mirror of
https://github.com/NousResearch/hermes-agent.git
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fef1a41248
Cross-checked 75 docs pages under user-guide/messaging/, developer-guide/,
guides/, and integrations/ against the live registries and gateway code.
messaging/
- index.md: API Server toolset is hermes-api-server (was 'hermes (default)');
Google Chat slug is hermes-google_chat (underscore — plugin name uses _).
- google_chat.md: drop bogus 'pip install hermes-agent[google_chat]' (no such
extra); list the actual deps (google-cloud-pubsub, google-api-python-client,
google-auth, google-auth-oauthlib).
- qqbot.md: config namespace is platforms.qqbot (was platforms.qq, which is
silently ignored by the adapter); QQ_STT_BASE_URL is not read directly —
baseUrl lives under platforms.qqbot.extra.stt.
- teams-meetings.md: 'hermes teams-pipeline' is plugin-gated (teams_pipeline
plugin must be enabled), not a built-in subcommand.
- sms.md: example log line 0.0.0.0:8080 -> 127.0.0.1:8080 (default
SMS_WEBHOOK_HOST).
- open-webui.md: API_SERVER_* are env vars, not YAML keys — write them to
per-profile .env, not 'hermes config set' (same pattern fixed in
api-server.md last round). Also bumped example ports to 8650+ to dodge the
default webhook (8644)/wecom-callback (8645)/msgraph-webhook (8646)
collision.
developer-guide/
- architecture.md: tool/toolset counts (61/52 -> 70+/~28); LOC stamps for
run_agent.py, cli.py, hermes_cli/main.py, setup.py, mcp_tool.py,
gateway/run.py replaced with 'large file' to stop drifting.
- agent-loop.md: same LOC drift (~13,700 -> 'a large file (15k+ lines)').
- gateway-internals.md: '14+ external messaging platforms' -> '20+'; gateway
platform tree updated (qqbot is a sub-package, not qqbot.py; added
yuanbao.py, feishu_comment.py, msgraph_webhook.py); 'gateway/builtin_hooks/
(always active)' was wrong — it's an empty extension point and
_register_builtin_hooks() is a no-op stub.
- acp-internals.md: drop fictional 'message_callback' from the bridged-
callbacks list; clarify thinking_callback is currently set to None.
- provider-runtime.md: provider list was missing AWS Bedrock, Azure Foundry,
NVIDIA NIM, xAI, Arcee, GMI Cloud, StepFun, Qwen OAuth, Xiaomi, Ollama
Cloud, LM Studio, Tencent TokenHub. Fallback section described only the
legacy single-pair model — corrected to the canonical list-form
fallback_providers chain.
- environments.md: parsers list missing llama4_json and the deepseek_v31
alias; both register via @register_parser.
- browser-supervisor.md: drop reference to scripts/browser_supervisor_e2e.py
which doesn't exist in-repo.
- contributing.md: tinker-atropos is a git submodule — note that
'git submodule update --init' is required if cloning without
--recurse-submodules.
guides/
- operate-teams-meeting-pipeline.md: cron flags were all wrong — schedule is
positional (not --schedule), the script-only flag is --no-agent (not
--script-only), and there's no --command flag. Replaced with a real example
that creates the script under ~/.hermes/scripts/ and uses the actual flags.
Also replaced fictional 'hermes cron show <name>' with 'hermes cron status'.
- automation-templates.md: 'cron create --skills "a,b"' doesn't work —
the flag is --skill (singular, repeatable). Fixed all 5 occurrences via AST
rewrite.
- minimax-oauth.md: 'hermes auth add minimax-oauth --region cn' silently
fails because --region isn't registered on the auth-add argparse spec.
Pointed users at the minimax-cn provider (or MINIMAX_CN_API_KEY env) for
China-region access.
- cron-script-only.md: 'hermes send' is fictional — replaced the comparison-
table mention with a webhook-subscription pointer; also fixed the dead link
to /guides/pipe-script-output (page doesn't exist).
- cron-troubleshooting.md: 'hermes serve' isn't a real subcommand. Pointed
at 'hermes gateway' (foreground) / 'hermes gateway start' (service).
- local-ollama-setup.md: 'agent.api_timeout' is not a config key. The right
knob is the HERMES_API_TIMEOUT env var.
- python-library.md: run_conversation() return dict has only final_response
and messages — task_id is stored on the agent instance, not echoed back.
- use-mcp-with-hermes.md: '--args /c "npx -y …"' wraps the npx command in
one quoted string, so cmd.exe gets a single arg instead of the multi-token
command line it needs. Removed the surrounding quotes — argparse nargs='*'
collects each token correctly.
integrations/
- providers.md: Bedrock guardrail YAML keys were 'id'/'version' (don't exist);
actual keys are guardrail_identifier/guardrail_version (matches DEFAULT_CONFIG
and the run_agent.py reader). GMI default base URL (api.gmi.ai/v1 ->
api.gmi-serving.com/v1) and portal URL (inference.gmi.ai -> www.gmicloud.ai)
refreshed. Fallback section rewritten to lead with the canonical
fallback_providers list form (was leading with the legacy fallback_model
single dict); supported-providers list extended to include azure-foundry,
alibaba-coding-plan, lmstudio.
index.md
- '68 built-in tools' -> '70+'; '15+ platforms' was both inconsistent with
integrations/index.md ('19+') and undercounted — bumped to 20+ and added
Weixin/QQ Bot/Yuanbao/Google Chat to the list.
Validation: 'npm run build' clean (exit 0); broken-link count unchanged at
155 (same as round-1 post-skill-regen baseline). 24 files, +132/-89.
6.5 KiB
6.5 KiB
| slug | sidebar_position | title | description | hide_table_of_contents | displayed_sidebar |
|---|---|---|---|---|---|
| / | 0 | Hermes Agent Documentation | The self-improving AI agent built by Nous Research. A built-in learning loop that creates skills from experience, improves them during use, and remembers across sessions. | true | docs |
Hermes Agent
The self-improving AI agent built by Nous Research. The only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, and builds a deepening model of who you are across sessions.
Install
Linux / macOS / WSL2
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
Windows (native, PowerShell) — early beta, details →
irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex
Android (Termux) — same curl one-liner as Linux; the installer auto-detects Termux.
See the full Installation Guide for what the installer does, the per-user vs root layout, and Windows-specific notes.
What is Hermes Agent?
It's not a coding copilot tethered to an IDE or a chatbot wrapper around a single API. It's an autonomous agent that gets more capable the longer it runs. It lives wherever you put it — a $5 VPS, a GPU cluster, or serverless infrastructure (Daytona, Modal) that costs nearly nothing when idle. Talk to it from Telegram while it works on a cloud VM you never SSH into yourself. It's not tied to your laptop.
Quick Links
| 🚀 Installation | Install in 60 seconds on Linux, macOS, WSL2, or native Windows (early beta) |
| 📖 Quickstart Tutorial | Your first conversation and key features to try |
| 🗺️ Learning Path | Find the right docs for your experience level |
| ⚙️ Configuration | Config file, providers, models, and options |
| 💬 Messaging Gateway | Set up Telegram, Discord, Slack, WhatsApp, Teams, or more |
| 🔧 Tools & Toolsets | 70+ built-in tools and how to configure them |
| 🧠 Memory System | Persistent memory that grows across sessions |
| 📚 Skills System | Procedural memory the agent creates and reuses |
| 🔌 MCP Integration | Connect to MCP servers, filter their tools, and extend Hermes safely |
| 🧭 Use MCP with Hermes | Practical MCP setup patterns, examples, and tutorials |
| 🎙️ Voice Mode | Real-time voice interaction in CLI, Telegram, Discord, and Discord VC |
| 🗣️ Use Voice Mode with Hermes | Hands-on setup and usage patterns for Hermes voice workflows |
| 🎭 Personality & SOUL.md | Define Hermes' default voice with a global SOUL.md |
| 📄 Context Files | Project context files that shape every conversation |
| 🔒 Security | Command approval, authorization, container isolation |
| 💡 Tips & Best Practices | Quick wins to get the most out of Hermes |
| 🏗️ Architecture | How it works under the hood |
| ❓ FAQ & Troubleshooting | Common questions and solutions |
Key Features
- A closed learning loop — Agent-curated memory with periodic nudges, autonomous skill creation, skill self-improvement during use, FTS5 cross-session recall with LLM summarization, and Honcho dialectic user modeling
- Runs anywhere, not just your laptop — 6 terminal backends: local, Docker, SSH, Daytona, Singularity, Modal. Daytona and Modal offer serverless persistence — your environment hibernates when idle, costing nearly nothing
- Lives where you do — CLI, Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Mattermost, Email, SMS, DingTalk, Feishu, WeCom, Weixin, QQ Bot, Yuanbao, BlueBubbles, Home Assistant, Microsoft Teams, Google Chat, and more — 20+ platforms from one gateway
- Built by model trainers — Created by Nous Research, the lab behind Hermes, Nomos, and Psyche. Works with Nous Portal, OpenRouter, OpenAI, or any endpoint
- Scheduled automations — Built-in cron with delivery to any platform
- Delegates & parallelizes — Spawn isolated subagents for parallel workstreams. Programmatic Tool Calling via
execute_codecollapses multi-step pipelines into single inference calls - Open standard skills — Compatible with agentskills.io. Skills are portable, shareable, and community-contributed via the Skills Hub
- Full web control — Search, extract, browse, vision, image generation, TTS
- MCP support — Connect to any MCP server for extended tool capabilities
- Research-ready — Batch processing, trajectory export, RL training with Atropos. Built by Nous Research — the lab behind Hermes, Nomos, and Psyche models
For LLMs and coding agents
Machine-readable entry points to this documentation:
/llms.txt— curated index of every doc page with short descriptions. ~17 KB, safe to load into an LLM context./llms-full.txt— every doc page concatenated into a single markdown file for one-shot ingestion. ~1.8 MB.
Both files also resolve at /docs/llms.txt and /docs/llms-full.txt. Generated fresh on every deploy.