Practical guides to AI, Python, Git, SQL, Web/API, SAP/ERP and mathematical models, with explanations, code examples, sources and limitations.
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A technical guide explaining why syntactically correct JSON from Large Language Models (LLMs) is insufficient for production systems and how JSON Schema provides the necessary structural and type guarantees.
Learn how to parse JSON data in Python from both string literals and files, and how to effectively handle potential decoding errors using the built-in json module.
Step-by-step guide to creating an index, generating embeddings, and executing hybrid queries that combine full-text and vector search using Azure AI Search.
Explore the principles of semantic search, its reliance on embeddings, and the reasons why text that appears similar might not provide the desired answer. Learn about vector search, hybrid search, and their applications in information retrieval.
Use If-None-Match to revalidate cached responses and If-Match to avoid overwriting a newer representation.
Understand the differences between offset-based and cursor-based pagination and when to use each, especially when dealing with frequently changing datasets.
How Python resolves relative paths depends on the process working directory, which varies by launcher. This guide shows how to inspect the working directory, choose and document an explicit path base, and understand why __file__ cannot always be trusted.
Distinguish response access from request sending, inspect an OPTIONS preflight and configure explicit origins for credentialed browser requests.