.env.example

# SkillOpt Environment Variables
# Copy this file to .env and fill in your values.
# Usage: set -a; source .env; set +a

# ── Azure OpenAI (required for openai_chat backend) ──────────────────
export AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
export AZURE_OPENAI_API_VERSION=2024-12-01-preview
# Authentication: choose one method
#   Option 1: API Key
export AZURE_OPENAI_API_KEY=
export AZURE_OPENAI_AUTH_MODE=api_key
#   Option 2: Azure CLI (no API key needed, recommended on Azure VMs)
# export AZURE_OPENAI_AUTH_MODE=azure_cli
#   Option 3: Managed Identity
# export AZURE_OPENAI_AUTH_MODE=managed_identity
# export AZURE_OPENAI_MANAGED_IDENTITY_CLIENT_ID=your-client-id

# ── OpenAI-compatible endpoints ──────────────────────────────────────
# Path 1: generic research backend. Select openai_compatible explicitly as
# model.optimizer_backend and/or model.target_backend.
# export OPENAI_COMPATIBLE_BASE_URL=https://api.deepseek.com/v1
# export OPENAI_COMPATIBLE_API_KEY=sk-...
# export OPENAI_COMPATIBLE_MODEL=deepseek-chat
# Novita AI (OpenAI-compatible) works the same way:
# export OPENAI_COMPATIBLE_BASE_URL=https://api.novita.ai/openai/v1
# export OPENAI_COMPATIBLE_API_KEY=...
# export OPENAI_COMPATIBLE_MODEL=zai-org/glm-5.2
# Per-role overrides use OPTIMIZER_OPENAI_COMPATIBLE_* and
# TARGET_OPENAI_COMPATIBLE_* (BASE_URL, API_KEY, MODEL, TEMPERATURE,
# MAX_TOKENS, TIMEOUT_SECONDS).
# For scripts/train.py and scripts/eval_only.py, also set model.optimizer and
# model.target in YAML (or via --cfg-options). Those role model values are
# applied after backend initialization and override *_MODEL environment values.

# Path 2: research openai_chat compatibility mode. This reuses the Azure-family
# variables but creates a plain OpenAI client (no Azure auth or api-version).
# export AZURE_OPENAI_ENDPOINT=https://api.openai.com/v1
# export AZURE_OPENAI_API_KEY=sk-...
# export AZURE_OPENAI_AUTH_MODE=openai_compatible

# Path 3: SkillOpt-Sleep. `skillopt-sleep run --backend azure_openai` uses the
# same three AZURE_* variables from path 2. Optional Sleep-only controls:
# export SKILLOPT_SLEEP_COMPAT_MAX_TOKENS=8192
# export SKILLOPT_SLEEP_CHAT_EXTRA_BODY='{"provider_option": true}'

# ── Claude Code CLI (for claude_chat backend) ─────────────────────────
# Install and authenticate the `claude` CLI before use. For a non-default path:
# export CLAUDE_CLI_BIN=/path/to/claude
# ANTHROPIC_API_KEY is one authentication option understood by the CLI; SkillOpt
# does not create a direct Anthropic API client for this backend.
# export ANTHROPIC_API_KEY=sk-ant-...

# ── Qwen via an OpenAI-compatible endpoint (qwen_chat backend) ──────
# export QWEN_CHAT_BASE_URL=http://localhost:8000/v1
# export QWEN_CHAT_MODEL=Qwen/Qwen3.5-4B
# Wire policy for chat_template_kwargs.enable_thinking, a vLLM/SGLang
# extension that OpenAI/Azure and strict gateways reject with HTTP 400:
#   server_default (default) omit the field | enabled | disabled
# export QWEN_CHAT_THINKING_MODE=disabled
# The train/eval entry points likewise override this model with
# model.optimizer/model.target for the selected Qwen roles.

# ── MiniMax (for minimax_chat backend) ──────────────────────────────
# Pick the service region instead of hardcoding a host: global_en (default)
# resolves to https://api.minimax.io/v1 and cn_zh resolves to
# https://api.minimaxi.com/v1. MINIMAX_BASE_URL still overrides the region.
# export MINIMAX_REGION=global_en
# export MINIMAX_BASE_URL=https://api.minimax.io/v1
# export MINIMAX_API_KEY=...
# When MiniMax is the target, set model.minimax_model in YAML. The current
# adapter shares one deployment across MiniMax roles; mixed-backend runs cannot
# independently select a MiniMax optimizer model and a different target model.