178 lines
7.4 KiB
Plaintext
178 lines
7.4 KiB
Plaintext
---
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title: "OpenClaw"
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icon: 'lobster'
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description: "Add AI-native memory to OpenClaw"
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sidebarTitle: 'OpenClaw'
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---
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[OpenClaw](https://openclaw.ai) is a general AI agent that can perform actions on behalf of a user. The Honcho plugin gives OpenClaw memory across every channel — WhatsApp, Telegram, Discord, Slack, and more.
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<Note>
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Honcho can run entirely locally with OpenClaw — no external API required. Keep your data on your machine while getting full memory capabilities across all channels. See the [self-hosting guide](/v3/contributing/self-hosting) to get started.
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</Note>
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For OpenClaw's own documentation on Honcho, see the [Honcho Memory guide](https://docs.openclaw.ai/concepts/memory-honcho).
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## Install the Plugin
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```bash
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openclaw plugins install @honcho-ai/openclaw-honcho
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openclaw honcho setup
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openclaw gateway --force
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```
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`openclaw honcho setup` prompts for your API key, writes the config, and optionally uploads any legacy memory files to Honcho.
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<iframe
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className="w-full aspect-video rounded-xl"
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src="https://www.loom.com/embed/bc870932f1694302a80f1f71276790e8"
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title="Loom video"
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allowFullScreen
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></iframe>
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<Note>
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**Alternative: ClawHub Skill**
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The `honcho-setup` skill handles installation and migration interactively from a chat session:
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```bash
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npx clawhub install honcho-setup
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# Restart OpenClaw, then invoke the skill from a session
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openclaw plugins install @honcho-ai/openclaw-honcho
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openclaw gateway restart
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```
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</Note>
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## Migrating Legacy Memory
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If you have existing workspace memory files (`USER.md`, `MEMORY.md`, `IDENTITY.md`, `memory/`, `canvas/`, etc.), `openclaw honcho setup` will detect them and offer to migrate them.
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<Note>
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Migration is **non-destructive** — files are uploaded to Honcho. Originals are never deleted or moved.
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</Note>
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### Legacy files
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**User/owner files** (content describes the user):
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- `USER.md`, `IDENTITY.md`, `MEMORY.md`
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- All files in `memory/` and `canvas/` directories
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**Agent/self files** (content describes the agent):
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- `SOUL.md`, `AGENTS.md`, `TOOLS.md`, `BOOTSTRAP.md`
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### Upload to Honcho
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Files are uploaded via `session.uploadFile()`. User/owner files go to the owner peer; agent/self files go to the openclaw peer.
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## How It Works
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Once installed, the plugin runs automatically:
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* **Message Observation** — After every AI turn, the conversation is persisted to Honcho. Both user and agent messages are observed, allowing Honcho to build and refine its models.
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* **Tool-Based Context Access** — The AI can query Honcho mid-conversation using tools like `honcho_context`, `honcho_search_conclusions`, `honcho_search_messages`, and `honcho_ask` to retrieve relevant context. Context is injected during OpenClaw's `before_prompt_build` phase, ensuring accurate turn boundaries.
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* **Dual Peer Model** — Honcho maintains separate representations: one for the user (preferences, facts, communication style) and one for the agent (personality, learned behaviors). Each OpenClaw agent gets its own Honcho peer (`agent-{id}`), so multi-agent workspaces maintain isolated memory.
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* **Clean Persistence** — Platform metadata (conversation info, sender headers, thread context, forwarded messages) is stripped before saving to Honcho, ensuring only meaningful content is persisted.
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## Multi-Agent Support
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OpenClaw uses a multi-agent architecture where a primary agent can spawn **subagents** to handle specialized tasks. The Honcho plugin is fully aware of this hierarchy:
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* **Automatic Subagent Detection** — When OpenClaw spawns a subagent, the plugin tracks the parent→child relationship via the `subagent_spawned` hook. Each subagent session records its `parentPeerId` in metadata.
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* **Parent Observer Peer** — The spawning agent is added as a silent observer in the subagent's Honcho session (`observeMe: false, observeOthers: true`). This gives Honcho visibility into the full agent tree — the parent can see what its subagents are doing without its own messages being attributed to the subagent session.
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## AI Tools
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### Data Retrieval (fast, no LLM)
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| Tool | Description |
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| ---- | ----------- |
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| `honcho_context` | User knowledge across all sessions. `detail='card'` for key facts, `'full'` for broad representation. |
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| `honcho_search_conclusions` | Semantic vector search over stored conclusions ranked by relevance. |
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| `honcho_search_messages` | Find specific messages across all sessions. Filter by sender, date, or metadata. |
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| `honcho_session` | Current session history and summary. Supports semantic search within the session. |
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### Q&A (LLM-powered)
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| Tool | Description |
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| ---- | ----------- |
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| `honcho_ask` | Ask Honcho a question about the user. `depth='quick'` for facts, `'thorough'` for synthesis. |
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## CLI Commands
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```bash
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openclaw honcho setup # Configure API key and migrate legacy files
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openclaw honcho status # Connection status
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openclaw honcho ask <question> # Query Honcho about the user
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openclaw honcho search <query> [-k N] [-d D] # Semantic search (topK, maxDistance)
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```
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## Configuration
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Run `openclaw honcho setup` to configure interactively, or set values directly in `~/.openclaw/openclaw.json` under `plugins.entries["openclaw-honcho"].config`.
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| Key | Default | Description |
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| --- | ------- | ----------- |
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| `apiKey` | — | Honcho API key (required for managed; omit for self-hosted). |
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| `workspaceId` | `"openclaw"` | Honcho workspace ID for memory isolation. |
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| `baseUrl` | `"https://api.honcho.dev"` | API endpoint (for self-hosted instances). |
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### Self-Hosted Honcho
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Point the plugin to your local instance and follow the [self-hosting guide](https://github.com/plastic-labs/honcho?tab=readme-ov-file#local-development) to get started:
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```bash
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openclaw honcho setup
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# Enter blank API key, set Base URL to http://localhost:8000
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```
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## Local File Search (QMD Integration)
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The plugin automatically exposes OpenClaw's `memory_search` and `memory_get` tools when a [memory backend](https://docs.openclaw.ai/concepts/memory) is configured, allowing both Honcho memory and local file search together.
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### Setup
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1. Install [QMD](https://github.com/tobi/qmd) on your server
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2. Configure OpenClaw to use QMD as the memory backend in `~/.openclaw/openclaw.json`:
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```json
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{
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"memory": {
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"backend": "qmd"
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}
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}
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```
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OpenClaw manages QMD collections automatically from your workspace memory files and any extra paths in `memory.qmd.paths`. See the [QMD Memory Engine docs](https://docs.openclaw.ai/concepts/memory-qmd) for full setup.
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3. Restart the gateway:
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```bash
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openclaw gateway restart
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```
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### Available Tools
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When QMD is configured, you get both Honcho and local file tools:
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| Tool | Source | Description |
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| ---- | ------ | ----------- |
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| `honcho_*` | Honcho | Cross-session memory, user modeling, dialectic reasoning |
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| `memory_search` | QMD | Search local markdown files |
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| `memory_get` | QMD | Retrieve file content |
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## Next Steps
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<CardGroup cols={2}>
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<Card title="GitHub Repository" icon="github" href="https://github.com/plastic-labs/openclaw-honcho">
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Source code, issues, and README.
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</Card>
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<Card title="OpenClaw Memory Docs" icon="book" href="https://docs.openclaw.ai/concepts/memory">
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Memory backends, search, and configuration in the OpenClaw docs.
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</Card>
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<Card title="Honcho Architecture" icon="sitemap" href="/v3/documentation/core-concepts/architecture">
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Learn about peers, sessions, and dialectic reasoning.
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</Card>
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</CardGroup>
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