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b07791db05
Background macOS desktop control via cua-driver MCP — does NOT steal the user's cursor or keyboard focus, works with any tool-capable model. Replaces the Anthropic-native `computer_20251124` approach from the abandoned #4562 with a generic OpenAI function-calling schema plus SOM (set-of-mark) captures so Claude, GPT, Gemini, and open models can all drive the desktop via numbered element indices. ## What this adds - `tools/computer_use/` package — swappable ComputerUseBackend ABC + CuaDriverBackend (stdio MCP client to trycua/cua's cua-driver binary). - Universal `computer_use` tool with one schema for all providers. Actions: capture (som/vision/ax), click, double_click, right_click, middle_click, drag, scroll, type, key, wait, list_apps, focus_app. - Multimodal tool-result envelope (`_multimodal=True`, OpenAI-style `content: [text, image_url]` parts) that flows through handle_function_call into the tool message. Anthropic adapter converts into native `tool_result` image blocks; OpenAI-compatible providers get the parts list directly. - Image eviction in convert_messages_to_anthropic: only the 3 most recent screenshots carry real image data; older ones become text placeholders to cap per-turn token cost. - Context compressor image pruning: old multimodal tool results have their image parts stripped instead of being skipped. - Image-aware token estimation: each image counts as a flat 1500 tokens instead of its base64 char length (~1MB would have registered as ~250K tokens before). - COMPUTER_USE_GUIDANCE system-prompt block — injected when the toolset is active. - Session DB persistence strips base64 from multimodal tool messages. - Trajectory saver normalises multimodal messages to text-only. - `hermes tools` post-setup installs cua-driver via the upstream script and prints permission-grant instructions. - CLI approval callback wired so destructive computer_use actions go through the same prompt_toolkit approval dialog as terminal commands. - Hard safety guards at the tool level: blocked type patterns (curl|bash, sudo rm -rf, fork bomb), blocked key combos (empty trash, force delete, lock screen, log out). - Skill `apple/macos-computer-use/SKILL.md` — universal (model-agnostic) workflow guide. - Docs: `user-guide/features/computer-use.md` plus reference catalog entries. ## Tests 44 new tests in tests/tools/test_computer_use.py covering schema shape (universal, not Anthropic-native), dispatch routing, safety guards, multimodal envelope, Anthropic adapter conversion, screenshot eviction, context compressor pruning, image-aware token estimation, run_agent helpers, and universality guarantees. 469/469 pass across tests/tools/test_computer_use.py + the affected agent/ test suites. ## Not in this PR - `model_tools.py` provider-gating: the tool is available to every provider. Providers without multi-part tool message support will see text-only tool results (graceful degradation via `text_summary`). - Anthropic server-side `clear_tool_uses_20250919` — deferred; client-side eviction + compressor pruning cover the same cost ceiling without a beta header. ## Caveats - macOS only. cua-driver uses private SkyLight SPIs (SLEventPostToPid, SLPSPostEventRecordTo, _AXObserverAddNotificationAndCheckRemote) that can break on any macOS update. Pin with HERMES_CUA_DRIVER_VERSION. - Requires Accessibility + Screen Recording permissions — the post-setup prints the Settings path. Supersedes PR #4562 (pyautogui/Quartz foreground backend, Anthropic- native schema). Credit @0xbyt4 for the original #3816 groundwork whose context/eviction/token design is preserved here in generic form. |
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| acp_registry | ||
| agent | ||
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| cron | ||
| datagen-config-examples | ||
| docker | ||
| environments | ||
| gateway | ||
| hermes_cli | ||
| nix | ||
| optional-skills | ||
| packaging/homebrew | ||
| plans | ||
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| scripts | ||
| skills | ||
| tests | ||
| tinker-atropos@65f084ee80 | ||
| tools | ||
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| web | ||
| website | ||
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| .env.example | ||
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| .mailmap | ||
| AGENTS.md | ||
| batch_runner.py | ||
| cli-config.yaml.example | ||
| cli.py | ||
| constraints-termux.txt | ||
| CONTRIBUTING.md | ||
| 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 | ||
| package-lock.json | ||
| package.json | ||
| pyproject.toml | ||
| README.md | ||
| RELEASE_v0.2.0.md | ||
| RELEASE_v0.3.0.md | ||
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| RELEASE_v0.10.0.md | ||
| RELEASE_v0.11.0.md | ||
| rl_cli.py | ||
| run_agent.py | ||
| SECURITY.md | ||
| setup-hermes.sh | ||
| toolset_distributions.py | ||
| toolsets.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.