# ---------------------------------------------------------------------------
# KXKM_Clown — Environment Variables
# ---------------------------------------------------------------------------
# Copy this file to .env and adjust values for your deployment.
#   cp .env.example .env
# ---------------------------------------------------------------------------

# --- Local LLM runtime (vLLM / TurboQuant) ---------------------------------
# Primary chat/completion runtime. Must expose an OpenAI-compatible API.
LLM_URL=http://host.docker.internal:11434
LLM_MODEL=qwen-14b-awq
LLM_API_KEY=                             # Bearer token for vLLM --api-key (leave empty for Ollama)

# --- Embeddings backend (auxiliary) ----------------------------------------
# TEI (recommended): dedicated embedding server on port 9500
# Ollama: fallback, uses /api/embed on port 11434
OLLAMA_URL=http://host.docker.internal:9500
EMBEDDING_BACKEND=tei                    # "tei" (OpenAI /v1/embeddings) or "ollama" (/api/embed)
RAG_EMBEDDING_MODEL=BAAI/bge-m3          # Model name (must match TEI --model-id or Ollama model)

# --- Ports ------------------------------------------------------------------
APP_PORT=3333          # V1 Express server
API_PORT=4180          # V2 API server
PG_PORT=5432           # PostgreSQL (exposed to host)
# LLM_PORT=11434       # Only needed if you expose the local runtime from compose

# --- Admin ------------------------------------------------------------------
ADMIN_BOOTSTRAP_TOKEN=          # Initial admin token (set a strong secret)
ADMIN_ALLOWED_SUBNETS=          # CIDR subnets for admin access (e.g. 192.168.1.0/24)
OWNER_NICK=                     # Owner nickname in chat

# --- Chat -------------------------------------------------------------------
MAX_GENERAL_RESPONDERS=4        # Max personas responding in #general

# --- Vision (image analysis in chat) ----------------------------------------
# VISION_MODEL=qwen3-vl:8b           # Vision model used by the configured runtime

# --- Training (Node Engine worker) ------------------------------------------
# PYTHON_BIN=/home/kxkm/venv/bin/python3   # Python with ML libs (PyTorch, Unsloth, TRL)
# TRAINING_TIMEOUT_MS=3600000               # Training timeout (default 1h)
# SCRIPTS_DIR=/app/scripts                  # Path to train_unsloth.py, eval_model.py
# Note: GPU passthrough is enabled by default in docker-compose (deploy.resources)
# Note: Host venv is mounted read-only at /home/kxkm/venv in the worker container

# --- ComfyUI (image generation) --------------------------------------------
# COMFYUI_URL=http://localhost:8188   # ComfyUI API endpoint for /imagine command

# --- Mascarade (optional cloud/provider routing) ----------------------------
# MASCARADE_URL=http://127.0.0.1:8100    # Optional cloud/provider router
# MASCARADE_API_KEY=                      # API key for authenticated endpoints (/agents, /orchestrate)

# --- External services (optional) ------------------------------------------
# WEB_SEARCH_API_BASE=          # Web search API endpoint for /web command
# SEARXNG_URL=http://localhost:8080    # SearXNG instance for web search (fallback: DuckDuckGo)

# --- Discord Bot (optional, --profile discord) --------------------------------
# DISCORD_BOT_TOKEN=                 # Discord bot token (from Discord Developer Portal)
# DISCORD_CHANNEL_ID=                # Discord channel ID to bridge with KXKM chat