---

name: "CSVBrain Natural Language Data Queries" description: "Load CSV files and ask questions in plain English. AI-powered natural language queries via Anthropic, OpenAI, or local Ollama. No SQL required." author: "@TheShadowRose" version: "1.0.3" tags: ["csv", "data-analysis", "natural-language", "ai", "query"] license: "MIT" env: ANTHROPIC_API_KEY: "Optional - for Anthropic/Claude models" OPENAI_API_KEY: "Optional - for OpenAI/GPT models" OLLAMA_HOST: "Optional - Ollama base URL, default http://localhost:11434"

CSVBrain

Version: 1.0.3 Author: @TheShadowRose License: MIT

Description

Load CSV files and ask questions in plain English. AI-powered natural language queries via Anthropic, OpenAI, or local Ollama. No SQL required.

CSVBrain parses CSV files (comma, semicolon, or tab-delimited), profiles your data automatically, and lets you query it with structured filters or plain English questions powered by AI.

Features

• CSV Loading — Parse CSV files with automatic delimiter detection (comma, semicolon, tab). Handles quoted fields and escaped quotes.
• Data Profiling — Instant statistics for every column: count, missing values, unique values, min/max/avg for numeric columns.
• Structured Queries — Filter, sort, limit, and aggregate your data programmatically.
• Natural Language Ask — Ask questions about your data in plain English. AI analyzes your dataset's structure, types, and statistics to give accurate answers with specific numbers.
• Multi-Provider AI — Route questions to Anthropic (Claude), OpenAI (GPT), or local Ollama models. Just change the model prefix.
• Zero Dependencies — Pure Node.js. No npm packages required. HTTP calls use built-in https/http modules.

Installation

Copy src/csv-brain.js into your project.

const { CSVBrain } = require('./src/csv-brain');

Quick Start

const { CSVBrain } = require('./src/csv-brain');

const brain = new CSVBrain();
const info = brain.load('sales.csv');
console.log(info);
// { rows: 1200, columns: 8, types: { month: 'text', revenue: 'number', ... } }

// Profile your data
const stats = brain.profile();
console.log(stats.revenue);
// { type: 'number', count: 1200, missing: 0, unique: 987, min: 12.5, max: 94200, avg: 8450.32 }

// Ask a question in plain English
const result = await brain.ask('What was our best month for revenue?');
console.log(result.answer);
// "Based on the data, March had the highest total revenue at $94,200."
console.log(result.model);
// "anthropic/claude-haiku-4-5"

API

new CSVBrain(options?)

Create a new instance.

Option	Type	Default	Description
model	string	"anthropic/claude-haiku-4-5"	Default AI model for ask()

const brain = new CSVBrain({ model: 'openai/gpt-4o-mini' });

load(filePath, options?)

Load a CSV file synchronously.

Option	Type	Default	Description
delimiter	string	auto-detect	Force a specific delimiter

Returns: { rows: number, columns: number, types: object }

const info = brain.load('data.csv');
const info2 = brain.load('data.tsv', { delimiter: '\t' });

profile()

Get statistical profile of all columns.

Returns: Object keyed by column name, each with type, count, missing, unique, and (for numeric columns) min, max, avg.

const stats = brain.profile();
console.log(stats);

query(options)

Run a structured query against loaded data.

Option	Type	Description
filter	{ column, operator, value }	Filter rows. Operators: >, <, >=, <=, =, contains
sort	{ column, order }	Sort by column. Order: "asc" or "desc"
limit	number	Maximum rows to return
aggregate	{ column }	Return count, sum, avg, min, max for a numeric column

// Filter and sort
const topSales = brain.query({
  filter: { column: 'revenue', operator: '>', value: 10000 },
  sort: { column: 'revenue', order: 'desc' },
  limit: 10
});

// Aggregate
const totals = brain.query({
  aggregate: { column: 'revenue' }
});
console.log(totals);
// { count: 1200, sum: 10140384, avg: 8450.32, min: 12.5, max: 94200 }

async ask(question, options?)

Ask a natural language question about your data. Requires an AI provider API key (or local Ollama).

Option	Type	Default	Description
model	string	Instance default	AI model with provider prefix
apiKey	string	From environment	Override the API key
ollamaHost	string	"http://localhost:11434"	Ollama server URL

Returns: { answer: string, data: any, query: object|null, model: string }

// Using Anthropic (default)
// Requires ANTHROPIC_API_KEY environment variable
const result = await brain.ask('Which product category has the highest average price?');
console.log(result.answer);
// "Electronics has the highest average price at $342.50, followed by Appliances at $289.00."

// Using OpenAI
// Requires OPENAI_API_KEY environment variable
const result2 = await brain.ask('How many orders were placed in Q4?', {
  model: 'openai/gpt-4o-mini'
});

// Using local Ollama (no API key needed)
const result3 = await brain.ask('Summarize the sales trends', {
  model: 'ollama/llama3'
});

AI Provider Setup

Anthropic (Claude)

Set your API key as an environment variable:

export ANTHROPIC_API_KEY="sk-ant-..."

Models: anthropic/claude-haiku-4-5, anthropic/claude-sonnet-4-20250514, etc.

OpenAI (GPT)

export OPENAI_API_KEY="sk-..."

Models: openai/gpt-4o-mini, openai/gpt-4o, etc.

Ollama (Local)

No API key required. Just run Ollama locally:

ollama serve
ollama pull llama3

Models: ollama/llama3, ollama/mistral, etc.

Optionally set a custom host:

export OLLAMA_HOST="http://192.168.1.100:11434"

Error Handling

If the AI provider is unavailable, ask() returns a graceful error instead of throwing:

const result = await brain.ask('What is the trend?');
if (result.answer.startsWith('AI unavailable:')) {
  console.log('Falling back to manual query...');
  const data = brain.query({ sort: { column: 'date', order: 'asc' } });
}

Supported File Formats

• CSV — Comma-separated values (.csv)
• TSV — Tab-separated values (.tsv, .txt)
• Semicolon-delimited — Common in European locale exports

Delimiter is auto-detected from the first line, or can be specified manually.

Note: Excel files (.xlsx, .xls) are not supported. Export your spreadsheet to CSV first.

Limitations

• Files are loaded synchronously and fully into memory. Very large files (100MB+) may cause performance issues.
• AI answers depend on the quality and context window of the chosen model. Only column profiles and the first 5 sample rows are sent to the AI — not the entire dataset.
• No streaming support. The full AI response is returned at once.
• No built-in export functionality. Use query() results with your own file-writing logic.

Disclaimer

CSVBrain is provided as-is under the MIT License. AI-generated answers may not always be accurate — always verify critical data analysis. API usage may incur costs from your AI provider.

Support

• Issues: github.com/TheShadowRose/CSVBrain/issues
• Author: @TheShadowRose