podcast-audio

name	podcast-audio
description	Turn the conversation and workspace material into a spoken podcast-style audio file (.wav), single- or multi-voice. Trigger with "make a podcast", "create an audio overview", "turn this into a podcast", "narrate this", or whenever the user wants an audio version of the material.

Podcast Audio

Produce a listenable audio episode as a real .wav file in the workspace. You write the script, synthesize it with the interpreter's synthesize() helper, and merge the segments — the file shows up in the artifacts panel with an inline player.

Requires a configured speech service. If synthesize() reports none is configured, tell the user audio generation isn't available and offer the written script instead.

1. Gather the material and pick a format

If the user named a format ("overview", "deep-dive", "briefing", "debate", "story"), match its voice count and tone. Default: a single warm narrator giving a clear overview, ~3–5 minutes (roughly 500–800 words).

2. Write the script

• Natural, conversational, spoken prose — no markdown, no bullet points, no headers (it is read aloud verbatim).
• Don't open with "Welcome to…" or close with a recap; start in the content and end when it's done.
• Weave the key findings into a narrative with real transitions.
• For a multi-voice format, split the script into a list of (speaker, text) turns and assign each speaker a distinct voice.

3. Synthesize and merge

synthesize(text, output, voice=None) writes one WAV per call. Generate per segment, then concatenate with Python's stdlib wave (all segments share the speech service's format):

import os, wave

# Single or multi-voice: list of (voice, text) turns.
turns = [
    ("host",  "Here's the thing everyone misses about the Q3 numbers."),
    ("guest", "Right — and it's not the headline growth rate at all."),
]

paths = []
for i, (voice, text) in enumerate(turns):
    p = f"seg_{i:03d}.wav"
    await synthesize(text, p, voice=voice)   # voice may be a configured name or None
    paths.append(p)

with wave.open(paths[0], "rb") as w0:
    params = w0.getparams()
with wave.open("podcast.wav", "wb") as out:
    out.setparams(params)
    for p in paths:
        with wave.open(p, "rb") as w:
            out.writeframes(w.readframes(w.getnframes()))

for p in paths:
    os.remove(p)  # keep only the final artifact

print("wrote podcast.wav")

Notes:

• Keep each synthesize call to a reasonable chunk (a paragraph or a turn) rather than one giant call or hundreds of tiny ones.
• Use a voice name only when the user or deployment supplied it; otherwise pass None rather than inventing an unsupported voice id. Multi-speaker output needs distinct configured voices.

4. Deliver

Save podcast.wav to the workspace root and tell the user it's ready with a one-line description and the approximate length. To revise, adjust the script and re-run.