# ====================================================================
# Hermes (Jarvis): Environment Configuration Template
# Copy this file to .env and fill in your keys.
# ====================================================================

# ── REQUIRED ─────────────────────────────────────────────────────────
# LLM inference via OpenRouter → https://openrouter.ai/keys
# Supports any model: Gemini, GPT-4o, Claude, DeepSeek, Llama, etc.
LLM_API_BASE=https://openrouter.ai/api/v1
OPENROUTER_API_KEY=your_openrouter_api_key_here
LLM_MODEL=google/gemini-2.5-flash
# Local model: LLM_MODEL=ollama/llama3 and LLM_API_BASE=http://host.docker.internal:11434/v1

# ── OPTIONAL: Per-agent model overrides ──────────────────────────────
# Override the model used by each specialized agent role.
# Falls back to LLM_MODEL if not set.
#
# Recommended combinations:
# - Research: Fast & cheap (e.g., ollama/llama3, google/gemini-2.5-flash, deepseek/deepseek-chat)
# - Code: High-reasoning models (e.g., deepseek/deepseek-r1, ollama/llama3, anthropic/claude-sonnet-4.5)
# - Analyst: Fast & visually descriptive (e.g., ollama/llama3, google/gemini-2.5-flash, openai/gpt-4o)
# - Planner: Highly structured JSON output (e.g., ollama/llama3, google/gemini-2.5-flash, openai/gpt-4o-mini)
#
AGENT_MODEL_RESEARCH=ollama/llama3
AGENT_MODEL_CODE=deepseek/deepseek-r1
AGENT_MODEL_ANALYST=ollama/llama3
AGENT_MODEL_PLANNER=ollama/llama3
# Model for specialists the core hires when no existing agent covers a request.
# AGENT_MODEL_SPECIALIST=ollama/llama3
COMPLEXITY_ROUTING=false

# ── AUTO-HIRE ────────────────────────────────────────────────────────
# When no agent covers a request, the core creates one in the same turn.
# ask: create it and wait for confirmation (default). on: hire and run, hands-free. off: report the gap.
AUTO_HIRE=ask
AUTO_HIRE_MAX_PER_TURN=1
AUTO_HIRE_MAX_PER_DAY=10
AUTO_HIRE_ALLOW_RISKY=0
# Auto-hired agents with no use in this many days show up for cleanup. They are not deleted.
AUTO_HIRE_UNUSED_DAYS=30

# ── SYSTEM BACKEND ───────────────────────────────────────────────────
PORT=8000

# ── TELEGRAM INTERFACE ───────────────────────────────────────────────
# Agents: all agents are accessible via Telegram
# Create a bot via @BotFather → https://t.me/BotFather
TELEGRAM_BOT_TOKEN=your_telegram_bot_token_here
# Get your numeric chat ID via @userinfobot → https://t.me/userinfobot
TELEGRAM_CHAT_ID=your_telegram_chat_id_here
# Authorized admin user ID(s) that the bot will respond to (comma-separated if multiple; all others are blocked at code level)
TELEGRAM_ADMIN_ID=your_telegram_admin_id_here
# HS256 secret for OIDC JWT sessions. Leave empty to disable JWT login (OTP sessions still work).
JWT_SECRET=

# ── SEARCH AGENT & FOOTBALL ANALYST ─────────────────────────────────
# Skill: web_search — powers web search, news, football results
# SearXNG — open-source self-hosted metasearch
SEARXNG_URL=http://localhost:8080

# ── CALENDAR & TASKS ───────────────────────────────────────────────
# Optional: Set path to your downloaded Google client_secret.json for Calendar
GOOGLE_CLIENT_SECRET_PATH=~/.config/hermes/google_client_secret.json

# ── SEARCH AGENT: WEATHER ────────────────────────────────────────────
# Skill: web_search (weather sub-feature)
# OpenWeatherMap — free tier: 1,000 calls/day → https://home.openweathermap.org/api_keys
OPENWEATHERMAP_API_KEY=your_openweathermap_api_key_here

# ── DAILY PLANNER: TODOIST ───────────────────────────────────────────
# Skill: todoist_sync
# Todoist → Settings → Integrations → Developer
# → https://app.todoist.com/app/settings/integrations/developer
TODOIST_API_TOKEN=your_todoist_token_here

# ── DAILY PLANNER: GOOGLE CALENDAR ───────────────────────────────────
# Skill: google_calendar — OAuth2 setup (one-time, on host machine)
# 1. Create Desktop OAuth 2.0 credentials at:
#    https://console.cloud.google.com/apis/credentials
# 2. Download the JSON and place it in the project root as client_secret_*.json
# 3. Run once on your host: python3 backend/google_auth.py
#    This generates google_token.json which is volume-mounted into Docker.

# ── OBSIDIAN RAG SKILL ───────────────────────────────────────────────
# Skill: obsidian_rag — local knowledge base search & sync
# Install "Local REST API" plugin in Obsidian:
# → https://github.com/coddingtonbear/obsidian-local-rest-api
OBSIDIAN_API_KEY=your_obsidian_local_rest_api_key_here
OBSIDIAN_HOST=host.docker.internal
OBSIDIAN_PORT=27124
OBSIDIAN_VAULT_PATH=/path/to/your/obsidian/vault

# ── MARKET DATA PROVIDER ─────────────────────────────────────────────
# Skill: market_monitor — real-time price alerts for crypto & stocks
#
# MARKET_DATA_PROVIDER controls which backend fetches prices.
#   http    → Default. CoinGecko (crypto) + Yahoo Finance (stocks).
#             Zero config, zero API keys. Works out of the box.
#   <other> → Resolved by an installed plugin via the market_data_provider(name)
#             hook (see backend/plugins.py). Falls back to http if none answers.
MARKET_DATA_PROVIDER=http

# ── DATABASE (OPTIONAL) ──────────────────────────────────────────────
# ── DATABASE ───────────────────────────────────────────────
# PostgreSQL is the required and only supported database backend for Jarvis.
# Example:
# DATABASE_URL=postgresql://postgres:postgres@localhost:5432/hermes

# ── STRIPE CONNECT MARKETPLACE ─────────────────────────────────────────
STRIPE_PUBLISHABLE_KEY=your_stripe_publishable_key_here
STRIPE_SECRET_KEY=your_stripe_secret_key_here
STRIPE_WEBHOOK_SECRET=your_stripe_webhook_secret_here

# ── HUGGING FACE TOKEN (FastEmbed / Vector Embeddings) ────────────────
HF_TOKEN=your_huggingface_token_here
HUGGING_FACE_HUB_TOKEN=your_huggingface_token_here