AI with Alex's Blog

A Multimodal AI Agent Application: AI Private Chef

Posted on 2026-05-11 Edited on 2026-06-10 In Python , AI
Symbols count in article: 26k Reading time ≈ 23 mins.

• Introduction
• What Are We Building?
  • Feature Overview
  • Architecture Overview
• Implementation Strategy
  • Model Selection
  • Tool Selection
  • Memory Strategy
  • System Prompt Design
• Prototyping in Jupyter
  • Environment Configuration
  • Dependencies
  • Loading Configuration
  • Defining Tools
  • Initializing the Multimodal Model
  • Memory Management
  • Creating the Agent
  • Testing with Image Input
  • Testing Conversation Memory
• Deploying with LangGraph and LangSmith
  • LangSmith Setup
  • Developing the Agent
  • Local Deployment with LangGraph CLI
  • Testing in LangSmith Studio

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LangChain Core Components: Model, Message, Prompt, Tool, Memory

Posted on 2026-05-04 Edited on 2026-06-06 In Python , AI
Symbols count in article: 26k Reading time ≈ 24 mins.

• What is LangChain?
  • The Platform
  • What is an Agent?
  • LLM vs Agent: The Difference
• Models — The Brain
  • Initializing a Model
  • Custom Models and Parameters
  • Using Model Classes
  • Calling the Model: invoke vs stream
  • Using Models in an Agent
• Messages — The Building Blocks of Conversation
  • Message Types
  • Multimodal Messages
• Prompts — Steering the Output
  • System Prompts
  • Prompt Engineering
  • Structured Output
• Tools — The Hands
  • Defining Tools
  • Custom Tools
  • Predefined Tools: Tavily Search
  • Combining Tools with an Agent
• Memory — Making the Agent Remember
  • Short-Term vs Long-Term Memory
  • Short-Term Memory with InMemorySaver
  • Persistent Memory (Optional)
  • Memory Management Strategies

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LangChain4J in Action: Building a Medical AI Assistant Agent

Posted on 2026-04-27 Edited on 2026-06-06 In Java , AI , Spring Boot
Symbols count in article: 19k Reading time ≈ 17 mins.

• 1. What is LangChain4J?
  • 1.1 The Problem LangChain4J Solves
  • 1.2 Core Concepts
• 2. Project Setup
  • 2.1 Dependencies
  • 2.2 Configuration
• 3. Your First LLM Integration
  • 3.1 Direct API Call
  • 3.2 Spring Boot Auto-Configuration
• 4. Building the AI Service
  • 4.1 The Assistant Interface
  • 4.2 System Messages
• 5. Adding Chat Memory
  • 5.1 Why Memory Matters
  • 5.2 Implementing Memory
  • 5.3 Memory Isolation
  • 5.4 Persistent Storage with MongoDB

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Message Middleware Selection Guide: RabbitMQ

Posted on 2026-04-26 Edited on 2026-06-05 In Backend Development
Symbols count in article: 11k Reading time ≈ 10 mins.

1. Introduction: Why We Need Message Middleware
2. Message Queue Comparison
3. RabbitMQ Core Concepts
4. Exchange Types Explained
5. Spring AMQP in Practice
6. Message Reliability Guarantees
7. Delayed Message Implementation
8. Best Practices & Common Issues
9. Summary

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Getting Started with Docker

Posted on 2026-04-19 Edited on 2026-06-05 In Docker , Backend Development , DevOps
Symbols count in article: 12k Reading time ≈ 11 mins.

• Understanding Docker Technology
  • Application Scenarios of Docker
  • Core Advantages
  • Core Concepts
• Docker vs Virtual Machines
• Basic Commands
• Docker Data Volumes
  • What is a Data Volume
  • Volume Commands
  • Mounting Local Directories
• Docker Networking
  • Default Networks
  • Custom Networks
• Building Custom Images
  • Image Structure
  • Dockerfile Syntax
  • Building Images
• Docker Compose
  • Basic Syntax
  • Common Commands
• Practical Examples
  • Deploying MySQL
  • Deploying a Java Application
• Best Practices
• FAQ
• Summary
• References

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Backtracking Algorithm

Posted on 2026-04-12 Edited on 2026-04-22 In Data Structure and Algorithm
Symbols count in article: 20k Reading time ≈ 19 mins.

• 1. Understanding Backtracking
  • 1.1 What is Backtracking?
  • 1.2 Real-World Analogy
  • 1.3 When to Use Backtracking
• 2. The Core Pattern
  • 2.1 The Three-Step Cycle
  • 2.2 Why “Undo” is Critical
  • 2.3 The Standard Template
• 3. Decision Tree Mental Model
  • 3.1 Tree Levels vs Branches
  • 3.2 Understanding startIndex
  • 3.3 What i + 1 Really Means
• 4. Pruning: Necessity, Not Optimization
  • 4.1 Early Termination Logic
  • 4.2 Pruning in practice
• 5. Deduplication Strategy
  • 5.1 Why Deduplication Matters
  • 5.2 The i > startIndex Pattern

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