Frank
31266fb7f3
Phase 1 of the voice-over goal (Gitea issue #2). One stdlib-only HTTP facade in front of whichever TTS engine wins the engine decision: POST /v1/audio/speech with voice=<name> answers audio in THAT voice, where a name is real exactly when /voices/<name>/reference.wav exists — an unknown name is a 400 listing the voices that are, never a silent fallback (a wrong-voice endpoint stays wrong for weeks). voice_id works as the alias the omp harness sends; response_format=mp3 is really mp3 (ffmpeg re-encode); oversized input is refused with 414 instead of half-narrated; /health reports the backend and the resolved voice list. Two backends behind the one surface, chosen by TTS_BACKEND: omni-http forwards to an OpenAI-shaped upstream carrying the voice as base64 reference_audio, and llama-tts-cli runs a local binary per request with --tts-speaker-file at nice 19 so narration never starves the text endpoints. Both are driven in the seam through stubs — no GPU, no containers. Named frank-tts, a first-class fleet model endpoint: port 7772 in the 7770/7771 family, alias naming per the StarCraft law, rootless boot-persistent self-healing quadlet with a read-only /home/dank/voices mount. Voice-pack law recorded in the env header: reference.wav PLUS the engine's own speaker artifact (required, so a voice is reusable in other runtimes), plus manifest.json provenance with offsets always past the first 10 s of the source file. Not deployed: the engine decision, the pack builder, deployer/homepage/Prometheus registration and the omp models.yml runner row are phase 2.
Server App Configs
AI Disclosures:
- Slop rating: 2/5 - Actively using, actively de-slopping, repository mostly human owned, lacks formal process.
- Completeness: Unfinished, planning planned, no plan yet
- Datacenter model/spend: Less than $20 of Deepseek 4.1 Flash and GLM-5.3-Flash
- Local model: Qwen 3.8 Flash Next
slop rating of 2 or lower indicates human reading is a worthwhile exercise, and that Frank has read the code and knows the architecture.
slop rating of 2 indicates that while this project is human owned, no human contribution process exists and/or release is agentically driven.
The single repository for the two homelab servers: the Podman container stacks and the LLM inference fleet. One repo, one checkout per host, one deploy script.
2026-08-22: the former
vllmScriptsrepository (LLM fleet) is merged into this repo with its full git history. See AGENTS.md for the merge note.
Targets
| Host | User | IP | Podman stack | LLM service | LLM port |
|---|---|---|---|---|---|
| dankserver | dank | 192.168.0.235 | media and library | frank-medium (ROCmFPX llama.cpp, Qwen3.8-27B AGENT) | 7770 |
| dankclaw | dank | 192.168.0.143 | AI, search, development, observability | frank-dragoon (gufo, Qwen3.8-27B UD-Q8_K_XL) | 7770 |
Active Services
| Service | Host | Hostname | Port |
|---|---|---|---|
| RomM | dankserver | romm.dankserver.local | 8085 |
| Copyparty | dankserver | files.dankserver.local | 3923 |
| Calibre-Web | dankserver | books.dankserver.local | 8083 |
| frank-medium | dankserver | — (bare endpoint) | 7770 |
| SearXNG | dankclaw | search.dankclaw.local | 8081 |
| ComfyUI | dankclaw | comfyui.dankclaw.local | 8188 |
| OpenWebUI | dankclaw | chat.dankclaw.local | 3000 |
| Hermes | dankclaw | hermes.dankclaw.local | 8090 |
| Gitea | dankclaw | gitea.dankclaw.local | 3001 |
| Grafana | dankclaw | grafana.dankclaw.local | 3002 |
| Prometheus | dankclaw | prometheus.dankclaw.local | 9090 |
| frank-dragoon | dankclaw | — (bare endpoint) | 7770 |
Structure
dankserver/— compose.yaml + Caddyfile + .env.example for the Dankserver stackdankclaw/— compose.yaml + Caddyfile + .env.example for the Dankclaw stackshared/— homepage, prometheus config, deploy helpersscripts/—deploy.shanddeploy-remote.sh(service-scoped deployment), the planner, LLM serve scripts, systemd units, env tunables, and bench harnessesold/— retired PP/NPU-era LLM scripts (reference only)serverAppConfigs-docs/— project knowledge base (Obsidian vault, wikilinks).serverAppConfigs-docs/LLM/is the LLM fleettests/— bats test suite (see Testing Policy)
Deployment
See serverAppConfigs-docs/Architecture/Deployment Flow.md
and serverAppConfigs-docs/LLM/deployment.md. Run
./scripts/deploy.sh <dankclaw|dankserver> after committing changes. It
plans and deploys only the changed services. Use --service NAME for an
explicit single-service retry; inference is restarted only when its own files
(or the shared chat template) changed.
Knowledge Base
The serverAppConfigs-docs/ directory is an Obsidian vault. Start at
serverAppConfigs-docs/index.md. The LLM fleet knowledge base lives at
serverAppConfigs-docs/LLM/index.md.
Testing
Run ./tests/run.sh before every push. See
serverAppConfigs-docs/Architecture/Testing Policy.md.