Can I use Lumen AI with my own database?

Yes, it supports various data sources including SQL databases (via SQLAlchemy and DuckDB), CSV files, Parquet, and remote data APIs.

What LLMs does Lumen AI support?

Lumen AI supports leading cloud providers like OpenAI, Anthropic, and Google Gemini, as well as local models via Ollama or LlamaCPP for privacy-focused deployments.

Does Lumen AI support RAG?

Yes, it includes built-in tools for Retrieval-Augmented Generation (RAG) to provide AI agents with specific context from documents like data dictionaries or business rules.

How does Lumen AI differ from standard dashboards?

Unlike fixed dashboards with predefined views, Lumen AI provides a conversational interface for ad-hoc exploration, allowing users to ask unpredictable questions in plain English.

Lumen AI Data Explorer

Name: Lumen AI Data Explorer
Author: robertpelloni

byrobertpelloni

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数据科学与机器学习

Enables natural language data exploration, automated SQL generation, and interactive visualization using agent-based AI frameworks.

关于

Lumen AI is an open-source framework that transforms plain-English queries into actionable data insights, SQL queries, and interactive visualizations. It leverages a specialized agent architecture to handle complex data tasks, supporting multiple LLM providers like OpenAI and Anthropic while offering both cloud and local deployment options. This skill is ideal for building self-service analytics interfaces, reducing analyst backlogs, and performing ad-hoc data exploration without the need for manual coding or SQL expertise.

主要功能

Specialized agent architecture for charts, tables, and domain-specific analysis
Seamless integration with the HoloViz ecosystem including Panel and hvPlot
3 GitHub stars
Conversational interface for SQL generation and data querying
Multi-LLM support including OpenAI, Anthropic, and local Ollama models
RAG integration for document-aware data exploration

使用场景

Creating AI-powered data exploration tools with RAG for internal documentation
Building self-service analytics portals for non-technical stakeholders
Prototyping ad-hoc data visualizations and statistical summaries via chat

关于

主要功能

Specialized agent architecture for charts, tables, and domain-specific analysis
Seamless integration with the HoloViz ecosystem including Panel and hvPlot
3 GitHub stars
Conversational interface for SQL generation and data querying
Multi-LLM support including OpenAI, Anthropic, and local Ollama models
RAG integration for document-aware data exploration

使用场景

Creating AI-powered data exploration tools with RAG for internal documentation
Building self-service analytics portals for non-technical stakeholders
Prototyping ad-hoc data visualizations and statistical summaries via chat