docs: 更新安装说明，统一使用 hyperextract 包名并优化 CLI 安装指令

Author: yifanfeng97

README.md

@@ -15,6 +15,7 @@
 
 [📖 English Version](./README.md) · [中文版](./README_ZH.md)
 
+[![PyPI Version](https://img.shields.io/pypi/v/hyperextract)](https://pypi.org/project/hyperextract/)
 [![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)](https://python.org)
 [![License](https://img.shields.io/badge/license-Apache%202.0-blue)](LICENSE)
 [![Status](https://img.shields.io/badge/status-active-success)]()
@@ -26,13 +27,24 @@
 
 <br/>
 
-<img src="docs/assets/hero.png" alt="Hero & Workflow" width="100%">
+<img src="docs/assets/hero.png" alt="Hero & Workflow" width="800" style="max-width: 100%;">
 
 <br/>
 </div>
 
 Hyper-Extract is an intelligent, LLM-powered knowledge extraction and evolution framework. It radically simplifies transforming highly unstructured texts into persistent, predictable, and strongly-typed **Knowledge Abstracts**. It effortlessly extracts information into a wide spectrum of formats—ranging from simple **Collections** (Lists/Sets) and **Pydantic Models**, to complex **Knowledge Graphs**, **Hypergraphs**, and even **Spatio-Temporal Graphs**.
 
+## 📑 Table of Contents
+
+- [Core Features](#-core-features)
+- [Quick Start](#-quick-start)
+  - [CLI](#2-the-command-line-way)
+  - [Python API](#-the-python-api-way)
+- [The 8 Auto-Types](#-deep-dive-the-8-auto-types)
+- [Architecture](#-architecture-overview)
+- [Comparison](#-comparison-with-other-libraries)
+- [Documentation](#-related-documentation)
+
 ## ✨ Core Features
 
 - 🔷 **8 Auto-Types:** From basic `AutoModel`/`AutoList` to advanced `AutoGraph`, `AutoHypergraph`, and `AutoSpatioTemporalGraph`.
@@ -46,8 +58,16 @@ Hyper-Extract is an intelligent, LLM-powered knowledge extraction and evolution
 
 ### 1. Installation
 
+**For CLI Users** (install `he` command globally):
+
 ```bash
-uv pip install hyper-extract
+uv tool install hyperextract
+```
+
+**For Python Developers** (use as library):
+
+```bash
+uv pip install hyperextract
 ```
 
 ### 2. The Command Line Way
@@ -77,7 +97,7 @@ he show ./output/
 ```
 
 <details>
-<summary><b>🐍 The Python API Way</b></summary>
+<summary><b>🐍 The Python API Way</b> (click to expand)</summary>
 <br>
 
 ### Installation
@@ -117,15 +137,15 @@ from hyperextract import Template
 ka = Template.create("general/biography_graph")
 
 # Parse a document
-with open("examples/en/tesla.md", "r") as f:
+with open("examples/en/tesla.md", "r", encoding="utf-8") as f:
     text = f.read()
 result = ka.parse(text)
 
 # Visualize the knowledge graph
 ka.show(result)
 
 # Incrementally supplement knowledge
-with open("examples/en/tesla_question.md", "r") as f:
+with open("examples/en/tesla_question.md", "r", encoding="utf-8") as f:
     new_text = f.read()
 ka.feed(result, new_text)
 
@@ -137,17 +157,26 @@ ka.show(result)
 
 </details>
 
+<br>
+
+**Installation Comparison:**
+
+| Use Case | Command | Purpose |
+|----------|---------|---------|
+| CLI Tool | `uv tool install hyperextract` | Install `he` command globally |
+| Python Library | `uv pip install hyperextract` | Use in Python code |
+
 ## 🧩 Deep Dive: The 8 Auto-Types
 
 Our framework embraces complexity without making you write boilerplate code.
 
-![Knowledge Structures Matrix](docs/assets/autotypes.png)
+<img src="docs/assets/autotypes.png" alt="Knowledge Structures Matrix" width="700" style="max-width: 100%;">
 
 ### Example: AutoGraph Visualization
 
 Here is the knowledge graph visualization after `AutoGraph` extraction:
 
-![AutoGraph Visualization](docs/assets/en_show.png)
+<img src="docs/assets/en_show.png" alt="AutoGraph Visualization" width="600" style="max-width: 100%; border-radius: 8px; box-shadow: 0 4px 12px rgba(0,0,0,0.1);">
 
 ## 🛠️ Architecture Overview
 
@@ -161,7 +190,7 @@ Hyper-Extract follows a **three-layer architecture**:
 
 Use via **CLI** (`he parse`, `he search`, `he show`...) or **Python API** (`Template.create()`).
 
-![Architecture](docs/assets/arch.png)
+<img src="docs/assets/arch.png" alt="Architecture" width="750" style="max-width: 100%;">
 
 ### 📚 Related Documentation
 

README_ZH.md

@@ -15,6 +15,7 @@
 
 [📖 English Version](./README.md) · [中文版](./README_ZH.md)
 
+[![PyPI版本](https://img.shields.io/pypi/v/hyperextract)](https://pypi.org/project/hyperextract/)
 [![Python版本](https://img.shields.io/badge/python-3.11%2B-blue)](https://python.org)
 [![开源协议](https://img.shields.io/badge/license-Apache%202.0-blue)](LICENSE)
 [![状态](https://img.shields.io/badge/status-active-success)]()
@@ -26,13 +27,24 @@
 
 <br/>
 
-<img src="docs/assets/hero.png" alt="Hero & Workflow" width="100%">
+<img src="docs/assets/hero.png" alt="Hero & Workflow" width="800" style="max-width: 100%;">
 
 <br/>
 </div>
 
 Hyper-Extract 是一个智能的、由大语言模型（LLM）驱动的知识提取与演进框架。它极大地简化了将杂乱不堪的文本转化为持久化、强类型的**知识摘要（Knowledge Abstracts）**的过程。无论从基础的**集合（Collection/List）和**结构化模型（Model），还是到高阶复杂的**知识图谱（Knowledge Graph）**、**超图（Hypergraph）**，甚至是**时空图谱（Spatio-Temporal Graph）**，它都能轻松拿捏。
 
+## 📑 目录
+
+- [核心亮点](#-核心亮点)
+- [快速上手](#-快速上手)
+  - [CLI命令行](#2-cli-命令行玩法)
+  - [Python API](#-python-api-深度集成)
+- [8大知识结构](#-8种核心知识结构)
+- [系统架构](#-系统架构)
+- [对比其他库](#-与其他相关库的对比)
+- [文档](#-相关文档)
+
 ## ✨ 核心亮点
 
 - 🔷 **8大基础知识结构数据结构（Auto-Types）：** 从基础的 `AutoModel`/`AutoList` 到高阶的 `AutoGraph`, `AutoHypergraph`, 以及 `AutoSpatioTemporalGraph`（时空图）。
@@ -44,10 +56,18 @@ Hyper-Extract 是一个智能的、由大语言模型（LLM）驱动的知识提
 
 ## ⚡ 快速上手
 
-### 1. 极速安装
+### 1. 安装
+
+**CLI 用户**（全局安装 `he` 命令）：
 
 ```bash
-uv pip install hyper-extract
+uv tool install hyperextract
+```
+
+**Python 开发者**（作为库使用）：
+
+```bash
+uv pip install hyperextract
 ```
 
 ### 2. CLI 命令行玩法
@@ -77,7 +97,7 @@ he show ./output/
 ```
 
 <details>
-<summary><b>🐍 Python API 深度集成</b></summary>
+<summary><b>🐍 Python API 深度集成</b>（点击展开）</summary>
 <br>
 
 ### 安装
@@ -137,17 +157,26 @@ ka.show(result)
 
 </details>
 
+<br>
+
+**安装方式对比：**
+
+| 使用场景 | 命令 | 说明 |
+|----------|------|------|
+| CLI 工具 | `uv tool install hyperextract` | 全局安装 `he` 命令 |
+| Python 库 | `uv pip install hyperextract` | 在 Python 代码中使用 |
+
 ## 🧩 8 种核心知识结构
 
 拒绝样板代码，纯干货聚焦数据本身。
 
-![Knowledge Structures Matrix](docs/assets/autotypes.png)
+<img src="docs/assets/autotypes.png" alt="知识结构矩阵" width="700" style="max-width: 100%;">
 
 ### 示例：AutoGraph 知识图谱可视化
 
 以下是 `AutoGraph` 类型提取后的知识图谱可视化效果：
 
-![AutoGraph 可视化](docs/assets/zh_show.png)
+<img src="docs/assets/zh_show.png" alt="AutoGraph 可视化" width="600" style="max-width: 100%; border-radius: 8px; box-shadow: 0 4px 12px rgba(0,0,0,0.1);">
 
 ## 🛠️ 系统架构
 
@@ -161,7 +190,7 @@ Hyper-Extract 采用**三层架构**：
 
 可通过 **CLI**（`he parse`、`he search`、`he show`...）或 **Python API**（`Template.create()`）使用。
 
-![Architecture](docs/assets/arch.png)
+<img src="docs/assets/arch.png" alt="系统架构" width="750" style="max-width: 100%;">
 
 ### 📝 相关文档
 
@@ -244,12 +273,13 @@ display:
 | 多语言支持   |     ✅    |     ❌    |    ❌   |   ❌  |         ✅         |
 
 
-## 📚 项目参考文档
+## 📚 相关文档
 
-- [CLI 命令行指南](./hyperextract/cli/README.md)
-- [模板画廊](./hyperextract/templates/)
-- [示例代码示例](./examples/)
-- [完整架构文档](./docs/)
+- [完整文档](https://hyper-extract.github.io/zh/) - 完整文档站点
+- [English Documentation](https://hyper-extract.github.io/en/) - English Documentation
+- [CLI 指南](https://hyper-extract.github.io/zh/cli/) - 命令行界面
+- [模板画廊](https://hyper-extract.github.io/zh/templates/) - 可用模板
+- [示例代码](./examples/) - 可运行示例
 
 ## 🤝 参与贡献与协议
 

docs/en/cli/index.md

@@ -9,13 +9,13 @@ The Hyper-Extract CLI (`he`) provides a powerful, easy-to-use interface for know
 === "uv (recommended)"
 
     ```bash
-    uv pip install hyper-extract
+    uv tool install hyperextract
     ```
 
-=== "pip"
+=== "pipx"
 
     ```bash
-    pip install hyper-extract
+    pipx install hyperextract
     ```
 
 Verify installation:

docs/en/getting-started/installation.md

@@ -4,39 +4,62 @@ Hyper-Extract requires **Python 3.11+**.
 
 ---
 
-## Install from PyPI
+## Install as CLI Tool
+
+If you want to use the `he` command from anywhere:
 
 === "uv (recommended)"
 
     ```bash
-    uv pip install hyper-extract
+    uv tool install hyperextract
     ```
 
-=== "pip"
+=== "pipx"
+
+    ```bash
+    pipx install hyperextract
+    ```
+
+---
+
+## Install as Python Library
+
+If you want to use Hyper-Extract in your Python code:
+
+=== "uv (recommended)"
 
     ```bash
-    pip install hyper-extract
+    uv pip install hyperextract
     ```
 
-=== "conda"
+=== "pip"
 
     ```bash
-    pip install hyper-extract
+    pip install hyperextract
     ```
 
 ---
 
 ## Verify Installation
 
-```bash
-he --version
-```
+=== "CLI"
 
-You should see something like:
+    ```bash
+    he --version
+    ```
 
-```
-Hyper-Extract CLI version 0.1.0
-```
+    You should see something like:
+
+    ```
+    Hyper-Extract CLI version 0.1.0
+    ```
+
+=== "Python"
+
+    ```python
+    import hyperextract
+    print(hyperextract.__version__)
+    ```
 
 ---
 

docs/en/getting-started/python-quickstart.md

@@ -22,8 +22,8 @@ cd my_extraction_project
 python -m venv venv
 source venv/bin/activate  # On Windows: venv\Scripts\activate
 
-# Install hyper-extract
-pip install hyper-extract
+# Install hyperextract
+pip install hyperextract
 ```
 
 ---
@@ -257,7 +257,7 @@ if __name__ == "__main__":
 ## Troubleshooting
 
 **"No module named 'hyperextract'"**
-→ Run `pip install hyper-extract`
+→ Run `pip install hyperextract`
 
 **"API key not found"**
 → Check your `.env` file or set `OPENAI_API_KEY` environment variable

docs/en/index.md

@@ -17,8 +17,8 @@
 === "CLI (Terminal)"
 
     ```bash
-    # 1. Install
-    pip install hyper-extract
+    # 1. Install CLI tool
+    uv tool install hyperextract
 
     # 2. Configure API Key
     he config init -k YOUR_OPENAI_API_KEY

docs/en/python/index.md

@@ -7,13 +7,13 @@ Build knowledge extraction pipelines with the Hyper-Extract Python API.
 ## Installation
 
 ```bash
-pip install hyper-extract
+pip install hyperextract
 ```
 
 For development:
 
 ```bash
-pip install hyper-extract[dev]
+pip install hyperextract[dev]
 ```
 
 ---

docs/en/python/quickstart.md

@@ -12,7 +12,7 @@ Get started with the Hyper-Extract Python SDK in 5 minutes.
 ## Installation
 
 ```bash
-pip install hyper-extract
+pip install hyperextract
 ```
 
 ## Basic Usage