New stem recording system captures 5 time-aligned WAV files (host, caller,
music, sfx, ads) during live shows. Standalone postprod.py processes stems
into broadcast-ready MP3 with gap removal, voice compression, music ducking,
and EBU R128 loudness normalization.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Music crossfade: smooth 3-second blend between tracks instead of hard stop/start
- Emotional detection: analyze host mood from recent messages so callers adapt tone
- AI caller summaries: generate call summaries with timestamps for show history
- Returning callers: persist regular callers across sessions with call history
- Session export: generate transcripts with speaker labels and chapter markers
- Caller screening: AI pre-screens phone callers to get name and topic while queued
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Named relationships (20M/20F): "my buddy Ray", "my wife Linda" — not generic
- Relationship status with detail: "married 15 years, second marriage"
- Vehicle they drive: rural southwest flavor (F-150s, Tacomas, old Broncos)
- What they were doing before calling: grounds call in a physical moment
- Specific memory/story to reference: flash floods, poker wins, desert nights
- Food/drink right now: Tecate on the porch, third cup of coffee
- Strong random opinions: speed limits, green chile, desert philosophy
- Contradictions/secrets: tough guy who cries at TV, reads physics at work
- Verbal fingerprints: 2 specific phrases per caller
- Emotional arcs: mood shifts during the call
- Show relationship: first-timer, regular, skeptic, reactive
- Late-night reasons: why they're awake
- Topic drift tendencies for some callers
- Regional speech patterns in prompt (over in, down the road, out here)
- Opening line variety based on personality
- Local town news enrichment via SearXNG
- Ad channel now configurable in settings UI
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add dedicated ad playback system (no loop, own channel)
- Ad channel defaults to 11, saved/loaded with audio settings
- Separate play_ad/stop_ad methods and API endpoints
- Frontend stop button now calls /api/ads/stop instead of stopMusic
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add 30s timeout to all frontend fetch calls (safeFetch)
- Add 20s asyncio.timeout around lock+LLM in chat, ai-respond, auto-respond
- Reduce OpenRouter timeout from 60s to 25s
- Reduce Inworld TTS timeout from 60s to 25s
- Return graceful fallback responses on timeout instead of hanging
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add ads playback system with backend endpoints and frontend UI
- Diversify AI callers: randomize voices per session, expand jobs/problems/interests/quirks/locations
- Update website tagline and descriptions to "biologically questionable organisms"
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When off air, callers hear a message and get disconnected. When on
air, calls route normally. Toggle button added to frontend header
with pulsing red ON AIR indicator.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add streamSid tracking and per-caller send locks for SignalWire
- Improve TTS streaming with real-time pacing and detailed logging
- Block host audio to caller during TTS playback
- Randomize caller names between sessions from name pools
- Update page title and show phone number in UI
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Mute host mic forwarding while TTS is streaming to prevent interleaving
both audio sources into the same playback buffer
- Replace nearest-neighbor downsampling with box-filter averaging on both
server (host mic) and browser (caller mic) for anti-aliased resampling
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
TTS audio was sent as a single huge WebSocket frame that overflowed the
browser's 3s ring buffer. Now streams in 60ms chunks at real-time rate.
Also increased browser ring buffer from 3s to 10s as safety net.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Replace per-callback async task spawning with persistent queue-based sender
- Buffer host mic to 60ms chunks (was 21ms) to reduce WebSocket frame rate
- Reduce server ring buffer prebuffer from 150ms to 80ms
- Reduce browser playback jitter buffer from 150ms to 100ms
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Reduce capture chunk from 4096 to 640 samples (256ms → 40ms)
- Replace BufferSource scheduling with AudioWorklet playback ring buffer
- Add 80ms jitter buffer with linear interpolation upsampling
- Reduce host mic and live caller stream blocksizes from 4096/2048 to 1024
- Replace librosa.resample with numpy interpolation in send_audio_to_caller
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Use persistent callback-based output stream instead of opening/closing per chunk
- Replace librosa.resample with simple decimation in real-time audio callbacks
- Move host stream initialization to background thread to avoid blocking
- Change live caller channel default to 9
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
