Architecting Agent Workflows with LangGraph
Curriculum
- 13 Sections
- 140 Lessons
- 10 Weeks
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- 📘 Architecting Agent Workflows with LangGraph – Index Page📋 LangGraph Overview & Setup11
- 1.1What is LangGraph and its purpose in modern agent development
- 1.2Comparison with traditional chatbots and linear workflow systems
- 1.3LangGraph vs other agent frameworks (AutoGen, CrewAI, etc.)
- 1.4LangGraph’s position in the LangChain ecosystem and architecture
- 1.5Use cases and real-world applications across industries
- 1.6Understanding agent workflows and state management principles
- 1.7Key benefits: modularity, observability, and scalability
- 1.8Installing LangGraph and managing dependencies
- 1.9Setting up development environment and project structure
- 1.10Configuration management and initial setup best practices
- 1.11Development workflow and testing environment setup
- 🚀 Building Your First Graph12
- 2.1Core primitives: nodes, edges, and state fundamentals
- 2.2Understanding graph execution flow and lifecycle
- 2.3Single-node vs multi-node architectures and design patterns
- 2.4Node definition and implementation strategies
- 2.5Input/output handling and data transformation
- 2.6State passing between operations and nodes
- 2.7Building a basic single-node graph with practical examples
- 2.8Execution patterns and flow control mechanisms
- 2.9Creating an “IsEven” checker graph (hands-on exercise)
- 2.10Running your first graph and understanding execution
- 2.11Debugging basic issues and troubleshooting techniques
- 2.12Output verification, validation, and testing strategies
- 🔗 Multi-Node Graph Design12
- 3.1Sequential node execution patterns and orchestration
- 3.2Data flow between nodes and transformation pipelines
- 3.3State transformation patterns and data processing
- 3.4Parallel execution strategies and concurrent processing
- 3.5Fork and merge architectures for complex workflows
- 3.6Conditional branching basics and decision points
- 3.7Graph topology design principles and best practices
- 3.8Linear workflow construction and implementation
- 3.9Branching workflow implementation and management
- 3.10Node composition, reusability, and modular design
- 3.11Complex graph structures and advanced patterns
- 3.12Performance considerations in multi-node designs
- 🎛️ Conditional & Dynamic Routing12
- 4.1If-Else logic implementation and conditional structures
- 4.2Switch statement patterns and multi-way branching
- 4.3Dynamic routing strategies and adaptive flow control
- 4.4Condition evaluation techniques and decision logic
- 4.5Loop and iteration patterns with controlled execution
- 4.6Retry logic implementation and failure recovery
- 4.7Smart routing decisions based on context and state
- 4.8Interactive flow control and user-driven routing
- 4.9State-based routing and context-aware decisions
- 4.10Error handling in routing and graceful degradation
- 4.11Advanced conditional patterns and optimization
- 4.12Performance optimization for complex routing scenarios
- 🤖 Working with LLM Nodes12
- 5.1Integrating LLMs into LangGraph workflows seamlessly
- 5.2Prompt-driven agent design and conversation management
- 5.3LLM response handling and output processing
- 5.4Message state management and conversation history
- 5.5Prompt engineering for agents and optimization techniques
- 5.6Chaining LLM calls and multi-step reasoning
- 5.7Interactive LLM workflows and dynamic conversations
- 5.8Context window management and memory optimization
- 5.9Streaming responses and real-time interactions
- 5.10Error handling for LLM calls and fallback strategies
- 5.11Optimizing LLM performance and response quality
- 5.12Cost management strategies and usage optimization
- 🧠 Maintaining & Customizing State11
- 6.1Memory management in agents and persistence strategies
- 6.2Context preservation across agent interactions
- 6.3Custom state schema design and data modeling
- 6.4Data persistence patterns and storage solutions
- 6.5State transformation techniques and data processing
- 6.6State serialization and deserialization methods
- 6.7Memory optimization strategies and performance tuning
- 6.8Cross-node state sharing and data synchronization
- 6.9State validation and integrity checking mechanisms
- 6.10Dynamic state modification and runtime updates
- 6.11State rollback mechanisms and error recovery
- 🛠️ Tool Use & Function Calls10
- 7.1Integrating external tools and API connections
- 7.2Function calling patterns and invocation strategies
- 7.3Tool selection strategies and intelligent routing
- 7.4Tool orchestration and coordination mechanisms
- 7.5Tool response handling and output processing
- 7.6Error handling for tool calls and recovery patterns
- 7.7Interactive tool usage and user-guided operations
- 7.8Chaining tool operations and complex workflows
- 7.9Tool performance optimization and caching strategies
- 7.10Async tool execution and concurrent operations
- 🔍 Debugging & Observability12
- 8.1Debugging techniques for LangGraph workflows
- 8.2LangSmith integration and monitoring setup
- 8.3Print tracing strategies and logging frameworks
- 8.4Performance monitoring and metrics collection
- 8.5Error tracking and logging best practices
- 8.6Visualization tools for workflow analysis
- 8.7Debugging complex workflows and troubleshooting
- 8.8Real-time monitoring and alerting systems
- 8.9Metrics collection and performance analysis
- 8.10Error analysis and resolution strategies
- 8.11Interactive debugging and development tools
- 8.12Performance profiling and optimization techniques
- 🚀 Deploying LangGraph Agents12
- 9.1Streamlit app integration and user interface development
- 9.2Web interface development and responsive design
- 9.3API endpoint creation and RESTful service design
- 9.4Security considerations and authentication mechanisms
- 9.5Scalability planning and architecture design
- 9.6Production deployment strategies and best practices
- 9.7Continuous integration setup and automation
- 9.8Monitoring in production and operational excellence
- 9.9Maintenance and updates for production systems
- 9.10Performance optimization and resource management
- 9.11Containerization strategies and Docker deployment
- 9.12Cloud deployment options and platform selection
- 🎯 Capstone Project: Modular Ordering Agent System12
- 10.1System architecture design for enterprise-scale systems
- 10.2Order processing workflow and business logic implementation
- 10.3Delivery agent implementation and coordination
- 10.4Multi-agent coordination and communication patterns
- 10.5State management across distributed agents
- 10.6Error handling and recovery in complex systems
- 10.7User interface integration and experience design
- 10.8Performance optimization and scalability testing
- 10.9Testing and validation strategies for agent systems
- 10.10Deployment and monitoring in production environments
- 10.11Analytics and reporting for business intelligence
- 10.12Maintenance and scaling strategies for growth
- 🧰 LangGraph Development Utilities8
- 11.1Helper functions for graph construction and management
- 11.2State management utilities and data handling tools
- 11.3Debugging and logging utilities for development
- 11.4Performance monitoring tools and metrics collection
- 11.5Graph visualization and analysis utilities
- 11.6Testing frameworks and validation tools
- 11.7Deployment utilities and automation scripts
- 11.8Configuration management and environment setup tools
- 📏 Advanced LangGraph Patterns8
- 12.1Complex workflow orchestration patterns
- 12.2Error handling and recovery strategies in production
- 12.3Performance optimization techniques for large-scale systems
- 12.4Security best practices for agent workflows
- 12.5Scalability patterns and distributed agent architectures
- 12.6Integration patterns with external systems and APIs
- 12.7Monitoring and observability in production environments
- 12.8Maintenance and evolution strategies for agent systems
- 🔄 Production Considerations8
- 13.1Deploying LangGraph agents to production environments
- 13.2Monitoring and alerting for agent workflows
- 13.3Performance optimization and resource management
- 13.4Security and compliance considerations
- 13.5Scalability planning and capacity management
- 13.6Disaster recovery and business continuity planning
- 13.7Cost optimization and resource efficiency
- 13.8Operational excellence and best practices for agent systems
Comparison with traditional chatbots and linear workflow systems
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