4ed293b38e
Adds Telegram's native streaming-draft API as a streaming transport so DM
replies render with smooth animated previews as tokens arrive, dropping
the per-edit jitter of the legacy editMessageText polling path.
Adapter contract (gateway/platforms/base.py):
- supports_draft_streaming(chat_type, metadata) -> bool. Default False.
Telegram returns True only for DMs and only when the bound python-
telegram-bot version exposes Bot.send_message_draft (PTB 22.6+).
- send_draft(chat_id, draft_id, content, metadata) -> SendResult.
Default raises NotImplementedError. Telegram delegates to PTB's
send_message_draft. Drafts have no message_id (Bot API contract);
SendResult.message_id is None on success.
Telegram adapter (gateway/platforms/telegram.py):
- supports_draft_streaming gates on chat_type='dm' AND PTB capability.
- send_draft trims to MAX_MESSAGE_LENGTH using utf16_len, threads
message_thread_id through metadata, and routes failures back as
SendResult(success=False, error=...) so the consumer can fall back.
Stream consumer (gateway/stream_consumer.py):
- StreamConsumerConfig gains transport ('auto'|'draft'|'edit'|'off')
and chat_type fields.
- run() resolves _use_draft_streaming once via a probe at the top of
the run, allocating a fresh class-wide draft_id_counter so each
response animates as its own preview (no animation collision across
consecutive responses to the same chat).
- _send_or_edit gains a pre-edit branch: when drafts are active AND
not finalizing AND no edit-path message_id is established, the
frame routes through _send_draft_frame instead of edit_message.
Drafts intentionally do NOT set _already_sent so the gateway's
final sendMessage path still fires — drafts have no message_id and
the user needs a real message in their chat history.
- _reset_segment_state bumps the draft_id when the consumer is in
draft mode so each text block after a tool boundary animates as a
fresh preview below the tool-progress bubble (avoids the inter-
tool-call leak openclaw documented in their #32535).
- Per-response fallback: any send_draft failure (transient network,
server reject, capability gap) flips _use_draft_streaming to False
for the rest of the run, gracefully returning to the edit path.
Gateway config (gateway/config.py):
- StreamingConfig.transport default flips edit -> auto. The auto path
is identical to edit on every chat type that doesn't currently
support drafts (groups, supergroups, forum topics, every non-
Telegram platform), so the default is backwards-compatible for
non-DM users.
Lifecycle model (Telegram Bot API 9.5):
1. sendMessageDraft(chat_id, draft_id, text='') opens the bubble.
2. Repeated sendMessageDraft calls with the SAME draft_id animate
the preview as text grows.
3. Drafts have no message_id and cannot be edited or deleted.
4. When the response finishes the gateway's normal sendMessage path
delivers the final answer; the draft preview clears naturally on
the client and the user sees a real message in their history.
Inspired by PR #3412 by @NivOO5. Re-authored against current main
(stream_consumer.py is now ~4x larger than at #3412's branch base, with
new _NEW_SEGMENT/_COMMENTARY/finalize/_on_new_message machinery the
original PR didn't account for) but the design call (DM-only, edit-
fallback, transport=auto|draft|edit|off) is faithful to the original
proposal, with two improvements baked in:
1. Per-response draft_id (monotonic counter, not a time hash) — no
collision risk across consecutive responses on the same chat.
2. Tool-boundary draft_id bump — prevents the inter-tool-call leak
openclaw hit during their rollout (their #32535).
Closes #21439 (duplicate feature request).
|
||
|---|---|---|
| .github | ||
| .plans | ||
| acp_adapter | ||
| acp_registry | ||
| agent | ||
| assets | ||
| cron | ||
| datagen-config-examples | ||
| docker | ||
| docs | ||
| environments | ||
| gateway | ||
| hermes_cli | ||
| locales | ||
| nix | ||
| optional-skills | ||
| packaging/homebrew | ||
| plans | ||
| plugins | ||
| providers | ||
| scripts | ||
| skills | ||
| tests | ||
| tinker-atropos@65f084ee80 | ||
| tools | ||
| tui_gateway | ||
| ui-tui | ||
| web | ||
| website | ||
| .dockerignore | ||
| .env.example | ||
| .envrc | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| .mailmap | ||
| AGENTS.md | ||
| batch_runner.py | ||
| cli-config.yaml.example | ||
| cli.py | ||
| constraints-termux.txt | ||
| CONTRIBUTING.md | ||
| docker-compose.yml | ||
| Dockerfile | ||
| flake.lock | ||
| flake.nix | ||
| hermes | ||
| hermes-already-has-routines.md | ||
| hermes_bootstrap.py | ||
| 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 | ||
| README.zh-CN.md | ||
| RELEASE_v0.2.0.md | ||
| RELEASE_v0.3.0.md | ||
| RELEASE_v0.4.0.md | ||
| RELEASE_v0.5.0.md | ||
| RELEASE_v0.6.0.md | ||
| RELEASE_v0.7.0.md | ||
| RELEASE_v0.8.0.md | ||
| RELEASE_v0.9.0.md | ||
| RELEASE_v0.10.0.md | ||
| RELEASE_v0.11.0.md | ||
| RELEASE_v0.12.0.md | ||
| RELEASE_v0.13.0.md | ||
| rl_cli.py | ||
| run_agent.py | ||
| SECURITY.md | ||
| setup-hermes.sh | ||
| toolset_distributions.py | ||
| toolsets.py | ||
| trajectory_compressor.py | ||
| utils.py | ||
| uv.lock | ||
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 | Seven 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-ready | Batch 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~/.hermesas 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
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/) — seeCONTRIBUTING.mdfor the full setup.
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.