feat(api): add conversation archive with vector search (MS22-DB-004, MS22-API-004)

- Add ConversationArchive Prisma model with pgvector(1536) embedding field
- Migration: 20260228000000_ms22_conversation_archive
- NestJS module at apps/api/src/conversation-archive/ with service, controller, DTOs, spec
- POST /api/conversations/ingest — ingest session logs, auto-embed via EmbeddingService
- POST /api/conversations/search — vector similarity search with agentId filter
- GET  /api/conversations — paginated list with agentId + date range filters
- GET  /api/conversations/:id — fetch full conversation including messages
- Register ConversationArchiveModule in app.module.ts
- 8 unit tests, all passing (vitest)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

apps/api/prisma/migrations/20260228000000_ms22_conversation_archive/migration.sql

@@ -0,0 +1,33 @@
+-- CreateTable
+CREATE TABLE "conversation_archives" (
+    "id" UUID NOT NULL,
+    "workspace_id" UUID NOT NULL,
+    "session_id" TEXT NOT NULL,
+    "agent_id" TEXT NOT NULL,
+    "messages" JSONB NOT NULL,
+    "message_count" INTEGER NOT NULL,
+    "summary" TEXT NOT NULL,
+    "embedding" vector(1536),
+    "started_at" TIMESTAMPTZ NOT NULL,
+    "ended_at" TIMESTAMPTZ,
+    "metadata" JSONB NOT NULL DEFAULT '{}',
+    "created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updated_at" TIMESTAMPTZ NOT NULL,
+
+    CONSTRAINT "conversation_archives_pkey" PRIMARY KEY ("id")
+);
+
+-- CreateIndex
+CREATE UNIQUE INDEX "conversation_archives_workspace_id_session_id_key" ON "conversation_archives"("workspace_id", "session_id");
+
+-- CreateIndex
+CREATE INDEX "conversation_archives_workspace_id_idx" ON "conversation_archives"("workspace_id");
+
+-- CreateIndex
+CREATE INDEX "conversation_archives_agent_id_idx" ON "conversation_archives"("agent_id");
+
+-- CreateIndex
+CREATE INDEX "conversation_archives_started_at_idx" ON "conversation_archives"("started_at");
+
+-- AddForeignKey
+ALTER TABLE "conversation_archives" ADD CONSTRAINT "conversation_archives_workspace_id_fkey" FOREIGN KEY ("workspace_id") REFERENCES "workspaces"("id") ON DELETE CASCADE ON UPDATE CASCADE;

apps/api/prisma/schema.prisma

@@ -313,6 +313,7 @@ model Workspace {
   llmUsageLogs                 LlmUsageLog[]
   userCredentials              UserCredential[]
   terminalSessions             TerminalSession[]
+  conversationArchives         ConversationArchive[]
 
   @@index([ownerId])
   @@map("workspaces")
@@ -1575,3 +1576,33 @@ model TerminalSession {
   @@index([workspaceId, status])
   @@map("terminal_sessions")
 }
+
+// ============================================
+// CONVERSATION ARCHIVE MODULE
+// ============================================
+
+model ConversationArchive {
+  id           String                       @id @default(uuid()) @db.Uuid
+  workspaceId  String                       @map("workspace_id") @db.Uuid
+  sessionId    String                       @map("session_id")
+  agentId      String                       @map("agent_id")
+  messages     Json
+  messageCount Int                          @map("message_count")
+  summary      String                       @db.Text
+  // Note: vector dimension (1536) must match EMBEDDING_DIMENSION constant in @mosaic/shared
+  embedding    Unsupported("vector(1536)")?
+  startedAt    DateTime                     @map("started_at") @db.Timestamptz
+  endedAt      DateTime?                    @map("ended_at") @db.Timestamptz
+  metadata     Json                         @default("{}")
+  createdAt    DateTime                     @default(now()) @map("created_at") @db.Timestamptz
+  updatedAt    DateTime                     @updatedAt @map("updated_at") @db.Timestamptz
+
+  // Relations
+  workspace Workspace @relation(fields: [workspaceId], references: [id], onDelete: Cascade)
+
+  @@unique([workspaceId, sessionId])
+  @@index([workspaceId])
+  @@index([agentId])
+  @@index([startedAt])
+  @@map("conversation_archives")
+}

apps/api/src/app.module.ts

@@ -47,6 +47,7 @@ import { WorkspacesModule } from "./workspaces/workspaces.module";
 import { AdminModule } from "./admin/admin.module";
 import { TeamsModule } from "./teams/teams.module";
 import { ImportModule } from "./import/import.module";
+import { ConversationArchiveModule } from "./conversation-archive/conversation-archive.module";
 import { RlsContextInterceptor } from "./common/interceptors/rls-context.interceptor";
 
 @Module({
@@ -117,6 +118,7 @@ import { RlsContextInterceptor } from "./common/interceptors/rls-context.interce
     AdminModule,
     TeamsModule,
     ImportModule,
+    ConversationArchiveModule,
   ],
   controllers: [AppController, CsrfController],
   providers: [

apps/api/src/conversation-archive/conversation-archive.controller.ts

@@ -0,0 +1,69 @@
+import { Controller, Post, Get, Body, Param, Query, UseGuards } from "@nestjs/common";
+import { AuthGuard } from "../auth/guards/auth.guard";
+import { WorkspaceGuard, PermissionGuard } from "../common/guards";
+import { Workspace, RequirePermission, Permission } from "../common/decorators";
+import { ConversationArchiveService } from "./conversation-archive.service";
+import { IngestConversationDto, SearchConversationDto, ListConversationsDto } from "./dto";
+
+/**
+ * Controller for conversation archive endpoints.
+ * All endpoints require workspace membership.
+ */
+@Controller("conversations")
+@UseGuards(AuthGuard, WorkspaceGuard, PermissionGuard)
+export class ConversationArchiveController {
+  constructor(private readonly service: ConversationArchiveService) {}
+
+  /**
+   * POST /api/conversations/ingest
+   * Ingest a conversation session log and auto-embed for semantic search.
+   * Requires: MEMBER or higher
+   */
+  @Post("ingest")
+  @RequirePermission(Permission.WORKSPACE_MEMBER)
+  async ingest(
+    @Workspace() workspaceId: string,
+    @Body() dto: IngestConversationDto
+  ): Promise<{ id: string }> {
+    return this.service.ingest(workspaceId, dto);
+  }
+
+  /**
+   * POST /api/conversations/search
+   * Vector similarity search across archived conversations.
+   * Requires: Any workspace member
+   */
+  @Post("search")
+  @RequirePermission(Permission.WORKSPACE_ANY)
+  async search(
+    @Workspace() workspaceId: string,
+    @Body() dto: SearchConversationDto
+  ): Promise<unknown> {
+    return this.service.search(workspaceId, dto);
+  }
+
+  /**
+   * GET /api/conversations
+   * List conversation archives with filtering and pagination.
+   * Requires: Any workspace member
+   */
+  @Get()
+  @RequirePermission(Permission.WORKSPACE_ANY)
+  async findAll(
+    @Workspace() workspaceId: string,
+    @Query() query: ListConversationsDto
+  ): Promise<unknown> {
+    return this.service.findAll(workspaceId, query);
+  }
+
+  /**
+   * GET /api/conversations/:id
+   * Get a single conversation archive by ID (includes full messages).
+   * Requires: Any workspace member
+   */
+  @Get(":id")
+  @RequirePermission(Permission.WORKSPACE_ANY)
+  async findOne(@Workspace() workspaceId: string, @Param("id") id: string): Promise<unknown> {
+    return this.service.findOne(workspaceId, id);
+  }
+}

apps/api/src/conversation-archive/conversation-archive.module.ts

@@ -0,0 +1,14 @@
+import { Module } from "@nestjs/common";
+import { PrismaModule } from "../prisma/prisma.module";
+import { AuthModule } from "../auth/auth.module";
+import { KnowledgeModule } from "../knowledge/knowledge.module";
+import { ConversationArchiveService } from "./conversation-archive.service";
+import { ConversationArchiveController } from "./conversation-archive.controller";
+
+@Module({
+  imports: [PrismaModule, AuthModule, KnowledgeModule],
+  controllers: [ConversationArchiveController],
+  providers: [ConversationArchiveService],
+  exports: [ConversationArchiveService],
+})
+export class ConversationArchiveModule {}

apps/api/src/conversation-archive/conversation-archive.service.spec.ts

@@ -0,0 +1,149 @@
+import { describe, it, expect, beforeEach, vi } from "vitest";
+import { Test, TestingModule } from "@nestjs/testing";
+import { ConflictException, NotFoundException } from "@nestjs/common";
+import { ConversationArchiveService } from "./conversation-archive.service";
+import { PrismaService } from "../prisma/prisma.service";
+import { EmbeddingService } from "../knowledge/services/embedding.service";
+
+const mockPrisma = {
+  conversationArchive: {
+    findUnique: vi.fn(),
+    create: vi.fn(),
+    count: vi.fn(),
+    findMany: vi.fn(),
+    findFirst: vi.fn(),
+  },
+  $queryRaw: vi.fn(),
+  $executeRaw: vi.fn(),
+};
+
+const mockEmbedding = {
+  isConfigured: vi.fn(),
+  generateEmbedding: vi.fn(),
+};
+
+describe("ConversationArchiveService", () => {
+  let service: ConversationArchiveService;
+
+  beforeEach(async () => {
+    vi.clearAllMocks();
+
+    const module: TestingModule = await Test.createTestingModule({
+      providers: [
+        ConversationArchiveService,
+        { provide: PrismaService, useValue: mockPrisma },
+        { provide: EmbeddingService, useValue: mockEmbedding },
+      ],
+    }).compile();
+
+    service = module.get<ConversationArchiveService>(ConversationArchiveService);
+  });
+
+  describe("ingest", () => {
+    const workspaceId = "ws-1";
+    const dto = {
+      sessionId: "sess-abc",
+      agentId: "agent-xyz",
+      messages: [
+        { role: "user", content: "Hello" },
+        { role: "assistant", content: "Hi there!" },
+      ],
+      summary: "A greeting conversation",
+      startedAt: "2026-02-28T10:00:00Z",
+    };
+
+    it("creates a conversation archive and returns id", async () => {
+      mockPrisma.conversationArchive.findUnique.mockResolvedValue(null);
+      mockPrisma.conversationArchive.create.mockResolvedValue({ id: "conv-1" });
+      mockEmbedding.isConfigured.mockReturnValue(false);
+
+      const result = await service.ingest(workspaceId, dto);
+
+      expect(result).toEqual({ id: "conv-1" });
+      expect(mockPrisma.conversationArchive.create).toHaveBeenCalledWith(
+        expect.objectContaining({
+          data: expect.objectContaining({
+            workspaceId,
+            sessionId: dto.sessionId,
+            agentId: dto.agentId,
+            messageCount: 2,
+          }),
+        })
+      );
+    });
+
+    it("throws ConflictException when session already exists", async () => {
+      mockPrisma.conversationArchive.findUnique.mockResolvedValue({ id: "existing" });
+
+      await expect(service.ingest(workspaceId, dto)).rejects.toThrow(ConflictException);
+    });
+  });
+
+  describe("findAll", () => {
+    const workspaceId = "ws-1";
+
+    it("returns paginated list", async () => {
+      mockPrisma.conversationArchive.count.mockResolvedValue(5);
+      mockPrisma.conversationArchive.findMany.mockResolvedValue([
+        { id: "conv-1", sessionId: "sess-1" },
+      ]);
+
+      const result = await service.findAll(workspaceId, { page: 1, limit: 10 });
+
+      expect(result.pagination.total).toBe(5);
+      expect(result.data).toHaveLength(1);
+    });
+
+    it("uses default pagination when not provided", async () => {
+      mockPrisma.conversationArchive.count.mockResolvedValue(0);
+      mockPrisma.conversationArchive.findMany.mockResolvedValue([]);
+
+      const result = await service.findAll(workspaceId, {});
+
+      expect(result.pagination.page).toBe(1);
+      expect(result.pagination.limit).toBe(20);
+    });
+  });
+
+  describe("findOne", () => {
+    const workspaceId = "ws-1";
+
+    it("returns record when found", async () => {
+      const record = { id: "conv-1", workspaceId, sessionId: "sess-1" };
+      mockPrisma.conversationArchive.findFirst.mockResolvedValue(record);
+
+      const result = await service.findOne(workspaceId, "conv-1");
+
+      expect(result).toEqual(record);
+    });
+
+    it("throws NotFoundException when record does not exist", async () => {
+      mockPrisma.conversationArchive.findFirst.mockResolvedValue(null);
+
+      await expect(service.findOne(workspaceId, "missing")).rejects.toThrow(NotFoundException);
+    });
+  });
+
+  describe("search", () => {
+    it("throws ConflictException when embedding is not configured", async () => {
+      mockEmbedding.isConfigured.mockReturnValue(false);
+
+      await expect(service.search("ws-1", { query: "test query" })).rejects.toThrow(
+        ConflictException
+      );
+    });
+
+    it("performs vector search when configured", async () => {
+      mockEmbedding.isConfigured.mockReturnValue(true);
+      mockEmbedding.generateEmbedding.mockResolvedValue(new Array(1536).fill(0.1));
+      mockPrisma.$queryRaw
+        .mockResolvedValueOnce([{ id: "conv-1", similarity: 0.9 }])
+        .mockResolvedValueOnce([{ count: BigInt(1) }]);
+
+      const result = await service.search("ws-1", { query: "greetings" });
+
+      expect(result.data).toHaveLength(1);
+      expect(result.pagination.total).toBe(1);
+    });
+  });
+});

apps/api/src/conversation-archive/conversation-archive.service.ts

@@ -0,0 +1,277 @@
+import { Injectable, Logger, NotFoundException, ConflictException } from "@nestjs/common";
+import { Prisma } from "@prisma/client";
+import { EMBEDDING_DIMENSION } from "@mosaic/shared";
+import { PrismaService } from "../prisma/prisma.service";
+import { EmbeddingService } from "../knowledge/services/embedding.service";
+import type { IngestConversationDto, SearchConversationDto, ListConversationsDto } from "./dto";
+
+/**
+ * Shape of a raw conversation archive row from $queryRaw vector search
+ */
+interface RawConversationResult {
+  id: string;
+  workspace_id: string;
+  session_id: string;
+  agent_id: string;
+  messages: unknown;
+  message_count: number;
+  summary: string;
+  started_at: Date;
+  ended_at: Date | null;
+  metadata: unknown;
+  created_at: Date;
+  updated_at: Date;
+  similarity: number;
+}
+
+/**
+ * Paginated response wrapper
+ */
+export interface PaginatedConversations<T> {
+  data: T[];
+  pagination: {
+    page: number;
+    limit: number;
+    total: number;
+    totalPages: number;
+  };
+}
+
+@Injectable()
+export class ConversationArchiveService {
+  private readonly logger = new Logger(ConversationArchiveService.name);
+  private readonly defaultSimilarityThreshold = 0.5;
+
+  constructor(
+    private readonly prisma: PrismaService,
+    private readonly embedding: EmbeddingService
+  ) {}
+
+  /**
+   * Ingest a conversation session log.
+   * Generates a vector embedding from the summary + message content and stores it alongside the record.
+   */
+  async ingest(workspaceId: string, dto: IngestConversationDto): Promise<{ id: string }> {
+    // Verify no duplicate session in this workspace
+    const existing = await this.prisma.conversationArchive.findUnique({
+      where: { workspaceId_sessionId: { workspaceId, sessionId: dto.sessionId } },
+      select: { id: true },
+    });
+
+    if (existing) {
+      throw new ConflictException(
+        `Conversation session '${dto.sessionId}' already exists in this workspace`
+      );
+    }
+
+    const messageCount = dto.messages.length;
+
+    // Create record first to get ID for embedding
+    const record = await this.prisma.conversationArchive.create({
+      data: {
+        workspaceId,
+        sessionId: dto.sessionId,
+        agentId: dto.agentId,
+        messages: dto.messages as unknown as Prisma.InputJsonValue,
+        messageCount,
+        summary: dto.summary,
+        startedAt: new Date(dto.startedAt),
+        endedAt: dto.endedAt ? new Date(dto.endedAt) : null,
+        metadata: (dto.metadata ?? {}) as Prisma.InputJsonValue,
+      },
+      select: { id: true },
+    });
+
+    // Generate and store embedding asynchronously (non-blocking for ingest)
+    if (this.embedding.isConfigured()) {
+      const textForEmbedding = this.buildEmbeddingText(dto.summary, dto.messages);
+      this.storeEmbedding(record.id, textForEmbedding).catch((err: unknown) => {
+        this.logger.error(`Failed to store embedding for conversation ${record.id}`, err);
+      });
+    }
+
+    this.logger.log(`Ingested conversation ${record.id} (session: ${dto.sessionId})`);
+    return { id: record.id };
+  }
+
+  /**
+   * Semantic vector search across conversation archives in a workspace.
+   */
+  async search(
+    workspaceId: string,
+    dto: SearchConversationDto
+  ): Promise<PaginatedConversations<RawConversationResult>> {
+    if (!this.embedding.isConfigured()) {
+      throw new ConflictException("Semantic search requires OpenAI API key to be configured");
+    }
+
+    const limit = dto.limit ?? 20;
+    const threshold = dto.similarityThreshold ?? this.defaultSimilarityThreshold;
+    const distanceThreshold = 1 - threshold;
+
+    const queryEmbedding = await this.embedding.generateEmbedding(dto.query);
+    const embeddingStr = `[${queryEmbedding.join(",")}]`;
+
+    const agentFilter = dto.agentId ? Prisma.sql`AND ca.agent_id = ${dto.agentId}` : Prisma.sql``;
+
+    const rows = await this.prisma.$queryRaw<RawConversationResult[]>`
+      SELECT
+        ca.id,
+        ca.workspace_id,
+        ca.session_id,
+        ca.agent_id,
+        ca.messages,
+        ca.message_count,
+        ca.summary,
+        ca.started_at,
+        ca.ended_at,
+        ca.metadata,
+        ca.created_at,
+        ca.updated_at,
+        (1 - (ca.embedding <=> ${embeddingStr}::vector(${EMBEDDING_DIMENSION}))) AS similarity
+      FROM conversation_archives ca
+      WHERE ca.workspace_id = ${workspaceId}::uuid
+        AND ca.embedding IS NOT NULL
+        AND (ca.embedding <=> ${embeddingStr}::vector(${EMBEDDING_DIMENSION})) <= ${distanceThreshold}
+        ${agentFilter}
+      ORDER BY ca.embedding <=> ${embeddingStr}::vector(${EMBEDDING_DIMENSION})
+      LIMIT ${limit}
+    `;
+
+    const countResult = await this.prisma.$queryRaw<[{ count: bigint }]>`
+      SELECT COUNT(*) AS count
+      FROM conversation_archives ca
+      WHERE ca.workspace_id = ${workspaceId}::uuid
+        AND ca.embedding IS NOT NULL
+        AND (ca.embedding <=> ${embeddingStr}::vector(${EMBEDDING_DIMENSION})) <= ${distanceThreshold}
+        ${agentFilter}
+    `;
+
+    const total = Number(countResult[0].count);
+
+    return {
+      data: rows,
+      pagination: {
+        page: 1,
+        limit,
+        total,
+        totalPages: Math.ceil(total / limit),
+      },
+    };
+  }
+
+  /**
+   * List conversation archives with filtering and pagination.
+   */
+  async findAll(
+    workspaceId: string,
+    query: ListConversationsDto
+  ): Promise<PaginatedConversations<object>> {
+    const page = query.page ?? 1;
+    const limit = query.limit ?? 20;
+    const skip = (page - 1) * limit;
+
+    const where: Prisma.ConversationArchiveWhereInput = {
+      workspaceId,
+      ...(query.agentId ? { agentId: query.agentId } : {}),
+      ...(query.startedAfter || query.startedBefore
+        ? {
+            startedAt: {
+              ...(query.startedAfter ? { gte: new Date(query.startedAfter) } : {}),
+              ...(query.startedBefore ? { lte: new Date(query.startedBefore) } : {}),
+            },
+          }
+        : {}),
+    };
+
+    const [total, records] = await Promise.all([
+      this.prisma.conversationArchive.count({ where }),
+      this.prisma.conversationArchive.findMany({
+        where,
+        select: {
+          id: true,
+          workspaceId: true,
+          sessionId: true,
+          agentId: true,
+          messageCount: true,
+          summary: true,
+          startedAt: true,
+          endedAt: true,
+          metadata: true,
+          createdAt: true,
+          updatedAt: true,
+        },
+        orderBy: { startedAt: "desc" },
+        skip,
+        take: limit,
+      }),
+    ]);
+
+    return {
+      data: records,
+      pagination: {
+        page,
+        limit,
+        total,
+        totalPages: Math.ceil(total / limit),
+      },
+    };
+  }
+
+  /**
+   * Get a single conversation archive by ID.
+   */
+  async findOne(workspaceId: string, id: string): Promise<object> {
+    const record = await this.prisma.conversationArchive.findFirst({
+      where: { id, workspaceId },
+      select: {
+        id: true,
+        workspaceId: true,
+        sessionId: true,
+        agentId: true,
+        messages: true,
+        messageCount: true,
+        summary: true,
+        startedAt: true,
+        endedAt: true,
+        metadata: true,
+        createdAt: true,
+        updatedAt: true,
+      },
+    });
+
+    if (!record) {
+      throw new NotFoundException(`Conversation archive '${id}' not found`);
+    }
+
+    return record;
+  }
+
+  /**
+   * Build text content for embedding from summary and messages.
+   */
+  private buildEmbeddingText(
+    summary: string,
+    messages: { role: string; content: string }[]
+  ): string {
+    const messageText = messages.map((m) => `${m.role}: ${m.content}`).join("\n");
+    return `${summary}\n\n${messageText}`.trim();
+  }
+
+  /**
+   * Generate embedding and store it on the conversation_archives row.
+   */
+  private async storeEmbedding(id: string, text: string): Promise<void> {
+    const vector = await this.embedding.generateEmbedding(text);
+    const embeddingStr = `[${vector.join(",")}]`;
+
+    await this.prisma.$executeRaw`
+      UPDATE conversation_archives
+      SET embedding = ${embeddingStr}::vector(${EMBEDDING_DIMENSION}),
+          updated_at = NOW()
+      WHERE id = ${id}::uuid
+    `;
+
+    this.logger.log(`Stored embedding for conversation ${id}`);
+  }
+}

apps/api/src/conversation-archive/dto/index.ts

@@ -0,0 +1,3 @@
+export { IngestConversationDto, ConversationMessageDto } from "./ingest-conversation.dto";
+export { SearchConversationDto } from "./search-conversation.dto";
+export { ListConversationsDto } from "./list-conversations.dto";

apps/api/src/conversation-archive/dto/ingest-conversation.dto.ts

@@ -0,0 +1,64 @@
+import {
+  IsString,
+  IsArray,
+  IsOptional,
+  IsDateString,
+  MinLength,
+  MaxLength,
+  IsObject,
+  ValidateNested,
+  ArrayMinSize,
+} from "class-validator";
+import { Type } from "class-transformer";
+
+/**
+ * Represents a single message in a conversation session
+ */
+export class ConversationMessageDto {
+  @IsString()
+  role!: string;
+
+  @IsString()
+  @MinLength(1)
+  content!: string;
+
+  @IsOptional()
+  @IsDateString()
+  timestamp?: string;
+}
+
+/**
+ * DTO for ingesting a conversation session log
+ */
+export class IngestConversationDto {
+  @IsString()
+  @MinLength(1)
+  @MaxLength(500)
+  sessionId!: string;
+
+  @IsString()
+  @MinLength(1)
+  @MaxLength(500)
+  agentId!: string;
+
+  @IsArray()
+  @ArrayMinSize(1)
+  @ValidateNested({ each: true })
+  @Type(() => ConversationMessageDto)
+  messages!: ConversationMessageDto[];
+
+  @IsString()
+  @MinLength(1)
+  summary!: string;
+
+  @IsDateString()
+  startedAt!: string;
+
+  @IsOptional()
+  @IsDateString()
+  endedAt?: string;
+
+  @IsOptional()
+  @IsObject()
+  metadata?: Record<string, unknown>;
+}

apps/api/src/conversation-archive/dto/list-conversations.dto.ts

@@ -0,0 +1,33 @@
+import { IsString, IsOptional, MaxLength, IsInt, Min, Max, IsDateString } from "class-validator";
+import { Type } from "class-transformer";
+
+/**
+ * DTO for listing/filtering conversation archives
+ */
+export class ListConversationsDto {
+  @IsOptional()
+  @IsString()
+  @MaxLength(500)
+  agentId?: string;
+
+  @IsOptional()
+  @IsDateString()
+  startedAfter?: string;
+
+  @IsOptional()
+  @IsDateString()
+  startedBefore?: string;
+
+  @IsOptional()
+  @Type(() => Number)
+  @IsInt()
+  @Min(1)
+  page?: number;
+
+  @IsOptional()
+  @Type(() => Number)
+  @IsInt()
+  @Min(1)
+  @Max(100)
+  limit?: number;
+}

apps/api/src/conversation-archive/dto/search-conversation.dto.ts

@@ -0,0 +1,40 @@
+import {
+  IsString,
+  IsOptional,
+  MinLength,
+  MaxLength,
+  IsInt,
+  Min,
+  Max,
+  IsNumber,
+} from "class-validator";
+import { Type } from "class-transformer";
+
+/**
+ * DTO for semantic search across conversation archives
+ */
+export class SearchConversationDto {
+  @IsString()
+  @MinLength(1)
+  @MaxLength(1000)
+  query!: string;
+
+  @IsOptional()
+  @IsString()
+  @MaxLength(500)
+  agentId?: string;
+
+  @IsOptional()
+  @Type(() => Number)
+  @IsInt()
+  @Min(1)
+  @Max(100)
+  limit?: number;
+
+  @IsOptional()
+  @Type(() => Number)
+  @IsNumber()
+  @Min(0)
+  @Max(1)
+  similarityThreshold?: number;
+}

docs/scratchpads/ms22-conversation-archive.md

@@ -0,0 +1,48 @@
+# MS22 — Conversation Archive Module
+
+## Objective
+
+Implement ConversationArchive module: ingest OpenClaw session logs, store with vector embeddings for semantic search.
+
+## Deliverables
+
+1. ConversationArchive Prisma model
+2. NestJS module at apps/api/src/conversation-archive/
+3. Endpoints: ingest, search, list, get-by-id
+4. Register in app.module.ts
+5. Migrate, lint, build, commit
+
+## Plan
+
+- Add model to schema.prisma (end of file)
+- Add relation to Workspace model
+- Create module structure: dto/, service, controller, spec, module
+- Use EmbeddingService from knowledge module (import KnowledgeModule or just PrismaModule + embed inline)
+- Follow pattern: AuthGuard + WorkspaceGuard + PermissionGuard
+- Endpoint prefix: conversations (maps to /api/conversations)
+- Vector search: $queryRaw with <=> operator (cosine distance)
+
+## Assumptions
+
+- ASSUMPTION: Embedding is stored inline on ConversationArchive (not a separate table) — simpler and sufficient for this use case, matches MemoryEmbedding pattern
+- ASSUMPTION: Import KnowledgeModule to reuse EmbeddingService (it exports it)
+- ASSUMPTION: messageCount computed server-side from messages array length on ingest
+- ASSUMPTION: Permission level WORKSPACE_MEMBER for ingest/search, WORKSPACE_ANY for list/get
+
+## Progress
+
+- [ ] Schema model
+- [ ] Migration
+- [ ] DTOs
+- [ ] Service
+- [ ] Controller
+- [ ] Spec
+- [ ] Module
+- [ ] app.module.ts registration
+- [ ] Lint + build
+- [ ] Commit
+
+## Risks
+
+- EmbeddingService exports from knowledge.module — need to import KnowledgeModule
+- Migration requires live DB (may need --skip-generate flag if no DB access)