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# ─────────────────────────────────────────────────────────────────────────────
# MelodyMuse — server environment
#
# The Node server (`server.mjs`) reads these from `process.env`. It refuses to
# start without `LLM_ENDPOINT` and `LLM_API_KEY`. Pass them in however you run
# the server:
#
# • Bare-metal: LLM_ENDPOINT=… LLM_API_KEY=… node server.mjs
# • Docker: -e LLM_ENDPOINT=… -e LLM_API_KEY=…
# • docker-compose: put them in a `.env` file next to compose.yml
# • Jannik-Cloud: AGE-encrypted `.env` generated by `generate-env.sh`
#
# Three things you set:
#
# LLM_ENDPOINT — base URL of an OpenAI-compatible /chat/completions route
# LLM_API_KEY — provider secret (never sent to the browser)
# LLM_MODEL — model name to send in each request
#
# Below the active config you'll find worked examples for several providers —
# copy one of them into the active block above to switch.
# ─────────────────────────────────────────────────────────────────────────────
# ─── Active provider (uncomment ONE of the examples below to switch) ──────────
LLM_ENDPOINT=https://api.minimax.io/v1
LLM_API_KEY=
LLM_MODEL=MiniMax-M3
# ─── Server config ────────────────────────────────────────────────────────────
PORT=3000
CORS_ORIGIN=*
# ╔═══════════════════════════════════════════════════════════════════════════╗
# ║ PROVIDER EXAMPLES — copy one block up to switch providers ║
# ╚═══════════════════════════════════════════════════════════════════════════╝
# ─── MiniMax (the default) ───────────────────────────────────────────────────
# https://api.minimax.io/v1
# Sign in at https://MiniMax.io to get a key.
#
# LLM_ENDPOINT=https://api.minimax.io/v1
# LLM_API_KEY=eyXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# LLM_MODEL=MiniMax-M3
# ─── OpenAI ──────────────────────────────────────────────────────────────────
# https://platform.openai.com/
# Keys look like: sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# Common models: gpt-4o, gpt-4o-mini, gpt-4-turbo, o1-mini, o1, …
#
# LLM_ENDPOINT=https://api.openai.com/v1
# LLM_API_KEY=sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# LLM_MODEL=gpt-4o-mini
# ─── OpenRouter (Claude, Llama, Mistral, Gemini, …) ────────────────────────
# https://openrouter.ai/
# One OpenAI-compatible endpoint that fronts hundreds of models. Easiest way
# to use Anthropic Claude, Meta Llama, Google Gemini, etc. without writing a
# custom adapter.
#
# Keys look like: sk-or-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# Model names are namespaced: anthropic/claude-3.5-sonnet, openai/gpt-4o,
# meta-llama/llama-3.1-405b-instruct, google/gemini-2.0-flash-exp, …
#
# LLM_ENDPOINT=https://openrouter.ai/api/v1
# LLM_API_KEY=sk-or-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# LLM_MODEL=anthropic/claude-3.5-sonnet
# ─── Poe ─────────────────────────────────────────────────────────────────────
# https://poe.com/
# Poe exposes an OpenAI-compatible API for the bots you've created in their
# UI. Create a bot there first (free), then use its exact name as the model.
#
# LLM_ENDPOINT=https://api.poe.com/v1
# LLM_API_KEY=sk-poe-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# LLM_MODEL=Claude-3.5-Sonnet
# ─── Anthropic Claude (DIRECT — needs a server adapter) ─────────────────────
# https://console.anthropic.com/
# Anthropic's native API is NOT OpenAI-compatible — it lives at
# POST /v1/messages with a different body shape (system message is a
# top-level field, not a message) and a different response shape.
#
# MelodyMuse's server does not currently talk to Anthropic's native API
# directly. Two options:
#
# 1. Use OpenRouter above — same model, OpenAI-compatible, zero code
# changes.
# 2. Add a small adapter to server.mjs that translates the request
# to Anthropic's Messages API format. Roughly 30 lines of code.
#
# If you do add the adapter, the endpoint would be:
#
# LLM_ENDPOINT=https://api.anthropic.com
# LLM_API_KEY=sk-ant-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
# LLM_MODEL=claude-3-5-sonnet-latest
# ─────────────────────────────────────────────────────────────────────────────
# Vite dev environment (only used by `npm run dev`, not by the server)
# ─────────────────────────────────────────────────────────────────────────────
# Leave empty to use the dev proxy (see vite.config.ts). Set this if you want
# the browser to talk to a server on a different origin.
# VITE_API_BASE_URL=http://localhost:3000
# Video AI Links configuration (comma-separated Key=URL pairs)
VIDEO_AI_LINKS="Kling AI=https://klingai.com,Luma=https://lumalabs.ai,Runway=https://runwayml.com"