Configuration

All settings are stored in the ~/.hermes/ directory for easy access.

Directory Structure

~/.hermes/
├── config.yaml     # Settings (model, terminal, TTS, compression, etc.)
├── .env            # API keys and secrets
├── auth.json       # OAuth provider credentials (Nous Portal, etc.)
├── SOUL.md         # Optional: global persona (agent embodies this personality)
├── memories/       # Persistent memory (MEMORY.md, USER.md)
├── skills/         # Agent-created skills (managed via skill_manage tool)
├── cron/           # Scheduled jobs
├── sessions/       # Gateway sessions
└── logs/           # Logs (errors.log, gateway.log — secrets auto-redacted)

Managing Configuration

hermes config              # View current configuration
hermes config edit         # Open config.yaml in your editor
hermes config set KEY VAL  # Set a specific value
hermes config check        # Check for missing options (after updates)
hermes config migrate      # Interactively add missing options

# Examples:
hermes config set model anthropic/claude-opus-4
hermes config set terminal.backend docker
hermes config set OPENROUTER_API_KEY sk-or-...  # Saves to .env

tip

The hermes config set command automatically routes values to the right file — API keys are saved to .env, everything else to config.yaml.

Configuration Precedence

Settings are resolved in this order (highest priority first):

1. CLI arguments — e.g., hermes chat --model anthropic/claude-sonnet-4 (per-invocation override)
2. ~/.hermes/config.yaml — the primary config file for all non-secret settings
3. ~/.hermes/.env — fallback for env vars; required for secrets (API keys, tokens, passwords)
4. Built-in defaults — hardcoded safe defaults when nothing else is set

Rule of Thumb

Secrets (API keys, bot tokens, passwords) go in .env. Everything else (model, terminal backend, compression settings, memory limits, toolsets) goes in config.yaml. When both are set, config.yaml wins for non-secret settings.

Inference Providers

You need at least one way to connect to an LLM. Use hermes model to switch providers and models interactively, or configure directly:

Provider	Setup
Nous Portal	hermes model (OAuth, subscription-based)
OpenAI Codex	hermes model (ChatGPT OAuth, uses Codex models)
OpenRouter	OPENROUTER_API_KEY in ~/.hermes/.env
Custom Endpoint	OPENAI_BASE_URL + OPENAI_API_KEY in ~/.hermes/.env

Codex Note

The OpenAI Codex provider authenticates via device code (open a URL, enter a code). Credentials are stored at ~/.codex/auth.json and auto-refresh. No Codex CLI installation required.

warning

Even when using Nous Portal, Codex, or a custom endpoint, some tools (vision, web summarization, MoA) use OpenRouter independently. An OPENROUTER_API_KEY enables these tools.

Optional API Keys

Feature	Provider	Env Variable
Web scraping	Firecrawl	FIRECRAWL_API_KEY
Browser automation	Browserbase	BROWSERBASE_API_KEY, BROWSERBASE_PROJECT_ID
Image generation	FAL	FAL_KEY
Premium TTS voices	ElevenLabs	ELEVENLABS_API_KEY
OpenAI TTS + voice transcription	OpenAI	VOICE_TOOLS_OPENAI_KEY
RL Training	Tinker + WandB	TINKER_API_KEY, WANDB_API_KEY
Cross-session user modeling	Honcho	HONCHO_API_KEY

OpenRouter Provider Routing

When using OpenRouter, you can control how requests are routed across providers. Add a provider_routing section to ~/.hermes/config.yaml:

provider_routing:
  sort: "throughput"          # "price" (default), "throughput", or "latency"
  # only: ["anthropic"]      # Only use these providers
  # ignore: ["deepinfra"]    # Skip these providers
  # order: ["anthropic", "google"]  # Try providers in this order
  # require_parameters: true  # Only use providers that support all request params
  # data_collection: "deny"   # Exclude providers that may store/train on data

Shortcuts: Append :nitro to any model name for throughput sorting (e.g., anthropic/claude-sonnet-4:nitro), or :floor for price sorting.

Terminal Backend Configuration

Configure which environment the agent uses for terminal commands:

terminal:
  backend: local    # or: docker, ssh, singularity, modal
  cwd: "."          # Working directory ("." = current dir)
  timeout: 180      # Command timeout in seconds

See Code Execution and the Terminal section of the README for details on each backend.

Memory Configuration

memory:
  memory_enabled: true
  user_profile_enabled: true
  memory_char_limit: 2200   # ~800 tokens
  user_char_limit: 1375     # ~500 tokens

Context Compression

compression:
  enabled: true
  threshold: 0.85    # Compress at 85% of context limit

Reasoning Effort

Control how much "thinking" the model does before responding:

agent:
  reasoning_effort: ""   # empty = use model default. Options: xhigh (max), high, medium, low, minimal, none

When unset (default), the model's own default reasoning level is used. Setting a value overrides it — higher reasoning effort gives better results on complex tasks at the cost of more tokens and latency.

TTS Configuration

tts:
  provider: "edge"              # "edge" | "elevenlabs" | "openai"
  edge:
    voice: "en-US-AriaNeural"   # 322 voices, 74 languages
  elevenlabs:
    voice_id: "pNInz6obpgDQGcFmaJgB"
    model_id: "eleven_multilingual_v2"
  openai:
    model: "gpt-4o-mini-tts"
    voice: "alloy"              # alloy, echo, fable, onyx, nova, shimmer

Display Settings

display:
  tool_progress: all    # off | new | all | verbose
  personality: "kawaii"  # Default personality for the CLI
  compact: false         # Compact output mode (less whitespace)

Mode	What you see
off	Silent — just the final response
new	Tool indicator only when the tool changes
all	Every tool call with a short preview (default)
verbose	Full args, results, and debug logs

Speech-to-Text (STT)

stt:
  provider: "openai"           # STT provider

Requires VOICE_TOOLS_OPENAI_KEY in .env for OpenAI STT.

Human Delay

Simulate human-like response pacing in messaging platforms:

human_delay:
  mode: "off"                  # off | natural | custom
  min_ms: 500                  # Minimum delay (custom mode)
  max_ms: 2000                 # Maximum delay (custom mode)

Code Execution

Configure the sandboxed Python code execution tool:

code_execution:
  timeout: 300                 # Max execution time in seconds
  max_tool_calls: 50           # Max tool calls within code execution

Delegation

Configure subagent behavior for the delegate tool:

delegation:
  max_iterations: 50           # Max iterations per subagent
  default_toolsets:             # Toolsets available to subagents
    - terminal
    - file
    - web

Clarify

Configure the clarification prompt behavior:

clarify:
  timeout: 120                 # Seconds to wait for user clarification response

Context Files (SOUL.md, AGENTS.md)

Drop these files in your project directory and the agent automatically picks them up:

File	Purpose
AGENTS.md	Project-specific instructions, coding conventions
SOUL.md	Persona definition — the agent embodies this personality
.cursorrules	Cursor IDE rules (also detected)
.cursor/rules/*.mdc	Cursor rule files (also detected)

• AGENTS.md is hierarchical: if subdirectories also have AGENTS.md, all are combined.
• SOUL.md checks cwd first, then ~/.hermes/SOUL.md as a global fallback.
• All context files are capped at 20,000 characters with smart truncation.

Working Directory

Context	Default
CLI (hermes)	Current directory where you run the command
Messaging gateway	Home directory ~ (override with MESSAGING_CWD)
Docker / Singularity / Modal / SSH	User's home directory inside the container or remote machine

Override the working directory:

# In ~/.hermes/.env or ~/.hermes/config.yaml:
MESSAGING_CWD=/home/myuser/projects    # Gateway sessions
TERMINAL_CWD=/workspace                # All terminal sessions