Llmem Setup

LLMem Setup

Install, configure, and integrate LLMem into an agent's harness so it can use structured memory.

When to Run

• Setting up memory for a new agent
• Adding memory to an existing agent harness
• After cloning LLMem and before first use
• When an agent asks "how do I get llmem working?"

Installation Philosophy

Plugin-first, zero-config instructions. LLMem uses platform plugins to inject memory context automatically at session start, extract memories on idle/end, and preserve context during compaction. This means:

• No manual instruction editing required. The plugin handles automatic lifecycle hooks.
• Skills provide on-demand behavioral guidance. When the agent encounters a memory-related situation, it loads the skill. No need to paste 80 lines of instructions into AGENTS.md.
• One line in config enables everything. Add the plugin and you're done.

Procedure

Step 1: Install LLMem CLI

# Option A: Install from source (Go binary)
git clone https://github.com/MichielDean/LLMem.git
cd LLMem && make build
# Binary at ~/.local/bin/llmem, symlinked to /usr/local/bin/llmem

# Option B: One-liner
curl -sSL https://raw.githubusercontent.com/MichielDean/LLMem/main/setup.sh | bash

Verify:

llmem --help
llmem stats

Step 2: Initialize

llmem init          # Interactive — detects providers
llmem init --non-interactive  # Script-friendly — uses defaults

This creates ~/.config/llmem/config.yaml and ~/.config/llmem/memory.db.

Step 3: Configure Provider

Choose one:

Ollama (local, free):

curl -fsSL https://ollama.com/install.sh | sh
ollama pull nomic-embed-text
ollama pull qwen2.5:1.5b
# Config auto-detected

OpenAI (cloud, needs API key):

export OPENAI_API_KEY=sk-...
llmem init --non-interactive

Local (sentence-transformers, no server):

pip install ".[local]"
# Set provider.default: local in config.yaml

None (FTS5-only mode): Works without any provider. Semantic search disabled.

Step 4: Install Plugin and Skills

The recommended approach — fully automatic:

The npm postinstall script deploys everything: skills, platform plugin, and tools.

cd LLMem && npm install

This runs install.js which:

1. Copies all skill directories to ~/.agents/skills/
2. Auto-detects your platform (OpenCode, Claude Code, Copilot CLI)
3. Deploys the correct plugin to the right location
4. Deploys OpenCode custom tools to .opencode/tools/ (if OpenCode detected)

Manual plugin deployment:

If you can't use npm install, deploy manually:

Force a specific platform:

node install.js --platform opencode    # OpenCode only
node install.js --platform claude-code # Claude Code only
node install.js --platform copilot     # Copilot CLI only
node install.js --platform all         # All platforms
node install.js --platform none         # Skills only, no plugins

Step 5: Configure Agent (Platform-Specific)

OpenCode

Add the plugin to your opencode.json:

{
  "plugin": ["llmem"]
}

Or, if using local plugin deployment (the file was already copied by install.js), no config needed — OpenCode auto-discovers plugins in ~/.config/opencode/plugins/.

Custom tools (.opencode/tools/) are auto-discovered by OpenCode when working in the LLMem repo. For other projects, copy the .opencode/tools/ directory or reference it via OPENCODE_CONFIG_DIR.

Instructions in AGENTS.md — optional. The plugin injects context at session start. The llmem skill loads on-demand. If you want a persistent reminder, add this minimal line:

## Memory

Plugin-managed. Search when uncertain: `llmem search "topic"`. Add when you learn: `llmem add --type fact --content "..."`.

Claude Code

The plugin is installed at ~/.claude/plugins/llmem/. Enable it:

claude plugin install ~/.claude/plugins/llmem
# Or use --plugin-dir for testing:
claude --plugin-dir ~/.claude/plugins/llmem

The plugin provides:

• SessionStart hook: Injects llmem stats and llmem search at session start
• PreCompact hook: Injects key memories before compaction
• Skills: llmem, llmem-setup — loaded on-demand

Instructions in CLAUDE.md — optional. The SessionStart hook injects context. If you want a persistent reminder:

## Memory

Plugin-managed. Search when uncertain: `llmem search "topic"`. Add when you learn: `llmem add --type fact --content "..."`.

Copilot CLI

The plugin is installed at ~/.copilot/installed-plugins/_direct/llmem/. Enable it:

copilot plugin install ~/.copilot/installed-plugins/_direct/llmem
# Or install directly from the GitHub repo:
copilot plugin install MichielDean/LLMem:plugins/agent

Copilot CLI uses the same plugin format as Claude Code (.claude-plugin/plugin.json) but installs to ~/.copilot/ instead of ~/.claude/. The hooks and skills are identical.

Instructions in COPILOT.md — optional. If you want a persistent reminder:

## Memory

Plugin-managed. Search when uncertain: `llmem search "topic"`. Add when you learn: `llmem add --type fact --content "..."`.

Step 6: Verify

# CLI works
llmem --help
llmem stats

# Can add and search
llmem add --type fact --content "test memory"
llmem search "test"

# Skills are discoverable
ls ~/.agents/skills/llmem

# Plugin deployed
# OpenCode:
ls ~/.config/opencode/plugins/llmem.js
# Claude Code:
ls ~/.claude/plugins/llmem/.claude-plugin/plugin.json
# Copilot CLI:
ls ~/.copilot/installed-plugins/_direct/llmem/.claude-plugin/plugin.json

# Optional: verify OpenCode tools
ls .opencode/tools/llmem-*.ts

Step 7: Dream Timer (Optional)

For automatic memory consolidation:

# Copy and enable systemd timer
cp harness/llmem-dream.service ~/.config/systemd/user/
cp harness/llmem-dream.timer ~/.config/systemd/user/
systemctl --user daemon-reload
systemctl --user enable llmem-dream.timer
systemctl --user start llmem-dream.timer

Runs nightly at 3am by default. Configure in ~/.config/llmem/config.yaml under dream:.

Architecture

Agent Session
    │
    ├── Plugin (auto, no instructions needed)
    │   ├── session.created/start → llmem stats + llmem search → inject context
    │   └── session.compacting    → llmem search → preserve key memories
    │
    ├── Skills (on-demand, loaded by trigger)
    │   ├── llmem                      → CLI reference, memory types, commands
    │   └── llmem-setup                → This file
    │
    └── Custom Tools (structural, zero-instruction)
        ├── llmem-search   → Search memories
        ├── llmem-add      → Add a memory
        ├── llmem-context  → Get context for a topic
        ├── llmem-invalidate → Soft-delete a memory
        └── llmem-stats    → Show memory statistics

The plugin handles everything the agent physically cannot do itself (inject context before the first message, preserve key memories during compaction). The skills provide behavioral guidance when the agent needs it. Custom tools provide typed access to memory operations without requiring skill loading.

Troubleshooting

llmem: command not found — Binary not on PATH. Check which llmem or ls ~/.local/bin/llmem. May need ln -s ~/.local/bin/llmem /usr/local/bin/llmem.

Ollama not reachable — Start Ollama (ollama serve), pull models (ollama pull nomic-embed-text), or switch providers. LLMem falls back: Ollama → OpenAI → Anthropic → local → none (FTS5-only).

Plugin not loading — Verify the plugin file exists at the expected path. For OpenCode, check ~/.config/opencode/plugins/llmem.js. For Claude Code, check ~/.claude/plugins/llmem/.

Skills not discovered — Verify skill directories: ls ~/.agents/skills/llmem/. If missing, re-run node install.js.

Context not injected at session start — Check the plugin log. For OpenCode, run llmem stats manually to verify the command works. The plugin runs these same commands.