She can now *do* things mid-conversation, not just reply. Adds a tool-calling
loop to the chat path and her first two tools; the same mechanism will carry the
poker tools (start_session, log_result, get_stats, solver) next.
- tools.py: registry of OpenAI-style tool specs + handlers + safe dispatch;
journal_write (knowing journaling) and note (tagged notepad, e.g. poker reads)
- llm.chat_call(): OpenAI-style call that returns tool_calls (cloud/mi50);
local has no tool support and returns plain content
- chat.respond(): tool loop — offer tools, run any calls, feed results back,
repeat until a text reply (capped at MAX_TOOL_ROUNDS); persists final reply
- tests: dispatch + full chat loop (tool call -> result -> reply)
Verified live: she invoked `note`, tagged it 'poker', stored a villain read.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Mid-size models (gpt-4o-mini, qwen2.5-14b) resist persona instructions —
help-desk closers and feelings-disclaimers leak through regardless. Route live
chat to a stronger model while keeping bulk consolidation cheap:
- config: CHAT_MODEL (default gpt-4o), distinct from CLOUD_MODEL (gpt-4o-mini)
- llm.complete gains a `model` override; chat.respond uses chat_model on cloud,
consolidation paths keep cloud_model
- persona: reword the "no sign-off" rule so genuine questions are welcome and
only reflexive customer-service closers are discouraged
Verified: on gpt-4o she owns her mood without disclaimers and drops most
help-desk tails — clearly more in-character than mini/qwen.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The MI50 box (CT202) runs an OpenAI-compatible llama.cpp server on
10.0.0.44:8080. Wire it in as a third backend:
- llm.complete gains backend="mi50" (OpenAI client pointed at MI50_BASE_URL)
- config: MI50_BASE_URL (default http://10.0.0.44:8080/v1) + MI50_MODEL
- chat.respond labels the model per backend; web _backend_for maps "mi50"
- UI backend selector adds "MI50 — local GPU"
Verified end-to-end: llm.complete(backend="mi50") returns from the live server.
See homelab-inference memory for the box topology.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Phase 1 — persona + persistent memory chat loop:
- lyra/persona.py + personas/lyra.md: editable identity/voice (friend-first,
honest, never invents poker math)
- lyra/chat.py: turn loop assembling persona + cross-session recall + recent
context, persisting both sides to SQLite
- lyra/session.py, lyra/__main__.py: session lifecycle + `lyra` REPL
Phase 1.25 — reuse the old web UI:
- vendored the prior single-page UI into lyra/web/static, repointed to
same-origin
- lyra/web/server.py (FastAPI): serves the UI and backs its endpoint contract
(/v1/chat/completions, session CRUD, health, inert thinking-stream) with the
new chat loop + memory; SQLite stays the single source of truth
- `lyra-web` console script
Local backends — test for free, no OpenAI key:
- llm.embed routes via EMBED_BACKEND (cloud=OpenAI, local=Ollama /api/embed)
- simplified UI backend selector to Local (Ollama) / Cloud (OpenAI), default local
- memory connection opened check_same_thread=False for the threaded server
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- lyra.config.load() reads env into a frozen Config dataclass
- lyra.llm.complete(messages, backend) routes to Ollama /api/chat or
OpenAI chat completions
- lyra.llm.embed(texts) calls OpenAI embeddings
- .env.example switched from Anthropic to OpenAI to match available key
serversdown
Claude