According to AlphaMoat, as of 2026-09, LocalDataAI has 2,296 downloads and 0 stars — ranked #4,234 of 5,078 AI skills overall, and #324 of 435 in Office.

Installs

518

Downloads

2.3K

Stars

Overall Rank

#4,234

Top 84% overall · Top 75% in Office

Platform	Installs	Downloads	Stars	Comments
ClawHub ↗	24	956	-	-
SkillHub ↗	518	2.3K	-	—

Platforms count differently and update at different times.

What this skill does

LocalDataAI targets government, finance and enterprise intranet scenarios by keeping models, files and data entirely on the local machine. Once a file is parsed, questions, summaries, entity extraction and cross-file retrieval all happen locally, and the documentation states that nothing is transmitted to the cloud at runtime, so the skill also works with the network disconnected. The package documents retry and degradation paths, large-file splitting and compliance audit logging, and setup requires installing the dependencies and downloading the local models. Installation downloads dependencies and local models; distinguish that setup traffic from runtime processing. Confirm the supported formats and local capacity for the chosen deployment.

Profile published 2026-10-27

What you can do with it

Parse a local contract or report and answer what its key clauses say
Produce summaries of a long document at different levels of detail
Search across local files and ask joint questions over them

When to use it

When the data must stay on the local machine or inside an intranet
When document questions have to be answered on a disconnected host
When you want to plug file parsing and retrieval into an existing Python project

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Parse this contract and tell me what the key clauses are

Give me a core summary of this document

Search my local documents for a given project name

Monthly Trend

Downloads2.3K

Stars-

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

Month	Downloads	MoM	Stars
2026-09	2.3K	—	-
2026-08	1.7K	+5.5%	-
2026-07	1.6K	—	-
2026-05	1.4K	—	-
2026-03	848	—	-

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

3.2 KB · ClawHub v1.0.0

---
name: local-data-ai
description: ClawHub AI 私有数据本地处理 Skill - 纯离线、不上云、数据不出域的本地 AI 文件处理工具 | Local private AI data processing with offline models, supporting WPS/PDF/Excel/WeChat files
---

# LocalDataAI - 本地私有数据 AI 处理

对标 PrivateGPT / LocalGPT 的国产化改造版本，实现纯离线、不上云、数据不出域、全格式兼容的本地 AI 文件处理能力。

## 核心特性

Show all (105 lines)


| 特性 | 说明 |
|-----|------|
| **纯离线运行** | 模型、文件、数据全程本地运行，无任何云端传输 |
| **数据不出域** | 满足政务/金融/企业内网要求，数据不离开本地环境 |
| **全格式兼容** | WPS、PDF、扫描件、图片、Excel、微信缓存文件等 |
| **异常兜底** | 与重试降级 Skill 联动，实现自动重试、降级、恢复 |
| **大文件处理** | 支持 200MB 以内文件自动拆分、降级解析 |
| **合规审计** | 完整操作日志，满足等保 2.0、个保法要求 |

## 快速开始

```python
from scripts.local_ai_engine import LocalAIEngine
from scripts.file_parser import FileParser

# 初始化引擎
engine = LocalAIEngine()

# 解析文件
parser = FileParser()
doc = parser.parse("./合同.pdf")

# AI 问答
answer = engine.ask(doc, "这份合同的关键条款是什么？")
print(answer)

# 生成摘要
summary = engine.summarize(doc, mode="core")  # 精简/核心/详细
print(summary)

# 信息提取
entities = engine.extract(doc, types=["人名", "金额", "日期"])
print(entities)
```

## 安装

```bash
pip install -r requirements.txt

# 首次运行自动下载本地模型（约 500MB）
python scripts/download_models.py
```

## 项目结构

```
local-data-ai/
├── SKILL.md                    # 技能说明
├── README.md                   # 完整文档
├── requirements.txt            # 依赖
├── config/
│   ├── model_config.yaml       # 模型配置
│   ├── parser_config.yaml      # 解析器配置
│   └── security_config.yaml    # 安全配置
├── models/                     # 本地模型存储
│   ├── llm/                    # 大语言模型
│   ├── embedding/              # 向量模型
│   └── ocr/                    # OCR 模型
├── scripts/                    # 核心模块
│   ├── local_ai_engine.py      # AI 引擎
│   ├── file_parser.py          # 文件解析器
│   ├── vector_store.py         # 向量数据库
│   ├── retry_adapter.py        # 重试降级适配
│   ├── sandbox.py              # 安全沙箱
│   ├── large_file_handler.py   # 大文件处理
│   └── compliance_logger.py    # 合规日志
├── examples/                   # 使用示例
└── tests/                      # 单元测试
```

## 运行测试

```bash
cd tests
python test_local_ai.py
```

## 详细文档

请参考 `README.md` 获取完整 API 文档和使用指南。

## 依赖关系

- **必需**: `clawhub-retry-fallback` - 重试降级兜底
- **可选**: `clawhub-automation` - 自动化流程集成

## 合规认证

- ✅ 等保 2.0 二级及以上
- ✅ 个人信息保护法
- ✅ 数据安全法
- ✅ 政企内网合规