Self-paced: RAG using LangChain.

Self-paced: Functions, Tools, and Agents with LangChain.

Online meeting: Use Case Tutorial and Demonstration.

Retrieval Augmented Generation using LangChain.

Exploring LangChain tools and agents.

Tutorial and demonstration of use cases.

In this tutorial, we describe and show every step in building your own local RAG application using Milvus, LangChain, Ollama and Llama 3.x. At the end of the talk, you will have a working RAG application. We will also cover tips and techniques to upgrade to more advanced RAG apps.

Exploring agents with frameworks like Langchain and vector databases; learn how to build apps that can perform tasks autonomously.

There will be some Python, but Python is kind of a neutral language and I'm not overly concerned about coding details.

Hands-on, beginner-friendly workshop covering LLM basics, Python, LangChain, LangGraph, retrieval-augmented generation (RAG), prompt engineering, LangChain introduction, and workflow automation with LangGraph, including a live demo of building your first AI agent.

In this talk, I will demonstrate how we leverage LangChain embedded in OBTO's application development platform to create developer agents capable of building and updating end-to-end web applications. OBTO introduces an innovative approach to structuring applications, which, combined with effective prompt engineering and fine-tuned models, significantly enhances the accuracy of these agents. Our platform ensures seamless communication across the tech stack using a unified language, and it incorporates flexible ways to optimize and manage the performance of these interactions. Additionally, OBTO enables continuous feedback loops to refine and improve the agent setups, ensuring a robust and efficient development process.

We’ve built North America's most capable pharmacy agents using LangChain and Elasticsearch, securing over $1M in pre-seed funding and serving pharmacy chains with over a thousand stores. I was at the Google Montreal office 2 weeks ago sharing my experiences at a genAI panel. I’d love to give a lightning talk at the Elastic and LangChain NYC Meetup on building high-accuracy agents for high-risk industries. Healthcare is a tough industry but LangChain helped us tremendously. Our journey through due diligence and navigating legacy sectors could offer valuable insights.

Earlier this month, my band did a run of shows in the Shanghai area, and there were some press clippings in Chinese that I needed to translate. I built an example application that translates the text of these clippings from Chinese to English using Doctran and uses vector search in Elasticsearch to learn more about the translated documents.

Discover how evaluations and LangSmith helped improve its performance and effectiveness.