README.md

---
datasets:
- RUC-DataLab/DataScience-Instruct-500K
license: mit
pipeline_tag: text-generation
library_name: transformers
---

<p align="center" width="100%">
<img src="assets/logo.png" alt="DeepAnalyze" style="width: 60%; min-width: 300px; display: block; margin: auto;">
</p>

# DeepAnalyze: Agentic Large Language Models for Autonomous Data Science
[![arXiv](https://img.shields.io/badge/arXiv-2510.16872-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2510.16872)
[![Paper](https://img.shields.io/badge/Paper-DeepAnalyze-red.svg?logo=huggingface)](https://huggingface.co/papers/2510.16872)
[![code](https://img.shields.io/badge/GitHub-DeepAnalyze-black.svg?logo=github)](https://github.com/ruc-datalab/DeepAnalyze)
[![homepage](https://img.shields.io/badge/%F0%9F%8C%90%20Homepage%20-DeepAnalyze%20Cases-blue.svg)](https://ruc-deepanalyze.github.io/)
[![model](https://img.shields.io/badge/%F0%9F%A4%97%20Huggingface%20-DeepAnalyze--8B-orange.svg)](https://huggingface.co/RUC-DataLab/DeepAnalyze-8B)
[![data](https://img.shields.io/badge/%F0%9F%93%9A%20Datasets%20-DataScience--Instruct--500K-darkgreen.svg)](https://huggingface.co/datasets/RUC-DataLab/DataScience-Instruct-500K)
![Badge](https://hitscounter.dev/api/hit?url=https%3A%2F%2Fgithub.com%2Fruc-datalab%2FDeepAnalyze&label=Visitors&icon=graph-up&color=%23dc3545&message=&style=flat&tz=UTC)

> **Authors**: **[Shaolei Zhang](https://zhangshaolei1998.github.io/), [Ju Fan*](http://iir.ruc.edu.cn/~fanj/), [Meihao Fan](https://scholar.google.com/citations?user=9RTm2qoAAAAJ), [Guoliang Li](https://dbgroup.cs.tsinghua.edu.cn/ligl/), [Xiaoyong Du](http://info.ruc.edu.cn/jsky/szdw/ajxjgcx/jsjkxyjsx1/js2/7374b0a3f58045fc9543703ccea2eb9c.htm)**


**DeepAnalyze** is the first agentic LLM for autonomous data science. It can autonomously complete a wide range of data-centric tasks without human intervention, supporting:
- 🛠 **Entire data science pipeline**: Automatically perform any data science tasks such as data preparation, analysis, modeling, visualization, and report generation.
- 🔍 **Open-ended data research**: Conduct deep research on diverse data sources, including structured data (Databases, CSV, Excel), semi-structured data (JSON, XML, YAML), and unstructured data (TXT, Markdown), and finally produce analyst-grade research reports.
- 📊 **Fully open-source**: The [model](https://huggingface.co/RUC-DataLab/DeepAnalyze-8B), [code](https://github.com/ruc-datalab/DeepAnalyze), [training data](https://huggingface.co/datasets/RUC-DataLab/DataScience-Instruct-500K), and [demo](https://huggingface.co/RUC-DataLab/DeepAnalyze-8B) of DeepAnalyze are all open-sourced, allowing you to deploy or extend your own data analysis assistant.

<p align="center" width="100%">
<img src="./assets/deepanalyze.jpg" alt="deepanalyze" style="width: 70%; min-width: 300px; display: block; margin: auto;">
</p>

More information refer to [DeepAnalyze's Repo](https://github.com/ruc-datalab/DeepAnalyze)