A 4b model replied to "하이" with "테니스 연습을 Trenches Gym에서..." — it copied
the literal "box at Trenches Gym" few-shot example embedded in the persona
prompt and mangled boxing into tennis, presenting a prompt example as if it
were a real user fact. Remove the copyable proper-noun example and add an
explicit guard: use ONLY names/places/activities that literally appear in the
memory section, never borrow them from the instructions or example wording.
Replies stayed long because the prompt stack gave conflicting length signals:
the persona said "one sentence (two at the very most)" AND told the model to
"state the answer in a sentence, then add a dry observation" (a 2nd sentence),
while voice_style said "two to three sentences maximum". The model followed the
longest. Make all three sources agree on exactly one sentence: the persona's
aside must now fold into the same sentence as a trailing clause (never a 2nd
sentence), voice_style caps at one sentence, and agents/llm.md says 한 문장.
Shorter replies also cut Edge-TTS latency, since synth time scales with text
length. Specs (prompts.spec.md) and docs/llm_contexts.md updated; deterministic
prompt-contract tests added.
load_settings() coerced any tts_engine outside {piper, chatterbox} to piper, so
with TTS_ENGINE=edge the reply engine saw "piper" and treated the voice as
English-only in reply_language_directive() (only the OUTPUT_LANGUAGE lock kept
replies Korean). Add "edge" (and "melo") to the accepted set so the engine is
labelled multilingual correctly.
Also: a stale tts_engine in the persistent /data/jarvis-settings.json (melo/xtts
from an earlier voice, no longer built) would override the configured engine via
the entrypoint merge and leave the bot silent. Reset those to the env engine
during the merge.
Verified: load_settings() with tts_engine=edge now returns "edge"; the merge
maps melo/xtts -> edge; reply_language_directive("edge") is multilingual; 27
tests pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
MeloTTS's single Korean speaker sounded non-native ("foreign accent"). Swap it
for Coqui XTTS-v2 with the built-in female studio speaker "Ana Florence"
(language ko), the natural voice used in earlier local runs.
- bridge/xtts_worker.py: new warm HTTP worker (own /opt/xtts venv), same
/synth + /health contract and PCM16 output as the old melo worker
- docker/setup-xtts.sh: builds the venv with cu128 torch (Blackwell) + Coqui
TTS and bakes the XTTS-v2 model offline. Pins transformers>=4.57,<5 (5.x
removed isin_mps_friendly, breaking XTTS) and installs the [codec] extra
(torch>=2.9 needs torchcodec) — both verified by a real host synth
- Dockerfile: replace the melo build layer with the xtts layer
- supervisord.conf: melo-worker -> xtts-worker, env passthrough for
XTTS_DEVICE/SPEAKER/LANGUAGE (always set via compose defaults)
- bridge/server.py: default TTS_ENGINE=xtts, route to the xtts worker, generic
worker-synth helper, neural-only fallback flag (XTTS_FALLBACK_PIPER)
- settings UI: engine dropdown xtts/piper, drop the dead melo_speed field, fix
the supervisorctl restart target to xtts-worker
- compose/.env.example/README: XTTS_* vars, speaker/language knobs, remove melo
- remove bridge/melo_worker.py and docker/setup-melo.sh
- tests: xtts treated as multilingual (not English-only)
Verified on host: coqui-tts loads XTTS-v2 and synthesises Korean as
"Ana Florence" to a 16-bit mono 24kHz WAV.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Drop Markdown files into an agents/ folder and their contents are appended to
the main reply LLM's system prompt, so an operator can extend the assistant's
rules/tone without code changes. Files are concatenated in filename order
(use 00-, 10- prefixes to control ordering) and re-read once per turn, so edits
apply on the next reply with no rebuild/restart. Fail-open: a missing, empty,
or unreadable folder yields no instructions and never breaks a reply.
- load_agent_instructions() in system_prompt.py (AGENTS_DIR env, default
/app/agents); reads *.md only, skips blanks, ignores non-dir paths
- engine.py appends it alongside the existing settings-UI llm_instructions,
under the same "Additional instructions from the operator:" framing
- docker-compose.yml bind-mounts ./agents:/app/agents:ro and sets AGENTS_DIR
- agents/example.md.sample starter template (.sample is not loaded)
- tests cover ordering, md-only filtering, blank-skip, env/arg resolution,
and fail-open paths
- README, .env.example, docs/llm_contexts.md updated
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Harden the reply-language lock so qwen2.5:3b reliably stays in the locked
language instead of leaking the query language back in:
- reply_language_directive(): single resolver with clear precedence —
explicit OUTPUT_LANGUAGE lock wins over the Piper/Chatterbox English-only
fallback (this deployment's actual TTS is Korean MeloTTS, so the legacy
English lock was both wrong and contradicting the Korean lock).
- Stronger, override-explicit directive wording, inserted near the FRONT of
the system prompt so a small model gives it primacy over the persona.
- build_system_prompt(output_language=...): rewrite the persona's "in the
user's language" clause to the locked language so the persona stops
fighting the lock.
- docs/llm_contexts.md: document the resolver, precedence, and placement.
Live-verified on the running brain (qwen2.5:3b): Korean voice-style input
and a cold English query both return fully Korean replies with no CJK/Hanja
leak. Tests cover unset/set/agnostic/whitespace + precedence + persona rewrite.
Add an optional OUTPUT_LANGUAGE env var that forces every reply into a
single language. When set, output_language_directive() injects a "respond
only in <language>" instruction (also forbidding other scripts) into the
chat loop's system prompt, next to the existing TTS English-only lock.
Empty (default) keeps the multilingual "reply in the user's language"
behaviour, so upstream is unaffected.
For the Korean-only deployment this also suppresses the occasional trailing
CJK/Hanja fragment qwen2.5:3b leaks on free-form chit-chat.
- system_prompt.py: language-agnostic output_language_directive() helper
- engine.py: read OUTPUT_LANGUAGE, append directive in _build_initial_system_message
- docker-compose.yml + .env.example: document/pass the new var
- docs/llm_contexts.md: note the new gating on the main reply context
- tests: cover unset/set/agnostic/whitespace cases
