Firecrawl for Internet-Enabled LLM Responses with Model Routing

In this video, I'll show you how to set up internet-enabled responses from LLMs using Serper, Firecrawl with dynamic model routing. We'll utilize a model router called Not Diamond to dynamically route queries to different models, including Anthropic, OpenAI, and Gemini. You'll learn to scrape web pages, handle embeddings with Langchain and OpenAI, and configure various APIs. I'll walk you through the entire setup process, including installing dependencies and creating the necessary routes and functions in TypeScript. By the end, you'll be able to create a flexible, context-aware LLM response system.

00:00 Introduction to Internet-Enabled Responses
00:04 Setting Up the Tools
00:15 Model Routing with Not Diamond
00:26 Example Query: Chat GPT Canvas
00:51 Skipping Embeddings for Full Context
01:49 API Keys and Configuration
02:30 Installing Dependencies
03:17 Setting Up the API Route
04:07 Search Functionality with Serper
05:07 Scraping with Firecrawl
06:46 Embedding Setup and Optimization
07:53 Generating LLM Responses
08:25 Final Steps and Error Handling
10:00 Conclusion and Thanks

[kevinconnolly]

Very cool! Thank you for your time in creating this and sharing it with us all. Well done.