integration

.env.example

@@ -144,12 +144,87 @@ TERMINAL_LIFETIME_SECONDS=300
 # SUDO_PASSWORD=your_password_here
 
 # =============================================================================
-# MODAL CLOUD BACKEND (Optional - for TERMINAL_ENV=modal)
+# MODAL CLOUD BACKEND (for TERMINAL_ENV=modal)
 # =============================================================================
-# Modal uses CLI authentication, not environment variables.
-# Run: pip install modal && modal setup
-# This will authenticate via browser and store credentials locally.
-# No API key needed in .env - Modal handles auth automatically.
+# Modal provides cloud sandboxes with per-second billing and auto-scaling.
+# This implementation uses a warm pool of sandboxes for cost efficiency.
+#
+# SETUP:
+#   pip install modal && modal setup
+#   (Authenticates via browser, stores credentials locally)
+#
+# FEATURES:
+# - Auto-scaling warm sandbox pool (no cold start after first use)
+# - Named sandbox recovery (reconnects after restart)
+# - Profile-based heterogeneous environments (CPU, GPU, different images)
+# - Server-side idle_timeout protection against orphaned sandboxes
+
+# Modal app name (groups all sandboxes, used for recovery)
+TERMINAL_MODAL_APP_NAME=hermes-sandbox
+
+# Default profile when none specified
+TERMINAL_MODAL_DEFAULT_PROFILE=default
+
+# Profile config file (optional - YAML format, see modal_profiles.yaml)
+# TERMINAL_MODAL_PROFILES_FILE=modal_profiles.yaml
+
+# --- Default Profile Settings (used if no YAML file) ---
+# These apply when no profile is specified or for the "default" profile
+TERMINAL_MODAL_IMAGE=python:3.11
+TERMINAL_MODAL_MIN_POOL=1
+TERMINAL_MODAL_MAX_POOL=5
+TERMINAL_MODAL_IDLE_TIMEOUT=120
+TERMINAL_MODAL_MAX_LIFETIME=3600
+TERMINAL_MODAL_SCALE_DOWN_IDLE=180
+
+# --- Custom Profile Example: pytorch-gpu ---
+# Uncomment to enable a GPU profile for ML tasks
+# Usage: terminal_tool("python train.py", profile="pytorch-gpu")
+#
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_IMAGE=pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_GPU=T4
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_MEMORY=16384
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_MIN_POOL=0
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_MAX_POOL=2
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_IDLE_TIMEOUT=60
+
+# --- Custom Profile Example: node ---
+# Uncomment to enable a Node.js profile
+# Usage: terminal_tool("npm test", profile="node")
+#
+# TERMINAL_MODAL_PROFILE_node_IMAGE=node:18
+# TERMINAL_MODAL_PROFILE_node_MIN_POOL=0
+# TERMINAL_MODAL_PROFILE_node_MAX_POOL=3
+
+# =============================================================================
+# MODAL SECRETS (Secure credential injection)
+# =============================================================================
+# Modal Secrets allow you to securely pass API keys, passwords, and other
+# sensitive data to your sandboxes without exposing them in code or logs.
+#
+# SETUP SECRETS:
+#   1. Via Dashboard: https://modal.com/secrets
+#   2. Via CLI: modal secret create my-secret KEY1=value1 KEY2=value2
+#   3. Via CLI with env: modal secret create my-secret API_KEY="$API_KEY"
+#
+# LIST SECRETS:
+#   modal secret list
+#
+# DELETE SECRETS:
+#   modal secret delete my-secret
+
+# Global secrets applied to ALL profiles (comma-separated secret names)
+# These secrets must be created on Modal dashboard or via CLI first
+# TERMINAL_MODAL_SECRETS=my-api-keys,database-creds
+
+# Per-profile secrets (comma-separated secret names)
+# TERMINAL_MODAL_PROFILE_pytorch_gpu_SECRETS=huggingface-token,wandb-key
+
+# Per-profile environment variables (semicolon-separated KEY=VALUE pairs)
+# TERMINAL_MODAL_PROFILE_default_ENV_VARS=DEBUG=1;LOG_LEVEL=info
+
+# Load local .env file into sandbox (useful for development)
+# TERMINAL_MODAL_PROFILE_default_USE_DOTENV=true
 
 # =============================================================================
 # BROWSER TOOL CONFIGURATION (agent-browser + Browserbase)