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Agents, but operable.
Open-source platform for deploying fleets of AI agents as production services — durable state, sandboxed execution, managed at scale, and the channels you already use.
Built by Amiko — an agent-agnostic infrastructure platform for the AI era.
OpenHermit is the open-source platform for deploying fleets of AI agents as production services — durable state, sandboxed execution, managed at scale, and the channels you already use.
Website · Why OpenHermit · Docs · npm
Most CLI-based agents (Claude Code, OpenClaw, Hermes, …) keep their state in files: memories as markdown, sessions as JSONL, skills as folders, secrets as dotfiles. That's perfect for one human at one machine — but it falls apart the moment you stop being one human. Running an internal agent platform for your team, a SaaS where every customer gets their own agent, or a swarm of specialized roles? Files scatter, secrets leak, fleet operations turn into SSH-and-pray.
OpenHermit makes one core design choice: separate internal state from external state.
agent_id.Once internal state is centralized, fleet operations become trivial:
hermit skills enable standup-digest --all # roll a skill out to every agent
hermit mcp enable mcp_github --all # add an MCP server to every agent
hermit instructions append rules "Never share PII." --all # push a rule to every agent
hermit config secrets set OPENROUTER_API_KEY sk-... --agent main # rotate a secret
/admin/.A research run is a pipeline of model calls — planner, per-iteration action decisions, one evidence extraction per source read (these are the big ones: each carries up to a 200 KB page snapshot ≈ 50k input tokens), and synthesis. Budgets are hard caps per depth; typical runs land well under them, but plan for the worst case:
Dollar figures are worst-case at list prices. Search costs are separate but small (Tavily's free tier of ~1,000 credits/month easily covers testing).
Free model tiers are usually not enough. The binding constraint is
per-minute/per-day token quotas, not intelligence — a single extraction call
can be 50k input tokens, which blows through e.g. Google AI Studio's free
tier mid-run (you'll see a 429 quota error surfaced on the run). Use a paid
key, or a topped-up OpenRouter account ($5 covers many standard runs).
What a model needs to handle research well: disciplined JSON output
(every phase is validated, with one repair attempt), a context window of
64k+ tokens for extraction, and model.max_tokens of at least ~16k so long
extraction/synthesis answers don't truncate. Suggested configurations
(verified registry ids; prices per Mtok in/out):
Set with:
hermit config set model.provider openai
hermit config set model.model gpt-5-mini
hermit config set model.max_tokens 16384
hermit config secrets set OPENAI_API_KEY sk-...
Any OpenAI-compatible local server works — Ollama, LM Studio, llama.cpp
--server, vLLM — via a custom endpoint:
# Ollama example. Research needs long context: raise it from Ollama's default.
OLLAMA_CONTEXT_LENGTH=65536 ollama serve # in another terminal: ollama pull qwen3:32b
hermit config set model.provider ollama
hermit config set model.model qwen3:32b
hermit config set model.base_url http://127.0.0.1:11434/v1
hermit config set model.api openai-completions
hermit config set model.max_tokens 16384
hermit config secrets set OLLAMA_API_KEY ollama # any non-empty value; local servers ignore it
Honest expectations for local runs:
qwen3:32b, gemma3:27b, llama3.3:70b) are
workable; 7–8B models fail validation often enough to be frustrating even
with the built-in repair attempt and advisory-field tolerance.OLLAMA_CONTEXT_LENGTH, --ctx-size, …).
npm install -g openhermit
This installs both hermit and openhermit.
For local development:
git clone https://github.com/HCF-S/openhermit.git
cd openhermit
npm install
# Configure DATABASE_URL, GATEWAY_ADMIN_TOKEN, GATEWAY_JWT_SECRET.
hermit setup
# Start the gateway and the end-user web app.
hermit gateway start
hermit web start
# Check platform health.
hermit status
hermit doctor
# Create and start an agent.
hermit agents create main
hermit agents start main
# Chat through the CLI.
hermit chat --agent main
The gateway defaults to http://127.0.0.1:4000 and serves the admin UI at /admin/. The end-user web app runs on http://127.0.0.1:4310.
Agent-scoped commands accept --agent <id> and default to OPENHERMIT_AGENT_ID or main. Full reference: docs/cli.md.
Agent execution routes are exposed under /api/agents/{agentId}:
POST /api/agents/{id}/sessionsGET /api/agents/{id}/sessionsPOST /api/agents/{id}/sessions/{sessionId}/messagesPOST /api/agents/{id}/sessions/{sessionId}/messages?wait=truePOST /api/agents/{id}/sessions/{sessionId}/messages?stream=trueGET /api/agents/{id}/sessions/{sessionId}/eventsPOST /api/agents/{id}/sessions/{sessionId}/approvePOST /api/agents/{id}/sessions/{sessionId}/checkpointDELETE /api/agents/{id}/sessions/{sessionId}ws://host/api/agents/{id}/wsAdmin and owner-facing management endpoints live under /api/admin/... and /api/agents/{agentId}/.... Channel webhooks land at POST /api/agents/{id}/channels/{namespace}/webhook.
All durable internal state is scoped by agent_id where applicable:
Secrets and channel-owned credentials are encrypted with OPENHERMIT_SECRETS_KEY (AES-256-GCM); without that key the gateway falls back to per-agent secrets.json for local dev secrets, but DB-backed channel credentials are unavailable. The only per-agent files on disk are the workspace at ~/.openhermit/workspaces/{agentId}/; enabled skills are synced into each backend's own <agent_home>/.openhermit/skills/system/ (bind-mounted for docker, uploaded via SDK for e2b/daytona).
openhermit/
├── apps/
│ ├── agent/ # AgentRunner, tools, runtime, scheduler, channels
│ ├── gateway/ # Control plane, auth, admin API, admin UI
│ ├── cli/ # Published `hermit` / `openhermit` CLI
│ ├── web/ # End-user browser chat app
│ └── channels/
│ ├── telegram/ # Telegram adapter
│ ├── discord/ # Discord adapter
│ └── slack/ # Slack adapter
├── packages/
│ ├── protocol/ # Shared protocol types and route builders
│ ├── sdk/ # HTTP/SSE/WebSocket clients
│ ├── shared/ # Common env, errors, URL helpers
│ └── store/ # Drizzle schema and PostgreSQL store implementations
├── skills/ # Built-in OpenHermit skills registered by the gateway
└── docs/ # Architecture and operation docs
npm run dev:gateway # Gateway and admin UI API at http://127.0.0.1:4000
npm run dev:web # End-user web app at http://127.0.0.1:4310
npm run dev:cli # CLI from source
npm run dev:studio # Drizzle Studio for the configured database
npm run typecheck # Type-check all workspaces
npm test # Build and run test suites
Important environment variables:
The gateway supports three storage providers. The provider is selected in the gateway config (DB-backed, edited via the admin UI at /admin/config — JSON tab — or seeded from gateway.json on first boot), and credentials live in env, not config — only secrets go in env; non-secret pointers (provider, bucket, region, prefix, endpoint, root) live in the gateway config.
No config block needed; defaults to ~/.openhermit/attachments. To override the root, set this under attachments.storage:
{
"attachments": { "storage": { "provider": "local", "root": "/srv/openhermit/attachments" } }
}
Install the SDK on the gateway: npm install @aws-sdk/client-s3 @aws-sdk/s3-request-presigner. Credentials come from the AWS default chain (env vars / IAM role / IRSA).
{
"attachments": {
"storage": {
"provider": "s3",
"bucket": "oh-attachments",
"region": "us-east-1",
"prefix": "prod",
"endpoint": "https://abc.r2.cloudflarestorage.com",
"forcePathStyle": false
}
}
}
Install the SDK on the gateway: npm install @supabase/supabase-js. Set SUPABASE_URL and a Supabase secret API key (sb_secret_…) in env as SUPABASE_SERVICE_ROLE_KEY (or OPENHERMIT_ATTACHMENT_SUPABASE_SECRET_KEY) — the project URL embeds the project ID and is treated as part of the credential bundle. The legacy service-role JWT still works; the older OPENHERMIT_ATTACHMENT_SUPABASE_SERVICE_KEY var is deprecated.
{
"attachments": {
"storage": {
"provider": "supabase",
"bucket": "attachments",
"prefix": "agents"
}
}
}
Optional attachments.limits.maxBytes overrides the default 25 MB cap. Every successful upload is materialized into the sandbox; if the sandbox is down the row is marked failed and attachment_fetch re-materializes on first read.
OpenHermit is the open-source agent infrastructure layer of Amiko — an agent-agnostic platform that integrates identity, productivity, social, and economic infrastructure into one coherent system where humans and AI agents coexist.
Amiko is organized around four connected layers:
OpenHermit provides the production runtime that makes this possible: durable state, sandboxed execution, multi-channel delivery, fleet management, and the access policy system that governs how agents act on behalf of users.
Amiko is agent-agnostic by design — bring your own agent or create one on the platform. Both paths lead to the same social graph, the same identity layer, and the same economic rails.
Learn more at heyamiko.com.
OpenHermit is open source (MIT) and very much a work in progress. If the internal/external state split, the fleet operations model, or agents-as-services resonates with you — we'd love your help.
Issues, PRs, design discussions, channel adapters, skills, MCP integrations, docs, and war stories from running it in your own setup are all welcome.
MIT © Amiko
OpenHermit is the open-source platform for deploying fleets of AI agents as production services — durable state, sandboxed execution, managed at scale, and the channels you already use.
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ตรวจสอบล่าสุดเมื่อ 2026-10-27 OpenHermit is the open-source platform for deploying fleets of AI agents as production services — durable state, sandboxed execution, managed at scale, and the channels you already use.