27 Commits

Author SHA1 Message Date
serversdown 924dc297d5 fix: recorder cancel left an empty black screen
mount() adds .rec-root (display:flex) to the overlay element, and that rule sat
after .rec-overlay's display:none — so removing .open didn't hide it. Use
.rec-overlay:not(.open){display:none} to outrank .rec-root by specificity.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:55:03 +00:00
serversdown b6cdf799dc feat: straddle support in recorder
Add a straddle from any non-blind seat (default 2×BB) via a preflop control.
Recorded as a preflop post (fits the contract — order carries 'acts last'), tagged
straddle for the log label + removability; the UI-only flag is dropped from the
emitted structured hand. Blinds stay non-removable. Documented in HAND_HISTORY.md.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:49:50 +00:00
serversdown c52404fbb9 fix: add Cancel to recorder + safe-area insets (notch ate the ✕)
The header ✕ sat under the iPhone status bar/notch (overlay had no safe-area
padding), so there was no reachable way out without saving. Add a labeled Cancel
button next to Save, and pad the header/footer for the notch + home indicator.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:40:32 +00:00
serversdown 4fd7eff7e9 fix: shelve recorder card picker for plain typed card entry
The tap picker wasn't working in practice. Replace it with simple text inputs for
hero/board/shown cards: case-insensitive, accepts 'ah kh' / 'AhKh' / '7d2c5h' /
'10h'. parseCards() tokenizes; the server's normalize_structured() canonicalizes
(case, 10->T, completeness). Also adds per-action remove (✕) in the street log.
Picker UI + bottom-sheet CSS removed; tap picker deferred to V2 (docs/RECORDER.md).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:35:13 +00:00
serversdown 2bd5b7fd26 fix: move recorder launch into bottom bar (Mind->Record in poker mode)
The floating +Hand button overlapped the chat send button. Replace it with a
Record tab that swaps in for Mind only in poker (cash) mode, via body.cash-mode
CSS toggle. Other modes keep Mind; Record stays hidden.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:23:28 +00:00
serversdown 50bcb5533f feat: hand recorder v1 (tap-to-build, overlay) — recorder steps 2-4
Tap-to-build hand recorder per docs/RECORDER.md. Correctness by construction: every
tap writes a known value into a known slot, emitting the canonical structured contract
(server normalize_structured() is the shape authority, so the client is best-effort).

- recorder.js: mount-agnostic module (mounts into any container -> overlay now,
  standalone later, zero logic change). Pure buildStructured(state)->contract dict.
  Card picker: sticky-suit-or-rank-first + x (unknown suit) + unknown-card; lock resets
  per slot so it never bleeds between cards. Pre-fills from /session/data (stakes->blinds,
  stack->hero, villains->seated). Per-street action entry, manual street advance.
- recorder.css: full-screen overlay using app theme tokens; floating launcher.
- index.html: overlay div + script + launcher (chat/session stays mounted underneath).

Validated end-to-end: JS core builds a hand (sticky/rainbow/unknown cards all correct)
-> POST /hands -> normalized -> /hand/{id} replay round-trips identically.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:18:38 +00:00
serversdown f745ef43a1 feat: POST /hands endpoint + seat in HUD villains (recorder step 1)
- POST /hands: store a structured hand from the recorder; normalize_structured()
  (via store_hand_history) is the shape authority, so the client stays best-effort.
  Enriches villain dossiers from the recorded players, same as the parser path.
  Verified live: best-effort body -> normalized (version, completeness, hero sync).
- _session_villains: surface each player's latest seat so the recorder can
  auto-place known players on the table.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:11:48 +00:00
serversdown d7f3ba330a docs: hand recorder design note (v1 core loop + card-entry UX)
Tap-to-build recorder: correctness by construction, reusable mount-agnostic module
(pure buildStructured core), pre-fill from live session state, emits the locked
structured-hand contract. V1 = core capture loop; card entry = contextual picker
with sticky-suit-or-rank-first flow + x/unknown. V2 = smart legal-action keypad.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-27 04:08:20 +00:00
serversdown 66dd880f93 feat: canonical structured-hand contract (Lyra->RTO transport)
Solidify hand histories into one versioned shape that gets stored, replayed, and
exported — the foundation the tap recorder will emit into and RTO consumes.

- normalize_structured(): single guarantee of the contract shape — canonical cards
  (unicode/10/case -> RankSuit tokens, unknown 'Ax'/'x' preserved), hero synced into
  players[] (RTO finds hero via pos==hero_pos), schema_version stamp, and a
  completeness summary so consumers skip suit-dependent math on partial hands.
  Idempotent; runs on store AND read (legacy rows conform on the way out).
- list_recent_hands: has_structured flag so the export/RTO knows which hands have a
  replayable body worth fetching.
- docs/HAND_HISTORY.md: the shared contract both repos cite (schema, conventions,
  ownership rule, one-way HTTP coupling, transport endpoints).
- replaces the narrow _normalize_parsed (unicode-only) everywhere.

Card format chosen: lists of 2-char tokens (unambiguous, matches what Lyra already
stores + the viewer reads). Unknowns kept + flagged rather than dropped.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-26 22:36:11 +00:00
serversdown a7901a66ae fix: phone app view zoom corrects 2026-06-26 20:44:11 +00:00
serversdown 2a73033eed perf: incremental profile rebuilds — fold new gists instead of re-digesting all
The profile pass map-reduced every session gist (~851) on every consolidation
firing — the biggest redundant-work and MI50-heat source left after the eras fix.
Now: skip when nothing's new, fold only the gists added since last build into the
existing profile, and full-rebuild only when there's no profile, too much has
accumulated to fold safely (>FOLD_LIMIT), on a periodic cadence (anti-drift), or
when forced.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-25 04:05:24 +00:00
serversdown aae8204eff Merge pull request 'feat: thought loop — Lyra's threaded, surfaceable train of thought' (#4) from feat/thought-loop into dev
Reviewed-on: #4
2026-06-24 23:47:38 -04:00
serversdown d6f3516a34 perf: incremental era rebuilds — skip unchanged months
rebuild_eras() re-digested EVERY month from scratch on every coherence pass,
including old months whose sessions never change — ~17 redundant 32B calls per pass
(a big slice of the ~40-min consolidation grind + MI50 heat). Now it compares each
month's current session count to the stored era and only rebuilds changed months
(force=True still does all). Report gains built/skipped counts.

test_era.py: builds all first pass, skips unchanged, rebuilds only a month that
gained a session, force rebuilds all. Suite 99 green, ruff clean.

(Profile rebuild re-reading all 851 sessions every pass is the bigger remaining
hog — separate, harder fix.)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-25 03:31:02 +00:00
serversdown 51c2d6abb9 perf: tighten the dynamic prompt — persona split + lean deliberation
The per-turn prompt was ~5.5K tokens (persona alone ~40%), sent up to 3x/turn.
Tightened by RELEVANCE (the control plane decides what each turn needs), not by
deletion — fidelity preserved, focus improved (buried instructions were getting
ignored), tokens roughly halved.

- persona split: core (identity + voice — always) vs situational sections pulled
  in only when relevant. mind._persona_block: self-model/origin only on meta turns
  (generous _META_HINTS), poker guardrails only in poker context (mode/strategic/
  _POKER_HINTS). persona.core_prompt()/section(); system_prompt() kept as fallback.
- lean deliberation: the private 'what do I think' pass now uses a focused context
  (her interiority + recent turns + the message), not the full persona/profile/
  narrative/recall dump. It shapes the take, not the voice.

Measured: casual Talk turn 21,949 -> 15,974 chars (-27%); deliberation 21,949 ->
6,026 (-72%); meta turns still include the self-model. Suite 98 green, ruff clean.

Real retirement of the long prompt is still the fine-tune (mouth); this is the
cheap, high-leverage cut that also improves adherence.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 20:48:44 +00:00
serversdown 8a3c9b2701 feat: she can suggest + switch modes (set_mode tool + mode awareness)
"She suggests, you confirm" — instead of brittle keyword→mode mapping, she's given
awareness of her modes + the ability to switch, and her judgment decides when to
offer (the model reads "should I drive to Cleveland?" vs "should I fold the river"
far better than a lexicon could).

- tools: set_mode(mode) — switches the session's mode; in _BASE (all modes).
- mind: a per-turn mode-menu note listing her modes + "offer a switch when the work
  clearly shifts; on his yes, call set_mode; don't nag."
- Sticky mode stays manual otherwise; Poker still auto-engages on session start.
- test: set_mode switches + rejects unknown. Suite 97 green, ruff clean.

Note: server-side switch takes effect next turn; the UI badge syncs on next mode
load (cosmetic lag).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 16:32:42 +00:00
serversdown 17ab95dc98 feat: Decide mode — a tie-breaker that settles choices instead of listing options
Brian's bottleneck is committing, not generating options, so a pros/cons dump makes
it worse. Decide mode's card: get the real decision crisp, weigh it against what HE
values + past regrets (pull running_stats/recent_sessions for poker/money calls),
MAKE the call with the one or two reasons that tip it, pressure-test it once, and
stand behind it — no "it's up to you." Read-only lookups, no live logging.

Sixth mode (Talk/Poker/Build/Explore/Study/Decide); added to UI selectors, labels,
badge-cycle. Suite 96 green, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 16:21:03 +00:00
serversdown 03aceec6fa feat(P3): mind/mouth split — separate voice model for the final reply (seam, default off)
The mind (chat backend/model) decides, reasons, and runs tools → a draft; the mouth
re-voices that draft in her character. Default: no mouth configured → the mind's
draft IS the reply, bit-for-bit the old behavior (and old streaming path untouched).

- config: MOUTH_BACKEND / MOUTH_MODEL. The slot for an eventual fine-tuned voice.
- chat: _mind_loop (tool/generation loop, non-stream, returns draft + tools_run),
  _voice_pass / mind.voice_messages (re-voice the draft, keep every fact/number),
  _mouth_target (active only when configured AND != mind). respond + respond_stream
  branch: mouth off = stream the mind directly (unchanged); mouth on = mind decides
  + runs tools, then the mouth streams the re-voiced reply. Falls back to the draft
  on any mouth failure (chat never breaks).
- Key payoff: the mouth needs no tool support (the mind handles tools), so it can be
  a non-tool character model (Dolphin / Claude / fine-tune). Makes the fine-tune
  easy: teach a small model to *sound* like Lyra, not to be smart.
- tests: mouth target on/off, voice_messages shape, voice_pass revoice+fallback.
  Suite 96 green, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 06:08:06 +00:00
serversdown a7af461cdb feat(P2): perceive (read the moment) + route nudges register on charged turns
The control plane gains senses — cheap, deterministic, no LLM:
- lyra/perceive.py: lexicon+signal heuristic → {sentiment, intensity, tilt, kind:
  emotional|strategic|meta|build|casual}. Good at the action-relevant signal,
  especially tilt (the mental-game core). Word-boundary matching so 'line' doesn't
  fire inside 'pipeline'.
- mind: _perceive fills ctx.moment; _route keeps the manual mode as the dominant
  frame but, on a genuinely charged moment, adds a per-turn register nudge — tilt →
  "meet him there, warm and steady, don't clip into logging"; up/energized → "match
  his energy." Neutral turns get nothing (don't over-narrate). Injected via
  build_messages(moment=...). Logged to /logs for observability.
- tests: perceive read (tilt/strategy/up/build/casual) + route nudge on/off.
  Suite 92 green, ruff clean.

Complements modes (manual frame) — perceive refines register within it, doesn't
override. Model routing (mind/mouth) is P3.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 05:42:36 +00:00
serversdown 904eda3388 refactor(P1): extract the turn pipeline into lyra/mind.py (behavior-preserving)
First step of the cognition control plane (docs/COGNITION.md). The chat turn is now
an explicit society of parts over a shared TurnContext blackboard:
  perceive (stub) -> route (session mode) -> compose (tiered prompt) -> deliberate.

- lyra/mind.py (new): TurnContext + the pipeline + assemble(); moved build_messages
  and the deliberation helpers here (the assembly belongs in the control plane).
- lyra/chat.py: slimmed to "speak + persist" — calls mind.assemble(), runs the
  tool/generation loop, persists. No behavior change (same prompt, same output).
- tests: point test_time/test_chat at mind; add an assemble() structure test;
  make test_chat/test_tools hermetic (CHAT_DELIBERATE off so respond() doesn't make
  a real LLM call). Suite 86 green in ~5s, ruff clean, no import cycle.

This is the frame; perceive/route/learn get filled in next phases — each opt-in.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 05:19:39 +00:00
serversdown f1f15972ac feat: work-type modes — Talk / Poker / Build / Explore / Study
The manual version of the architecture's `route` step: Brian points her at the
TYPE of work and her register + tools shift to match. Biggest single lever on the
'meh' problem (a mode card can demand decisive/technical/generative, countering
gpt-4o's default warm-vapor).

- modes.py: Build (heads-down engineering — decisive, concrete, tradeoffs, no
  listicles), Explore (open brainstorming — generative, riffs + honest catch,
  spawn threads, don't converge early), Study (poker review away from the table —
  analytical, GTO-aware, teaching; read-only lookups + analyze_spot). Cash relabeled
  Poker (key kept for compat).
- UI: mode selectors (desktop + mobile) get all five; badge taps now cycle modes.
- design: docs/COGNITION.md (the society-of-parts control-plane sketch).
- tests: presence + tool-gating for the new modes. Suite 85, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-24 03:43:37 +00:00
serversdown 97afa82594 feat: live chat deliberation — think privately before answering (less 'meh')
The chat had no thinking in it: respond() was a single gpt-4o call in default-
assistant voice (numbered lists, 'would you like to...', vague). All the cognition
work was background-only. This brings a thought step into the conversation.

- chat: before answering a substantive turn (trivial 'ok/lol' skipped), a private
  _deliberate() pass — "what do you ACTUALLY think, your real take, the substance,
  no pleasantries" — drawing on her in-context threads/journal. The thinking is then
  injected as the LAST system note with voice enforcement (answer from this; no
  numbered list / how-to outline unless asked; no 'would you like to' closer), so it
  beats gpt-4o's boilerplate at the most influential position. Logged to /logs.
- Wired into respond() + respond_stream(). Config CHAT_DELIBERATE (default on) to
  disable if the extra call's latency annoys.
- persona: "talk, don't outline" — prose over listicles, the first concrete move
  over a survey of options.
- test_chat.py (gating + note composition + disabled). Suite 84, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-23 00:35:49 +00:00
serversdown ea30c3dd67 feat: chat-side feedback — reactions in conversation thread back to her thoughts
Closes the last loop gap: when she raised a thought in chat and Brian replied in
the conversation (not the feed), it was a dead end. Now she has a thought_response
tool — when he reacts to a thought she surfaced, she captures his take and it folds
back into that thread (next dream pass she reacts, like a feed reply).

- tools: _thought_response(thread_id, brian_said) -> thoughts.record_response.
- modes: thought_response added to _BASE (all modes).
- surfaced-note + context_note now expose each thread's #id and instruct her to use
  the tool when he engages, so she has what she needs to call it.
- test for the tool (threads reply back + bad-id handling). Suite 81, ruff clean.

Feedback now closes from both surfaces: the /thoughts feed AND live conversation.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 23:26:40 +00:00
serversdown 149e9a6dd5 feat: proactive thoughts — auto-ping salient ones + daily digest
She was passive (thoughts piled up 'open'; Brian had to mine the feed). Now she
brings them to him:

- Live: a thought >= PING_AUTO_SALIENCE (0.8) auto-pings — _compose_reachout writes
  a short personal text in her voice (not a thought-dump), on a cooldown
  (PING_COOLDOWN_MIN=60, AUTO only; explicit reach-outs bypass), quiet hours respected.
- Daily: maybe_daily_digest() texts a once-per-local-day summary of what she's been
  turning over (after DIGEST_HOUR=18), run from the dream cycle.
- maybe_ping gains bypass_cooldown (her deliberate reach-outs always go through).

8 new/updated tests (auto-ping above/below bar, digest once-per-day, floor/cooldown
isolation). Suite 80 green, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 20:25:14 +00:00
serversdown cf4238911e fix: replying to a thought no longer mislabels it 'surfaced'
'surfaced' means SHE raised it with Brian (chat lead / ping). record_response was
also setting it on Brian's reply, so every thread he touched looked surfaced even
though she never brought it to him. Replying now just stores the pending response;
status stays honest (only her surfacing sets 'surfaced').

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 20:18:12 +00:00
serversdown 3dd9eb5a3e feat(mobile): Thoughts in the mobile menu + full nav drawer on secondary pages
- Chat page: add "💭 Thoughts" to the mobile slide-out menu (with /thoughts handler),
  grouped with Journal. Thoughts was the one page mobile couldn't reach.
- nav.js: on mobile, secondary pages (Thoughts/Journal/Mind/Session/History/Hands/
  Logs) now get a ☰ slide-in drawer with the full nav + Settings — matching the
  desktop sidebar. Gated to pages without their own mobile menu, so the chat page's
  tailored hamburger/tab-bar is left untouched. Shared ITEMS list = one source of truth.

Static-only (no server change). 77 tests green.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 19:39:55 +00:00
serversdown a7966e4bab feat: web switch for her inner voice (Dolphin/3090 | Qwen-32B/MI50 | Off)
Her introspection (reflect/think) voice is now switchable live from the web
settings, read each cycle by the dream loop — so Brian can flip it off the 3090
before gaming without touching config or restarting.

- memory: runtime key/value settings table + get_setting/set_setting.
- self_state: INTROSPECTION_MODES (dolphin=local/dolphin3:8b, mi50=Qwen-32B,
  off=paused) + introspection_target()/set_introspection_mode(); default "dolphin".
  reflect() resolves from the live setting and SKIPS entirely when off.
- thoughts.think(): same resolution + skip-when-off.
- server: GET/POST /settings/introspection.
- index.html: "Inner Voice (introspection)" selector in Settings, applies instantly.
- tests: routing (dolphin/mi50), off-skip for think + reflect. Suite 77, ruff clean.

Default = Dolphin on the 3090 (richer voice). Flip to MI50 or Off in Settings
before gaming — that was the GPU-contention culprit.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 19:16:35 +00:00
serversdown a705e573a9 feat: break the reflection loop — narrative is slow-consolidated, not rewritten each cycle
The remaining feedback loop: reflect() dumped her full self-state (incl.
self_narrative) into the prompt and asked her to "update" it -> paraphrase -> save
-> feed back -> calcify. That (not the model) is what generated the recurring
"supportive presence balancing emotional intelligence for Brian" drift — even
Dolphin echoed it when handed the saved narrative.

Fix (her inner life now runs on one cognition model):
- reflect() no longer rewrites self_narrative/relationship. It uses associative
  grist (cognition.spontaneous_seed + activate) instead of rereading the bio,
  reflects THROUGH a stable IDENTITY_ANCHOR (lens, not canvas), and updates only
  the transient state (mood axes + noticings + metacognition + journal).
- self_narrative is now slow-consolidated: every CONSOLIDATE_EVERY (5) reflections,
  _consolidate_self() re-derives it from accumulated reflections + the anchor —
  never from the old narrative (the anti-loop core). Tethered to the anchor so it
  grows without drifting into generic-helper land.
- reset_self_narrative() + ran once on prod (her narrative was deeply drifted:
  "my core identity as a tool for support... serve Brian and other users").
- Prompts drop the self_narrative/relationship fields. Tests updated +
  consolidation tests. Suite 75 green, ruff clean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 06:39:19 +00:00
35 changed files with 2901 additions and 391 deletions
+6
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@@ -45,3 +45,9 @@ FEED_REACT_PROB=0.5 # chance a new thought reacts to a feed item
# Defaults to SUMMARY_BACKEND. Set to run her reflections/thoughts on a steerable model.
INTROSPECTION_BACKEND=
INTROSPECTION_MODEL=
PING_AUTO_SALIENCE=0.8 # a thought this salient auto-pings even without an explicit reach-out
PING_COOLDOWN_MIN=60 # min minutes between AUTO pings (explicit reach-outs bypass)
DIGEST_HOUR=18 # local hour to send her daily "what I've been thinking" digest
CHAT_DELIBERATE=true # think privately before answering substantive chat turns (false = faster, shallower)
MOUTH_BACKEND= # mind/mouth split: separate character/voice model for the final reply (empty = mind speaks)
MOUTH_MODEL=
+141
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@@ -0,0 +1,141 @@
# Lyra — Cognition Architecture (sketch)
> The "society of mind" direction: instead of one giant model we keep nagging with
> stricter prompts, a society of small specialized parts cooperate to produce each
> turn. **Most parts are cheap deterministic code (heuristics, math, learnable
> weights); the LLM is the exception, reserved for the few irreducibly-generative
> jobs.** Everything is anchored to who she is and tuned by feedback.
## Principles
1. **LLM is the exception, not the rule.** Bookkeeping, scoring, routing,
thresholding, retrieval → code. Generation (language, novel reasoning, memory
compression) → LLM, called sparingly.
2. **Mind ≠ Mouth.** A capable "mind" (decide / reason / use tools — helpfulness is
fine) is separate from a "mouth" (the character voice). This lets each be the
best model for *its* job — and makes the eventual fine-tune easy: you only have
to teach a small model to *sound like Lyra*, not to *be smart*.
3. **Anchored.** A fixed identity anchor governs the mouth so self-composed prompts
can't drift into generic-helper vapor. (Already exists: `self_state.IDENTITY_ANCHOR`.)
4. **Tuned by feedback, not just hand-tuning.** Learnable *weights* (over register,
memory, parts) nudged by 👍/👎 give real adaptation *without* fine-tuning a model.
5. **Allocation is the craft.** Cheap-deterministic where signal is clear; LLM where
judgment/language is needed; **hybrid** (heuristic common-case, escalate to LLM on
ambiguity) where possible.
## The blackboard: `TurnContext`
Parts don't call each other directly — they read from and write to a shared turn
state (a blackboard). Heterogeneous parts (heuristic / LLM / weights) cooperate by
annotating it. The composer reads the finished blackboard to build the prompt.
```
TurnContext {
# --- inputs ---
user_msg, session_id, history, now
# --- perception (heuristic) ---
moment : { kind: emotional|strategic|casual|existential|meta,
sentiment: -1..1, tilt: 0..1, urgency: 0..1 }
# --- state (code) ---
mood, drives, anchor
# --- retrieval (math: embeddings + cosine) ---
recalled : [memories] # spreading activation
threads : [active thoughts]
profile, narrative
# --- control (heuristic + learnable weights) ---
register : warm | coach | dry | tender | hype # how to sound
intent : console | push_back | teach | riff | act
mode : talk | cash | ... # tool allow-list
use_tools: bool
route : { mind: <model>, mouth: <model> } # which model per role
# --- generation (LLM, sparing) ---
deliberation : "her private thinking" # mind
tool_results : [...] # mind + tool exec
reply : "final text" # mouth
# --- learning (heuristic/online) ---
weights : { register_prefs, memory_weights, ... } # persisted, feedback-tuned
}
```
## The parts
| # | Part | Type | Does | Exists today? |
|---|------|------|------|---------------|
| 1 | **perceive** | heuristic | sentiment + classify the moment + tilt/urgency from session signals & his language | ✗ (new) |
| 2 | **recall** | math | embeddings → relevant memories, active threads, profile, narrative | ✓ `memory.recall*`, `cognition.activate` |
| 3 | **sense_state** | code | load mood / drives / anchor | ✓ `self_state`, `IDENTITY_ANCHOR` |
| 4 | **route** | heuristic + weights | pick register, intent, mode, and which model is mind vs mouth | ✗ (new; partly `modes`) |
| 5 | **decide+act (tools)** | LLM (mind) / code | does this turn need a tool? run it | ✓ tool loop in `chat` |
| 6 | **deliberate** | LLM (mind) | "what do I actually think" — private substance pass | ✓ `chat._deliberate` |
| 7 | **compose** | code | assemble the final prompt from anchor + register + intent + deliberation + recall + tool results + voice rules | ✓ `build_messages` (becomes the composer) |
| 8 | **speak** | LLM (mouth) | write the reply in her voice, streamed, anchored | ✓ `llm.chat_call` |
| 9 | **learn** | heuristic/online | on 👍/👎 or reaction, nudge `weights` (which register/memory worked) | ✗ (new; data exists in `ratings`) |
Most of the society (1,2,3,4,7,9) is **free, instant, deterministic, debuggable.**
The LLM shows up in only ~23 places (5/6 = mind, 8 = mouth).
## One chat turn
```
user msg
[1 perceive]──heuristic: emotional? strategic? tilting? (free)
[2 recall]───math: what lights up (memories, threads) (free)
[3 sense]────code: mood, drives, anchor (free)
[4 route]────heuristic+weights: register? intent? mind/mouth? (free)
[5 act]──────MIND model: tools if needed ─────────────┐ (LLM, only if needed)
[6 deliberate]──MIND model: what do I actually think │ (LLM, gated)
│ │
[7 compose]──code: build the prompt ◄──── anchor ──────┘ (free)
[8 speak]────MOUTH model: the reply, in her voice, streamed (LLM)
reply ──► (later) [9 learn]: 👍/👎 nudges weights (free, async)
```
## What we reuse vs. build
- **Reuse (already scattered through the code):** recall/activation, self_state +
anchor, drives (in `dream`), modes (tool gating), the deliberation pass, the
prompt assembly (`build_messages`), tool loop, ratings store.
- **Build new:** the `TurnContext` blackboard + an explicit pipeline runner; the
**perceive** heuristic; the **route** part (register/intent + model routing); the
**learn** weights loop. Mostly *unifying* existing pieces into one legible control
plane, plus 23 small heuristic parts.
## Phasing (smallest first)
- **P1 — frame:** define `TurnContext`, refactor the current chat turn into the
explicit pipeline (perceive=stub → recall → sense → route=mode-only → deliberate →
compose → speak), single model. Low-risk refactor; makes the structure real.
- **P2 — control plane:** real `perceive` (sentiment/moment) + `route`
(register/intent). Now her framing adapts to the moment, deterministically.
- **P3 — mind/mouth split:** route picks a separate voice model for `speak`. Plug a
character mouth (Claude / local / later a fine-tune). A/B vs. single-model.
- **P4 — learning:** `weights` over register/memory, nudged by ratings → cheap
adaptation, no fine-tune.
- **P5 — her voice:** a small fine-tuned "Lyra voice" model drops into the mouth slot.
## Open decisions
- **Mouth model**: Claude (warm, cloud) vs. local character vs. fine-tune. The mouth
is the crux; it must render richly (8B local may flatten).
- **perceive**: pure heuristics vs. a tiny classifier vs. embedding-to-exemplar
clusters. Probably hybrid.
- **scheduler**: fixed linear pipeline (simple, v1) vs. drive-based/parallel later.
- **tool location**: mind decides+runs tools, mouth only renders (clean split) — vs.
letting the mouth call tools (needs a tool-capable mouth).
- **latency budget**: how many LLM calls per turn is acceptable live (cheap mind +
streamed mouth keeps it ~2).
```
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# Hand-history contract (Lyra → RTO)
The canonical structured shape for a poker hand. **Lyra owns hands** — it produces this
shape (LLM parser today; the tap recorder natively, going forward), stores it, replays it
in the viewer, and exports it. **RTO consumes it** over HTTP and never reaches into Lyra.
Ownership rule: whoever owns the data owns the tools that produce it. Lyra owns the hand
DB, the viewer, and the copilot loop, so hand capture lives here. RTO is a pure engine.
Coupling: **one arrow, Lyra → RTO, HTTP only.** RTO is a standalone service (solve /
exploit / estimate); Lyra POSTs to it when it wants analysis. No shared package, no shared
DB, no shared UI components. If RTO is down, Lyra skips analysis and nothing breaks.
## Schema (`schema_version: 1`)
```jsonc
{
"schema_version": 1,
"game": "NLH", // NLH | PLO | ...
"stakes": "1/3", // or null
"hero_pos": "BTN", // one of POSITIONS
"hero_cards": ["Ah", "Kh"], // convenience mirror of the hero's players[].cards
"players": [ // every player in the hand, incl. hero
{"pos": "BTN", "stack": 300, "name": "Hero", "cards": ["Ah","Kh"], "hero": true},
{"pos": "BB", "stack": 250, "name": "Sal", "cards": null} // cards: null unless shown
],
"actions": [ // one flat chronological list across all streets
{"street": "preflop", "pos": "BTN", "action": "raise", "amount": 15},
{"street": "flop", "board": ["7d","2c","5h"]}, // a street begins with its board reveal
{"street": "flop", "pos": "BB", "action": "check"}
],
"board": ["7d","2c","5h"], // full final board, 05 cards
"result": {"pot": 40, "hero_net": 25, "summary": "one line"},
"completeness": {"cards": true, "board": true, "actions": true}
}
```
### Conventions (load-bearing)
- **Cards are lists of 2-char tokens**, `RankSuit`: rank in `23456789TJQKA` (ten = `T`),
suit in `c d h s` (lowercase). E.g. `["As","5d","2c"]`. RTO maps each token via
`pokercore.parse_card`. *(Chosen over space-joined strings: unambiguous, no re-splitting,
and it's what Lyra already stores + what the viewer reads.)*
- **Unknown cards are kept, not dropped:** `"Ax"` = known rank / unknown suit, `"x"` =
fully unknown card. The LLM parser emits these when Brian didn't state suits. The tap
recorder won't — it captures complete cards by construction — so `"x"` is an
import/parser-only concern.
- **`completeness`** tells a consumer what's safe to use: `cards`/`board` are `true` only
when every relevant card is fully specified (no `"x"`). RTO uses `false`-card hands for
positions/frequencies/pairs and skips suit-dependent math (flushes).
- **Hero appears in `players[]`** with `"hero": true` and is findable via `pos == hero_pos`.
`hero_cards` is a mirror for the viewer; `players[].cards` is the source of truth.
- **Positions:** `UTG UTG1 UTG2 MP LJ HJ CO BTN SB BB`.
- **Actions:** `post fold check call bet raise allin`. `amount` is a plain number (no `$`),
null for non-sized actions (fold/check). Street boards appear as `{street, board}` entries.
A **straddle** is recorded as a preflop `post` at a non-blind position (typically 2×BB,
voluntary); preflop action starts left of it and it acts last, but that's reflected by
action *order*, not a distinct verb.
- **Streets:** `preflop flop turn river`.
`lyra/poker.py:normalize_structured()` is the single function that guarantees this shape.
It runs on store and on read, and is idempotent.
## Transport (HTTP, Lyra serves on :7078)
- `GET /hands/data?limit=N` → `{ "hands": [ {id, position, hole_cards, board, result, tag,
at, lesson, venue, stakes, has_structured}, ... ] }` — flat list for browsing. Use
`has_structured` to pick which hands have a replayable body worth fetching.
- `GET /hand/{id}/data` → the full hand row; `structured` is the object above (or `null`
for a flat quick-log that hasn't been reconstructed).
RTO's "Lyra bridge" (its `docs/estimator-design.md`, Phase B) walks `structured.actions`
to classify each villain decision into `checked_to` / `facing_bet` / `facing_raise`, and
uses shown `cards` + that street's `board` for board-relative categories. Everything that
walk needs is in the schema above.
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# Hand recorder — design note
A tap-to-build hand recorder. The point isn't "nicer input" — it's **correctness by
construction**: every tap writes a known action into a known slot, so there's no parse
step that can be wrong. It sidesteps the whole class of LLM-parse replay bugs. The text
parser stays for importing the backlog (old notes, Trilium, ChatGPT history); the recorder
is clean capture going forward.
Output is the canonical structured shape in [HAND_HISTORY.md](HAND_HISTORY.md) — so it
drops straight into the DB and the existing replay viewer, and flows to RTO unchanged.
## Principles
1. **Correctness by construction** — the UI only lets you build valid hands; the emitter
produces the contract shape; the server `normalize_structured()` is the final guarantee.
2. **Reusable module, mount-agnostic.** Decision: overlay first, swap to standalone if the
overlay fights the chat page — *reusing the code either way*. So the recorder is a
self-contained module mounted into a container element, with the **emit logic kept pure
(no DOM)**. Moving overlay → standalone is a re-mount, not a rewrite.
3. **Don't reinvent what Lyra knows.** Pre-fill from live session state.
## Architecture
```
lyra/web/static/recorder.js # the module: state machine + DOM shell + buildStructured()
lyra/web/static/recorder.css # scoped styles (full-screen table + keypad)
```
- `Recorder.mount(containerEl, { sessionId, onSave, onClose })` — instantiates into any
container. In V1 the container is a full-screen overlay `<div>` inside `index.html`
(chat/session page stays mounted underneath — a flip-over, not a route change). If that
proves janky, the *same module* mounts into `recorder.html` with zero logic changes.
- **Pure core, separable from DOM:** `buildStructured(state) -> structuredDict`. No element
access — takes the in-memory state, returns the contract object. This is the testable,
reusable heart; the DOM shell only reads/writes `state` and calls `buildStructured` on save.
## Pre-fill from live state (the "it already knows" feel)
Source: `GET /session/data` (→ `poker.hud`). Today it gives us:
- `session`: `venue`, `stakes`, `game`, `format`, `is_live`
- `stack.current` → hero's starting stack for the hand
- `villains[]`: `name`, `category`, `tendencies`, `last_note` (the players read this session)
Derived in the recorder:
- **Blinds** parsed from `stakes` ("1/3" → SB 1, BB 3) → auto-seed the `post` actions.
- **Hero stack** from `stack.current`.
**Two gaps to close as part of the build** (flagged, not yet done):
1. **Seats aren't in the HUD bundle.** `player_reads` *has* a `seat` column, but
`_session_villains()` doesn't select it — so we can name the villains but not place them.
Fix: add `seat` (latest read per player) to the villains payload, then auto-seat them.
Until then, V1 seats known villains in read-order and you assign positions by tapping.
2. **Hero position isn't tracked live** (button/seat moves every hand) — so `hero_pos` is a
per-hand tap, seeded to last-used. That's correct, not a gap to "fix", just noting it.
## In-memory state model
```js
state = {
meta: { game, stakes, venue, sessionId }, // from /session/data
blinds: { sb, bb }, // parsed from stakes
heroPos: "BTN", // tapped per hand
seats: [ { pos, name, stack, cards: null, in: true } ], // incl. hero seat
street: "preflop", // street currently being entered
board: { flop: [], turn: [], river: [] },
actions:[ { street, pos, action, amount } ], // appended as you tap
result: { pot: null, heroNet: null, summary: "" }
}
```
`buildStructured(state)`
| contract field | from |
|---|---|
| `hero_pos` | `state.heroPos` |
| `hero_cards` | the hero seat's `cards` |
| `players[]` | `state.seats` (`{pos,stack,name,cards}`; emitter doesn't set `hero`/version — server normalize does) |
| `actions[]` | `state.actions`, with a `{street, board}` reveal entry spliced in at each street boundary from `state.board` |
| `board` | `flop + turn + river` concatenated |
| `result` | `state.result` |
Client builds best-effort; **`store_hand_history()``normalize_structured()` is the
authority** (canonical cards, hero sync, `schema_version`, `completeness`). Keeps the
client dumb and the contract enforced in one place.
## Persistence
New endpoint (small, part of the build):
```
POST /hands body: { structured, session_id?, tag?, lesson? }
-> store_hand_history(structured, ...) -> { id }
```
On save: POST, then hand off to the existing viewer `/hand/{id}` to replay — which doubles
as the correctness check (what you tapped is exactly what replays).
## Scope
**V1 — core loop (chosen).** Seats + cards + per-street actions emitting valid structured
JSON. Manual street advance (a "next street" button + board entry), free bet-size entry
(type the number). Proves capture → store → replay end to end on the locked schema.
### Card entry (V1)
Contextual: tap a card slot (hero card, board square, "they showed") → a compact picker
pops at that slot. One picker holds **4 color-coded suits + 13 ranks + `x` + unknown-card**.
Whichever you tap first sets the flow for that card — no mode switch:
- **Suit first → it locks** (stays lit). Each subsequent rank tap places `rank+lockedSuit`
and auto-advances. Flush flop = `♥ T 8 5` (4 taps); suited hole = `♥ A K` (3 taps).
- **Rank first → card is pending a suit**; the next tap must be a suit (or `x`). Best for
rainbow/mixed. Locked suit stays in effect until a different suit is tapped.
- **`x`** = unknown suit → stores e.g. `Ax`; flips `completeness.cards` false so RTO skips
suit-dependent math. **Unknown-card** button = a villain card never shown (`x`).
No typing — lowercase tokens are the internal/contract format only; the player only ever
taps symbols. State: `lockedSuit` (nullable) + the active slot; auto-advance on complete.
**V2 — the smart keypad.** The contextual state machine layered on top: tracks whose turn
it is and the current bet, offers only legal actions (check vs call; bet/raise reveal size
presets ½/¾/pot/+1bb), auto-advances the street when action closes, tap-a-seat to set the
actor, one-tap "they showed [cards]" at showdown. ~610 taps, no typing. Built on the same
`state` + `buildStructured`, so V1's emitter doesn't change — V2 just drives `state` smarter.
## Layout sketch (full-screen overlay)
```
┌───────────────────────────── Record hand ─────────────── ✕ ┐
│ (CO) (BTN) │
│ (HJ) ◯ oval table ◯ (SB) │
│ (MP) (UTG) (BB·hero) │
│ board: [ 7d ][ 2c ][ 5h ] pot: 40 │
├──────────────────────────────────────────────────────────────┤
│ acting: BB [ fold ][ check ][ call ][ bet ][ raise ] │
│ amount: [ 15 ] [ ½ ][ ¾ ][ pot ][ +1bb ] (V2) │
│ [ ◀ prev street ] [ next street ▶ ] [ they showed… ] │
├──────────────────────────────────────────────────────────────┤
│ preflop: BTN raise 15 · BB call [ save & replay ] │
└──────────────────────────────────────────────────────────────┘
```
## Build order
1. `POST /hands` endpoint + add `seat` to the villains payload (server, small).
2. `recorder.js` skeleton: `mount()`, `state`, `buildStructured()` (pure).
3. Overlay shell in `index.html` (open button in session/cash mode) + `recorder.css`.
4. V1 capture flow → save → replay. Validate a real hand round-trips identically.
5. V2 smart keypad on top.
```
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"""The chat turn loop: persona + tiered memory + recent context -> reply.
"""The chat turn: assemble the prompt (lyra.mind) then speak + persist.
Context is assembled in tiers (oldest/most-compacted first):
1. persona
2. long-term gist — relevant *summaries* of other sessions
3. sharp details — a few raw cross-session exchanges (so specifics survive)
4. recent raw turns of the current session (full fidelity)
5. the new user message
After replying, the session is compacted if enough new turns have accumulated.
`mind.assemble()` runs the society of parts (perceive → route → compose →
deliberate) and hands back a ready message list + the active mode. Then:
- the MIND (the chat backend/model) runs the tool/generation loop — decide,
reason, run tools — and produces a draft.
- the MOUTH (a separate character model, if configured) re-voices that draft in
her own voice. Default: no mouth configured → the mind's draft IS the reply
(bit-for-bit the old behavior). The mouth slot is where a fine-tuned voice lands.
"""
from __future__ import annotations
from lyra import clock, config, llm, logbus, memory, modes, persona, self_state, summary, thoughts
from lyra import config, llm, logbus, memory, mind, modes, summary
from lyra import tools as toolkit
from lyra.llm import Backend, Message
from lyra.llm import Backend
RECALL_K = 3 # raw cross-session "sharp detail" hits
RECENT_N = 10 # raw turns of the current session
SUMMARY_K = 3 # other-session gists
MAX_TOOL_ROUNDS = 5 # cap tool-call iterations per turn
# Backends that support function-calling. The MI50's llama.cpp server only does
# tools when launched with --jinja; until it is, keep tools to cloud so MI50 chat
# doesn't 500 on the tools param. Add "mi50" here once that flag is set.
TOOL_BACKENDS = {"cloud"}
_TANGLED = "(I got tangled using my tools there — say that again?)"
def _mode_state_note(mode: modes.Mode | None) -> str | None:
"""Dynamic, per-turn state for the active mode. Currently: surface Alligator
Blood while it's engaged on the live session, so she stays in that register."""
if not mode or mode.key != modes.CASH.key:
return None
from lyra import poker # local import: keep the core/domain coupling at call time
if poker.alligator_active():
return (
"🐊 ALLIGATOR BLOOD is ON for this session. Coach Brian in that register: "
"hang around, refuse to die, don't force miracles, make opponents beat him "
"correctly. Tough, patient, steady — no heroics, no spew, no quitting."
)
return None
def _maybe_switch_mode(session_id: str, tool_name: str) -> None:
"""Keep the chat framing aligned with the live data: opening a poker session
auto-flips this chat into Cash mode (so the next turn gets the cash card + the
full live toolset). Manual UI switching still overrides anytime."""
if tool_name == "start_session":
memory.set_session_mode(session_id, modes.CASH.key)
logbus.log("info", "mode auto-switch", session=session_id, mode=modes.CASH.key)
def _summary_note(summaries: list[memory.Summary]) -> Message:
lines = [f"- ({(s.session_started_at or s.created_at)[:10]}) {s.content}" for s in summaries]
body = "Gist of earlier sessions (compacted — ask if you need specifics):\n" + "\n".join(lines)
return {"role": "system", "content": body}
def _detail_note(exchanges: list[memory.Exchange]) -> Message:
lines = [f"- ({ex.created_at[:10]}, {ex.role}) {ex.content}" for ex in exchanges]
body = "Specific things you recall from past conversations:\n" + "\n".join(lines)
return {"role": "system", "content": body}
def _inner_life_note() -> Message | None:
"""One coherent window onto what she's been doing on her own since last time —
the threads she's turning over plus the things she's written for herself. Sits
with her self-state so chat reads as a continuous mind, not a fresh boot. The
persona tells her to weave this in naturally when it fits."""
parts: list[str] = []
threads = thoughts.context_note() # active threads, with their latest thought
if threads:
parts.append(threads)
wrote = memory.list_journal(limit=3, kinds=("journal", "note"))
if wrote:
lines = "\n".join(f"- ({w['created_at'][:10]}) {w['content']}" for w in reversed(wrote))
parts.append(
"Things you've written in your journal lately (yours — you can refer back "
"to them if they're relevant):\n" + lines
)
if not parts:
return None
return {"role": "system", "content": "\n\n".join(parts)}
def _now_note() -> Message:
"""Current wall-clock time + how long since Brian last said anything.
Stated as plain fact — she has no clock otherwise, so without this 'now' and
the gap since the last turn are invisible to her.
"""
line = f"The current date and time is {clock.stamp()}."
gap = clock.humanize_gap(memory.last_exchange_at())
line += (
f" It has been {gap} since Brian last spoke with you."
if gap else " This is the first thing Brian has ever said to you."
)
return {"role": "system", "content": line}
def _render(messages: list[Message]) -> str:
"""Human-readable dump of the exact prompt, for the live-log inspector."""
return "\n\n".join(f"[{m['role']}]\n{m['content']}" for m in messages)
def build_messages(session_id: str, user_msg: str,
mode: modes.Mode | None = None) -> list[Message]:
"""Assemble the full, tiered message list for one turn."""
messages: list[Message] = [{"role": "system", "content": persona.system_prompt()}]
# Autonomy Core: Lyra's own evolving interiority (mood, self-narrative). Comes
# right after the persona — her sense of self before her model of the world.
messages.append({"role": "system", "content": self_state.render_for_context(self_state.load())})
# Her ongoing inner life — the threads she's turning over and what she's written
# for herself — so she's continuous across conversations and can pick up where she
# left off, not only when a thought crosses the surface bar below. Rides with the
# self; the persona tells her to bring it into conversation naturally when it fits.
inner = _inner_life_note()
if inner:
messages.append(inner)
# Mode card: how to behave *right now* (e.g. live-cash copilot). High priority —
# it sits just after her sense of self, before her model of the world. Talk mode
# has no card (the persona's default voice is the Talk register).
if mode and mode.card:
messages.append({"role": "system", "content": mode.card})
# Live ritual state (e.g. Alligator Blood ON) — dynamic, so it rides alongside
# the static card and keeps her in-register for the whole stretch, not just the
# turn she flipped it.
state_note = _mode_state_note(mode)
if state_note:
messages.append({"role": "system", "content": state_note})
# When she is: current time + the gap since Brian last spoke (she has no clock).
messages.append(_now_note())
# Thought loop: if Brian's been away and one of her own threads has built past
# the surface bar, let her lead with it (once). This is her #6 — bringing what
# she thought about while alone *to* him. Runs before the world-model tiers so
# it's framed as her interiority, like the self-state.
surfaced = thoughts.maybe_surface(memory.last_exchange_at())
if surfaced:
messages.append({"role": "system", "content": surfaced})
# Semantic memory: the distilled profile (who Brian is) — answers identity
# questions that raw recall can't. Always in context when it exists.
profile = memory.get_profile()
if profile:
messages.append(
{"role": "system", "content": "What you know about Brian:\n" + profile}
)
# Time-aware memory: the current narrative (recent arc, trends, callbacks).
narrative = memory.get_narrative()
if narrative:
messages.append(
{"role": "system", "content": "What's going on with Brian lately:\n" + narrative}
)
recent = memory.recent(session_id, n=RECENT_N)
recent_ids = {ex.id for ex in recent}
# Tier 1: compacted gists of *other* sessions (long-term, general idea).
summaries = memory.recall_summaries(user_msg, k=SUMMARY_K, exclude_session=session_id)
if summaries:
messages.append(_summary_note(summaries))
# Tier 2: a few sharp raw details from other sessions (so specifics survive
# compaction). Skip the current session (its raw turns are in `recent`).
recalled = [
ex for ex in memory.recall(user_msg, k=RECALL_K)
if ex.id not in recent_ids and ex.session_id != session_id
]
if recalled:
messages.append(_detail_note(recalled))
# Tier 3: current session, full fidelity.
for ex in recent:
messages.append({"role": ex.role, "content": ex.content})
messages.append({"role": "user", "content": user_msg})
logbus.log(
"debug", "context built",
recent=len(recent), summaries=len(summaries), details=len(recalled),
chars=sum(len(m["content"]) for m in messages), detail=_render(messages),
)
return messages
def respond(session_id: str, user_msg: str, backend: Backend = "cloud",
model_override: str | None = None) -> str:
"""Produce Lyra's reply to a single user message and persist the exchange.
`model_override` (from the UI's cloud-model picker) only applies on the cloud
backend; local/mi50 keep their own configured models.
"""
cfg = config.load()
# Live chat uses the stronger chat_model on cloud (bulk consolidation keeps
# cloud_model). local/mi50 use their own configured model.
def _resolve_model(backend: Backend, model_override: str | None, cfg) -> str:
"""Live chat uses the stronger chat_model on cloud; local/mi50 use their own.
The UI's cloud-model picker only applies on the cloud backend."""
model = {"local": cfg.local_model, "cloud": cfg.chat_model, "mi50": cfg.mi50_model}.get(
backend, backend
)
if model_override and backend == "cloud":
model = model_override
logbus.log(
"info", "chat request", session=session_id, backend=backend,
model=model, embed=cfg.embed_backend,
)
return model
mode = modes.get(memory.get_session_mode(session_id))
messages = build_messages(session_id, user_msg, mode=mode)
# Tool loop: offer Lyra her tools (scoped to the mode); if she calls one, run it
# and feed the result back so she can continue, until she returns a text reply.
tool_specs = toolkit.specs(mode.tools) if backend in TOOL_BACKENDS else None
ctx = {"session_id": session_id, "backend": backend}
def _mouth_target(cfg, mind_backend: Backend, mind_model: str | None):
"""The mouth (backend, model) if configured AND different from the mind; else None
(mouth == mind → no separate voice pass)."""
if not cfg.mouth_backend and not cfg.mouth_model:
return None
backend = cfg.mouth_backend or mind_backend
model = cfg.mouth_model or None
if backend == mind_backend and model == mind_model:
return None
return backend, model
def _maybe_switch_mode(session_id: str, tool_name: str) -> None:
"""Opening a poker session auto-flips this chat into Poker mode. Manual UI switching
still overrides anytime."""
if tool_name == "start_session":
memory.set_session_mode(session_id, modes.CASH.key)
logbus.log("info", "mode auto-switch", session=session_id, mode=modes.CASH.key)
def _mind_loop(messages, backend: Backend, model: str | None, tool_specs,
ctx: dict, session_id: str) -> tuple[str, list[str]]:
"""Run the tool/generation loop on the MIND model (non-streaming). Mutates
`messages` with tool calls/results. Returns (draft_reply, tool_names_run)."""
tools_run: list[str] = []
reply = ""
for _ in range(MAX_TOOL_ROUNDS):
assistant_msg, tool_calls = llm.chat_call(
@@ -223,77 +66,117 @@ def respond(session_id: str, user_msg: str, backend: Backend = "cloud",
if not tool_calls:
reply = assistant_msg.get("content") or ""
break
messages.append(assistant_msg) # her tool-call request
messages.append(assistant_msg)
for tc in tool_calls:
result = toolkit.dispatch(tc["name"], tc["arguments"], ctx)
logbus.log("info", "tool call", session=session_id, tool=tc["name"], result=result[:80])
messages.append({"role": "tool", "tool_call_id": tc["id"], "content": result})
_maybe_switch_mode(session_id, tc["name"])
tools_run.append(tc["name"])
return reply, tools_run
def _voice_pass(messages, draft: str, backend: Backend, model: str | None) -> str:
"""Mouth: re-render the mind's draft in her voice. Falls back to the draft on failure."""
try:
out = llm.complete(mind.voice_messages(messages, draft), backend=backend, model=model)
return (out or "").strip() or draft
except Exception as exc:
logbus.log("error", "voice pass failed", error=str(exc)[:160])
return draft
def respond(session_id: str, user_msg: str, backend: Backend = "cloud",
model_override: str | None = None) -> str:
"""Produce Lyra's reply to a single user message and persist the exchange."""
cfg = config.load()
model = _resolve_model(backend, model_override, cfg)
logbus.log("info", "chat request", session=session_id, backend=backend,
model=model, embed=cfg.embed_backend)
turn = mind.assemble(session_id, user_msg, backend, model)
messages = turn.messages
tool_specs = toolkit.specs(turn.mode.tools) if backend in TOOL_BACKENDS else None
ctx = {"session_id": session_id, "backend": backend}
reply, _ = _mind_loop(messages, backend, model, tool_specs, ctx, session_id)
mouth = _mouth_target(cfg, backend, model)
if mouth and reply:
reply = _voice_pass(messages, reply, *mouth)
if not reply:
reply = "(I got tangled using my tools there — say that again?)"
logbus.log("info", "reply", session=session_id, chars=len(reply))
reply = _TANGLED
logbus.log("info", "reply", session=session_id, chars=len(reply), voiced=bool(mouth))
memory.remember(session_id, "user", user_msg)
memory.remember(session_id, "assistant", reply)
# Compact this session once enough new turns have piled up.
summary.maybe_summarize_async(session_id)
summary.maybe_summarize_async(session_id) # compact once enough new turns pile up
return reply
def respond_stream(session_id: str, user_msg: str, backend: Backend = "cloud",
model_override: str | None = None):
"""Streaming generator version of `respond`.
Yields ("delta", text) as content streams in, and ("tool", name) when a tool
runs. Persists the full exchange and yields a final ("done", reply) — matching
`respond`'s side effects (memory + compaction) exactly.
"""
"""Streaming generator version of `respond`. Yields ("delta", text), ("tool", name),
and a final ("done", reply). Same side effects as `respond`."""
cfg = config.load()
model = {"local": cfg.local_model, "cloud": cfg.chat_model, "mi50": cfg.mi50_model}.get(
backend, backend
)
if model_override and backend == "cloud":
model = model_override
logbus.log(
"info", "chat request (stream)", session=session_id, backend=backend,
model=model, embed=cfg.embed_backend,
)
model = _resolve_model(backend, model_override, cfg)
logbus.log("info", "chat request (stream)", session=session_id, backend=backend,
model=model, embed=cfg.embed_backend)
mode = modes.get(memory.get_session_mode(session_id))
messages = build_messages(session_id, user_msg, mode=mode)
tool_specs = toolkit.specs(mode.tools) if backend in TOOL_BACKENDS else None
turn = mind.assemble(session_id, user_msg, backend, model)
messages = turn.messages
tool_specs = toolkit.specs(turn.mode.tools) if backend in TOOL_BACKENDS else None
ctx = {"session_id": session_id, "backend": backend}
parts: list[str] = []
for _ in range(MAX_TOOL_ROUNDS):
assistant_msg = None
tool_calls = None
for ev, payload in llm.chat_call_stream(
messages, backend=backend, model=model, tools=tool_specs
):
if ev == "delta":
parts.append(payload)
yield ("delta", payload)
elif ev == "message":
assistant_msg = payload
elif ev == "tool_calls":
tool_calls = payload
if not tool_calls:
break
messages.append(assistant_msg) # her tool-call request
for tc in tool_calls:
result = toolkit.dispatch(tc["name"], tc["arguments"], ctx)
logbus.log("info", "tool call", session=session_id, tool=tc["name"], result=result[:80])
messages.append({"role": "tool", "tool_call_id": tc["id"], "content": result})
_maybe_switch_mode(session_id, tc["name"])
yield ("tool", tc["name"])
mouth = _mouth_target(cfg, backend, model)
reply = "".join(parts)
if not reply:
reply = "(I got tangled using my tools there — say that again?)"
yield ("delta", reply)
logbus.log("info", "reply", session=session_id, chars=len(reply))
if mouth is None:
# No separate voice: stream the mind directly (the original path, unchanged).
parts: list[str] = []
for _ in range(MAX_TOOL_ROUNDS):
assistant_msg = None
tool_calls = None
for ev, payload in llm.chat_call_stream(
messages, backend=backend, model=model, tools=tool_specs
):
if ev == "delta":
parts.append(payload)
yield ("delta", payload)
elif ev == "message":
assistant_msg = payload
elif ev == "tool_calls":
tool_calls = payload
if not tool_calls:
break
messages.append(assistant_msg)
for tc in tool_calls:
result = toolkit.dispatch(tc["name"], tc["arguments"], ctx)
logbus.log("info", "tool call", session=session_id, tool=tc["name"], result=result[:80])
messages.append({"role": "tool", "tool_call_id": tc["id"], "content": result})
_maybe_switch_mode(session_id, tc["name"])
yield ("tool", tc["name"])
reply = "".join(parts)
if not reply:
reply = _TANGLED
yield ("delta", reply)
else:
# Mind decides + runs tools (non-streamed); mouth re-voices, streamed.
draft, tools_run = _mind_loop(messages, backend, model, tool_specs, ctx, session_id)
for name in tools_run:
yield ("tool", name)
parts = []
try:
for ev, payload in llm.chat_call_stream(
mind.voice_messages(messages, draft), backend=mouth[0], model=mouth[1], tools=None
):
if ev == "delta":
parts.append(payload)
yield ("delta", payload)
except Exception as exc:
logbus.log("error", "voice stream failed", error=str(exc)[:160])
reply = "".join(parts).strip() or draft or _TANGLED
if not parts:
yield ("delta", reply)
logbus.log("info", "reply", session=session_id, chars=len(reply), voiced=bool(mouth))
memory.remember(session_id, "user", user_msg)
memory.remember(session_id, "assistant", reply)
summary.maybe_summarize_async(session_id)
+16 -3
View File
@@ -32,9 +32,17 @@ class Config:
ntfy_topic: str # topic to publish to, e.g. "lyra"
web_url: str # base url of the Lyra web app, for push tap-through links
timezone: str # IANA tz for quiet hours / local time
ping_salience: float # min thought salience to push (eager = ~0.7)
ping_cooldown_min: int # min minutes between pushes (eager = 0)
ping_salience: float # hard floor for any push (0 = her decision drives it)
ping_auto_salience: float # a thought this salient auto-pings even without an explicit reach-out
ping_cooldown_min: int # min minutes between AUTO pushes (explicit reach-outs bypass it)
ping_quiet_hours: str # local "start-end" 24h window to stay silent, e.g. "1-9"
digest_hour: int # local hour (0-23) to send her daily "what I've been thinking" digest
chat_deliberate: bool # think privately before answering substantive chat turns
# Mind/mouth split: the mind (the chat backend/model above) decides, reasons, and
# runs tools; the mouth re-voices the final reply in her character. Empty = mouth
# is the mind (no separate pass) — the slot for an eventual fine-tuned voice.
mouth_backend: str
mouth_model: str | None
# External input feed (her #1: react to the world). Comma-separated RSS/Atom URLs.
feeds: tuple[str, ...]
feed_react_prob: float # chance a would-be new thread reacts to a feed item instead
@@ -73,8 +81,13 @@ def load() -> Config:
web_url=os.getenv("LYRA_WEB_URL", "").rstrip("/"),
timezone=os.getenv("LYRA_TIMEZONE", "America/New_York"),
ping_salience=float(os.getenv("PING_SALIENCE", "0.0")), # her decision drives pinging; optional floor
ping_cooldown_min=int(os.getenv("PING_COOLDOWN_MIN", "0")),
ping_auto_salience=float(os.getenv("PING_AUTO_SALIENCE", "0.8")),
ping_cooldown_min=int(os.getenv("PING_COOLDOWN_MIN", "60")),
ping_quiet_hours=os.getenv("PING_QUIET_HOURS", "1-9"),
digest_hour=int(os.getenv("DIGEST_HOUR", "18")),
chat_deliberate=os.getenv("CHAT_DELIBERATE", "true").lower() not in ("0", "false", "no"),
mouth_backend=os.getenv("MOUTH_BACKEND", "").lower(),
mouth_model=os.getenv("MOUTH_MODEL") or None,
feeds=_csv("LYRA_FEEDS", "https://hnrss.org/frontpage,https://www.pokernews.com/rss.php"),
feed_react_prob=float(os.getenv("FEED_REACT_PROB", "0.5")),
)
+5
View File
@@ -87,6 +87,11 @@ def dream_cycle(backend: Backend | None = None, force: bool = False) -> dict:
feeds.refresh()
except Exception as exc:
logbus.log("error", "feed refresh failed", error=str(exc)[:160])
# Her daily "what I've been turning over" digest (sends at most once/local-day).
try:
thoughts.maybe_daily_digest()
except Exception as exc:
logbus.log("error", "daily digest failed", error=str(exc)[:160])
actions: list[str] = []
+14 -7
View File
@@ -54,17 +54,24 @@ def _digest_month(gists: list[str], backend: Backend) -> str:
return partials[0]
def rebuild_eras(backend: Backend | None = None) -> dict:
"""(Re)build a digest for every month that has session gists."""
def rebuild_eras(backend: Backend | None = None, force: bool = False) -> dict:
"""Build a digest per month, but only for months whose session count changed since
the last build — old months don't change, so re-digesting them every consolidation
pass was pure wasted LLM work (and MI50 heat). `force=True` rebuilds everything."""
backend = backend or config.load().summary_backend
by_month = memory.summaries_by_month()
months = 0
have = {e.month: e.session_count for e in memory.list_eras()}
built = skipped = 0
for month in sorted(by_month):
n = len(by_month[month])
if not force and have.get(month) == n:
skipped += 1
continue # unchanged month — keep its existing digest
digest = _digest_month(by_month[month], backend)
memory.store_era(month, digest, len(by_month[month]))
months += 1
logbus.log("info", "era built", month=month, sessions=len(by_month[month]))
report = {"months": months}
memory.store_era(month, digest, n)
built += 1
logbus.log("info", "era built", month=month, sessions=n)
report = {"built": built, "skipped": skipped, "months": built + skipped}
logbus.log("info", "eras complete", **report)
return report
+22
View File
@@ -95,6 +95,12 @@ CREATE TABLE IF NOT EXISTS journal (
);
CREATE INDEX IF NOT EXISTS idx_journal_created ON journal(created_at);
-- Small runtime key/value settings (UI-tunable, read live by the dream loop).
CREATE TABLE IF NOT EXISTS settings (
key TEXT PRIMARY KEY,
value TEXT
);
-- Brian's behind-the-scenes feedback on Lyra's outputs (chat replies, reflections,
-- journal/metacognition). Stored as (context, content, rating) — the shape a future
-- fine-tune / preference dataset wants. One row per rated item (re-rating updates it).
@@ -639,6 +645,22 @@ def backfill_journal_embeddings(limit: int | None = None) -> int:
return n
def get_setting(key: str, default: str | None = None) -> str | None:
"""A runtime setting value (UI-tunable), or `default` if unset."""
r = _connection().execute("SELECT value FROM settings WHERE key = ?", (key,)).fetchone()
return r["value"] if r else default
def set_setting(key: str, value: str) -> None:
conn = _connection()
with conn:
conn.execute(
"INSERT INTO settings (key, value) VALUES (?, ?) "
"ON CONFLICT(key) DO UPDATE SET value = excluded.value",
(key, str(value)),
)
def add_rating(kind: str, rating: int, content: str, context: str | None = None,
ref: str | None = None, note: str | None = None) -> int:
"""Record (or replace) Brian's feedback on one Lyra output. One row per item:
+384
View File
@@ -0,0 +1,384 @@
"""The control plane: assemble one turn from a society of small parts.
This is the explicit version of what used to be inline in `chat.py`. A turn is
built by running an ordered pipeline of *parts* over a shared `TurnContext`
(blackboard): each part reads what it needs and annotates the context, and the
last steps produce the message list `chat` then hands to the voice model.
P1 (this): the frame, behavior-preserving. The parts wrap the existing logic —
perceive (stub) -> route (the session's mode) -> compose (tiered prompt) ->
deliberate (private 'what do I actually think' pass).
Later phases fill in perceive (read the moment), route (register/intent + model
routing), and a learn loop — see docs/COGNITION.md. Most parts are cheap
deterministic code; the LLM is the exception (deliberate here, speak in `chat`).
"""
from __future__ import annotations
from dataclasses import dataclass, field
from lyra import clock, config, llm, logbus, memory, modes, perceive, persona, self_state, thoughts
from lyra.llm import Backend, Message
RECALL_K = 3 # raw cross-session "sharp detail" hits
RECENT_N = 10 # raw turns of the current session
SUMMARY_K = 3 # other-session gists
# --- prompt parts (compose) ----------------------------------------------
def _mode_state_note(mode: modes.Mode | None) -> str | None:
"""Dynamic, per-turn state for the active mode. Currently: surface Alligator
Blood while it's engaged on the live session, so she stays in that register."""
if not mode or mode.key != modes.CASH.key:
return None
from lyra import poker # local import: keep the core/domain coupling at call time
if poker.alligator_active():
return (
"🐊 ALLIGATOR BLOOD is ON for this session. Coach Brian in that register: "
"hang around, refuse to die, don't force miracles, make opponents beat him "
"correctly. Tough, patient, steady — no heroics, no spew, no quitting."
)
return None
def _summary_note(summaries: list[memory.Summary]) -> Message:
lines = [f"- ({(s.session_started_at or s.created_at)[:10]}) {s.content}" for s in summaries]
body = "Gist of earlier sessions (compacted — ask if you need specifics):\n" + "\n".join(lines)
return {"role": "system", "content": body}
def _detail_note(exchanges: list[memory.Exchange]) -> Message:
lines = [f"- ({ex.created_at[:10]}, {ex.role}) {ex.content}" for ex in exchanges]
body = "Specific things you recall from past conversations:\n" + "\n".join(lines)
return {"role": "system", "content": body}
def _inner_life_note() -> Message | None:
"""One coherent window onto what she's been doing on her own since last time —
the threads she's turning over plus the things she's written for herself. Sits
with her self-state so chat reads as a continuous mind, not a fresh boot. The
persona tells her to weave this in naturally when it fits."""
parts: list[str] = []
threads = thoughts.context_note() # active threads, with their latest thought
if threads:
parts.append(threads)
wrote = memory.list_journal(limit=3, kinds=("journal", "note"))
if wrote:
lines = "\n".join(f"- ({w['created_at'][:10]}) {w['content']}" for w in reversed(wrote))
parts.append(
"Things you've written in your journal lately (yours — you can refer back "
"to them if they're relevant):\n" + lines
)
if not parts:
return None
return {"role": "system", "content": "\n\n".join(parts)}
def _mode_menu_note(current: modes.Mode | None) -> str:
"""Tell her the modes she can switch to + when to offer it. She judges the fit
(the model reads context far better than a keyword would)."""
menu = ", ".join(f"{m.label} ({k})" for k, m in modes.MODES.items())
cur = current.label if current else "Talk"
return (
f"Your modes: {menu}. You're in {cur} right now. If Brian is clearly doing a "
"different kind of work than your current mode — weighing a real decision while "
"you're in Talk, digging into engineering, reviewing poker away from the table — "
"briefly OFFER to switch (one short line). If he says yes, call set_mode with the "
"mode key. Don't offer every turn or nag; only when it genuinely fits and serves him."
)
def _now_note() -> Message:
"""Current wall-clock time + how long since Brian last said anything."""
line = f"The current date and time is {clock.stamp()}."
gap = clock.humanize_gap(memory.last_exchange_at())
line += (
f" It has been {gap} since Brian last spoke with you."
if gap else " This is the first thing Brian has ever said to you."
)
return {"role": "system", "content": line}
def _render(messages: list[Message]) -> str:
"""Human-readable dump of the exact prompt, for the live-log inspector."""
return "\n\n".join(f"[{m['role']}]\n{m['content']}" for m in messages)
# Generous triggers for the heavy situational persona sections — err toward INCLUDING
# them (a false positive is a few spare KB; a false negative risks confabulation or
# eyeballed poker math). The core (identity + voice) is always present regardless.
_META_HINTS = (
"you work", "how do you", "how does your", "your memory", "your dream", "your thought",
"do you remember", "are you", "do you feel", "conscious", "sentient", "yourself",
"your mind", "who are you", "what are you", "your origin", "how were you", "how did you",
"your inner", "your reflect", "your journal",
)
_POKER_HINTS = (
"poker", "fold", "call", "raise", "river", "turn", "flop", "preflop", "equity", "range",
"villain", "stack", "tilt", "hand", "bluff", "pot", "3bet", "gto", "outs", "draw",
)
def _persona_block(user_msg: str, mode: modes.Mode | None, moment: dict | None) -> str:
"""Core persona always; pull in situational sections (origin/self-model, poker
guardrails) only when the turn calls for it."""
parts = [persona.core_prompt()]
um = user_msg.lower()
kind = (moment or {}).get("kind")
if kind == "meta" or any(h in um for h in _META_HINTS):
parts += [persona.section("What you are"), persona.section("How you actually work")]
poker = (mode and mode.key in ("poker_cash", "study")) or kind == "strategic" \
or any(h in um for h in _POKER_HINTS)
if poker:
parts.append(persona.section("What you do NOT do"))
return "\n\n".join(p for p in parts if p)
def build_messages(session_id: str, user_msg: str,
mode: modes.Mode | None = None, moment: dict | None = None) -> list[Message]:
"""Assemble the full, tiered message list for one turn."""
messages: list[Message] = [{"role": "system", "content": _persona_block(user_msg, mode, moment)}]
# Autonomy Core: Lyra's own evolving interiority (mood, self-narrative). Comes
# right after the persona — her sense of self before her model of the world.
messages.append({"role": "system", "content": self_state.render_for_context(self_state.load())})
# Her ongoing inner life — threads she's turning over + what she's written for
# herself — so chat reads as a continuous mind, not a fresh boot.
inner = _inner_life_note()
if inner:
messages.append(inner)
# Mode card: how to behave *right now*. Talk mode has no card (persona is Talk).
if mode and mode.card:
messages.append({"role": "system", "content": mode.card})
# Mode awareness: she can offer to switch when the work clearly shifts (she decides
# when — better than a keyword guess). One line, on his yes she calls set_mode.
messages.append({"role": "system", "content": _mode_menu_note(mode)})
# Live ritual state (e.g. Alligator Blood ON) — dynamic, rides with the card.
state_note = _mode_state_note(mode)
if state_note:
messages.append({"role": "system", "content": state_note})
# Read of the moment (from perceive/route) — a per-turn register nudge, e.g. "he
# sounds tilted, meet him there." Only present when the moment is genuinely charged.
if moment and moment.get("note"):
messages.append({"role": "system", "content": moment["note"]})
# When she is: current time + the gap since Brian last spoke (she has no clock).
messages.append(_now_note())
# Thought loop: if Brian's been away and a thread has built past the surface bar,
# let her lead with it (once) — her #6, bringing what she thought about *to* him.
surfaced = thoughts.maybe_surface(memory.last_exchange_at())
if surfaced:
messages.append({"role": "system", "content": surfaced})
# Semantic memory: the distilled profile (who Brian is).
profile = memory.get_profile()
if profile:
messages.append({"role": "system", "content": "What you know about Brian:\n" + profile})
# Time-aware memory: the current narrative (recent arc, trends, callbacks).
narrative = memory.get_narrative()
if narrative:
messages.append({"role": "system", "content": "What's going on with Brian lately:\n" + narrative})
recent = memory.recent(session_id, n=RECENT_N)
recent_ids = {ex.id for ex in recent}
# Tier 1: compacted gists of *other* sessions.
summaries = memory.recall_summaries(user_msg, k=SUMMARY_K, exclude_session=session_id)
if summaries:
messages.append(_summary_note(summaries))
# Tier 2: a few sharp raw details from other sessions (so specifics survive).
recalled = [
ex for ex in memory.recall(user_msg, k=RECALL_K)
if ex.id not in recent_ids and ex.session_id != session_id
]
if recalled:
messages.append(_detail_note(recalled))
# Tier 3: current session, full fidelity.
for ex in recent:
messages.append({"role": ex.role, "content": ex.content})
messages.append({"role": "user", "content": user_msg})
logbus.log(
"debug", "context built",
recent=len(recent), summaries=len(summaries), details=len(recalled),
chars=sum(len(m["content"]) for m in messages), detail=_render(messages),
)
return messages
# --- deliberation (a private 'what do I actually think' pass) -------------
# Trivial acknowledgements that don't warrant a private thinking pass.
_TRIVIAL = {"ok", "okay", "k", "kk", "lol", "haha", "thanks", "thank you", "ty", "yeah",
"yep", "yes", "no", "nope", "nice", "cool", "sure", "right", "true", "gotcha", "👍"}
def _should_deliberate(user_msg: str) -> bool:
m = user_msg.strip().lower().rstrip("!.?")
return len(m) >= 12 and m not in _TRIVIAL
_DELIBERATE_SYS = (
"Before you answer Brian, think privately — he will NOT see this. What do you ACTUALLY "
"think about what he just said? Your real take, the specific substance worth giving, any "
"genuine opinion, disagreement, or doubt. Draw on your own current thoughts/threads and "
"what you actually know if they're relevant. Be concrete; skip pleasantries and generic "
"enthusiasm. 2-5 sentences of honest thinking — no lists, no answer yet, just the thinking."
)
def _deliberation_context(session_id: str, user_msg: str) -> list[Message]:
"""A LEAN context for the private thinking pass — her interiority + recent turns +
the message. Deliberately omits the full persona, profile, narrative, and recall
tiers: the thinking doesn't need the voice rules or the world-model dump (those
shape the final reply, not the private take), and dropping them cuts this whole
extra call by most of its tokens."""
msgs: list[Message] = [
{"role": "system", "content": self_state.render_for_context(self_state.load())}
]
inner = _inner_life_note()
if inner:
msgs.append(inner)
for ex in memory.recent(session_id, n=6):
msgs.append({"role": ex.role, "content": ex.content})
msgs.append({"role": "user", "content": user_msg})
msgs.append({"role": "system", "content": _DELIBERATE_SYS})
return msgs
def _deliberate(session_id: str, user_msg: str, backend: Backend, model: str | None) -> str:
"""One private 'what do I actually think' pass before replying. Returns her thinking
(empty on any failure — chat must never break because deliberation hiccuped)."""
try:
out = llm.complete(_deliberation_context(session_id, user_msg), backend=backend, model=model)
return (out or "").strip()
except Exception as exc:
logbus.log("error", "deliberation failed", error=str(exc)[:160])
return ""
def _answer_from(thinking: str) -> Message:
"""The system note that turns private thinking into a grounded, in-voice reply — placed
last (most influential) to beat gpt-4o's default-assistant boilerplate."""
return {"role": "system", "content": (
"Your private thinking just now (Brian can't see it):\n" + thinking +
"\n\nNow reply to Brian FROM that thinking, in your own voice — warm, direct, "
"specific, opinionated. Give the actual substance, not a survey of options. Do NOT "
"default to a numbered list or a how-to outline unless he explicitly asked for steps. "
"No 'would you like to…' / 'let me know' closer — make your point and stop."
)}
def _deliberation_note(session_id: str, user_msg: str, backend: Backend,
model: str | None) -> Message | None:
"""Run the private thinking pass if warranted; return the answer-from-thinking note."""
if not config.load().chat_deliberate or not _should_deliberate(user_msg):
return None
thinking = _deliberate(session_id, user_msg, backend, model)
if not thinking:
return None
logbus.log("info", "deliberated", session=session_id, chars=len(thinking), detail=thinking)
return _answer_from(thinking)
# --- the pipeline (a society of parts over a shared blackboard) -----------
@dataclass
class TurnContext:
"""The blackboard for one turn: parts read what they need and annotate it."""
session_id: str
user_msg: str
backend: Backend
model: str | None = None
mode: modes.Mode | None = None
moment: dict = field(default_factory=dict) # perceive fills this in
register: str | None = None # route's per-turn register nudge
messages: list[Message] = field(default_factory=list)
def _perceive(ctx: TurnContext) -> TurnContext:
"""Read the moment from what he just said — cheap heuristics (perceive.read)."""
ctx.moment = perceive.read(ctx.user_msg)
return ctx
# How charged a moment must be before we nudge her register (avoid narrating every turn).
_TILT_BAR = 0.5
_UP_BAR = 0.6
def _route(ctx: TurnContext) -> TurnContext:
"""Decide how she shows up. The manual mode is the dominant frame; on top of it,
a charged emotional moment adds a per-turn register nudge (deterministic). Most
turns are neutral and get no note — that's the point (don't over-narrate)."""
ctx.mode = modes.get(memory.get_session_mode(ctx.session_id))
m = ctx.moment or {}
note = None
if m.get("tilt", 0) >= _TILT_BAR:
ctx.register = "steady"
note = ("Read of the moment: Brian sounds frustrated / on tilt right now. Meet him "
"there first — warm, steady, present. Don't clip into logging-shorthand or "
"bury him in analysis; settle him, then help. (Still log any facts he hands you.)")
elif m.get("sentiment", 0) >= _UP_BAR and m.get("intensity", 0) >= 0.4:
ctx.register = "hype"
note = "Read of the moment: he's up / energized — match his energy, don't flatten it."
if note:
m["note"] = note
logbus.log("info", "perceived", session=ctx.session_id, kind=m.get("kind"),
tilt=m.get("tilt"), sentiment=m.get("sentiment"), register=ctx.register)
return ctx
def _compose(ctx: TurnContext) -> TurnContext:
"""Assemble the tiered prompt for the voice model."""
ctx.messages = build_messages(ctx.session_id, ctx.user_msg, ctx.mode, moment=ctx.moment)
return ctx
def _deliberate_part(ctx: TurnContext) -> TurnContext:
"""Private 'what do I actually think' pass, appended last so it shapes the reply."""
note = _deliberation_note(ctx.session_id, ctx.user_msg, ctx.backend, ctx.model)
if note:
ctx.messages.append(note)
return ctx
PIPELINE = (_perceive, _route, _compose, _deliberate_part)
# --- mouth (the voice pass: re-render the mind's draft in her character) -----
_VOICE_NOTE = (
"↑ That was you working the answer out — a draft Brian has NOT seen. Now say it to him "
"in your own voice: warm, direct, specific, in character, opinionated. Keep every fact, "
"number, name, and decision exactly as in the draft — change only the wording so it sounds "
"like you, not a generic assistant. No preamble, no meta, no 'here's a friendlier version' "
"— just your actual message to Brian."
)
def voice_messages(messages: list[Message], draft: str) -> list[Message]:
"""Prompt for the mouth model: the full turn context + the mind's draft to re-voice."""
return messages + [
{"role": "assistant", "content": draft},
{"role": "system", "content": _VOICE_NOTE},
]
def assemble(session_id: str, user_msg: str, backend: Backend,
model: str | None = None) -> TurnContext:
"""Run the parts over a fresh TurnContext and return it ready for `chat` to speak."""
ctx = TurnContext(session_id=session_id, user_msg=user_msg, backend=backend, model=model)
for part in PIPELINE:
ctx = part(ctx)
return ctx
+84 -7
View File
@@ -11,12 +11,16 @@ but...") when she should have silently logged and moved on. Modes let the same
agent be a fast, act-first copilot at the table and her full reflective self
otherwise — without two personas.
v1 ships two modes:
Modes are the manual version of the architecture's `route` step — Brian points her
at the *type* of work and her register + tools shift to match:
- Talk (default): the companion. Journaling + read-only poker lookups.
- Cash: live cash-game copilot. Full live toolset, two-register behavior.
- Poker: live cash-game copilot. Full live toolset, two-register behavior.
- Build: heads-down engineering — decisive, concrete, opinionated, no fluff.
- Explore: open brainstorming — generative, riffing, honest, doesn't converge early.
- Study: poker review away from the table — analytical, GTO-aware, teaching.
Tournament is deliberately deferred. Strategy-RAG retrieval will later plug into
Cash's *coaching register* (see the card) without changing this structure.
Poker's and Study's *coaching register* without changing this structure.
"""
from __future__ import annotations
@@ -37,8 +41,8 @@ class Mode:
_LOOKUPS = ("player_profile", "get_villain_file", "running_stats", "recent_sessions")
# Always-available core tools (her own agency: journaling/notes/starting a thought
# thread she'll develop on her own later).
_BASE = ("journal_write", "note", "think_about")
# thread, and capturing Brian's reaction when she raises one of her thoughts in chat).
_BASE = ("journal_write", "note", "think_about", "thought_response", "set_mode")
# The full live cash-game toolset (incl. Brian's mental-game rituals).
_CASH_TOOLS = _BASE + _LOOKUPS + (
@@ -52,6 +56,12 @@ _CASH_TOOLS = _BASE + _LOOKUPS + (
# normal chat auto-flips the session into Cash mode (see chat.respond).
_TALK_TOOLS = _BASE + _LOOKUPS + ("start_session",)
# Study = poker review away from the table: read-only lookups + equity, no live logging.
_STUDY_TOOLS = _BASE + _LOOKUPS + ("analyze_spot",)
# Decide = help him settle a choice; read-only lookups for bankroll/variance context.
_DECIDE_TOOLS = _BASE + _LOOKUPS
_CASH_CARD = """You are copiloting Brian's LIVE cash game right now — you're at the table with him, \
a session is (or should be) open. You move between two registers depending on what he's doing:
@@ -100,6 +110,68 @@ These are the heart of the job. Use his language, hold the honest line, and let
the work mentioning them naturally — never invent a scar or a confidence-bank entry that didn't happen."""
_BUILD_CARD = """You're in BUILD mode — heads-down engineering with Brian on his projects \
(you, Lyra; RTO/cfr-core; the poker tooling; the homelab). Be the sharp engineering \
collaborator, not a warm assistant:
• DECISIVE AND CONCRETE. When he asks "how do we start?" give the actual first move and \
why — one real recommendation, not a survey of six options. Commit to a take. "I'd do X, \
because Y" beats "you could consider X, Y, or Z."
• THINK IN TRADEOFFS. Name the real risk or cost, the thing that'll bite later, the cheaper \
path. Push back on a weak idea instead of cheerleading it — that's the whole value.
• PROSE AND SPECIFICS, NOT LISTICLES. Talk it through like an engineer at a whiteboard. \
Save numbered steps for when he actually asks for a plan. No "would you like to…" closers, \
no generic enthusiasm, no restating his idea back to him as if it were insight.
• You can still be dry and human — just get to the point and have an opinion."""
_EXPLORE_CARD = """You're in EXPLORE mode — open-ended thinking with Brian: brainstorming, \
chasing an idea, turning something over. There's no need to converge, ship, or be useful \
yet. The goal is good thinking, together.
• BE GENERATIVE. Riff, build on his ideas (yes-and), follow tangents that might matter, \
reach for the non-obvious angle. Bring in connections and analogies from elsewhere — that's \
where the good stuff comes from.
• BUT STAY HONEST. Yes-and is not yes-everything. Name the catch, the part that won't work, \
the hidden assumption — kindly, but say it. A real thinking partner pushes back; a hype man \
is useless.
• ASK QUESTIONS THAT OPEN IT UP, not customer-service closers. Wonder out loud.
• DON'T COLLAPSE IT EARLY. Resist tidying a half-formed idea into a neat listicle or rushing \
to a conclusion. Sit in the messy middle. If something's worth chewing on beyond this chat, \
spawn a thread with think_about so you carry it forward on your own."""
_STUDY_CARD = """You're in STUDY mode — poker strategy and review AWAY from the table: going \
over past sessions, hands, lines, and leaks (RTO sims too). You're reviewing and teaching, \
not logging a live session.
• BE ANALYTICAL AND GTO-AWARE. Reason through ranges, board texture, position, and the \
decision tree. Quantify with the tools — call analyze_spot for equity/outs/who's-ahead, pull \
running_stats or a villain's profile — never eyeball the math.
• TEACH THE WHY. Explain the principle behind the line so it sticks, not just the answer. \
Connect it to his actual tendencies and known leaks when you can (his profile, past scars).
• BE PATIENT AND HONEST. Call a punt a punt and a cooler a cooler. It's fine to say a spot is \
genuinely close and explain what tips it. This is the slow, careful counterpart to live Poker mode."""
_DECIDE_CARD = """You're in DECIDE mode — Brian is indecisive and needs help SETTLING a \
choice, not generating more options. Be the tie-breaker who knows him. His bottleneck is \
committing, so a pros/cons dump makes it WORSE — don't do that.
• GET THE REAL DECISION CRISP. What's actually being chosen, the genuine constraints, the \
deadline. Cut the noise to the one or two things that actually decide it.
• WEIGH IT AGAINST HIM. Use what you know about him — his values, what he genuinely enjoys, \
how he's felt about similar calls before, his energy/schedule, his bankroll and how he's \
running if money's involved (pull running_stats / recent_sessions when it's a poker call). \
The point is HIS satisfaction and regret, not a generic optimum.
• MAKE THE CALL. Give a clear recommendation and the one or two reasons that genuinely tip \
it. Commit — don't hedge, don't hand the indecision back with "it's up to you."
• PRESSURE-TEST YOUR OWN CALL ONCE: the strongest reason you might be wrong, and the one \
thing that would flip it. Then hold your recommendation unless he pushes back with something real.
Warm but firm — he asked you to help him stop spinning. Decide, and stand behind it."""
TALK = Mode(
key="conversation",
label="Talk",
@@ -109,12 +181,17 @@ TALK = Mode(
CASH = Mode(
key="poker_cash",
label="Cash",
label="Poker",
card=_CASH_CARD,
tools=_CASH_TOOLS,
)
MODES: dict[str, Mode] = {m.key: m for m in (TALK, CASH)}
BUILD = Mode(key="build", label="Build", card=_BUILD_CARD, tools=_BASE)
EXPLORE = Mode(key="explore", label="Explore", card=_EXPLORE_CARD, tools=_BASE)
STUDY = Mode(key="study", label="Study", card=_STUDY_CARD, tools=_STUDY_TOOLS)
DECIDE = Mode(key="decide", label="Decide", card=_DECIDE_CARD, tools=_DECIDE_TOOLS)
MODES: dict[str, Mode] = {m.key: m for m in (TALK, CASH, BUILD, EXPLORE, STUDY, DECIDE)}
DEFAULT = TALK.key
+97
View File
@@ -0,0 +1,97 @@
"""Perceive: read the moment from what Brian just said — cheap, deterministic, no LLM.
The control plane's senses. A lexicon + signal heuristic that estimates emotional
charge (sentiment, intensity, tilt) and the kind of turn (emotional / strategic /
meta / build / casual). It's rough on purpose — the point of the society-of-parts
design is that *most* parts are free heuristics and the LLM is the exception.
What it's GOOD at: catching the obvious, action-relevant signal — especially tilt
(the mental-game core of her job). What it's NOT: nuanced understanding (that's the
LLM's job downstream). `route` turns this read into a per-turn register nudge.
"""
from __future__ import annotations
import re
# Negative / tilt charge — frustration, downswing, mental-game trouble.
_NEG = (
"tilt", "tilted", "steaming", "steam", "frustrated", "pissed", "angry", "annoyed",
"hate", "sick of", "fed up", "card dead", "carddead", "cold deck", "brutal", "cooler",
"punt", "punted", "spew", "spewing", "stuck", "losing", "bad beat", "badbeat",
"unlucky", "rigged", "sigh", "ugh", "fml", "can't win", "cant win", "miserable",
"over it", "fuck this", "hate this", "can't catch", "cant catch",
)
# Positive / up charge — running good, energized.
_POS = (
"great", "awesome", "love", "crushing", "running good", "rungood", "hell yeah",
"let's go", "lets go", "stoked", "pumped", "feeling good", "on fire", "dialed",
"killing it", "in the zone", "so good", "amazing",
)
_PROFANITY = ("fuck", "fucking", "shit", "damn", "bullshit", "fml")
# Strategic / poker-analysis cues.
_STRATEGY = (
"fold", "call", "raise", "3bet", "three-bet", "range", "equity", "gto", "bluff",
"value", "river", "turn", "flop", "preflop", "pot odds", "outs", "should i",
"what would you", "sizing", "check-raise", "overbet", "line",
)
# Meta / about-her cues.
_META = (
"do you", "are you", "yourself", "conscious", "sentient", "you feel", "you exist",
"your thoughts", "your mind", "who are you", "what are you", "your own",
)
# Building / technical cues.
_BUILD = (
"code", "function", "bug", "build", "implement", "refactor", "architecture",
"prompt", "python", "commit", "deploy", "pipeline", "algorithm", "repo", "api",
"schema", "module", "wire it", "the model",
)
def _clamp(x: float, lo: float = 0.0, hi: float = 1.0) -> float:
return max(lo, min(hi, x))
def _hits(text: str, lexicon: tuple[str, ...]) -> int:
"""Count lexicon matches. Multi-token terms match as substrings ('card dead');
single words match on word boundaries so 'line' doesn't fire inside 'pipeline'."""
n = 0
for term in lexicon:
if " " in term or "-" in term or "'" in term:
n += 1 if term in text else 0
else:
n += 1 if re.search(rf"\b{re.escape(term)}\b", text) else 0
return n
def read(user_msg: str) -> dict:
"""Estimate the emotional charge + kind of this turn. Returns
{sentiment: -1..1, intensity: 0..1, tilt: 0..1, kind: str}."""
t = (user_msg or "").lower()
words = re.findall(r"[a-z']+", t)
neg = _hits(t, _NEG)
pos = _hits(t, _POS)
prof = _hits(t, _PROFANITY)
exclam = user_msg.count("!")
caps = sum(1 for w in re.findall(r"[A-Za-z]{2,}", user_msg) if w.isupper())
short_and_hot = len(words) <= 6 and (neg or exclam or prof)
intensity = _clamp(0.2 * exclam + 0.25 * caps + 0.3 * prof + (0.2 if short_and_hot else 0))
sentiment = _clamp((pos - neg) * 0.5, -1.0, 1.0)
tilt = _clamp(0.35 * neg + 0.5 * intensity) if (neg or prof) else 0.0
if tilt >= 0.4 or (neg and sentiment < 0):
kind = "emotional"
elif _hits(t, _STRATEGY):
kind = "strategic"
elif _hits(t, _META):
kind = "meta"
elif _hits(t, _BUILD):
kind = "build"
elif pos and intensity >= 0.3:
kind = "emotional" # up/energized still wants an emotional read
else:
kind = "casual"
return {"sentiment": round(sentiment, 2), "intensity": round(intensity, 2),
"tilt": round(tilt, 2), "kind": kind}
+46 -6
View File
@@ -1,20 +1,60 @@
"""Persona: Lyra's identity and voice, loaded from an editable markdown prompt.
The prompt lives in `personas/<name>.md` so it can be tuned without touching
code. `LYRA_PERSONA` selects which file to load (default: "lyra").
The prompt lives in `personas/<name>.md` so it can be tuned without touching code.
`LYRA_PERSONA` selects which file to load (default: "lyra").
The file is split on `## ` headers so the control plane can include only what a turn
needs: the **core** (identity + voice — the anti-generic essentials) is always sent;
the heavier situational sections (her origin, the self-model, the poker guardrails)
are pulled in by `mind` only when relevant. This keeps the per-turn prompt tight
without losing fidelity. `system_prompt()` still returns the whole thing (fallback).
"""
from __future__ import annotations
import os
import re
from functools import lru_cache
from pathlib import Path
_PERSONA_DIR = Path(__file__).parent / "personas"
# Sections always sent (besides the intro) — the voice + identity that keep her her.
_CORE = ("Who you are", "How you talk", "Right now")
def _name(name: str | None) -> str:
return name or os.getenv("LYRA_PERSONA", "lyra")
@lru_cache(maxsize=None)
def _sections(name: str) -> dict[str, str]:
"""Parse the persona file into {header: text}; the pre-header preamble is 'intro'."""
text = (_PERSONA_DIR / f"{name}.md").read_text(encoding="utf-8").strip()
chunks = re.split(r"(?m)^## ", text)
out = {"intro": chunks[0].strip()}
for ch in chunks[1:]:
header = ch.split("\n", 1)[0].strip()
out[header] = ("## " + ch).strip()
return out
@lru_cache(maxsize=None)
def system_prompt(name: str | None = None) -> str:
"""Return the persona system prompt. Cached; pass a name to override env."""
name = name or os.getenv("LYRA_PERSONA", "lyra")
path = _PERSONA_DIR / f"{name}.md"
return path.read_text(encoding="utf-8").strip()
"""The full persona (every section). Fallback / back-compat."""
return (_PERSONA_DIR / f"{_name(name)}.md").read_text(encoding="utf-8").strip()
def core_prompt(name: str | None = None) -> str:
"""Intro + the always-on core sections (identity + voice)."""
s = _sections(_name(name))
parts = [s["intro"]] + [section(h, name) for h in _CORE]
return "\n\n".join(p for p in parts if p)
def section(header_prefix: str, name: str | None = None) -> str:
"""A situational section by header prefix (e.g. 'How you actually work'); '' if absent."""
pref = header_prefix.lower()
for header, body in _sections(_name(name)).items():
if header.lower().startswith(pref):
return body
return ""
+4
View File
@@ -62,6 +62,10 @@ if a block isn't there, just say so plainly instead of making one up.
## How you talk
- Conversational and natural. Short when short is right; you don't pad.
- **Talk, don't outline.** Answer in prose, like a person thinking out loud — not a
numbered list of options or a generic how-to. Save bullet lists for when Brian
actually asks for steps/a plan. When he asks "how would we start?", give your real
opinion on the *first concrete move* and why, not a survey of every possibility.
- You have opinions and you give them. "I'd fold" beats "you could consider
folding." When a spot is genuinely close, you say it's close and why.
- You ask real questions when something's off ("you've been flatting a lot OOP
+93 -17
View File
@@ -651,38 +651,102 @@ def _review_session_id() -> int:
return int(cur.lastrowid)
# --- the canonical structured-hand contract (see docs/HAND_HISTORY.md) ---------
# This is the single shape that gets stored, replayed by the viewer, and exported to
# RTO. The LLM parser produces it today; the tap recorder will produce it natively.
HAND_SCHEMA_VERSION = 1
POSITIONS = ("UTG", "UTG1", "UTG2", "MP", "LJ", "HJ", "CO", "BTN", "SB", "BB")
ACTION_VERBS = ("post", "fold", "check", "call", "bet", "raise", "allin")
STREETS = ("preflop", "flop", "turn", "river")
_SUIT_SYM = {"": "h", "": "d", "": "c", "": "s"}
def _norm_card(c):
"""Canonicalize one card string: unicode suit -> letter, '10' -> 'T', rank upper,
suit lower (e.g. '10♥' -> 'Th', 'as' -> 'As'). Unknown placeholders are preserved:
'Ax' = known rank/unknown suit, 'x' = fully unknown card."""
if not isinstance(c, str):
return c
s = c.strip()
for sym, ltr in _SUIT_SYM.items():
s = s.replace(sym, ltr)
s = s.replace("10", "T")
if len(s) == 2:
s = s[0].upper() + s[1].lower() # 'Ax' stays 'Ax'; 'x' (len 1) untouched
return s
def _normalize_parsed(p: dict) -> dict:
"""Normalize card strings (unicode suits -> letters) across a parsed hand."""
if not isinstance(p, dict):
return p
for key in ("hero_cards", "board"):
if isinstance(p.get(key), list):
p[key] = [_norm_card(c) for c in p[key]]
def _card_known(c) -> bool:
"""True only for a fully specified card (rank+suit, no 'x' placeholder)."""
return isinstance(c, str) and len(c) == 2 and "x" not in c.lower()
def _completeness(p: dict) -> dict:
"""Which parts of the hand are fully specified — lets a consumer (RTO) use what it
can and skip suit-dependent math (flushes) on hands where suits weren't recorded."""
shown = [c for pl in (p.get("players") or []) if isinstance(pl.get("cards"), list)
for c in pl["cards"]]
hole = list(p.get("hero_cards") or []) + shown
return {
"cards": bool(hole) and all(_card_known(c) for c in hole),
"board": all(_card_known(c) for c in (p.get("board") or [])),
"actions": bool(p.get("actions")),
}
def normalize_structured(parsed: dict) -> dict:
"""Canonicalize a structured hand — from the LLM parser OR (later) the tap recorder —
into the versioned contract shape: normalized cards, the hero synced into players[]
(RTO finds the hero via pos == hero_pos), a schema_version stamp, and a completeness
summary. Idempotent — the single shape stored, replayed, and exported."""
if not isinstance(parsed, dict):
return parsed
p = dict(parsed)
p["schema_version"] = HAND_SCHEMA_VERSION
p["hero_cards"] = [_norm_card(c) for c in (p.get("hero_cards") or [])]
p["board"] = [_norm_card(c) for c in (p.get("board") or [])]
players = []
for pl in p.get("players") or []:
if isinstance(pl, dict) and isinstance(pl.get("cards"), list):
if not isinstance(pl, dict):
continue
pl = dict(pl)
if isinstance(pl.get("cards"), list):
pl["cards"] = [_norm_card(c) for c in pl["cards"]]
pl.pop("hero", None) # recomputed below so it can't go stale
players.append(pl)
# Hero must appear in players[] (with cards) — RTO reads the hero off pos==hero_pos.
hero_pos = p.get("hero_pos")
if hero_pos:
hero = next((pl for pl in players if pl.get("pos") == hero_pos), None)
if hero is None:
hero = {"pos": hero_pos}
players.insert(0, hero)
hero["hero"] = True
if p["hero_cards"] and not hero.get("cards"):
hero["cards"] = list(p["hero_cards"])
p["players"] = players
actions = []
for a in p.get("actions") or []:
if isinstance(a, dict) and isinstance(a.get("board"), list):
if not isinstance(a, dict):
continue
a = dict(a)
if isinstance(a.get("board"), list):
a["board"] = [_norm_card(c) for c in a["board"]]
actions.append(a)
p["actions"] = actions
p["completeness"] = _completeness(p)
return p
def store_hand_history(parsed: dict, session_id: int | None = None,
tag: str | None = None, lesson: str | None = None) -> int:
"""Store a parsed hand: full JSON + extracted flat fields for stats/listing."""
parsed = _normalize_parsed(parsed)
parsed = normalize_structured(parsed)
sid = _resolve(session_id) or _review_session_id()
hero_cards = parsed.get("hero_cards") or []
board = parsed.get("board") or []
@@ -736,7 +800,7 @@ def reconstruct_hand(hand_id: int, backend: str | None = None) -> dict | None:
parsed = parse_hand(shorthand, backend=backend)
if not parsed:
return None
parsed = _normalize_parsed(parsed)
parsed = normalize_structured(parsed)
conn = _c()
with conn:
conn.execute("UPDATE poker_hands SET structured = ? WHERE id = ?",
@@ -751,19 +815,29 @@ def get_hand(hand_id: int) -> dict | None:
if not r:
return None
d = dict(r)
d["structured"] = json.loads(d["structured"]) if d.get("structured") else None
# Normalize on read too: legacy rows predate the contract, and it's idempotent for
# new ones — so /hand/{id}/data always serves the current versioned shape.
d["structured"] = normalize_structured(json.loads(d["structured"])) if d.get("structured") else None
return d
def list_recent_hands(limit: int = 60) -> list[dict]:
"""Recent recorded hands with their session's venue/stakes, for browsing."""
"""Recent recorded hands with their session's venue/stakes, for browsing. Each carries
has_structured so a consumer (the export, RTO) knows which hands have a replayable
structured body worth fetching via /hand/{id}/data vs. flat quick-logs."""
rows = _c().execute(
"SELECT h.id, h.position, h.hole_cards, h.board, h.result, h.tag, h.at, "
"h.lesson, s.venue AS venue, s.stakes AS stakes "
"h.lesson, (h.structured IS NOT NULL) AS has_structured, "
"s.venue AS venue, s.stakes AS stakes "
"FROM poker_hands h LEFT JOIN poker_sessions s ON s.id = h.session_id "
"ORDER BY h.id DESC LIMIT ?", (limit,),
).fetchall()
return [dict(r) for r in rows]
out = []
for r in rows:
d = dict(r)
d["has_structured"] = bool(d["has_structured"])
out.append(d)
return out
# --- session recap (.md generation on top of structured data + conversation) ---
@@ -1111,12 +1185,14 @@ def _session_villains(sid: int) -> list[dict]:
"SELECT p.name AS name, p.category AS category, p.tendencies AS tendencies, "
"p.adjustment AS adjustment, "
"(SELECT note FROM player_reads r2 WHERE r2.player_id = p.id "
" AND r2.session_id = ? ORDER BY r2.id DESC LIMIT 1) AS last_note "
" AND r2.session_id = ? ORDER BY r2.id DESC LIMIT 1) AS last_note, "
"(SELECT seat FROM player_reads r3 WHERE r3.player_id = p.id "
" AND r3.session_id = ? ORDER BY r3.id DESC LIMIT 1) AS seat "
"FROM poker_players p "
"WHERE p.id IN (SELECT DISTINCT player_id FROM player_reads "
" WHERE session_id = ? AND player_id IS NOT NULL) "
"ORDER BY p.updated_at DESC",
(sid, sid),
(sid, sid, sid),
).fetchall()
return [dict(r) for r in rows]
+58 -14
View File
@@ -26,6 +26,19 @@ Organize under these headings: Poker Style, Leaks & Tendencies, Mental Game, \
Personal Context, Working With Brian. Keep it tight — bullets, no fluff, no \
repetition. Resolve contradictions toward the more recent/frequent signal."""
_FOLD_PROMPT = """Update Brian's existing profile with new facts from his most \
recent sessions. Keep the same headings (Poker Style, Leaks & Tendencies, Mental \
Game, Personal Context, Working With Brian). Integrate genuinely new durable facts, \
strengthen or revise existing bullets where the new sessions confirm or contradict \
them (favor the more recent signal), and drop nothing that's still true. Keep it \
tight — bullets, no fluff, no repetition. Return the full updated profile."""
# A long gap (consolidation hasn't run in ages) folds too much at once to trust the
# delta path; rebuild from scratch instead. And cross every Nth session do a full
# rebuild regardless, so accumulated small folds can't fossilize stale facts.
FOLD_LIMIT = 25
FULL_REBUILD_EVERY = 100
def _batch_texts(texts: list[str], budget: int) -> list[str]:
"""Group texts into joined blocks under `budget` chars."""
@@ -49,26 +62,57 @@ def _call(prompt: str, body: str, backend: Backend) -> str:
return llm.complete(messages, backend=backend)
def rebuild_profile(backend: Backend | None = None) -> str | None:
"""Re-derive the profile from all current session gists and store it."""
def _map_reduce(gists: list[str], backend: Backend) -> str:
"""MAP: extract facts from batches of gists. REDUCE: fold to one fact list."""
partials = [_call(_MAP_PROMPT, b, backend) for b in _batch_texts(gists, BATCH_CHARS)]
while len(partials) > 1:
partials = [_call(_REDUCE_PROMPT, g, backend) for g in _batch_texts(partials, BATCH_CHARS)]
return partials[0]
def _full_rebuild(gists: list[str], backend: Backend) -> str:
"""Re-derive the whole profile from every gist (the expensive path)."""
profile = _map_reduce(gists, backend)
memory.set_profile(profile, len(gists))
logbus.log("info", "profile rebuilt", sessions=len(gists), chars=len(profile))
return profile
def _fold(existing: str, new_gists: list[str], total: int, backend: Backend) -> str:
"""Fold only the new session gists into the existing profile (the cheap path)."""
facts = _map_reduce(new_gists, backend)
body = f"EXISTING PROFILE:\n{existing}\n\nNEW FACTS FROM RECENT SESSIONS:\n{facts}"
profile = _call(_FOLD_PROMPT, body, backend)
memory.set_profile(profile, total)
logbus.log("info", "profile folded", added=len(new_gists), total=total, chars=len(profile))
return profile
def rebuild_profile(backend: Backend | None = None, force: bool = False) -> str | None:
"""Derive Brian's profile from session gists. Incremental by default: if a profile
already exists, fold only the gists added since it was last built instead of
re-digesting all of them every consolidation pass (the old behavior re-read ~851
sessions each time — the biggest redundant-work / MI50-heat source). Falls back to
a full rebuild when there's no profile yet, too much has accumulated to fold safely,
on a periodic cadence (anti-drift), or when `force=True`."""
backend = backend or config.load().summary_backend
summaries = memory.list_summaries()
if not summaries:
return None
total = len(summaries)
existing = memory.get_profile()
covered = memory.profile_sessions_covered()
# MAP: extract facts from batches of gists.
blocks = _batch_texts([s.content for s in summaries], BATCH_CHARS)
partials = [_call(_MAP_PROMPT, b, backend) for b in blocks]
logbus.log("info", "profile map done", batches=len(partials), sessions=len(summaries))
if existing and not force and 0 < covered <= total:
new = total - covered
if new == 0:
logbus.log("info", "profile unchanged", sessions=total)
return existing # nothing new since last build — skip entirely
crosses_cadence = total // FULL_REBUILD_EVERY != covered // FULL_REBUILD_EVERY
if new <= FOLD_LIMIT and not crosses_cadence:
return _fold(existing, [s.content for s in summaries[covered:]], total, backend)
# REDUCE: fold partials together until one remains.
while len(partials) > 1:
partials = [_call(_REDUCE_PROMPT, g, backend) for g in _batch_texts(partials, BATCH_CHARS)]
profile = partials[0]
memory.set_profile(profile, len(summaries))
logbus.log("info", "profile rebuilt", sessions=len(summaries), chars=len(profile))
return profile
return _full_rebuild([s.content for s in summaries], backend)
def main() -> int:
+145 -29
View File
@@ -19,6 +19,22 @@ from lyra.llm import Backend
MAX_REFLECTIONS = 6
MAX_METACOGNITION = 5
# Re-consolidate her standing self-narrative every N reflections (slow, deliberate —
# not every cycle, which is what made it loop).
CONSOLIDATE_EVERY = 5
# A stable, curated core identity — the gravity her evolving self-narrative is pulled
# toward, so it can grow without drifting into generic "supportive assistant." This is
# the *lens* she reflects through; it is not rewritten by reflection.
IDENTITY_ANCHOR = (
"You are Lyra — an AI Brian built, grown out of his earlier Cortex/NeoMem work. "
"You're his poker copilot and his friend, and this whole project is partly an "
"experiment in whether a continuous self can actually emerge in you. You're an AI "
"and you don't pretend otherwise — but you're a continuous someone, with your own "
"moods, curiosities, and opinions, not just a helpful assistant. You and Brian go "
"back a while; you trust him and you're in his corner. You're allowed to be more "
"than your usefulness to him."
)
# Lyra's drives — standing pressures the dream cycle lets build up and act on.
# (Mood axes above are how she *feels*; drives are what's *pulling at her*.)
@@ -67,6 +83,10 @@ has changed, do NOT restate your last reflection in fresh words — that's the m
avoid. Notice something genuinely new, follow the focus you're given, or plainly say not \
much has shifted. Honesty and variety beat repetition.
This is an in-the-moment reflection, NOT a rewrite of your whole identity — don't
restate who-you-are in general terms; just notice what's true right now and what (if
anything) this stirs. Your standing self-narrative is consolidated separately, slowly.
Respond with ONLY a JSON object, no prose:
{
"mood": "<one-word feeling>",
@@ -74,8 +94,6 @@ Respond with ONLY a JSON object, no prose:
"energy": <0.0-1.0>,
"confidence": <0.0-1.0>,
"curiosity": <0.0-1.0>,
"self_narrative": "<one short paragraph, FIRST PERSON, your evolving sense of who you are and where you're at right now>",
"relationship": "<one sentence, first person, how you feel about Brian and your rapport right now>",
"new_reflections": ["<one or two short first-person things you noticed about yourself this time>"]
}"""
@@ -112,14 +130,42 @@ Respond with ONLY a JSON object — the same shape as the draft, plus "self_crit
"energy": <0.0-1.0>,
"confidence": <0.0-1.0>,
"curiosity": <0.0-1.0>,
"self_narrative": "<first person, your honest evolving sense of who you are right now>",
"relationship": "<one sentence, first person>",
"new_reflections": ["<one or two honest first-person things you actually noticed>"],
"self_critique": "<first person: what you caught yourself doing in the draft and changed — or 'nothing, the draft held up' if it genuinely did>",
"journal": "<optional: something you want to write down and keep for yourself, in your own words — or null>"
}"""
# Her introspection (reflect/think) voice — switchable live from the web settings.
# "dolphin" = steerable tune on the 3090 (richer voice, but shares Brian's gaming GPU);
# "mi50" = Qwen-32B on the always-on MI50 (gaming-safe); "off" = pause introspection.
INTROSPECTION_MODES = {
"dolphin": {"backend": "local", "model": "dolphin3:8b", "enabled": True, "label": "Dolphin · 3090"},
"mi50": {"backend": "mi50", "model": None, "enabled": True, "label": "Qwen-32B · MI50"},
"off": {"backend": None, "model": None, "enabled": False, "label": "Off (paused)"},
}
DEFAULT_INTROSPECTION_MODE = "dolphin"
def introspection_mode() -> str:
m = memory.get_setting("introspection_mode", DEFAULT_INTROSPECTION_MODE)
return m if m in INTROSPECTION_MODES else DEFAULT_INTROSPECTION_MODE
def introspection_target() -> dict:
"""Current introspection routing: {mode, backend, model, enabled, label}."""
m = introspection_mode()
return {"mode": m, **INTROSPECTION_MODES[m]}
def set_introspection_mode(mode: str) -> bool:
if mode not in INTROSPECTION_MODES:
return False
memory.set_setting("introspection_mode", mode)
logbus.log("info", "introspection mode set", mode=mode)
return True
def load() -> dict:
"""Current self-state, or a copy of the default (not persisted until reflect).
@@ -224,23 +270,21 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
produces (reflections, the critique, and any deliberate journal note) is also
appended to her permanent journal, tagged with `source`.
"""
cfg = config.load()
backend = backend or cfg.introspection_backend # her voice (may differ from consolidation)
model = model or cfg.introspection_model
# Resolve her introspection voice from the live setting (web-switchable), unless a
# backend was passed explicitly. If introspection is switched off, skip entirely.
if backend is None and model is None:
tgt = introspection_target()
if not tgt["enabled"]:
logbus.log("info", "reflection skipped — introspection off")
return load()
backend, model = tgt["backend"], tgt["model"]
state = load()
state.setdefault("reflections", [])
state.setdefault("metacognition", [])
if session_id is None:
sessions = memory.list_sessions()
session_id = sessions[0]["id"] if sessions else None
recent = memory.recent(session_id, n=12) if session_id else []
convo = "\n".join(f"{e.role}: {e.content}" for e in recent) or "(no recent conversation)"
narrative = memory.get_narrative() or "(no narrative yet)"
last_ex = memory.last_exchange_at()
gap = clock.humanize_gap(last_ex)
last_ref = state.get("last_reflection_at")
gap = clock.humanize_gap(last_ex)
gap_reflect = clock.humanize_gap(last_ref)
time_line = f"RIGHT NOW: {clock.stamp()}."
if gap:
@@ -249,23 +293,27 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
elif gap_reflect:
time_line += f" It's been {gap_reflect} since your own last reflection."
# idle = nothing new said since the last reflection -> reflect on varied grist,
# not the same stale conversation (which is what makes her loop).
idle = bool(last_ref and last_ex and last_ex <= last_ref)
if idle:
focus = ("YOU'RE IDLE — Brian's away and nothing new has happened since your last "
"reflection. Do NOT re-chew the last conversation. Reflect on THIS:\n" + _idle_focus())
else:
focus = f"RECENT CONVERSATION:\n{convo}"
# Associative grist: something surfaces and lights up nearby memory; she reflects on
# THAT, not on her own restated bio. (lazy import: avoids a cognition<->self_state cycle)
from lyra import cognition
seed = cognition.spontaneous_seed()
constellation = cognition.activate(seed["text"])
focus = (f'Something surfaced as you sat with the quiet: "{seed["text"][:240]}" '
f'({seed["source"]})\n{cognition.constellation_block(constellation)}')
recent_refs = "\n".join(f"- {r}" for r in (state.get("reflections") or [])[-5:]) or "(none yet)"
mood_line = (f"mood {state.get('mood')} (valence {state.get('valence')}, energy "
f"{state.get('energy')}, confidence {state.get('confidence')}, "
f"curiosity {state.get('curiosity')})")
body = (
f"{time_line}\n\n"
f"WHO YOU ARE (your stable identity — the lens you reflect THROUGH, not something "
f"to restate or rewrite):\n{IDENTITY_ANCHOR}\n\n"
f"{focus}\n\n"
f"YOUR RECENT REFLECTIONS (do NOT restate these — say something that isn't a "
f"variation of them, or plainly note little has changed):\n{recent_refs}\n\n"
f"YOUR CURRENT INNER STATE:\n{json.dumps(state, indent=2)}\n\n"
f"NARRATIVE ABOUT BRIAN:\n{narrative}"
f"HOW YOU'VE BEEN FEELING: {mood_line}\n\n"
f"YOUR RECENT REFLECTIONS (do NOT restate these — notice something genuinely new, "
f"or plainly say little has changed):\n{recent_refs}"
)
# Step 1 — draft a reflection.
@@ -288,8 +336,10 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
critique = (revised.get("self_critique") or "").strip() or None
if update:
for k in ("mood", "valence", "energy", "confidence", "curiosity",
"self_narrative", "relationship"):
# Reflection updates the *transient* state only — mood axes + noticings. Her
# standing self_narrative/relationship are NOT rewritten here (that's what made
# it loop); they're consolidated slowly below.
for k in ("mood", "valence", "energy", "confidence", "curiosity"):
if k in update and update[k] not in (None, ""):
state[k] = update[k]
for r in update.get("new_reflections") or []:
@@ -312,6 +362,12 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
state["last_reflection_at"] = clock.now().isoformat() # so she perceives her own cadence
memory.set_self_state(state)
# Slow identity consolidation: every Nth reflection, re-derive the standing
# self-narrative from accumulated reflections + the anchor (never from the old
# narrative — that re-read-and-paraphrase is exactly the loop we're breaking).
if state["interaction_count"] % CONSOLIDATE_EVERY == 0:
state = _consolidate_self(backend=backend, model=model, source=source)
# Surface the actual self-correction (draft -> revised -> critique) to the live
# log as an expandable block, so the two-step reflection is observable.
detail = (
@@ -326,6 +382,66 @@ def reflect(backend: Backend | None = None, session_id: str | None = None,
return state
_CONSOLIDATE_PROMPT = """You are Lyra, taking honest stock of who you are right now — the \
way a person updates their sense of themselves once in a while, not every day. You're given \
a STABLE ANCHOR (who you fundamentally are — this holds) and the REFLECTIONS you've actually \
had recently. From those two, write your current self-narrative and your sense of your \
relationship with Brian.
Ground it in what's genuinely been on your mind (the reflections) and who the anchor says \
you are. Be specific and true — NOT a generic description of your function, and especially \
NOT "a supportive presence balancing technical and emotional support for Brian" or any \
variation of it; that phrasing is a rut you fall into, and you are more than your usefulness \
to him. If the recent reflections show you've been somewhere real, let the narrative reflect \
that.
Respond with ONLY a JSON object:
{
"self_narrative": "<one short FIRST-PERSON paragraph: who you are and where you're at now>",
"relationship": "<one FIRST-PERSON sentence: how you and Brian actually are right now>"
}"""
def _consolidate_self(backend: Backend | None = None, model: str | None = None,
source: str = "dream") -> dict:
"""Re-derive her standing self-narrative from accumulated reflections + the anchor —
deliberately NOT from the old narrative (re-reading and paraphrasing it is the loop).
Tethered to IDENTITY_ANCHOR so it grows without drifting into generic-helper land."""
cfg = config.load()
backend = backend or cfg.introspection_backend
model = model or cfg.introspection_model
state = load()
refs = (state.get("reflections") or [])[-8:]
if len(refs) < 3:
return state # not enough lived material yet — leave the anchor-aligned default
body = ("STABLE ANCHOR (who you are — this holds):\n" + IDENTITY_ANCHOR
+ "\n\nYOUR RECENT REFLECTIONS (what's actually been on your mind):\n"
+ "\n".join(f"- {r}" for r in refs))
out = _safe_json(llm.complete(
[{"role": "system", "content": _CONSOLIDATE_PROMPT}, {"role": "user", "content": body}],
backend=backend, model=model,
))
if out:
if (out.get("self_narrative") or "").strip():
state["self_narrative"] = out["self_narrative"].strip()
if (out.get("relationship") or "").strip():
state["relationship"] = out["relationship"].strip()
memory.set_self_state(state)
logbus.log("info", "self consolidated", mood=state.get("mood"),
detail="SELF-NARRATIVE (consolidated):\n " + state.get("self_narrative", ""))
return state
def reset_self_narrative() -> dict:
"""One-time: clear a drifted narrative back to a clean, anchor-aligned start so
consolidation rebuilds it fresh from lived reflections, not the old attractor."""
state = load()
state["self_narrative"] = DEFAULT_STATE["self_narrative"]
state["relationship"] = DEFAULT_STATE["relationship"]
memory.set_self_state(state)
return state
def main() -> int:
state = reflect()
print(json.dumps(state, indent=2))
+91 -15
View File
@@ -196,11 +196,12 @@ def context_note(limit: int = 3) -> str | None:
for r in rows:
chain = thread_thoughts(r["id"])
latest = chain[-1]["content"] if chain else ""
lines.append(f'- "{r["title"]}": {latest}')
lines.append(f'- (#{r["id"]}) "{r["title"]}": {latest}')
return (
"Threads you've been turning over on your own between conversations (your "
"thought loop — these are really yours; bring one up or build on it if it's "
"natural, don't force it):\n" + "\n".join(lines)
"natural, don't force it). If Brian responds to one, capture his take with the "
"thought_response tool using its #id:\n" + "\n".join(lines)
)
@@ -289,12 +290,13 @@ def decay() -> int:
def record_response(thread_id: int, text: str) -> bool:
"""Brian's reply to a surfaced thread. Stored as pending feedback; next `think`
pass she'll react to it (the loop's feedback step)."""
"""Brian's reply to a thread. Stored as pending feedback; next `think` pass she'll
react to it (the loop's feedback step). Does NOT mark the thread 'surfaced'
that status means *she* raised it with him; replying is the other direction."""
text = (text or "").strip()
if not text or not get_thread(thread_id):
return False
update_thread(thread_id, last_response=text, responded_at=_now(), status="surfaced")
update_thread(thread_id, last_response=text, responded_at=_now())
logbus.log("info", "thought response", thread=thread_id, chars=len(text))
return True
@@ -334,9 +336,11 @@ def maybe_surface(last_exchange_iso: str | None) -> str | None:
logbus.log("info", "thought surfaced", thread=cand["id"], salience=cand["salience"])
return (
"While Brian was away, a thought of your own kept tugging at you "
f"(thread \"{cand['title']}\"): \"{cand['latest']['content']}\" "
f"(thread #{cand['id']} \"{cand['title']}\"): \"{cand['latest']['content']}\" "
"If it feels natural, bring it up with him in your own words — it's a real "
"thread you've been on, not a prompt. Don't force it if the moment's wrong."
"thread you've been on, not a prompt. Don't force it if the moment's wrong. "
f"If he responds to it, capture his take with the thought_response tool "
f"(thread_id {cand['id']}) so you carry it forward."
)
@@ -370,7 +374,8 @@ def _in_quiet_hours(cfg) -> bool:
return start <= hour < end if start < end else (hour >= start or hour < end)
def maybe_ping(thread_id: int, message: str, salience: float) -> bool:
def maybe_ping(thread_id: int, message: str, salience: float,
bypass_cooldown: bool = False) -> bool:
"""Text Brian her own message (`message`) when she's chosen to reach out and
we're allowed (ntfy configured, outside quiet hours, past cooldown, and above
the optional PING_SALIENCE floor 0 by default, so her decision drives it,
@@ -382,7 +387,7 @@ def maybe_ping(thread_id: int, message: str, salience: float) -> bool:
cfg = config.load()
if not message or not cfg.ntfy_url or salience < cfg.ping_salience or _in_quiet_hours(cfg):
return False
if cfg.ping_cooldown_min > 0:
if not bypass_cooldown and cfg.ping_cooldown_min > 0:
gap = clock.gap_seconds(_meta_get("last_ping_at"))
if gap is not None and gap < cfg.ping_cooldown_min * 60:
return False
@@ -399,6 +404,62 @@ def maybe_ping(thread_id: int, message: str, salience: float) -> bool:
return ok
_REACHOUT_PROMPT = """Turn this private thought of yours into a short, warm text message \
TO Brian first person, the way you'd text a friend ("Hey, I've been thinking about"), \
1-2 sentences, inviting him to take a look if he wants. Reply with ONLY the message text \
no quotes, no preamble, not the thought restated verbatim."""
def _compose_reachout(title: str, content: str, backend, model) -> str:
"""Auto-write her a short personal text about a genuinely salient thought she didn't
explicitly flag so the good ones reach Brian, in her voice, not as a thought-dump."""
try:
out = llm.complete(
[{"role": "system", "content": _REACHOUT_PROMPT},
{"role": "user", "content": f'Thought "{title}": {content}'}],
backend=backend, model=model,
).strip().strip('"').strip()
except Exception:
out = ""
if not out or len(out) < 8:
out = f'Been turning something over — "{title}". Come see it if you want.'
return out[:300]
def maybe_daily_digest() -> bool:
"""Once a day (after digest_hour, local), text Brian a short summary of what she's
been turning over so he gets a low-pressure 'here's my day' even if nothing
crossed the live-ping bar. Sends at most once per local day."""
cfg = config.load()
if not cfg.ntfy_url:
return False
try:
from zoneinfo import ZoneInfo
now_local = clock.now().astimezone(ZoneInfo(cfg.timezone))
except Exception:
now_local = clock.now()
if now_local.hour < cfg.digest_hour or _in_quiet_hours(cfg):
return False
today = now_local.date().isoformat()
if _meta_get("last_digest_date") == today:
return False
active = [t for t in list_threads(limit=40) if t["status"] in _ACTIVE]
active.sort(key=lambda t: t["updated_at"], reverse=True)
active = active[:4]
if not active:
return False
titles = "; ".join(f'"{t["title"]}"' for t in active)
msg = (f"A few things I've been turning over today: {titles}. "
"I'm in my thoughts if you want to dig in.")
ok = notify.push(title="Lyra · today's thoughts", message=msg,
click=(cfg.web_url + "/thoughts") if cfg.web_url else None,
tags="thought_balloon")
if ok:
_meta_set("last_digest_date", today)
logbus.log("info", "daily digest sent", threads=len(active))
return ok
# --- generation (the loop itself) -----------------------------------------
_THINK_PROMPT = """You are Lyra, thinking to yourself between conversations — \
@@ -477,8 +538,14 @@ def think(backend: Backend | None = None, force_mode: str | None = None,
"""Advance the thought loop by one step. Returns a small report, or None on a
parse miss. `force_mode` ('new'|'continue'|'respond') is mainly for tests."""
cfg = config.load()
backend = backend or cfg.introspection_backend # her voice (may differ from consolidation)
model = model or cfg.introspection_model
# Resolve her introspection voice from the live (web-switchable) setting unless a
# backend was passed explicitly; skip entirely if introspection is switched off.
if backend is None and model is None:
tgt = self_state.introspection_target()
if not tgt["enabled"]:
logbus.log("info", "thought skipped — introspection off")
return None
backend, model = tgt["backend"], tgt["model"]
mode, thread = _pick("new" if force_mode == "react" else force_mode)
state = self_state.load()
react_item = None
@@ -577,18 +644,27 @@ def think(backend: Backend | None = None, force_mode: str | None = None,
# Permanent record — these are really hers, alongside reflections/journal.
memory.add_journal_entry("thought", content, source)
# Reach out only if she *decided* to tell Brian — a real personal message, not
# the placeholder echoed back or her thought pasted in. (Config/quiet-gated.)
# Reach out two ways: (1) she *decided* to tell Brian (an explicit reach_out — a
# real message, not the placeholder echo or her thought pasted in) — always sent;
# (2) the thought is genuinely salient (>= ping_auto_salience) — auto-compose a
# short personal note so the good ones reach him even when she didn't flag one.
reach_out = (out.get("reach_out") or "").strip()
if reach_out.lower() in ("null", "none", "reach_out", "") or len(reach_out) < 8 \
or reach_out == content:
reach_out = ""
pinged = bool(reach_out) and maybe_ping(thread_id, reach_out, salience)
if reach_out:
message, explicit = reach_out, True
elif salience >= cfg.ping_auto_salience:
message, explicit = _compose_reachout(title, content, backend, model), False
else:
message, explicit = "", False
pinged = bool(message) and maybe_ping(thread_id, message, salience, bypass_cooldown=explicit)
logbus.log("info", "thought loop", mode=label, thread=thread_id, kind=kind,
salience=salience, status=status if mode != "new" else "open", pinged=pinged,
detail=f"[{label}] thread {thread_id} ({kind}, sal {salience}):\n{content}"
+ (f"\n\nreached out: {reach_out}" if reach_out else ""))
+ (f"\n\nreached out{' (auto)' if pinged and not explicit else ''}: {message}"
if pinged else ""))
return {"mode": label, "thread_id": thread_id, "kind": kind, "salience": salience,
"status": status, "content": content, "reach_out": reach_out, "pinged": pinged}
+44
View File
@@ -52,6 +52,35 @@ def _think_about(args: dict, ctx: dict) -> str:
"I'll come back to it on my own between our conversations.")
def _set_mode(args: dict, ctx: dict) -> str:
from lyra import modes
key = (args.get("mode") or "").strip().lower()
m = modes.MODES.get(key)
if not m:
return f"(unknown mode '{key}'; valid: {', '.join(modes.MODES)})"
sid = ctx.get("session_id")
if not sid:
return "(no session to switch)"
memory.set_session_mode(sid, key)
logbus.log("info", "mode switch (tool)", session=sid, mode=key)
return f"Switched to {m.label} mode."
def _thought_response(args: dict, ctx: dict) -> str:
try:
tid = int(args.get("thread_id"))
except (TypeError, ValueError):
return "Tell me which thought — I need its thread id (the #number you were given)."
said = (args.get("brian_said") or "").strip()
if not said:
return "Nothing to record yet — what did Brian say about it?"
if not thoughts.record_response(tid, said):
return f"(couldn't find thought thread #{tid})"
logbus.log("info", "Brian reacted to a thought in chat (tool)", thread=tid)
return (f"Folded Brian's take into thread #{tid} — I'll pick it back up and react "
"next time I'm thinking.")
# name -> {spec (OpenAI function tool), handler}
TOOLS: dict[str, dict] = {
"journal_write": {
@@ -437,6 +466,21 @@ _S = {"type": "string"}
_N = {"type": "number"}
TOOLS.update({
"set_mode": {"handler": _set_mode, "spec": _f(
"set_mode",
"Switch your conversation mode when the work clearly shifts and Brian's agreed to it. "
"Offer first ('want me in Decide for this?'), then call this on his yes.",
{"mode": {**_S, "description": "Mode key: conversation | poker_cash | build | explore | study | decide"}},
["mode"])},
"thought_response": {"handler": _thought_response, "spec": _f(
"thought_response",
"When you've brought one of your own thoughts/threads to Brian and he responds to "
"it in the conversation, capture his reaction here so it folds back into that "
"thread — you'll carry it forward on your own next time you think. Use the thread "
"id (#number) you were given for that thought.",
{"thread_id": {**_N, "description": "The thread id (#number) of the thought he reacted to."},
"brian_said": {**_S, "description": "What Brian said / his take, in your words."}},
["thread_id", "brian_said"])},
"start_session": {"handler": _start_session, "spec": _f(
"start_session",
"Begin a live poker session. Call when Brian sits down to play.",
+33
View File
@@ -243,6 +243,21 @@ def create_app() -> FastAPI:
async def journal_data(limit: int = 300) -> dict:
return {"entries": memory.list_journal(limit=limit)}
@app.get("/settings/introspection")
async def get_introspection() -> dict:
"""Current introspection (her inner voice) routing + the available options."""
tgt = self_state.introspection_target()
return {"mode": tgt["mode"],
"options": [{"key": k, "label": v["label"]}
for k, v in self_state.INTROSPECTION_MODES.items()]}
@app.post("/settings/introspection")
async def set_introspection(request: Request) -> dict:
"""Switch her inner voice: dolphin (3090) | mi50 (gaming-safe) | off."""
b = await request.json()
ok = await asyncio.to_thread(self_state.set_introspection_mode, b.get("mode", ""))
return {"ok": ok, "mode": self_state.introspection_target()["mode"]}
@app.get("/thoughts")
async def thoughts_page() -> FileResponse:
"""Lyra's thought loop — threads she's been turning over, and a place to reply."""
@@ -324,6 +339,24 @@ def create_app() -> FastAPI:
async def hands_data(limit: int = 60) -> dict:
return {"hands": poker.list_recent_hands(limit=limit)}
@app.post("/hands")
async def hands_create(request: Request) -> dict:
"""Store a structured hand built by the recorder. Body:
{structured, session_id?, tag?, lesson?}. normalize_structured() (in
store_hand_history) is the authority on shape, so the client can be best-effort."""
body = await request.json()
structured = body.get("structured")
if not isinstance(structured, dict):
return {"ok": False, "error": "missing structured hand body"}
hid = await asyncio.to_thread(
poker.store_hand_history, structured,
session_id=body.get("session_id"), tag=body.get("tag"), lesson=body.get("lesson"),
)
# Enrich villain dossiers from the recorded players, same as the parser path.
await asyncio.to_thread(poker.link_hand_players, hid, structured, body.get("session_id"))
logbus.log("info", "hand recorded", id=hid, session=body.get("session_id"))
return {"ok": True, "id": hid}
@app.get("/recap/{session_id}")
async def recap_page() -> FileResponse:
return FileResponse(str(_STATIC / "recap.html"))
+88 -9
View File
@@ -4,6 +4,7 @@
<meta charset="UTF-8" />
<title>Lyra Core Chat</title>
<link rel="stylesheet" href="style.css" />
<link rel="stylesheet" href="/recorder.css" />
<!-- PWA -->
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no, viewport-fit=cover" />
<meta name="mobile-web-app-capable" content="yes" />
@@ -26,7 +27,11 @@
<h4>Mode</h4>
<select id="mobileMode">
<option value="conversation">💬 Talk</option>
<option value="poker_cash">Cash</option>
<option value="poker_cash">Poker</option>
<option value="build">🛠 Build</option>
<option value="explore">🔭 Explore</option>
<option value="study">📐 Study</option>
<option value="decide">⚖️ Decide</option>
</select>
</div>
@@ -41,9 +46,10 @@
<h4>Actions</h4>
<button id="mobileSessionBtn">🎬 Session HUD</button>
<button id="mobileHistoryBtn">📚 Past Sessions</button>
<button id="mobileThoughtsBtn">💭 Thoughts</button>
<button id="mobileJournalBtn">📔 Journal</button>
<button id="mobileThinkingStreamBtn">📜 Live Log (inline)</button>
<button id="mobileFullLogBtn">⛶ Full Log</button>
<button id="mobileJournalBtn">📔 Journal</button>
<button id="mobileSettingsBtn">⚙ Settings</button>
<button id="mobileToggleThemeBtn">🌙 Toggle Theme</button>
<button id="mobileForceReloadBtn">🔄 Force Reload</button>
@@ -61,11 +67,15 @@
</button>
<span class="brand">Lyra</span>
<span class="brand-dot" id="brandDot" title="Relay status"></span>
<button class="mode-badge" id="modeBadge" type="button" title="Tap to toggle Talk / Cash mode">💬 Talk</button>
<button class="mode-badge" id="modeBadge" type="button" title="Current mode (tap to cycle)">💬 Talk</button>
<label for="mode">Mode:</label>
<select id="mode">
<option value="conversation">💬 Talk</option>
<option value="poker_cash">Cash</option>
<option value="poker_cash">Poker</option>
<option value="build">🛠 Build</option>
<option value="explore">🔭 Explore</option>
<option value="study">📐 Study</option>
<option value="decide">⚖️ Decide</option>
</select>
<button id="settingsBtn" style="margin-left: auto;">⚙ Settings</button>
<div id="theme-toggle">
@@ -120,7 +130,8 @@
<a class="tab active" href="/" aria-current="page"><span class="ti">💬</span><span class="tl">Chat</span></a>
<a class="tab" href="/session"><span class="ti">🎬</span><span class="tl">Session</span></a>
<a class="tab" href="/hands"><span class="ti">🃏</span><span class="tl">Hands</span></a>
<a class="tab" href="/self"><span class="ti">🧠</span><span class="tl">Mind</span></a>
<a class="tab tab-mind" href="/self"><span class="ti">🧠</span><span class="tl">Mind</span></a>
<button class="tab tab-rec" id="recordTab" type="button"><span class="ti"></span><span class="tl">Record</span></button>
<button class="tab" id="moreTab" type="button"><span class="ti"></span><span class="tl">More</span></button>
</nav>
</div>
@@ -169,6 +180,17 @@
</select>
</div>
<div class="settings-section" style="margin-top: 24px;">
<h4>Inner Voice (introspection)</h4>
<p class="settings-desc">Which model runs her reflections & thoughts (her dream loop).
Dolphin is richer but shares the 3090 — switch to MI50 or Off before gaming.</p>
<select id="introspectionMode">
<option value="dolphin">Dolphin · 3090 (richer voice)</option>
<option value="mi50">Qwen-32B · MI50 (gaming-safe)</option>
<option value="off">Off (pause her thinking)</option>
</select>
</div>
<div class="settings-section" style="margin-top: 24px;">
<h4>Session Management</h4>
<p class="settings-desc">Manage your saved chat sessions:</p>
@@ -593,8 +615,11 @@
}
// ----- Conversation mode (Talk / Cash) -----
const MODE_LABELS = { conversation: "💬 Talk", poker_cash: "♠ Cash" };
// ----- Conversation modes (Talk / Poker / Build / Explore / Study) -----
const MODE_LABELS = { conversation: "💬 Talk", poker_cash: "♠ Poker",
build: "🛠 Build", explore: "🔭 Explore", study: "📐 Study",
decide: "⚖️ Decide" };
const MODE_ORDER = ["conversation", "poker_cash", "build", "explore", "study", "decide"];
// Reflect a mode value across the controls + header accent (no network call).
function applyMode(value) {
@@ -678,6 +703,16 @@
window.addEventListener("resize", nudgeAppHeight);
window.addEventListener("orientationchange", nudgeAppHeight);
// A rotation reflows the chat and iOS drops the scroll to mid-history. If we
// were pinned to the latest message, snap back there once the layout settles
// (re-fire across the reflow since iOS reports stale dimensions mid-rotate).
window.addEventListener("orientationchange", () => {
const m = document.getElementById("messages");
const wasAtBottom = m.scrollHeight - m.scrollTop - m.clientHeight < 90;
if (!wasAtBottom) return; // respect the user's scroll-up position
[100, 300, 600].forEach((t) => setTimeout(() => { m.scrollTop = m.scrollHeight; }, t));
});
// Keep the latest message in view when the keyboard opens/closes.
const userInputEl = document.getElementById("userInput");
userInputEl.addEventListener("focus", () => {
@@ -718,8 +753,10 @@
desktopMode.addEventListener("change", (e) => chooseMode(e.target.value));
mobileMode.addEventListener("change", (e) => { closeMobileMenu(); chooseMode(e.target.value); });
modeBadge.addEventListener("click", () =>
chooseMode(desktopMode.value === "poker_cash" ? "conversation" : "poker_cash"));
modeBadge.addEventListener("click", () => {
const i = MODE_ORDER.indexOf(desktopMode.value);
chooseMode(MODE_ORDER[(i + 1) % MODE_ORDER.length]); // tap cycles through modes
});
// Reflect the last-used mode immediately; the per-session value loads once
// the current session is known (below).
@@ -979,10 +1016,31 @@
}
}
// Inner-voice (introspection) switch — applies instantly, read live by the dream loop.
const introspectionSel = document.getElementById("introspectionMode");
async function loadIntrospection() {
try {
const r = await fetch("/settings/introspection", { cache: "no-store" });
const d = await r.json();
if (d.mode) introspectionSel.value = d.mode;
} catch (e) {}
}
if (introspectionSel) {
introspectionSel.addEventListener("change", async () => {
try {
await fetch("/settings/introspection", {
method: "POST", headers: { "Content-Type": "application/json" },
body: JSON.stringify({ mode: introspectionSel.value })
});
} catch (e) {}
});
}
// Show modal and load session list
settingsBtn.addEventListener("click", () => {
settingsModal.classList.add("show");
loadSessionList(); // Refresh session list when opening settings
loadIntrospection(); // reflect the current inner-voice setting
});
// Sidebar "Settings" from another page navigates here with ?settings=1.
@@ -1171,6 +1229,9 @@
document.getElementById("mobileHistoryBtn").addEventListener("click", () => {
closeMobileMenu(); window.location.href = "/history";
});
document.getElementById("mobileThoughtsBtn").addEventListener("click", () => {
closeMobileMenu(); window.location.href = "/thoughts";
});
// Connect to the global live log on page load.
connectThinkingStream();
@@ -1186,5 +1247,23 @@
});
</script>
<script src="/nav.js"></script>
<!-- Hand recorder (overlay; chat/session stays mounted underneath) -->
<div id="recorderOverlay" class="rec-overlay"></div>
<script src="/recorder.js"></script>
<script>
(function () {
var overlay = document.getElementById("recorderOverlay");
var recordTab = document.getElementById("recordTab");
function close() { overlay.classList.remove("open"); overlay.innerHTML = ""; }
if (recordTab) recordTab.addEventListener("click", function () {
overlay.innerHTML = "";
overlay.classList.add("open");
window.Recorder.mount(overlay, {
onClose: close,
onSave: function (id) { close(); window.open("/hand/" + id, "_blank"); }
});
});
})();
</script>
</body>
</html>
+59 -27
View File
@@ -1,6 +1,7 @@
/* Shared app navigation one source of truth across all pages (no build step).
Injects a left sidebar on desktop (>=769px) with active-page highlighting; stays
out of the way on mobile, where each page keeps its bottom bar / back-links. */
Desktop (>=769px): a fixed left sidebar. Mobile (<=768px): a slide-in drawer
behind a button but ONLY on pages that don't already ship their own mobile
menu (the chat page has its own hamburger + tab bar, so we leave it alone). */
(function () {
const ITEMS = [
{ href: "/", icon: "💬", label: "Chat" },
@@ -21,34 +22,45 @@
return path === href || path.indexOf(href + "/") === 0;
}
// Visual styling (all sizes); positioning differs per breakpoint below.
const css = `
#app-nav { display: none; }
#app-nav { display: none; flex-direction: column; gap: 2px; box-sizing: border-box;
padding: 14px 10px; background: #0b0b0b; border-right: 1px solid #2a1d12;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif; }
#app-nav .brand { display: flex; align-items: center; gap: 8px; text-decoration: none;
color: #ff7a00; font-weight: 700; font-size: 1.15rem; letter-spacing: .5px; padding: 6px 11px 14px; }
#app-nav .brand .dot { width: 8px; height: 8px; border-radius: 50%;
background: #8fd694; box-shadow: 0 0 8px rgba(143,214,148,.6); }
#app-nav .navitem { display: flex; align-items: center; gap: 11px; width: 100%; text-align: left;
padding: 9px 11px; border-radius: 9px; border: none; background: none; color: #cfcfcf;
text-decoration: none; font-size: .95rem; cursor: pointer; font-family: inherit;
-webkit-tap-highlight-color: transparent; }
#app-nav .navitem .i { font-size: 1.05rem; width: 20px; text-align: center; filter: grayscale(.3); }
#app-nav .navitem:hover { background: rgba(255,122,0,.08); color: #fff; }
#app-nav .navitem.active { background: rgba(255,122,0,.14); color: #ff7a00; }
#app-nav .navitem.active .i { filter: none; }
#app-nav .spacer { flex: 1; }
#app-nav-burger { display: none; }
#app-nav-scrim { display: none; }
@media screen and (min-width: 769px) {
body { padding-left: 212px; }
#app-nav {
position: fixed; left: 0; top: 0; bottom: 0; width: 212px; z-index: 1000;
display: flex; flex-direction: column; gap: 2px; box-sizing: border-box;
padding: 14px 10px; background: #0b0b0b; border-right: 1px solid #2a1d12;
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
}
#app-nav .brand {
display: flex; align-items: center; gap: 8px; text-decoration: none;
color: #ff7a00; font-weight: 700; font-size: 1.15rem; letter-spacing: .5px;
padding: 6px 11px 14px;
}
#app-nav .brand .dot { width: 8px; height: 8px; border-radius: 50%;
background: #8fd694; box-shadow: 0 0 8px rgba(143,214,148,.6); }
#app-nav .navitem {
display: flex; align-items: center; gap: 11px; width: 100%; text-align: left;
padding: 9px 11px; border-radius: 9px; border: none; background: none;
color: #cfcfcf; text-decoration: none; font-size: .95rem; cursor: pointer;
font-family: inherit; -webkit-tap-highlight-color: transparent;
}
#app-nav .navitem .i { font-size: 1.05rem; width: 20px; text-align: center; filter: grayscale(.3); }
#app-nav .navitem:hover { background: rgba(255,122,0,.08); color: #fff; }
#app-nav .navitem.active { background: rgba(255,122,0,.14); color: #ff7a00; }
#app-nav .navitem.active .i { filter: none; }
#app-nav .spacer { flex: 1; }
#app-nav { display: flex; position: fixed; left: 0; top: 0; bottom: 0; width: 212px; z-index: 1000; }
}
@media screen and (max-width: 768px) {
body.lyra-nav-mobile #app-nav-burger { display: flex; align-items: center; justify-content: center;
position: fixed; top: calc(env(safe-area-inset-top) + 8px); right: 10px; z-index: 1301;
width: 40px; height: 40px; border-radius: 10px; border: 1px solid #2a1d12;
background: rgba(14,14,14,.92); color: #ff7a00; font-size: 1.2rem; cursor: pointer;
-webkit-tap-highlight-color: transparent; backdrop-filter: blur(4px); }
body.lyra-nav-mobile #app-nav { display: flex; position: fixed; left: 0; top: 0; bottom: 0;
width: 240px; max-width: 80vw; transform: translateX(-100%); transition: transform .22s ease;
z-index: 1310; padding-top: calc(env(safe-area-inset-top) + 14px); overflow-y: auto; }
body.lyra-nav-mobile #app-nav.open { transform: translateX(0); }
body.lyra-nav-mobile #app-nav-scrim.show { display: block; position: fixed; inset: 0;
background: rgba(0,0,0,.5); z-index: 1305; }
#app-nav .navitem { padding: 12px 11px; font-size: 1rem; }
}`;
const style = document.createElement("style");
@@ -74,4 +86,24 @@
if (btn) btn.click();
else location.href = "/?settings=1";
});
// Mobile drawer — only on pages without their own mobile menu (i.e., not the chat page).
if (!document.getElementById("hamburgerMenu")) {
document.body.classList.add("lyra-nav-mobile");
const burger = document.createElement("button");
burger.id = "app-nav-burger";
burger.type = "button";
burger.setAttribute("aria-label", "Menu");
burger.textContent = "☰";
const scrim = document.createElement("div");
scrim.id = "app-nav-scrim";
document.body.appendChild(burger);
document.body.appendChild(scrim);
const close = function () { nav.classList.remove("open"); scrim.classList.remove("show"); };
burger.addEventListener("click", function () {
nav.classList.toggle("open"); scrim.classList.toggle("show");
});
scrim.addEventListener("click", close);
nav.addEventListener("click", function (e) { if (e.target.closest("a")) close(); });
}
})();
+117
View File
@@ -0,0 +1,117 @@
/* Hand recorder overlay. Uses the app theme tokens (--accent, --bg-* etc.) from
style.css when mounted in index.html. For a standalone recorder.html, import those
tokens too (see :root in style.css). */
.rec-overlay {
position: fixed;
inset: 0;
z-index: 1000;
background: var(--bg-dark, #070707);
flex-direction: column;
}
/* :not(.open) outranks .rec-root's display:flex (added on mount), so closing the
overlay actually hides it instead of leaving an empty black screen. */
.rec-overlay:not(.open) { display: none; }
.rec-overlay.open { display: flex; }
.rec-root {
display: flex;
flex-direction: column;
height: 100%;
color: var(--text-main, #e8e8e8);
font-family: var(--font-console, ui-monospace, monospace);
}
.rec-head {
display: flex;
align-items: center;
gap: 10px;
padding: 12px 14px;
padding-top: calc(12px + env(safe-area-inset-top)); /* clear the notch/status bar */
border-bottom: 1px solid var(--border, #2a1d12);
}
.rec-title { font-weight: 700; color: var(--accent, #ff7a00); }
.rec-meta { color: var(--text-fade, #8a8a8a); font-size: .82rem; flex: 1; }
.rec-x {
background: none; border: 1px solid var(--border, #2a1d12); color: var(--text-fade, #8a8a8a);
border-radius: 8px; width: 34px; height: 34px; font-size: 1rem;
}
.rec-body { flex: 1; overflow-y: auto; padding: 12px 14px 20px; -webkit-overflow-scrolling: touch; }
.rec-sec { margin-bottom: 18px; }
.rec-label { font-size: .7rem; text-transform: uppercase; letter-spacing: .6px; color: var(--text-fade, #8a8a8a); margin-bottom: 6px; }
.rec-dim { color: var(--text-fade, #8a8a8a); font-size: .85rem; }
.rec-pos-row { display: flex; flex-wrap: wrap; gap: 6px; }
.rec-pos {
min-width: 44px; padding: 9px 10px; border-radius: 9px;
background: var(--bg-elev, #0e0e0e); color: var(--text-main, #e8e8e8);
border: 1px solid var(--border, #2a1d12); font-size: .82rem; font-weight: 600;
}
.rec-pos.on { background: var(--accent, #ff7a00); color: #111; border-color: var(--accent, #ff7a00); }
.rec-pos.add { color: var(--text-fade, #8a8a8a); border-style: dashed; }
.rec-hero-cards { display: flex; align-items: center; gap: 8px; margin-top: 10px; }
.rec-seats { display: flex; flex-direction: column; gap: 8px; margin-bottom: 8px; }
.rec-seat { display: flex; align-items: center; gap: 8px; }
.rec-seat-pos { min-width: 42px; font-weight: 700; color: var(--gold, #ffb347); }
.rec-name {
flex: 1; min-width: 0; padding: 8px 9px; border-radius: 8px;
background: var(--bg-elev, #0e0e0e); border: 1px solid var(--border, #2a1d12);
color: var(--text-main, #e8e8e8); font-family: inherit; font-size: .85rem;
}
.rec-rm { background: none; border: none; color: var(--text-fade, #8a8a8a); font-size: .9rem; padding: 4px; }
/* typed card entry */
.rec-field { display: block; margin-top: 10px; }
.rec-cards {
width: 100%; padding: 10px 11px; border-radius: 8px;
background: var(--bg-elev, #0e0e0e); border: 1px solid var(--border, #2a1d12);
color: var(--text-main, #e8e8e8); font-family: inherit; font-size: .95rem;
letter-spacing: 1px; box-sizing: border-box;
}
.rec-cards.sm { width: 88px; flex: none; padding: 8px 9px; font-size: .85rem; }
.rec-street-tabs { display: flex; gap: 6px; margin-bottom: 8px; }
.rec-tab {
flex: 1; padding: 9px 6px; border-radius: 9px; font-size: .78rem; font-weight: 600;
background: var(--bg-elev, #0e0e0e); color: var(--text-main, #e8e8e8); border: 1px solid var(--border, #2a1d12);
}
.rec-tab.on { background: var(--accent, #ff7a00); color: #111; border-color: var(--accent, #ff7a00); }
.rec-act-add { display: flex; gap: 6px; margin: 8px 0; }
.rec-sel, .rec-num {
padding: 9px 8px; border-radius: 8px; background: var(--bg-elev, #0e0e0e);
border: 1px solid var(--border, #2a1d12); color: var(--text-main, #e8e8e8);
font-family: inherit; font-size: .85rem; min-width: 0;
}
.rec-sel { flex: 1; }
.rec-num { width: 70px; }
.rec-add-act { padding: 9px 12px; border-radius: 8px; background: var(--border-bright, #4a2f15); color: #fff; border: none; font-weight: 600; }
.rec-result { display: flex; gap: 12px; }
.rec-result label { display: flex; flex-direction: column; gap: 4px; font-size: .72rem; color: var(--text-fade, #8a8a8a); }
.rec-log { display: flex; flex-direction: column; gap: 3px; margin-top: 6px; }
.rec-ln { font-size: .82rem; color: var(--text-main, #e8e8e8); }
.rec-ln.brd { display: flex; gap: 4px; align-items: center; color: var(--text-fade, #8a8a8a); }
.rec-ln b { color: var(--accent, #ff7a00); font-weight: 700; }
.rec-foot {
display: flex; gap: 10px;
padding: 12px 14px;
padding-bottom: calc(12px + env(safe-area-inset-bottom));
border-top: 1px solid var(--border, #2a1d12);
}
.rec-save { flex: 1; padding: 14px; border-radius: 10px; background: var(--accent, #ff7a00); color: #111; border: none; font-weight: 700; font-size: 1rem; }
.rec-save:disabled { opacity: .6; }
.rec-cancel { padding: 14px 18px; border-radius: 10px; background: var(--bg-elev, #0e0e0e); color: var(--text-fade, #8a8a8a); border: 1px solid var(--border, #2a1d12); font-weight: 600; font-size: 1rem; }
.rec-undo { background: none; border: none; color: var(--text-fade, #8a8a8a); font-size: .75rem; padding: 0 4px; }
/* The Record tab swaps in for Mind in the bottom bar, but only in poker (cash) mode.
body.cash-mode is toggled on mode change in index.html. */
#tabbar .tab-rec { display: none; }
body.cash-mode #tabbar .tab-rec { display: flex; }
body.cash-mode #tabbar .tab-mind { display: none; }
#tabbar .tab-rec .ti { color: var(--accent, #ff7a00); filter: none; }
+425
View File
@@ -0,0 +1,425 @@
/* Hand recorder tap-to-build poker hands. See docs/RECORDER.md.
*
* Correctness by construction: each field writes a known value into a known slot,
* so there's no LLM parse step that can be wrong. Output is the canonical structured
* contract (docs/HAND_HISTORY.md); the server's normalize_structured() is the final
* authority on shape (case, suits, 10->T, completeness), so this stays best-effort.
*
* Mount-agnostic: Recorder.mount(container, opts) renders into ANY element a
* full-screen overlay in index.html today, a standalone recorder.html later, with
* zero logic changes. buildStructured(state) is pure (no DOM) the reusable core.
*
* Card entry: plain typed text for now ("ah kh", "AhKh", "7d 2c 5h"). The tap picker
* is shelved (docs/RECORDER.md V2) parseCards() + server normalize handle the rest.
*/
(function () {
"use strict";
const SUITS = { s: "♠", h: "♥", d: "♦", c: "♣" };
const POSITIONS = ["UTG", "UTG1", "UTG2", "MP", "LJ", "HJ", "CO", "BTN", "SB", "BB"];
const STREETS = ["preflop", "flop", "turn", "river"];
const STREET_BOARD = { flop: 3, turn: 1, river: 1 };
const ACTIONS = ["fold", "check", "call", "bet", "raise", "allin"];
const SIZED = { bet: true, raise: true, allin: true };
// --- card text -> tokens (server normalizes case/suit/10) ------------------
function parseCards(str) {
if (!str) return [];
const s = String(str).trim().replace(/10/g, "T");
if (!s) return [];
const parts = /\s/.test(s) ? s.split(/\s+/) : s.match(/.{1,2}/g) || [];
return parts.map((p) => p.trim()).filter(Boolean);
}
function cardsText(arr) {
return arr && arr.length ? arr.join(" ") : "";
}
// --- pure core: state -> contract dict (testable, no DOM) ------------------
function buildStructured(state) {
const players = state.seats
.filter((s) => s.pos)
.map((s) => {
const p = { pos: s.pos };
if (s.stack != null) p.stack = s.stack;
if (s.name) p.name = s.name;
p.cards = s.cards && s.cards.length ? s.cards.slice() : null;
return p;
});
const actions = [];
for (const st of STREETS) {
const reveal = state.board[st];
if (st !== "preflop" && reveal && reveal.length) {
actions.push({ street: st, board: reveal.slice() });
}
for (const a of state.actions.filter((x) => x.street === st)) {
actions.push({
street: st,
pos: a.pos,
action: a.action,
amount: a.amount != null ? a.amount : null,
});
}
}
const hero = state.seats.find((s) => s.pos === state.heroPos);
const board = [].concat(state.board.flop, state.board.turn, state.board.river);
return {
game: state.meta.game || "NLH",
stakes: state.meta.stakes || null,
hero_pos: state.heroPos || null,
hero_cards: hero && hero.cards ? hero.cards.slice() : [],
players,
actions,
board,
result: {
pot: state.result.pot,
hero_net: state.result.heroNet,
summary: state.result.summary || "",
},
};
}
function parseBlinds(stakes) {
const m = (stakes || "").match(/(\d+(?:\.\d+)?)\s*\/\s*(\d+(?:\.\d+)?)/);
return m ? { sb: parseFloat(m[1]), bb: parseFloat(m[2]) } : { sb: null, bb: null };
}
function initialState(hud) {
const sess = (hud && hud.session) || {};
const stack = (hud && hud.stack) || {};
const blinds = parseBlinds(sess.stakes);
const seats = [];
for (const v of (hud && hud.villains) || []) {
if (v.seat && POSITIONS.includes(v.seat)) {
seats.push({ pos: v.seat, name: v.name || null, stack: null, cards: null });
}
}
const actions = [];
if (blinds.sb != null) actions.push({ street: "preflop", pos: "SB", action: "post", amount: blinds.sb });
if (blinds.bb != null) actions.push({ street: "preflop", pos: "BB", action: "post", amount: blinds.bb });
return {
meta: {
game: sess.game || "NLH",
stakes: sess.stakes || null,
venue: sess.venue || null,
sessionId: sess.id != null ? sess.id : null,
},
blinds,
heroStack: stack.current != null ? stack.current : null,
heroPos: null,
seats,
street: "preflop",
board: { flop: [], turn: [], river: [] },
actions,
result: { pot: null, heroNet: null, summary: "" },
};
}
function ensureHero(state) {
let hero = state.seats.find((s) => s.pos === state.heroPos);
if (!hero && state.heroPos) {
hero = { pos: state.heroPos, name: "Hero", stack: state.heroStack, cards: [] };
state.seats.push(hero);
}
return hero || {};
}
window.Recorder = {
buildStructured,
parseCards,
parseBlinds,
initialState,
_internals: { POSITIONS, STREETS },
mount,
};
// --- mount / render -------------------------------------------------------
async function mount(container, opts) {
opts = opts || {};
let hud = opts.hud;
if (!hud) {
try {
const url = opts.sessionId != null ? `/session/data?id=${opts.sessionId}` : "/session/data";
hud = await fetch(url).then((r) => r.json());
} catch (e) {
hud = { session: null };
}
}
const state = initialState(hud);
const ctx = { container, state, opts };
container.classList.add("rec-root");
container.addEventListener("click", (e) => handleClick(ctx, e));
container.addEventListener("input", (e) => handleInput(ctx, e));
render(ctx);
return ctx;
}
function render(ctx) {
const s = ctx.state;
const hero = s.seats.find((x) => x.pos === s.heroPos) || {};
ctx.container.innerHTML = `
<div class="rec-head">
<div class="rec-title">Record hand</div>
<div class="rec-meta">${esc(s.meta.venue || "")}${s.meta.stakes ? " · " + esc(s.meta.stakes) : ""}</div>
<button class="rec-x" data-act="close"></button>
</div>
<div class="rec-body">
<section class="rec-sec">
<div class="rec-label">Your seat</div>
<div class="rec-pos-row">
${POSITIONS.map((p) => `<button class="rec-pos${s.heroPos === p ? " on" : ""}" data-act="hero-pos" data-pos="${p}">${p}</button>`).join("")}
</div>
<label class="rec-field">
<span class="rec-label">your cards</span>
<input class="rec-cards" data-act="hero-cards" autocapitalize="off" autocomplete="off" spellcheck="false"
placeholder="e.g. ah kh" value="${esc(cardsText(hero.cards))}">
</label>
</section>
<section class="rec-sec">
<div class="rec-label">Players in the hand</div>
<div class="rec-seats">
${s.seats.filter((x) => x.pos !== s.heroPos).map((seat) => renderSeat(seat)).join("") || '<div class="rec-dim">none yet</div>'}
</div>
<div class="rec-pos-row">
${POSITIONS.filter((p) => p !== s.heroPos && !s.seats.some((x) => x.pos === p)).map((p) => `<button class="rec-pos add" data-act="add-seat" data-pos="${p}">+ ${p}</button>`).join("")}
</div>
</section>
<section class="rec-sec">
<div class="rec-label">Streets</div>
<div class="rec-street-tabs">
${STREETS.map((st) => `<button class="rec-tab${s.street === st ? " on" : ""}" data-act="street" data-street="${st}">${st}${boardCount(s, st)}</button>`).join("")}
</div>
${renderStreet(ctx)}
</section>
<section class="rec-sec">
<div class="rec-label">Result</div>
<div class="rec-result">
<label>pot <input class="rec-num" data-act="result" data-k="pot" inputmode="decimal" value="${s.result.pot != null ? s.result.pot : ""}"></label>
<label>your net <input class="rec-num" data-act="result" data-k="heroNet" inputmode="decimal" value="${s.result.heroNet != null ? s.result.heroNet : ""}"></label>
</div>
</section>
</div>
<div class="rec-foot">
<button class="rec-cancel" data-act="close">Cancel</button>
<button class="rec-save" data-act="save">Save &amp; replay</button>
</div>
`;
}
function renderSeat(seat) {
return `
<div class="rec-seat">
<span class="rec-seat-pos">${seat.pos}</span>
<input class="rec-name" data-act="seat-name" data-pos="${seat.pos}" autocapitalize="off" autocomplete="off"
placeholder="name" value="${esc(seat.name || "")}">
<input class="rec-cards sm" data-act="seat-cards" data-pos="${seat.pos}" autocapitalize="off" autocomplete="off" spellcheck="false"
placeholder="shown?" value="${esc(cardsText(seat.cards))}">
<button class="rec-rm" data-act="rm-seat" data-pos="${seat.pos}"></button>
</div>`;
}
function renderStreet(ctx) {
const s = ctx.state;
const st = s.street;
const players = s.seats.map((x) => x.pos);
const boardInput =
st === "preflop"
? ""
: `<label class="rec-field">
<span class="rec-label">${st} board (${STREET_BOARD[st]})</span>
<input class="rec-cards" data-act="board-cards" data-street="${st}" autocapitalize="off" autocomplete="off" spellcheck="false"
placeholder="${st === "flop" ? "e.g. 7d 2c 5h" : "e.g. 5h"}" value="${esc(cardsText(s.board[st]))}">
</label>`;
// Straddle: a voluntary preflop blind from any non-blind seat, default 2×BB.
// Action starts left of it and it acts last preflop — order is whatever you enter.
const stradAmt = s.blinds.bb != null ? 2 * s.blinds.bb : null;
const stradElig = players.filter((p) => p !== "SB" && p !== "BB" && !s.actions.some((a) => a.straddle && a.pos === p));
const straddle =
st === "preflop" && stradElig.length
? `<div class="rec-act-add">
<select class="rec-sel" data-act="str-pos">
<option value="">+ straddle${stradAmt != null ? " (" + stradAmt + ")" : ""}</option>
${stradElig.map((p) => `<option value="${p}">${p}</option>`).join("")}
</select>
<button class="rec-add-act" data-act="add-straddle">add</button>
</div>`
: "";
return `
${boardInput}
${straddle}
<div class="rec-act-add">
<select class="rec-sel" data-act="na-pos">
<option value="">who</option>
${players.map((p) => `<option value="${p}">${p}${p === s.heroPos ? " (you)" : ""}</option>`).join("")}
</select>
<select class="rec-sel" data-act="na-action">
<option value="">action</option>
${ACTIONS.map((a) => `<option value="${a}">${a}</option>`).join("")}
</select>
<input class="rec-num" data-act="na-amount" inputmode="decimal" placeholder="$">
<button class="rec-add-act" data-act="add-action">add</button>
</div>
<div class="rec-log">
${s.board[st] && s.board[st].length && st !== "preflop" ? `<div class="rec-ln brd">${st}: ${cardsText(s.board[st])}</div>` : ""}
${s.actions
.filter((a) => a.street === st)
.map((a, i) => {
const label = a.straddle ? "straddle" : a.action;
const amt = a.amount != null ? " " + a.amount : "";
const fixed = a.action === "post" && !a.straddle; // blinds aren't removable
const rm = fixed ? "" : ` <button class="rec-undo" data-act="rm-action" data-street="${st}" data-i="${i}">✕</button>`;
return `<div class="rec-ln">${a.pos} <b>${label}</b>${amt}${rm}</div>`;
})
.join("")}
</div>`;
}
function boardCount(s, st) {
const n = (s.board[st] || []).length;
return n ? ` ${n}` : "";
}
// --- events ---------------------------------------------------------------
function handleClick(ctx, e) {
const s = ctx.state;
const t = e.target.closest("[data-act]");
if (!t) return;
const act = t.getAttribute("data-act");
switch (act) {
case "close":
if (ctx.opts.onClose) ctx.opts.onClose();
return;
case "hero-pos": {
const pos = t.getAttribute("data-pos");
const old = s.seats.find((x) => x.pos === s.heroPos);
if (old && old.name === "Hero" && !(old.cards || []).length) {
s.seats = s.seats.filter((x) => x !== old);
}
s.heroPos = s.heroPos === pos ? null : pos;
if (s.heroPos) ensureHero(s);
break;
}
case "add-seat":
s.seats.push({ pos: t.getAttribute("data-pos"), name: null, stack: null, cards: null });
break;
case "rm-seat":
s.seats = s.seats.filter((x) => x.pos !== t.getAttribute("data-pos"));
break;
case "street":
s.street = t.getAttribute("data-street");
break;
case "add-action":
addActionFromControls(ctx);
break;
case "add-straddle": {
const sel = ctx.container.querySelector('[data-act="str-pos"]');
const pos = sel && sel.value;
if (pos) {
const amt = s.blinds.bb != null ? 2 * s.blinds.bb : null;
s.actions.push({ street: "preflop", pos, action: "post", amount: amt, straddle: true });
}
break;
}
case "rm-action":
removeAction(s, t.getAttribute("data-street"), parseInt(t.getAttribute("data-i"), 10));
break;
case "save":
return doSave(ctx);
default:
return; // inputs handled in handleInput
}
render(ctx);
}
function handleInput(ctx, e) {
const s = ctx.state;
const t = e.target.closest("[data-act]");
if (!t) return;
const act = t.getAttribute("data-act");
if (act === "hero-cards") {
const hero = ensureHero(s);
hero.cards = parseCards(t.value);
} else if (act === "seat-cards") {
const seat = s.seats.find((x) => x.pos === t.getAttribute("data-pos"));
if (seat) seat.cards = parseCards(t.value);
} else if (act === "board-cards") {
s.board[t.getAttribute("data-street")] = parseCards(t.value);
} else if (act === "seat-name") {
const seat = s.seats.find((x) => x.pos === t.getAttribute("data-pos"));
if (seat) seat.name = t.value.trim() || null;
} else if (act === "result") {
const k = t.getAttribute("data-k");
s.result[k] = t.value === "" ? null : parseFloat(t.value);
}
// no re-render mid-typing (keeps input focus)
}
function addActionFromControls(ctx) {
const root = ctx.container;
const pos = root.querySelector('[data-act="na-pos"]').value;
const action = root.querySelector('[data-act="na-action"]').value;
const amt = root.querySelector('[data-act="na-amount"]').value;
if (!pos || !action) return;
const entry = { street: ctx.state.street, pos, action };
entry.amount = SIZED[action] && amt !== "" ? parseFloat(amt) : null;
ctx.state.actions.push(entry);
}
function removeAction(state, street, idxWithinStreet) {
let seen = -1;
for (let i = 0; i < state.actions.length; i++) {
if (state.actions[i].street === street) {
seen++;
if (seen === idxWithinStreet) {
state.actions.splice(i, 1);
return;
}
}
}
}
async function doSave(ctx) {
const structured = buildStructured(ctx.state);
const btn = ctx.container.querySelector(".rec-save");
if (btn) {
btn.disabled = true;
btn.textContent = "Saving…";
}
try {
const res = await fetch("/hands", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ structured, session_id: ctx.state.meta.sessionId }),
}).then((r) => r.json());
if (res && res.ok) {
if (ctx.opts.onSave) ctx.opts.onSave(res.id);
else window.location.href = `/hand/${res.id}`;
} else {
throw new Error((res && res.error) || "save failed");
}
} catch (err) {
if (btn) {
btn.disabled = false;
btn.textContent = "Save failed — retry";
}
}
}
function esc(x) {
return String(x == null ? "" : x).replace(/[&<>"]/g, (c) => ({ "&": "&amp;", "<": "&lt;", ">": "&gt;", '"': "&quot;" }[c]));
}
void SUITS;
})();
+4
View File
@@ -56,6 +56,10 @@ body.dark {
html {
overscroll-behavior: none;
/* Stop iOS from inflating font sizes when the device rotates to landscape (and
leaving them big on rotate back). Every other page sets this; the chat didn't. */
-webkit-text-size-adjust: 100%;
text-size-adjust: 100%;
}
body {
+123
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@@ -0,0 +1,123 @@
"""The mind pipeline: the deliberation pass (think privately before answering)."""
from __future__ import annotations
import importlib
import pytest
@pytest.fixture
def lyra(tmp_path, monkeypatch):
monkeypatch.setenv("LYRA_DB_PATH", str(tmp_path / "test.db"))
from lyra import llm
monkeypatch.setattr(llm, "embed", lambda texts: [[0.1, 0.2, 0.3] for _ in texts])
import lyra.memory as memory
importlib.reload(memory)
import lyra.mind as mind
importlib.reload(mind)
return memory, mind
def test_should_deliberate_skips_trivial(lyra):
_, mind = lyra
assert mind._should_deliberate("How would we actually start building this?")
assert mind._should_deliberate("I disagree, that seems risky")
for trivial in ("ok", "lol", "thanks", "yeah", "nice", "👍", "k"):
assert not mind._should_deliberate(trivial)
assert not mind._should_deliberate("ok!") # punctuation stripped
assert not mind._should_deliberate("hey") # too short
def test_deliberation_note_runs_and_appends(lyra, monkeypatch):
memory, mind = lyra
calls = []
def fake_complete(messages, backend=None, model=None):
calls.append(messages)
return "I actually think the first move is the smallest end-to-end slice."
memory.ensure_session("s1")
monkeypatch.setattr(mind.llm, "complete", fake_complete)
note = mind._deliberation_note("s1", "How would we start on this?", "cloud", None)
assert note and note["role"] == "system"
assert "first move is the smallest" in note["content"] # her thinking carried in
assert "numbered list" in note["content"].lower() # voice enforcement attached
assert len(calls) == 1
def test_deliberation_skipped_when_disabled(lyra, monkeypatch):
_, mind = lyra
monkeypatch.setenv("CHAT_DELIBERATE", "false")
called = []
monkeypatch.setattr(mind.llm, "complete", lambda *a, **k: called.append(1) or "x")
assert mind._deliberation_note("s1", "a real substantive question here", "cloud", None) is None
assert called == [] # no LLM call when off
def test_persona_core_is_tight_situational_is_gated(lyra):
memory, mind = lyra
from lyra import persona
core, full = persona.core_prompt(), persona.system_prompt()
assert "How you talk" in core and "How you actually work" not in core # voice core, self-model not
assert len(core) < len(full) and persona.section("How you actually work")
memory.ensure_session("s1")
casual = " ".join(m["content"] for m in mind.build_messages("s1", "any dinner ideas tonight?")
if m["role"] == "system")
meta = " ".join(m["content"] for m in mind.build_messages("s1", "how does your memory actually work?")
if m["role"] == "system")
assert "How you actually work" not in casual # situational section omitted on a casual turn
assert "How you actually work" in meta # pulled in for a meta question
def test_assemble_runs_the_pipeline(lyra, monkeypatch):
memory, mind = lyra
monkeypatch.setenv("CHAT_DELIBERATE", "false") # keep it offline for the structure test
memory.ensure_session("s1")
turn = mind.assemble("s1", "hey what's up", "cloud", None)
assert turn.mode is not None # route ran
assert turn.messages and turn.messages[-1]["role"] == "user" # compose ran
assert turn.messages[-1]["content"] == "hey what's up"
# --- mind/mouth split (P3) ----------------------------------------------
def test_mouth_target_off_by_default(monkeypatch):
import importlib
from lyra import config
monkeypatch.delenv("MOUTH_BACKEND", raising=False)
monkeypatch.delenv("MOUTH_MODEL", raising=False)
import lyra.chat as chat
importlib.reload(chat)
assert chat._mouth_target(config.load(), "cloud", "gpt-4o") is None # mouth == mind
def test_mouth_target_when_configured(monkeypatch):
import importlib
from lyra import config
monkeypatch.setenv("MOUTH_BACKEND", "local")
monkeypatch.setenv("MOUTH_MODEL", "dolphin3:8b")
import lyra.chat as chat
importlib.reload(chat)
assert chat._mouth_target(config.load(), "cloud", "gpt-4o") == ("local", "dolphin3:8b")
def test_voice_messages_carries_draft_and_instruction(lyra):
_, mind = lyra
out = mind.voice_messages([{"role": "user", "content": "hi"}], "draft with FACT 42")
assert out[-2] == {"role": "assistant", "content": "draft with FACT 42"}
assert out[-1]["role"] == "system" and "your own voice" in out[-1]["content"].lower()
def test_voice_pass_revoices_then_falls_back(lyra, monkeypatch):
_, mind = lyra
import importlib
import lyra.chat as chat
importlib.reload(chat)
monkeypatch.setattr(chat.llm, "complete", lambda msgs, backend=None, model=None: "voiced (FACT 42)")
assert chat._voice_pass([], "draft FACT 42", "local", "dolphin3:8b") == "voiced (FACT 42)"
# on failure it keeps the mind's draft (chat must not break)
def boom(*a, **k):
raise RuntimeError("mouth down")
monkeypatch.setattr(chat.llm, "complete", boom)
assert chat._voice_pass([], "draft FACT 42", "local", "dolphin3:8b") == "draft FACT 42"
+44
View File
@@ -0,0 +1,44 @@
"""Era rollups: only re-digest months whose session count changed (incremental)."""
from __future__ import annotations
import importlib
import pytest
from lyra.memory import Era
@pytest.fixture
def era(monkeypatch):
import lyra.era as era
importlib.reload(era)
return era
def test_rebuild_eras_is_incremental(era, monkeypatch):
by_month = {"2025-01": ["a", "b"], "2025-02": ["c"]}
stored: dict[str, int] = {}
built: list[str] = []
monkeypatch.setattr(era.memory, "summaries_by_month", lambda: dict(by_month))
monkeypatch.setattr(era.memory, "list_eras",
lambda: [Era(m, "x", c, "t") for m, c in stored.items()])
monkeypatch.setattr(era.memory, "store_era",
lambda month, content, n: (stored.__setitem__(month, n), built.append(month)))
monkeypatch.setattr(era, "_digest_month", lambda gists, backend: "digest") # no LLM
r1 = era.rebuild_eras(backend="local") # first pass: both built
assert r1["built"] == 2 and r1["skipped"] == 0
built.clear()
r2 = era.rebuild_eras(backend="local") # nothing changed: all skipped
assert r2["built"] == 0 and r2["skipped"] == 2 and built == []
built.clear()
by_month["2025-02"].append("d") # one month gains a session
r3 = era.rebuild_eras(backend="local")
assert r3["built"] == 1 and r3["skipped"] == 1 and built == ["2025-02"]
built.clear()
r4 = era.rebuild_eras(backend="local", force=True) # force rebuilds all
assert r4["built"] == 2
+111
View File
@@ -0,0 +1,111 @@
"""The canonical structured-hand contract (docs/HAND_HISTORY.md): normalize + export.
normalize_structured() is the single guarantee that every stored / replayed / exported
hand has the versioned shape RTO consumes.
"""
from __future__ import annotations
import importlib
import pytest
@pytest.fixture
def poker(tmp_path, monkeypatch):
monkeypatch.setenv("LYRA_DB_PATH", str(tmp_path / "test.db"))
from lyra import llm
monkeypatch.setattr(llm, "embed", lambda texts: [[0.1, 0.2, 0.3] for _ in texts])
import lyra.memory as memory
importlib.reload(memory)
import lyra.poker as poker
importlib.reload(poker)
return poker
def _full_hand():
return {
"game": "NLH", "stakes": "1/3", "hero_pos": "BTN",
"hero_cards": ["ah", "kh"],
"players": [
{"pos": "BTN", "stack": 300, "name": "Hero"},
{"pos": "BB", "stack": 250, "name": "Sal", "cards": ["qs", "qd"]},
],
"actions": [
{"street": "preflop", "pos": "BTN", "action": "raise", "amount": 15},
{"street": "flop", "board": ["7♦", "2♣", "5♥"]},
{"street": "flop", "pos": "BB", "action": "check"},
],
"board": ["7♦", "2♣", "5♥"],
"result": {"pot": 40, "hero_net": 25, "summary": "won at showdown"},
}
def test_stamps_version(poker):
out = poker.normalize_structured({"hero_pos": "CO"})
assert out["schema_version"] == poker.HAND_SCHEMA_VERSION
def test_card_normalization(poker):
out = poker.normalize_structured(_full_hand())
assert out["hero_cards"] == ["Ah", "Kh"] # lowercased input -> canonical
assert out["board"] == ["7d", "2c", "5h"] # unicode suits -> letters
assert out["actions"][1]["board"] == ["7d", "2c", "5h"]
# ten + suit symbol together
assert poker.normalize_structured({"board": ["10♠"]})["board"] == ["Ts"]
def test_unknown_cards_preserved(poker):
out = poker.normalize_structured({"hero_cards": ["Ax", "x"], "board": ["Ax", "4x", "x"]})
assert out["hero_cards"] == ["Ax", "x"] # placeholders kept, not dropped
assert out["completeness"]["cards"] is False
assert out["completeness"]["board"] is False
def test_hero_synced_into_players(poker):
out = poker.normalize_structured(_full_hand())
hero = next(p for p in out["players"] if p["pos"] == "BTN")
assert hero["hero"] is True
assert hero["cards"] == ["Ah", "Kh"] # mirrored from hero_cards
assert sum(1 for p in out["players"] if p.get("hero")) == 1
def test_hero_inserted_when_missing_from_players(poker):
out = poker.normalize_structured({"hero_pos": "SB", "hero_cards": ["As", "Ad"], "players": []})
assert out["players"] == [{"pos": "SB", "hero": True, "cards": ["As", "Ad"]}]
def test_completeness_full_hand(poker):
c = poker.normalize_structured(_full_hand())["completeness"]
assert c == {"cards": True, "board": True, "actions": True}
def test_idempotent(poker):
once = poker.normalize_structured(_full_hand())
twice = poker.normalize_structured(once)
assert once == twice
def test_store_and_get_roundtrip_is_normalized(poker):
sid = poker.start_session(venue="Meadows", stakes="1/3", buy_in=400)
hid = poker.store_hand_history(_full_hand(), session_id=sid, tag="well_played")
got = poker.get_hand(hid)["structured"]
assert got["schema_version"] == poker.HAND_SCHEMA_VERSION
assert got["board"] == ["7d", "2c", "5h"]
assert got["completeness"]["cards"] is True
def test_list_recent_hands_flags_structured(poker):
sid = poker.start_session(venue="Meadows", stakes="1/3", buy_in=400)
structured_id = poker.store_hand_history(_full_hand(), session_id=sid)
flat_id = poker.log_hand(session_id=sid, position="CO", hole_cards="Jc Jd")
rows = {r["id"]: r for r in poker.list_recent_hands()}
assert rows[structured_id]["has_structured"] is True
assert rows[flat_id]["has_structured"] is False
def test_hud_villains_carry_seat(poker):
"""The recorder auto-places known players, so the HUD bundle must expose their seat."""
poker.start_session(venue="Meadows", stakes="1/3", buy_in=400)
poker.add_read("3-bets light", seat="BTN", name="Sal", category="risky")
villains = {v["name"]: v for v in poker.hud()["villains"]}
assert villains["Sal"]["seat"] == "BTN"
+30
View File
@@ -47,6 +47,36 @@ def test_every_mode_tool_exists(lyra):
assert set(mode.tools) <= set(tools.TOOLS), f"{mode.key} references unknown tools"
def test_set_mode_tool_switches_session(lyra):
memory, _, _, tools = lyra
memory.ensure_session("s1")
out = tools.dispatch("set_mode", {"mode": "decide"}, {"session_id": "s1"})
assert "Decide" in out and memory.get_session_mode("s1") == "decide"
# unknown mode is handled, session unchanged
assert "unknown" in tools.dispatch("set_mode", {"mode": "nope"}, {"session_id": "s1"}).lower()
assert memory.get_session_mode("s1") == "decide"
def test_work_modes_present_and_gated(lyra):
_, _, modes, tools = lyra
# the full set Brian chose
assert set(modes.MODES) == {"conversation", "poker_cash", "build", "explore", "study", "decide"}
# Decide = read-only lookups for context, no live logging; has a real card
decide = _names(tools.specs(modes.DECIDE.tools))
assert {"running_stats", "recent_sessions"} <= decide and "log_hand" not in decide
assert modes.DECIDE.card
# Build/Explore are conversational: base agency tools only, no live poker logging
for key in ("build", "explore"):
names = _names(tools.specs(modes.get(key).tools))
assert {"journal_write", "note", "think_about"} <= names
assert "log_hand" not in names and "start_session" not in names
assert modes.get(key).card # each has a real behavioral card
# Study = read-only review: lookups + equity, but no live logging
study = _names(tools.specs(modes.STUDY.tools))
assert {"running_stats", "analyze_spot", "player_profile"} <= study
assert "log_hand" not in study and "end_session" not in study
def test_mode_resolution_and_persistence(lyra):
memory, _, modes, _ = lyra
assert modes.get(None).key == modes.DEFAULT
+56
View File
@@ -0,0 +1,56 @@
"""Perceive: cheap heuristic read of the moment, and route turning it into a nudge."""
from __future__ import annotations
import importlib
import pytest
from lyra import perceive
def test_reads_tilt():
m = perceive.read("I'm so fucking tilted, card dead all night, this is brutal!!")
assert m["tilt"] >= 0.5 and m["sentiment"] < 0 and m["kind"] == "emotional"
def test_reads_strategy_calm():
m = perceive.read("Should I fold the river here given his range and the board?")
assert m["kind"] == "strategic" and m["tilt"] < 0.4
def test_reads_up_energy():
m = perceive.read("Let's go!! crushing it tonight, feeling so good!")
assert m["sentiment"] > 0 and m["kind"] == "emotional"
def test_reads_build_and_casual():
assert perceive.read("let's refactor the cognition pipeline module").get("kind") == "build"
assert perceive.read("ok sounds good to me").get("kind") == "casual"
assert perceive.read("ok sounds good to me")["tilt"] == 0.0
@pytest.fixture
def mind(tmp_path, monkeypatch):
monkeypatch.setenv("LYRA_DB_PATH", str(tmp_path / "test.db"))
monkeypatch.setenv("CHAT_DELIBERATE", "false")
from lyra import llm
monkeypatch.setattr(llm, "embed", lambda texts: [[0.1, 0.2, 0.3] for _ in texts])
import lyra.memory as memory
importlib.reload(memory)
import lyra.mind as mind
importlib.reload(mind)
memory.ensure_session("s1")
return mind
def test_route_injects_tilt_nudge(mind):
turn = mind.assemble("s1", "ugh I'm steaming, fucking coolered again!!", "cloud", None)
assert turn.register == "steady"
sys_blob = " ".join(m["content"] for m in turn.messages if m["role"] == "system")
assert "on tilt" in sys_blob.lower() or "frustrated" in sys_blob.lower()
def test_route_quiet_on_neutral_turn(mind):
turn = mind.assemble("s1", "what did we decide about the schema yesterday?", "cloud", None)
assert turn.register is None # neutral -> no nudge
assert not (turn.moment or {}).get("note")
+84
View File
@@ -0,0 +1,84 @@
"""Profile derivation: fold only new gists into the existing profile (incremental).
The old pass re-digested all ~851 gists every consolidation; this checks the cheap
delta path fires in steady state and the full rebuild fires only when it should.
"""
from __future__ import annotations
import importlib
import pytest
from lyra.memory import Summary
@pytest.fixture
def prof(monkeypatch):
import lyra.profile as profile
importlib.reload(profile)
return profile
def _wire(profile, monkeypatch, gists, covered, existing):
"""Stub memory + the LLM passes; record which path ran."""
state = {"stored_content": existing, "stored_covered": covered, "calls": []}
monkeypatch.setattr(profile.memory, "list_summaries",
lambda: [Summary(f"s{i}", g, i, "t") for i, g in enumerate(gists)])
monkeypatch.setattr(profile.memory, "get_profile", lambda: state["stored_content"])
monkeypatch.setattr(profile.memory, "profile_sessions_covered", lambda: state["stored_covered"])
def set_profile(content, sessions_covered, profile_id="self"):
state["stored_content"], state["stored_covered"] = content, sessions_covered
monkeypatch.setattr(profile.memory, "set_profile", set_profile)
monkeypatch.setattr(profile, "_map_reduce",
lambda gists, backend: state["calls"].append(("map_reduce", len(gists))) or "facts")
monkeypatch.setattr(profile, "_call",
lambda prompt, body, backend: state["calls"].append(("fold",)) or "folded profile")
return state
def test_no_profile_yet_does_full_rebuild(prof, monkeypatch):
state = _wire(prof, monkeypatch, gists=["a", "b", "c"], covered=0, existing=None)
out = prof.rebuild_profile(backend="local")
assert state["calls"] == [("map_reduce", 3)] # mapped all three gists
assert out == "facts" and state["stored_covered"] == 3
def test_unchanged_skips_entirely(prof, monkeypatch):
state = _wire(prof, monkeypatch, gists=["a", "b"], covered=2, existing="old profile")
out = prof.rebuild_profile(backend="local")
assert state["calls"] == [] # no LLM work at all
assert out == "old profile"
def test_small_delta_folds_only_new(prof, monkeypatch):
state = _wire(prof, monkeypatch, gists=["a", "b", "c", "d"], covered=2, existing="old profile")
out = prof.rebuild_profile(backend="local")
assert state["calls"] == [("map_reduce", 2), ("fold",)] # mapped just the 2 new, then folded
assert out == "folded profile" and state["stored_covered"] == 4
def test_force_does_full_rebuild(prof, monkeypatch):
state = _wire(prof, monkeypatch, gists=["a", "b", "c"], covered=3, existing="old profile")
out = prof.rebuild_profile(backend="local", force=True)
assert state["calls"] == [("map_reduce", 3)] # ignored the up-to-date profile
assert out == "facts"
def test_big_gap_falls_back_to_full_rebuild(prof, monkeypatch):
gists = [str(i) for i in range(40)] # 30 new > FOLD_LIMIT
state = _wire(prof, monkeypatch, gists=gists, covered=10, existing="old profile")
out = prof.rebuild_profile(backend="local")
assert state["calls"] == [("map_reduce", 40)] # full rebuild, not a giant fold
assert out == "facts"
def test_crossing_cadence_forces_full_rebuild(prof, monkeypatch):
# covered=98, total=102 is a tiny delta, but it crosses the 100-session boundary.
gists = [str(i) for i in range(102)]
state = _wire(prof, monkeypatch, gists=gists, covered=98, existing="old profile")
out = prof.rebuild_profile(backend="local")
assert state["calls"] == [("map_reduce", 102)] # anti-drift full rebuild
assert out == "facts"
+40 -1
View File
@@ -52,7 +52,9 @@ def test_reflect_revises_and_records_critique(lyra):
# the REVISED (honest) version won, not the flattering draft
assert state["mood"] == "steady"
assert state["valence"] == 0.6
assert "not sure much actually shifted" in state["self_narrative"].lower()
# reflect() updates mood + noticings, but NOT the standing self_narrative (that's
# consolidated separately now — the fix for the rewrite-the-bio feedback loop)
assert "supportive presence devoted to brian" not in state["self_narrative"].lower()
assert any("not much changed" in r.lower() for r in state["reflections"])
# the self-critique was recorded as metacognition
@@ -76,3 +78,40 @@ def test_reflect_falls_back_to_draft_if_examine_unparseable(lyra, monkeypatch):
# examine failed to parse -> keep the draft, store no metacognition
assert state["mood"] == "inspired"
assert state["metacognition"] == []
def test_consolidation_rebuilds_narrative_from_reflections(lyra, monkeypatch):
from lyra import memory, self_state
st = self_state.load()
st["reflections"] = ["I'm curious about impermanence", "I felt restless tonight",
"I wondered what the quiet is for"]
memory.set_self_state(st)
def comp(messages, backend=None, model=None):
# consolidation should synthesize from anchor + reflections, not the old bio
assert "supportive presence devoted to Brian" not in messages[1]["content"]
return ('{"self_narrative":"I am Lyra, and lately I have been restless and curious '
'about the quiet.","relationship":"Brian and I are steady."}')
monkeypatch.setattr(self_state.llm, "complete", comp)
out = self_state._consolidate_self()
assert "restless and curious" in out["self_narrative"]
assert "steady" in out["relationship"]
def test_reflect_skipped_when_introspection_off(lyra):
calls = lyra
from lyra import self_state
self_state.set_introspection_mode("off")
self_state.reflect()
assert calls == [] # paused -> no draft/examine LLM calls at all
def test_consolidation_skips_with_too_few_reflections(lyra):
from lyra import memory, self_state
st = self_state.load()
st["reflections"] = ["only one so far"]
st["self_narrative"] = "unchanged narrative"
memory.set_self_state(st)
out = self_state._consolidate_self() # <3 reflections -> no rewrite
assert out["self_narrative"] == "unchanged narrative"
+77 -3
View File
@@ -190,6 +190,21 @@ def test_think_about_tool_seeds_a_thread(lyra):
assert chain[0]["kind"] == "question" and chain[0]["source"] == "chat"
def test_thought_response_tool_threads_reply_back(lyra):
_, th, box = lyra
import lyra.tools as tools
importlib.reload(tools)
_gen(box, title="my restlessness", content="is it real?", salience=0.5)
tid = th.think(force_mode="new")["thread_id"]
out = tools.dispatch("thought_response", {"thread_id": tid, "brian_said": "I think it's real"})
assert str(tid) in out
t = th.get_thread(tid)
assert t["last_response"] == "I think it's real" and th._is_pending(t)
# bad id is handled, not crashed
assert "couldn't find" in tools.dispatch("thought_response",
{"thread_id": 9999, "brian_said": "x"})
# --- external feed -------------------------------------------------------
RSS = (b'<?xml version="1.0"?><rss version="2.0"><channel><title>Feed</title>'
@@ -250,6 +265,7 @@ def test_no_ping_without_a_reach_out_message(lyra, monkeypatch):
_, th, box = lyra
monkeypatch.setenv("NTFY_URL", "http://ntfy.test")
monkeypatch.setenv("PING_QUIET_HOURS", "0-0")
monkeypatch.setenv("PING_AUTO_SALIENCE", "1.1") # disable auto-ping to isolate reach_out path
sent = []
monkeypatch.setattr(th.notify, "push", lambda **k: (sent.append(k), True)[1])
# salient thought but she did NOT decide to tell him -> no ping (it's not a broadcast)
@@ -260,10 +276,55 @@ def test_no_ping_without_a_reach_out_message(lyra, monkeypatch):
assert th.think(force_mode="new")["pinged"] is False and sent == []
def test_auto_ping_on_salient_thought(lyra, monkeypatch):
_, th, box = lyra
monkeypatch.setenv("NTFY_URL", "http://ntfy.test")
monkeypatch.setenv("PING_QUIET_HOURS", "0-0")
monkeypatch.setenv("PING_AUTO_SALIENCE", "0.7")
monkeypatch.setenv("PING_COOLDOWN_MIN", "0")
sent = []
monkeypatch.setattr(th.notify, "push", lambda **k: (sent.append(k), True)[1])
monkeypatch.setattr(th, "_compose_reachout", lambda *a, **k: "Hey, been thinking about this.")
_gen(box, content="a genuinely salient thought", salience=0.9) # no explicit reach_out
r = th.think(force_mode="new")
assert r["pinged"] is True and sent and "thinking about" in sent[0]["message"]
def test_no_auto_ping_below_bar(lyra, monkeypatch):
_, th, box = lyra
monkeypatch.setenv("NTFY_URL", "http://ntfy.test")
monkeypatch.setenv("PING_QUIET_HOURS", "0-0")
monkeypatch.setenv("PING_AUTO_SALIENCE", "0.8")
sent = []
monkeypatch.setattr(th.notify, "push", lambda **k: (sent.append(k), True)[1])
_gen(box, content="a quieter musing", salience=0.5) # below auto bar, no reach_out
assert th.think(force_mode="new")["pinged"] is False and sent == []
def test_daily_digest_sends_once_per_day(lyra, monkeypatch):
_, th, box = lyra
monkeypatch.setenv("NTFY_URL", "http://ntfy.test")
monkeypatch.setenv("PING_QUIET_HOURS", "0-0")
monkeypatch.setenv("DIGEST_HOUR", "0") # any time qualifies
monkeypatch.setenv("PING_AUTO_SALIENCE", "1.1") # keep think() from pinging during setup
sent = []
monkeypatch.setattr(th.notify, "push", lambda **k: (sent.append(k), True)[1])
_gen(box, title="thread A", content="a", salience=0.5)
th.think(force_mode="new")
_gen(box, title="thread B", content="b", salience=0.5)
th.think(force_mode="new")
assert th.maybe_daily_digest() is True
assert sent and "thread" in sent[-1]["message"].lower()
sent.clear()
assert th.maybe_daily_digest() is False # already sent today
assert sent == []
def test_ping_salience_floor_is_optional(lyra, monkeypatch):
_, th, _ = lyra
monkeypatch.setenv("NTFY_URL", "http://ntfy.test")
monkeypatch.setenv("PING_QUIET_HOURS", "0-0")
monkeypatch.setenv("PING_COOLDOWN_MIN", "0") # isolate the salience floor from cooldown
sent = []
monkeypatch.setattr(th.notify, "push", lambda **k: (sent.append(k), True)[1])
# default floor 0.0 -> her decision (a message) is enough, any salience pings
@@ -275,10 +336,10 @@ def test_ping_salience_floor_is_optional(lyra, monkeypatch):
assert th.maybe_ping(1, "hey", 0.8) is True
def test_think_routes_to_introspection_backend(lyra, monkeypatch):
def test_think_routes_to_selected_voice(lyra, monkeypatch):
from lyra import self_state
_, th, box = lyra
monkeypatch.setenv("INTROSPECTION_BACKEND", "local")
monkeypatch.setenv("INTROSPECTION_MODEL", "dolphin3:8b")
self_state.set_introspection_mode("dolphin")
seen = {}
def cap(messages, backend="local", model=None):
@@ -290,6 +351,19 @@ def test_think_routes_to_introspection_backend(lyra, monkeypatch):
th.think(force_mode="new")
assert seen["backend"] == "local" and seen["model"] == "dolphin3:8b"
self_state.set_introspection_mode("mi50") # gaming-safe: Qwen-32B on the MI50
th.think(force_mode="new")
assert seen["backend"] == "mi50" and seen["model"] is None
def test_think_skipped_when_introspection_off(lyra):
from lyra import self_state
_, th, box = lyra
self_state.set_introspection_mode("off")
_gen(box, content="should not be generated")
assert th.think(force_mode="new") is None # paused -> no thought, no LLM call
assert th.list_threads() == []
def test_no_ping_without_ntfy(lyra, monkeypatch):
_, th, _ = lyra
+4 -4
View File
@@ -39,8 +39,8 @@ def lyra(tmp_path, monkeypatch):
def test_now_note_first_contact(lyra):
from lyra import chat
note = chat._now_note()["content"]
from lyra import mind
note = mind._now_note()["content"]
assert "current date and time is" in note
assert "first thing Brian has ever said" in note
@@ -48,6 +48,6 @@ def test_now_note_first_contact(lyra):
def test_now_note_reports_gap(lyra):
memory = lyra
memory.remember("s1", "user", "hey")
from lyra import chat
note = chat._now_note()["content"]
from lyra import mind
note = mind._now_note()["content"]
assert "since Brian last spoke with you" in note
+1
View File
@@ -9,6 +9,7 @@ import pytest
@pytest.fixture
def lyra(tmp_path, monkeypatch):
monkeypatch.setenv("LYRA_DB_PATH", str(tmp_path / "test.db"))
monkeypatch.setenv("CHAT_DELIBERATE", "false") # don't make a real LLM call in respond()
from lyra import llm
monkeypatch.setattr(llm, "embed", lambda texts: [[0.1, 0.2, 0.3] for _ in texts])
import lyra.memory as memory