ForeSight

A temporal-aspect long-term memory plugin for DeepSeek Harness (dsh).

Every memory carries explicit temporal semantics — a linguistic aspect (进行体 / 完成体 / 未然体 / 恒常体) paired with an anchor (time point / interval / open / none). The framework executes lifecycle mechanically: decay on anchor expiry, TTL fallback, renewal nudge, prospective review, prediction verification, and conflict resolution by evidence with a single conservative/aggressive knob (β).

Unlike chat vendors' rolling memories, ForeSight treats memory as scheduled first-class data: expiration, injection eligibility, retrieval weighting and contradiction resolution all derive from one structured policy file (policy.yaml) — zero hardcoded behavior.

Why it exists

Long-term memory is a data-management problem, not a prompt-engineering one. ForeSight applies the two axes that matter:

Axis	Values	What it controls
体 (aspect)	progressive / perfect / prospective / gnomic	lifecycle: expires, permanent, to-verify, never-injected
锚定 (anchor)	none / point / interval / open	when the statement is true (valid time)

Requirements

• Node.js ≥ 20
• DeepSeek Harness (dsh) with the cordis plugin system
• An embedding backend (default: Ollama with nomic-embed-text-v2-moe, 768-dim)
• (Optional) An LLM API for classification/derivation (default: DeepSeek compatible API; rules-based fallbacks exist)

Installation (dsh profile)

# in your ~/.dsh/profiles/<name>/
pnpm add @foresight/memory

Then add the plugin to your profile's bundle list and wire it in a patch:

# cordis.patch.yml (profile-level)
- id: foresight-core
  config:
    memoryRoot: '<your data directory>'   # e.g. /home/you/.config/foresight
    dbFile: 'foresight.db'
    embedBaseUrl: 'http://localhost:11434'
    embedModel: 'nomic-embed-text-v2-moe'

Configuration — where does my data go?

Your data lives OUTSIDE the repo, in your own data directory. The plugin never ships any user data; the repository is pure code + templates.

Data directory layout

<memoryRoot>/
├── SOUL.md          # personality (copy from templates/SOUL.md.example)
├── user.md          # user profile (copy from templates/user.md.example)
├── policy.yaml      # all tunables (copy from templates/policy.yaml.example)
└── foresight.db     # SQLite store (created automatically)

On first run the plugin expects the three text files to exist. The plugin creates the directory if needed but does not silently write policy — copy the templates, then adjust:

mkdir -p ~/.config/foresight
cp templates/SOUL.md.example  ~/.config/foresight/SOUL.md
cp templates/user.md.example  ~/.config/foresight/user.md
cp templates/policy.yaml.example ~/.config/foresight/policy.yaml

Resolution chain

explicit options (adapter) → environment variables → policy.yaml → defaults

Setting	Env var	Default
data directory	FORESIGHT_MEMORY_DIR	%APPDATA%/foresight (win) / ~/.local/share/foresight (unix)
db file	FORESIGHT_DB_FILE	foresight.db
embed URL	FORESIGHT_EMBED_URL	http://localhost:11434
embed model	FORESIGHT_EMBED_MODEL	nomic-embed-text-v2-moe
LLM base URL	FORESIGHT_LLM_BASE_URL	https://api.deepseek.com/v1
LLM model	FORESIGHT_LLM_MODEL	deepseek-v4-flash

Policy file

policy.yaml is the single source of truth for behavior: permission matrix, aspect registry (TTL, dwell, injection mode), gate categories, activation β and decay constants, retrieval factor weights, injection budgets, nudge cadence, server port/token. You decide your assistant's personality, profile, and memory policy — none of it is baked into the code.

Layout

src/
├── types.ts            # domain types (aspect×anchor)
├── defaults.ts         # the ONLY place default values live
├── config.ts           # resolution chain + data dir bootstrap
├── policy.ts           # policy.yaml loader + behavior lookup
├── schema.ts           # SQLite DDL + migration + sqlite-vec
├── store.ts            # CRUD, soft-delete, vectors, FTS, audit
├── gate/               # write gate: classify + validate (aspect-text)
├── govern/             # permission model
├── evolve/             # temporal expiry/TTL, activation, β conflict
├── retrieve/           # composable scoring factors + search (3 shapes)
└── store/embed.ts      # embed provider interface (Ollama default)

Verification

pnpm install
pnpm build     # tsc
pnpm test      # node --test tests/ — no external services required

All tests run against an in-memory/temp store and a fake embedder — the suite passes on a clean machine with no Ollama, no API key, and no data directory.

License

MIT