How to Build a High‑Quality Enterprise Codebase for AI‑Powered Code Completion

Preparing a High‑Quality Enterprise Code Repository

To ensure efficient retrieval and accurate code completion, follow these guidelines when creating your codebase:

Upload only source files (e.g., .java, .cs, .js, .jsx); exclude test scripts, mock code, and build artifacts such as dist or build directories.

Do not include compiled binaries (DLLs, etc.) or any generated files.

Add detailed comments at the beginning of each function you want the system to retrieve. Comments should be at least 15 characters long and contain clear semantics, keywords, and return‑value descriptions.

Use descriptive function names (e.g., exportOrdersToPDF, updateOrderStatus) instead of generic placeholders like func1.

Package the source files into a .zip, .gz or .tar.gz archive not exceeding 100 MB.

Backend Scenario: Using Natural‑Language Comments

Step 1 – Upload Code : Compress the required backend code (e.g., a Snowflake ID generator) and upload it to the enterprise repository, ensuring the target function follows the comment guidelines.

/**
 * 更新指定订单状态。
 * @param orderId 订单的唯一标识符。
 * @param newStatus 新的订单状态。
 * @return boolean 表示更新是否成功。
 */
public boolean updateOrderStatus(String orderId, String newStatus) { ... }

Step 2 – Enter Comment : In the IDE, type a natural‑language comment that describes the desired function, e.g., "//请通过雪花算法生成唯一编号的代码，返回生成的id".

Step 3 – Generate Code : The first invocation returns a suggestion based on the comment; subsequent invocations retrieve completions from the uploaded codebase.

Backend Scenario: Using Function Signatures

Step 1 – Upload Code : Same as above – ensure functions have clear, unique signatures.

Step 2 – Input Signature : Type the signature, for example:

public List<Object> nextList(String name, int size)

Parameter names may differ; the tool will adjust them automatically.

Step 3 – Code Completion : The plugin suggests completions based on the signature and the repository.

Frontend Scenario: Using Tag Completion

Step 1 – Upload Code : Add React component files to the repository.

<LTable
  isReady={isReady}
  formInitialValues={formInitialValues}
  rowKey="key"
  tableRef={tableRef}
  toolbarLeft={<Button type="primary">新增</Button>}
  formItems={formItems}
  formRef={formRef}
  columns={columns}
  request={async (params, requestType) => {
    const res = await apiGetUserList(params);
    return { data: res.data, total: res.total };
  }}
/>

Step 2 – Write Component : Open the .jsx file and start typing HTML tags or custom component tags such as <BatchUntagEditor />.

Step 3 – Automatic Completion : When the typed code matches a component in the repository, the IDE auto‑completes the full component code.

Common Issues and Solutions

Problem: After reinstalling the plugin, code retrieval still fails.

macOS: Run

ps -ef|grep lingma|grep start|awk '{print $2}'|xargs -I {} kill -9 {}

to restart the process and clear the cache.

Windows: End the Lingma process via Task Manager.

To manually trigger completion, press ⌥P on macOS or Alt+P on Windows.

For more detailed guidance, refer to the "Administrator Guide for High‑Quality Enterprise Codebases" section.