AFFiNE-Mirror/packages/backend/server/src/models/copilot-context.ts

import { randomUUID } from 'node:crypto';

import { Injectable } from '@nestjs/common';
import { Prisma } from '@prisma/client';

import { CopilotSessionNotFound } from '../base';
import { BaseModel } from './base';
import {
  ContextConfigSchema,
  ContextDoc,
  ContextEmbedStatus,
  CopilotContext,
  DocChunkSimilarity,
  Embedding,
  FileChunkSimilarity,
  MinimalContextConfigSchema,
} from './common/copilot';

type UpdateCopilotContextInput = Pick<CopilotContext, 'config'>;

/**
 * Copilot Job Model
 */
@Injectable()
export class CopilotContextModel extends BaseModel {
  // ================ contexts ================

  async create(sessionId: string) {
    const session = await this.db.aiSession.findFirst({
      where: { id: sessionId },
      select: { workspaceId: true },
    });
    if (!session) {
      throw new CopilotSessionNotFound();
    }

    const row = await this.db.aiContext.create({
      data: {
        sessionId,
        config: {
          workspaceId: session.workspaceId,
          docs: [],
          files: [],
          categories: [],
        },
      },
    });
    return row;
  }

  async get(id: string) {
    const row = await this.db.aiContext.findFirst({
      where: { id },
    });
    return row;
  }

  async getConfig(id: string) {
    const row = await this.get(id);
    if (row) {
      const config = ContextConfigSchema.safeParse(row.config);
      if (config.success) {
        return config.data;
      }
      const minimalConfig = MinimalContextConfigSchema.safeParse(row.config);
      if (minimalConfig.success) {
        // fulfill the missing fields
        return {
          ...minimalConfig.data,
          docs: [],
          files: [],
          categories: [],
        };
      }
    }
    return null;
  }

  async getBySessionId(sessionId: string) {
    const row = await this.db.aiContext.findFirst({
      where: { sessionId },
    });
    return row;
  }

  async mergeDocStatus(workspaceId: string, docs: ContextDoc[]) {
    const docIds = Array.from(new Set(docs.map(doc => doc.id)));
    const finishedDoc = await this.hasWorkspaceEmbedding(workspaceId, docIds);

    for (const doc of docs) {
      const status = finishedDoc.has(doc.id)
        ? ContextEmbedStatus.finished
        : undefined;
      doc.status = status || doc.status;
    }

    return docs;
  }

  async update(contextId: string, data: UpdateCopilotContextInput) {
    const ret = await this.db.aiContext.updateMany({
      where: {
        id: contextId,
      },
      data: {
        config: data.config || undefined,
      },
    });
    return ret.count > 0;
  }

  // ================ embeddings ================

  async checkEmbeddingAvailable(): Promise<boolean> {
    const [{ count }] = await this.db.$queryRaw<
      { count: number }[]
    >`SELECT count(1) FROM pg_tables WHERE tablename in ('ai_context_embeddings', 'ai_workspace_embeddings')`;
    return Number(count) === 2;
  }

  async hasWorkspaceEmbedding(workspaceId: string, docIds: string[]) {
    const canEmbedding = await this.checkEmbeddingAvailable();
    if (!canEmbedding) {
      return new Set();
    }

    const existsIds = await this.db.aiWorkspaceEmbedding
      .findMany({
        where: {
          workspaceId,
          docId: { in: docIds },
        },
        select: {
          docId: true,
        },
      })
      .then(r => r.map(r => r.docId));
    return new Set(existsIds);
  }

  private processEmbeddings(
    contextOrWorkspaceId: string,
    fileOrDocId: string,
    embeddings: Embedding[],
    withId = true
  ) {
    const groups = embeddings.map(e =>
      [
        withId ? randomUUID() : undefined,
        contextOrWorkspaceId,
        fileOrDocId,
        e.index,
        e.content,
        Prisma.raw(`'[${e.embedding.join(',')}]'`),
        new Date(),
      ].filter(v => v !== undefined)
    );
    return Prisma.join(groups.map(row => Prisma.sql`(${Prisma.join(row)})`));
  }

  async insertFileEmbedding(
    contextId: string,
    fileId: string,
    embeddings: Embedding[]
  ) {
    const values = this.processEmbeddings(contextId, fileId, embeddings);

    await this.db.$executeRaw`
    INSERT INTO "ai_context_embeddings"
    ("id", "context_id", "file_id", "chunk", "content", "embedding", "updated_at") VALUES ${values}
    ON CONFLICT (context_id, file_id, chunk) DO UPDATE SET
    content = EXCLUDED.content, embedding = EXCLUDED.embedding, updated_at = excluded.updated_at;
  `;
  }

  async deleteFileEmbedding(contextId: string, fileId: string) {
    await this.db.aiContextEmbedding.deleteMany({
      where: { contextId, fileId },
    });
  }

  async matchFileEmbedding(
    embedding: number[],
    contextId: string,
    topK: number,
    threshold: number
  ): Promise<Omit<FileChunkSimilarity, 'blobId' | 'name' | 'mimeType'>[]> {
    const similarityChunks = await this.db.$queryRaw<
      Array<Omit<FileChunkSimilarity, 'blobId' | 'name' | 'mimeType'>>
    >`
      SELECT "file_id" as "fileId", "chunk", "content", "embedding" <=> ${embedding}::vector as "distance" 
      FROM "ai_context_embeddings"
      WHERE context_id = ${contextId}
      ORDER BY "distance" ASC
      LIMIT ${topK};
    `;
    return similarityChunks.filter(c => Number(c.distance) <= threshold);
  }

  async insertWorkspaceEmbedding(
    workspaceId: string,
    docId: string,
    embeddings: Embedding[]
  ) {
    const values = this.processEmbeddings(
      workspaceId,
      docId,
      embeddings,
      false
    );
    await this.db.$executeRaw`
      INSERT INTO "ai_workspace_embeddings"
        ("workspace_id", "doc_id", "chunk", "content", "embedding", "updated_at")
      VALUES ${values}
      ON CONFLICT (workspace_id, doc_id, chunk)
      DO UPDATE SET
        embedding = EXCLUDED.embedding,
        updated_at = excluded.updated_at;
    `;
  }

  async deleteWorkspaceEmbedding(workspaceId: string, docId: string) {
    await this.db.aiWorkspaceEmbedding.deleteMany({
      where: { workspaceId, docId },
    });
  }

  async matchWorkspaceEmbedding(
    embedding: number[],
    workspaceId: string,
    topK: number,
    threshold: number,
    matchDocIds?: string[]
  ): Promise<DocChunkSimilarity[]> {
    const similarityChunks = await this.db.$queryRaw<Array<DocChunkSimilarity>>`
      SELECT
        w."doc_id" as "docId",
        w."chunk",
        w."content",
        w."embedding" <=> ${embedding}::vector as "distance"
      FROM "ai_workspace_embeddings" w
      LEFT JOIN "ai_workspace_ignored_docs" i
        ON i."workspace_id" = w."workspace_id"
          AND i."doc_id" = w."doc_id"
          ${matchDocIds?.length ? Prisma.sql`AND w."doc_id" NOT IN (${Prisma.join(matchDocIds)})` : Prisma.empty}
      WHERE
        w."workspace_id" = ${workspaceId}
        AND i."doc_id" IS NULL
        AND (w."embedding" <=> ${embedding}::vector) <= ${threshold}
      ORDER BY "distance" ASC
      LIMIT ${topK};
    `;

    return similarityChunks;
  }
}