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Building AI agents with Gen AI Toolbox for Databases and Dgraph
- Gen AI Toolbox for Databases, in partnership with Hypermode, expands its capabilities to support Dgraph, a fully open-source graph database for AI apps.
- Dgraph offers real-time performance, horizontal scalability, AI-native primitives, and flexible data modeling, making it ideal for recommendation systems and knowledge graphs.
- The integration between Dgraph and Toolbox simplifies configuration, offers production-ready infrastructure, and enhances enterprise-grade observability for application developers.
- A real-world use case is demonstrated where an ecommerce agent is built using a polyglot database approach involving AlloyDB for PostgreSQL, Dgraph for personalized recommendations, and LangChain for workflow orchestration.
- By modeling a product knowledge graph in Dgraph, developers can generate personalized recommendations using Dgraph Query Language (DQL) efficiently.
- Tools in Toolbox are defined using YAML, enabling parameterized database queries for seamless interaction with both PostgreSQL and Dgraph.
- LangChain framework is utilized to build the agent, connecting to the Toolbox server, loading the toolset, and implementing a chat interface using Gemini Pro LLM via Google's Vertex AI cloud service.
- Gen AI-powered shopping assistant created with Toolbox delivers natural language search capabilities, product information retrieval, personalized recommendations, and product reviews to enhance the user experience.
- Gen AI Toolbox for Databases simplifies database connectivity complexities, enabling developers to focus on delivering seamless user experiences with database-connected agents.
- Developers interested in building database-connected agents can explore Gen AI Toolbox with Dgraph support through various resources provided by Hypermode and Google.
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