A practical look at using tower as the middleware layer for Rust AWS Lambda functions, with examples that build up to a DynamoDB-backed per-IP rate limiter. It covers Service, Layer, stack ordering, short-circuiting, boxed async futures, and testing middleware without deploying a Lambda. Comments
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Fixed-length chunking requires no external services, yet semantic chunking absolutely needs an Embedding API — why? The core idea of semantic chunking is to split text at semantic boundaries. Determining whether "two pieces of text belong to the same topic" requires converting text into vectors and computing similarity — that's exactly what the Embedding API does. Dimension Fixed-Length / Recur
RAG stands for Retrieval Augmented Generation. Why do we even need RAG?? To answer this lets take a look at What LLMs and SLMs are. LLM(Large Language Model). Data on several categories(generalized) will be given as input. From that, a model would be created. What is a model ? To understand this, lets take mathematical equation of a straight line y = mx +c Lets take x values to be 1, 2, 3, ... a
Why Do We Need Specialized Vector Databases? In the first five articles, we figured out how to chunk documents and generate embeddings. Now where do these vectors live, and how are they efficiently retrieved? You might wonder: "Can't I just store vectors in Redis or PostgreSQL?" No — traditional databases are designed for exact queries (e.g., WHERE id = 123), while vector retrieval is Approximat
A hands-on dev review focused on i18n, date/number formatting, and non-ASCII edge cases. Why I Tested TestSprite for Locale Handling Specifically Most AI testing tools get reviewed for their core functionality — does it find bugs, does it write good test code, does it integrate with CI/CD. Those reviews exist. What I couldn't find was a focused review on how TestSprite handles locale-specific edge