# ============================================================================
# HiMe — Environment Configuration
# Copy this to .env, fill the REQUIRED block; all else has sensible defaults.
# ============================================================================

# ----------------------------------------------------------------------------
# Required
# ----------------------------------------------------------------------------
# Pick your provider, then put its key in §LLM provider keys below.
DEFAULT_LLM_PROVIDER=gemini
# For IM chat (Telegram/Feishu) also fill the relevant gateway section below.

# ----------------------------------------------------------------------------
# LLM provider keys
# ----------------------------------------------------------------------------
# Primary
GEMINI_API_KEY=         # Google Gemini (recommended)
GOOGLE_API_KEY=         # Google AI key (Gemini/Google providers fallback)
OPENAI_API_KEY=         # OpenAI (GPT-4.5 / GPT-5)
ANTHROPIC_API_KEY=      # Anthropic (Claude 3.5 / 4.x)
DEEPSEEK_API_KEY=       # DeepSeek (V4 — flash / pro, 1M ctx)

# OpenAI-compatible
GROQ_API_KEY=           # Groq
MISTRAL_API_KEY=        # Mistral AI
MINIMAX_API_KEY=        # MiniMax
XAI_API_KEY=            # x.AI (Grok)
OPENROUTER_API_KEY=     # OpenRouter (multi-provider router)
PERPLEXITY_API_KEY=     # Perplexity
ZHIPUAI_API_KEY=        # ZhipuAI (GLM family)

# Cloud-hosted
# Azure OpenAI — endpoint URL + key + API version
AZURE_OPENAI_ENDPOINT=
AZURE_OPENAI_API_KEY=
AZURE_OPENAI_API_VERSION=2024-12-01-preview
# Google Cloud Vertex AI — uses ADC; set GOOGLE_CLOUD_API_KEY for API-key auth
GOOGLE_CLOUD_PROJECT=
GOOGLE_CLOUD_LOCATION=us-central1
GOOGLE_CLOUD_API_KEY=
# Amazon Bedrock — IAM credentials
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION=us-east-1

# Local
# vLLM — locally-served OpenAI-compatible endpoint
VLLM_BASE_URL=http://localhost:8421/v1
VLLM_MODEL=gemma-4-26b-a4b

# ----------------------------------------------------------------------------
# Agent behavior
# ----------------------------------------------------------------------------
#DEFAULT_MODEL=gemini-3-flash-preview          # overrides DEFAULT_MODEL_<provider>
# Capacity fallback: re-issues call after 3 consecutive 503/529/overloaded
FALLBACK_LLM_PROVIDER=
FALLBACK_LLM_MODEL=
AGENT_MAX_ITERATIONS=100      # hard safety limit per analysis/chat
AGENT_CONTEXT_WINDOW_SIZE=20  # turn groups kept in full (rest auto-summarized)
AGENT_MAX_TOKENS=8192         # max tokens per LLM response (0 = no limit)
#AGENT_MAX_CONTEXT_TOKENS=180000   # token-budget for compression
#AGENT_CONTEXT_WINDOW_HOURS=24     # how far back agent reads on startup
#CHAT_MAX_TURNS=20                 # hard cap for chat loop turns
CHAT_HISTORY_SIZE=20          # sliding window per gateway chat (messages)
AUTO_RESTORE_AGENT=false      # restart last agent on backend startup
# OpenAI/Azure reasoning (gpt-5*, o1-o4): minimal|low|medium|high|xhigh|none
# Empty = server default ("medium"). "minimal" disables parallel tools.
OPENAI_REASONING_EFFORT=
# Fact verification LLM (empty = reuse agent's provider/model)
FACT_VERIFY_LLM_PROVIDER=
FACT_VERIFY_LLM_MODEL=
# IANA timezone name. Cron expressions in scheduled_tasks and the
# wall-clock shown in agent prompts are interpreted in this zone, so
# scheduling is independent of the container's system clock.
# Examples: UTC, Europe/London, America/New_York, Asia/Shanghai.
TIMEZONE=UTC

# ----------------------------------------------------------------------------
# Per-provider default models  (April 2026 lineup)
# ----------------------------------------------------------------------------
# Dashboard placeholders + create_provider(model=None) fallbacks. Each block
# shows the provider's small / medium / large variants — uncomment one to
# override the built-in default (= medium tier).
# DEFAULT_MODEL_AZURE_OPENAI = your Azure *deployment name* (not model name).
# vLLM is excluded — it always uses VLLM_MODEL above.

# Anthropic Claude 4.x:    small | medium | large
# claude-haiku-4-5  |  claude-sonnet-4-6  |  claude-opus-4-7
#DEFAULT_MODEL_ANTHROPIC=claude-sonnet-4-6

# OpenAI GPT-5.4 family:   small | medium | large
# gpt-5.4-nano  |  gpt-5.4-mini  |  gpt-5.4
#DEFAULT_MODEL_OPENAI=gpt-5.4-mini

# Azure OpenAI — values are your *deployment names*; deploy these models first
# gpt-5-nano  |  gpt-5-mini  |  gpt-5
#DEFAULT_MODEL_AZURE_OPENAI=gpt-5-mini

# Google Gemini 3 family:  small | medium | large
# gemini-3.1-flash-lite-preview  |  gemini-3-flash-preview  |  gemini-3.1-pro-preview
#DEFAULT_MODEL_GEMINI=gemini-3-flash-preview

# Google Vertex AI (same Gemini lineup, hosted on Vertex)
#DEFAULT_MODEL_GOOGLE_VERTEX=gemini-3-flash-preview

# DeepSeek V4 (April 2026, 1M ctx, 384K max output): flash | pro
# deepseek-v4-flash  (284B / 13B active — fast, cheap default)
# deepseek-v4-pro    (1.6T / 49B active — frontier; 75% off until 2026/05/31)
# Legacy ``deepseek-chat`` / ``deepseek-reasoner`` route to V4-Flash and are
# fully retired after 2026-07-24 15:59 UTC.
#DEFAULT_MODEL_DEEPSEEK=deepseek-v4-flash
# DeepSeek thinking-mode toggle. HIME default = "disabled" (fast/cheap for
# agentic tool-calling loops). Set to "enabled" for deep reasoning, or leave
# empty to fall back to the DeepSeek server default (thinking on).
DEEPSEEK_THINKING=disabled
# DeepSeek reasoning depth (only meaningful when thinking is enabled): high | max
#DEEPSEEK_REASONING_EFFORT=

# Mistral 3 family:        small | medium | large
# mistral-small-latest  |  mistral-medium-latest  |  mistral-large-latest
#DEFAULT_MODEL_MISTRAL=mistral-medium-latest

# Groq (open-weight hosted; format <vendor>/<model> for Llama 4 / others):
# meta-llama/llama-4-scout-17b-16e-instruct
# llama-3.3-70b-versatile
# meta-llama/llama-4-maverick-17b-128e-instruct
#DEFAULT_MODEL_GROQ=llama-3.3-70b-versatile

# xAI Grok 4 family: small (coding) | medium (fast) | large (frontier)
# grok-code-fast-1  |  grok-4-1-fast-reasoning  |  grok-4.20-reasoning
#DEFAULT_MODEL_XAI=grok-4-1-fast-reasoning

# OpenRouter (router; use <vendor>/<model>): small | medium | large
# google/gemini-3-flash  |  anthropic/claude-sonnet-4-6  |  anthropic/claude-opus-4-7
#DEFAULT_MODEL_OPENROUTER=anthropic/claude-sonnet-4-6

# Perplexity Sonar:        search | reasoning | grounded-pro
# sonar  |  sonar-reasoning  |  sonar-pro
#DEFAULT_MODEL_PERPLEXITY=sonar-pro

# Amazon Bedrock — Nova:   small | mid | large
# amazon.nova-micro-v1:0  |  amazon.nova-lite-v1:0  |  amazon.nova-pro-v1:0
# (Or use Anthropic on Bedrock: anthropic.claude-sonnet-4-6 / anthropic.claude-opus-4-7)
#DEFAULT_MODEL_AMAZON_BEDROCK=amazon.nova-pro-v1:0

# MiniMax:                 legacy | M2 | M2.5
# abab6.5s-chat  |  MiniMax-M2  |  MiniMax-M2.5
#DEFAULT_MODEL_MINIMAX=MiniMax-M2

# ZhipuAI / Z.AI GLM:      small | flash | flagship
# glm-4-air  |  glm-4.7-flash  |  glm-4.7   (glm-5 = preview)
#DEFAULT_MODEL_ZHIPUAI=glm-4.7

# ----------------------------------------------------------------------------
# Storage
# ----------------------------------------------------------------------------
DATA_STORE_PATH=./data/data_stores  # wearable sensor data (parquet, DBs)
AGENT_LOGS_PATH=./logs              # all logs (backend, frontend, LLM CSV)
MEMORY_DB_PATH=./memory             # agent memory (SQLite, state JSON)
#DATA_RETENTION_DAYS=30             # rolling retention window (days)

# ----------------------------------------------------------------------------
# Networking & domain
# ----------------------------------------------------------------------------
#API_HOST=0.0.0.0
#API_PORT=8000
# CORS origins (JSON array string). Add your public domain when deploying.
CORS_ORIGINS='["http://localhost:5173", "http://localhost:3000"]'
# Public URLs shown in logs/scripts (leave blank for local-only)
DASHBOARD_URL=
API_URL=
WATCH_URL=

# ----------------------------------------------------------------------------
# API authentication
# ----------------------------------------------------------------------------
# When set, /api/* requires `Authorization: Bearer <token>`; WebSocket clients
# may pass `?token=<token>`. Empty = disabled (unsafe for public deployments).
API_AUTH_TOKEN=

# ----------------------------------------------------------------------------
# Telegram gateway
# ----------------------------------------------------------------------------
# Telegram is one of two supported IM gateways.
CHAT_ID=                        # default chat for autonomous pushes
TELEGRAM_TOKEN=                 # bot token from @BotFather
TELEGRAM_GATEWAY_ENABLED=false  # true = enable two-way (long-poll)
TELEGRAM_POLL_TIMEOUT=30        # long-poll timeout (seconds)
TELEGRAM_GROUP_LINK=            # group link (iOS app jump)
TELEGRAM_ALLOWED_CHAT_IDS=      # csv; empty = only CHAT_ID (default-deny)

# ----------------------------------------------------------------------------
# Feishu (Lark) gateway
# ----------------------------------------------------------------------------
# Feishu is the second IM gateway; pick this OR Telegram, not usually both.
FEISHU_GATEWAY_ENABLED=false
FEISHU_APP_ID=                  # from Feishu developer console
FEISHU_APP_SECRET=
FEISHU_TRANSPORT=ws             # "ws" (lark_oapi WebSocket) or "webhook"
FEISHU_WEBHOOK_PATH=/api/feishu/webhook
# Required when FEISHU_TRANSPORT=webhook
FEISHU_VERIFICATION_TOKEN=
FEISHU_ENCRYPT_KEY=
FEISHU_DEFAULT_CHAT_ID=         # open_chat_id for outbound pushes
FEISHU_ALLOWED_CHAT_IDS=        # csv open_chat_ids; empty = default-deny

# ----------------------------------------------------------------------------
# WeChat (Weixin ClawBot / iLink) gateway
# ----------------------------------------------------------------------------
# Third IM gateway, talks to the iLink bot API. One-time setup:
#   1. enable here, set the user-id allowlist below, restart the backend
#   2. on the host, run:  python -m backend.weixin.qr_login
#   3. in WeChat, open Settings → Plugins → ClawBot, scan the QR
# The bot_token is cached at WEIXIN_BOT_TOKEN_PATH; re-run step 2 only if
# getupdates starts returning 401. Note: outbound replies require a recent
# context_token from the user, so proactive pushes only work after the user
# has messaged the bot at least once.
WEIXIN_GATEWAY_ENABLED=false
WEIXIN_BOT_TOKEN_PATH=./data/weixin_bot_token.json
# WEIXIN_DEFAULT_USER_ID — outbound push target, e.g. xxx@im.wechat.
# Only needed for autonomous pushes initiated by the agent (e.g. scheduled
# reports). For chat replies it is filled automatically from the inbound
# message, so you can leave this blank until you actually want pushes.
WEIXIN_DEFAULT_USER_ID=
# WEIXIN_ALLOWED_USER_IDS — csv of user_ids. Empty = trust whoever scanned
# the QR (the only person who can reach the bot anyway, since ClawBot has
# no shareable handle). Fill this only if you scanned with one account but
# want a different account to talk to the bot.
WEIXIN_ALLOWED_USER_IDS=

# ----------------------------------------------------------------------------
# In-app iOS channel (native chat — alternative to the IM gateways above)
# ----------------------------------------------------------------------------
# When enabled, the iOS app talks to the agent directly (POST /api/agent/chat
# in, replies stream over the /api/stream/agent WebSocket out), authenticated
# by the API bearer token (if API_AUTH_TOKEN is set). No bot binding required.
# Set to false if you only want the IM gateways.
IOS_GATEWAY_ENABLED=true
# Accept user→agent image uploads (needs a vision-capable LLM: anthropic /
# gemini / openai). Off by default; turn on once a vision model is in use.
IOS_VISION_ENABLED=false
# Max accepted inbound image size in bytes (default 5 MiB).
IOS_MAX_IMAGE_BYTES=5242880

# --- APNs (Apple Push Notification service) — proactive push to a closed app.
# Disabled by default: replies/reports are delivered when the app next opens.
# To enable real background push: create an APNs Auth Key (.p8) in your Apple
# Developer account, set the fields below, and `pip install aioapns`. APNS_ENV
# must match your build (sandbox for debug/dev builds, production for TestFlight
# / App Store).
APNS_ENABLED=false
APNS_KEY_PATH=
APNS_KEY_ID=
APNS_TEAM_ID=
APNS_BUNDLE_ID=
APNS_ENV=production

# ----------------------------------------------------------------------------
# Skills subsystem
# ----------------------------------------------------------------------------
# os.pathsep-separated skill-package dirs. Registry also auto-scans
# ~/.hime/skills and ./skills on every agent start.
HIME_SKILLS_DIR=./skills

# ----------------------------------------------------------------------------
# Code-tool sandbox
# ----------------------------------------------------------------------------
# Runs agent-generated Python in Docker (--network none, limited).
# Requires Docker daemon (Engine / Desktop) running.
CODE_TOOL_DOCKER_SANDBOX=false
CODE_TOOL_DOCKER_IMAGE=python:3.12-slim

# ----------------------------------------------------------------------------
# Data source
# ----------------------------------------------------------------------------
# Keep `live` unless using historic dataset playback.
DATA_SOURCE=live

# ----------------------------------------------------------------------------
# Localization
# ----------------------------------------------------------------------------
# Affects backend reply language. Unknown values fall back to 'en'.
DEFAULT_USER_LANGUAGE=en