/**
 * VectorStatsPort implementation for backlog/stats queries.
 * Works without sqlite-vec.
 *
 * @module src/store/vector/stats
 */

import type { Database } from "bun:sqlite";

import type { StoreResult } from "../types";
import type { BacklogItem, VectorStatsPort } from "./types";

import { err, ok } from "../types";

const statsDatabases = new WeakMap<VectorStatsPort, Database>();

/** Internal bridge for exact-input backlog; mock/third-party stats have no database. */
export function getVectorStatsDatabase(
  stats: VectorStatsPort
): Database | undefined {
  return statsDatabases.get(stats);
}

/**
 * Create a VectorStatsPort for backlog detection and vector stats.
 * Uses EXISTS-based queries to avoid duplicates from multiple docs sharing mirror_hash.
 */
export function createVectorStatsPort(db: Database): VectorStatsPort {
  function buildActiveDocumentExistsClause(collection?: string): {
    sql: string;
    params: string[];
  } {
    if (collection) {
      return {
        sql: `
          EXISTS (
            SELECT 1 FROM documents d
            WHERE d.mirror_hash = c.mirror_hash AND d.active = 1 AND d.collection = ?
          )
        `,
        params: [collection],
      };
    }

    return {
      sql: `
        EXISTS (
          SELECT 1 FROM documents d
          WHERE d.mirror_hash = c.mirror_hash AND d.active = 1
        )
      `,
      params: [],
    };
  }

  const port: VectorStatsPort = {
    countVectors(model: string): Promise<StoreResult<number>> {
      try {
        const result = db
          .prepare(
            "SELECT COUNT(*) as count FROM content_vectors WHERE model = ?"
          )
          .get(model) as { count: number };
        return Promise.resolve(ok(result.count));
      } catch (e) {
        return Promise.resolve(
          err(
            "QUERY_FAILED",
            `Failed to count vectors: ${e instanceof Error ? e.message : String(e)}`
          )
        );
      }
    },

    countBacklog(
      model: string,
      embedFingerprint: string,
      options?: { collection?: string }
    ): Promise<StoreResult<number>> {
      try {
        const activeDoc = buildActiveDocumentExistsClause(options?.collection);
        // Count chunks needing embedding (fast for progress display)
        // Uses EXISTS to avoid duplicates when multiple docs share mirror_hash
        const sql = `
          SELECT COUNT(*) as count
          FROM content_chunks c
          WHERE ${activeDoc.sql}
          AND NOT EXISTS (
            SELECT 1 FROM content_vectors v
            WHERE v.mirror_hash = c.mirror_hash
              AND v.seq = c.seq
              AND v.model = ?
              AND v.embed_fingerprint = ?
              AND v.embedded_at >= c.created_at
          )
        `;
        const result = db
          .prepare(sql)
          .get(...activeDoc.params, model, embedFingerprint) as {
          count: number;
        };
        return Promise.resolve(ok(result.count));
      } catch (e) {
        return Promise.resolve(
          err(
            "QUERY_FAILED",
            `Failed to count backlog: ${e instanceof Error ? e.message : String(e)}`
          )
        );
      }
    },

    getBacklog(
      model: string,
      embedFingerprint: string,
      options?: {
        limit?: number;
        after?: { mirrorHash: string; seq: number };
        collection?: string;
      }
    ): Promise<StoreResult<BacklogItem[]>> {
      try {
        const limit = options?.limit ?? 1000;
        const after = options?.after;
        const activeDoc = buildActiveDocumentExistsClause(options?.collection);

        // Seek pagination: use cursor to avoid skipping items as backlog shrinks
        // Query structure changes based on whether we have a cursor
        // Include document title for contextual embedding
        const sql = after
          ? `
          SELECT c.mirror_hash as mirrorHash, c.seq, c.text,
            (SELECT d.title FROM documents d WHERE d.mirror_hash = c.mirror_hash AND d.active = 1 ORDER BY d.id LIMIT 1) as title,
            CASE
              WHEN NOT EXISTS (
                SELECT 1 FROM content_vectors v
                WHERE v.mirror_hash = c.mirror_hash
                  AND v.seq = c.seq
                  AND v.model = ?
                  AND v.embed_fingerprint = ?
              ) THEN 'new'
              ELSE 'changed'
            END as reason
          FROM content_chunks c
          WHERE ${activeDoc.sql}
          AND NOT EXISTS (
            SELECT 1 FROM content_vectors v
            WHERE v.mirror_hash = c.mirror_hash
              AND v.seq = c.seq
              AND v.model = ?
              AND v.embed_fingerprint = ?
              AND v.embedded_at >= c.created_at
          )
          AND (c.mirror_hash > ? OR (c.mirror_hash = ? AND c.seq > ?))
          ORDER BY c.mirror_hash, c.seq
          LIMIT ?
        `
          : `
          SELECT c.mirror_hash as mirrorHash, c.seq, c.text,
            (SELECT d.title FROM documents d WHERE d.mirror_hash = c.mirror_hash AND d.active = 1 ORDER BY d.id LIMIT 1) as title,
            CASE
              WHEN NOT EXISTS (
                SELECT 1 FROM content_vectors v
                WHERE v.mirror_hash = c.mirror_hash
                  AND v.seq = c.seq
                  AND v.model = ?
                  AND v.embed_fingerprint = ?
              ) THEN 'new'
              ELSE 'changed'
            END as reason
          FROM content_chunks c
          WHERE ${activeDoc.sql}
          AND NOT EXISTS (
            SELECT 1 FROM content_vectors v
            WHERE v.mirror_hash = c.mirror_hash
              AND v.seq = c.seq
              AND v.model = ?
              AND v.embed_fingerprint = ?
              AND v.embedded_at >= c.created_at
          )
          ORDER BY c.mirror_hash, c.seq
          LIMIT ?
        `;

        const params = after
          ? [
              model,
              embedFingerprint,
              ...activeDoc.params,
              model,
              embedFingerprint,
              after.mirrorHash,
              after.mirrorHash,
              after.seq,
              limit,
            ]
          : [
              model,
              embedFingerprint,
              ...activeDoc.params,
              model,
              embedFingerprint,
              limit,
            ];

        const results = db.prepare(sql).all(...params) as BacklogItem[];
        return Promise.resolve(ok(results));
      } catch (e) {
        return Promise.resolve(
          err(
            "QUERY_FAILED",
            `Failed to get backlog: ${e instanceof Error ? e.message : String(e)}`
          )
        );
      }
    },
  };
  statsDatabases.set(port, db);
  return port;
}