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braidio

Weave commentary — solo, duo, panel, debate, interview, documentary — with source clips into a production.

braidio braids the strands of a piece that talks about something (a song, a book, a film, an event) into one rendered production. The talk is the spine — a single presenter, two hosts, a panel, a narrator — and source clips and narration bridges are the "illustration" layers woven onto it. Audio today, with visual support to follow (it braids A/V — braid-io, and it sounds like radio).

Two things braidio gives you:

  1. Ready-made format templates under the standard, industry names people already recognize — Deep Dive, Song Exploder-style, Panel, Debate, Documentary VO — each a high-quality bundle of defaults you can render in one call.
  2. Full parametrization underneath, so any style is expressible: a Script of beats, cast via a ConversationCast, tuned by WeaveConfig + Delivery, with per-beat voice/delivery overrides.

Status: early. braidio is extracted from the Hamilton lyrics-podcast (its first application) into a reusable engine. APIs will move quickly.

The model

A production is a Script — an ordered list of beats:

Beat What it is
Narration(text, voice?, voice_settings?, …) one voice reading — a narrator or a solo presenter. voice / voice_settings override per beat, so one timeline can carry a lively presenter and a graver book-narrator.
Dialogue(turns=[(role, text)]) a multi-speaker exchange, synthesized in one pass (so it sounds like people talking to each other, not alternating monologues). A ConversationCast maps roles → voices.
SegmentBeat(reference) a span of source media to cut and weave in (resolved by a pluggable SegmentSource — quote → [start, end]).

WeaveConfig holds every editing knob (casting, turns, pacing, clip pre/post-roll, duck, crossfades, loudness). Delivery presets bundle the TTS model + voice settings (e.g. V2_PRESENTER lively vs V2_NARRATOR grave). The renderer loudness-normalizes every part, tucks clips under the speech (speech stays dominant), and masters the result.

Ready-made formats

Pick a standard format and render it — the template supplies the cast, voices, delivery and mix defaults:

from braidio import DEEP_DIVE, render_format

render_format(DEEP_DIVE, script, source=my_source, out_path="episode.mp3")
Preset id Standard name Shape
solo_explainer Solo-Presenter Explainer (video/audio essay, close reading) one presenter + exhibits
deep_dive Two-Host Conversation ("Deep Dive", Switched on Pop, NotebookLM) two hosts; one teaches, one probes
interview Interview (host + guest) Q→A, guest is the center
interview_host_removed Song Exploder-style (host removed) guest monologue; each claim illustrated by its isolated stem; full artifact at the tail
panel Panel / Roundtable (Pop Culture Happy Hour) moderator routes distinct voices
debate Debate (Oxford-style) proposition / opposition / moderator, phased
documentary_vo Documentary Voice-Over ("Voice of God", This American Life) narrator on top; interviews + clips + actuality beneath

Narration bridges and source clips are optional illustration layers usable with any format. The taxonomy, weaving grammar, exemplar recipes and the full template specs are in misc/docs/research/commentary-formats-and-styles.md.

Render support note: the cast, per-role voices, narration deliveries, loudness master, per-clip placementSegmentBeat(placement="before" | "under" | "after"), where under lays the clip concurrently beneath the talk, ducked — and a music bed (MusicBed, an app-supplied instrumental laid under the whole production) are applied today. Scene stings and fade-to-spotlight (dropping the bed before a key exhibit) remain on the render-side roadmap (braidio#1).

Parametrize anything

The templates are just good defaults over the primitives — compose directly for full control:

from braidio import Script, Dialogue, Narration, SegmentBeat, WeaveConfig
from braidio.conversation import ConversationCast, JESSICA, CHRIS
from braidio import V2_NARRATOR, render_production

script = Script(
    title="…",
    id_slug="01",
    beats=[
        Dialogue(
            (("A", "First thing that gets me…"), ("B", "right — but isn't that…"))
        ),
        SegmentBeat("the lyric being discussed", label="hook"),
        Narration(
            "Here's how the book tells it —", voice_settings=V2_NARRATOR.voice_settings
        ),  # graver, per-beat
    ],
)
render_production(
    script,
    source=my_source,
    cast=ConversationCast(roles={"A": JESSICA, "B": CHRIS}),
    config=WeaveConfig(),
    out_path="out.mp3",
)

Cost tracking

ElevenLabs TTS is braidio's only spend (everything else is local ffmpeg). braidio.estimate_cost(script) previews a production's cost before you pay for synthesis, and real renders attribute a per-character cost onto their artifacts. Dollars are a rate estimate — set your ElevenLabs plan's rate for exact figures:

Env var Meaning
BRAIDIO_TTS_USD_PER_1K_CHARS USD per 1000 characters. Unset → a conservative default; none → mark spend unpriced (character counts still reported, dollars None).
BRAIDIO_TTS_VOICE Default ElevenLabs voice id for narration.

What it deliberately does not do

braidio is a thin orchestration layer. It delegates:

Concern Owner
Content acquisition (Genius, audiobooks, news…) the consuming app, via SegmentSource adapters
Linked-artifact graph / content-addressed media lacing
Project workflow, provenance, plan/execute, partial re-render nw
Video render + visual support reelee
Raw audio DSP + TTS (crop, concat, duck, loudnorm, synth) mixing / falaw

braidio orchestrates these; it never reimplements the DSP or the graph.

Ecosystem

braidio is a production kind on top of nw — a reusable definition of "commentary that weaves talk with extracted media" — the way a music video is another production kind. It sits on lacing (graph) + nw (workflow / provenance) + mixing/falaw (audio/TTS), and will use reelee for video. The optional nw-app layer (braidio.HAS_GRAPH / HAS_NW) records render choices as provenance so a change re-renders only the affected parts.

Install

pip install braidio   # (once published)

License

MIT

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