donald/5why-analyzer
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: Implement role-based access control (RBAC) with 3-tier authorization

Browse Source 
- Add 3 user roles: user, admin, super_admin
- Restrict LLM config management to super_admin only
- Restrict audit logs and statistics to super_admin only
- Update AdminPage with role-based tab visibility
- Add complete 5 Why prompt from 5why-analyzer.jsx
- Add system documentation and authorization guide
- Add ErrorModal component and seed test users script

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
donald
2025-12-08 19:29:28 +08:00
parent 957003bc7c
commit 66cdcacce9
11 changed files with 1791 additions and 158 deletions
Download Patch File Download Diff File Expand all files Collapse all files

151
routes/analyze.js
View File

@@ -13,7 +13,7 @@ const router = express.Router();
*/
async function getActiveLLMConfig() {
const [config] = await query(
`SELECT provider_name, api_endpoint, api_key, model_name, temperature, max_tokens, timeout_seconds
`SELECT provider, api_url, api_key, model_name, temperature, max_tokens, timeout
FROM llm_configs
WHERE is_active = 1
LIMIT 1`
@@ -22,13 +22,13 @@ async function getActiveLLMConfig() {
// 如果沒有資料庫配置，使用環境變數的 Ollama 配置
if (!config) {
return {
provider_name: 'Ollama',
api_endpoint: ollamaConfig.apiUrl,
provider: 'Ollama',
api_url: ollamaConfig.apiUrl,
api_key: null,
model_name: ollamaConfig.model,
temperature: ollamaConfig.temperature,
max_tokens: ollamaConfig.maxTokens,
timeout_seconds: ollamaConfig.timeout / 1000
timeout: ollamaConfig.timeout
};
}
@@ -52,13 +52,14 @@ router.post('/', requireAuth, asyncHandler(async (req, res) => {
}
const startTime = Date.now();
let analysis = null;
try {
// 取得啟用的 LLM 配置
const llmConfig = await getActiveLLMConfig();
// 建立分析記錄
const analysis = await Analysis.create({
analysis = await Analysis.create({
user_id: userId,
finding,
job_content: jobContent,
@@ -121,7 +122,7 @@ router.post('/', requireAuth, asyncHandler(async (req, res) => {
注意：
- 5 Why 的目的不是「湊滿五個問題」，而是穿透表面症狀直達根本原因
- 若在第 3 或第 4 個 Why 就已找到真正的根本原因，可以停止（設為 null）
- 若在第 3 或第 4 個 Why 就已找到真正的根本原因，可以停止
- 每個 Why 必須標註是「已驗證事實」還是「待驗證假設」
- 最終對策必須是「永久性對策」
@@ -159,26 +160,42 @@ router.post('/', requireAuth, asyncHandler(async (req, res) => {
}`;
// 呼叫 LLM API（支援 DeepSeek, Ollama 等）
// DeepSeek 限制 max_tokens 最大為 8192，確保不超過
const effectiveMaxTokens = Math.min(
Math.max(parseInt(llmConfig.max_tokens) || 4000, 4000),
8000 // DeepSeek 最大限制
);
const effectiveTemperature = parseFloat(llmConfig.temperature) || 0.7;
console.log('Using max_tokens:', effectiveMaxTokens, 'temperature:', effectiveTemperature);
const response = await axios.post(
`${llmConfig.api_endpoint}/v1/chat/completions`,
`${llmConfig.api_url}/v1/chat/completions`,
{
model: llmConfig.model_name,
messages: [
{
role: 'system',
content: 'You are an expert consultant specializing in 5 Why root cause analysis. You always respond in valid JSON format without any markdown code blocks.'
content: `你是 5 Why 根因分析專家。
重要規則：
1. 只回覆 JSON，不要任何其他文字
2. 不要使用 markdown 代碼塊
3. 直接以 { 開頭，以 } 結尾
4. 確保 JSON 格式正確完整
5. analyses 陣列必須包含 3 個分析角度
6. 每個角度的 whys 陣列包含 3-5 個 why`
},
{
role: 'user',
content: prompt
}
],
temperature: llmConfig.temperature,
max_tokens: llmConfig.max_tokens,
temperature: effectiveTemperature,
max_tokens: effectiveMaxTokens,
stream: false
},
{
timeout: llmConfig.timeout_seconds * 1000,
timeout: llmConfig.timeout,
headers: {
'Content-Type': 'application/json',
...(llmConfig.api_key && { 'Authorization': `Bearer ${llmConfig.api_key}` })
@@ -188,12 +205,97 @@ router.post('/', requireAuth, asyncHandler(async (req, res) => {
// 處理回應
if (!response.data || !response.data.choices || !response.data.choices[0]) {
throw new Error(`Invalid response from ${llmConfig.provider_name} API`);
throw new Error(`Invalid response from ${llmConfig.provider} API`);
}
const content = response.data.choices[0].message.content;
const cleanContent = content.replace(/```json|```/g, '').trim();
const result = JSON.parse(cleanContent);
console.log('LLM Response length:', content.length);
console.log('LLM Response (first 500 chars):', content.substring(0, 500));
// 清理回應內容
let cleanContent = content
.replace(/```json\s*/gi, '')
.replace(/```\s*/g, '')
.replace(/<\|[^|]*\|>/g, '') // 移除 <|channel|> 等特殊標記
.replace(/<think>[\s\S]*?<\/think>/gi, '') // 移除思考過程
.replace(/^[\s\S]*?(?=\{)/m, '') // 移除 JSON 之前的所有內容
.trim();
// 找到 JSON 開始和結束位置
const jsonStart = cleanContent.indexOf('{');
const jsonEnd = cleanContent.lastIndexOf('}');
if (jsonStart === -1) {
console.error('No JSON found in response:', cleanContent.substring(0, 500));
throw new Error('LLM 回應格式錯誤，無法找到 JSON');
}
// 提取 JSON 部分
cleanContent = cleanContent.substring(jsonStart, jsonEnd + 1);
console.log('Extracted JSON length:', cleanContent.length);
// 嘗試解析 JSON
let result;
try {
result = JSON.parse(cleanContent);
} catch (parseError) {
console.log('JSON parse failed:', parseError.message);
console.log('Attempting to fix JSON...');
// 嘗試修復常見問題
let fixedContent = cleanContent
// 修復未轉義的換行符
.replace(/\n/g, '\\n')
.replace(/\r/g, '\\r')
.replace(/\t/g, '\\t')
// 修復尾部逗號
.replace(/,(\s*[\}\]])/g, '$1')
// 修復缺少逗號
.replace(/"\s*\n\s*"/g, '",\n"')
.replace(/\}\s*\{/g, '},{')
.replace(/\]\s*\[/g, '],[');
try {
result = JSON.parse(fixedContent);
console.log('Fixed JSON parse successful');
} catch (fixError) {
// 最後嘗試：用更激進的方式修復
console.log('Aggressive fix attempt...');
// 計算括號平衡
let braces = 0, brackets = 0, inStr = false, escape = false;
for (const c of fixedContent) {
if (escape) { escape = false; continue; }
if (c === '\\') { escape = true; continue; }
if (c === '"') { inStr = !inStr; continue; }
if (!inStr) {
if (c === '{') braces++;
else if (c === '}') braces--;
else if (c === '[') brackets++;
else if (c === ']') brackets--;
}
}
// 嘗試補上缺少的括號
fixedContent = fixedContent.replace(/,\s*$/, '');
while (brackets > 0) { fixedContent += ']'; brackets--; }
while (braces > 0) { fixedContent += '}'; braces--; }
try {
result = JSON.parse(fixedContent);
console.log('Aggressive fix successful');
} catch (finalError) {
console.error('All JSON fix attempts failed');
console.error('Original content (first 1000):', cleanContent.substring(0, 1000));
throw new Error(`JSON 解析失敗。請重試或簡化輸入內容。`);
}
}
}
// 驗證結果結構
if (!result.problemRestatement || !result.analyses || !Array.isArray(result.analyses)) {
throw new Error('LLM 回應缺少必要欄位 (problemRestatement 或 analyses)');
}
// 計算處理時間
const processingTime = Math.floor((Date.now() - startTime) / 1000);
@@ -295,7 +397,7 @@ ${JSON.stringify(analysis.analysis_result, null, 2)}
}`;
const response = await axios.post(
`${llmConfig.api_endpoint}/v1/chat/completions`,
`${llmConfig.api_url}/v1/chat/completions`,
{
model: llmConfig.model_name,
messages: [
@@ -313,7 +415,7 @@ ${JSON.stringify(analysis.analysis_result, null, 2)}
stream: false
},
{
timeout: llmConfig.timeout_seconds * 1000,
timeout: llmConfig.timeout,
headers: {
'Content-Type': 'application/json',
...(llmConfig.api_key && { 'Authorization': `Bearer ${llmConfig.api_key}` })
@@ -322,7 +424,22 @@ ${JSON.stringify(analysis.analysis_result, null, 2)}
);
const content = response.data.choices[0].message.content;
const cleanContent = content.replace(/```json|```/g, '').trim();
// 清理回應內容，移除 markdown 代碼塊標記和特殊標記
let cleanContent = content
.replace(/```json\s*/gi, '')
.replace(/```\s*/g, '')
.replace(/<\|[^|]*\|>/g, '')
.replace(/^[^{]*/, '')
.trim();
// 嘗試提取 JSON 對象
const jsonMatch = cleanContent.match(/\{[\s\S]*\}/);
if (!jsonMatch) {
throw new Error('翻譯結果格式錯誤');
}
cleanContent = jsonMatch[0];
const result = JSON.parse(cleanContent);
res.json({