---
title: "What is Flock?"
description: "Deep Integration of Language Models and RAG into DuckDB — Proc. VLDB Endow. 2025"
---

<Tip>
  Proc. VLDB Endow. 2025 · Vol. 18, No. 12 · *Beyond Quacking*
</Tip>

# What is Flock?

**Flock** is a DuckDB extension that deeply integrates LLM and RAG capabilities into OLAP systems. Mix analytics with
semantic analysis in SQL using map and reduce functions for generation, classification, embeddings, and more. It runs on
native platforms and in the browser via DuckDB-WASM.

## Integrating LM and IR capabilities in SQL

Flock integrates advanced language models into RDBMSs, enabling powerful tasks like text generation, classification,
filtering, and embeddings directly through SQL queries. Streamline your data workflows with AI-driven insights.

<Columns cols={1}>
  <Card title="Administrative Views for Managing Prompts and Models" icon="database">
    Treat models and prompts as resources similar to tables. You can CREATE PROMPT(s) and MODEL(s) and iterate on them
    without making changes to SQL queries.
  </Card>
  <Card title="Scalar / Map Functions for Tuple and Passage Transformation" icon="filter">
    Map tuples or text passages to new text, boolean, or JSON values using LLMs to support various types of semantic
    analysis such as extraction and classification.
  </Card>
  <Card title="Aggregate / Reduce Functions to Reduce over Tuples and Passages" icon="layer-group">
    Use Aggregate / Reduce functions to reduce tuples or text passages using LLMs to support various types of semantic
    analysis such as reranking and summarization.
  </Card>
</Columns>

```sql
-- 1) Create a model
CREATE MODEL(
  'product_summarizer',
  'gpt-4o',
  'openai'
);

-- 2) Call it from SQL
SELECT
  product_id,
  name,
  llm_complete(
    {'model_name': 'product_summarizer'},
    {
      'prompt': 'Summarize this product in one sentence.',
      'context_columns': [{'data': name}]
    }
  ) AS short_description
FROM products
LIMIT 3;
```

| ID | Product | Short Description (from LLM) |
| --- | --- | --- |
| 1 | Wireless Headphones | Comfortable Bluetooth headphones with clear sound and long battery life. |
| 2 | Gaming Laptop | High-performance laptop designed for modern games and creative workloads. |
| 3 | Smart Watch | Everyday smartwatch that tracks activity, notifications, and heart rate. |

## Why use Flock?

- Create reusable models and prompts once, then call them from simple SQL.
- Run LLM workloads next to your data without custom services or glue code.
- Keep results in tables you can join, filter, and visualize with regular DuckDB queries.

See [Installation](/installation) to get started, then [Getting Started](/getting-started/overview) for provider setup.
Browse [Scalar](/scalar-functions/overview) and [Aggregate](/aggregate-functions/overview) functions for the full API.

## Paper

**Beyond Quacking: Deep Integration of Language Models and RAG into DuckDB**

Anas Dorbani, Sunny Yasser, Jimmy Lin, Amine Mhedhbi

Proc. VLDB Endow. 2025, Vol. 18, No. 12

If you found Flock useful, cite us!

[https://doi.org/10.14778/3750601.3750685](https://doi.org/10.14778/3750601.3750685)

```bibtex
@article{10.14778/3750601.3750685,
  author  = {Dorbani, Anas and Yasser, Sunny and Lin, Jimmy and Mhedhbi, Amine},
  title   = {Beyond Quacking: Deep Integration of Language Models and RAG into DuckDB},
  journal = {Proc. VLDB Endow.},
  year    = {2025},
  volume  = {18},
  number  = {12},
  doi     = {10.14778/3750601.3750685},
  url     = {https://doi.org/10.14778/3750601.3750685}
}
```