config.toml.example

# OpenCrabs Configuration File
# Copy this file to one of these locations:
#   - Linux/macOS: ~/.opencrabs/config.toml
#   - Windows: %APPDATA%\opencrabs\config.toml or opencrabs\config.toml
#
# IMPORTANT: API keys should NOT be stored here!
# Instead, store API keys in keys.toml (chmod 600) for security:
#   - ~/.opencrabs/keys.toml
# Keys in keys.toml take priority over this file.

[database]
# Database file location (stores conversation history)
# path = "~/.opencrabs/opencrabs.db"  # Default; only override if needed

[providers]
# ========================================
# Custom: OpenAI-Compatible Provider (Local LLMs, and any OpenAI Compatible model)
# ========================================
# Use this for LM Studio, Ollama, LocalAI, etc.
# Every custom provider needs a name — the label after "custom." (e.g. lm_studio, nvidia, groq).
# You can define as many as you need and switch between them via /models.
[providers.custom.lm_studio]
enabled = true
base_url = "http://localhost:1234/v1/chat/completions"  # LM Studio default
models = ["kimi-k2.5", "glm-5", "MiniMax-M2.5", "qwen3-coder", "gpt-oss-120b", "llama-4-70B", "mistral-Large-3", "qwen3-coder-next"]

# ⭐ IMPORTANT: Set this to match the model name loaded in LM Studio!
# Common examples:
#   - qwen2.5-coder-7b-instruct
#   - codellama-7b-instruct
#   - deepseek-coder-6.7b-instruct
#   - llama-3.2-1b-instruct
default_model = "qwen3-coder-next"

# Other local LLM servers — just add another named section:
#
# [providers.custom.ollama]
# enabled = false
# base_url = "http://localhost:11434/v1/chat/completions"
# default_model = "mistral"
# models = ["mistral", "llama3", "codellama"]

# ========================================
# Official OpenAI Provider
# ========================================
[providers.openai]
enabled = false
default_model = "gpt-4o"  # Optional: override default model

# ========================================
# Anthropic Provider (Claude)
# ========================================
[providers.anthropic]
enabled = false
default_model = "claude-sonnet-4-6"  # Optional: override default

# ========================================
# OpenRouter Provider (100+ models via OpenAI-compatible API)
# ========================================
[providers.openrouter]
enabled = false
base_url = "https://openrouter.ai/api/v1/chat/completions"
default_model = "qwen/qwen3-coder-next"  # Many options at openrouter.ai/models

# ========================================
# Google Gemini Provider
# ========================================
# Models fetched live from the Gemini API during onboarding and /models
# API key goes in keys.toml under [providers.gemini]
# Get key from: aistudio.google.com
[providers.gemini]
enabled = false
default_model = "gemini-2.5-flash"

# ========================================
# Minimax Provider (Chinese AI, OpenAI-compatible)
# ========================================
# Note: Minimax does NOT have a /models endpoint, so add models manually
[providers.minimax]
enabled = false
base_url = "https://api.minimax.io/v1"
default_model = "MiniMax-M2.5"
models = ["MiniMax-M2.5", "MiniMax-M2.1", "MiniMax-Text-01"]

# ========================================
# STT (Speech-to-Text) Providers
# ========================================
# Groq Whisper for transcription
[providers.stt.groq]
enabled = false
default_model = "whisper-large-v3-turbo"

# ========================================
# TTS (Text-to-Speech) Providers
# ========================================
# OpenAI TTS for voice output
[providers.tts.openai]
enabled = false
default_model = "gpt-4o-mini-tts"
voice = "ash"             # TTS voice name
model = "gpt-4o-mini-tts" # TTS model

# ========================================
# Image Generation & Vision (Google Gemini)
# ========================================
# API key goes in keys.toml under [image]
# Get key from: aistudio.google.com
# Use /onboard:image to configure via wizard

[image.generation]
enabled = false
model = "gemini-3.1-flash-image-preview"   # Gemini image-gen model ("Nano Banana")

[image.vision]
enabled = false
model = "gemini-3.1-flash-image-preview"   # Gemini vision model

# ========================================
# Tips for Using Local LLMs
# ========================================
# 1. Make sure LM Studio is running before starting OpenCrabs
# 2. Load a model in LM Studio first
# 3. Set default_model to EXACTLY match the model name shown in LM Studio
# 4. Increase context length in LM Studio if you get overflow errors:
#    - Recommended: 8192 or higher
#    - Location: LM Studio > Model Settings > Context Length

# ==================================================
# Channels (Telegram / WhatsApp / Slack / Discord / Trello)
# ==================================================

# respond_to controls which messages the bot replies to (applies to Telegram, Discord, Slack):
#   "all"      — reply to every message in allowed channels (default)
#   "dm_only"  — reply only to direct/private messages
#   "mention"  — reply only when the bot is @mentioned or replied-to

[channels.whatsapp]
enabled = false
# Phone numbers allowed to message the bot (E.164 format, leading + optional)
# Access control is purely phone-based — add numbers here to restrict who can message the bot.
allowed_phones = ["+15551234567"]
# session_idle_hours = 24.0             # Archive inactive non-owner sessions after N hours (default: never)

[channels.discord]
enabled = false
allowed_channels = ["channel_id"]       # Where the bot operates (empty = all channels)
allowed_users = [123456789012345]        # Who the bot replies to (numeric user ID, empty = everyone)
# respond_to = "all"                    # "all" | "dm_only" | "mention"
# session_idle_hours = 24.0             # Archive inactive non-owner sessions after N hours (default: never)

[channels.telegram]
enabled = false
allowed_users = [123456789]             # Who the bot replies to (numeric user ID, empty = everyone)
# allowed_channels = ["-100123456789"]  # Chat/group IDs to restrict to (empty = all chats)
# respond_to = "all"                    # "all" | "dm_only" | "mention"
# session_idle_hours = 24.0             # Archive inactive non-owner sessions after N hours (default: never)

[channels.slack]
enabled = false
allowed_channels = ["C12345678"]        # Where the bot operates (Slack channel ID, empty = all)
allowed_users = ["U12345678"]           # Who the bot replies to (Slack user ID, empty = everyone)
# respond_to = "all"                    # "all" | "dm_only" | "mention"
# session_idle_hours = 24.0             # Archive inactive non-owner sessions after N hours (default: never)

# ========================================
# Trello — board card management
# ========================================
# API keys/tokens go in keys.toml under [channels.trello]
# Default mode: tool-only — no automatic polling. The AI acts on Trello only
# when you explicitly ask it to via trello_send / trello_connect.
# Opt-in polling: set poll_interval_secs > 0 to have the agent watch boards
# for @mentions of the bot username and respond to them.
[channels.trello]
enabled = false
# Board IDs or names to monitor — you can mix 24-char hex IDs and human-readable board names.
# The agent resolves names at startup. Comma-separated in the wizard; TOML array here.
board_ids = ["your-board-name", "abc123def456abc123def456"]
allowed_users = []                      # Trello member IDs allowed to @mention the bot (empty = all)
# poll_interval_secs = 30              # Opt-in: poll boards every N seconds for @mentions. Default = disabled.
# session_idle_hours = 24.0             # Archive inactive non-owner sessions after N hours (default: never)

# ========================================
# Agent-to-Agent (A2A) Protocol
# ========================================
# Enables HTTP gateway for peer-to-peer agent communication.
# Other A2A-compatible agents can send tasks, collaborate, and debate.
[a2a]
enabled = false
bind = "127.0.0.1"     # Loopback only by default for security
port = 18790            # A2A gateway port
# CORS allowed origins (empty = no cross-origin requests allowed)
# allowed_origins = ["http://localhost:3000"]
# API key for Bearer token auth on /a2a/v1 (optional, recommended for non-loopback)
# Can also be set in keys.toml under [a2a] api_key = "..."
# api_key = "your-secret-key"

# ========================================
# Web Search Providers (default to free Duck Duck Go, no need additional web search provider)
# ========================================

[providers.web_search.exa]
enabled = true
# MCP is enabled by default as its free. If want through API its free up to 1000 requests. API key goes in keys.toml: [providers.web_search.exa] api_key = "..."

[providers.web_search.duckduckgo]
enabled = true
# Completely free, enabled by default"

[providers.web_search.brave]
enabled = false
# Its free up to 1000 requests. API key goes in keys.toml: [providers.web_search.brave] api_key = "..."