teknium1 e76d8bf5aa fix(tui): stop persisting full tool output in trail lines (silent OOM death)
A heavy --tui session (browser snapshots, large tool outputs) silently
OOM-killed the Node parent within minutes — closing the gateway child's
stdin, which the user saw only as a bare "gateway exited" / stdin EOF.
CLI was immune. Root cause: each completed tool's verbose trail line
embedded up to 16KB of result_text, persisted in transcript Msg.tools[]
for the whole session and rendered EXPANDED by default, so an Ink
render-node tree was built for every one of up to 800 messages at once.
That tree blew past Node's heap at a few hundred MB — far below the 2.5GB
memory-monitor exit threshold, so the death was never even attributed.

- text.ts: persisted verbose tool-trail blocks now cap to a small preview
  (VERBOSE_TRAIL_MAX_CHARS=800/12 lines), not the 16KB live-render budget.
  Retained trail strings drop ~17x (12.2MB -> 0.7MB at 800 msgs); the live
  streaming tail still uses the larger LIVE_RENDER budget.
- tui_gateway/server.py: lower the gateway-side verbose text cap to match
  (1KB/16 lines) so we stop shipping output the TUI no longer renders.
- memoryMonitor.ts: derive critical/high thresholds from the real V8 heap
  ceiling (~88%/70%) instead of the hardcoded 2.5GB that killed the process
  at 31% of an 8GB ceiling; add a one-shot onWarn early-warning on fast
  sub-threshold heap growth so the next such death is diagnosable, not silent.
- entry.tsx: wire onWarn to a crash-log breadcrumb + stderr line.

Full tool output is unchanged in the agent context and SQLite session — this
is display/transport only, no behavior or context change.

Fixes #34095. Related #27282.

Tests: ui-tui text + new memoryMonitor suites (33 pass), python verbose-cap
guard (5 pass); full ui-tui suite shows no new failures vs pristine main.
E2E repro confirms the retention drop.
2026-06-03 06:00:22 -07:00
2026-02-25 11:53:44 -08:00
2026-05-31 17:46:56 -05:00
2026-04-11 15:30:37 -04:00
2026-03-07 13:43:08 -08:00
2026-05-31 17:46:56 -05:00
2026-05-05 22:45:12 -04:00

Hermes Agent

Hermes Agent ☤

Documentation Discord License: MIT Built by Nous Research 中文

The self-improving AI agent built by Nous Research. It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a deepening model of who you are across sessions. Run it on a $5 VPS, a GPU cluster, or serverless infrastructure that costs nearly nothing when idle. It's not tied to your laptop — talk to it from Telegram while it works on a cloud VM.

Use any model you want — Nous Portal, OpenRouter (200+ models), NovitaAI (AI-native cloud for Model API, Agent Sandbox, and GPU Cloud), NVIDIA NIM (Nemotron), Xiaomi MiMo, z.ai/GLM, Kimi/Moonshot, MiniMax, Hugging Face, OpenAI, or your own endpoint. Switch with hermes model — no code changes, no lock-in.

A real terminal interfaceFull TUI with multiline editing, slash-command autocomplete, conversation history, interrupt-and-redirect, and streaming tool output.
Lives where you doTelegram, Discord, Slack, WhatsApp, Signal, and CLI — all from a single gateway process. Voice memo transcription, cross-platform conversation continuity.
A closed learning loopAgent-curated memory with periodic nudges. Autonomous skill creation after complex tasks. Skills self-improve during use. FTS5 session search with LLM summarization for cross-session recall. Honcho dialectic user modeling. Compatible with the agentskills.io open standard.
Scheduled automationsBuilt-in cron scheduler with delivery to any platform. Daily reports, nightly backups, weekly audits — all in natural language, running unattended.
Delegates and parallelizesSpawn isolated subagents for parallel workstreams. Write Python scripts that call tools via RPC, collapsing multi-step pipelines into zero-context-cost turns.
Runs anywhere, not just your laptopSix terminal backends — local, Docker, SSH, Singularity, Modal, and Daytona. Daytona and Modal offer serverless persistence — your agent's environment hibernates when idle and wakes on demand, costing nearly nothing between sessions. Run it on a $5 VPS or a GPU cluster.
Research-readyBatch trajectory generation, trajectory compression for training the next generation of tool-calling models.

Quick Install

Linux, macOS, WSL2, Termux

curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash

Windows (native, PowerShell)

Heads up: Native Windows runs Hermes without WSL — CLI, gateway, TUI, and tools all work natively. If you'd rather use WSL2, the Linux/macOS one-liner above works there too. Found a bug? Please file issues.

Run this in PowerShell:

iex (irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1)

The installer handles everything: uv, Python 3.11, Node.js, ripgrep, ffmpeg, and a portable Git Bash (MinGit, unpacked to %LOCALAPPDATA%\hermes\git — no admin required, completely isolated from any system Git install). Hermes uses this bundled Git Bash to run shell commands.

If you already have Git installed, the installer detects it and uses that instead. Otherwise a ~45MB MinGit download is all you need — it won't touch or interfere with any system Git.

Android / Termux: The tested manual path is documented in the Termux guide. On Termux, Hermes installs a curated .[termux] extra because the full .[all] extra currently pulls Android-incompatible voice dependencies.

Windows: Native Windows is fully supported — the PowerShell one-liner above installs everything. If you'd rather use WSL2, the Linux command works there too. Native Windows install lives under %LOCALAPPDATA%\hermes; WSL2 installs under ~/.hermes as on Linux. The only Hermes feature that currently needs WSL2 specifically is the browser-based dashboard chat pane (it uses a POSIX PTY — classic CLI and gateway both run natively).

After installation:

source ~/.bashrc    # reload shell (or: source ~/.zshrc)
hermes              # start chatting!

Getting Started

hermes              # Interactive CLI — start a conversation
hermes model        # Choose your LLM provider and model
hermes tools        # Configure which tools are enabled
hermes config set   # Set individual config values
hermes gateway      # Start the messaging gateway (Telegram, Discord, etc.)
hermes setup        # Run the full setup wizard (configures everything at once)
hermes claw migrate # Migrate from OpenClaw (if coming from OpenClaw)
hermes update       # Update to the latest version
hermes doctor       # Diagnose any issues

📖 Full documentation →


Skip the API-key collection — Nous Portal

Hermes works with whatever provider you want — that's not changing. But if you'd rather not collect five separate API keys for the model, web search, image generation, TTS, and a cloud browser, Nous Portal covers all of them under one subscription:

  • 300+ models — pick any of them with /model <name>
  • Tool Gateway — web search (Firecrawl), image generation (FAL), text-to-speech (OpenAI), cloud browser (Browser Use), all routed through your sub. No extra accounts.

One command from a fresh install:

hermes setup --portal

That logs you in via OAuth, sets Nous as your provider, and turns on the Tool Gateway. Check what's wired up any time with hermes portal status. Full details on the Tool Gateway docs page.

You can still bring your own keys per-tool whenever you want — the gateway is per-backend, not all-or-nothing.


CLI vs Messaging Quick Reference

Hermes has two entry points: start the terminal UI with hermes, or run the gateway and talk to it from Telegram, Discord, Slack, WhatsApp, Signal, or Email. Once you're in a conversation, many slash commands are shared across both interfaces.

Action CLI Messaging platforms
Start chatting hermes Run hermes gateway setup + hermes gateway start, then send the bot a message
Start fresh conversation /new or /reset /new or /reset
Change model /model [provider:model] /model [provider:model]
Set a personality /personality [name] /personality [name]
Retry or undo the last turn /retry, /undo /retry, /undo
Compress context / check usage /compress, /usage, /insights [--days N] /compress, /usage, /insights [days]
Browse skills /skills or /<skill-name> /<skill-name>
Interrupt current work Ctrl+C or send a new message /stop or send a new message
Platform-specific status /platforms /status, /sethome

For the full command lists, see the CLI guide and the Messaging Gateway guide.


Documentation

All documentation lives at hermes-agent.nousresearch.com/docs:

Section What's Covered
Quickstart Install → setup → first conversation in 2 minutes
CLI Usage Commands, keybindings, personalities, sessions
Configuration Config file, providers, models, all options
Messaging Gateway Telegram, Discord, Slack, WhatsApp, Signal, Home Assistant
Security Command approval, DM pairing, container isolation
Tools & Toolsets 40+ tools, toolset system, terminal backends
Skills System Procedural memory, Skills Hub, creating skills
Memory Persistent memory, user profiles, best practices
MCP Integration Connect any MCP server for extended capabilities
Cron Scheduling Scheduled tasks with platform delivery
Context Files Project context that shapes every conversation
Architecture Project structure, agent loop, key classes
Contributing Development setup, PR process, code style
CLI Reference All commands and flags
Environment Variables Complete env var reference

Migrating from OpenClaw

If you're coming from OpenClaw, Hermes can automatically import your settings, memories, skills, and API keys.

During first-time setup: The setup wizard (hermes setup) automatically detects ~/.openclaw and offers to migrate before configuration begins.

Anytime after install:

hermes claw migrate              # Interactive migration (full preset)
hermes claw migrate --dry-run    # Preview what would be migrated
hermes claw migrate --preset user-data   # Migrate without secrets
hermes claw migrate --overwrite  # Overwrite existing conflicts

What gets imported:

  • SOUL.md — persona file
  • Memories — MEMORY.md and USER.md entries
  • Skills — user-created skills → ~/.hermes/skills/openclaw-imports/
  • Command allowlist — approval patterns
  • Messaging settings — platform configs, allowed users, working directory
  • API keys — allowlisted secrets (Telegram, OpenRouter, OpenAI, Anthropic, ElevenLabs)
  • TTS assets — workspace audio files
  • Workspace instructions — AGENTS.md (with --workspace-target)

See hermes claw migrate --help for all options, or use the openclaw-migration skill for an interactive agent-guided migration with dry-run previews.


Contributing

We welcome contributions! See the Contributing Guide for development setup, code style, and PR process.

Quick start for contributors — clone and go with setup-hermes.sh:

git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
./setup-hermes.sh     # installs uv, creates venv, installs .[all], symlinks ~/.local/bin/hermes
./hermes              # auto-detects the venv, no need to `source` first

Manual path (equivalent to the above):

curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv .venv --python 3.11
source .venv/bin/activate
uv pip install -e ".[all,dev]"
scripts/run_tests.sh

Community

  • 💬 Discord
  • 📚 Skills Hub
  • 🐛 Issues
  • 🔌 computer-use-linux — Linux desktop-control MCP server for Hermes and other MCP hosts, with AT-SPI accessibility trees, Wayland/X11 input, screenshots, and compositor window targeting.
  • 🔌 HermesClaw — Community WeChat bridge: Run Hermes Agent and OpenClaw on the same WeChat account.

License

MIT — see LICENSE.

Built by Nous Research.

Description
Hermes Agent (mirror)
Readme 148 MiB
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