Module livekit.agents.voice.report

Classes

class SessionReport (enable_recording: bool,
job_id: str,
room_id: str,
room: str,
options: AgentSessionOptions,
events: list[AgentEvent],
chat_history: ChatContext,
audio_recording_path: Path | None = None,
audio_recording_started_at: float | None = None,
duration: float | None = None,
started_at: float | None = None,
timestamp: float = <factory>)

Expand source code

@dataclass
class SessionReport:
    enable_recording: bool
    job_id: str
    room_id: str
    room: str
    options: AgentSessionOptions
    events: list[AgentEvent]
    chat_history: ChatContext
    audio_recording_path: Path | None = None
    audio_recording_started_at: float | None = None
    """Timestamp when the audio recording started"""
    duration: float | None = None
    started_at: float | None = None
    """Timestamp when the session started"""
    timestamp: float = field(default_factory=time.time)
    """Timestamp when the session report was created, typically at the end of the session"""

    def to_dict(self) -> dict:
        events_dict: list[dict] = []

        for event in self.events:
            if event.type == "metrics_collected":
                continue  # metrics are too noisy, Cloud is using the chat_history as the source of thruth

            events_dict.append(event.model_dump())

        return {
            "job_id": self.job_id,
            "room_id": self.room_id,
            "room": self.room,
            "events": events_dict,
            "audio_recording_path": (
                str(self.audio_recording_path.absolute()) if self.audio_recording_path else None
            ),
            "audio_recording_started_at": self.audio_recording_started_at,
            "options": {
                "allow_interruptions": self.options.allow_interruptions,
                "discard_audio_if_uninterruptible": self.options.discard_audio_if_uninterruptible,
                "min_interruption_duration": self.options.min_interruption_duration,
                "min_interruption_words": self.options.min_interruption_words,
                "min_endpointing_delay": self.options.min_endpointing_delay,
                "max_endpointing_delay": self.options.max_endpointing_delay,
                "max_tool_steps": self.options.max_tool_steps,
                "user_away_timeout": self.options.user_away_timeout,
                "min_consecutive_speech_delay": self.options.min_consecutive_speech_delay,
                "preemptive_generation": self.options.preemptive_generation,
            },
            "chat_history": self.chat_history.to_dict(exclude_timestamp=False),
            "timestamp": self.timestamp,
        }

SessionReport(enable_recording: 'bool', job_id: 'str', room_id: 'str', room: 'str', options: 'AgentSessionOptions', events: 'list[AgentEvent]', chat_history: 'ChatContext', audio_recording_path: 'Path | None' = None, audio_recording_started_at: 'float | None' = None, duration: 'float | None' = None, started_at: 'float | None' = None, timestamp: 'float' = )

Instance variables

var audio_recording_path : pathlib.Path | None

var audio_recording_started_at : float | None

Timestamp when the audio recording started

var chat_history : livekit.agents.llm.chat_context.ChatContext

var duration : float | None

var enable_recording : bool

var events : list[livekit.agents.voice.events.UserInputTranscribedEvent | livekit.agents.voice.events.UserStateChangedEvent | livekit.agents.voice.events.AgentStateChangedEvent | livekit.agents.voice.events.AgentFalseInterruptionEvent | livekit.agents.voice.events.MetricsCollectedEvent | livekit.agents.voice.events.ConversationItemAddedEvent | livekit.agents.voice.events.FunctionToolsExecutedEvent | livekit.agents.voice.events.SpeechCreatedEvent | livekit.agents.voice.events.ErrorEvent | livekit.agents.voice.events.CloseEvent]

var job_id : str

var options : livekit.agents.voice.agent_session.AgentSessionOptions

var room : str

var room_id : str

var started_at : float | None

Timestamp when the session started

var timestamp : float

Timestamp when the session report was created, typically at the end of the session

Methods

def to_dict(self) ‑> dict

Expand source code

def to_dict(self) -> dict:
    events_dict: list[dict] = []

    for event in self.events:
        if event.type == "metrics_collected":
            continue  # metrics are too noisy, Cloud is using the chat_history as the source of thruth

        events_dict.append(event.model_dump())

    return {
        "job_id": self.job_id,
        "room_id": self.room_id,
        "room": self.room,
        "events": events_dict,
        "audio_recording_path": (
            str(self.audio_recording_path.absolute()) if self.audio_recording_path else None
        ),
        "audio_recording_started_at": self.audio_recording_started_at,
        "options": {
            "allow_interruptions": self.options.allow_interruptions,
            "discard_audio_if_uninterruptible": self.options.discard_audio_if_uninterruptible,
            "min_interruption_duration": self.options.min_interruption_duration,
            "min_interruption_words": self.options.min_interruption_words,
            "min_endpointing_delay": self.options.min_endpointing_delay,
            "max_endpointing_delay": self.options.max_endpointing_delay,
            "max_tool_steps": self.options.max_tool_steps,
            "user_away_timeout": self.options.user_away_timeout,
            "min_consecutive_speech_delay": self.options.min_consecutive_speech_delay,
            "preemptive_generation": self.options.preemptive_generation,
        },
        "chat_history": self.chat_history.to_dict(exclude_timestamp=False),
        "timestamp": self.timestamp,
    }