feat(ai): unify AI architecture, implement RAG and legacy migration

backend/src/modules/ai/qdrant.service.ts

@@ -0,0 +1,104 @@
+// File: src/modules/ai/qdrant.service.ts
+// Change Log
+// - 2026-05-14: เพิ่ม Qdrant gateway สำหรับ AI Module พร้อม project payload filter.
+// - 2026-05-14: เพิ่ม OnModuleInit เพื่อ auto-call ensureCollection() (💡 S2).
+import {
+  Injectable,
+  Logger,
+  OnModuleInit,
+  ServiceUnavailableException,
+} from '@nestjs/common';
+import { ConfigService } from '@nestjs/config';
+import { QdrantClient } from '@qdrant/js-client-rest';
+
+const AI_COLLECTION_NAME = 'lcbp3_vectors';
+const AI_VECTOR_SIZE = 768;
+
+export interface AiVectorSearchResult {
+  pointId: string | number;
+  score: number;
+  payload: Record<string, unknown>;
+}
+
+/** Gateway กลางสำหรับ Qdrant ที่บังคับ project_public_id ทุก search */
+@Injectable()
+export class AiQdrantService implements OnModuleInit {
+  private readonly logger = new Logger(AiQdrantService.name);
+  private readonly client: QdrantClient;
+
+  constructor(private readonly configService: ConfigService) {
+    const url =
+      this.configService.get<string>('AI_QDRANT_URL') ??
+      this.configService.get<string>('QDRANT_URL') ??
+      'http://localhost:6333';
+    this.client = new QdrantClient({ url });
+  }
+
+  /** เรียก ensureCollection() อัตโนมัติเมื่อโมดูลถูก bootstrap */
+  async onModuleInit(): Promise<void> {
+    try {
+      await this.ensureCollection();
+    } catch (err) {
+      this.logger.error(
+        `AiQdrantService: collection init failed — ${err instanceof Error ? err.message : String(err)}`
+      );
+    }
+  }
+
+  /** เตรียม collection และ tenant payload index สำหรับ project isolation */
+  async ensureCollection(): Promise<void> {
+    const collections = await this.client.getCollections();
+    const exists = collections.collections.some(
+      (collection) => collection.name === AI_COLLECTION_NAME
+    );
+
+    if (!exists) {
+      await this.client.createCollection(AI_COLLECTION_NAME, {
+        vectors: { size: AI_VECTOR_SIZE, distance: 'Cosine' },
+      });
+      await this.client.createPayloadIndex(AI_COLLECTION_NAME, {
+        field_name: 'project_public_id',
+        field_schema: { type: 'keyword', is_tenant: true } as Parameters<
+          QdrantClient['createPayloadIndex']
+        >[1]['field_schema'],
+      });
+      this.logger.log(`Created Qdrant collection ${AI_COLLECTION_NAME}`);
+    }
+  }
+
+  /** ค้นหา vector โดยบังคับ projectPublicId เพื่อป้องกันข้อมูลข้ามโครงการ */
+  async searchByProject(
+    vector: number[],
+    projectPublicId: string,
+    limit: number
+  ): Promise<AiVectorSearchResult[]> {
+    if (!projectPublicId) {
+      throw new ServiceUnavailableException('AI_QDRANT_PROJECT_SCOPE_REQUIRED');
+    }
+
+    const results = await this.client.search(AI_COLLECTION_NAME, {
+      vector,
+      limit,
+      filter: {
+        must: [{ key: 'project_public_id', match: { value: projectPublicId } }],
+      },
+      with_payload: true,
+    });
+
+    return results.map((result) => ({
+      pointId: result.id,
+      score: result.score,
+      payload: result.payload ?? {},
+    }));
+  }
+
+  /** ลบ vector ของเอกสารด้วย publicId ผ่าน queue processor ในขั้นถัดไป */
+  async deleteByDocumentPublicId(documentPublicId: string): Promise<void> {
+    await this.client.delete(AI_COLLECTION_NAME, {
+      wait: true,
+      filter: {
+        must: [{ key: 'public_id', match: { value: documentPublicId } }],
+      },
+    });
+  }
+}