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canopic jug [soylentnews.org] writes:

Developer Niels Provos has a short guide on building your own generative AI search engine using Python and PlanAI [provos.org]:

PlanAI [getplanai.com] is an open-source Python framework that simplifies building complex AI workflows. In this tutorial, we’ll implement a generative AI search engine similar to Perplexity using PlanAI’s task-based architecture and integrations.

This tutorial is aimed at developers with a basic understanding of Python and general familiarity with AI concepts. We’ll be building a search engine that can answer complex questions by synthesizing information from multiple web sources. It’s “Perplexity-style” in that it provides a concise, AI-generated answer along with cited sources, much like the search engine Perplexity.ai. PlanAI makes building this type of application much easier by handling the complexities of task dependencies, data flow, caching, and integrating with various Large Language Models (LLMs). It even allows for human-in-the-loop input when automated methods fail, making it robust for real-world scenarios.

He goes over the prerequisite skills and tools, gives an overview of the architecture, and then walks through the steps with code examples.

The result is a search engine build from a Large Language Model (LLM)

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