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Azure HorizonDB integrates with leading LLM orchestration frameworks for building both AI applications and autonomous agents. These frameworks provide the scaffolding for managing LLMs, embedding models, agent memory, multi-agent workflows, and database connectivity.
Framework integrations
The following frameworks and services integrate with Azure HorizonDB:
| Framework | Description | Azure HorizonDB integration |
|---|---|---|
| Microsoft Agent Framework (incorporating Semantic Kernel) | A unified, production-ready open-source SDK by Microsoft for building AI agents in .NET and Python. It merges the orchestration and plugin capabilities of Semantic Kernel with multi-agent workflow patterns. | Python connector .NET connector Java connector |
| LangChain / LangGraph | LangChain simplifies LLM application development with tools for context-aware reasoning in Python and JavaScript. LangGraph adds stateful, graph-based orchestration for complex multi-agent workflows with checkpointed execution. | Develop AI apps with LangChain and Azure HorizonDB (Preview) JavaScript |
| LlamaIndex | A framework for building context-augmented AI applications that integrates private or domain-specific data with LLMs for complex workflows. Excels at structured data retrieval and knowledge-graph-powered reasoning. | Python |
| GraphRAG | A framework by Microsoft that uses Azure HorizonDB to create AI-powered knowledge graphs. It enables robust data models and reveals relationships in semistructured data. | Quickstart |
| CrewAI | An open-source framework for orchestrating role-based, collaborative multi-agent workflows with task delegation and standard operating procedures. | PGSearchTool |
| Auto-Gen | A Microsoft framework for multi-agent conversation patterns. Supports flexible agent communication topologies and tool integration. | PostgreSQL tools |
| Microsoft Foundry Agent Service | A managed service for building, deploying, and scaling AI agents with built-in tool support, tracing, and monitoring. | Overview |