env.example.txt

# ============================================
# CONSILIUM - Environment Configuration
# ============================================
# Rename this file to .env and fill in your API keys
# mv env.example.txt .env
#
# QUICK SETUP:
# 1. Copy this file:  cp env.example.txt .env
# 2. Add your OpenRouter API key (minimum required)
# 3. If using Docker + local Ollama, uncomment the host.docker.internal line
#
# ============================================
# SERVER CONFIGURATION
# ============================================
PORT=3801
FRONTEND_URL=http://localhost:3800

# Are you running Consilium in Docker? (used for better error messages)
# DOCKER_RUNNING=true

# ============================================
# CLOUD AI PROVIDERS
# ============================================

# OpenRouter (Unified API for multiple providers)
# Get your key at: https://openrouter.ai/keys
OPENROUTER_API_KEY=sk-or-v1-your-key-here

# OpenAI Direct
# Get your key at: https://platform.openai.com/api-keys
OPENAI_API_KEY=sk-your-openai-key-here

# Anthropic Direct
# Get your key at: https://console.anthropic.com/
ANTHROPIC_API_KEY=sk-ant-your-anthropic-key-here

# Google AI (Gemini)
# Get your key at: https://makersuite.google.com/app/apikey
GOOGLE_AI_API_KEY=your-google-ai-key-here

# xAI (Grok)
# Get your key at: https://console.x.ai/
XAI_API_KEY=xai-your-key-here

# Mistral AI
# Get your key at: https://console.mistral.ai/
MISTRAL_API_KEY=your-mistral-key-here

# Cohere
# Get your key at: https://dashboard.cohere.com/api-keys
COHERE_API_KEY=your-cohere-key-here

# Together AI
# Get your key at: https://api.together.xyz/
TOGETHER_API_KEY=your-together-key-here

# Groq (Fast inference)
# Get your key at: https://console.groq.com/keys
GROQ_API_KEY=gsk_your-groq-key-here

# Perplexity AI
# Get your key at: https://www.perplexity.ai/settings/api
PERPLEXITY_API_KEY=pplx-your-key-here

# DeepSeek
# Get your key at: https://platform.deepseek.com/
DEEPSEEK_API_KEY=your-deepseek-key-here

# ============================================
# LOCAL AI PROVIDERS
# ============================================
# 
# IMPORTANT: URL depends on how you're running Consilium and the local model server
#
# ┌─────────────────────────────────────────────────────────────────────────────┐
# │ SCENARIO                          │ USE THIS URL                           │
# ├─────────────────────────────────────────────────────────────────────────────┤
# │ Consilium native + Ollama native  │ http://localhost:11434                 │
# │ Consilium Docker + Ollama native  │ http://host.docker.internal:11434      │
# │ Consilium Docker + Ollama Docker  │ http://ollama:11434 (same network)     │
# │ Consilium native + Ollama Docker  │ http://localhost:11434 (port mapped)   │
# └─────────────────────────────────────────────────────────────────────────────┘
#
# "Native" = installed directly on your machine (not in Docker)
# "Docker" = running in a Docker container
# "host.docker.internal" = special DNS that Docker provides to reach host machine

# --------------------------------------------
# Ollama (Local LLM server)
# --------------------------------------------
# Install: https://ollama.ai/download
# Default port: 11434
#
# Running Consilium natively (npm run dev)?
OLLAMA_URL=http://localhost:11434
#
# Running Consilium in Docker with Ollama on host machine?
# OLLAMA_URL=http://host.docker.internal:11434
#
# Running both Consilium and Ollama in Docker (same docker network)?
# OLLAMA_URL=http://ollama:11434

# --------------------------------------------
# LM Studio (Local LLM server)
# --------------------------------------------
# Install: https://lmstudio.ai/
# Default port: 1234
# Note: Enable "Server" mode in LM Studio and start the server
#
# Running Consilium natively?
LMSTUDIO_URL=http://localhost:1234
#
# Running Consilium in Docker with LM Studio on host?
# LMSTUDIO_URL=http://host.docker.internal:1234

# --------------------------------------------
# LocalAI (OpenAI-compatible local server)
# --------------------------------------------
# Install: https://localai.io/
# Default port: 8080
LOCALAI_URL=http://localhost:8080

# --------------------------------------------
# Text Generation WebUI (oobabooga)
# --------------------------------------------
# Install: https://github.com/oobabooga/text-generation-webui
# Default port: 5000 (API) or 7860 (WebUI)
TEXT_GEN_WEBUI_URL=http://localhost:5000

# --------------------------------------------
# vLLM Server
# --------------------------------------------
# Install: https://docs.vllm.ai/
# Default port: 8000
VLLM_URL=http://localhost:8000

# ============================================
# SEARCH / RESEARCH MODE (SearXNG)
# ============================================
#
# SearXNG is a privacy-respecting metasearch engine that Consilium uses
# for the "Research" mode to fetch web content before querying models.
#
# Install SearXNG: https://docs.searxng.org/admin/installation.html
# Or use Docker: docker run -d -p 4000:8080 searxng/searxng
#
# ┌─────────────────────────────────────────────────────────────────────────────┐
# │ SCENARIO                           │ USE THIS URL                          │
# ├─────────────────────────────────────────────────────────────────────────────┤
# │ Consilium native + SearXNG native  │ http://localhost:4000                 │
# │ Consilium Docker + SearXNG native  │ http://host.docker.internal:4000      │
# │ Consilium Docker + SearXNG Docker  │ http://searxng:8080 (same network)    │
# │ Consilium native + SearXNG Docker  │ http://localhost:4000 (port mapped)   │
# └─────────────────────────────────────────────────────────────────────────────┘
#
# Running Consilium natively?
SEARXNG_URL=http://localhost:4000
#
# Running Consilium in Docker with SearXNG on host?
# SEARXNG_URL=http://host.docker.internal:4000
#
# Running both in Docker on same network?
# SEARXNG_URL=http://searxng:8080

# Number of search results to fetch and include (default: 10)
SEARCH_RESULTS_LIMIT=10

# ============================================
# FEATURE FLAGS
# ============================================

# Run local models sequentially (STRONGLY RECOMMENDED!)
# Local models share GPU resources - running them in parallel:
# - Splits VRAM and compute power between models
# - Results in degraded response quality
# - Can cause OOM errors on smaller GPUs
# Serial execution ensures each model gets 100% GPU power for best answers
LOCAL_MODELS_SEQUENTIAL=true

# Enable debug logging
DEBUG=false

# ============================================
# DATABASE
# ============================================

# SQLite database path (relative to backend folder)
DATABASE_PATH=./consilium.db