data

CSV
Embeddings
Converter

Convert CSV files into vector embeddings by selecting and combining columns into text representations. Supports header mapping, custom delimiters, and batch processing for large datasets.

Max file size: 1 GB

Estimated: 1-5 sec per 1000 rows

2 input formats

How It Works

Upload a CSV file or provide a URL.

Column headers are parsed and mapped to embedding fields.

Selected columns are concatenated into a text representation per row.

Each row's text is embedded using the selected model.

Embeddings are returned with row identifiers and metadata.

Code Examples

from mixpeek import Mixpeek

client = Mixpeek(api_key="YOUR_API_KEY")

result = client.convert(
    source="https://example.com/products.csv",
    from_format="csv",
    to_format="embeddings",
    options={
        "model": "e5-large-instruct",
        "columns": ["name", "description", "category"],
        "id_column": "sku"
    }
)

print(f"Embedded {len(result.embeddings)} rows")

Use Cases

Embed product catalogs exported from e-commerce platforms

Create vector indexes from CRM data exports

Build semantic search over spreadsheet data

Enable AI-powered queries on analytics data

Supported Input Formats

CSV

TSV

Quick Info

Categorydata

Max File Size1 GB

Est. Time1-5 sec per 1000 rows

Extractorstructured-data-descriptor

Try This Conversion

Get started with the Mixpeek API and convert your first file in minutes.

Frequently Asked Questions

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