.env.example

# Microsoft Foundry Project (Required for most lessons)
# Your Microsoft Foundry project endpoint
AZURE_AI_PROJECT_ENDPOINT="https://..."

# Model deployment name in your Foundry project. Use a non-deprecated model that
# supports the Responses API, e.g. gpt-5-mini (gpt-4.1 / gpt-4.1-mini retire 14 Oct 2026).
AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-5-mini"

# Optional: model routing for Lesson 16 (small vs large tier). Defaults to
# AZURE_AI_MODEL_DEPLOYMENT_NAME if unset. Point these at two deployed models
# to see cost-aware routing in action.
AZURE_AI_SMALL_MODEL="gpt-5-nano"
AZURE_AI_LARGE_MODEL="gpt-5-mini"

# Azure OpenAI (Responses API - used by lessons that call the model directly)
# The Responses API uses the stable /openai/v1/ endpoint - no api_version needed.
# NOTE: GitHub Models is deprecated (retiring July 2026) and does NOT support the
# Responses API. All samples now use Azure OpenAI with the Responses API instead.
AZURE_OPENAI_ENDPOINT="https://<your-resource>.openai.azure.com"
AZURE_OPENAI_DEPLOYMENT="gpt-5-mini"
# Optional: use a key instead of Entra ID / AzureCliCredential
AZURE_OPENAI_API_KEY="..."

# Chat deployment name used by Lesson 15 (browser-use). Usually the same model.
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME="gpt-5-mini"

# Azure AI Search (Required for Lesson 05 - Agentic RAG)
AZURE_SEARCH_SERVICE_ENDPOINT="https://..."
AZURE_SEARCH_API_KEY="..."

# Azure AI Bing Connection (Required for Lesson 08 - Bing grounding workflow)
BING_CONNECTION_ID="..."

# MiniMax (Alternative OpenAI-compatible provider)
# MiniMax offers large-context models (up to 204K tokens) via an OpenAI-compatible API.
# Get your API key from https://platform.minimaxi.com/
MINIMAX_API_KEY="..."
MINIMAX_BASE_URL="https://api.minimax.io/v1"
MINIMAX_MODEL_ID="MiniMax-M3"