dbt-llm-agent is an open-source AI agent that integrates LLMs into your dbt workflow, enabling natural language querying of models, automated SQL generation, and contextual documentation lookup. It supports popular LLM providers, offers code review suggestions, and generates test cases for your data models. With a simple CLI and Python SDK, it streamlines data engineering tasks and accelerates analytics development.
AI Memory Systems
Data Analysis
Decision Support
Predictive Analytics
#data engineering
#SQL Automation
#Language model integration
#dbt project assistance
#AI code review
#data quality testing
#automated documentation
#data model optimization
#NLP for data teams
#code efficiency
#real-time querying
#AI data workflows
#dbt support tools
#data management solutions
#query language assistance
#Project Collaboration
#data analytics improvement
#virtual assistant for data
#data pipeline automation
...
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dbt-llm-agent
dbt-llm-agent is an open-source AI agent that integrates LLMs into your dbt workflow, enabling natural language querying of models, automated SQL generation, and contextual documentation lookup. It supports popular LLM providers, offers code review suggestions, and generates test cases for your data models. With a simple CLI and Python SDK, it streamlines data engineering tasks and accelerates analytics development.
AI Memory Systems
Data Analysis
Decision Support
Predictive Analytics
#data engineering
#SQL Automation
#Language model integration
#dbt project assistance
#AI code review
#data quality testing
#automated documentation
#data model optimization
#NLP for data teams
#code efficiency
#real-time querying
#AI data workflows
#dbt support tools
#data management solutions
#query language assistance
#Project Collaboration
#data analytics improvement
#virtual assistant for data
#data pipeline automation
...
Featured
What is dbt-llm-agent?
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.
Who will use dbt-llm-agent?
- Data Engineers
- Analytics Engineers
- BI Analysts
- Data Teams
- dbt Users
How to use the dbt-llm-agent?
- Step1: Install the dbt-llm-agent package via pip.
- Step2: Configure your LLM API credentials in environment variables or a config file.
- Step3: Initialize the agent in your dbt project directory using the CLI or Python SDK.
- Step4: Use natural language prompts to query models, generate SQL, or fetch documentation.
- Step5: Review and apply the generated SQL or code suggestions within your dbt workflows.
- Step6: Optionally integrate the agent into CI/CD pipelines for automated code reviews and testing.
Platform
- mac
- windows
- linux
dbt-llm-agent's Core Features & Benefits
The Core Features
- Natural language querying of dbt models
- Automated SQL code generation
- Contextual documentation retrieval
- AI-driven code review suggestions
- Automated model test generation
- Multi-provider LLM support (OpenAI, Cohere, Vertex AI)
The Benefits
- Accelerates SQL development
- Enhances documentation discoverability
- Reduces manual code review time
- Improves data model quality
- Streamlines data engineering workflows
dbt-llm-agent's Main Use Cases & Applications
- Interactive SQL generation based on plain-English prompts
- On-the-fly lookup of dbt model documentation
- AI-assisted SQL code refactoring and optimization
- Automated generation of dbt model tests for data validation
- Seamless integration into CI/CD pipelines for data workflows
dbt-llm-agent's Pros & Cons
The Pros
Allows natural language interaction with dbt projects.
Automates documentation generation, improving data catalog quality.
Enables semantic search for intuitive data discovery.
Includes Slack integration to streamline team workflows.
Open source with clear setup instructions and flexible deployment options.
Uses advanced AI techniques like large language models and agentic reasoning.
The Cons
Currently in Beta, which may imply potential stability or feature maturity issues.
Requires setup with PostgreSQL and pgvector, which could be complex for some users.
No explicit pricing page found; pricing details are not clearly outlined.
No mobile app or additional platform support (e.g., iOS, Android, Chrome extensions).
dbt-llm-agent's Pricing
| Has free plan | No |
|---|---|
| Free trial details | |
| Pricing model | |
| Is credit card required | No |
| Paid from | |
| Has lifetime plan | No |
| Billing frequency |
FAQs of dbt-llm-agent
dbt-llm-agent Company Information
dbt-llm-agent Reviews
5/5
dbt-llm-agent's Main Competitors and alternatives?
- SQLGPT
- Tabnine
- GitHub Copilot for SQL
- Datafold
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