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* revert(gateway): remove stale-code self-check and auto-restart Removes the _detect_stale_code / _trigger_stale_code_restart mechanism introduced in #17648 and iterated in #19740. On every incoming message the gateway compared the boot-time git HEAD SHA to the current SHA on disk, and if they differed it would reply with Gateway code was updated in the background -- restarting this gateway so your next message runs on the new code. Please retry in a moment. and then kick off a graceful restart. This is unwanted behaviour: users who run a long-lived gateway and do their own ad-hoc git operations on the checkout end up with their chat interrupted and the current message dropped every time HEAD moves, with no way to opt out. If an operator really needs the old protection against stale sys.modules after "hermes update", the SIGKILL-survivor sweep in hermes update (hermes_cli/main.py, also tagged #17648) already handles the supervisor-respawn case on its own. Removed: gateway/run.py: - _STALE_CODE_SENTINELS, _GIT_SHA_CACHE_TTL_SECS - _read_git_head_sha(), _compute_repo_mtime() module helpers - class-level _boot_wall_time / _boot_repo_mtime / _boot_git_sha / _stale_code_restart_triggered defaults - __init__ boot-snapshot block (_boot_*, _cached_current_sha*, _repo_root_for_staleness, _stale_code_notified) - _current_git_sha_cached(), _detect_stale_code(), _trigger_stale_code_restart() methods - stale-code check + user-facing restart notice at the top of _handle_message() tests/gateway/test_stale_code_self_check.py (deleted, 412 lines) No new logic added. Zero remaining references to any removed symbol. Gateway test suite passes the same 4589 tests it passed before; the 3 pre-existing unrelated failures (discord free-channel, feishu bot admission, teams typing) are unchanged by this commit. * fix(agent): stateful streaming scrubber for reasoning-block leaks (#17924) Per-delta _strip_think_blocks ran at _fire_stream_delta and destroyed downstream state. When MiniMax-M2.7 / DeepSeek / Qwen3 streamed a tag split across deltas (delta1='<think>', delta2='Let me check'), the regex case-2 match erased delta1 entirely, so CLI/gateway state machines never learned a block was open and leaked delta2 as content. Raw consumers (ACP, api_server, TTS) had no downstream defense at all. Replace the per-delta regex with a stateful StreamingThinkScrubber that survives delta boundaries: - Closed <tag>X</tag> pairs always stripped (matches _strip_think_blocks case 1). - Unterminated open at block boundary enters a block; content discarded until close tag arrives. At end-of-stream, held content is dropped. - Orphan close tags stripped without boundary gating. - Partial tags at delta boundaries held back until resolved. - Block-boundary rule (start-of-stream, after \n, or whitespace-only since last \n) preserves prose that mentions tag names. Reset at turn start alongside the existing context scrubber; flush at turn end so a benign '<' held back at end-of-stream reaches the UI. E2E-verified on live OpenRouter->MiniMax-m2 streams: closed pairs strip cleanly, first word of post-block content is preserved, pure content passes through unchanged. Stefan's screenshot case (#17924) — 'Let me check' getting chopped to ' me check' — no longer happens. Final _strip_think_blocks calls on completed strings (final_response, replay, compression) are preserved; only the streaming per-delta call site switched to the scrubber. |
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| docker | ||
| docs | ||
| environments | ||
| gateway | ||
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| AGENTS.md | ||
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| cli-config.yaml.example | ||
| cli.py | ||
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| CONTRIBUTING.md | ||
| docker-compose.yml | ||
| Dockerfile | ||
| flake.lock | ||
| flake.nix | ||
| hermes | ||
| hermes-already-has-routines.md | ||
| hermes_constants.py | ||
| hermes_logging.py | ||
| hermes_state.py | ||
| hermes_time.py | ||
| LICENSE | ||
| MANIFEST.in | ||
| mcp_serve.py | ||
| mini_swe_runner.py | ||
| model_tools.py | ||
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| pyproject.toml | ||
| README.md | ||
| RELEASE_v0.2.0.md | ||
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| rl_cli.py | ||
| run_agent.py | ||
| SECURITY.md | ||
| setup-hermes.sh | ||
| toolset_distributions.py | ||
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Hermes Agent ☤
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 interface | Full TUI with multiline editing, slash-command autocomplete, conversation history, interrupt-and-redirect, and streaming tool output. |
| Lives where you do | Telegram, Discord, Slack, WhatsApp, Signal, and CLI — all from a single gateway process. Voice memo transcription, cross-platform conversation continuity. |
| A closed learning loop | Agent-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 automations | Built-in cron scheduler with delivery to any platform. Daily reports, nightly backups, weekly audits — all in natural language, running unattended. |
| Delegates and parallelizes | Spawn 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 laptop | Six terminal backends — local, Docker, SSH, Daytona, Singularity, and Modal. 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-ready | Batch trajectory generation, Atropos RL environments, trajectory compression for training the next generation of tool-calling models. |
Quick Install
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
Works on Linux, macOS, WSL2, and Android via Termux. The installer handles the platform-specific setup for you.
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 not supported. Please install WSL2 and run the command above.
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
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/) ships via theatroposlibandtinkerdependencies pulled in by.[all,dev]— no submodule setup required.
Community
- 💬 Discord
- 📚 Skills Hub
- 🐛 Issues
- 🔌 HermesClaw — Community WeChat bridge: Run Hermes Agent and OpenClaw on the same WeChat account.
License
MIT — see LICENSE.
Built by Nous Research.