[David Elner (delner)]

Adds a common recording layer that turns caller and agent audio into an aligned
session recording, exported progressively as attachments. This is the foundation
for the LiveKit integration and future Pipecat recording work.

An adapter supplies audio, its position in the conversation, and a capture policy:

from braintrust._audio.session import AudioSessionRecorder

recording = AudioSessionRecorder(
    session_span,
    sources=("caller", "agent"),
    allowed=can_record_audio,
)
recording.record(
    "caller", pcm,
    sample_rate_hz=24_000, channels=1, offset_ns=0,
)
await recording.finish()

The session accumulates timed recording segments with aligned audio channels:

session.input.audio
├─ part-0   00:00–01:00   caller | agent
└─ part-1   01:00–02:00   caller | agent

Design

flowchart LR
    P[Positioned PCM] --> R[Shared timeline / recorder]
    R --> W[Background normalization / encoding]
    W --> U[Attachment upload]
    U --> S[Session references + segment metadata]

Loading

• The AudioSessionRecorder maintains a timeline that is used to preserve silence, channel alignment and source identity across audio streams with different sample rates.
• PCM audio segments are progressively flushed as duration and byte thresholds are reached.
• Middleware applies encoding to the flushed PCM audio.
• When the session is finished, the remaining audio is drained.

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