Introduction: Command-line tools are the developer’s natural habitat. Adding LLM capabilities to CLI tools creates powerful utilities for code generation, documentation, data transformation, and automation. Unlike web apps, CLI tools are fast to build, easy to integrate into existing workflows, and perfect for power users who live in the terminal. This guide covers building production-quality […]
Read more →Category: Technology Engineering
Technology Engineering
Multi-Modal AI: Advanced Vision, Audio, and Multi-Modal RAG (Part 2 of 2)
Introduction: Multi-modal AI combines text, images, audio, and video understanding in a single model. GPT-4V, Claude 3, and Gemini can analyze images, extract text from screenshots, understand charts, and reason about visual content. This guide covers building multi-modal applications: image analysis and description, document understanding with vision, combining OCR with LLM reasoning, audio transcription and […]
Read more →Context Window Management: Token Budgets, Prioritization, and Compression
Introduction: Context windows define how much information an LLM can process at once—from 4K tokens in older models to 128K+ in modern ones. Effective context management means fitting the most relevant information within these limits while leaving room for generation. This guide covers practical context window strategies: token counting and budget allocation, content prioritization, compression […]
Read more →Multi-Model Orchestration: Routing, Parallel Execution, and Specialized Pipelines
Introduction: Production LLM applications often benefit from using multiple models—routing simple queries to cheaper models, using specialized models for specific tasks, and falling back to alternatives when primary models fail. Multi-model orchestration enables cost optimization, improved reliability, and access to each model’s unique strengths. This guide covers practical orchestration patterns: model routing based on query […]
Read more →Building AI Chatbots with Memory: From Stateless to Intelligent Assistants
Introduction: Chatbots without memory feel robotic—they forget your name, repeat questions, and lose context mid-conversation. Production chatbots need sophisticated memory systems: short-term memory for the current conversation, long-term memory for user preferences and history, and summary memory to compress long interactions. This guide covers implementing these memory patterns: conversation buffers, vector-based retrieval, automatic summarization, and […]
Read more →Multi-Modal AI: Building Applications with Vision-Language Models (Part 1 of 2)
Introduction: The era of text-only LLMs is ending. Modern vision-language models like GPT-4V, Claude 3, and Gemini can see images, understand diagrams, read documents, and reason about visual content alongside text. This opens entirely new application categories: document understanding, visual Q&A, image-based search, accessibility tools, and creative applications. This guide covers building multi-modal AI applications […]
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