Build Blazing-Fast LLM Apps with Groq, Langflow, & LangChain
In this recorded webinar, experts from Groq Inc., Langflow, and LangChain come together to discuss building blazing-fast LLM applications. The session is moderated by David Jones-Gilardi, who guides the exploration of Groq’s LLM model inference, Langflow’s no-code approach, and LangChain’s simplified code integration.
Hatice Ozen from Groq introduces their LPU inference engine, which offers world-record-breaking inference speeds for large language models. She demonstrates how to get started with Groq’s models using their API and chat UI, emphasizing the ease of switching from other APIs to Groq’s for faster performance.
Misbah Syed from Langflow showcases how to build LLM applications without coding using Langflow’s drag-and-drop interface. He provides examples of creating basic and advanced workflows, integrating Groq’s models, and exporting the flows for deployment.
Lance Martin from LangChain discusses tool calling and its importance in building agent applications. He explains how LangChain integrates Groq’s models for efficient tool use and demonstrates building reliable agents using LangGraph, a new way to layout agent workflows.
The webinar includes interactive elements like Q&A sessions and polls to engage the audience. The experts provide resources, including links to GitHub repositories, video tutorials, and documentation, to help developers get started with these tools.
Overall, the webinar highlights the synergy between Groq, Langflow, and LangChain in accelerating the development of LLM applications, offering both no-code and code-based solutions for developers.