Congratulations! You’ve successfully completed the Agents module of the Neo4j & Generative AI Hands-On Workshop. 🎉
Throughout this module, you’ve learned how to build conversational agents that leverage Neo4j’s graph capabilities to provide intelligent, context-aware responses. Let’s take a moment to reflect on what you’ve accomplished.
What You’ve Accomplished
Understanding Agents
You now understand:
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What agents are - Conversational wrappers around retrievers that analyze user queries and select appropriate tools
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Agent architecture - How agents combine retrievers with conversation frameworks to create interactive systems
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The ReAct framework - How agents use reasoning and acting cycles to process queries and generate responses
Building Agents with LangChain
You’ve learned how to:
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Create agents using LangChain - Build conversational agents that integrate with Neo4j
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Integrate multiple retrievers - Combine schema, vector + Cypher, and text-to-Cypher retrievers as agent tools
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Configure agent behavior - Set up agents with appropriate prompts and tool descriptions
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Handle agent responses - Process and display agent outputs in conversational interfaces
Working with Aura Agents
You’ve explored:
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No-code agent creation - Build agents through Neo4j Aura’s web interface
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Agent tool types - Similarity Search, Cypher Template, and Text-to-Cypher tools
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Agent configuration - Set up agents with names, descriptions, and prompt instructions
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Testing and deployment - Test agents through the Aura interface and make them available via API
Additional Resources
Summary
Congratulations on completing the Generative AI Hands-On Workshop!
You’ve learned how to build conversational agents that leverage Neo4j’s graph capabilities, integrated multiple retriever types as agent tools, and explored both code-based and no-code approaches to agent creation. You’re now ready to build your own intelligent conversational applications with Neo4j and GraphRAG.