Tutorials
In-depth AI tutorials — from fundamentals to production: RAG, agents, deployment, fine-tuning and more.
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Azure OpenAI GPT-4 Deployment: Complete Guide for AI Applications 2026
Azure OpenAI GPT-4 Deployment: Complete Guide 2026 Overview Azure OpenAI GPT-4 Deployment provides enterprise-grade AI capabilities for deploying OpenAI models with Azure compliance. As one of the leading cloud AI platforms, it offers the reliability, scalability, and security that production applications demand.
Bubble.io + OpenAI: How to Integrate AI into no-code Bubble apps (2026)
Bubble.io + OpenAI Integration Guide 2026 Overview This guide shows you exactly how to integrate AI into no-code Bubble apps using Bubble.io and OpenAI. We cover setup, core integration, and production-ready patterns. Prerequisites - Bubble.io en
Celery for AI Applications: Async task processing for AI Guide 2026
Celery for AI Applications: async task processing for AI 2026 Introduction Use Celery to handle long-running AI tasks asynchronously in Python applications. This guide shows you how to effectively use Celery in your AI development workflow. Why Ce
Chain-of-Thought Prompting: Complete Guide and Examples
Chain-of-Thought Prompting: Complete Guide What is Chain-of-Thought Prompting? Chain-of-Thought Prompting is a prompting technique that involves step-by-step reasoning in prompts. It is particularly effective for math and logic tasks. When to Use
Claude Artifacts vs GPT Code Interpreter: Side-by-Side Comparison
Claude Artifacts vs ChatGPT Code Interpreter (2026): the former is a browser-side interactive rendering canvas (UI prototypes/visualizations/publishable and shareable), the latter is a server-side Python sandbox (file analysis/data processing). If the task is 'build something interactive', choose the former; if it's 'crunch this file', choose the latter. Includes combined usage.
Claude Opus 4 API Tutorial 2026: Advanced Reasoning and Long Context
Complete Claude Opus 4 API tutorial. Covers system prompts, document analysis, tool use, vision, streaming, and cost optimization strategies for routing between Opus/Sonnet/Haiku.
Cloudflare AI Workers AI: Complete Guide for AI Applications 2026
Cloudflare AI Workers AI: Complete Guide 2026 Overview Cloudflare AI Workers AI provides enterprise-grade AI capabilities for edge AI inference with zero latency. As one of the leading cloud AI platforms, it offers the reliability, scalability, and
Cloudflare Workers + Workers AI: How to Run AI at the edge with Cloudflare (2026)
Cloudflare Workers + Workers AI Integration Guide 2026 Overview This guide shows you exactly how to run AI at the edge with Cloudflare using Cloudflare Workers and Workers AI. We cover setup, core integration, and production-ready patterns. Prereq
Constrained Generation: Complete Guide and Examples
Constrained Generation: Complete Guide What is Constrained Generation? Constrained Generation is a prompting technique that involves controlling output format via prompts. It is particularly effective for structured data. When to Use Constrained G
CrewAI Tutorial 2026: Build Multi-Agent Systems That Work Together
Complete tutorial for building multi-agent AI systems using CrewAI in 2026. Covers agent role design, task delegation, crew orchestration, tool integration, and building production workflows where multiple specialized AI agents collaborate on complex tasks.
Dify Enterprise Private Knowledge Base Complete Setup Guide: RAG Configuration & Best Practices (2026)
A detailed walkthrough of building an enterprise private knowledge base with Dify: Docker private deployment, document preprocessing strategies, chunk parameter tuning, embedding model selection, hybrid search configuration, and practical tips to fix common issues like 'irrelevant answers' or 'missing key information'.
Dify Workflow Platform: Tutorial and Best Practices
Dify Workflow Platform What is Dify? Dify is a framework for open-source LLM workflow platform. It simplifies building AI applications by providing high-level abstractions over raw LLM APIs. **Best for**: platform Installation ```bash pip instal
Directional Stimulus: Complete Guide and Examples
Directional Stimulus: Complete Guide What is Directional Stimulus? Directional Stimulus is a prompting technique that involves guiding LLM with hints and cues. It is particularly effective for targeted outputs. When to Use Directional Stimulus Us
ElevenLabs Voice AI 2026: Clone Voices, Build Podcasts, Automate Audio Content
Detailed tutorial for ElevenLabs voice AI platform covering voice cloning, multilingual TTS, audio book production, podcast automation, and building production voice applications with the API. Includes pricing analysis and ethical usage guidelines.
ElevenLabs vs Suno vs Udio: AI Audio Tools Complete Guide 2026
Complete comparison of ElevenLabs (voice AI), Suno v4 (music generation), and Udio (genre control) for professional audio production. Includes API examples and production workflow templates.
Enterprise Generative AI Adoption Playbook 2026: From Pilot to Scale
Enterprise generative AI playbook: use-case prioritization, build vs buy, RAG knowledge access, governance, cost structure, org models, and metrics.
Building Enterprise-Grade RAG 2.0 Systems: A Complete Practice from Document Parsing to Knowledge Retrieval
This article systematically introduces the construction and optimization methods of enterprise-grade RAG 2.0 systems, covering key technologies such as document parsing, query rewriting, hybrid retrieval, ranking fusion, ontology constraints, and cache optimization. Combined with real-world scenarios in manufacturing and finance, it explains in detail how to address core challenges like parsing complex document structures, multi-turn dialogue anaphora resolution, and balancing retrieval precision and recall. It also introduces ontology-driven semantic constraints and caching mechanisms to improve accuracy and response efficiency in professional domains. Suitable for developers with basic RAG knowledge who want to build production-level systems.
FastAPI + Anthropic: How to Build production FastAPI AI services (2026)
FastAPI + Anthropic Integration Guide 2026 Overview This guide shows you exactly how to build production FastAPI AI services using FastAPI and Anthropic. We cover setup, core integration, and production-ready patterns. Prerequisites - FastAPI env
FastAPI vs LangServe: Side-by-Side Comparison
FastAPI vs LangServe Comparison (2026): Default to FastAPI—LangServe is in maintenance mode, with LangChain's deployment focus shifting to LangGraph Platform. Covers reasons for LangServe's decline, code examples of FastAPI serving any LLM stack directly, and when a stateful Agent is worth using a platform.
Filesystem MCP Server: Complete Setup and Usage Guide 2026
The official Filesystem MCP Server lets AI assistants safely read, write, edit, and search files within directories you allow. Based on @modelcontextprotocol/server-filesystem: npx/Docker install, allowed-directory access control, the full file toolset, and dynamic roots.
Gemini 2.0 API Tutorial 2026: Multimodal AI with 2M Token Context
Complete Gemini 2.0 API tutorial covering multimodal inputs, 2M token context, function calling, grounding with Google Search, and code execution.
Gemini 2.5 Pro (2026-01): What's New and How to Use It
Gemini 2.5 Pro Guide (2026): Default thinking (controllable budget) + 1M long context + native multimodal defines its track. Includes API usage, long-context discipline (lost in the middle), context caching, OpenAI-compatible layer for multi-vendor routing, and current version positioning. Specifications subject to official page.
Generated Knowledge: Complete Guide and Examples
Generated Knowledge: Complete Guide What is Generated Knowledge? Generated Knowledge is a prompting technique that involves prompting to generate context before answering. It is particularly effective for factual accuracy. When to Use Generated Kn
Generative AI Enterprise Strategy: From Pilots to Production at Scale
Strategic guide for enterprises deploying generative AI at scale, covering use case prioritization, build vs buy decisions, governance frameworks, ROI measurement, and organizational change management.
GitHub + Claude: How to Add AI code review to GitHub (2026)
GitHub + Claude Integration Guide 2026 Overview This guide shows you exactly how to add AI code review to GitHub using GitHub and Claude. We cover setup, core integration, and production-ready patterns. Prerequisites - GitHub environment set up -
GitHub Copilot Advanced Tips 2026: 8 Powerful Features 90% of People Don't Use
8 advanced GitHub Copilot tips for 2026: inline Chat slash commands, repo-level copilot-instructions.md (highest leverage), #file/@workspace context variables, Edits multi-file editing, Agent mode acceptance criteria upfront, hidden completion operations, code review, and CLI.
GitHub MCP Server: Complete Setup and Usage Guide 2026
The official GitHub MCP Server lets AI tools read and write your repositories, issues, and pull requests. Based on the official github/github-mcp-server repo: remote vs local (Docker/binary) install, PAT and OAuth auth, toolset configuration, and read-only mode.
Google Vertex AI Gemini API: Complete Guide for AI Applications 2026
Google Vertex AI Gemini API: Complete Guide 2026 Overview Google Vertex AI Gemini API provides enterprise-grade AI capabilities for Google Cloud AI with Gemini multimodal capabilities. As one of the leading cloud AI platforms, it offers the reliabi
OpenAI GPT-4o API Tutorial 2026: Vision, Audio, and Real-Time Capabilities
Complete guide to OpenAI's GPT-4o API covering multimodal inputs, real-time audio streaming, function calling, and building production apps. Includes code examples for vision analysis, speech-to-text integration, and cost optimization strategies.
Groq API: Developer Guide and Quick Start 2026
Get started with the Groq API: LPU-powered low-latency LLM inference, Python SDK setup, streaming, OpenAI-compatible endpoint, rate limits, and retry patterns.
HeyGen AI Avatar Videos for Enterprise: Scaling Training and Marketing Content
Enterprise guide to HeyGen AI avatar technology for corporate training, sales enablement, and marketing localization in 40+ languages with lip-sync and LMS integration.
Hugging Face Inference API: Production Guide
Hugging Face Inference Production Guide (2026): First distinguish between two products—free serverless (for evaluation, cold start/rate limiting) vs Inference Endpoints (for production, dedicated GPU/SLA). HF wins on Hub long-tail models and private fine-tuned model hosting; mainstream LLMs are usually more cost-effective on specialized clouds. Includes cost threshold algorithm.
Human-AI Collaboration Patterns: 2025 Guide
Six Practical Models of Human-AI Collaboration (2026): AI Review, AI Draft, Human-in-the-Loop (HITL), Human-on-the-Loop, Escalation Chain, and Pair Work — select autonomy level based on "cost of error." Includes risk-graded approval gate code, plus design countermeasures for two failure modes: approval fatigue and rubber-stamping.
iOS/Swift + Apple Intelligence: How to Integrate AI into iOS apps (2026)
iOS/Swift + Apple Intelligence Integration Guide 2026 Overview This guide shows you exactly how to integrate AI into iOS apps using iOS/Swift and Apple Intelligence. We cover setup, core integration, and production-ready patterns. Prerequisites -
LangChain vs LlamaIndex: Which Framework to Choose in 2025?
Comprehensive comparison of LangChain and LlamaIndex for building LLM applications. Compare architecture, use cases, performance, and ecosystem to make the right choice for your project.
LangChain vs LlamaIndex 2026: Which Framework Should You Use for RAG?
Detailed comparison of LangChain and LlamaIndex for building retrieval-augmented generation applications in 2026. Covers architecture differences, performance benchmarks, integration ecosystems, and specific use cases where each framework excels.
Langfuse Integration: Developer Guide and Quick Start 2026
Langfuse Integration: Developer Guide 2026 What is Langfuse Integration? **Langfuse Integration** enables open-source LLM observability. This guide covers everything you need to get started quickly. Why Use Langfuse Integration? - Solves the spec
LangSmith for LLM Evaluation: Building Systematic Feedback Loops
LangSmith LLM Evaluation Workflow (2026): Trace → Dataset → Evaluator (including LLM-as-judge) → Experiment — the four-piece suite that turns "feels better" into measurable progress. Includes @traceable code, weekly evaluation loops, bias calibration for LLM judges, and comparison vs Langfuse.
Large Model Post-Training in Practice: From SFT to RL — The Complete Tech Stack
This article systematically explains the key techniques of large model post-training, including supervised fine-tuning (SFT), parameter-efficient fine-tuning (PEFT), reinforcement learning from human feedback (RLHF), and on-policy distillation (OPD). It focuses on the principles, pros and cons, and applicable scenarios of each method, and introduces a stability-plasticity trade-off framework to quantify the general capability loss caused by fine-tuning. By comparing the forgetting characteristics of full fine-tuning, LoRA, OFT, and other PEFT methods, it reveals that the destruction of activation space geometric structure is the key mechanism of forgetting. Finally, it summarizes the advantages of OPD as a new paradigm and provides practical guidelines and FAQs.
LiteLLM Provider Switching: Tutorial and Best Practices
LiteLLM Provider Switching What is LiteLLM? LiteLLM is a framework for unified API for 100+ LLM providers. It simplifies building AI applications by providing high-level abstractions over raw LLM APIs. **Best for**: multi-provider Installation `
LlamaIndex Practical Guide: RAG Application Development from Beginner to Production
LlamaIndex is purpose-built for RAG applications, making it the go-to framework for building enterprise knowledge base Q&A systems. This article covers the core architecture, key differences from LangChain, and 5 complete code examples from document loading to production deployment.
LlamaIndex vs LangChain: Which One to Use for Building RAG (2026 Hands-On Comparison)
Everyone says LlamaIndex focuses on retrieval and LangChain leans toward orchestration, but when it comes to actual projects, you still get stuck. This article breaks it down by 'what you want to do,' with real code and pitfalls, helping you make a decision in 10 minutes.
LLM API Cost Control in Practice: 12 Ways to Cut Your AI Bill from $500 to $80
A practical llm cost optimization guide: 12 actionable methods—model routing, prompt compression, semantic caching, Batch API, context trimming, attribution.
LLM Fallback Strategy: When Models Go Down, Can Your App Survive?
Production LLM fallback: retries with backoff and jitter, circuit breakers, multi-provider fallback routing, timeout budgets, cache safety nets, and pitfalls.
LLM Intent Classification: Practical Tutorial
LLM Intent Classification in Practice (2026): The entry point for chatbots/agents. Use a small model + fixed label set (literal/enum) + structured output to enforce valid intent returns, with confidence scores as fallback; for high concurrency, use embeddings or fine-tune a small model to reduce costs.
2026 Local LLM Showdown: Llama 3.3 vs Qwen 2.5 vs Mistral vs DeepSeek
Local LLM showdown 2026: Llama vs Qwen vs Mistral—Llama has the best ecosystem/tools, Qwen excels in multilingual (Chinese) and coding breadth, Mistral/Mixtral focuses on efficiency (MoE). Includes deployment (Ollama/vLLM) and quantization pipelines, model library comparison.
Loop Engineering: The New Paradigm for AI Coding Agents
Loop Engineering is a new paradigm for AI coding agent collaboration, centered on replacing manual agent instructions with automated loops. This article dives into the five core modules (automated scheduling, worktrees, project skills, plugin connectors, sub-agents) and persistent memory, with concrete implementations in Claude Code and Codex, plus Anthropic's internal Skills taxonomy and writing tips. Ideal for intermediate to advanced developers looking to move from manual operations to systematic agent orchestration.
Metacognitive Prompting: Complete Guide with Examples 2026
Metacognitive prompting makes an LLM reflect before answering: a five-stage process (understand, preliminary judgment, critical evaluation, decision, confidence), with real prompt examples and how it differs from CoT.