Model Fallback Middleware Overview - Langchain's model fallback middleware enhances application reliability by providing alternative models during outages or API quota exhaustion [1] - The middleware allows fallback to models from different providers, such as switching from OpenAI to Anthropic [3] - Users can specify multiple fallback models to ensure continued functionality [3] Implementation and Demonstration - The demonstration simulates model failure using non-existent Anthropic models and successfully falls back to GPT-4 mini from OpenAI [4] - The Linksmith trace view illustrates the initial failure of the primary and fallback models before successfully using the final GPT-4 mini model [5] - The middleware is implemented using Langchain's create agent primitive [4] Benefits and Usage - The model fallback middleware helps build more resilient agents capable of handling model outages and API credit limitations [3] - It allows applications to remain functional by automatically switching to a safe and functional model [1] - Creating a custom middleware is possible, offering flexibility beyond the built-in options [2]