type MemoryEmbeddingProviderRuntime,

} from "openclaw/plugin-sdk/memory-core-host-engine-embeddings";

import { createSubsystemLogger } from "openclaw/plugin-sdk/memory-core-host-engine-foundation";

import { type SessionFileEntry } from "openclaw/plugin-sdk/memory-core-host-engine-qmd";

import {

buildMultimodalChunkForIndexing,

chunkMarkdown,

hashText,

remapChunkLines,

type MemoryChunk,

type MemoryFileEntry,

type MemorySource,

} from "openclaw/plugin-sdk/memory-core-host-engine-storage";

import {

const log = createSubsystemLogger("memory");

type MemoryIndexEntry = {

path: string;

absPath: string;

mtimeMs: number;

size: number;

hash: string;

kind?: "markdown" | "multimodal";

contentText?: string;

lineMap?: number[];

};

export function resolveEmbeddingTimeoutMs(params: {

kind: "query" | "batch";

providerId?: string;

private async embedChunksWithBatch(

chunks: MemoryChunk[],

_entry: MemoryFileEntry | SessionFileEntry,

_entry: MemoryIndexEntry,

source: MemorySource,

): Promise<number[][]> {

const provider = this.provider;

this.db.prepare(`DELETE FROM chunks WHERE path = ? AND source = ?`).run(pathname, source);

}

private upsertFileRecord(entry: MemoryFileEntry | SessionFileEntry, source: MemorySource): void {

private upsertFileRecord(entry: MemoryIndexEntry, source: MemorySource): void {

this.db

.prepare(

`INSERT INTO files (path, source, hash, mtime, size) VALUES (?, ?, ?, ?, ?)

* Pass an empty embeddings array to skip vector writes (FTS-only mode).

*/

private writeChunks(

entry: MemoryFileEntry | SessionFileEntry,

entry: MemoryIndexEntry,

source: MemorySource,

model: string,

chunks: MemoryChunk[],

}

protected async indexFile(

entry: MemoryFileEntry | SessionFileEntry,

entry: MemoryIndexEntry,

options: { source: MemorySource; content?: string },

) {

// FTS-only mode: no embedding provider, but we can still build a FTS index