690606:1538 ADR-035-135 #05

backend/src/modules/ai/processors/ai-batch.processor.spec.ts

@@ -84,6 +84,7 @@ describe('AiBatchProcessor', () => {
   };
   const mockRedis = {
     setex: jest.fn().mockResolvedValue('OK'),
+    get: jest.fn().mockResolvedValue(null),
   };
   const mockAttachmentRepo = {
     findOne: jest.fn().mockResolvedValue({
@@ -143,6 +144,7 @@ describe('AiBatchProcessor', () => {
       resolvedPrompt: 'Resolved test prompt with OCR text',
       versionNumber: 2,
     }),
+    findByVersion: jest.fn().mockResolvedValue(null),
     saveTestResult: jest.fn().mockResolvedValue(undefined),
   };
   beforeEach(async () => {
@@ -315,6 +317,68 @@ describe('AiBatchProcessor', () => {
       expect.stringContaining('completed')
     );
   });
+  it('sandbox-ai-extract ควร regenerate response ใหม่เมื่อ parse JSON ครั้งแรกล้มเหลว', async () => {
+    const cachedOcrPayload = {
+      ocrText: 'OCR text for retry test\u0002\u0000',
+      ocrUsed: true,
+      engineUsed: 'typhoon-np-dms-ocr',
+      fallbackUsed: false,
+      timestamp: '2026-06-06T15:00:00.000Z',
+    };
+    mockRedis.get = jest
+      .fn()
+      .mockResolvedValueOnce(JSON.stringify(cachedOcrPayload));
+    mockAiPromptsService.findByVersion = jest.fn().mockResolvedValue({
+      id: 1,
+      promptType: 'ocr_extraction',
+      versionNumber: 2,
+      template:
+        'Resolved test prompt with OCR text {{ocr_text}} and context {{master_data_context}}',
+      isActive: true,
+      contextConfig: { filter: {} },
+    });
+    mockOllamaService.generate
+      .mockResolvedValueOnce('{\u0002\u0000')
+      .mockResolvedValueOnce(
+        JSON.stringify({
+          subject: 'Recovered after retry',
+          confidence: 0.91,
+          tags: ['retry'],
+        })
+      );
+    const job = {
+      id: 'job-ai-extract-retry',
+      data: {
+        jobType: 'sandbox-ai-extract',
+        documentPublicId: 'idem-ai-extract-123',
+        projectPublicId: 'default',
+        payload: { promptVersion: 2 },
+        idempotencyKey: 'idem-ai-extract-123',
+      },
+    } as unknown as Job<AiBatchJobData>;
+    await processor.process(job);
+    expect(mockOllamaService.generate).toHaveBeenCalledTimes(2);
+    expect(mockOllamaService.generate).toHaveBeenNthCalledWith(
+      1,
+      expect.not.stringContaining('\u0002'),
+      expect.objectContaining({
+        timeoutMs: 120000,
+      })
+    );
+    expect(mockAiPromptsService.saveTestResult).toHaveBeenCalledWith(
+      'ocr_extraction',
+      2,
+      expect.objectContaining({
+        subject: 'Recovered after retry',
+        confidence: 0.91,
+      })
+    );
+    expect(mockRedis.setex).toHaveBeenLastCalledWith(
+      'ai:rag:result:idem-ai-extract-123',
+      3600,
+      expect.stringContaining('"llmPrompt"')
+    );
+  });
   it('EC-001: ควรบันทึก aiIssues เมื่อ AI สกัด Tag ใหม่ที่ไม่มีในระบบ', async () => {
     mockTagsService.findOrSuggestTags.mockResolvedValueOnce([
       {

backend/src/modules/ai/processors/ai-batch.processor.ts

@@ -78,6 +78,21 @@ export interface AiBatchJobData {
 
 /** OCR text สูงสุดที่ส่งเข้า LLM prompt — ป้องกัน context overflow (num_ctx 8192, Thai ~3 chars/token) */
 const MAX_OCR_TEXT_CHARS = 15000;
+const MAX_JSON_PARSE_ATTEMPTS = 2;
+const removeControlCharacters = (
+  value: string,
+  includeDeleteCharacter = false
+): string =>
+  Array.from(value)
+    .filter((character) => {
+      const code = character.charCodeAt(0);
+      const isAsciiControl =
+        (code >= 0 && code <= 8) || code === 11 || code === 12;
+      const isAdditionalControl = code >= 14 && code <= 31;
+      const isDeleteCharacter = includeDeleteCharacter && code === 127;
+      return !isAsciiControl && !isAdditionalControl && !isDeleteCharacter;
+    })
+    .join('');
 
 const readString = (value: unknown): string | undefined =>
   typeof value === 'string' && value.trim().length > 0 ? value : undefined;
@@ -145,6 +160,14 @@ const parseMigrateDocumentMetadata = (
   };
 };
 
+const sanitizeLlmJsonResponse = (response: string): string =>
+  removeControlCharacters(
+    response.replace(/```json/g, '').replace(/```/g, '')
+  ).trim();
+
+const sanitizeOcrText = (text: string): string =>
+  removeControlCharacters(text.replace(/\r\n/g, '\n'), true).trim();
+
 /** Processor สำหรับงาน AI batch ที่รันทีละงานเพื่อคุม VRAM
  *  lockDuration: 150000ms — รองรับ Ollama sandbox ที่ใช้เวลาสูงสุด 120s (ADR-029 FR-008)
  *  ค่า default ของ BullMQ คือ 30000ms ซึ่งน้อยกว่า timeout → job stall
@@ -174,6 +197,51 @@ export class AiBatchProcessor extends WorkerHost {
     super();
   }
 
+  /** เรียก LLM แล้ว parse JSON แบบ retry จริงเมื่อได้ผลลัพธ์ไม่สมบูรณ์ */
+  private async generateStructuredJson(
+    prompt: string,
+    options: { timeoutMs: number; model?: string; system?: string }
+  ): Promise<{
+    extractedMetadata: Record<string, unknown>;
+    rawResponse: string;
+    cleanedResponse: string;
+  }> {
+    let lastRawResponse = '';
+    let lastCleanedResponse = '';
+    for (let attempt = 1; attempt <= MAX_JSON_PARSE_ATTEMPTS; attempt += 1) {
+      const rawResponse = await this.ollamaService.generate(prompt, options);
+      const cleanedResponse = sanitizeLlmJsonResponse(rawResponse);
+      lastRawResponse = rawResponse;
+      lastCleanedResponse = cleanedResponse;
+      this.logger.debug(`Raw LLM response: ${rawResponse}`);
+      try {
+        return {
+          extractedMetadata: JSON.parse(cleanedResponse) as Record<
+            string,
+            unknown
+          >,
+          rawResponse,
+          cleanedResponse,
+        };
+      } catch {
+        if (attempt >= MAX_JSON_PARSE_ATTEMPTS) {
+          this.logger.error(
+            `Failed to parse LLM response as JSON after ${MAX_JSON_PARSE_ATTEMPTS} attempts. Raw: ${lastRawResponse}, Cleaned: ${lastCleanedResponse}`
+          );
+          throw new Error(
+            `Failed to parse LLM response as JSON after ${MAX_JSON_PARSE_ATTEMPTS} attempts. Raw: ${lastRawResponse.substring(0, 200)}, Cleaned: ${lastCleanedResponse.substring(0, 200)}`
+          );
+        }
+        this.logger.warn(
+          `JSON parse attempt ${attempt} failed, regenerating response...`
+        );
+      }
+    }
+    throw new Error(
+      `Failed to parse LLM response as JSON after ${MAX_JSON_PARSE_ATTEMPTS} attempts`
+    );
+  }
+
   /** Dispatch งาน batch ตาม jobType */
   async process(job: Job<AiBatchJobData>): Promise<void> {
     const isSandbox =
@@ -410,6 +478,12 @@ export class AiBatchProcessor extends WorkerHost {
         pdfPath,
         engineType
       );
+      const sanitizedOcrText = sanitizeOcrText(ocrResult.text);
+      if (sanitizedOcrText.length !== ocrResult.text.length) {
+        this.logger.warn(
+          `OCR text sanitized before LLM: raw=${ocrResult.text.length} chars, sanitized=${sanitizedOcrText.length} chars`
+        );
+      }
 
       const activePrompt =
         await this.aiPromptsService.getActive('ocr_extraction');
@@ -426,12 +500,12 @@ export class AiBatchProcessor extends WorkerHost {
       );
 
       const ocrTextSafe =
-        ocrResult.text.length > MAX_OCR_TEXT_CHARS
+        sanitizedOcrText.length > MAX_OCR_TEXT_CHARS
           ? (this.logger.warn(
-              `OCR text truncated: ${ocrResult.text.length} chars > ${MAX_OCR_TEXT_CHARS} limit (context overflow protection)`
+              `OCR text truncated: ${sanitizedOcrText.length} chars > ${MAX_OCR_TEXT_CHARS} limit (context overflow protection)`
             ),
-            ocrResult.text.substring(0, MAX_OCR_TEXT_CHARS))
+            sanitizedOcrText.substring(0, MAX_OCR_TEXT_CHARS))
-          : ocrResult.text;
+          : sanitizedOcrText;
 
       const resolvedPrompt = activePrompt.template
         .replace('{{ocr_text}}', ocrTextSafe)
@@ -444,45 +518,12 @@ export class AiBatchProcessor extends WorkerHost {
         `Prompt stats: OCR=${ocrTextSafe.length} chars, MasterData=${JSON.stringify(masterDataContext, null, 2).length} chars, Total=${resolvedPrompt.length} chars`
       );
 
-      const response = await this.ollamaService.generate(resolvedPrompt, {
+      const { extractedMetadata } = await this.generateStructuredJson(
-        timeoutMs: 120000,
+        resolvedPrompt,
-      });
+        {
-      this.logger.debug(`Raw LLM response: ${response}`);
+          timeoutMs: 120000,
-      const cleanedResponse = response
-        .replace(/```json/g, '')
-        .replace(/```/g, '')
-        .trim();
-      let extractedMetadata: Record<string, unknown> | null = null;
-      let parseAttempts = 0;
-      const maxParseAttempts = 2;
-      while (parseAttempts < maxParseAttempts) {
-        try {
-          extractedMetadata = JSON.parse(cleanedResponse) as Record<
-            string,
-            unknown
-          >;
-          break;
-        } catch {
-          parseAttempts++;
-          if (parseAttempts >= maxParseAttempts) {
-            this.logger.error(
-              `Failed to parse LLM response as JSON after ${maxParseAttempts} attempts. Raw: ${response}, Cleaned: ${cleanedResponse}`
-            );
-            throw new Error(
-              `Failed to parse LLM response as JSON after ${maxParseAttempts} attempts. Raw: ${response.substring(0, 200)}, Cleaned: ${cleanedResponse.substring(0, 200)}`
-            );
-          }
-          this.logger.warn(
-            `JSON parse attempt ${parseAttempts} failed, retrying...`
-          );
-          await new Promise((resolve) => setTimeout(resolve, 1000));
         }
-      }
+      );
-      if (!extractedMetadata) {
-        throw new Error(
-          `Failed to parse LLM response as JSON after ${maxParseAttempts} attempts`
-        );
-      }
       await this.aiPromptsService.saveTestResult(
         'ocr_extraction',
         activePrompt.versionNumber,
@@ -495,7 +536,7 @@ export class AiBatchProcessor extends WorkerHost {
           requestPublicId: idempotencyKey,
           status: 'completed',
           answer: JSON.stringify(extractedMetadata, null, 2),
-          ocrText: ocrResult.text,
+          ocrText: sanitizedOcrText,
           ocrUsed: ocrResult.ocrUsed,
           engineUsed: ocrResult.engineUsed,
           fallbackUsed: ocrResult.fallbackUsed,
@@ -549,13 +590,19 @@ export class AiBatchProcessor extends WorkerHost {
         engineType,
         typhoonOptions
       );
+      const sanitizedOcrText = sanitizeOcrText(ocrResult.text);
+      if (sanitizedOcrText.length !== ocrResult.text.length) {
+        this.logger.warn(
+          `OCR text sanitized before cache: raw=${ocrResult.text.length} chars, sanitized=${sanitizedOcrText.length} chars`
+        );
+      }
 
       // Cache OCR text สำหรับ Step 2
       await this.redis.setex(
         `ai:sandbox:ocr:${idempotencyKey}`,
         3600,
         JSON.stringify({
-          ocrText: ocrResult.text,
+          ocrText: sanitizedOcrText,
           ocrUsed: ocrResult.ocrUsed,
           engineUsed: ocrResult.engineUsed,
           fallbackUsed: ocrResult.fallbackUsed,
@@ -569,7 +616,7 @@ export class AiBatchProcessor extends WorkerHost {
         JSON.stringify({
           requestPublicId: idempotencyKey,
           status: 'completed',
-          ocrText: ocrResult.text,
+          ocrText: sanitizedOcrText,
           ocrUsed: ocrResult.ocrUsed,
           engineUsed: ocrResult.engineUsed,
           fallbackUsed: ocrResult.fallbackUsed,
@@ -624,7 +671,12 @@ export class AiBatchProcessor extends WorkerHost {
         fallbackUsed?: boolean;
         timestamp: string;
       };
-      const { ocrText } = parsedOcr;
+      const ocrText = sanitizeOcrText(parsedOcr.ocrText);
+      if (ocrText.length !== parsedOcr.ocrText.length) {
+        this.logger.warn(
+          `Cached OCR text sanitized before AI extraction: raw=${parsedOcr.ocrText.length} chars, sanitized=${ocrText.length} chars`
+        );
+      }
 
       // ดึง prompt version
       const activePrompt =
@@ -667,48 +719,15 @@ export class AiBatchProcessor extends WorkerHost {
           '{{master_data_context}}',
           JSON.stringify(masterDataContext, null, 2)
         );
-
+      this.logger.debug(
-      const response = await this.ollamaService.generate(resolvedPrompt, {
+        `Prompt stats: OCR=${ocrTextSafe.length} chars, MasterData=${JSON.stringify(masterDataContext, null, 2).length} chars, Total=${resolvedPrompt.length} chars`
-        timeoutMs: 120000,
+      );
-      });
+      const { extractedMetadata } = await this.generateStructuredJson(
-
+        resolvedPrompt,
-      this.logger.debug(`Raw LLM response: ${response}`);
+        {
-      const cleanedResponse = response
+          timeoutMs: 120000,
-        .replace(/```json/g, '')
-        .replace(/```/g, '')
-        .trim();
-
-      let extractedMetadata: Record<string, unknown> | null = null;
-      let parseAttempts = 0;
-      const maxParseAttempts = 2;
-      while (parseAttempts < maxParseAttempts) {
-        try {
-          extractedMetadata = JSON.parse(cleanedResponse) as Record<
-            string,
-            unknown
-          >;
-          break;
-        } catch {
-          parseAttempts++;
-          if (parseAttempts >= maxParseAttempts) {
-            this.logger.error(
-              `Failed to parse LLM response as JSON after ${maxParseAttempts} attempts. Raw: ${response}, Cleaned: ${cleanedResponse}`
-            );
-            throw new Error(
-              `Failed to parse LLM response as JSON after ${maxParseAttempts} attempts. Raw: ${response.substring(0, 200)}, Cleaned: ${cleanedResponse.substring(0, 200)}`
-            );
-          }
-          this.logger.warn(
-            `JSON parse attempt ${parseAttempts} failed, retrying...`
-          );
-          await new Promise((resolve) => setTimeout(resolve, 1000));
         }
-      }
+      );
-      if (!extractedMetadata) {
-        throw new Error(
-          `Failed to parse LLM response as JSON after ${maxParseAttempts} attempts`
-        );
-      }
 
       await this.aiPromptsService.saveTestResult(
         'ocr_extraction',
@@ -728,6 +747,7 @@ export class AiBatchProcessor extends WorkerHost {
           engineUsed: parsedOcr.engineUsed,
           fallbackUsed: parsedOcr.fallbackUsed,
           promptVersionUsed: targetPrompt.versionNumber,
+          llmPrompt: resolvedPrompt,
           completedAt: new Date().toISOString(),
         })
       );

memory/agent-memory.md

@@ -20,6 +20,7 @@
 - 2026-06-05 (Session 15): Feature 234 RAG Pipeline สมบูรณ์ — implement BGE-M3 embedding (dense 1024 + sparse), BGE-Reranker-Large, Semantic Chunking (typhoon2.5 + `<chunk topic>` tags + fallback), Hybrid Qdrant schema (drop+recreate), workflow hook `syncStatus()` → `enqueueRagPrepare()`, processRagPrepare pipeline ใน ai-batch.processor; แก้ CRITICAL 2 ประเด็นจาก speckit-analyze; ผ่าน speckit-tester (19/19 tests), speckit-validate (15/15 FR, ทุก SC); ปิด Gap ทั้ง 2 รายการ (jobId dedup confirmed + integration test 9 tests); สร้าง validation-report.md ใน specs/200-fullstacks/234-rag-pipeline-enhancements/
 - 2026-06-06: เพิ่ม MCP MariaDB Tools section ใน memory/agent-memory.md, AGENTS.md, และ rule files (.agents/rules/08-development-flow.md, .devin/rules/08-development-flow.md) — รวม 8 tools (test_connection, show_databases, show_tables, describe_table, query, insert, update, delete), การใช้งานร่วมกับ Development Flow, และข้อควรระวังเรื่อง DDL operations
 - 2026-06-06: เพิ่ม MCP Memory Tools section ใน memory/agent-memory.md — รวม 9 tools (create_entities, create_relations, add_observations, delete_entities, delete_relations, delete_observations, open_nodes, read_graph, search_nodes), การใช้งานร่วมกับ Development Flow สำหรับจัดการ Knowledge Graph และ Long-term Memory
+- 2026-06-06 (Session 15): LLM JSON Parse Failure & VRAM Fix (ADR-035-135) — แก้ปัญหา JSON parse failure ใน Sandbox AI Extraction โดยเพิ่ม retry logic (2 attempts) + enhanced error logging ใน ai-batch.processor.ts, เพิ่ม system prompt support ใน ollama.service.ts, แก้ VRAM contention โดยเปลี่ยน keep_alive=0 ใน ocr-sidecar/app.py (Desk-5439), แก้ ESLint seg fault โดยลด heap size 8192 → 4096 ใน backend/package.json, แก้ Schema mismatch โดยสร้าง delta SQL 2026-06-06-add-ai-prompts-public-id.sql เพิ่ม public_id และ context_config columns ใน ai_prompts table, เพิ่ม prompt stats log + llmPrompt field ใน Sandbox Result, เพิ่ม LLM Prompt UI card (สีม่วง) ใน OcrSandboxPromptManager.tsx
 -->
 
 # 🧠 Agent Long-term Project Memory

specs/03-Data-and-Storage/deltas/2026-06-06-add-ai-prompts-public-id.sql

@@ -0,0 +1,23 @@
+-- Delta: เพิ่ม public_id และ context_config columns ใน ai_prompts
+-- Date: 2026-06-06
+-- Related ADR: ADR-019 (UUID strategy), ADR-029 (Dynamic Prompts)
+-- ------------------------------------------------------------
+-- การเปลี่ยนแปลงโครงสร้างฐานข้อมูล (Schema changes)
+-- ------------------------------------------------------------
+
+-- เพิ่ม public_id column (UUIDv7) สำหรับ ADR-019 compliance
+ALTER TABLE ai_prompts
+ADD COLUMN public_id UUID UNIQUE COMMENT 'Public UUID สำหรับ API (ADR-019)';
+
+-- เพิ่ม context_config column สำหรับ ADR-029 context filtering
+ALTER TABLE ai_prompts
+ADD COLUMN context_config JSON NULL COMMENT 'Configuration สำหรับ Master Data context filtering (project/contract scope)';
+
+-- สร้าง UUID สำหรับ records ที่มีอยู่แล้ว
+UPDATE ai_prompts
+SET public_id = UUID()
+WHERE public_id IS NULL;
+
+-- ตั้ง public_id เป็น NOT NULL หลังจาก populate ครบแล้ว
+ALTER TABLE ai_prompts
+MODIFY COLUMN public_id UUID NOT NULL;