dbt-llm-agent leverages large language models to transform how data teams interact with dbt projects. It empowers users to explore and query their data models using plain English, auto-generate SQL based on high-level prompts, and retrieve model documentation instantly. The agent supports multiple LLM providers—OpenAI, Cohere, Vertex AI—and integrates seamlessly with dbt’s Python environment. It also offers AI-driven code reviews, suggesting optimizations for SQL transformations, and can generate model tests to validate data quality. By embedding an LLM as a virtual assistant within your dbt workflow, this tool reduces manual coding efforts, enhances documentation discoverability, and accelerates the development and maintenance of robust data pipelines.

Agents-Flex is a lightweight and elegant Java framework for Large Language Model (LLM) applications. It allows developers to define, parse and execute local methods efficiently. The framework supports local function definitions, parsing capabilities, callbacks through LLMs, and the execution of methods returning results. With minimal code, developers can harness the power of LLMs and integrate sophisticated functionalities into their applications.