the agent.

Phase 2 — Agent classification:

Within the agent section, spans are classified as agents or unrolled:

============================== ======================================= Span type Result ============================== ======================================= type="agent" TimelineSpan(span_type="agent") type="solver" TimelineSpan(span_type="agent") type="tool" + ModelEvents TimelineSpan(span_type="agent") ToolEvent with agent field TimelineSpan(span_type="agent") type="tool" (no models) Unrolled into parent Any other span type Unrolled into parent ============================== =======================================

“Unrolled” means the span wrapper is removed and its child events dissolve into the parent’s content list.

Phase 3 — Post-processing passes:

Utility agent classification (single-turn agents with different system prompts)

Source

def timeline_build(
    events: list[Event], *, name: str | None = None, description: str | None = None
) -> Timeline

events list[Event]: Flat list of Events from a transcript.
name str | None: Optional name for timeline (defaults to “Default”)
description str | None: Optional description for timeline (defaults to ““)

timeline_dump

Serialize a Timeline to a JSON-compatible dict.

Converts a Timeline into a plain dictionary suitable for JSON serialization. Event objects within the timeline are replaced by their UUIDs, keeping the serialized form compact and self-referencing.

Source

def timeline_dump(timeline: Timeline) -> dict[str, Any]

timeline Timeline: The Timeline to serialize.

timeline_filter

Return a new timeline with only spans matching the predicate.

Recursively walks the span tree, keeping TimelineSpan items where predicate(span) returns True. Non-matching spans and their entire subtrees are pruned. TimelineEvent items are always kept (they belong to the parent span).

Use this to pre-filter a timeline before passing it to timeline_messages().

Source

def timeline_filter(
    timeline: Timeline,
    predicate: Callable[[TimelineSpan], bool],
) -> Timeline

timeline Timeline: The timeline to filter.
predicate Callable[[TimelineSpan], bool]: Function that receives a TimelineSpan and returns True to keep it (and its subtree), False to prune it.

timeline_load

Deserialize a Timeline from a dict produced by timeline_dump.

Reconstructs a full Timeline by resolving the UUID strings stored in data back to their corresponding Event objects from events.

Source

def timeline_load(data: dict[str, Any], events: list[Event]) -> Timeline

data dict[str, Any]: A dict previously produced by timeline_dump.
events list[Event]: The flat list of Event objects whose UUIDs appear in data. Events without a UUID are ignored.

timeline_branch

Context manager for creating a timeline branch.

Emits an AnchorEvent in the current (parent) span so the viewer can resolve from_anchor to a position, then opens a type="branch" span and emits a BranchEvent inside it.

Source

@contextlib.asynccontextmanager
async def timeline_branch(
    *, name: str, from_anchor: str, id: str | None = None
) -> AsyncIterator[None]

name str: Name of branch span.
from_anchor str: Anchor id at the branch point.
id str | None: Optional span ID. Generated if not provided.

Timeline

A named timeline view over a transcript.

Multiple timelines allow different interpretations of the same event stream — e.g. a default agent-centric view alongside an alternative grouping or filtered view.

Source

class Timeline(BaseModel)

Methods

render

Render an ASCII swimlane diagram of the timeline.

Source

def render(self, width: int | None = None) -> str

width int | None: Total width of the output in characters. Defaults to 120.

TimelineEvent

Wraps a single Event.

Source

class TimelineEvent(BaseModel)

Methods

start_time

Event timestamp (required field on all events).

Source

def start_time(self) -> datetime

end_time

Event completion time if available, else timestamp.

Source

def end_time(self) -> datetime

total_tokens

Tokens from this event (ModelEvent only).

Includes input_tokens_cache_read and input_tokens_cache_write in the total, as these represent actual token consumption for any LLM system using prompt caching. The sum of all token fields provides an accurate measure of total context window usage across all sources.

Source

def total_tokens(self) -> int

idle_time

Seconds of idle time (always 0 for a single event).

Source

def idle_time(self) -> float

TimelineSpan

A span of execution — agent, scorer, tool, or root.

Source

class TimelineSpan(BaseModel)

Attributes

tool_invoked bool

True if this agent span was invoked as a tool (via task/as_tool/handoff).

Tool-invoked subagents are explicit user-intended sub-trajectories and are never classified as utility regardless of turn count or prompt differences. The _classify_utility_agents heuristic targets internal helper model calls, not explicit subagent invocations.

Methods

start_time

Earliest start time among content (and optionally branches).

Source

def start_time(self, include_branches: bool = True) -> datetime

include_branches bool: Include branches in time calcluation.

end_time

Latest end time among content (and optionally branches).

Source

def end_time(self, include_branches: bool = True) -> datetime

include_branches bool: Include branches in time calcluation.

total_tokens

Sum of tokens from content (and optionally branches).

Source

def total_tokens(self, include_branches: bool = True) -> int

include_branches bool: Include branches in token calcluation.

idle_time

Seconds of idle time within this span (and optionally branches).

Source

def idle_time(self, include_branches: bool = True) -> float

include_branches bool: Include branches in time calcluation.

Outline

Hierarchical outline of events for an agent.

Source

class Outline(BaseModel)

OutlineNode

A node in an agent’s outline, referencing an event by UUID.

Source

class OutlineNode(BaseModel)

Eval Events

SampleInitEvent

Beginning of processing a Sample.

Source

class SampleInitEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['sample_init']: Event type.
sample Sample: Sample.
state JsonValue: Initial state.

SampleLimitEvent

The sample was unable to finish processing due to a limit

Source

class SampleLimitEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['sample_limit']: Event type.
type Literal['message', 'time', 'working', 'token', 'cost', 'operator', 'custom']: Type of limit that halted processing
message str: A message associated with this limit
limit float | None: The limit value (if any)

StateEvent

Change to the current TaskState

Source

class StateEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['state']: Event type.
changes list[JsonChange]: List of changes to the TaskState

StoreEvent

Change to data within the current Store.

Source

class StoreEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['store']: Event type.
changes list[JsonChange]: List of changes to the Store.

InputEvent

Input screen interaction.

Source

class InputEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['input']: Event type.
input str: Input interaction (plain text).
input_ansi str: Input interaction (ANSI).

ScoreEditEvent

Event recorded when a score is edited.

Source

class ScoreEditEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['score_edit']: Event type.
score_name str: Name of the score being edited.
edit ScoreEdit: The edit being applied to the score.

InterruptEvent

Records that an agent’s turn or sample was cut short.

Emitted in three cases:

source="user_cancel" — an ACP client (e.g. an editor or TUI) called session/cancel while a turn was in flight.
source="limit" — a sample-level limit (tokens, time, cost, messages) tripped during execution.
source="system" — the eval is shutting down for an external reason and is cancelling active samples.

The interrupted field records what was running at the moment the cancel reached the cancel scope. interrupted_tool_call_id and interrupted_model_event_id give cross-references when applicable so downstream consumers can correlate this event with the in-flight ToolEvent or ModelEvent.

Source

class InterruptEvent(BaseEvent)

Attributes

uuid str | None: Unique identifer for event.
span_id str | None: Span the event occurred within.
timestamp UtcDatetime: Clock time at which event occurred.
working_start float: Working time (within sample) at which the event occurred.
metadata dict[str, Any] | None: Additional event metadata.
pending bool | None: Is this event pending?
event Literal['interrupt']: Event type.
source Literal['user_cancel', 'limit', 'system']: What caused the interrupt.
interrupted Literal['generate', 'tool_call', 'between_turns']: What was running at the moment of the interrupt.
interrupted_tool_call_id str | None: ToolEvent.id (the underlying ToolCall.id) of the in-flight tool, if any.
interrupted_model_event_id str | None: ModelEvent.uuid of the in-flight model call, if any.

Types

LoggingLevel

Logging level.

Source

LoggingLevel = Literal[
    "debug", "trace", "http", "sandbox", "info", "warning", "error", "critical"
]

LoggingMessage

Message written to Python log.

Source

class LoggingMessage(BaseModel)

Attributes

name str | None: Logger name (e.g. ‘httpx’)
level LoggingLevel: Logging level.
message str: Log message.
created float: Message created time.
filename str: Logged from filename.
module str: Logged from module.
lineno int: Logged from line number.