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         # Primary agent identity (slot #1 in system prompt)
├── 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

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

Environment Variable Substitution​

You can reference environment variables in config.yaml using ${VAR_NAME} syntax:

auxiliary:
  vision:
    api_key: ${GOOGLE_API_KEY}
    base_url: ${CUSTOM_VISION_URL}

delegation:
  api_key: ${DELEGATION_KEY}

Multiple references in a single value work: url: "${HOST}:${PORT}". If a referenced variable is not set, the placeholder is kept verbatim (${UNDEFINED_VAR} stays as-is). Only the ${VAR} syntax is supported — bare $VAR is not expanded.

For AI provider setup (OpenRouter, Anthropic, Copilot, custom endpoints, self-hosted LLMs, fallback models, etc.), see AI Providers.

Terminal Backend Configuration​

Hermes supports six terminal backends. Each determines where the agent's shell commands actually execute — your local machine, a Docker container, a remote server via SSH, a Modal cloud sandbox, a Daytona workspace, or a Singularity/Apptainer container.

terminal:
  backend: local    # local | docker | ssh | modal | daytona | singularity
  cwd: "."          # Working directory ("." = current dir for local, "/root" for containers)
  timeout: 180      # Per-command timeout in seconds
  env_passthrough: []  # Env var names to forward to sandboxed execution (terminal + execute_code)
  singularity_image: "docker://nikolaik/python-nodejs:python3.11-nodejs20"  # Container image for Singularity backend
  modal_image: "nikolaik/python-nodejs:python3.11-nodejs20"                 # Container image for Modal backend
  daytona_image: "nikolaik/python-nodejs:python3.11-nodejs20"               # Container image for Daytona backend

Backend Overview​

Local Backend​

The default. Commands run directly on your machine with no isolation. No special setup required.

terminal:
  backend: local

Docker Backend​

Runs commands inside a Docker container with security hardening (all capabilities dropped, no privilege escalation, PID limits).

terminal:
  backend: docker
  docker_image: "nikolaik/python-nodejs:python3.11-nodejs20"
  docker_mount_cwd_to_workspace: false  # Mount launch dir into /workspace
  docker_forward_env:              # Env vars to forward into container
    - "GITHUB_TOKEN"
  docker_volumes:                  # Host directory mounts
    - "/home/user/projects:/workspace/projects"
    - "/home/user/data:/data:ro"   # :ro for read-only

  # Resource limits
  container_cpu: 1                 # CPU cores (0 = unlimited)
  container_memory: 5120           # MB (0 = unlimited)
  container_disk: 51200            # MB (requires overlay2 on XFS+pquota)
  container_persistent: true       # Persist /workspace and /root across sessions

Requirements: Docker Desktop or Docker Engine installed and running. Hermes probes $PATH plus common macOS install locations (/usr/local/bin/docker, /opt/homebrew/bin/docker, Docker Desktop app bundle).

Container lifecycle: Each session starts a long-lived container (docker run -d ... sleep 2h). Commands run via docker exec with a login shell. On cleanup, the container is stopped and removed.

Security hardening:

• --cap-drop ALL with only DAC_OVERRIDE, CHOWN, FOWNER added back
• --security-opt no-new-privileges
• --pids-limit 256
• Size-limited tmpfs for /tmp (512MB), /var/tmp (256MB), /run (64MB)

Credential forwarding: Env vars listed in docker_forward_env are resolved from your shell environment first, then ~/.hermes/.env. Skills can also declare required_environment_variables which are merged automatically.

SSH Backend​

Runs commands on a remote server over SSH. Uses ControlMaster for connection reuse (5-minute idle keepalive). Persistent shell is enabled by default — state (cwd, env vars) survives across commands.

terminal:
  backend: ssh
  persistent_shell: true           # Keep a long-lived bash session (default: true)

Required environment variables:

TERMINAL_SSH_HOST=my-server.example.com
TERMINAL_SSH_USER=ubuntu

Optional:

How it works: Connects at init time with BatchMode=yes and StrictHostKeyChecking=accept-new. Persistent shell keeps a single bash -l process alive on the remote host, communicating via temporary files. Commands that need stdin_data or sudo automatically fall back to one-shot mode.

Modal Backend​

Runs commands in a Modal cloud sandbox. Each task gets an isolated VM with configurable CPU, memory, and disk. Filesystem can be snapshot/restored across sessions.

terminal:
  backend: modal
  container_cpu: 1                 # CPU cores
  container_memory: 5120           # MB (5GB)
  container_disk: 51200            # MB (50GB)
  container_persistent: true       # Snapshot/restore filesystem

Required: Either MODAL_TOKEN_ID + MODAL_TOKEN_SECRET environment variables, or a ~/.modal.toml config file.

Persistence: When enabled, the sandbox filesystem is snapshotted on cleanup and restored on next session. Snapshots are tracked in ~/.hermes/modal_snapshots.json.

Credential files: Automatically mounted from ~/.hermes/ (OAuth tokens, etc.) and synced before each command.

Daytona Backend​

Runs commands in a Daytona managed workspace. Supports stop/resume for persistence.

terminal:
  backend: daytona
  container_cpu: 1                 # CPU cores
  container_memory: 5120           # MB → converted to GiB
  container_disk: 10240            # MB → converted to GiB (max 10 GiB)
  container_persistent: true       # Stop/resume instead of delete

Required: DAYTONA_API_KEY environment variable.

Persistence: When enabled, sandboxes are stopped (not deleted) on cleanup and resumed on next session. Sandbox names follow the pattern hermes-{task_id}.

Disk limit: Daytona enforces a 10 GiB maximum. Requests above this are capped with a warning.

Singularity/Apptainer Backend​

Runs commands in a Singularity/Apptainer container. Designed for HPC clusters and shared machines where Docker isn't available.

terminal:
  backend: singularity
  singularity_image: "docker://nikolaik/python-nodejs:python3.11-nodejs20"
  container_cpu: 1                 # CPU cores
  container_memory: 5120           # MB
  container_persistent: true       # Writable overlay persists across sessions

Requirements: apptainer or singularity binary in $PATH.

Image handling: Docker URLs (docker://...) are automatically converted to SIF files and cached. Existing .sif files are used directly.

Scratch directory: Resolved in order: TERMINAL_SCRATCH_DIR → TERMINAL_SANDBOX_DIR/singularity → /scratch/$USER/hermes-agent (HPC convention) → ~/.hermes/sandboxes/singularity.

Isolation: Uses --containall --no-home for full namespace isolation without mounting the host home directory.

Common Terminal Backend Issues​

If terminal commands fail immediately or the terminal tool is reported as disabled:

• Local — No special requirements. The safest default when getting started.
• Docker — Run docker version to verify Docker is working. If it fails, fix Docker or hermes config set terminal.backend local.
• SSH — Both TERMINAL_SSH_HOST and TERMINAL_SSH_USER must be set. Hermes logs a clear error if either is missing.
• Modal — Needs MODAL_TOKEN_ID env var or ~/.modal.toml. Run hermes doctor to check.
• Daytona — Needs DAYTONA_API_KEY. The Daytona SDK handles server URL configuration.
• Singularity — Needs apptainer or singularity in $PATH. Common on HPC clusters.

When in doubt, set terminal.backend back to local and verify commands run there first.

Docker Volume Mounts​

When using the Docker backend, docker_volumes lets you share host directories with the container. Each entry uses standard Docker -v syntax: host_path:container_path[:options].

terminal:
  backend: docker
  docker_volumes:
    - "/home/user/projects:/workspace/projects"   # Read-write (default)
    - "/home/user/datasets:/data:ro"              # Read-only
    - "/home/user/outputs:/outputs"               # Agent writes, you read

This is useful for:

• Providing files to the agent (datasets, configs, reference code)
• Receiving files from the agent (generated code, reports, exports)
• Shared workspaces where both you and the agent access the same files

Can also be set via environment variable: TERMINAL_DOCKER_VOLUMES='["/host:/container"]' (JSON array).

Docker Credential Forwarding​

By default, Docker terminal sessions do not inherit arbitrary host credentials. If you need a specific token inside the container, add it to terminal.docker_forward_env.

terminal:
  backend: docker
  docker_forward_env:
    - "GITHUB_TOKEN"
    - "NPM_TOKEN"

Hermes resolves each listed variable from your current shell first, then falls back to ~/.hermes/.env if it was saved with hermes config set.

Optional: Mount the Launch Directory into /workspace​

Docker sandboxes stay isolated by default. Hermes does not pass your current host working directory into the container unless you explicitly opt in.

Enable it in config.yaml:

terminal:
  backend: docker
  docker_mount_cwd_to_workspace: true

When enabled:

• if you launch Hermes from ~/projects/my-app, that host directory is bind-mounted to /workspace
• the Docker backend starts in /workspace
• file tools and terminal commands both see the same mounted project

When disabled, /workspace stays sandbox-owned unless you explicitly mount something via docker_volumes.

Security tradeoff:

• false preserves the sandbox boundary
• true gives the sandbox direct access to the directory you launched Hermes from

Use the opt-in only when you intentionally want the container to work on live host files.

Persistent Shell​

By default, each terminal command runs in its own subprocess — working directory, environment variables, and shell variables reset between commands. When persistent shell is enabled, a single long-lived bash process is kept alive across execute() calls so that state survives between commands.

This is most useful for the SSH backend, where it also eliminates per-command connection overhead. Persistent shell is enabled by default for SSH and disabled for the local backend.

terminal:
  persistent_shell: true   # default — enables persistent shell for SSH

To disable:

hermes config set terminal.persistent_shell false

What persists across commands:

• Working directory (cd /tmp sticks for the next command)
• Exported environment variables (export FOO=bar)
• Shell variables (MY_VAR=hello)

Precedence:

Per-backend environment variables take highest precedence. If you want persistent shell on the local backend too:

export TERMINAL_LOCAL_PERSISTENT=true

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

File Read Safety​

Controls how much content a single read_file call can return. Reads that exceed the limit are rejected with an error telling the agent to use offset and limit for a smaller range. This prevents a single read of a minified JS bundle or large data file from flooding the context window.

file_read_max_chars: 100000  # default — ~25-35K tokens

Raise it if you're on a model with a large context window and frequently read big files. Lower it for small-context models to keep reads efficient:

# Large context model (200K+)
file_read_max_chars: 200000

# Small local model (16K context)
file_read_max_chars: 30000

The agent also deduplicates file reads automatically — if the same file region is read twice and the file hasn't changed, a lightweight stub is returned instead of re-sending the content. This resets on context compression so the agent can re-read files after their content is summarized away.

Git Worktree Isolation​

Enable isolated git worktrees for running multiple agents in parallel on the same repo:

worktree: true    # Always create a worktree (same as hermes -w)
# worktree: false # Default — only when -w flag is passed

When enabled, each CLI session creates a fresh worktree under .worktrees/ with its own branch. Agents can edit files, commit, push, and create PRs without interfering with each other. Clean worktrees are removed on exit; dirty ones are kept for manual recovery.

You can also list gitignored files to copy into worktrees via .worktreeinclude in your repo root:

# .worktreeinclude
.env
.venv/
node_modules/

Context Compression​

Hermes automatically compresses long conversations to stay within your model's context window. The compression summarizer is a separate LLM call — you can point it at any provider or endpoint.

All compression settings live in config.yaml (no environment variables).

Full reference​

compression:
  enabled: true                                     # Toggle compression on/off
  threshold: 0.50                                   # Compress at this % of context limit
  target_ratio: 0.20                                # Fraction of threshold to preserve as recent tail
  protect_last_n: 20                                # Min recent messages to keep uncompressed
  summary_model: "google/gemini-3-flash-preview"    # Model for summarization
  summary_provider: "auto"                          # Provider: "auto", "openrouter", "nous", "codex", "main", etc.
  summary_base_url: null                            # Custom OpenAI-compatible endpoint (overrides provider)

Common setups​

Default (auto-detect) — no configuration needed:

compression:
  enabled: true
  threshold: 0.50

Uses the first available provider (OpenRouter → Nous → Codex) with Gemini Flash.

Force a specific provider (OAuth or API-key based):

compression:
  summary_provider: nous
  summary_model: gemini-3-flash

Works with any provider: nous, openrouter, codex, anthropic, main, etc.

Custom endpoint (self-hosted, Ollama, zai, DeepSeek, etc.):

compression:
  summary_model: glm-4.7
  summary_base_url: https://api.z.ai/api/coding/paas/v4

Points at a custom OpenAI-compatible endpoint. Uses OPENAI_API_KEY for auth.

How the three knobs interact​

The summary_model must support a context length at least as large as your main model's, since it receives the full middle section of the conversation for compression.

Iteration Budget Pressure​

When the agent is working on a complex task with many tool calls, it can burn through its iteration budget (default: 90 turns) without realizing it's running low. Budget pressure automatically warns the model as it approaches the limit:

Warnings are injected into the last tool result's JSON (as a _budget_warning field) rather than as separate messages — this preserves prompt caching and doesn't disrupt the conversation structure.

agent:
  max_turns: 90                # Max iterations per conversation turn (default: 90)

Budget pressure is enabled by default. The agent sees warnings naturally as part of tool results, encouraging it to consolidate its work and deliver a response before running out of iterations.

Context Pressure Warnings​

Separate from iteration budget pressure, context pressure tracks how close the conversation is to the compaction threshold — the point where context compression fires to summarize older messages. This helps both you and the agent understand when the conversation is getting long.

In the CLI, context pressure appears as a progress bar in the tool output feed:

  ◐ context ████████████░░░░░░░░ 62% to compaction  48k threshold (50%) · approaching compaction

On messaging platforms, a plain-text notification is sent:

◐ Context: ████████████░░░░░░░░ 62% to compaction (threshold: 50% of window).

If auto-compression is disabled, the warning tells you context may be truncated instead.

Context pressure is automatic — no configuration needed. It fires purely as a user-facing notification and does not modify the message stream or inject anything into the model's context.

Credential Pool Strategies​

When you have multiple API keys or OAuth tokens for the same provider, configure the rotation strategy:

credential_pool_strategies:
  openrouter: round_robin    # cycle through keys evenly
  anthropic: least_used      # always pick the least-used key

Options: fill_first (default), round_robin, least_used, random. See Credential Pools for full documentation.

Auxiliary Models​

Hermes uses lightweight "auxiliary" models for side tasks like image analysis, web page summarization, and browser screenshot analysis. By default, these use Gemini Flash via auto-detection — you don't need to configure anything.

The universal config pattern​

Every model slot in Hermes — auxiliary tasks, compression, fallback — uses the same three knobs:

When base_url is set, Hermes ignores the provider and calls that endpoint directly (using api_key or OPENAI_API_KEY for auth). When only provider is set, Hermes uses that provider's built-in auth and base URL.

Available providers: auto, openrouter, nous, codex, copilot, anthropic, main, zai, kimi-coding, minimax, and any provider registered in the provider registry.

Full auxiliary config reference​

auxiliary:
  # Image analysis (vision_analyze tool + browser screenshots)
  vision:
    provider: "auto"           # "auto", "openrouter", "nous", "codex", "main", etc.
    model: ""                  # e.g. "openai/gpt-4o", "google/gemini-2.5-flash"
    base_url: ""               # Custom OpenAI-compatible endpoint (overrides provider)
    api_key: ""                # API key for base_url (falls back to OPENAI_API_KEY)
    timeout: 30                # seconds — LLM API call; increase for slow local vision models
    download_timeout: 30       # seconds — image HTTP download; increase for slow connections

  # Web page summarization + browser page text extraction
  web_extract:
    provider: "auto"
    model: ""                  # e.g. "google/gemini-2.5-flash"
    base_url: ""
    api_key: ""
    timeout: 30                # seconds

  # Dangerous command approval classifier
  approval:
    provider: "auto"
    model: ""
    base_url: ""
    api_key: ""
    timeout: 30                # seconds

  # Context compression timeout (separate from compression.* config)
  compression:
    timeout: 120               # seconds — compression summarizes long conversations, needs more time

  # Session search — summarizes past session matches
  session_search:
    provider: "auto"
    model: ""
    base_url: ""
    api_key: ""
    timeout: 30

  # Skills hub — skill matching and search
  skills_hub:
    provider: "auto"
    model: ""
    base_url: ""
    api_key: ""
    timeout: 30

  # MCP tool dispatch
  mcp:
    provider: "auto"
    model: ""
    base_url: ""
    api_key: ""
    timeout: 30

  # Memory flush — summarizes conversation for persistent memory
  flush_memories:
    provider: "auto"
    model: ""
    base_url: ""
    api_key: ""
    timeout: 30

Changing the Vision Model​

To use GPT-4o instead of Gemini Flash for image analysis:

auxiliary:
  vision:
    model: "openai/gpt-4o"

Or via environment variable (in ~/.hermes/.env):

AUXILIARY_VISION_MODEL=openai/gpt-4o

Provider Options​

Common Setups​

Using a direct custom endpoint (clearer than provider: "main" for local/self-hosted APIs):

auxiliary:
  vision:
    base_url: "http://localhost:1234/v1"
    api_key: "local-key"
    model: "qwen2.5-vl"

base_url takes precedence over provider, so this is the most explicit way to route an auxiliary task to a specific endpoint. For direct endpoint overrides, Hermes uses the configured api_key or falls back to OPENAI_API_KEY; it does not reuse OPENROUTER_API_KEY for that custom endpoint.

Using OpenAI API key for vision:

# In ~/.hermes/.env:
# OPENAI_BASE_URL=https://api.openai.com/v1
# OPENAI_API_KEY=sk-...

auxiliary:
  vision:
    provider: "main"
    model: "gpt-4o"       # or "gpt-4o-mini" for cheaper

Using OpenRouter for vision (route to any model):

auxiliary:
  vision:
    provider: "openrouter"
    model: "openai/gpt-4o"      # or "google/gemini-2.5-flash", etc.

Using Codex OAuth (ChatGPT Pro/Plus account — no API key needed):

auxiliary:
  vision:
    provider: "codex"     # uses your ChatGPT OAuth token
    # model defaults to gpt-5.3-codex (supports vision)

Using a local/self-hosted model:

auxiliary:
  vision:
    provider: "main"      # uses your active custom endpoint
    model: "my-local-model"

provider: "main" follows the same custom endpoint Hermes uses for normal chat. That endpoint can be set directly with OPENAI_BASE_URL, or saved once through hermes model and persisted in config.yaml.

Environment Variables (legacy)​

Auxiliary models can also be configured via environment variables. However, config.yaml is the preferred method — it's easier to manage and supports all options including base_url and api_key.

Compression and fallback model settings are config.yaml-only.

Reasoning Effort​

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

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

When unset (default), reasoning effort defaults to "medium" — a balanced level that works well for most tasks. Setting a value overrides it — higher reasoning effort gives better results on complex tasks at the cost of more tokens and latency.

You can also change the reasoning effort at runtime with the /reasoning command:

/reasoning           # Show current effort level and display state
/reasoning high      # Set reasoning effort to high
/reasoning none      # Disable reasoning
/reasoning show      # Show model thinking above each response
/reasoning hide      # Hide model thinking

Tool-Use Enforcement​

Some models (especially GPT-family) occasionally describe intended actions as text instead of making tool calls. Tool-use enforcement injects guidance that steers the model back to actually calling tools.

agent:
  tool_use_enforcement: "auto"   # "auto" | true | false | ["model-substring", ...]

When enabled, the system prompt includes guidance reminding the model to make actual tool calls rather than describing what it would do. This is transparent to the user and has no effect on models that already use tools reliably.

TTS Configuration​

tts:
  provider: "edge"              # "edge" | "elevenlabs" | "openai" | "neutts"
  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
    base_url: "https://api.openai.com/v1"  # Override for OpenAI-compatible TTS endpoints
  neutts:
    ref_audio: ''
    ref_text: ''
    model: neuphonic/neutts-air-q4-gguf
    device: cpu

This controls both the text_to_speech tool and spoken replies in voice mode (/voice tts in the CLI or messaging gateway).

Display Settings​

display:
  tool_progress: all      # off | new | all | verbose
  tool_progress_command: false  # Enable /verbose slash command in messaging gateway
  skin: default           # Built-in or custom CLI skin (see user-guide/features/skins)
  theme_mode: auto        # auto | light | dark — color scheme for skin-aware rendering
  personality: "kawaii"  # Legacy cosmetic field still surfaced in some summaries
  compact: false          # Compact output mode (less whitespace)
  resume_display: full    # full (show previous messages on resume) | minimal (one-liner only)
  bell_on_complete: false # Play terminal bell when agent finishes (great for long tasks)
  show_reasoning: false   # Show model reasoning/thinking above each response (toggle with /reasoning show|hide)
  streaming: false        # Stream tokens to terminal as they arrive (real-time output)
  background_process_notifications: all  # all | result | error | off (gateway only)
  show_cost: false        # Show estimated $ cost in the CLI status bar
  tool_preview_length: 0  # Max chars for tool call previews (0 = no limit, show full paths/commands)

Theme mode​

The theme_mode setting controls whether skins render in light or dark mode:

This works with any skin — built-in or custom. Skin authors can provide colors_light in their skin definition for optimal light-terminal appearance.

In the CLI, cycle through these modes with /verbose. To use /verbose in messaging platforms (Telegram, Discord, Slack, etc.), set tool_progress_command: true in the display section above. The command will then cycle the mode and save to config.

Privacy​

privacy:
  redact_pii: false  # Strip PII from LLM context (gateway only)

When redact_pii is true, the gateway redacts personally identifiable information from the system prompt before sending it to the LLM on supported platforms:

Platform support: Redaction applies to WhatsApp, Signal, and Telegram. Discord and Slack are excluded because their mention systems (<@user_id>) require the real ID in the LLM context.

Hashes are deterministic — the same user always maps to the same hash, so the model can still distinguish between users in group chats. Routing and delivery use the original values internally.

Speech-to-Text (STT)​

stt:
  provider: "local"            # "local" | "groq" | "openai"
  local:
    model: "base"              # tiny, base, small, medium, large-v3
  openai:
    model: "whisper-1"         # whisper-1 | gpt-4o-mini-transcribe | gpt-4o-transcribe
  # model: "whisper-1"         # Legacy fallback key still respected

Provider behavior:

• local uses faster-whisper running on your machine. Install it separately with pip install faster-whisper.
• groq uses Groq's Whisper-compatible endpoint and reads GROQ_API_KEY.
• openai uses the OpenAI speech API and reads VOICE_TOOLS_OPENAI_KEY.

If the requested provider is unavailable, Hermes falls back automatically in this order: local → groq → openai.

Groq and OpenAI model overrides are environment-driven:

STT_GROQ_MODEL=whisper-large-v3-turbo
STT_OPENAI_MODEL=whisper-1
GROQ_BASE_URL=https://api.groq.com/openai/v1
STT_OPENAI_BASE_URL=https://api.openai.com/v1

Voice Mode (CLI)​

voice:
  record_key: "ctrl+b"         # Push-to-talk key inside the CLI
  max_recording_seconds: 120    # Hard stop for long recordings
  auto_tts: false               # Enable spoken replies automatically when /voice on
  silence_threshold: 200        # RMS threshold for speech detection
  silence_duration: 3.0         # Seconds of silence before auto-stop

Use /voice on in the CLI to enable microphone mode, record_key to start/stop recording, and /voice tts to toggle spoken replies. See Voice Mode for end-to-end setup and platform-specific behavior.

Streaming​

Stream tokens to the terminal or messaging platforms as they arrive, instead of waiting for the full response.

CLI Streaming​

display:
  streaming: true         # Stream tokens to terminal in real-time
  show_reasoning: true    # Also stream reasoning/thinking tokens (optional)

When enabled, responses appear token-by-token inside a streaming box. Tool calls are still captured silently. If the provider doesn't support streaming, it falls back to the normal display automatically.

Gateway Streaming (Telegram, Discord, Slack)​

streaming:
  enabled: true           # Enable progressive message editing
  transport: edit         # "edit" (progressive message editing) or "off"
  edit_interval: 0.3      # Seconds between message edits
  buffer_threshold: 40    # Characters before forcing an edit flush
  cursor: " ▉"            # Cursor shown during streaming

When enabled, the bot sends a message on the first token, then progressively edits it as more tokens arrive. Platforms that don't support message editing (Signal, Email, Home Assistant) are auto-detected on the first attempt — streaming is gracefully disabled for that session with no flood of messages.

Overflow handling: If the streamed text exceeds the platform's message length limit (~4096 chars), the current message is finalized and a new one starts automatically.

Group Chat Session Isolation​

Control whether shared chats keep one conversation per room or one conversation per participant:

group_sessions_per_user: true  # true = per-user isolation in groups/channels, false = one shared session per chat

• true is the default and recommended setting. In Discord channels, Telegram groups, Slack channels, and similar shared contexts, each sender gets their own session when the platform provides a user ID.
• false reverts to the old shared-room behavior. That can be useful if you explicitly want Hermes to treat a channel like one collaborative conversation, but it also means users share context, token costs, and interrupt state.
• Direct messages are unaffected. Hermes still keys DMs by chat/DM ID as usual.
• Threads stay isolated from their parent channel either way; with true, each participant also gets their own session inside the thread.

For the behavior details and examples, see Sessions and the Discord guide.

Unauthorized DM Behavior​

Control what Hermes does when an unknown user sends a direct message:

unauthorized_dm_behavior: pair

whatsapp:
  unauthorized_dm_behavior: ignore

• pair is the default. Hermes denies access, but replies with a one-time pairing code in DMs.
• ignore silently drops unauthorized DMs.
• Platform sections override the global default, so you can keep pairing enabled broadly while making one platform quieter.

Quick Commands​

Define custom commands that run shell commands without invoking the LLM — zero token usage, instant execution. Especially useful from messaging platforms (Telegram, Discord, etc.) for quick server checks or utility scripts.

quick_commands:
  status:
    type: exec
    command: systemctl status hermes-agent
  disk:
    type: exec
    command: df -h /
  update:
    type: exec
    command: cd ~/.hermes/hermes-agent && git pull && pip install -e .
  gpu:
    type: exec
    command: nvidia-smi --query-gpu=name,utilization.gpu,memory.used,memory.total --format=csv,noheader

Usage: type /status, /disk, /update, or /gpu in the CLI or any messaging platform. The command runs locally on the host and returns the output directly — no LLM call, no tokens consumed.

• 30-second timeout — long-running commands are killed with an error message
• Priority — quick commands are checked before skill commands, so you can override skill names
• Autocomplete — quick commands are resolved at dispatch time and are not shown in the built-in slash-command autocomplete tables
• Type — only exec is supported (runs a shell command); other types show an error
• Works everywhere — CLI, Telegram, Discord, Slack, WhatsApp, Signal, Email, Home Assistant

Human Delay​

Simulate human-like response pacing in messaging platforms:

human_delay:
  mode: "off"                  # off | natural | custom
  min_ms: 800                  # Minimum delay (custom mode)
  max_ms: 2500                 # 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

Web Search Backends​

The web_search, web_extract, and web_crawl tools support four backend providers. Configure the backend in config.yaml or via hermes tools:

web:
  backend: firecrawl    # firecrawl | parallel | tavily | exa

Backend selection: If web.backend is not set, the backend is auto-detected from available API keys. If only EXA_API_KEY is set, Exa is used. If only TAVILY_API_KEY is set, Tavily is used. If only PARALLEL_API_KEY is set, Parallel is used. Otherwise Firecrawl is the default.

Self-hosted Firecrawl: Set FIRECRAWL_API_URL to point at your own instance. When a custom URL is set, the API key becomes optional (set USE_DB_AUTHENTICATION=false on the server to disable auth).

Parallel search modes: Set PARALLEL_SEARCH_MODE to control search behavior — fast, one-shot, or agentic (default: agentic).

Browser​

Configure browser automation behavior:

browser:
  inactivity_timeout: 120        # Seconds before auto-closing idle sessions
  command_timeout: 30             # Timeout in seconds for browser commands (screenshot, navigate, etc.)
  record_sessions: false         # Auto-record browser sessions as WebM videos to ~/.hermes/browser_recordings/

The browser toolset supports multiple providers. See the Browser feature page for details on Browserbase, Browser Use, and local Chrome CDP setup.

Timezone​

Override the server-local timezone with an IANA timezone string. Affects timestamps in logs, cron scheduling, and system prompt time injection.

timezone: "America/New_York"   # IANA timezone (default: "" = server-local time)

Supported values: any IANA timezone identifier (e.g. America/New_York, Europe/London, Asia/Kolkata, UTC). Leave empty or omit for server-local time.

Discord​

Configure Discord-specific behavior for the messaging gateway:

discord:
  require_mention: true          # Require @mention to respond in server channels
  free_response_channels: ""     # Comma-separated channel IDs where bot responds without @mention
  auto_thread: true              # Auto-create threads on @mention in channels

• require_mention — when true (default), the bot only responds in server channels when mentioned with @BotName. DMs always work without mention.
• free_response_channels — comma-separated list of channel IDs where the bot responds to every message without requiring a mention.
• auto_thread — when true (default), mentions in channels automatically create a thread for the conversation, keeping channels clean (similar to Slack threading).

Security​

Pre-execution security scanning and secret redaction:

security:
  redact_secrets: true           # Redact API key patterns in tool output and logs
  tirith_enabled: true           # Enable Tirith security scanning for terminal commands
  tirith_path: "tirith"          # Path to tirith binary (default: "tirith" in $PATH)
  tirith_timeout: 5              # Seconds to wait for tirith scan before timing out
  tirith_fail_open: true         # Allow command execution if tirith is unavailable
  website_blocklist:             # See Website Blocklist section below
    enabled: false
    domains: []
    shared_files: []

• redact_secrets — automatically detects and redacts patterns that look like API keys, tokens, and passwords in tool output before it enters the conversation context and logs.
• tirith_enabled — when true, terminal commands are scanned by Tirith before execution to detect potentially dangerous operations.
• tirith_path — path to the tirith binary. Set this if tirith is installed in a non-standard location.
• tirith_timeout — maximum seconds to wait for a tirith scan. Commands proceed if the scan times out.
• tirith_fail_open — when true (default), commands are allowed to execute if tirith is unavailable or fails. Set to false to block commands when tirith cannot verify them.

Website Blocklist​

Block specific domains from being accessed by the agent's web and browser tools:

security:
  website_blocklist:
    enabled: false               # Enable URL blocking (default: false)
    domains:                     # List of blocked domain patterns
      - "*.internal.company.com"
      - "admin.example.com"
      - "*.local"
    shared_files:                # Load additional rules from external files
      - "/etc/hermes/blocked-sites.txt"

When enabled, any URL matching a blocked domain pattern is rejected before the web or browser tool executes. This applies to web_search, web_extract, browser_navigate, and any tool that accesses URLs.

Domain rules support:

• Exact domains: admin.example.com
• Wildcard subdomains: *.internal.company.com (blocks all subdomains)
• TLD wildcards: *.local

Shared files contain one domain rule per line (blank lines and # comments are ignored). Missing or unreadable files log a warning but don't disable other web tools.

The policy is cached for 30 seconds, so config changes take effect quickly without restart.

Smart Approvals​

Control how Hermes handles potentially dangerous commands:

approvals:
  mode: manual   # manual | smart | off

Smart mode is particularly useful for reducing approval fatigue — it lets the agent work more autonomously on safe operations while still catching genuinely destructive commands.

Checkpoints​

Automatic filesystem snapshots before destructive file operations. See the Checkpoints & Rollback for details.

checkpoints:
  enabled: true                  # Enable automatic checkpoints (also: hermes --checkpoints)
  max_snapshots: 50              # Max checkpoints to keep per directory

Delegation​

Configure subagent behavior for the delegate tool:

delegation:
  # model: "google/gemini-3-flash-preview"  # Override model (empty = inherit parent)
  # provider: "openrouter"                  # Override provider (empty = inherit parent)
  # base_url: "http://localhost:1234/v1"    # Direct OpenAI-compatible endpoint (takes precedence over provider)
  # api_key: "local-key"                    # API key for base_url (falls back to OPENAI_API_KEY)

Subagent provider:model override: By default, subagents inherit the parent agent's provider and model. Set delegation.provider and delegation.model to route subagents to a different provider:model pair — e.g., use a cheap/fast model for narrowly-scoped subtasks while your primary agent runs an expensive reasoning model.

Direct endpoint override: If you want the obvious custom-endpoint path, set delegation.base_url, delegation.api_key, and delegation.model. That sends subagents directly to that OpenAI-compatible endpoint and takes precedence over delegation.provider. If delegation.api_key is omitted, Hermes falls back to OPENAI_API_KEY only.

The delegation provider uses the same credential resolution as CLI/gateway startup. All configured providers are supported: openrouter, nous, copilot, zai, kimi-coding, minimax, minimax-cn. When a provider is set, the system automatically resolves the correct base URL, API key, and API mode — no manual credential wiring needed.

Precedence: delegation.base_url in config → delegation.provider in config → parent provider (inherited). delegation.model in config → parent model (inherited). Setting just model without provider changes only the model name while keeping the parent's credentials (useful for switching models within the same provider like OpenRouter).

Clarify​

Configure the clarification prompt behavior:

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

Context Files (SOUL.md, AGENTS.md)​

Hermes uses two different context scopes:

• SOUL.md is the agent's primary identity. It occupies slot #1 in the system prompt, completely replacing the built-in default identity. Edit it to fully customize who the agent is.
• If SOUL.md is missing, empty, or cannot be loaded, Hermes falls back to a built-in default identity.
• Project context files use a priority system — only ONE type is loaded (first match wins): .hermes.md → AGENTS.md → CLAUDE.md → .cursorrules. SOUL.md is always loaded independently.
• AGENTS.md is hierarchical: if subdirectories also have AGENTS.md, all are combined.
• Hermes automatically seeds a default SOUL.md if one does not already exist.
• All loaded context files are capped at 20,000 characters with smart truncation.

See also:

• Personality & SOUL.md
• Context Files

Working Directory​

Override the working directory:

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