๐ง Eling
Lightweight memory, powerful retrieval โ 6-tier second brain for AI agents
Blackbox flight recorder ยท HRR reasoning ยท 4 MCP servers (62 tools) ยท Obsidian local vault Layer 6 ยท Continuum Layer 8 multi-agent orchestration hub ยท temporal queries ยท per-fact versioning ยท vector search ยท Zettelkasten linking ยท memory evolution ยท spec-kit verification ยท conditional + universal verify-on-stop ยท ELING_HOME override ยท handshake agent auto-attribution ยท full-page retrieval (eling_get_page_full) ยท FactMemoryProvider
"Eling" (Javanese): to remember, to be conscious, to be aware
โจ What is Eling?
Eling is a lightweight, unified second brain for AI agents. It merges 6 memory tiers via four MCP servers โ and adds a Continuum Layer 8 orchestration tier that turns eling into a shared hub for multiple AI coding agents. The Blackbox Layer 2 flight recorder captures all agent telemetry (file reads, edits, shell commands, tool calls) and scores them with 11 context-efficiency metrics โ turning raw observability into actionable optimization suggestions. The Obsidian Layer 6 gives agents local Markdown vault access โ scoped project notes, daily logs, research notebooks, and memory review as plain files. No external databases, no cloud services needed for local operation (though it optionally syncs to Notion for online sharing and to Continuum for multi-agent orchestration).
Think of it as one memory stack that serves both the agent and the human โ and one orchestration hub that serves every agent you run, with a flight recorder that watches everything they do:
๐ก Layer 8: CONTINUUM โ multi-agent orchestration hub (shared continuum.db, 15 continuum_* tools)
๐ง Layer 7: NOTION โ online brain, persistent, human-readable (optional)
๐ Layer 6: OBSIDIAN โ local Markdown vault, project notes, daily logs, research (optional)
๐ Layer 5: KB โ FTS5 knowledge corpus for long-form knowledge
๐ธ๏ธ Layer 4: CODE โ codegraph symbol intelligence
๐ Layer 3: FACTS โ SQLite + HRR + BM25 hybrid with trust scoring
๐ Layer 2: BLACKBOX โ flight recorder + telemetry + 11-metric efficiency scoring
โก Layer 1: BUILTIN โ MEMORY.md / USER.md (always-on, zero setup)
How the tiers work together
| Tier | What it stores | How it's queried | Persistence |
|---|---|---|---|
| ๐ก Continuum | Dispatch registry, agent knowledge, PLOT protocol | continuum_* MCP tools |
continuum.db โ shared across agents |
| ๐ง Notion | Permanent pages, project plans, vault entries | eling_reflect promotes facts; eling_sync push syncs |
Cloud โ human-viewable, survives everything |
| ๐ Obsidian | Local Markdown notes, daily logs, research, memory review | brain_obsidian_* MCP tools |
Local filesystem โ human-readable, Git-friendly |
| ๐ KB | Articles, docs, long-form knowledge chunks | FTS5 full-text search | Local SQLite โ persistent |
| ๐ธ๏ธ Code | Function symbols, imports, class hierarchies | Codegraph traversal | Local SQLite โ auto-indexed |
| ๐ Facts | Short facts, preferences, observations | HRR + BM25 + trigram hybrid with trust scores | Local SQLite โ append-only, versioned |
| ๐ Blackbox | Agent telemetry events, efficiency scores, baselines | blackbox_* MCP tools (watch/ingest/score) |
Local SQLite โ auto-recorded |
| โก Builtin | Agent identity, user profile, conventions | Always in prompt context (MEMORY.md / USER.md) | Flat files |
๐ง Notion as Online Memory (Layer 7)
Tier 7 (Notion) is what makes eling human-readable. While tiers 1โ6 live locally as SQLite databases or flat files, Tier 7 optionally syncs high-trust facts to your Notion vault as permanent, well-formatted pages:
eling_reflect <fact_id>โ promote a high-trust fact to a Notion pageeling_sync --direction pushโ batch-sync all high-trust facts to Notioneling_sync --direction pullโ pull Notion pages back into the knowledge baseeling_sync --direction allโ bidirectional sync
This gives you a recoverable brain: even if your local SQLite databases are lost, your Notion vault retains the curated facts and permanent knowledge. The opinionated vault structure keeps the main page as a clean index of credential children, with all log entries auto-routed to a dedicated child page.
๐ Quick Start
pip install eling
# Run the Notion-only MCP server (online/remote memory, 6 tools)
python3 -m eling mcp
# Run the local-layers MCP server (facts, KB, code, builtin, Blackbox, Obsidian, HRR โ 38 tools)
python3 -m eling.as_brain.mcp_server
# or
eling as-brain
# Run the Blackbox flight recorder MCP (telemetry, scoring, baselines โ 16 blackbox_* tools)
python3 -m eling blackbox mcp
# Run the Continuum Layer 8 orchestration hub (multi-agent, 15 continuum_* tools)
python3 -m eling continuum mcp
# or
eling-continuum
# Use the CLI
python3 -m eling --help
# If using OpenCode, install the lifecycle plugin:
eling-install-opencode
๐ Agent Integration
| Agent | Integration | Status |
|---|---|---|
| Hermes | MCP (Notion eling + local as_brain + Blackbox blackbox + Continuum continuum) + Memory Provider + Plugin |
โ Tested |
| OpenCode | MCP (all 3 servers) + Lifecycle Plugin | โ Tested |
| MiMo-Code | MCP (all 3 servers, OpenCode fork) | โ Tested |
| Zero | MCP (all 3 servers) + Hooks + Skill | โ Bundled installer |
| Claude Code | MCP (all 3 servers via mcpServers) |
โ Wiring provided |
| Codex | MCP (all 3 servers via mcp_servers) |
โ Wiring provided |
One shared hub for every agent (Continuum Layer 8)
Continuum turns eling into a single MCP hub that all your coding agents connect to. Each agent gets isolated git worktrees, a shared orchestration registry, and two-tier knowledge (fundamental = binding rules, situational = semantic search) โ all routed through eling's memory. Every entry is auto-attributed by the agent's MCP handshake name, so you always know which agent wrote what.
Wire all six agents in one command (Hermes, OpenCode, MiMo-Code, Zero, Claude Code, Codex):
# from the eling repo
chmod +x continuum/install.sh
continuum/install.sh --eling-home /shared/eling # shared store for all agents
continuum/healthcheck.sh --eling-home /shared/eling # verify every agent is wired
Per-agent configs live in continuum/configs/; uninstall with continuum/uninstall.sh.
See continuum/README.md for the full guide.
Non-tested agents connect via the stdio MCP servers โ any MCP-compatible host can use
eling (notion-only, 6 tools), as_brain (local layers, 33 tools), blackbox
(flight recorder, 16 blackbox_* tools), and continuum (orchestration hub, 15 continuum_* tools).
๐ Blackbox Flight Recorder (Layer 2)
Blackbox is eling's observability layer โ a real-time flight recorder that captures everything your agents do and scores their efficiency. Think of it as a black-box data recorder for AI agents: it logs every tool call, file read, file edit, shell command, and subagent spawn, then runs 11 context-efficiency metrics on the collected data.
16 MCP tools for telemetry capture and analysis:
| Tool | Purpose |
|---|---|
blackbox_watch_start / stop |
Watch a Zero stream-JSON session in real-time |
blackbox_ingest |
Ingest telemetry events directly |
blackbox_ingest_zero_jsonl |
Import Zero stream-JSON log files |
blackbox_ingest_hermes_session |
Import a Hermes session from the state DB |
blackbox_runs_list / run_get |
List and inspect recorded runs |
blackbox_stats |
Aggregate statistics across runs |
blackbox_run_score |
11-metric efficiency scoring |
blackbox_run_effectiveness |
Outcome scoring (did the task land?) |
blackbox_run_timeline |
Compact causal timeline of actions |
blackbox_run_suggest |
Optimization suggestions based on scores |
blackbox_run_handoff |
Export run summary for another agent |
blackbox_baselines_get |
Per-archetype baseline comparison |
11 efficiency metrics (ported from Agent-Blackbox by Taewoo Park):
| Metric | What it measures |
|---|---|
| Redundant reads | Files read twice without changes between |
| Cache hit ratio | Terminal output reuse vs. re-execution |
| Read amplification | Lines read per line written |
| Retry waste | Bash/compile failures retried |
| Yield density | Edits per tool call |
| Token efficiency | Total tokens used |
| Edit efficiency | Edits per file open |
| Test success | Passes per test run |
| Commit frequency | Commits per hour |
| Context window utilization | Proportion of context actually used |
| Subagent overhead | Orchestration cost of subagents |
Agent support:
- Zero โ auto-captures telemetry via the eling hook plugin; watch live streams with
blackbox_watch_start - Hermes โ import past sessions with
blackbox_ingest_hermes_session; live capture via as_brain MCP - Any MCP agent โ ingest events directly via
blackbox_ingest
The Blackbox recorder feeds its findings into the Facts layer (Layer 3) for persistent causal memory, and baselines are stored per project across runs so you can track agent efficiency over time.
Hermes
Eling plugs into Hermes Agent at 3 levels:
1. MCP Server โ add to ~/.hermes/config.yaml:
mcp_servers:
eling:
command: python3
args: ["-m", "eling.mcp_server"]
enabled: true
2. Memory Provider โ sets default brain for remember/recall:
memory:
provider: eling
3. Plugin โ registers eling_remember + eling_recall as quick tools:
plugins:
enabled:
- eling
eling:
home: /root/.eling
OpenCode
Eling provides an OpenCode lifecycle plugin that auto-writes session memory:
# After installing eling, run this to install the plugin:
eling-install-opencode
# Or:
python3 -m eling install-opencode
This copies eling-memory.js to OpenCode's plugin directory and registers it in opencode.jsonc. The plugin hooks into:
chat.messageโ stores user prompts as factstool.execute.afterโ stores tool observations as factsevent(session.idle / session.compacted) โ pushes high-trust facts to Notion
The eling MCP server should also be configured in OpenCode (opencode.jsonc):
"mcp": {
"eling": {
"type": "local",
"command": ["python3", "-m", "eling.mcp_server"],
"enabled": true
}
}
Zero
Eling provides a one-command installer for Zero terminal agent โ hooks + skill + MCP in one go:
# After installing eling:
eling-install-zero
# Or:
python3 -m eling install-zero
# Preview without changes:
python3 -m eling install-zero --dry-run
This sets up:
| Component | What it does |
|---|---|
| MCP Server | Adds eling to Zero's config.json โ all 22 tools available |
| Hooks (4) | Registers lifecycle hooks for auto-memory |
| Skill | Installs a SKILL.md that teaches Zero about eling's tools |
Hook mapping
| Zero Event | Eling action |
|---|---|
sessionStart |
Warm caches, log session info |
beforeTool |
Recall relevant context for the tool |
afterTool |
Store file edits + tool results as facts |
sessionEnd |
Flush memory to disk, push to Notion |
Manual config
If you prefer to wire it up yourself, add the MCP server to Zero's ~/.config/zero/config.json:
"mcp": {
"eling": {
"command": "python3",
"args": ["-m", "eling.mcp_server"]
}
}
๐ CLI Commands
python3 -m eling remember "I learned that..."
python3 -m eling recall "what did I learn about X"
python3 -m eling probe "X"
python3 -m eling reason ["X", "Y"]
python3 -m eling reflect 1 # promote fact_id 1 to Notion
python3 -m eling verify # query verification status
python3 -m eling verify-spec # run spec-kit conformance
# Memory version control
python3 -m eling snapshot --reason "pre_evolution" # snapshot facts DB
python3 -m eling list-snapshots # list all snapshots
python3 -m eling rollback <snapshot_id> # restore to snapshot
# Zettelkasten linking + evolution
python3 -m eling link-stats # link graph stats
python3 -m eling linked-facts 1 # facts linked to fact_id 1
python3 -m eling evolve # merge near-duplicate facts
python3 -m eling stats
python3 -m eling export --format markdown
python3 -m eling sync --direction push # facts โ Notion
# Agent integration
python3 -m eling install-opencode # install OpenCode lifecycle plugin
python3 -m eling install-zero # install Zero hooks + skill + MCP
python3 -m eling init-rules # write steering rules for AI agents
# Temporal search (v0.6.0)
python3 -m eling search-temporal "last 3 days" --category testing
python3 -m eling search-temporal "kemarin" # Indonesian language support
# Per-fact versioning (v0.6.0)
python3 -m eling versioned-update 1 "Updated content" --reason "correction"
python3 -m eling version-history 1
python3 -m eling undo-to-version 1 --version-id 0
python3 -m eling versioning-stats
๐ Notion Setup (Tier 5)
Optional โ skip this if you only need local memory.
-
Create a Notion integration at https://www.notion.so/my-integrations
- Give it a name (e.g. "Eling Brain")
- Copy the Internal Integration Secret (starts with
ntn_)
-
Share a parent page with your integration
- Open the page you want as your second brain root
- Click Share โ Invite โ select your integration
- Copy the page URL and extract the page ID (the UUID in the URL, e.g.
38f7b66e-c7e0-813f-85b0-d37cef59c1f7)
-
Set environment variables:
export NOTION_API_KEY="ntn_..."
export NOTION_PARENT_PAGE_ID="38f7b66e-c7e0-813f-85b0-d37cef59c1f7"
Note-taking behavior
Once configured, eling auto-creates a ๐ Task Logs child page under your parent on first use:
๐ Hermes Vault (parent page โ your configured root)
โโโ ๐ Task Logs โ auto-created by eling
โ โโโ ๐ก Eling test โ child pages from eling_reflect / remember(layer="notion")
โ โโโ ๐ก Another note
โโโ ๐ API Keys...
โโโ ...
Two ways to add notes to Notion:
| Method | Usage | Route |
|---|---|---|
brain.reflect(fact_id) / eling_reflect |
Promote a high-trust fact to Notion | โ auto-routes by category |
brain.remember("text", layer="notion") / eling_remember with layer=notion |
Store content directly as a Notion page | โ auto-routes by category |
Auto-routing by category
Content is automatically detected and routed to the right child page:
| Category | Triggers | Child page |
|---|---|---|
project_summary |
"project done/complete/selesai", "deploy success", "summary completion" | ๐ฏ Project Summaries |
credential |
"api_key", "password", "secret", "token", "credential" | ๐ Credentials |
address |
"alamat", "address", "domicile", "tinggal di" | ๐ Addresses |
config |
"config", "setup", "setting", "environment" | โ๏ธ Configurations |
| (uncategorised) | Everything else | ๐ Task Logs |
Example:
# Auto-routes to ๐ฏ Project Summaries
b.remember("Project done, deployed to production", layer="notion")
# Auto-routes to ๐ Credentials
b.remember("DATABASE_URL = postgres://...", layer="notion")
# Auto-routes to ๐ Task Logs (no pattern match)
b.remember("General note", layer="notion")
All child pages under these category pages are full Notion pages โ you can edit, move, share, or reference them normally.
Or pass them explicitly in code:
from eling.brain import Brain
b = Brain(
notion_api_key="ntn_...",
notion_parent_id="38f7b66e-..."
)
result = b.reflect(fact_id=1)
print(result) # {"page_id": "...", "promoted": True}
# Or store directly as a note
result = b.remember("Quick note for Notion", layer="notion")
print(result) # {"layer": "notion", "page_id": "...", ...}
Note:
eling_reflectandremember(layer="notion")check availability at call time and return a clear error if any config is missing โ no silent failures.
๐ Temporal Search & Per-Fact Versioning (v0.6.0)
Eling v0.6.0 introduces time-aware fact retrieval and append-only per-fact versioning โ never lose a piece of knowledge again.
Temporal Search
Query facts by time range using natural language โ English or Indonesian:
python3 -m eling search-temporal "last 3 days"
python3 -m eling search-temporal "this week"
python3 -m eling search-temporal "kemarin" # Indonesian: yesterday
python3 -m eling search-temporal "hari ini" # today
Supported patterns:
| Language | Examples |
|---|---|
| ๐ฌ๐ง English | today, yesterday, this week, last month, last 3 days, last 7 days, last 30 days |
| ๐ฎ๐ฉ Indonesian | hari ini, kemarin, minggu ini, bulan lalu, 3 hari terakhir, 7 hari terakhir, 30 hari terakhir |
Python API:
from eling.brain import Brain
b = Brain()
# Temporal search - English
results = b.search_temporal("last 3 days", category="testing")
# Indonesian
results = b.search_temporal("kemarin")
# All facts in a time window
results = b.search_temporal("", since_days=7)
Per-Fact Versioning
Every fact update is append-only โ old versions are preserved in a fact_versions table:
# Update a fact โ previous content is versioned
result = b.versioned_update(1, "Newer content", reason="corrected typo")
# โ {"fact_id": 1, "version_id": 2, "previous": "Old content", "new": "Newer content"}
# Get version history
history = b.get_version_history(1)
# โ [{"version_id": 0, "content": "Original...", "changed_at": "...", "reason": "initial"},
# {"version_id": 1, "content": "Updated...", "changed_at": "...", "reason": "corrected typo"}]
# Undo to a specific version (also versioned!)
result = b.undo_to_version(1, version_id=0)
# โ {"fact_id": 1, "version_id": 3, "restored_from": 0}
# Versioning stats
stats = b.versioning_stats()
# โ {"versioned_facts": 42, "total_versions": 156, "version_operations": 114}
Available as MCP tools: eling_versioned_update, eling_get_version_history, eling_undo_to_version, eling_versioning_stats.
๐ง Memory Version Control
Eling provides Git-like snapshot and rollback for your facts database:
# Before destructive ops, create a snapshot
python3 -m eling snapshot --reason "pre_evolution"
# List available snapshots
python3 -m eling list-snapshots
# Rollback to a previous state (auto-backups current DB first)
python3 -m eling rollback 20260703-120000-123
Snapshots are file-level copies managed via snapshot.py. Available as MCP tools: eling_snapshot, eling_list_snapshots, eling_rollback.
๐ฏ Steering Rules
Teach your AI agent when to use eling's MCP tools. Auto-detects Cursor, Claude Code, OpenCode, Kiro, and Gemini:
cd your-project
python3 -m eling init-rules
This writes:
- Cursor:
.cursor/rules/eling-memory-*.mdc - Claude Code:
.claude/rules/eling-memory-*.md - OpenCode: Appends to
AGENTS.md - Generic:
ELING_MEMORY.mdin project root
Rules cover: when to store/retrieve memories, session lifecycle, and memory hygiene.
๐ Vector Embeddings
Optional semantic search via sentence-transformers:
pip install eling[embeddings]
# or
pip install eling[all]
Enable when creating a Brain or set ELING_EMBEDDING_MODEL:
from eling.brain import Brain
b = Brain(embedding_model="all-MiniLM-L6-v2")
Hybrid search ranking: BM25 + Jaccard + HRR + cosine similarity from embeddings. Stored in a separate fact_embeddings table.
๐ก๏ธ Verify-on-Stop (Conditional + Universal)
Eling provides verify-on-stop nudges for AI agents that lack built-in
verification (e.g., OpenCode, OpenClaw, Cursor, Windsurf). When running under
Hermes, this feature automatically skips โ because Hermes already has its
own agent/verification_stop.py.
Universal mode โ one shared brain for every agent
The as_brain MCP server can act as a universal brain for all connected
agents at once. Set ELING_VERIFY_ALL_AGENTS=1 to force eling's
verify-on-stop to stay active for every agent โ including Hermes โ so the
shared brain provides verification regardless of harness. The default
(unset) keeps the original behaviour: Hermes skips eling's nudges and relies
on its own built-in verification.
# Run the shared brain with verification for ALL agents
ELING_VERIFY_ALL_AGENTS=1 python3 -m eling.as_brain.mcp_server
This powers multi-agent setups (e.g. Hermes + OpenCode + Zero sharing one
as_brain instance) where you want a single source of truth for
verification evidence.
How it works
- Auto-detection โ Eling detects the host agent from the MCP client's
initializehandshake (clientInfo.name), which is more reliable than environment variable heuristics (prevents false Hermes detection when OpenCode runs under Hermes) - Agent auto-attribution โ The handshake client name becomes the default
sourceforbrain_remember, so each agent's memories are tagged with its own identity without manual configuration (override with an explicitsourceargument) - File edit tracking โ When code files are edited via hooks or MCP tools, eling records them in a verification ledger
- Spec-kit conformance โ If the project has spec-kit artifacts
(
specs/*/spec.md), eling checks whether code changes cover each spec requirement and includes gaps in the nudge - Verification nudge โ If code was edited but no passing tests/verification
was recorded, eling produces a
[System: ...]nudge message - Recording โ Agents can call
brain_verifyMCP tool (as_brain server) to record verification results (passed,failed,skipped)
Spec-kit Verification
Projects using spec-kit (Spec-Driven Development) get automatic spec conformance checking:
- Eling detects
specs/<feature>/spec.md,plan.md, andtasks.mdartifacts - Requirements are extracted from spec markdown and matched against code files
- The
eling_verify_spectool returns coverage stats + uncovered requirements - The standard
eling_verifytool includes spec-kit results whenspec_check=true - Uncovered requirements are listed in the verification nudge for the agent to address
Usage via MCP
// Query current status
{ "method": "tools/call", "params": { "name": "eling_verify", "arguments": {} } }
// Record a passing verification
{ "method": "tools/call", "params": {
"name": "eling_verify",
"arguments": { "status": "passed", "command": "pytest", "output": "364 passed" }
} }
// Run spec-kit conformance check
{ "method": "tools/call", "params": {
"name": "eling_verify_spec",
"arguments": { "changed_files": ["src/main.py"] }
} }
// Combine both: verify + spec-kit
{ "method": "tools/call", "params": {
"name": "eling_verify",
"arguments": { "spec_check": true }
} }
Config
| Key | Default | Env | Description |
|---|---|---|---|
verify_on_stop |
true |
ELING_VERIFY_ON_STOP |
Enable nudges for non-Hermes agents |
verify_on_stop_max_attempts |
2 |
ELING_VERIFY_MAX_ATTEMPTS |
Max nudges per session |
adapter |
hermes |
ELING_ADAPTER |
Force adapter type |
home |
$HERMES_HOME/eling |
ELING_HOME |
Data directory for the universal brain (as_brain server) |
verify_all_agents |
false |
ELING_VERIFY_ALL_AGENTS |
Universal mode: provide verify-on-stop for ALL agents incl. Hermes |
plugins:
eling:
adapter: auto # auto-detect from env
verify_on_stop: true
๐๏ธ Architecture
eling/
โโโ mcp_server.py โ JSON-RPC stdio server (Notion-only, 5 tools: eling_*)
โโโ as_brain/
โ โโโ mcp_server.py โ JSON-RPC stdio server (local brain + Blackbox, 33 tools)
โโโ blackbox/ โ Layer 2: Flight recorder & telemetry
โ โโโ core.py โ TraceEvent, RunSummary, AgentMetadata
โ โโโ store.py โ SQLite-backed event store
โ โโโ score.py โ 11-metric efficiency scoring engine
โ โโโ effectiveness.py โ Outcome scoring
โ โโโ timeline.py โ Causal timeline builder
โ โโโ mcp_server.py โ 16 blackbox_* MCP tools
โ โโโ cli.py โ Blackbox CLI subcommands
โ โโโ adapters/
โ โโโ zero.py โ Zero stream-JSON adapter + plugin
โ โโโ hermes.py โ Hermes session DB adapter
โโโ continuum/ โ Layer 8: Multi-agent orchestration hub
โ โโโ mcp_server.py โ JSON-RPC stdio server (15 continuum_* tools)
โ โโโ store.py โ continuum.db: projects, agents, knowledge, plot, reservations
โ โโโ worktree.py โ Isolated per-agent git worktree manager
โ โโโ plot.py โ PLOT.md canonical protocol (unified-diff mutations)
โ โโโ continuum.sh โ Shared wrapper exec'd by every agent's MCP config
โโโ brain.py โ Orchestrator: routing + RRF fusion + sync + snapshot
โโโ config.py โ Layered config: env โ json โ defaults
โโโ hooks.py โ 15 lifecycle hooks + HookRegistry
โโโ verify_on_stop.py โ Verification ledger + nudge builder + spec-kit wiring
โโโ spec_kit.py โ Spec-kit artifact parser + coverage analyzer
โโโ snapshot.py โ Git-like snapshot & rollback for facts DB
โโโ rules.py โ Steering rules generator (Cursor, Claude Code, OpenCode)
โโโ privacy.py โ PII/secret stripping (19 patterns)
โโโ compress.py โ SHA-256 dedup + length compression
โโโ cli.py โ `eling` CLI (18 subcommands, includes blackbox dispatch)
โโโ fact_memory_provider.py โ Standalone facts layer provider (no Brain)
โโโ opencode_plugin/ โ Bundled OpenCode lifecycle plugin
โ โโโ eling-memory.js
โโโ layers/
โโโ builtin.py โ Layer 1: MEMORY.md / USER.md loader
โโโ facts.py โ Layer 3: SQLite + HRR + BM25 + Embeddings + Trust + Zettelkasten + Temporal + Versioning
โโโ embeddings.py โ Optional vector embeddings (Mistral API + sentence-transformers)
โโโ hrr.py โ Holographic Reduced Representations (numpy)
โโโ code.py โ Layer 4: CodeLayer wrapper
โโโ code_index.py โ Pure-Python AST+regex code indexer
โโโ kb.py โ Layer 5: FTS5 + porter + trigram + RRF
โโโ notion.py โ Layer 7: httpx Notion API client
โโโ obsidian.py โ Layer 6: local Markdown vault client
โก Performance
- Lazy imports โ numpy and httpx are imported only when their layer is first used, not at module load time
import elingtakes ~1.3s (was ~4.5s with module-level imports on Alpine)- Pure-Python fallback when numpy unavailable (BM25-only retrieval still works)
๐ Documentation
๐ค Credits
See CREDITS.md for full attribution โ Hermes Agent (Nous Research),
Agent-Blackbox / Taewoo Park, Continuum / Pouya Hasanamreji, spec-kit (GitHub),
dusterbloom's holographic plugin, and all other contributors.
๐ License
MIT ยฉ 2026 PatrickNoFilter
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