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f683132c1d
OpenAI-compatible clients (Open WebUI, LobeChat, etc.) can now send vision
requests to the API server. Both endpoints accept the canonical OpenAI
multimodal shape:
Chat Completions: {type: text|image_url, image_url: {url, detail?}}
Responses: {type: input_text|input_image, image_url: <str>, detail?}
The server validates and converts both into a single internal shape that the
existing agent pipeline already handles (Anthropic adapter converts,
OpenAI-wire providers pass through). Remote http(s) URLs and data:image/*
URLs are supported.
Uploaded files (file, input_file, file_id) and non-image data: URLs are
rejected with 400 unsupported_content_type.
Changes:
- gateway/platforms/api_server.py
- _normalize_multimodal_content(): validates + normalizes both Chat and
Responses content shapes. Returns a plain string for text-only content
(preserves prompt-cache behavior on existing callers) or a canonical
[{type:text|image_url,...}] list when images are present.
- _content_has_visible_payload(): replaces the bare truthy check so a
user turn with only an image no longer rejects as 'No user message'.
- _handle_chat_completions and _handle_responses both call the new helper
for user/assistant content; system messages continue to flatten to text.
- Codex conversation_history, input[], and inline history paths all share
the same validator. No duplicated normalizers.
- run_agent.py
- _summarize_user_message_for_log(): produces a short string summary
('[1 image] describe this') from list content for logging, spinner
previews, and trajectory writes. Fixes AttributeError when list
user_message hit user_message[:80] + '...' / .replace().
- _chat_content_to_responses_parts(): module-level helper that converts
chat-style multimodal content to Responses 'input_text'/'input_image'
parts. Used in _chat_messages_to_responses_input for Codex routing.
- _preflight_codex_input_items() now validates and passes through list
content parts for user/assistant messages instead of stringifying.
- tests/gateway/test_api_server_multimodal.py (new, 38 tests)
- Unit coverage for _normalize_multimodal_content, including both part
formats, data URL gating, and all reject paths.
- Real aiohttp HTTP integration on /v1/chat/completions and /v1/responses
verifying multimodal payloads reach _run_agent intact.
- 400 coverage for file / input_file / non-image data URL.
- tests/run_agent/test_run_agent_multimodal_prologue.py (new)
- Regression coverage for the prologue no-crash contract.
- _chat_content_to_responses_parts round-trip coverage.
- website/docs/user-guide/features/api-server.md
- Inline image examples for both endpoints.
- Updated Limitations: files still unsupported, images now supported.
Validated live against openrouter/anthropic/claude-opus-4.6:
POST /v1/chat/completions → 200, vision-accurate description
POST /v1/responses → 200, same image, clean output_text
POST /v1/chat/completions [file] → 400 unsupported_content_type
POST /v1/responses [input_file] → 400 unsupported_content_type
POST /v1/responses [non-image data URL] → 400 unsupported_content_type
Closes #5621, #8253, #4046, #6632.
Co-authored-by: Paul Bergeron <paul@gamma.app>
Co-authored-by: zhangxicen <zhangxicen@example.com>
Co-authored-by: Manuel Schipper <manuelschipper@users.noreply.github.com>
Co-authored-by: pradeep7127 <pradeep7127@users.noreply.github.com>
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| .plans | ||
| acp_adapter | ||
| acp_registry | ||
| agent | ||
| assets | ||
| cron | ||
| datagen-config-examples | ||
| docker | ||
| environments | ||
| gateway | ||
| hermes_cli | ||
| nix | ||
| optional-skills | ||
| packaging/homebrew | ||
| plans | ||
| plugins | ||
| 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 | ||
| 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 | ||
| 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 | ||
| requirements.txt | ||
| 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 | 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> |
/skills or /<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]"
python -m pytest tests/ -q
RL Training (optional): To work on the RL/Tinker-Atropos integration:
git submodule update --init tinker-atropos uv pip install -e "./tinker-atropos"
Community
- 💬 Discord
- 📚 Skills Hub
- 🐛 Issues
- 💡 Discussions
- 🔌 HermesClaw — Community WeChat bridge: Run Hermes Agent and OpenClaw on the same WeChat account.
License
MIT — see LICENSE.
Built by Nous Research.