How to Set Up AWS Bedrock with Claude: A Complete Guide with Code Examples

What Is AWS Bedrock? AWS Bedrock is Amazon’s managed AI platform that provides API access to a curated selection of foundation models from multiple providers — Anthropic’s Claude, Meta’s Llama, Mistral AI, Cohere, Amazon’s own Titan models, and others — through a unified AWS API. Rather than integrating with each model provider separately, Bedrock gives … Read more

How to Use pgvector with PostgreSQL for LLM Applications: A Complete Guide

What Is pgvector? pgvector is a PostgreSQL extension that adds vector similarity search to the world’s most popular open-source relational database. Instead of running a separate vector database service alongside your Postgres instance, pgvector lets you store embeddings as a native column type and query them with familiar SQL syntax. This dramatically simplifies the infrastructure … Read more

How to Build LLM Agents with LangChain: Tools, Memory, and Production Patterns

Why LangChain for Agents? LangChain is the most widely-used framework for building LLM-powered agents and applications. Its agent abstractions handle the decision loop — deciding which tools to use, calling them, processing results, and continuing until the task is complete — so you can focus on defining tools and goals rather than orchestration logic. In … Read more

How to Use the Anthropic Claude API: A Complete Guide with Code Examples

Getting Started with the Anthropic API The Anthropic API provides access to Claude — Anthropic’s family of AI models including Claude Opus, Sonnet, and Haiku. This guide covers everything from initial setup through production-grade usage patterns including streaming, tool use, vision, prompt caching, and async processing. Install the Python SDK and set your API key: … Read more

How to Reduce LLM Token Usage and Cut API Costs Without Losing Quality

Why Token Optimisation Matters Every token sent to an LLM API costs money — both input and output tokens. At low volume, the amounts are trivial. At production scale, they become significant operational expenses that compound with every feature addition, every edge case in prompt design, and every traffic spike. An application that sends 5,000 … Read more

How to Use OpenAI Function Calling: A Complete Guide with Examples

What Is Function Calling? Function calling (also called tool use) allows LLMs to request the execution of functions you define, rather than just returning text. Instead of answering “the weather in London is 18°C” from training knowledge, the model can call a get_weather function with the argument {“location”: “London”}, receive the actual current data, and … Read more

How to Detect and Reduce LLM Hallucinations in Production Applications

What Is LLM Hallucination? Hallucination refers to LLM outputs that are factually incorrect, fabricated, or unsupported by the model’s input context — presented with the same confident tone as accurate information. The term covers a wide range of failure modes: citing research papers that do not exist, stating incorrect facts with high confidence, generating plausible-sounding … Read more

How to Build a Production RAG Pipeline with LlamaIndex: A Complete Guide

Why LlamaIndex for Production RAG? LlamaIndex is a data framework built specifically for connecting LLMs to external data sources. While LangChain is a general-purpose LLM application framework, LlamaIndex focuses specifically on the ingestion, indexing, and retrieval pipeline — the components that make RAG applications work well in production. Its abstractions for document loading, chunking strategies, … Read more