Building Cost Effective AI Pipelines with OpenAI, LangChain, and Dagster
Blog post from Dagster
This tutorial showcases an approach to leveraging Large Language Models (LLMs) like OpenAI's GPT-4 while keeping costs in check. The authors build an AI pipeline on top of Dagster's new OpenAI integration, which enables seamless interactions with OpenAI APIs and automatic usage tracking. They demonstrate how to dynamically declare different models using LangChain and utilize features of a modern orchestrator (Dagster) to improve developer productivity. The authors also discuss future directions, including expanding the use of Dagster Cloud's Insights, leveraging Dagster's data catalog, ensuring data freshness and reliability, and optimizing AI pipeline efficiency and effectiveness.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 6 | 2,643 | 305 | 124 | -22% |
| Vector Search | 6 | 1,187 | 169 | 73 | -55% |
| Developer Experience | 2 | 386 | 181 | 87 | +52% |
| Real-time | 2 | 2,009 | 572 | 187 | -14% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.