# ============================================
# OpenSpace Environment Variables
# Copy this file to .env and fill in your keys
# ============================================

# ── LLM Credentials ──────────────────────────────────────
#
# OpenSpace resolves LLM credentials in this order (first match wins):
#
#   1. OPENSPACE_LLM_*       — explicit override, always highest priority
#   2. Provider-native vars   — OPENROUTER_API_KEY, OPENAI_API_KEY, etc.
#   3. ~/.nanobot/config.json or ~/.openclaw/openclaw.json — fallback (only when no explicit or provider key found)
#
# For most users, setting ONE of the provider-native keys below is enough.
# LiteLLM reads them automatically. See https://docs.litellm.ai/docs/providers
#
# Full configuration guide: openspace/config/README.md

# --- Option A: Provider-native key (simplest) ---
# Set the key that matches your model's provider:

# OpenRouter (for openrouter/* models, e.g. openrouter/anthropic/claude-sonnet-4.5)
OPENROUTER_API_KEY=

# Anthropic (for anthropic/claude-* models)
# ANTHROPIC_API_KEY=

# OpenAI (for openai/gpt-* models)
# OPENAI_API_KEY=

# DeepSeek (for deepseek/* models)
# DEEPSEEK_API_KEY=

# --- Option B: Explicit OpenSpace override (takes priority over Option A) ---
# Use these when you need full control, e.g. custom API base or non-standard provider.

# OPENSPACE_MODEL=openrouter/anthropic/claude-sonnet-4.5
# OPENSPACE_LLM_API_KEY=sk-xxx
# OPENSPACE_LLM_API_BASE=https://openrouter.ai/api/v1

# --- Recommended split routing for OpenSpace itself ---
# Keep the main LLM on your OpenAI-compatible provider,
# but route skill embeddings separately.
#
# Example: LLM via sub2api / local gateway, skill embeddings via local fastembed
#
# OPENSPACE_MODEL=gpt-5.4
# OPENSPACE_LLM_API_KEY=sk-xxx
# OPENSPACE_LLM_API_BASE=http://127.0.0.1:8080/v1
# OPENSPACE_SKILL_EMBEDDING_BACKEND=local
# OPENSPACE_SKILL_EMBEDDING_MODEL=BAAI/bge-small-en-v1.5

# ── OpenSpace Cloud (optional) ──────────────────────────────
# Register at https://open-space.cloud to get your key.
# Enables cloud skill search & upload; local features work without it.

OPENSPACE_API_KEY=sk_xxxxxxxxxxxxxxxx


# ── GUI Backend (optional) ──────────────────────────────────
# Required only if using the GUI backend (Anthropic Computer Use).
# Uses the same ANTHROPIC_API_KEY above.
# Optional backup key for rate limit fallback:
# ANTHROPIC_API_KEY_BACKUP=

# ── Skill Embedding (optional, router-only) ─────────────────
# Controls the skill-router semantic re-rank path independently
# from the main LLM provider.
#
# OPENSPACE_SKILL_EMBEDDING_BACKEND=auto
#   - auto   → prefer explicit remote embedding config, then legacy OpenAI-compatible env, then local fastembed
#   - local  → force local fastembed model
#   - remote → force remote OpenAI-compatible /embeddings endpoint
#
# OPENSPACE_SKILL_EMBEDDING_BACKEND=local
# OPENSPACE_SKILL_EMBEDDING_MODEL=BAAI/bge-small-en-v1.5
#
# Or use a dedicated remote embedding endpoint:
# OPENSPACE_SKILL_EMBEDDING_BACKEND=remote
# OPENSPACE_SKILL_EMBEDDING_API_KEY=sk-xxx
# OPENSPACE_SKILL_EMBEDDING_API_BASE=https://example.com/v1
# OPENSPACE_SKILL_EMBEDDING_MODEL=openai/text-embedding-3-small

# ── Tool / Generic Embedding (optional) ─────────────────────
# Used by tool search's semantic retrieval. Can also act as a fallback
# remote embedding endpoint for the skill router when the dedicated
# OPENSPACE_SKILL_EMBEDDING_* vars are not set.
#
# If not set, tool search uses a local embedding model (BAAI/bge-small-en-v1.5).
# EMBEDDING_BASE_URL=
# EMBEDDING_API_KEY=
# EMBEDDING_MODEL=openai/text-embedding-3-small

# ── E2B Sandbox (optional) ──────────────────────────────────
# Required only if sandbox mode is enabled in security config.
# E2B_API_KEY=

# ── Local Server (optional) ─────────────────────────────────
# Override the default local server URL (default: http://127.0.0.1:5000)
# Useful for remote VM integration (e.g., OSWorld).
# LOCAL_SERVER_URL=http://127.0.0.1:5000

# ---- Debug (Optional) ----
# OPENSPACE_DEBUG=true