Two Ways to Execute Python With AI Agents
This tutorial will dive into the mechanics behind executing Python code with AI Agents. We will set up and agent with LangGraph, generate and then execute Python code in two distinct ways.
Benjamin Falkeborg
AI Engineer & Architect. I designed the personalization architecture for the world's largest jewelry company and automated claims handling for the leading insurance company in the Nordics
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Repeat Purchase Analytics with LLMs
This playbook will walk you through building a repeat purchase analytics library. We'll cover everything from writing SQL queries to creating a Python class for your analysis tools. We'll then create a suite of LangChain tools out of the class and let LLMs figure out how to use the different tools.
Cross-Selling and Re-Selling with LangChain
In this playbook, we'll implement a market basket recommender to find products that can be used for cross-selling. We'll then use this with the Next Product Recommender and LangChain to optimize CLV.
BigQuery-Shopify RAG with LangGraph
In this playbook, we'll build a simple product recommendation system using BigQuery's vector search capabilities combined with LangGraph.
Next Product Recommendations
In this playbook, we will develop the analytical infrastructure for building robust recommendation engines with SQL. I'll show how to use the recommenders as LLM tools, allowing you to incorporate advanced natural language capabilities into your recommendation systems.
Learn LangChain in 7 Easy Steps
In this tutorial, I will teach you LangChain as efficiently as possible by breaking down the framework into seven key components you need to understand to start developing more advanced LLM applications.