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Build agentic RAG on Google Cloud databases with LlamaIndex
- Agentic RAG is a type of AI agent that combines the power of information retrieval with advanced action planning capabilities, such as multiple-step tasks that reason, plan, make decisions, and execute goals.
- LlamaIndex is a framework for building knowledge-driven and agentic systems, providing pre-built agent architectures and customizable workflows for developers to build sophisticated AI agents.
- LlamaIndex has collaborated with Google Cloud databases including AlloyDB for PostgreSQL and Cloud SQL for PostgreSQL, offering integrations for LlamaIndex Vector Store, Document Store, and Index Store.
- LlamaIndex supports various industry use cases, including report generation, agentic RAG, customer support, SQL agents, and productivity assistants.
- Joint customers of LlamaIndex and Google Cloud databases can expect a streamlined knowledge retrieval process, efficient complex document parsing, and secure authentication and authorization.
- LlamaIndex Workflows provide the flexibility to build and deploy complex agentic systems with granular control of conditional execution, as well as powerful state management.
- Report generation spans many industries, and LlamaIndex provides all the core components for generating reports such as structured output definitions, intelligent document parsing, knowledge base storage, and agentic workflows.
- Developers can follow the provided tutorial to get started with LlamaIndex integrations for AlloyDB and Cloud SQL for PostgreSQL.
- Overall, the LlamaIndex and Google Cloud collaboration opens up new possibilities for developers to build cutting-edge, knowledge-driven AI agents.
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