ada3713e77
- 25 documentation pages covering Getting Started, User Guide, Developer Guide, and Reference - Docusaurus with custom amber/gold theme matching the landing page branding - GitHub Actions workflow to deploy landing page + docs to GitHub Pages - Landing page at root, docs at /docs/ on hermes-agent.nousresearch.com - Content extracted and restructured from existing repo docs (README, AGENTS.md, CONTRIBUTING.md, docs/) - Auto-deploy on push to main when website/ or landingpage/ changes
98 lines
3.2 KiB
Markdown
98 lines
3.2 KiB
Markdown
---
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sidebar_position: 3
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title: "Persistent Memory"
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description: "How Hermes Agent remembers across sessions — MEMORY.md, USER.md, and session search"
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---
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# Persistent Memory
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Hermes Agent has bounded, curated memory that persists across sessions. This lets it remember your preferences, your projects, your environment, and things it has learned.
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## How It Works
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Two files make up the agent's memory:
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| File | Purpose | Token Budget |
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|------|---------|-------------|
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| **MEMORY.md** | Agent's personal notes — environment facts, conventions, things learned | ~800 tokens (~2200 chars) |
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| **USER.md** | User profile — your preferences, communication style, expectations | ~500 tokens (~1375 chars) |
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Both are stored in `~/.hermes/memories/` and are injected into the system prompt as a frozen snapshot at session start. The agent manages its own memory via the `memory` tool — it can add, replace, or remove entries.
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:::info
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Character limits keep memory focused. When memory is full, the agent consolidates or replaces entries to make room for new information.
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:::
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## Configuration
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```yaml
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# In ~/.hermes/config.yaml
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memory:
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memory_enabled: true
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user_profile_enabled: true
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memory_char_limit: 2200 # ~800 tokens
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user_char_limit: 1375 # ~500 tokens
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```
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## Memory Tool Actions
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The agent uses the `memory` tool with these actions:
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- **add** — Add a new memory entry
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- **replace** — Replace an existing entry with updated content
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- **remove** — Remove an entry that's no longer relevant
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- **read** — Read current memory contents
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## Session Search
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Beyond MEMORY.md and USER.md, the agent can search its past conversations using the `session_search` tool:
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- All CLI and messaging sessions are stored in SQLite (`~/.hermes/state.db`) with FTS5 full-text search
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- Search queries return relevant past conversations with Gemini Flash summarization
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- The agent can find things it discussed weeks ago, even if they're not in its active memory
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```bash
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hermes sessions list # Browse past sessions
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```
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## Honcho Integration (Cross-Session User Modeling)
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For deeper, AI-generated user understanding that works across tools, you can optionally enable [Honcho](https://honcho.dev/) by Plastic Labs. Honcho runs alongside existing memory — USER.md stays as-is, and Honcho adds an additional layer of context.
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When enabled:
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- **Prefetch**: Each turn, Honcho's user representation is injected into the system prompt
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- **Sync**: After each conversation, messages are synced to Honcho
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- **Query tool**: The agent can actively query its understanding of you via `query_user_context`
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**Setup:**
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```bash
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# 1. Install the optional dependency
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uv pip install honcho-ai
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# 2. Get an API key from https://app.honcho.dev
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# 3. Create ~/.honcho/config.json
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cat > ~/.honcho/config.json << 'EOF'
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{
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"enabled": true,
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"apiKey": "your-honcho-api-key",
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"peerName": "your-name",
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"hosts": {
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"hermes": {
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"workspace": "hermes"
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}
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}
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}
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EOF
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```
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Or via environment variable:
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```bash
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hermes config set HONCHO_API_KEY your-key
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```
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:::tip
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Honcho is fully opt-in — zero behavior change when disabled or unconfigured. All Honcho calls are non-fatal; if the service is unreachable, the agent continues normally.
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:::
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