<ul><li>Langchain simplifies development by allowing tasks to be ‘chained’ together, integrating with major LLM interfaces and APIs for designing intelligent systems.</li><li>Langgraph adds functionalities to build efficient AI workflows, focusing on state management and type validation for control granularity.</li><li>With Langgraph, building the graph involves defining nodes and edges with Python functions, enabling human-in-the-loop interactions and tool binding.</li><li>The workflow involves parsing user prompts, calling tools in the right sequence for reasoning, decision-making, and knowledge graph creation pushed to Neo4J using Langgraph.</li></ul>

Exploring Agentic Workflows with Langgraph and Neo4j

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