Tutorials
section.md. This single file contains all pages in this section, optimized for AI coding agent context.
This section contains tutorials that showcase relevant use cases and provide step-by-step instructions on how to implement various features using Flyte and Union.
Automatic prompt engineering
Easily run prompt optimization with real-time observability, traceability, and automatic recovery.GPU-accelerated climate modeling
Run ensemble atmospheric simulations on H200 GPUs with multi-source data ingestion and real-time extreme event detection.Run LLM-generated code
Securely execute and iterate on LLM-generated code using a code agent with error reflection and retry logic.Deep research
Build an agentic workflow for deep research with multi-step reasoning and evaluation.Distributed LLM pretraining
Pretrain large language models at scale with PyTorch Lightning, FSDP, and H200 GPUs, featuring streaming data and real-time metrics.Hyperparameter optimization
Run large-scale HPO experiments with zero manual tracking, deterministic results, and automatic recovery.Multi-agent trading simulation
A multi-agent trading simulation, modeling how agents within a firm might interact, strategize, and make trades collaboratively.Text-to-SQL
Learn how to turn natural language questions into SQL queries with Flyte and LlamaIndex, and explore prompt optimization in practice.