Tutorials - Code-First Guides for Agentic AI Development
Explore step-by-step tutorials for building agentic AI software. Here's what you can expect:
- 💡 Simple breakdowns of complex AI concepts
- 🛠️ Practical tips on applying AI in real-world scenarios
- 🌐 Insights into AI's tools, frameworks and techniques
Learn the tools, techniques, and best practices to create production-ready AI applications!
Latest Tutorials
LangGraph Tutorial: Implementing Multi-Response Agent Architecture - Unit 1.3 Exercise 3
Learn how to implement a multi-response agent architecture in LangGraph using specialized response nodes. This tutorial covers classification-based response generation, state context preservation, and message type management to enable intelligent, context-aware conversation flows.
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LangGraph Tutorial: Implementing Tool Calling Node - Unit 2.1 Exercise 2
Explore how to implement a tool-calling node in LangGraph that intelligently determines when to use tools and structures tool calls based on user input. This tutorial covers state management, decision-making logic, and the generation of well-structured tool invocations for seamless integration into multi-agent workflows.
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LangGraph Tutorial: Intelligent Tool Selection System - Unit 2.2 Exercise 4
Learn how to build an intelligent tool selection system in LangGraph that uses message type management and state tracking to decide which tools to invoke based on user input. This tutorial explores message hierarchy, conversation flow control, and robust logic for selecting and reasoning about tools for various tasks.
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LangGraph Tutorial: Mastering ToolNode Implementation - Unit 2.2 Exercise 6
Master the implementation of ToolNode in LangGraph with this comprehensive tutorial. Learn how to structure state management, create robust tools, and execute them efficiently with proper message formatting, result handling, and error management. This exercise demonstrates critical best practices to build scalable and reliable tool execution workflows.
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LangGraph Tutorial: Message Classification and Routing System - Unit 1.3 Exercise 5
Learn how to build a dynamic message classification and routing system in LangGraph with this hands-on tutorial. Explore advanced state management, confidence-based classification, and multi-node response handling. Develop robust workflows with conditional edge routing and create flexible, scalable systems for intelligent conversation management.
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LangGraph Tutorial: Message History Management with Sliding Windows - Unit 1.2 Exercise 3
Explore how to efficiently manage conversation history with a sliding window approach in LangGraph. This tutorial covers state-based message management, automatic pruning, and memory optimization techniques, ensuring scalable and context-aware workflows. Learn how to maintain recent context while controlling resource usage in production environments.
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LangGraph Tutorial: Parallel Tool Execution State Management - Unit 2.3 Exercise 1
Learn how to manage state effectively for parallel tool execution in LangGraph. This tutorial explores creating a robust state structure for concurrent operations, tracking pending tools, managing results and errors, and ensuring type safety. Discover how to initialize and update the state to streamline multi-tool workflows and handle results seamlessly.
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LangGraph Tutorial: Parallel Tool Execution - Unit 2.3 Exercise 4
Discover efficient state management practices, optimize performance for multi-tool workflows, and ensure stability in production environments. This hands-on guide includes robust implementation patterns, debugging tips, and practical demonstrations to help you scale your LangGraph applications.
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LangGraph Tutorial: Processing Tool Results - Unit 2.1 Exercise 4
Learn to process raw tool outputs into structured messages and integrate them into conversation flows with LangGraph. This tutorial covers result handling, state management, and flow control to create coherent, dynamic workflows.
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LangGraph Tutorial: Rate Limiting Implementation - Unit 2.2 Exercise 3
Learn to implement rate limiting in LangGraph applications for controlling tool usage and ensuring system stability. This tutorial covers state management, usage tracking, and error handling to prevent resource abuse and maintain fair usage policies.
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LangGraph Tutorial: Result Aggregation Patterns - Unit 2.3 Exercise 5
Learn how to implement result aggregation in LangGraph using binary operators and fan-in patterns. This tutorial covers combining tool outputs, structuring error summaries, and maintaining message flow for efficient and coherent conversations.
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LangGraph Tutorial: State Initialization Patterns - Unit 2.3 Exercise 7
Learn to implement robust state initialization patterns in LangGraph for multi-tool agents. This tutorial covers designing flexible state structures, managing tool configurations, and creating dynamic initialization scenarios with type safety and customization options.
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LangGraph Tutorial: Testing Configuration - Unit 2.3 Exercise 9
Explore robust testing strategies for LangGraph applications. This tutorial covers mock tool creation, state validation, scenario testing, and graph-based workflows, ensuring reliable and comprehensive test coverage for complex systems.
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LangGraph Tutorial: Tool Configuration for Parallel Execution - Unit 2.3 Exercise 2
Learn how to configure tools for parallel execution in LangGraph, including real and mock tool setups, secure API key management, and testing with consistent settings for streamlined development and reliable functionality.
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LangGraph Tutorial: Tool Execution with Configuration Management - Unit 2.1 Exercise 3
Learn to execute tools in LangGraph with secure configuration management, including API key handling, state tracking, and error recovery. This tutorial ensures robust tool execution and consistent state management for reliable operations.
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LangGraph Tutorial: Tool Result Processing - Unit 2.2 Exercise 7
Learn how to process and format tool execution results in LangGraph. This tutorial covers result state management, error handling, message generation, and maintaining state immutability to ensure consistent and robust conversation flow.
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LangGraph Tutorial: Tool State Setup with Mock Integration - Unit 2.1 Exercise 1
Learn how to set up a tool-enabled state in LangGraph with mock API integration. This tutorial covers configuration management using Pydantic, state initialization with TypedDict, and tool setup for seamless execution, providing a secure and modular foundation for LangGraph applications.
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LangGraph Tutorial: Error Handling Patterns - Unit 2.3 Exercise 6
Learn how to implement robust error handling patterns in LangGraph. This tutorial covers error categorization, routing, and analytics to build resilient systems. Explore strategies for error tracking, message-based reporting, and systematic recovery, ensuring stability and transparency in multi-tool workflows.
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LangGraph Tutorial: Graph Configuration and Routing - Unit 2.3 Exercise 8
Master the essentials of building and configuring execution graphs in LangGraph. This tutorial explores graph structure design, parallel processing, conditional routing, and state management to create scalable, robust workflows for multi-tool systems.
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LangGraph Tutorial: Advanced Message Classification with State Management - Unit 1.3 Exercise 1
Learn how to implement advanced message classification in LangGraph with state management. This tutorial explores classification metadata, confidence scoring, and type-safe message handling for enhanced conversational agents.
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LangGraph Tutorial: Advanced Message Processing with State Management - Unit 1.2 Exercise 2
Learn advanced message processing techniques in LangGraph with state management. This tutorial covers state management with multiple fields, message processing logic, type safety with TypedDict, and field preservation in state updates for robust conversational agents.
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LangGraph Tutorial: Advanced State Management with Extended Fields - Unit 1.2 Exercise 1
Explore advanced state management in LangGraph with extended fields for context tracking and memory control. Learn how to enhance your state structure for robust conversational agents.
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LangGraph Tutorial: Asynchronous Tool Execution - Unit 2.3 Exercise 3
Learn how to implement asynchronous tool execution in LangGraph, including parallel processing, timeout management, and error handling, for efficient and responsive conversational systems.
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LangGraph Tutorial: Building a Tool-Enabled Conversational Agent - Unit 2.1 Exercise 5
Discover how to create a conversational agent that combines AI-driven decision-making with real-world tools for dynamic, context-aware interactions.
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LangGraph Tutorial: Building Advanced Multi-Node Message Processing Pipelines - Unit 1.2 Exercise 5
Discover how to build advanced multi-node message processing pipelines in LangGraph. Learn pipeline design, state flow management, and modular node integration for scalable AI workflows.
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LangGraph Tutorial: Building Agent Graphs - Unit 2.2 Exercise 9
Learn how to build agent graphs in LangGraph for dynamic, tool-enabled conversations. Explore node implementation, flow control, and state management to create advanced AI systems.
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LangGraph Tutorial: Building an Advanced Stateful Conversation System - Unit 1.1 Exercise 5
Master the art of building advanced stateful conversation systems with LangGraph. Learn memory management, sentiment-based responses, and dynamic conversation flows for smarter AI agents.
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LangGraph Tutorial: Building Your First Graph - Unit 1.1 Exercise 3
Learn how to build your first graph in LangGraph! Discover the basics of StateGraph, node creation, edge configuration, and graph execution to kickstart your journey into graph-based conversation flows.
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LangGraph Tutorial: Complete Multi-Tool Agent System - Unit 2.2 Exercise 10
Build a complete multi-tool agent system with LangGraph! Learn to integrate tools, manage state, enforce rate limits, and coordinate system flow for robust AI-driven solutions.
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LangGraph Tutorial: Complete System Integration - Unit 2.3 Exercise 10
Master LangGraph with a complete system integration tutorial! Learn to combine multi-tool parallel execution, advanced state management, error handling, and performance monitoring to build production-ready AI systems.
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LangGraph Tutorial: Conversation Flow Control - Unit 2.2 Exercise 8
Learn to master conversation flow control in LangGraph! This tutorial covers state-based routing, end condition detection, and step transitions to build seamless, context-aware conversational agents.
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LangGraph Tutorial: Creating Custom LangChain Tools - Unit 2.2 Exercise 2
Discover how to create powerful custom tools in LangChain with this hands-on tutorial. Learn to define and implement tools for mathematical calculations and weather simulations, following modern best practices.
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LangGraph Tutorial: Creating Dynamic Conversation Flows - Unit 1.1 Exercise 4
With step-by-step guidance, explore techniques for annotated message handling, flexible flow control, and proper termination management, ensuring seamless and robust interactions.
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LangGraph Tutorial: Direct Tool Execution System - Unit 2.2 Exercise 5
Learn how to build a direct tool execution system in LangGraph with safe mathematical evaluations, robust error handling, and state management. This tutorial guides you through defining tools, implementing an execution engine, and testing with various scenarios to ensure reliability and scalability.
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LangGraph Tutorial: Dynamic Conversation Summarization - Unit 1.2 Exercise 4
This tutorial demonstrates how to maintain context in long-running conversations by implementing intelligent summarization techniques. Learn to manage message histories efficiently, generate summaries dynamically, and integrate summarization logic into LangGraph for scalable conversation processing.
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LangGraph Tutorial: Enhanced State Management for Multi-Tool Agents - Unit 2.2 Exercise 1
Learn how to implement enhanced state management for multi-tool agents in LangGraph. This tutorial covers creating a state structure for tool usage tracking, rate limiting, and type-safe updates, ensuring precise control over tool execution and clear status monitoring.
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LangGraph Tutorial: Implementing Advanced Conditional Routing - Unit 1.3 Exercise 4
Learn how to implement robust error handling patterns in LangGraph. This tutorial covers error categorization, routing, and analytics to build resilient systems. Explore strategies for error tracking, message-based reporting, and systematic recovery, ensuring stability and transparency in multi-tool workflows.
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LangGraph Tutorial: Implementing Message Classification Nodes - Unit 1.3 Exercise 2
Learn how to implement message classification in LangGraph using dedicated classifier nodes. This tutorial covers content analysis, confidence scoring, and state preservation to create robust systems for intent-based routing and automated decision-making.
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LangGraph Tutorial: Understanding State Management - Unit 1.1 Exercise 1
Learn the fundamentals of state management in LangGraph. This tutorial covers creating type-safe state containers with TypedDict, ensuring data consistency and reliability for conversational agents.
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LangGraph Tutorial: Working with LangChain Messages - Unit 1.1 Exercise 2
Learn how to work with LangChain message types in LangGraph. This tutorial covers message hierarchy, type-safe storage, and state integration to build robust conversational agents.
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GPU Memory Requirement Calculator for AI Models
Use this calculator to estimate the GPU memory required to run an AI model based on parameters like number of parameters, byte size, bits for model loading, and overhead.
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Getting Started with NVIDIA NIM: A Comprehensive Tutorial
Learn how to leverage NVIDIA NIM for various AI tasks including chat completion, vector embeddings, text-to-image generation, and more.
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Efficient Document Retrieval with ColPali and BLIP-2 for AI Queries
Discover a cutting-edge AI-powered document retrieval system using ColPali and BLIP-2 models. This open-source project efficiently extracts relevant pages from large document sets before querying them with BLIP-2, significantly reducing computational costs. Ideal for handling PDFs and images, the system enables quick, accurate insights with minimal resources. Explore the full repository and learn how to enhance your document query process at AI Product Engineer.
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