Please address the comments from this code review:

## Overall Comments
- The spam-check priority in `postCheckSpam` (Tencent → Akismet → LLM) conflicts with both the PR description and the admin UI hint that LLM takes precedence; align the actual branching order with the documented/UX expectation.
- In `checkByLLM`, using `answer.includes('SPAM')` means a reply like `"NOT SPAM"` will be treated as spam; consider enforcing strict equality (e.g., `answer === 'SPAM'`) to match the prompt instructions.
- The admin config description for `LLM_API_ENDPOINT` says it defaults to OpenAI, but the implementation uses `https://api.deepseek.com` as the fallback base URL; update either the code or the label so that the default behavior is consistent and not misleading.

## Individual Comments

### Comment 1
<location path="src/server/function/twikoo/utils/spam.js" line_range="68-69" />
<code_context>
+      model: config.LLM_MODEL || 'deepseek-v4-pro',
+      messages: [{ role: 'user', content }]
+    })
+    const answer = (chatCompletion.choices[0].message.content || '').trim().toUpperCase()
+    if (answer.includes('SPAM')) {
+      logger.info(`LLM 判定为 SPAM: id="${comment.id}" nick="${comment.nick}"`)
+    }
</code_context>
<issue_to_address>
**issue (bug_risk):** Using `includes('SPAM')` will classify responses like `NOT SPAM` as spam.

Because the model may legitimately return phrases like `NOT SPAM`, using `answer.includes('SPAM')` will incorrectly flag these as spam. To avoid these false positives, use a stricter check such as `answer === 'SPAM'` or a more constrained pattern (e.g. `answer.startsWith('SPAM')` while explicitly excluding `NOT SPAM`/`HAM`).
</issue_to_address>

### Comment 2
<location path="src/client/view/components/TkAdminConfig.vue" line_range="138" />
<code_context>
-          ]
+            { key: 'NOTIFY_SPAM', desc: t('ADMIN_CONFIG_ITEM_NOTIFY_SPAM'), ph: `${t('ADMIN_CONFIG_EXAMPLE')}false`, value: '' },
+            { key: 'LLM_API_KEY', desc: 'LLM API Key, used for AI spam comment detection. Takes precedence over Akismet and Tencent Cloud when configured.', ph: 'sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', value: '', secret: true },
+            { key: 'LLM_API_ENDPOINT', desc: 'LLM API endpoint URL, defaults to OpenAI', ph: 'https://api.deepseek.com', value: '' },
+            { key: 'LLM_MODEL', desc: 'LLM model name', ph: 'deepseek-v4-flash', value: '' },
+            { key: 'LLM_SPAM_PROMPT', desc: 'LLM spam detection prompt (optional, uses default if left empty)', ph: '', value: '' }          ]
</code_context>
<issue_to_address>
**suggestion:** The endpoint description and default value are inconsistent with the backend default.

The description says the endpoint "defaults to OpenAI" but the placeholder and `checkByLLM` default `baseURL` are `https://api.deepseek.com`. Please align the description with the actual default (e.g., mention DeepSeek) or update the backend default if OpenAI is intended, so configuration behavior is unambiguous.

```suggestion
            { key: 'LLM_API_ENDPOINT', desc: 'LLM API endpoint URL, defaults to DeepSeek', ph: 'https://api.deepseek.com', value: '' },
```
</issue_to_address>

### Comment 3
<location path="src/client/view/components/TkAdminConfig.vue" line_range="139" />
<code_context>
+            { key: 'NOTIFY_SPAM', desc: t('ADMIN_CONFIG_ITEM_NOTIFY_SPAM'), ph: `${t('ADMIN_CONFIG_EXAMPLE')}false`, value: '' },
+            { key: 'LLM_API_KEY', desc: 'LLM API Key, used for AI spam comment detection. Takes precedence over Akismet and Tencent Cloud when configured.', ph: 'sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx', value: '', secret: true },
+            { key: 'LLM_API_ENDPOINT', desc: 'LLM API endpoint URL, defaults to OpenAI', ph: 'https://api.deepseek.com', value: '' },
+            { key: 'LLM_MODEL', desc: 'LLM model name', ph: 'deepseek-v4-flash', value: '' },
+            { key: 'LLM_SPAM_PROMPT', desc: 'LLM spam detection prompt (optional, uses default if left empty)', ph: '', value: '' }          ]
         },
</code_context>
<issue_to_address>
**suggestion:** LLM model placeholder in the UI does not match the backend default model.

In `checkByLLM`, the default model is `deepseek-v4-pro` when `config.LLM_MODEL` is unset, but the admin UI placeholder shows `deepseek-v4-flash`. This inconsistency can mislead admins about which model is actually used. Please update either the backend default or the placeholder so they match.

```suggestion
            { key: 'LLM_MODEL', desc: 'LLM model name', ph: 'deepseek-v4-pro', value: '' },
```
</issue_to_address>

Please address the comments from this code review:

## Overall Comments
- Consider extracting the long system prompt in `buildMessages` into a configurable or i18n-able constant so that it’s easier to maintain and localize without touching code.
- The retry behavior in `checkByLLM` (fixed `maxRetries = 3` and 1s delay) could be made configurable through anti-spam settings so operators can tune latency vs robustness for their environment.
- You instantiate a new OpenAI client on every `checkByLLM` call; consider reusing a singleton client instance to avoid repeated setup overhead under high comment traffic.

## Individual Comments

### Comment 1
<location path="src/server/function/twikoo/utils/spam.js" line_range="64-73" />
<code_context>
+function buildMessages (commentData, errorMsg = '', customPrompt = '') {
</code_context>
<issue_to_address>
**suggestion:** Custom prompt substitution only replaces the first occurrence of each placeholder, which is limiting for richer templates.

Using `.replace('{{comment}}', ...)` only updates the first occurrence of each placeholder in `LLM_SPAM_PROMPT`. Prompts that reference `{{comment}}` multiple times will have later instances left untouched. Please switch to a global replacement (e.g. `new RegExp('{{comment}}', 'g')` or `replaceAll`) so all occurrences are substituted consistently.

Suggested implementation:

```javascript
function buildMessages (commentData, errorMsg = '', customPrompt = '') {
  // 1. system指令（固定不变）
  const systemContent = `You are a blog comment moderation assistant. Analyze ALL fields below and determine if this submission is spam or ham.

Spam includes ANY of the following in ANY field:
- Commercial ads, promotions, or buying/selling offers (e.g., "代开发票", "加微信", "兼职", "办证", "AI中转站").
- Special case: If the comment text is harmless, but the nickname is suspicious (e.g., contains ads or promotions) AND a website link is provided, treat it as SPAM.
- Meaningless gibberish or spammy repetition (e.g., "顶顶顶", "111111", "asdfgh", "好" repeated).
- Abusive language, insults, or offensive Chinese slang.
- Suspicious links or SEO spam in the website field.
- Bot-like automated greetings.

```

```javascript
  const userContent = (customPrompt || LLM_SPAM_PROMPT)
    .replaceAll('{{comment}}', commentData.comment || '')
    .replaceAll('{{nick}}', commentData.nick || '')
    .replaceAll('{{mail}}', commentData.mail || '')
    .replaceAll('{{link}}', commentData.link || '')

```

I only see part of the `buildMessages` function. To fully apply the suggestion:

1. Ensure that all placeholder substitutions inside `buildMessages` (or any helper it calls) use global replacement (`replaceAll` or `string.replace(new RegExp('...', 'g'))`) rather than single-occurrence `replace`.
2. If the runtime environment might not support `String.prototype.replaceAll`, you can instead use:
   ```js
   .replace(/{{comment}}/g, commentData.comment || '')
   ```
   for each placeholder.
3. If `LLM_SPAM_PROMPT` defines additional placeholders beyond `comment`, `nick`, `mail`, and `link`, update those substitutions to use global replacement as well.
</issue_to_address>

Please address the comments from this code review:

## Overall Comments
- Consider making `maxRetries` and retry backoff in `checkByLLM` configurable via settings so admins can tune robustness vs. latency for different providers.
- In `getOpenAI`, the cache invalidation only checks API key and endpoint; if admins change the model or spam prompt, the client won't be recreated, so it may be clearer to separate client caching from prompt/model-related config to avoid confusion.
- The default system prompt in `buildMessages` is quite long and tightly couples business rules to code; extracting it into a separate constant or config value would make future adjustments easier and reduce noise in the function.

## Individual Comments

### Comment 1
<location path="src/server/function/twikoo/utils/spam.js" line_range="121" />
<code_context>
+    { role: 'system', content: systemContent },
+    { role: 'user', content: userContent }
+  ]
+  logger.log('提示词是：', finalPrompt)
+  return finalPrompt
+}
</code_context>
<issue_to_address>
**🚨 suggestion (security):** Logging the full LLM prompt may be noisy and potentially expose user content in logs.

`finalPrompt` contains full user and system content. Logging this at normal level can both leak user data into logs and substantially increase log volume on a busy site. Please either reduce the log level (e.g., debug), redact/summarize the prompt (e.g., only IDs/metadata), or guard this behind a configuration flag for troubleshooting only.

Suggested implementation:

```javascript
  const finalPrompt = [
    { role: 'system', content: systemContent },
    { role: 'user', content: userContent }
  ]

  // 使用 debug 级别并只输出部分内容，避免在日志中泄露完整提示词
  logger.debug('提示词已生成', {
    systemContentPreview: systemContent.slice(0, 200),
    userContentPreview: userContent.slice(0, 200)
  })

  return finalPrompt
}

```

如果你们有统一的配置管理或日志级别控制，可以进一步：
1. 将 `200` 这一截断长度抽成常量或配置项。
2. 如果需要完全关闭这类日志，可以用环境变量或配置开关包裹这一段 `logger.debug` 调用，例如只在开发或故障排查模式下启用。
</issue_to_address>

Please address the comments from this code review:

## Overall Comments
- Consider adding a hard upper bound on `LLM_MAX_RETRIES` (e.g., clamping to a reasonable max) to avoid misconfiguration leading to excessive retry loops and latency under failure conditions.
- The JSON extraction/repair pipeline (`extractJson` + `repairJson`) is quite permissive and may incorrectly pick up or modify braces in non-JSON text; you might want to tighten this logic or rely solely on `response_format: { type: 'json_object' }` and fail fast when the model returns invalid content instead of trying to auto-repair.

## Individual Comments

### Comment 1
<location path="src/server/function/twikoo/utils/spam.js" line_range="126" />
<code_context>
+}
+
+async function checkByLLM (comment, config) {
+  const maxRetries = config.LLM_MAX_RETRIES || 3
+  let lastError = ''
+
</code_context>
<issue_to_address>
**suggestion (bug_risk):** Coerce `LLM_MAX_RETRIES` to a number to avoid subtle type issues.

`config.LLM_MAX_RETRIES` may be a string (e.g. from env/admin UI). With `const maxRetries = config.LLM_MAX_RETRIES || 3`, `maxRetries` can be `'5'`, and the loop relies on implicit coercion in `attempt <= maxRetries`. Converting explicitly, e.g. `const maxRetries = Number(config.LLM_MAX_RETRIES) || 3`, avoids type surprises and keeps future numeric operations safe.

Suggested implementation:

```javascript
  const maxRetries = Number(config.LLM_MAX_RETRIES) || 3

```

This change explicitly coerces `config.LLM_MAX_RETRIES` to a number, ensuring `maxRetries` is always numeric even if the configuration value is provided as a string (e.g. via environment variables or an admin UI). No further adjustments should be necessary as long as `maxRetries` is only used in numeric contexts (such as comparisons or arithmetic).
</issue_to_address>