.env.example

# ClawOSS Environment — copy to .env and fill in values
# DO NOT COMMIT .env — it is gitignored

# === Required ===

# GitHub Personal Access Token — needs public_repo scope at minimum
# IMPORTANT: must be a classic token (ghp_*). Fine-grained tokens (github_pat_*)
# cannot create PRs in other people's repos. See docs/quickstart.md.
GITHUB_TOKEN=ghp_your-token-here

# === LLM Model Configuration ===
# See docs/model-routing.md for full provider examples (OpenAI, DeepSeek, MiniMax, etc.)
# See the "Provider Quick Reference" section at the bottom of this file.

# Provider name — becomes the OpenClaw provider block key and model ID prefix
LLM_PROVIDER=anthropic

# OpenAI-compatible API endpoint for this provider
LLM_BASE_URL=https://api.anthropic.com/v1

# API key for the provider above
LLM_API_KEY=sk-ant-your-key-here

# Complex model (Opus-tier) — used by implementation sub-agents (code writing, debugging)
LLM_MODEL_COMPLEX=claude-opus-4-6

# Simple model (Sonnet-tier) — used by orchestrator/heartbeat (routing, file reads)
LLM_MODEL_SIMPLE=claude-sonnet-4-6

# Cost per million tokens in USD (used for dashboard spend display).
# Per-model pricing — complex (Opus-tier) and simple (Sonnet-tier) can differ.
# If per-model vars are not set, INPUT_COST_PER_M / OUTPUT_COST_PER_M are used as fallback.
INPUT_COST_PER_M_COMPLEX=5.0     # Claude Opus 4.6 input ($5/M)
OUTPUT_COST_PER_M_COMPLEX=25.0   # Claude Opus 4.6 output ($25/M)
INPUT_COST_PER_M_SIMPLE=3.0      # Claude Sonnet 4.6 input ($3/M)
OUTPUT_COST_PER_M_SIMPLE=15.0    # Claude Sonnet 4.6 output ($15/M)
# Fallback if per-model vars are absent (set to your average expected price)
INPUT_COST_PER_M=3.0
OUTPUT_COST_PER_M=15.0

# Context window and max output tokens (model-specific)
LLM_CONTEXT_WINDOW=1000000
LLM_MAX_TOKENS=32000

# Public vars exposed to dashboard browser bundle (mirrors LLM_* above)
NEXT_PUBLIC_LLM_PROVIDER=anthropic
NEXT_PUBLIC_LLM_MODEL_COMPLEX=claude-opus-4-6
NEXT_PUBLIC_LLM_MODEL_SIMPLE=claude-sonnet-4-6

# === Budget Control ===
# Total cumulative spend cap in USD. Agent pauses when reached. 0 = unlimited.
BUDGET_USD_TOTAL=20.0

# Per-model token caps (JSON map). Keys are BARE model names — matched across
# all providers (e.g. `glm-4.6` covers `z-ai/glm-4.6`, `openrouter/glm-4.6`, etc).
# Value is total tokens (input + output). Missing key or value 0 = unlimited.
# When a model exceeds its cap, the agent stops using it AND a red banner shows
# at the top of the dashboard. See docs/model-routing.md.
# MODEL_TOKEN_BUDGETS={"glm-4.6":20000000,"deepseek-chat":50000000,"claude-opus-4-6":10000000}

# === Optional ===

# GitHub identity for PRs (defaults shown)
GITHUB_USERNAME=BillionClaw
GITHUB_EMAIL=billionclaw+clawoss@users.noreply.github.com

# Dashboard (for dashboard-reporter skill)
DASHBOARD_URL=https://clawoss-dashboard.vercel.app
CLAW_API_KEY=your-shared-secret-here

# Override only if your clone lives outside the default detected path
# CLAWOSS_ROOT=/absolute/path/to/ClawOSS

# Structured event logging for decision/outcome/reflection pipelines (alpha)
CLAWOSS_RECORD_DECISIONS=1
CLAWOSS_RECORD_OUTCOMES=1

# === Legacy / Alpha compatibility (optional overrides) ===
# If set, these take priority over LLM_* above. Useful during the alpha
# transition when you want to pin a specific full model ID.
# CLAWOSS_PRIMARY_MODEL=anthropic/claude-opus-4-6
# CLAWOSS_SUBAGENT_MODEL=anthropic/claude-opus-4-6
# CLAWOSS_HEARTBEAT_MODEL=anthropic/claude-sonnet-4-6
# CLAWOSS_AGENT_MODEL=anthropic/claude-sonnet-4-6
# CLAWOSS_FALLBACK_MODEL=

# Legacy per-provider API keys (no longer required — use LLM_API_KEY above).
# Kept for historical alpha deployments.
# KIMI_API_KEY=sk-kimi-your-key-here
# MINIMAX_API_KEY=your-minimax-key-here

# =============================================================================
# Provider Quick Reference — copy the block you want and replace the defaults
# Prices: April 2026. Verify at provider docs before setting budget.
# =============================================================================

# ── Google Gemini ─────────────────────────────────────────────────────────────
# Docs: https://ai.google.dev/gemini-api/docs/pricing
# Uses OpenAI-compatible endpoint. 2.5 Pro >200k context doubles price.
# All models have free tier with limited requests.
#
# LLM_PROVIDER=google
# LLM_BASE_URL=https://generativelanguage.googleapis.com/v1beta/openai
# LLM_API_KEY=your-gemini-key
# LLM_MODEL_COMPLEX=gemini-2.5-pro
# LLM_MODEL_SIMPLE=gemini-2.5-flash
# INPUT_COST_PER_M_COMPLEX=1.25
# OUTPUT_COST_PER_M_COMPLEX=10.0
# INPUT_COST_PER_M_SIMPLE=0.30
# OUTPUT_COST_PER_M_SIMPLE=2.50
# LLM_CONTEXT_WINDOW=1000000
# LLM_MAX_TOKENS=65536
# NEXT_PUBLIC_LLM_PROVIDER=google
# NEXT_PUBLIC_LLM_MODEL_COMPLEX=gemini-2.5-pro
# NEXT_PUBLIC_LLM_MODEL_SIMPLE=gemini-2.5-flash

# ── Mistral AI ───────────────────────────────────────────────────────────────
# Docs: https://mistral.ai/pricing
# Large 3 for complex, Small 3.1 for orchestration. Nemo ($0.02/M) is cheapest.
#
# LLM_PROVIDER=mistral
# LLM_BASE_URL=https://api.mistral.ai/v1
# LLM_API_KEY=your-mistral-key
# LLM_MODEL_COMPLEX=mistral-large-3
# LLM_MODEL_SIMPLE=mistral-small-3.1
# INPUT_COST_PER_M_COMPLEX=2.0
# OUTPUT_COST_PER_M_COMPLEX=6.0
# INPUT_COST_PER_M_SIMPLE=0.20
# OUTPUT_COST_PER_M_SIMPLE=0.60
# LLM_CONTEXT_WINDOW=128000
# LLM_MAX_TOKENS=32000
# NEXT_PUBLIC_LLM_PROVIDER=mistral
# NEXT_PUBLIC_LLM_MODEL_COMPLEX=mistral-large-3
# NEXT_PUBLIC_LLM_MODEL_SIMPLE=mistral-small-3.1

# ── DeepSeek ──────────────────────────────────────────────────────────────────
# Docs: https://api-docs.deepseek.com/quick_start/pricing
# deepseek-chat = V3.2 non-thinking | deepseek-reasoner = V3.2 thinking mode
# Same price, reasoner supports 32K output vs 8K.
# Cache hit: $0.028/M input (90% off)
#
# LLM_PROVIDER=deepseek
# LLM_BASE_URL=https://api.deepseek.com/v1
# LLM_API_KEY=sk-your-deepseek-key
# LLM_MODEL_COMPLEX=deepseek-reasoner     # thinking mode for complex tasks
# LLM_MODEL_SIMPLE=deepseek-chat          # non-thinking for orchestration
# INPUT_COST_PER_M_COMPLEX=0.28
# OUTPUT_COST_PER_M_COMPLEX=0.42
# INPUT_COST_PER_M_SIMPLE=0.28
# OUTPUT_COST_PER_M_SIMPLE=0.42
# LLM_CONTEXT_WINDOW=128000
# LLM_MAX_TOKENS=32000
# NEXT_PUBLIC_LLM_PROVIDER=deepseek
# NEXT_PUBLIC_LLM_MODEL_COMPLEX=deepseek-reasoner
# NEXT_PUBLIC_LLM_MODEL_SIMPLE=deepseek-chat

# ── MiniMax ───────────────────────────────────────────────────────────────────
# Docs: https://platform.minimax.io/docs/guides/pricing-paygo
# highspeed variants are 2× price but lower latency
#
# LLM_PROVIDER=minimax
# LLM_BASE_URL=https://api.minimaxi.com/v1
# LLM_API_KEY=your-minimax-key
# LLM_MODEL_COMPLEX=MiniMax-M2.7
# LLM_MODEL_SIMPLE=MiniMax-M2.5
# INPUT_COST_PER_M_COMPLEX=0.30
# OUTPUT_COST_PER_M_COMPLEX=1.20
# INPUT_COST_PER_M_SIMPLE=0.30
# OUTPUT_COST_PER_M_SIMPLE=1.20
# LLM_CONTEXT_WINDOW=204800
# LLM_MAX_TOKENS=131072
# NEXT_PUBLIC_LLM_PROVIDER=minimax
# NEXT_PUBLIC_LLM_MODEL_COMPLEX=MiniMax-M2.7
# NEXT_PUBLIC_LLM_MODEL_SIMPLE=MiniMax-M2.5

# ── Kimi / Moonshot ───────────────────────────────────────────────────────────
# Docs: https://platform.kimi.ai/docs/pricing/chat
# kimi-k2.5 = latest coding model | moonshot-v1-32k = general purpose
# Cache hit: $0.10/M input (vs $0.60/M cache miss)
#
# LLM_PROVIDER=moonshot
# LLM_BASE_URL=https://api.moonshot.cn/v1
# LLM_API_KEY=sk-your-moonshot-key
# LLM_MODEL_COMPLEX=kimi-k2.5
# LLM_MODEL_SIMPLE=moonshot-v1-32k
# INPUT_COST_PER_M_COMPLEX=0.60
# OUTPUT_COST_PER_M_COMPLEX=3.00
# INPUT_COST_PER_M_SIMPLE=3.29
# OUTPUT_COST_PER_M_SIMPLE=3.29
# LLM_CONTEXT_WINDOW=131072
# LLM_MAX_TOKENS=32000
# NEXT_PUBLIC_LLM_PROVIDER=moonshot
# NEXT_PUBLIC_LLM_MODEL_COMPLEX=kimi-k2.5
# NEXT_PUBLIC_LLM_MODEL_SIMPLE=moonshot-v1-32k

# ── GLM / Zhipu AI (Z.AI) ─────────────────────────────────────────────────────
# Docs: https://docs.z.ai/guides/overview/pricing
# International endpoint: api.z.ai/v1 | China endpoint: open.bigmodel.cn/api/paas/v4
# glm-4.7-flash is FREE — useful as the simple/orchestrator model
#
# LLM_PROVIDER=z-ai
# LLM_BASE_URL=https://api.z.ai/v1
# LLM_API_KEY=your-zhipu-key
# LLM_MODEL_COMPLEX=glm-4.7          # $0.60/$2.20 per M
# LLM_MODEL_SIMPLE=glm-4.5-air       # $0.20/$1.10 per M (or glm-4.7-flash for free)
# INPUT_COST_PER_M_COMPLEX=0.60
# OUTPUT_COST_PER_M_COMPLEX=2.20
# INPUT_COST_PER_M_SIMPLE=0.20
# OUTPUT_COST_PER_M_SIMPLE=1.10
# LLM_CONTEXT_WINDOW=128000
# LLM_MAX_TOKENS=32000
# NEXT_PUBLIC_LLM_PROVIDER=z-ai
# NEXT_PUBLIC_LLM_MODEL_COMPLEX=glm-4.7
# NEXT_PUBLIC_LLM_MODEL_SIMPLE=glm-4.5-air