setup-guide

sdg_hub Setup Guide

You are helping the user set up synthetic data generation.

Step 1: Detect Environment

"${CLAUDE_PLUGIN_ROOT}/scripts/sdg_detect.sh"

Step 2: Install if Needed

If library=missing:

• Explain: "sdg_hub is a framework for synthetic data generation — it uses composable blocks and YAML-defined flows to build LLM training datasets from seed data."
• Ask permission: "I can install it for you. Want me to proceed?"
• If yes and installer=uv: run uv pip install sdg_hub
• If yes and installer=pip: run pip install sdg_hub
• If installer=none: tell the user they need Python and pip/uv installed first

Step 3: Quick Setup or Custom

Also check for API keys in the environment:

echo "openai_key=${OPENAI_API_KEY:+found}" "anthropic_key=${ANTHROPIC_API_KEY:+found}"

If an API key was detected, offer a one-question fast path:

"I detected your OpenAI API key. I can set up with these defaults:

• Model: openai/gpt-4o-mini
• Temperature: 0.7
• Concurrency: 5

Accept these defaults, or would you like to customize?"

If the user accepts, skip to Step 5 using the detected key and defaults.

For Anthropic keys, default to anthropic/claude-sonnet-4-20250514.

If no API key was detected, or the user wants to customize, proceed to Step 4.

Step 4: Collect Configuration

Ask these questions one at a time:

1. Model: "Which LLM model do you want to use for generation?" — e.g., openai/gpt-4o-mini, meta-llama/Llama-3.3-70B-Instruct, anthropic/claude-sonnet-4-20250514
2. API endpoint: "What's your model endpoint URL?" — e.g., http://localhost:8000/v1 for vLLM, or leave empty for cloud provider defaults
3. Temperature: "What temperature for generation?" (default: 0.7)
4. Max concurrency: "How many parallel LLM requests?" (default: 5) — higher is faster but may hit rate limits
5. Checkpoint directory: "Where should generation checkpoints be saved?" (default: ./checkpoints) — allows resuming interrupted runs