e9f05b3524
model_metadata tests (61 tests, was 39):
- Token estimation: concrete value assertions, unicode, tool_call messages,
vision multimodal content, additive verification
- Context length resolution: cache-over-API priority, no-base_url skips cache,
missing context_length key in API response
- API metadata fetch: canonical_slug aliasing, TTL expiry with time mock,
stale cache fallback on API failure, malformed JSON resilience
- Probe tiers: above-max returns 2M, zero returns None
- Error parsing: Anthropic format ('X > Y maximum'), LM Studio, empty string,
unreasonably large numbers — also fixed parser to handle Anthropic format
- Cache: corruption resilience (garbage YAML, wrong structure), value updates,
special chars in model names
Firecrawl config tests (8 tests, was 4):
- Singleton caching (core purpose — verified constructor called once)
- Constructor failure recovery (retry after exception)
- Return value actually asserted (not just constructor args)
- Empty string env vars treated as absent
- Proper setup/teardown for env var isolation
Hermes Agent ⚕
The fully open-source AI agent that grows with you. Install it on a machine, give it your messaging accounts, and it becomes a persistent personal agent — learning your projects, building its own skills, running tasks on a schedule, and reaching you wherever you are.
Use any model you want — Nous Portal, OpenRouter, OpenAI Codex, 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, and CLI — all from a single gateway process. Voice memo transcription, cross-platform conversation continuity. |
| Grows the longer it runs | Persistent memory across sessions. When it solves a hard problem, it writes a skill document for next time. Skills are searchable, shareable, and 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. |
| Real sandboxing | Five terminal backends — local, Docker, SSH, Singularity, and Modal — with persistent workspaces and container security hardening. |
| 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, and WSL2. The installer handles everything — Python, Node.js, dependencies, and the hermes command. No prerequisites except git.
Windows: Native Windows is not supported. Please install WSL2 and run the command above.
After installation:
source ~/.bashrc # reload shell (or: source ~/.zshrc)
hermes setup # configure your LLM provider
hermes # start chatting!
Getting Started
hermes # Interactive CLI — start a conversation
hermes model # Switch provider or model
hermes setup # Re-run the setup wizard
hermes gateway # Start the messaging gateway (Telegram, Discord, etc.)
hermes update # Update to the latest version
hermes doctor # Diagnose any issues
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, 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 |
Contributing
We welcome contributions! See the Contributing Guide for development setup, code style, and PR process.
Quick start for contributors:
git clone --recurse-submodules https://github.com/NousResearch/hermes-agent.git
cd hermes-agent
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]"
uv pip install -e "./mini-swe-agent"
python -m pytest tests/ -q
Community
- 💬 Discord
- 📚 Skills Hub
- 🐛 Issues
- 💡 Discussions
License
MIT — see LICENSE.
Built by Nous Research.