kami
5fe8f228c1
Add a read-only /ecosystem page that consumes the sibling services' JSON APIs (Nexus entities, Praxis attention, Hexis capabilities), fetched concurrently with honest per-panel error states. Siblings stay headless — mavweb is their human surface (arch §16). Wired via mavweb -nexus/-praxis/-hexis flags; mavweb joins the ecosystem compose network. Fix mobile horizontal overflow across all pages: .content is a flex child with default min-width:auto, so it refused to shrink below the tables' intrinsic width. min-width:0 lets wide tables pan inside .scroll instead of dragging the page sideways. Verified via CDP geometry check (scrollWidth === clientWidth at 430px). Also includes in-progress Ethos UI redesign, ecosystem deploy compose, and planning docs. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
4.3 KiB
Maven — Re-architecture (Qwen3 resident model, revised 2026-07-18)
Supersedes the classifier-first routing model. Agreed in a design session after diagnosing that homesrv deploys with a stub phraser (no LLM running) and an embedder-classifier that routes by nearest-neighbor between frozen seed phrases — the structural cause of "she messes up queries."
Hardware reality: homesrv = Ryzen 5 5600U laptop, Vega iGPU, 14 GB shared RAM. Workstation (RX 7900 XT) is NOT the deploy target and is often busy. So: small models, on-demand where heavy, always-on where cheap.
Principle
The LLM is not the center of everything. Deterministic tools handle the bulk. One locally trained Qwen3-1.7B resident model is used for routing and talking back. Its system prompt selects one of two independently evaluated contracts: route actions or persona responses.
If the router is good, Maven feels good. Routing is the linchpin.
The spine
utterance
→ [world-state context] cheap: time, presence, calendar_busy, weather (no LLM)
→ ROUTER = Qwen3-1.7B (always-on, grammar-constrained)
reads utterance + context + tool schema, emits a STRUCTURED action:
• call a tool (deterministic) • answer directly
→ tools (deterministic, fast)
→ PHRASER = Qwen3-1.7B (same resident process) → TTS / text
- Router = Phraser = one resident Qwen3-1.7B llama-server, with separate route and persona prompts/contracts. Always warm; classifier/stub remain the failure floors.
- The resident checkpoint is trained end-to-end as: Qwen3-1.7B-Base → RU CPT → joint persona/router SFT → merge → GGUF. Larger on-demand reasoning models are deferred until the main feature set is complete.
- Embedder demoted from router to tool — it now backs
memory.search(RAG) and gives the router a cheap "similar past notes/intents" hint. The router no longer depends on it clearing a threshold. Upgrade MiniLM → bge-m3 for better RU retrieval later (model swap, not architecture).
Router output
- Constrained structured JSON action
{tool, args, escalate}— NOT free-form multi-step function-calling. Sub-1B is far more reliable emitting a fixed schema. Enforce with a GBNF grammar in llama.cpp (near-bulletproof). - Keep the existing stage-0 exact-match fast-path for dead-obvious commands (skips the router entirely) — cheap insurance, already built.
The proactive / memory half — one background engine
"Take notes," "remember," "reflect," "suggest do you want to add X?", "remind" are NOT request-path features. They are one digestion worker:
DIGESTION WORKER (periodic + event-driven, off the request path)
• reads new facts/notes since last pass
• RAG-consolidates: dedupe, link, summarize into durable memory
• reflects: detect patterns ("mentioned X three times")
• proposes: "want me to add X / remind you about Y?" → nudge dispatcher
• surfaces due reminders
uses the resident Qwen3 model for bounded synthesis — never blocks a turn
Notes capture is a deterministic Tier-0 tool; making notes mean something later is the worker + RAG.
Layer table
| Layer | What | Runs |
|---|---|---|
| Context | world-state (time/presence/calendar/weather) | always, no LLM |
| Router | Qwen3 structured-action orchestrator — linchpin | always-on |
| Tools | note/reminder/memory/calendar/weather/act (deterministic) | always |
| Reasoner | larger specialist model | deferred |
| Phraser | Qwen3 persona response | always-on (same proc as router) |
| Digestion worker | reflection → suggestions/nudges/memory | background |
| Reach | telegram (+ existing ntfy/voice) | quick win |
| Voice quality | custom/better TTS | deferred (workstation GPU busy) |
Build order
- Foundation + router — completed shared llama-server client, router, fallback, replier, TTS normalization and telegram reach.
- Qwen3 resident checkpoint — finish RU CPT, pass the raw-vs-CPT gate, jointly SFT persona/router contracts, merge, quantize and deploy.
- Main features — reflection, proactive suggestions, memory consolidation, RAG read-back.
- Deferred work — larger reasoner, custom Piper voice and other expansions.
Non-goals (unchanged)
Never phones home. Not a nag. Not autonomous. Feminine-gendered RU self-ref.