ai-podcast/CLAUDE.md

AI Podcast - Project Instructions

Git Remote (Gitea)

• Repo: git@gitea-nas:luke/ai-podcast.git
• Web: http://mmgnas:3000/luke/ai-podcast
• SSH Host: gitea-nas (configured in ~/.ssh/config)
  • HostName: mmgnas (use mmgnas-10g if wired connection issues)
  • Port: 2222
  • User: git
  • IdentityFile: ~/.ssh/gitea_mmgnas

NAS Access

• Hostname: mmgnas (wireless) or mmgnas-10g (wired/10G)
• SSH Port: 8001
• User: luke
• Docker path: /share/CACHEDEV1_DATA/.qpkg/container-station/bin/docker

Castopod (Podcast Publishing)

• URL: https://podcast.macneilmediagroup.com
• Podcast handle: @LukeAtTheRoost
• API Auth: Basic auth (credentials in .env: CASTOPOD_USERNAME, CASTOPOD_PASSWORD)
• Container: castopod-castopod-1
• Database: castopod-mariadb-1 (user: castopod, db: castopod)

Running the App

# Start backend — ALWAYS use --reload-dir to avoid CPU thrashing from file watchers
python -m uvicorn backend.main:app --reload --reload-dir backend --host 0.0.0.0 --port 8000

# Or use run.sh
./run.sh

Publishing Episodes

python publish_episode.py ~/Desktop/episode.mp3

Environment Variables

Required in .env:

• OPENROUTER_API_KEY
• ELEVENLABS_API_KEY (optional)
• INWORLD_API_KEY (for Inworld TTS)

Post-Production Pipeline (added Feb 2026)

• Branch: feature/real-callers — all current work is here, pushed to gitea
• Stem Recorder (backend/services/stem_recorder.py): Records 5 WAV stems (host, caller, music, sfx, ads) during live shows. Uses lock-free deque architecture — audio callbacks just append to deques, a background writer thread drains to disk. write() for continuous streams (host mic, music, ads), write_sporadic() for burst sources (caller TTS, SFX) with time-aligned silence padding.
• Audio hooks in backend/services/audio.py: 7 tap points guarded by if self.stem_recorder:. Persistent mic stream (start_stem_mic/stop_stem_mic) runs during recording to capture host voice continuously, not just during push-to-talk.
• API endpoints: POST /api/recording/start, POST /api/recording/stop (auto-runs postprod in background thread), POST /api/recording/process
• Frontend: REC button in header with red pulse animation when recording
• Post-prod script (postprod.py): 6-step pipeline — load stems → gap removal → voice compression (ffmpeg acompressor) → music ducking → stereo mix → EBU R128 loudness normalization to -16 LUFS. All steps skippable via CLI flags.
• Known issues resolved: Lock-free recorder (old version used threading.Lock in audio callbacks causing crashes), scipy.signal.resample replaced with nearest-neighbor (was producing artifacts on small chunks), sys import bug in auto-postprod, host mic not captured without persistent stream

LLM Settings

• _pick_response_budget() in main.py controls caller dialog token limits (150-450 tokens). MiniMax respects limits strictly — if responses seem short, check these values.
• Default max_tokens in llm.py is 300 (for non-caller uses)
• Grok (x-ai/grok-4-fast) works well for natural dialog; MiniMax tends toward terse responses
• generate_with_tools() in llm.py supports OpenRouter function calling for the intern feature

Caller Generation System

• CallerBackground dataclass: Structured output from LLM background generation (JSON mode). Fields: name, age, gender, job, location, reason_for_calling, pool_name, communication_style, energy_level, emotional_state, signature_detail, situation_summary, natural_description, seeds, verbal_fluency, calling_from.
• Voice-personality matching: _match_voices_to_styles() runs after background generation. 68 voice profiles in VOICE_PROFILES (tts.py), 18 style-to-voice mappings in STYLE_VOICE_PREFERENCES (main.py). Soft matching — scores voices against style preferences.
• Adaptive call shapes: SHAPE_STYLE_AFFINITIES maps communication styles to shape weight multipliers. Consecutive shape repeats are dampened.
• Inter-caller awareness: Thematic matching in get_show_history() scores previous callers by keyword/category overlap. Adaptive reaction frequency (60%/35%/15%). Show energy tracking via _get_show_energy().
• Caller memory: Returning callers store structured backgrounds, key moments, arc status, and relationships with other regulars. RegularCallerService has add_relationship() and expanded update_after_call().
• Show pacing: _sort_caller_queue() sorts presentation order by energy alternation, topic variety, shape variety.
• Call quality signals: _assess_call_quality() captures exchange count, response length, host engagement, shape target hit, natural ending.

Devon (Intern Character)

• Service: backend/services/intern.py — persistent show character, not a caller
• Personality: 23-year-old NMSU grad, eager, slightly incompetent, gets yelled at. Voice: "Nate" (Inworld), no phone filter.
• Tools: web_search (SearXNG), get_headlines, fetch_webpage, wikipedia_lookup — via generate_with_tools() function calling
• Endpoints: POST /api/intern/ask, /interject, /monitor, GET /api/intern/suggestion, POST /api/intern/suggestion/play, /dismiss
• Auto-monitoring: Watches conversation every 15s during calls, buffers suggestions for host approval
• Persistence: data/intern.json stores lookup history
• Frontend: Ask Devon input (D key), Interject button, monitor toggle, suggestion indicator with Play/Dismiss

Frontend Control Panel

• Keyboard shortcuts: 1-0 (callers), H (hangup), W (wrap up), M (music toggle), D (ask Devon), Escape (close modals)
• Wrap It Up: Amber button that signals callers to wind down gracefully. Reduces response budget, injects wrap-up signals, forces goodbye after 2 exchanges.
• Caller info panel: Shows call shape, energy level, emotional state, signature detail, situation summary during active calls
• Caller buttons: Energy dots (colored by level) and shape badges on each button
• Pinned SFX: Cheer/Applause/Boo always visible, rest collapsible
• Visual polish: Thinking pulse, call glow, compact media row, smoother transitions

Website

• Domain: lukeattheroost.com (behind Cloudflare)
• Analytics: Cloudflare Web Analytics (enable in Cloudflare dashboard, no code changes needed)
• Deploy: npx wrangler pages deploy website/ --project-name=lukeattheroost --branch=main

Git Push

• If mmgnas times out, use the 10g hostname:

  GIT_SSH_COMMAND="ssh -o HostName=mmgnas-10g -p 2222 -i ~/.ssh/gitea_mmgnas" git push origin main
  

Hetzner VPS

• IP: 46.225.164.41
• SSH: ssh root@46.225.164.41 (uses default key ~/.ssh/id_rsa)
• Specs: 2 CPU, 4GB RAM, 38GB disk (~33GB free)
• Mail: docker-mailserver at /opt/mailserver/
• Manage accounts: docker exec mailserver setup email add/del/list
• Available for future services — has headroom for lightweight containers. Not suitable for storage-heavy services (e.g. Castopod with daily episodes) without a disk upgrade or attached volume.

Podcast Workflow

• Publishing pipeline: episodes go through Castopod, CDN, website, YouTube, and social
• Always check Python venv is active and packages are installed before running publish scripts
• Episode numbering must be verified against existing episodes

Episodes Published

• Episode 6 published 2026-02-08 (podcast6.mp3, ~31 min)