ai-podcast/CLAUDE.md

AI Podcast - Project Instructions

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

• 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-4.3) works well for natural dialog; MiniMax tends toward terse responses. Note grok-4, grok-4-fast and grok-4.1-fast were retired from OpenRouter — a retired id 404s, and llm.py swallows the error and returns empty text, so callers go silent with nothing in the logs. tests/test_model_config.py guards against reintroducing them.
• generate_with_tools() in llm.py supports OpenRouter function calling for the intern feature

Caller Generation System

• Two-stage pipeline: (1) batch identity pregen via Sonnet 4.6 at session start, (2) live dialog via Sonnet 4.6 per turn. Cost ~$3-4/show.
• Slim caller dict: Populated once at Session._pregenerate_backgrounds() via caller_gen.generate_batch(). Keys: name, age, voice, location, identity, situation, reason_calling, opening_line, secret_want, specific_details, emotional_register. Stored in session.caller_backgrounds[caller_key].
• Dialog model: Always Sonnet 4.6 via the caller_dialog category in config.category_models. No per-caller model routing — deleted in Phase 5B.
• Prompt builder: get_caller_prompt(caller) in main.py builds the slim system prompt from the dict; see tests/test_caller_prompt.py for the contract.
• Regulars: backend/services/regulars_v2.py loads lore from Obsidian markdown files for named recurring callers (e.g. Silas). The batch prompt optionally includes 2-3 active regulars per session.
• Inter-caller awareness: get_show_history() scores previous callers by keyword overlap with the current caller's situation/reason_calling. Reaction frequency scales with match strength (60%/35%/15%).
• Caller memory: Returning callers auto-promote from first-timers at ~5% probability after 8+ exchanges. RegularCallerService tracks summaries, relationships, arc state.
• Call quality signals: _assess_call_quality() captures exchange count, response length, host engagement, caller depth, 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
• SearXNG: runs on the NAS (http://mmgnas:8888), deployed via deploy_searxng.sh. URL is settings.searxng_url (env SEARXNG_URL). If Devon's web_search returns "Search failed", check the searxng container on mmgnas is Up. The config enables the JSON API + disables the bot limiter — both required for programmatic queries.
• 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 identity, situation, signature detail, secret want during active calls
• Caller buttons: Populated from the slim caller background dicts
• 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

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: check Castopod for the latest episode number, don't hardcode

Scripts

• publish_episode.py — Transcribes audio, generates metadata (title, description, cover art), publishes to Castopod. Usage: python publish_episode.py ~/Desktop/episode.mp3
• make_clips.py — Two-pass clip extraction: fast Whisper transcription → LLM selects best moments → quality Whisper re-transcription for precise timestamps. Usage: python make_clips.py ~/Desktop/episode.mp3 --count 3
• generate_milestone_images.py — Generates social milestone images via Gemini Flash (requires GOOGLE_API_KEY)
• post_milestone.py — Posts milestone announcements to social platforms via Postiz
• make_x_launch_assets.py — Generates branded visual assets for X/Twitter (header, quote cards, intro/review graphics)
• schedule_x_launch.py — Schedules X/Twitter launch campaign posts via Postiz API

Reaper Scripts

• reaper/dialog_regions.lua — Background script that polls /tmp/reaper_state.txt and creates colored regions (green=DIALOG, red=AD, blue=IDENT) as the backend writes state changes during recording
• reaper/strip_silence_dialog.lua — Post-production script: strips long silences from dialog regions, normalizes AD/IDENT/music volume, trims music to voice length with fade-out, mutes music during AD/IDENT regions

Cost Dashboard

• Route: /costs — standalone analytics page, linked from control panel header
• Database: data/costs.db (SQLite) — aggregates all session cost data for cross-session queries
• Data layer: backend/services/cost_db.py — schema, JSON import, all query functions
• Dual-write: cost_tracker.py writes to both JSON (data/cost_reports/) and SQLite on every LLM/TTS call
• API: 8 endpoints under /api/costs/ — summary, timeline, models, categories, sessions, session detail, expensive calls, TTS providers
• Frontend: frontend/costs.html, frontend/css/costs.css, frontend/js/costs.js — Chart.js for visualizations
• Pricing: Hardcoded in cost_tracker.py (OPENROUTER_PRICING, TTS_PRICING) — update when provider prices change
• Not tracked yet: SignalWire call costs

Data Directory

State files (not config — these are written at runtime):

• regulars.json — Returning caller profiles (backgrounds, key moments, arc status, relationships)
• used_topics_history.json — Previously used caller topics to avoid repeats
• session_checkpoint.json — Current show session state (call history, caller queue)
• publish_state.json — Publishing pipeline progress per episode
• intern.json — Devon's lookup history
• emails.json — Listener email submissions
• voicemails.json — Listener voicemail submissions

Personal

• Don't build anything until you have 95% clarity on what I want you to do. Ask clarifying questions until you reach 95% understanding of what I'm asking
• When working as a team, propose the plan before executing — don't just start building
• Flag trade-offs that affect show quality or listener experience rather than silently resolving them