LangGraph 101: (with code snippets) Are you new to LangGraph? Curious about how to build AI Agents using LangGraph @LangChain? This thread is for you. A Thread 🧵👇What is LangGraph? LangGraph is a low-level orchestration framework designed for building stateful, multi-agent systems by representing workflows as graphs Its core architecture is built upon four primary components: 1. State 2. Nodes 3. Edges 4. Graph1. State: The application's memory The State is a shared data structure that acts as the application's memory. It tracks variables and context that nodes can access and modify during execution.2. Nodes (The "Workers") Nodes are individual Python functions or operations that perform specific tasks . Every node receives the current state as input, processes it, and returns a dictionary containing updates to that state3. Edges (The "Roadmap") Edges define the flow of execution between nodes. • Normal Edges: Create a direct, sequential path from one node to another • Conditional Edges: Use logic-based routing to decide the next step based on the current state (e.g., a router deciding between a therapist agent or a logical agent) . • Virtual Nodes: The graph uses START and END to mark where the workflow begins and concludes4. The Graph (Orchestration Framework) The StateGraph is the framework used to design and manage the task flow. Once the nodes and edges are defined, the graph must be compiled into a runnable application and then invoked with an initial stateHere is the complete working code all together. Build your first agent and let me know what you think about it.I hope you find this post useful. Follow me @itsafiz for more such content. Like and RT this post to share with your friends.

LangGraph 101: (with code snippets) Are you new to LangGraph? Curious about how to build AI Agents using LangGraph @LangChain? This thread is for you. A Thread 🧵 ... What is LangGraph? LangGraph is a low-level orchestration framework designed for building stateful, multi-agent systems by representing workflows as graphs Its core architecture is built upon four primary components: 1. State 2. Nodes 3. Edges 4. Graph ... 1. State: The application's memory The State is a shared data structure that acts as the application's memory. It tracks variables and context that nodes can access and modify during execution. ... 2. Nodes (The "Workers") Nodes are individual Python functions or operations that perform specific tasks . Every node receives the current state as input, processes it, and returns a dictionary containing updates to that state ... 3. Edges (The "Roadmap") Edges define the flow of execution between nodes. • Normal Edges: Create a direct, sequential path from one node to another • Conditional Edges: Use logic-based routing to decide the next step based on the current state (e.g., a router deciding between a therapist agent or a logical agent) . • Virtual Nodes: The graph uses START and END to mark where the workflow begins and concludes ... 4. The Graph (Orchestration Framework) The StateGraph is the framework used to design and manage the task flow. Once the nodes and edges are defined, the graph must be compiled into a runnable application and then invoked with an initial state ... Here is the complete working code all together. Build your first agent and let me know what you think about it. ... I hope you find this post useful. Follow me @itsafiz for more such content. Like and RT this post to share with your friends.