update docs: development

alibaba · Jul 22, 2024 · f59404a · f59404a
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diff --git a/README.md b/README.md
@@ -100,53 +100,46 @@ Once the extension is installed:
         }
         ```
 
-## How to develop
-
-This extension project is divided into two parts:
-
-- **Frontend** is responsible for the user interaction interface, communication with the backend service, and executing the API calls returned by the backend service.
-
-- **Backend** utilizes large language models (LLMs) to orchestrate the optimal API calls to fulfill user requirements based on [App-Controller](https://github.com/alibaba/app-controller) framework.
-
-When you only need to develop the frontend of the extension, you can install the frontend from source code and start your own backend service from a container for testing and development.
-
-### Install the extension frontend from source code
-- Before you start, ensure that you have `Node.js` and `npm` installed on your system.
-- Clone the [repository](https://github.com/alibaba/smart-vscode-extension.git) to your local machine
-- Install the `Yarn` package manager by running `npm install --global yarn`
-- On the root directory, run `yarn` command to install the dependencies listed in `package.json`
-- Within VS Code - run the project by simply hitting `F5`
-
-### Start your own backend service from a container
-- Download the `Dockerfile` from the link by running 
-    ```bash
-    wget https://raw.githubusercontent.com/alibaba/pilotscope/master/Dockerfile
-    ``` 
-- Build a Docker image named `llm4api` locally by running:
-    ```bash
-    docker build -t llm4api:latest \
-    --build-arg OPENAI_BASE_URL='https://api.openai.com' \
-    --build-arg OPENAI_API_KEY='your_api_key' \
-    --build-arg SERVER_PORT='your_server_port_number_in_contain' \
-    .
-    ```
-    Replace `your_api_key` and `your-server-port-number-in-contain` with your own settings.
-
-    - `OPENAI_BASE_URL` is the base URL for the OpenAI API. It specifies the endpoint for API calls. The default value is `'https://api.openai.com'`. Modify it only if you are using a different endpoint. If you customize it, please make sure you have the same format. e.g. starts with `https://` without a trailing slash. The completions endpoint suffix is added internally, e.g. for reference: `${apiBaseUrl}/v1/completions`
-    - `OPENAI_API_KEY` is your unique API key for authenticating requests to the OpenAI API. Replace `your_api_key` with your actual API key obtained from [OpenAI](https://beta.openai.com/account/api-keys).
-    - `SERVER_PORT` (optional) specifies the port number inside the container where the service will start. The default setting is 5000. You can modify it based on your preference or requirements.
-
-- Start a Docker container by running:
-    ```bash
-    docker run -it  --name llm4api_test  --shm-size 5gb  --cap-add sys_ptrace  -p your_server_port_number_in_host:your_server_port_number_in_contain -p 5022:22 -d llm4api /bin/bash
-    ```
-    This command boots up a container named `llm4api_test`. `your_server_port_number_in_host` and `your_server_port_number_in_contain` should be replaced with your own settings. Port mappings are configured as follows:
-
-    - The container’s port `your_server_port_number_in_contain` is mapped to host machine’s port `your_server_port_number_in_host` (5000 is recommended), allowing starting the backend service via host port `your_server_port_number_in_host`. 
-    - (Recommended) The container’s port 22 (SSH) is mapped to host machine’s port 5022, enabling SSH access to the container from the host via port 5022.
-
-### Configure Frontend to Communicate with Backend
-- Ensure that the frontend can correctly access the backend service. Modify `llm4apisServiceBaseUrl` in the `src/Common/Config.ts` file of the frontend project to set the backend service URL. Ensure that the `IP address` and the `port number` correspond to the **host machine** where the service is deployed. 
+## Supported Tasks
+Here we provide an overview of the tasks supported by SmartVscode. 
+
+
+| Task                  | Input Example                                   |
+| --------------------- | ----------------------------------------------- |
+| **Settings**          |                                                 |
+| Theme                 | Switch to dark theme                            |
+| Font                  | Set font size to 14                             |
+| Keybinding            | I want to set a shortcut key for saving as      |
+| **Editor**            |                                                 |
+| Format                | Format this file                                |
+| Format                | Format the selected code                        |
+| Replace               | Replace "var" with "let"                        |
+| Comment               | Comment the selected code                       |
+| Comment               | Uncomment the selected code                     |
+| Duplicate             | Duplicate the current line                      |
+| Duplicate             | Duplicate the selected code                     |
+| File                  | Open the file named "main.py"                   |
+| Navigate              | Go to line 20                                   |
+| Navigate              | Jump to the function "greet"                    |
+| Navigate              | Navigate back to the previous location          |
+| Fold                  | Collapse all sections in the current JSON file  |
+| Fold                  | Unfold all sections in the current JSON file    |
+| **View**              |                                                 |
+| Workspace             | Open a workspace folder in a new window         |
+| Workspace             | Close current workspace folder                  |
+| Sidebar               | Close the sidebar on the left                   |
+| **Execution**         |                                                 |
+| Breakpoint            | Set a breakpoint at line 50                     |
+| Debug                 | Start debugging                                 |
+| Debug                 | Run the file named "main.py"                    |
+| **Remote Connection** |                                                 |
+| Config                | Open the remote configuration file              |
+| Connection            | Create a remote ssh server connection in vscode |
+| **Extension**         |                                                 |
+| Install               | Install the extension named "python"            |
+
+## Documentation
+[Documentation] provides the comprehensive information on the supported tasks and how to develop SmartVscode. You can refer to these documentations for an improved experience with SmartVscode.
 
 ## License
 SmartVscode is released under Apache License 2.0.

diff --git a/docs/sphinx_doc/en/source/tutorial/development.md b/docs/sphinx_doc/en/source/tutorial/development.md
@@ -8,42 +8,26 @@ This extension project is divided into two parts:
 
 - **Backend** utilizes large language models (LLMs) to orchestrate the optimal API calls to fulfill user requirements based on [App-Controller](https://github.com/alibaba/app-controller) framework.
 
-When you only need to develop the frontend of the extension, you can install the frontend from source code and start your own backend service from a container for testing and development.
+When you need to develop the frontend of the extension, you can install the frontend from source code and start your own backend service for testing and development.
 
-## Install the extension frontend from source code
+## Step 1: Install and run the extension frontend from source code
 - Before you start, ensure that you have `Node.js` and `npm` installed on your system.
 - Clone the [repository](https://github.com/alibaba/smart-vscode-extension.git) to your local machine
 - Install the `Yarn` package manager by running `npm install --global yarn`
 - On the root directory, run `yarn` command to install the dependencies listed in `package.json`
+- Configure the frontend to commuicate with backend by modifying `llm4apisServiceBaseUrl` in the `src/Common/Config.ts` file. Ensure that the `llm4apisServiceBaseUrl` correspond to the service to be deployed. 
 - Within VS Code - run the project by simply hitting `F5`
 
-## Start your own backend service from a container
-- Download the `Dockerfile` from the link by running 
-    ```bash
-    wget https://raw.githubusercontent.com/alibaba/pilotscope/master/Dockerfile
-    ``` 
-- Build a Docker image named `llm4api` locally by running:
-    ```bash
-    docker build -t llm4api:latest \
-    --build-arg OPENAI_BASE_URL='https://api.openai.com' \
-    --build-arg OPENAI_API_KEY='your_api_key' \
-    --build-arg SERVER_PORT='your_server_port_number_in_contain' \
-    .
-    ```
-    Replace `your_api_key` and `your-server-port-number-in-contain` with your own settings.
-
-    - `OPENAI_BASE_URL` is the base URL for the OpenAI API. It specifies the endpoint for API calls. The default value is `'https://api.openai.com'`. Modify it only if you are using a different endpoint. If you customize it, please make sure you have the same format. e.g. starts with `https://` without a trailing slash. The completions endpoint suffix is added internally, e.g. for reference: `${apiBaseUrl}/v1/completions`
-    - `OPENAI_API_KEY` is your unique API key for authenticating requests to the OpenAI API. Replace `your_api_key` with your actual API key obtained from [OpenAI](https://beta.openai.com/account/api-keys).
-    - `SERVER_PORT` (optional) specifies the port number inside the container where the service will start. The default setting is 5000. You can modify it based on your preference or requirements.
-
-- Start a Docker container by running:
-    ```bash
-    docker run -it  --name llm4api_test  --shm-size 5gb  --cap-add sys_ptrace  -p your_server_port_number_in_host:your_server_port_number_in_contain -p 5022:22 -d llm4api /bin/bash
-    ```
-    This command boots up a container named `llm4api_test`. `your_server_port_number_in_host` and `your_server_port_number_in_contain` should be replaced with your own settings. Port mappings are configured as follows:
-
-    - The container’s port `your_server_port_number_in_contain` is mapped to host machine’s port `your_server_port_number_in_host` (5000 is recommended), allowing starting the backend service via host port `your_server_port_number_in_host`. 
-    - (Recommended) The container’s port 22 (SSH) is mapped to host machine’s port 5022, enabling SSH access to the container from the host via port 5022.
-
-## Configure Frontend to Communicate with Backend
-- Ensure that the frontend can correctly access the backend service. Modify `llm4apisServiceBaseUrl` in the `src/Common/Config.ts` file of the frontend project to set the backend service URL. Ensure that the `IP address` and the `port number` correspond to the **host machine** where the service is deployed. 
+## Step 2: Start your own backend service from source code
+- Install the backend (i.e. App-Controller) by following the [docs](https://alibaba.github.io/app-controller/en/tutorial/installation.html).
+
+- Configure the service by following the [docs](https://alibaba.github.io/app-controller/en/tutorial/deploy.html#step3-configuration-your-app-controller).
+
+- Start your own backend service by following the [docs](https://alibaba.github.io/app-controller/en/tutorial/deploy.html#step4-start-the-service).
+
+## Step3: Start to develop
+
+- You can expand the functionality of SmartVscode by providing more API knowledge, specifically referring to: [Data Preparation](https://alibaba.github.io/app-controller/en/tutorial/deploy.html#step1-data-preparation).
+
+- You can expand more interactions between SmartVscode (fontend) and App-Controller (backend) by referring to:
+[Communication Interface Implementation](https://alibaba.github.io/app-controller/en/tutorial/deploy.html#step2-communication-interface-implementation).