snav dee71a31e5 feat(compression): make protect_first_n configurable
The number of head messages preserved verbatim across context compactions
was previously hardcoded to 3 in AIAgent.__init__. Expose it as
`compression.protect_first_n` in config, matching the existing
`protect_last_n` pattern.

Motivation: users who rely on rolling compaction for long-running sessions
had the opening user/assistant exchange pinned as head forever, which
doesn't always match how they want the session framed after many
compactions. Lowering to 1 preserves the system prompt + first non-system
message; lowering to 0 preserves only the system prompt and lets the
entire first exchange age out naturally through the summary.

Semantics: `protect_first_n` counts non-system head messages protected
**in addition to** the system prompt, which is always implicitly protected
when present. Same meaning across both code paths:

  protect_first_n=0 → system prompt only (or nothing if no system message)
  protect_first_n=2 → system prompt + first 2 non-system messages (default)

This unifies the CLI path (which reads messages with the system prompt at
position 0) and the gateway path (where the gateway /compress handler
strips the system prompt before calling compress() — see
gateway/run.py L9150-9154 on the parent fork). Previously these two paths
disagreed:

  CLI path:     protect_first_n=1 → protect system prompt only
  Gateway path: protect_first_n=1 → protect first USER turn forever

In practice on long-running gateway sessions the old semantics pinned
whatever stale aside happened to be the first user message, reinserting
it into every compaction summary indefinitely.

Default chosen as 2 (not 3) so that the effective protected head count
remains 3 messages in the common case — assuming a system prompt is
present, default protection becomes system + 2 non-system = 3 total,
matching the pre-feature behaviour where `protect_first_n` was hardcoded
to protect 3 messages total. Sessions without a system prompt will see a
small behaviour change (2 protected head messages instead of 3), but this
is the rare path and the new semantics make the system-prompt-present
case the well-defined one.

Changes:

- agent/context_compressor.py: redefine protect_first_n as the count of
  non-system head messages protected beyond the implicit system-prompt
  guarantee; both paths converge. Constructor default updated to 2.
- hermes_cli/config.py: add `compression.protect_first_n` default (2),
  matching the new semantics. `show_config` label tweaked to
  'Protect first: N non-system head messages' for clarity.
- run_agent.py: read protect_first_n from config; 0 is now valid (system
  prompt is always implicitly protected).
- cli-config.yaml.example: document the new key and rationale.
- tests/agent/test_context_compressor.py: cover default, override, the
  end-to-end `protect_first_n=0` and `protect_first_n=1` behaviour,
  the no-system-prompt (gateway) path, and the new shared-semantics
  regression test.

Fixes #13751
Tested on Ubuntu 24.04.
2026-05-13 22:25:16 -07:00
2026-02-25 11:53:44 -08:00
2026-04-10 00:46:37 -04:00
2026-04-11 15:30:37 -04:00
2026-03-07 13:43:08 -08:00
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), 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 laptopSeven terminal backends — local, Docker, SSH, Singularity, Modal, Daytona, and Vercel Sandbox. 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, Atropos RL environments, 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) — Early Beta

Heads up: Native Windows support is early beta. It installs and runs, but hasn't been road-tested as broadly as our Linux/macOS/WSL2 paths. Please file issues when you hit rough edges. For the most battle-tested Windows setup today, run the Linux/macOS one-liner above inside WSL2.

Run this in PowerShell:

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

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 supported as an early beta — the PowerShell one-liner above installs everything, but expect rough edges and please file issues when you hit them. If you'd rather use WSL2 (our most battle-tested Windows path), 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 →

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

RL Training (optional): The RL/Atropos integration (environments/) — see CONTRIBUTING.md for the full setup.


Community


License

MIT — see LICENSE.

Built by Nous Research.

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