256 lines
9.7 KiB
Markdown
256 lines
9.7 KiB
Markdown
# DivaCode — AI Being Platform Action Plan
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**Language:** Go
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**Inference:** llama.cpp (HTTP server), OpenAI-compatible API planned
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**Inspiration:** OpenHer, Agent Diva, nanobot
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---
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## Current Status (2026-06-10)
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**Builds:** yes
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**Runs:** yes (requires llama.cpp on :8080)
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**Known issues:**
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- Prompt template is raw text — model dumps reasoning/self-correction meta-text instead of just the response
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- No chat template configurability (ChatML, Llama 3 instruct, etc.)
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- TUI is basic (no streaming, no word-wrap polish)
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- Memory store uses keyword `LIKE` search, not real embeddings
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- OpenAI-compatible adapter not yet built
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- Matrix adapter is a stub
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---
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## Architecture Overview
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```
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User
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│
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├── TUI (Bubble Tea)
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└── Matrix (future)
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│
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┌─────┴──────────────────────────────┐
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│ Core Agent Loop │
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│ (internal/agent/) │
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└─────┬──────────────────────────────┘
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│
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┌─────┴──────────────────────────────┐
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│ Companion Layer │
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│ (internal/companion/) │
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│ ├─ Personality (5 bounded traits) │
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│ ├─ Relationship (familiarity,trust)│
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│ ├─ Reflection (diary,observations)│
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│ ├─ Mood (6 states + energy) │
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│ └─ Prompt Composer (dynamic ctx) │
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└─────┬──────────────────────────────┘
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│
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┌─────┴──────────────────────────────┐
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│ Memory Layer │
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│ (internal/memory/) │
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│ ├─ RAG store (keywords → vectors) │
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│ └─ Self-memory (promises,strats) │
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└─────┬──────────────────────────────┘
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│
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┌─────┴──────────────────────────────┐
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│ Inference (internal/llama/) │
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│ ├─ llama.cpp HTTP client │
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│ └─ OpenAI-compatible (planned) │
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└────────────────────────────────────┘
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Skills / Tools:
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├─ web_fetch
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├─ web_search (stub)
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└─ MCP protocol (future)
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```
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---
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## Phase 0 — Foundation & Scaffolding
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**Status: COMPLETE**
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- [x] Go module: `git.db123.ir/db123/divacode`
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- [x] Project structure per Holy Code Bible conventions
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- [x] `internal/config/` — std lib `os.Getenv` only
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- [x] `internal/storage/` — `modernc.org/sqlite` (pure Go, no CGO), auto-creates `data/` dir
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- [x] `internal/llama/client.go` — HTTP client for `POST /completion`, `POST /embedding`, `GET /health`
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- [x] `.env.example`, `Makefile`, `.gitignore`, `Dockerfile`, `docker-compose.yml`
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- [x] `AGENTS.md` with architecture, commands, conventions
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---
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## Phase 1 — Core Agent Loop
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**Status: COMPLETE** (minor issues remain)
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- [x] `internal/agent/agent.go` — message → memory search → prompt → llama → save → respond
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- [x] `internal/agent/scheduler.go` — tick every 15m, check mood/diary/auto-message
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- [x] `cmd/divad/main.go` — wires everything: config, DB, llama, TUI, scheduler, Matrix, API
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- [x] Conversation persistence to SQLite (`conversations`, `messages` tables)
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- [x] Bubble Tea TUI with viewport + input bar
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- [ ] Prompt template is wrong — uses raw headers, no chat format. Model outputs meta-text
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- [ ] No token tracking — context window grows unbounded
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- [ ] TUI doesn't stream tokens (waits for full completion)
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---
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## Phase 2 — Prompt Templating & Format Fix
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**Goal:** Fix the model output. Swap raw prompt text for a configurable chat template so the model only returns the assistant response.
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- [ ] `internal/llama/template.go` — chat template formatter:
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- ChatML (`<|im_start|>system...<|im_end|>`)
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- Llama 3 instruct (`<|begin_of_text|><|start_header_id|>system<|end_header_id|>`)
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- Configurable via env `CHAT_TEMPLATE=chatml` (default)
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- [ ] Refactor `companion/promptbuilder.go` to output structured segments, then let template.go wrap them
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- [ ] Strip system prompt of raw formatting — let the template handle structure
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- [ ] Test: "hi" produces just "Hello!" not paragraphs of self-correction
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---
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## Phase 3 — Long-Term Memory (RAG)
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**Goal:** Embedding-based retrieval so the agent recalls across sessions.
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- [ ] `internal/memory/embed.go` — call llama.cpp `POST /embedding` to get vectors
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- [ ] `internal/memory/store.go` — upgrade `Search()` from keyword `LIKE` to cosine similarity
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- [ ] Store embeddings as BLOB in `memories` table
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- [ ] Temporal decay — older memories scored lower
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- [ ] Importance scoring — "remember this" / emotional content boosts score
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- [ ] **Test:** Store info, restart, ask about stored info → recall
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---
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## Phase 4 — OpenAI-Compatible Adapter
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**Goal:** Swap inference to any OpenAI-compatible API (OpenAI, vLLM, Ollama, etc.).
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- [ ] `internal/llama/provider.go` — interface:
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```go
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type Provider interface {
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Complete(ctx, *Request) (*Response, error)
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Embed(ctx, string) ([]float64, error)
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Health() error
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}
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```
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- [ ] Rename `internal/llama/` → `internal/inference/`
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- [ ] `llama.go` — implements Provider (existing code)
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- [ ] `openai.go` — implements Provider via OpenAI-compatible REST API
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- [ ] Config: `INFERENCE_PROVIDER=llama|openai`, `OPENAI_API_KEY`, `OPENAI_BASE_URL`
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- [ ] **Test:** Both providers produce same interface, switchable via env
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---
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## Phase 5 — Episodic Diary & Reflection
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**Status: CODE DONE** — needs integration into the scheduled pipeline.
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- [x] `internal/companion/reflection.go` — `GenerateDiary`, `RecentObservations`, `AddObservation`
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- [x] `diary_entries` table with date, summary, mood, topics, observations
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- [x] `observations` table with confidence, category, applied flag
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- [ ] Connect scheduler's diary trigger to actual LLM-generated summaries (currently writes stub text)
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- [ ] Reflection → Personality update pipeline:
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- Observations accumulate → periodic analysis → bounded trait drift
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- Max 0.5% change/day, max 5%/month
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---
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## Phase 6 — MCP Tools & Integrations
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**Status: PARTIAL**
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- [x] `internal/tools/registry.go` — register/list/execute tools
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- [x] `internal/tools/builtin.go` — `web_fetch`, `web_search` (stub)
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- [ ] MCP protocol client (`internal/tools/mcp.go`) — stdio/TCP, list tools, execute, parse results
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- [ ] Tool call loop in agent: LLM decides → agent executes → result appended → LLM finalizes
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- [ ] Plugins: Obsidian vault, Gitea, Actual Budget
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---
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## Phase 7 — Matrix Integration
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**Status: STUB**
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- [x] `internal/channel/matrix.go` — config + start stub
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- [ ] Full Matrix bot with `mautrix-go`:
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- Listen for invitations, join rooms
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- Handle DMs with typing indicators
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- Bot identity: `@diva:homeserver.tld`
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- [ ] Sync TUI and Matrix state
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- [ ] **Test:** Send DM, verify response, verify cross-session memory
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---
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## Phase 8 — Self-Memory & Identity
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**Status: CODE DONE**
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- [x] `internal/memory/self_memory.go` — promises, strategies
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- [x] `agent_promises` table (id, promise, context, fulfilled, deadline)
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- [x] `agent_strategies` table (id, situation, strategy, outcome)
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- [ ] Wire into Prompt Composer: "You promised to X" context
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- [ ] **Test:** "What did you promise me?" → recall
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---
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## Phase 9 — Safety Guardrails & Identity Stability
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**Goal:** Prevent personality drift, maintain core safety.
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- [ ] `internal/companion/safety.go` — core identity (stable) vs state (dynamic)
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- [ ] Personality safety: bounded traits, safety overrides personality, no tool access changes
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- [ ] Prompt injection protection: user input wrapped in delimiters, strict template sections
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---
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## Phase 10 — Polish: Streaming TUI, Token Tracking, Observability
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**Goal:** Production-quality UX.
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- [ ] Token streaming in TUI (char-by-char from llama.cpp SSE or chunked response)
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- [ ] Context window manager — track tokens, sliding window when full, auto-summarize old messages
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- [ ] `POST /v1/chat` streaming via SSE in API mode
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- [ ] Prometheus metrics (`GET /metrics`)
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- [ ] Graceful shutdown — drain in-flight requests, save state
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---
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## Phase 11 — Future Enhancements (Optional)
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- [ ] Voice: whisper.cpp (STT) + piper/XTTS (TTS)
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- [ ] VRM/Live2D avatar rendering
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- [ ] Multi-user with per-user relationship tracking
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- [ ] Multi-room Matrix
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- [ ] Plugin system
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- [ ] WebUI dashboard
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- [ ] Home Assistant integration
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---
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## Database Schema (15 tables across 2 DBs)
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`divacode.db`:
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- `conversations`, `messages`, `context_state`, `memories`
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`companion.db`:
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- `personality_traits`, `relationship_metrics`, `shared_topics`, `inside_jokes`
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- `diary_entries`, `observations`
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- `agent_promises`, `agent_strategies`
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---
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## Key Principles
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1. **Smallest loop first** — get message → memory → llm → response working before adding complexity
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2. **Personality is data, not prompt text** — traits in SQLite, composed dynamically
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3. **Memory ≠ Personality** — factual memory separate from relationship/emotional state
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4. **Slow evolution** — max 0.5% trait change/day, 5%/month
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5. **Core Identity stable** — never allow personality to override safety rules
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6. **Diary before reflection** — nightly diary is the emotional continuity layer
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7. **Autonomous messaging** — scheduler makes it feel alive, not the LLM
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8. **No config libs** — std lib `os.Getenv` only
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9. **No HTTP routers** — std lib `net/http` only
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10. **Error wrapping** — `fmt.Errorf("context: %w", err)`, never discard
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