@answerai/answeragent-mcp/dist/services/document-store.js

A lightweight Model Context Protocol (MCP) server for Answer AI chatflow and document store management

import { apiClient } from "./api-client.js";
export class DocumentStoreService {
    constructor() { }
    static getInstance() {
        if (!DocumentStoreService.instance) {
            DocumentStoreService.instance = new DocumentStoreService();
        }
        return DocumentStoreService.instance;
    }
    async listDocumentStores() {
        const { data } = await apiClient.get("/document-store/store");
        return data;
    }
    async getDocumentStore(id) {
        const { data } = await apiClient.get(`/document-store/store/${id}`);
        return data;
    }
    async createDocumentStore(data) {
        const { data: res } = await apiClient.post("/document-store/store", data);
        return res;
    }
    async updateDocumentStore(id, updates) {
        const { data } = await apiClient.put(`/document-store/store/${id}`, updates);
        return data;
    }
    async deleteDocumentStore(id) {
        await apiClient.delete(`/document-store/store/${id}`);
    }
    async upsertDocument(id, payload) {
        const { data } = await apiClient.post(`/document-store/upsert/${id}`, payload);
        return data;
    }
    async refreshDocumentStore(id, payload) {
        const { data } = await apiClient.post(`/document-store/refresh/${id}`, payload);
        return data;
    }
    async queryVectorStore(payload) {
        const { data } = await apiClient.post(`/document-store/vectorstore/query`, payload);
        return data;
    }
}