export declare const envExampleTemplate = "# Public Site URL\n# Used by sitemap.xml and robots.txt. Overrides `url` in config.json when set.\n# NEXT_PUBLIC_SITE_URL=https://docs.example.com\n\n# Password Protection (optional)\n# Set a shared password to gate the whole site behind a login screen. When set,\n# pages require the password, the content APIs (chat + search) return 401\n# without it, and the site is hidden from search engines and crawlers. Leave\n# unset (or remove) to keep the site public.\n# SITE_PASSWORD=choose-a-strong-shared-password\n\n# Paid API Access (recommended for public deployments with AI enabled)\n# Public documentation remains intentionally public by default. Set RAG_API_KEY\n# to require Authorization: Bearer <key> for /api/rag and prevent anonymous LLM\n# spend. The browser chat cannot safely hold this server secret; use\n# SITE_PASSWORD instead when authenticated browser chat is required.\n# RAG_API_KEY=generate-a-long-random-secret\n# Set DOCS_API_KEY to require bearer authentication for /api/mcp. If omitted,\n# MCP follows the site access mode and remains public on an intentionally public\n# documentation site.\n# DOCS_API_KEY=generate-another-long-random-secret\n\n# Remote Dev Access (optional, dev server only)\n# Hostnames (besides localhost) allowed to load the Next.js dev server's\n# resources, for when you browse the dev server over a LAN IP or a\n# Tailscale/VPN hostname. Without this, Next blocks the dev HMR socket for\n# such hosts and the page renders but never becomes interactive. Ignored by\n# production builds. Comma-separate multiple hostnames.\n# ALLOWED_DEV_ORIGINS=my-machine.tailnet-name.ts.net\n\n# LLM Provider Configuration\n# Choose your preferred LLM provider: openai, anthropic, or google\nLLM_PROVIDER=openai\n\n# API Keys (set the one matching your provider)\nOPENAI_API_KEY=your_openai_api_key_here\nANTHROPIC_API_KEY=your_anthropic_api_key_here\nGOOGLE_API_KEY=your_google_api_key_here\n\n# Optional: Override default chat model\n# See available models at your provider's docs:\n#   OpenAI:    https://platform.openai.com/docs/models\n#   Anthropic: https://docs.anthropic.com/claude/docs/models-overview\n#   Google:    https://ai.google.dev/models/gemini\n# LLM_CHAT_MODEL=\n\n# Optional: Override default embedding model\n# See available embedding models at your provider's docs:\n#   OpenAI: https://platform.openai.com/docs/guides/embeddings\n#   Google: https://ai.google.dev/gemini-api/docs/embeddings\n# Note: Anthropic doesn't provide embeddings, will fallback to OpenAI\n# LLM_EMBEDDING_MODEL=\n\n# Optional: Set temperature (0-1, default: 0)\n# LLM_TEMPERATURE=0\n\n# Optional: Embedding dimensions for the prebuilt search index (default: 512)\n# Doc vectors are Matryoshka-truncated to this many dimensions and stored as\n# int8, which keeps services/mcp/docs-index.json small (~20x smaller than raw\n# floats) so large doc sets don't stall the AI chat on serverless cold starts.\n# Lower = smaller index, slightly lower recall. Values >= the model's native\n# dimension keep full precision. Rebuild after changing this.\n# LLM_EMBEDDING_DIMS=512\n";