feat: add enus dir

.vitepress/config.mts

@@ -16,7 +16,7 @@ const Logo = `
 `;
 
 const sources = ['blog', 'rfcs'];
-const dests = ['zhcn'];
+const dests = ['zhcn', 'enus'];
 
 // route based on fs, so copy files when deploy
 if (process.env.NODE_ENV === 'production') {
@@ -41,27 +41,28 @@ export default defineConfig({
     root: {
       label: 'English',
       lang: 'en',
+      link: '/enus/',
       themeConfig: {
         nav: [
           {
             text: 'Docs',
-            link: '/guide/get_started/introduction',
-            activeMatch: '/guide/',
+            link: '/enus/guide/get_started/introduction',
+            activeMatch: '/enus/guide/',
           },
           {
             text: 'Blog',
-            link: '/blog/agents',
-            activeMatch: '/blog/',
+            link: '/enus/blog/agents',
+            activeMatch: '/enus/blog/',
           },
           {
             text: 'RFCs',
-            link: '/rfcs/RFC-116-MetaGPT优化方案',
-            activeMatch: '/rfcs/',
+            link: '/enus/rfcs/RFC-116-MetaGPT优化方案',
+            activeMatch: '/enus/rfcs/',
           },
         ],
         sidebar: {
-          '/guide/': {
-            base: '/guide/',
+          '/enus/guide/': {
+            base: '/enus/guide/',
             items: [
               {
                 text: 'Get Started',
@@ -176,17 +177,17 @@ export default defineConfig({
               },
             ],
           },
-          '/blog/': {
-            base: '/blog/',
+          '/enus/blog/': {
+            base: '/enus/blog/',
             items: [
               {
                 text: 'Agents',
                 link: 'agents',
               },
             ],
           },
-          '/rfcs/': {
-            base: '/rfcs/',
+          '/enus/rfcs/': {
+            base: '/enus/rfcs/',
             items: [
               {
                 text: 'RFC-116-MetaGPT优化方案',

src/guide/api.md → src/enus/guide/api.md

@@ -1,2 +1,3 @@
 # API
+
 Will be updated soon, stay tuned.

src/enus/guide/contribute/rfc_template.md

@@ -0,0 +1 @@
+Will be updated soon, stay tuned.

src/guide/faq.md → src/enus/guide/faq.md

@@ -81,11 +81,11 @@ MetaGPT Community - The position of Chief Evangelist rotates on a monthly basis.
 
   The official OPENAI_API_BASE address is `https://api.openai.com/v1`
 
-  If the official OPENAI_API_BASE address is inaccessible in your environment (this can be verified with curl), it's recommended to configure using the reverse proxy OPENAI_API_BASE provided by libraries such as openai-forward. For instance, ` OPENAI_API_BASE: "``https://api.openai-forward.com/v1``" `
+  If the official OPENAI_API_BASE address is inaccessible in your environment (this can be verified with curl), it's recommended to configure using the reverse proxy OPENAI_API_BASE provided by libraries such as openai-forward. For instance, `OPENAI_API_BASE: "``https://api.openai-forward.com/v1``"`
 
   If the official OPENAI_API_BASE address is inaccessible in your environment (again, verifiable via curl), another option is to configure the OPENAI_PROXY parameter. This way, you can access the official OPENAI_API_BASE via a local proxy. If you don't need to access via a proxy, please do not enable this configuration; if accessing through a proxy is required, modify it to the correct proxy address. Note that when OPENAI_PROXY is enabled, don't set OPENAI_API_BASE.
 
-  Note: OpenAI's default API design ends with a v1. An example of the correct configuration is: ` OPENAI_API_BASE: "``https://api.openai.com/v1``" `
+  Note: OpenAI's default API design ends with a v1. An example of the correct configuration is: `OPENAI_API_BASE: "``https://api.openai.com/v1``"`
 
 - **Absolutely! How can I assist you today?**
 

src/guide/get_started/installation.md → src/enus/guide/get_started/installation.md

@@ -1,37 +1,49 @@
 # Installation
+
 We provide several ways for installing MetaGPT, please take the one most convenient to your case.
+
 ## Support system and version
-| System Version | Python Version  |  Supported  |
-|      ----      |     ----        |   -----   |
-|   macOS 13.x   |    python 3.9   |    Yes    |
-|   Windows 11   |    python 3.9   |    Yes    |
-|   Ubuntu 22.04 |    python 3.9   |    Yes    |
+
+| System Version | Python Version | Supported |
+| -------------- | -------------- | --------- |
+| macOS 13.x     | python 3.9     | Yes       |
+| Windows 11     | python 3.9     | Yes       |
+| Ubuntu 22.04   | python 3.9     | Yes       |
 
 Ensure that Python 3.9+ is installed on your system. You can check this by using:
+
 ```
 python3 --version
 ```
+
 ## Install stable version
+
 Recommended for most users. You can import MetaGPT like any python package, employ teams of diverse built-in roles, and build your own agents to serve all kinds of application.
+
 ```
 pip install metagpt
 ```
 
 ## Install latest development version
+
 Best for experiencing newest features.
+
 ```
 pip install git+https://github.com/geekan/MetaGPT
 ```
 
 ## Install in development mode
+
 Recommended for developers and researchers looking to customize the framework for their unique requirements, experiment on new ideas, or create sophisticated functionalities like a novel memory mechanism using the framework.
+
 ```
 git clone https://github.com/geekan/MetaGPT.git
 cd /your/path/to/MetaGPT
 pip install -e .
 ```
 
 ## Install with Docker
+
 ### Use default MetaGPT image
 
 ```bash
@@ -75,35 +87,45 @@ git clone https://github.com/geekan/MetaGPT.git
 cd MetaGPT && docker build -t metagpt:custom .
 ```
 
-
 ## Installation for full features
+
 This is relevant if you want to generate diagrams such as quadrant chart, system designs, sequence flow, etc. They are provided as intermediate results if you run the [software startup example](https://github.com/geekan/MetaGPT/blob/main/metagpt/startup.py).
+
 ### Mermaid
+
 Mermaid is a language that uses text to generate flowcharts, pie charts, Gantt charts, and other diagrams. MetaGPT uses Mermaid to create flowcharts, sequence diagrams, Gantt charts, etc. Mermaid is implemented in Node.js, and direct installation can be somewhat costly. MetaGPT provides the following Mermaid Engines to convert Mermaid text into diagrams:
 
 **nodejs**
 Install mermaid-cli directly through nodejs. MetaGPT calls the command line to turn Mermaid text into diagrams. You need to install nodejs first, then use npm to install:
+
 ```
 npm install -g @mermaid-js/mermaid-cli
 ```
+
 The official method provided by mermaid, installed via nodejs, thus it basically supports all platforms and also supports output in png/svg/pdf formats. However, it requires the installation of nodejs and mermaid-cli, which comes with certain costs for installation and use, and also requires a browser environment at runtime.
 
 **pyppeteer**
 Mermaid can also be called via JavaScript, and pyppeteer is a web automation testing tool implemented in Python that can execute JavaScript scripts. Therefore, using pyppeteer + mermaidjs can convert Mermaid text into diagrams. You can install pyppeteer with pip:
+
 ```
 pip install pyppeteer
 ```
+
 This method is relatively simple to install, has no platform restrictions, and supports output in png/svg/pdf formats. However, it requires a dependency on a browser, so you need to install a browser first and set the browser path when running:
+
 ```
 export PUPPETEER_EXECUTABLE_PATH=/path/to/your/chromium  # or edge or chrome
 ```
+
 (Note: pyppeteer is no longer maintained)
 
 **playwright**
 As pyppeteer is no longer maintained, it recommends using playwright-python as a replacement. The principle of running mermaid with playwright is the same as with pyppeteer. However, playwright-python requires the installation of its own provided browser and cannot use an already installed browser. The official only supports the following platforms:
+
 - Windows 10+, Windows Server 2016+ or Windows Subsystem for Linux (WSL).
 - MacOS 12 Monterey or MacOS 13 Ventura.
 - Debian 11, Debian 12, Ubuntu 20.04 or Ubuntu 22.04.
+
 ```
 pip install playwright
 playwright install --with-deps chromium

src/guide/get_started/introduction.md → src/enus/guide/get_started/introduction.md

@@ -8,7 +8,7 @@
 2. Internally, MetaGPT includes **product managers / architects / project managers / engineers.** It provides the entire process of a **software company along with carefully orchestrated SOPs.**
    1. `Code = SOP(Team)` is the core philosophy. We materialize SOP and apply it to teams composed of LLMs.
 
-![A software company consists of LLM-based roles](/image/software_company_cd.jpg)
+![A software company consists of LLM-based roles](../../../public/image/software_company_cd.jpg)
 
 <p align="center">Software Company Multi-Role Schematic</p>
 
@@ -24,6 +24,6 @@ MetaGPT started as a software company, but its capabilities are not limited to t
 
 For example, if you type `metagpt "Design a RecSys like Toutiao"`, you would get many outputs, one of them is data & api design
 
-![Jinri Toutiao Recsys Data & API Design](/image/data_api_design.png)
+![Jinri Toutiao Recsys Data & API Design](../../../public/image/data_api_design.png)
 
 It costs approximately **$0.2** (in GPT-4 API fees) to generate one example with analysis and design, and around **$2.0** for a full project.

src/guide/get_started/quickstart.md → src/enus/guide/get_started/quickstart.md

@@ -1,31 +1,39 @@
-
 # Quickstart
+
 ## Installation
+
 ```
 pip install metagpt
 ```
- Available installation methods can be found in the [Installation](./installation) section
+
+Available installation methods can be found in the [Installation](./installation) section
 
 ## Setup
+
 ```
 import os
 os.environ["OPENAI_API_KEY"] = "sk-..."
 os.environ["OPENAI_API_MODEL"] = "gpt-4"
 ```
+
 Variations for setting up LLM API (OpenAI, Azure, Anthropic, etc.) and other components can be found in the [Setup](./setup) section.
 
 We use environment variables for a quick demo. For formal usage of MetaGPT, we recommend using a config or key file. See [Setup](./setup).
 
 ## Develop software with a one-line requirement
->Note:
+
+> Note:
 >
->Below is a breakdown of the [software startup example](https://github.com/geekan/MetaGPT/blob/main/metagpt/startup.py). If you install MetaGPT with the git clone approach, simply run
->```
->metagpt --idea "write a cli blackjack game"
->```
-Now, let's get started! We will create a team of agents to write software based on one line of our instruction.
+> Below is a breakdown of the [software startup example](https://github.com/geekan/MetaGPT/blob/main/metagpt/startup.py). If you install MetaGPT with the git clone approach, simply run
+>
+> ```
+> metagpt --idea "write a cli blackjack game"
+> ```
+>
+> Now, let's get started! We will create a team of agents to write software based on one line of our instruction.
 
 First, import off-the-shelf roles
+
 ```python
 import asyncio
 from metagpt.roles import (
@@ -36,7 +44,9 @@ from metagpt.roles import (
 )
 from metagpt.team import Team
 ```
+
 Next, initiate the team, equip it with agents, set their budget, and provide our requirement of writing a small game
+
 ```python
 async def startup(idea: str):
     company = Team()
@@ -53,7 +63,9 @@ async def startup(idea: str):
 
     await company.run(n_round=5)
 ```
+
 Finally, run it and get the code!
+
 ```python
 await startup(idea="write a cli blackjack game")
 ```

src/guide/get_started/setup.md → src/enus/guide/get_started/setup.md

@@ -1,40 +1,55 @@
 # Setup
+
 Using MetaGPT involves connecting with model providers. We will walk through the setup in this page.
+
 ## Setup for LLM API
+
 We will take OpenAI API as an example. You can finish the setup in either way:
+
 1. Use environment variables. This can be used temporarily for a quick start or trying out a demo.
 2. Use a config or key file. This is the recommended way, best for continuous and full-feature usage and development.
+
 ### 1. Use environment variables
+
 Run in command line:
+
 ```shell
 export OPENAI_API_KEY="sk-..."  # YOUR_API_KEY
 export OPENAI_API_MODEL="intended model" # gpt-4, gpt-3.5-turbo, etc.
 ```
+
 Or in python:
+
 ```python
 import os
 os.environ["OPENAI_API_KEY"] = "sk-..."  # YOUR_API_KEY
 os.environ["OPENAI_API_MODEL"] = "intended model" # gpt-4, gpt-3.5-turbo, etc.
 ```
+
 ### 2. Use a config or key file
+
 1. In your current working directory, create a folder `config` and add a new file named `config.yaml` or `key.yaml` under it.
 2. Copy the content from the example [config.yaml](https://github.com/geekan/MetaGPT/blob/main/config/config.yaml) file into your new files
 3. Fill in your own values to the file:
+
 ```yaml
-OPENAI_API_KEY: "sk-..." # YOUR_API_KEY
-OPENAI_API_MODEL: "intended model" # gpt-4, gpt-3.5-turbo, etc.
+OPENAI_API_KEY: 'sk-...' # YOUR_API_KEY
+OPENAI_API_MODEL: 'intended model' # gpt-4, gpt-3.5-turbo, etc.
 ```
+
 Remember: If you follow the `git clone` approach in [Installation](./installation), `config/config.yaml` will already be there. Just edit it or make a copy named `config/key.yaml` for editting. This way you don't accidentally commit and share your API key using git.
+
 > Note:
 > MetaGPT will read your setup in this priority order: `config/key.yaml > config/config.yaml > environment variable`
 
 Here you are good to go! See [Quickstart](./quickstart) or our [Tutorials](/guide/tutorials/agent_101) for your first run!
 
 ## Setup for different model providers
+
 ### OpenAI
 
 ### Azure
 
 ### Anthropic
 
-## Setup for other APIs
+## Setup for other APIs

src/guide/getting-started.md → src/enus/guide/getting-started.md

@@ -192,10 +192,10 @@ metagpt "Write a cli snake game based on pygame"
 ### Usage
 
 ```
- Usage: metagpt [OPTIONS] IDEA                                                                                                                                                                                            
-                                                                                                                                                                                                                          
- Run a startup. Be a boss.                                                                                                                                                                                                
-                                                                                                                                                                                                                          
+ Usage: metagpt [OPTIONS] IDEA
+
+ Run a startup. Be a boss.
+
 ╭─ Arguments ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
 │ *    idea      TEXT  Your innovative idea, such as 'Create a 2048 game.' [default: None] [required]                                                                                                                    │
 ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

src/guide/in_depth_guides/agent_communication.md → src/enus/guide/in_depth_guides/agent_communication.md

@@ -1,2 +1,3 @@
 # Agent Communication
+
 Will be updated soon, stay tuned.

src/enus/guide/in_depth_guides/memory.md

@@ -0,0 +1 @@
+# Memory

src/enus/guide/in_depth_guides/use_own_llm.md

@@ -0,0 +1 @@
+# Use Your Own LLM

src/guide/tutorials/agent_101.md → src/enus/guide/tutorials/agent_101.md

@@ -6,6 +6,7 @@ After this tutorial, you will be able to:
 2. Develop your first agent capable of one or more actions
 
 ## Use off-the-shelf agents
+
 Import any role, initialize it, run it with a starting message, done!
 
 ```python
@@ -25,6 +26,7 @@ if __name__ == '__main__':
 ```
 
 ## Develop your first agent
+
 Consider agent from a practical usage viewpoint, what are the bare essentials for an agent to be of any utility to us? From MetaGPT's standpoint, if an agent can execute certain actions (whether powered by LLM or otherwise), it holds some degree of usefulness. Put it simply, we define what actions our agent is expected to possess, equip the agent with these capabilities, and we have a basic useful agent! MetaGPT provides high flexibility to define your own action and your own agent. We will walk you through this in the rest of this section.
 
 ### Flowchart of one agent run cycle
@@ -218,4 +220,4 @@ python3 examples/build_customized_agent.py --msg "write a function that calculat
 
 Or try it on Colab
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1SF3bJiDjKw6Xwnz2Rf0j8Hc0U4KsSB2L?usp=sharing)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1SF3bJiDjKw6Xwnz2Rf0j8Hc0U4KsSB2L?usp=sharing)

src/guide/tutorials/agent_think_act.md → src/enus/guide/tutorials/agent_think_act.md

@@ -2,4 +2,4 @@
 
 ## Three react modes
 
-## Customize thinking process
+## Customize thinking process