DAT

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DAT addresses the critical challenge of enterprise data querying by allowing business users to communicate directly with databases using natural language. It leverages a robust pre-modeled semantic layer to ensure that AI-driven responses are not only confident but also accurate and reliable. The tool's core innovation stems from its Askdata Agent workflow, meticulously designed to prioritize precise and complete knowledge, execute multiple computational steps, and allow for extended deliberation, thereby delivering high-quality and deterministic results crucial for real-world commercial applications.

Características Principales

• Intelligent semantic SQL generation driven by LLM-based natural language understanding
• Comprehensive multi-database support for MySQL, PostgreSQL, Oracle, and more
• 132 GitHub stars
• Rich semantic modeling capabilities for entities, dimensions, and measures via YAML configuration
• Pluggable SPI architecture supporting flexible integration of databases, LLMs, and embedding models
• Vectorized Retrieval Augmented Generation (RAG) for content storage, semantic retrieval, and business knowledge vectorization

Casos de Uso

• Empowering business users to query complex enterprise data using natural language, bypassing SQL expertise
• Developing custom AI-powered data querying applications and user interfaces based on the DAT framework and SDK
• Integrating natural language data interaction services into existing Java applications or offering them via OpenAPI/MCP