mirror of
https://github.com/Mintplex-Labs/vector-admin.git
synced 2026-08-27 02:21:18 -04:00
add document embedding search on document view
This commit is contained in:
timothycarambat
@@ -22,6 +22,9 @@ const { validEmbedding } = require("../../../utils/tokenizer");
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const { documentDeletedJob } = require("../../../utils/jobs/documentDeleteJob");
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const { cloneDocumentJob } = require("../../../utils/jobs/cloneDocumentJob");
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const { selectConnector } = require("../../../utils/vectordatabases/providers");
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const {
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documentEmbeddingSearch,
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} = require("../../../utils/search/documentEmbeddings");
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process.env.NODE_ENV === "development"
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? require("dotenv").config({ path: `.env.${process.env.NODE_ENV}` })
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@@ -325,6 +328,41 @@ function documentEndpoints(app) {
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}
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}
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);
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app.get(
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"/v1/documents/:documentId/search-embeddings",
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[validSessionForUser],
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async function (request, response) {
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try {
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const { documentId } = request.params;
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const { method, q: query } = request.query;
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const user = await userFromSession(request);
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if (!user) {
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response.sendStatus(403).end();
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return;
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}
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const document = await WorkspaceDocument.get(`id = ${documentId}`);
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if (!document) {
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response.status(200).json({
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fragments: [],
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error: "No document found.",
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});
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return;
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}
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const { fragments, error } = await documentEmbeddingSearch(
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document,
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method,
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query
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);
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response.status(200).json({ fragments, error });
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} catch (e) {
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console.log(e.message, e);
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response.sendStatus(500).end();
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}
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}
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);
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}
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module.exports = { documentEndpoints };
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@@ -0,0 +1,44 @@
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const { DocumentVectors } = require("../../../models/documentVectors");
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const { WorkspaceDocument } = require("../../../models/workspaceDocument");
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const { readJSON } = require("../../storage");
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// Dirty, but works fast for most cases. Wont be perfect but also not something we should rely
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// heavily on for exact text searching.
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function fuzzyMatch(pattern, str) {
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pattern = ".*" + pattern.split("").join(".*") + ".*";
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const re = new RegExp(pattern);
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return re.test(str);
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}
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async function findTextInDoc(wsDoc, query) {
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try {
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const fragmentIds = [];
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const data = await readJSON(WorkspaceDocument.vectorFilepath(wsDoc));
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for (const chunk of data) {
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if (!chunk.hasOwnProperty("metadata")) continue;
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for (const value of Object.values(chunk?.metadata)) {
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const valid = fuzzyMatch(query, String(value));
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if (valid) fragmentIds.push(chunk.vectorDbId);
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}
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}
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return fragmentIds;
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} catch (e) {
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console.error(e);
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return [];
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}
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}
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async function exactTextSearch(document, query) {
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const matchingVectorIds = await findTextInDoc(document, query);
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if (matchingVectorIds.length === 0) return { fragments: [], error: null };
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const queryString = matchingVectorIds.map((vid) => `'${vid}'`).join(",");
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const fragments = await DocumentVectors.where(`vectorId IN (${queryString})`);
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return { fragments, error: null };
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}
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module.exports = {
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exactTextSearch,
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};
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@@ -0,0 +1,32 @@
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const { Telemetry } = require("../../../models/telemetry");
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const { exactTextSearch } = require("./exactText");
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const { metadataSearch } = require("./metadata");
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const { semanticSearch } = require("./semantic");
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const { vectorIdSearch } = require("./vectorId");
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const SEARCH_METHODS = {
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semantic: semanticSearch,
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exactText: exactTextSearch,
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metadata: metadataSearch,
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vectorId: vectorIdSearch,
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};
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function validSearchMethod(method) {
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return Object.keys(SEARCH_METHODS).includes(method);
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}
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async function documentEmbeddingSearch(document, method, query) {
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try {
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if (!validSearchMethod(method))
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throw new Error(`Invalid search method ${method}`);
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await Telemetry.sendTelemetry("search_executed", { searchMethod: method });
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return await SEARCH_METHODS[method](document, decodeURIComponent(query));
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} catch (e) {
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console.error("Workspace document search", e.message);
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return { fragments: [], error: e.message };
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}
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}
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module.exports = {
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documentEmbeddingSearch,
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};
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@@ -0,0 +1,50 @@
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const { DocumentVectors } = require("../../../models/documentVectors");
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const { WorkspaceDocument } = require("../../../models/workspaceDocument");
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const { readJSON } = require("../../storage");
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// Dirty, but works fast for most cases. Wont be perfect but also not something we should rely
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// heavily on for exact text searching.
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function fuzzyMatch(pattern, str) {
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pattern = ".*" + pattern.split("").join(".*") + ".*";
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const re = new RegExp(pattern);
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return re.test(str);
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}
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async function findKeyValueInDoc(wsDoc, query) {
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try {
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const fragmentIds = [];
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const data = await readJSON(WorkspaceDocument.vectorFilepath(wsDoc));
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const [keyToFind, valueToFind] = query.split(":");
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for (const chunk of data) {
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if (!chunk.hasOwnProperty("metadata")) continue;
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for (const [key, value] of Object.entries(chunk?.metadata)) {
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const validKey = fuzzyMatch(keyToFind, key);
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if (!validKey) continue;
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const match = fuzzyMatch(valueToFind, String(value));
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if (match) fragmentIds.push(chunk.vectorDbId);
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}
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}
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return fragmentIds;
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} catch (e) {
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console.error(e);
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return [];
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}
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}
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async function metadataSearch(document, query) {
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const matchingVectorIds = await findKeyValueInDoc(document, query);
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if (matchingVectorIds.length === 0) return { fragments: [], error: null };
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const queryString = matchingVectorIds.map((vid) => `'${vid}'`).join(",");
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const fragments = await DocumentVectors.where(
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`vectorId IN (${queryString})`,
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200
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);
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return { fragments, error: null };
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}
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module.exports = {
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metadataSearch,
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};
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@@ -0,0 +1,53 @@
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const { DocumentVectors } = require("../../../models/documentVectors");
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const {
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OrganizationConnection,
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} = require("../../../models/organizationConnection");
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const {
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OrganizationWorkspace,
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} = require("../../../models/organizationWorkspace");
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const { SystemSettings } = require("../../../models/systemSettings");
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const { WorkspaceDocument } = require("../../../models/workspaceDocument");
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const { OpenAi } = require("../../openAi");
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const { selectConnector } = require("../../vectordatabases/providers");
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async function semanticSearch(document, query) {
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const workspace = await OrganizationWorkspace.get(
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`id = ${document.workspace_id}`
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);
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const connector = await OrganizationConnection.get(
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`organization_id = ${document.organization_id}`
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);
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if (!connector)
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return { fragments: [], error: "No connector found for org." };
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const openAiKey = (await SystemSettings.get(`label = 'open_ai_api_key'`))
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?.value;
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if (!openAiKey)
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return { fragments: [], error: "No OpenAI key available to embed query." };
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const vectorDb = selectConnector(connector);
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const openai = new OpenAi(openAiKey);
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const queryVector = await openai.embedTextChunk(query);
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if (!queryVector) return { fragments: [], error: "Failed to embed query." };
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// Execute Similarity search for vector DB provider so we can find inferred documents.
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const searchResults = await vectorDb.similarityResponse(
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workspace.slug,
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queryVector
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);
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// From similarity search we can find all document vector DB items to infer their associated
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// document record.
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const searchString = searchResults.vectorIds
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.map((vid) => `'${vid}'`)
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.join(",");
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const fragments = await DocumentVectors.where(
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`vectorId IN (${searchString})`
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);
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return { fragments, error: null };
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}
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module.exports = {
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semanticSearch,
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};
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@@ -0,0 +1,12 @@
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const { DocumentVectors } = require("../../../models/documentVectors");
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async function vectorIdSearch(_document, query) {
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const documentVector = await DocumentVectors.get(`vectorId = '${query}'`);
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if (!documentVector)
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return { fragments: [], error: "No document vector found with that id." };
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return { fragments: [documentVector], error: null };
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}
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module.exports = {
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vectorIdSearch,
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};
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@@ -1,3 +1,4 @@
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import { ISearchTypes } from '../pages/DocumentView/FragmentList/SearchView';
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import { API_BASE } from '../utils/constants';
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import { baseHeaders } from '../utils/request';
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@@ -106,6 +107,27 @@ const Document = {
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return { success: false, error: e.message };
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});
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},
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searchEmbeddings: async (
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documentId: number,
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method: ISearchTypes,
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query: string
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): Promise<{ documents: object[] }> => {
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const searchEndpoint = new URL(
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`${API_BASE}/v1/documents/${documentId}/search-embeddings`
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);
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searchEndpoint.searchParams.append('method', method);
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searchEndpoint.searchParams.append('q', encodeURIComponent(query));
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return await fetch(searchEndpoint, {
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method: 'GET',
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headers: baseHeaders(),
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})
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.then((res) => res.json())
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.then((res) => res?.fragments || [])
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.catch((e) => {
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console.error(e.message);
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return [];
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});
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},
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};
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export default Document;
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@@ -0,0 +1,235 @@
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import {
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Dispatch,
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SetStateAction,
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SyntheticEvent,
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useRef,
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useState,
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} from 'react';
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import { ChevronDown, Search, Loader } from 'react-feather';
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import Document from '../../../../models/document';
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export type ISearchTypes = 'semantic' | 'exactText' | 'metadata' | 'vectorId';
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const SEARCH_MODES = {
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exactText: {
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display: 'Fuzzy Text Search',
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placeholder: 'Find embedding via a fuzzy text match on your query.',
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},
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semantic: {
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display: 'Semantic Search',
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placeholder:
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'Search with natural language finding the most similar embedding by meaning. Use of this search will cost OpenAI credits to embed the query.',
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},
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metadata: {
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display: 'Metadata',
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placeholder:
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'Find embedding by exact key:value pair. Formatted as key:value_to_look_for',
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},
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vectorId: {
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display: 'Vector Id',
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placeholder: 'Find by a specific vector ID',
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},
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};
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export default function SearchView({
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searchMode,
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setSearchMode,
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document,
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FragmentItem,
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canEdit,
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}: {
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searchMode: boolean;
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document: object;
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setSearchMode: Dispatch<SetStateAction<boolean>>;
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FragmentItem: (props: any) => JSX.Element;
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canEdit: boolean;
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}) {
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const formEl = useRef<HTMLFormElement>(null);
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const [searching, setSearching] = useState(false);
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const [showSearchMethods, setShowSearchMethods] = useState(false);
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const [searchBy, setSearchBy] = useState<ISearchTypes>('exactText');
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const [searchTerm, setSearchTerm] = useState<string>('');
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const [fragments, setFragments] = useState([]);
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const [sourceDoc, setSourceDoc] = useState(null);
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const clearSearch = () => {
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setSearchBy('exactText');
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setSearchTerm('');
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setFragments([]);
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setSearching(false);
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setSearchMode(false);
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setSourceDoc(null);
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(formEl.current as HTMLFormElement).reset();
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};
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const handleSearch = async (e: SyntheticEvent<HTMLElement, SubmitEvent>) => {
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e.preventDefault();
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setSearchMode(true);
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const formData = new FormData(e.target as any);
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const query = formData.get('query') as string;
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setSearching(true);
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setSearchTerm(query);
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const matches = await Document.searchEmbeddings(
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document.id,
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searchBy,
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query
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);
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const vectorIds = matches.map((fragment) => fragment.vectorId);
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const metadataForIds = await Document.metadatas(document.id, vectorIds);
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setSourceDoc(metadataForIds);
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setFragments(matches);
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setSearching(false);
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};
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return (
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<div className="w-full flex-1 rounded-sm py-6">
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<div className="flex items-center">
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<form ref={formEl} onSubmit={handleSearch} className="w-full">
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<div className="relative flex">
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<button
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onClick={() => setShowSearchMethods(!showSearchMethods)}
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className="z-10 inline-flex flex-shrink-0 items-center rounded-l-lg border border-gray-300 bg-gray-100 px-4 py-2.5 text-center text-sm font-medium text-gray-900 hover:bg-gray-200 focus:outline-none focus:ring-4 focus:ring-gray-100 dark:border-gray-600 dark:bg-gray-700 dark:text-white dark:hover:bg-gray-600 dark:focus:ring-gray-700"
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type="button"
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>
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{SEARCH_MODES[searchBy].display}
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<ChevronDown size={18} />
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</button>
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<div
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hidden={!showSearchMethods}
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className="absolute left-0 top-12 z-99 w-44 divide-y divide-gray-100 rounded-lg bg-white shadow dark:bg-gray-700"
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>
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<ul
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className="py-2 text-sm text-gray-700 dark:text-gray-200"
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aria-labelledby="dropdown-button"
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>
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{Object.keys(SEARCH_MODES).map((_key, i) => {
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const method = _key as ISearchTypes;
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return (
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<li key={i}>
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<button
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onClick={() => {
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setSearchBy(method);
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setShowSearchMethods(false);
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setFragments([]);
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}}
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type="button"
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className="inline-flex w-full px-4 py-2 hover:bg-gray-100 dark:hover:bg-gray-600 dark:hover:text-white"
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>
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{SEARCH_MODES[method].display}
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</button>
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</li>
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);
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})}
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</ul>
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</div>
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<div className="relative w-full">
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<input
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type="search"
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name="query"
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className="z-20 block w-full rounded-r-lg border border-l-2 border-gray-300 border-l-gray-50 bg-gray-50 p-2.5 text-sm text-gray-900 focus:border-blue-500 focus:ring-blue-500 dark:border-gray-600 dark:border-l-gray-700 dark:bg-gray-700 dark:text-white dark:placeholder-gray-400 dark:focus:border-blue-500"
|
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placeholder={SEARCH_MODES[searchBy].placeholder}
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required
|
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/>
|
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<button
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type="submit"
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disabled={searching}
|
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className="absolute right-0 top-0 h-full rounded-r-lg border border-blue-700 bg-blue-700 p-2.5 text-sm font-medium text-white hover:bg-blue-800 focus:outline-none focus:ring-4 focus:ring-blue-300 dark:bg-blue-600 dark:hover:bg-blue-700 dark:focus:ring-blue-800"
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>
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{searching ? (
|
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<Loader size={18} className="animate-spin" />
|
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) : (
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<Search size={18} />
|
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)}
|
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<span className="sr-only">Search</span>
|
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</button>
|
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</div>
|
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<button
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onClick={clearSearch}
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type="button"
|
||||
className="ml-2 flex items-center rounded-lg px-4 py-2 text-center text-black hover:bg-gray-200"
|
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>
|
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X
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</button>
|
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</div>
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</form>
|
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</div>
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|
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<div hidden={!searchMode} className="h-auto w-auto">
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{searching ? (
|
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<div>
|
||||
<div className="flex min-h-[40vh] w-full px-8">
|
||||
<div className="flex flex h-auto w-full flex-col items-center justify-center gap-y-2 rounded-lg bg-slate-50">
|
||||
<Loader size={15} className="animate-spin rounded-sm" />
|
||||
<p className="text-sm">
|
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Running {SEARCH_MODES[searchBy].display} for{' '}
|
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<code className="bg-gray-200 px-2">"{searchTerm}"</code>
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
) : (
|
||||
<>
|
||||
{fragments.length > 0 ? (
|
||||
<table className="w-full text-left text-sm text-gray-500 dark:text-gray-400">
|
||||
<thead className="bg-gray-50 text-xs uppercase text-gray-700 dark:bg-gray-700 dark:text-gray-400">
|
||||
<tr>
|
||||
<th scope="col" className="px-6 py-3">
|
||||
#
|
||||
</th>
|
||||
<th scope="col" className="px-6 py-3">
|
||||
Vector DB Id
|
||||
</th>
|
||||
<th scope="col" className="px-6 py-3">
|
||||
Text Chunk
|
||||
</th>
|
||||
<th scope="col" className="px-6 py-3">
|
||||
Last Updated
|
||||
</th>
|
||||
<th scope="col" className="px-6 py-3">
|
||||
Actions
|
||||
</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{fragments.map((fragment) => {
|
||||
return (
|
||||
<FragmentItem
|
||||
key={fragment.id}
|
||||
fragment={fragment}
|
||||
sourceDoc={sourceDoc}
|
||||
canEdit={canEdit}
|
||||
/>
|
||||
);
|
||||
})}
|
||||
</tbody>
|
||||
</table>
|
||||
) : (
|
||||
<>
|
||||
<div>
|
||||
<div className="flex min-h-[40vh] w-full px-8">
|
||||
<div className="flex flex h-auto w-full flex-col items-center justify-center gap-y-2 rounded-lg bg-slate-50">
|
||||
{!!searchTerm ? (
|
||||
<p className="text-sm">
|
||||
No results on {SEARCH_MODES[searchBy].display} for{' '}
|
||||
<code className="bg-gray-200 px-2">
|
||||
"{searchTerm}"
|
||||
</code>
|
||||
</p>
|
||||
) : (
|
||||
<p className="text-sm">
|
||||
Type in a query to search for an embedding
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -6,6 +6,7 @@ import moment from 'moment';
|
||||
import { useParams } from 'react-router-dom';
|
||||
import paths from '../../../utils/paths';
|
||||
import DocumentListPagination from '../../../components/DocumentPaginator';
|
||||
import SearchView from './SearchView';
|
||||
const DeleteEmbeddingConfirmation = lazy(
|
||||
() => import('./DeleteEmbeddingConfirmation')
|
||||
);
|
||||
@@ -23,6 +24,7 @@ export default function FragmentList({
|
||||
}) {
|
||||
const { slug, workspaceSlug } = useParams();
|
||||
const [loading, setLoading] = useState(true);
|
||||
const [searchMode, setSearchMode] = useState(false);
|
||||
const [fragments, setFragments] = useState([]);
|
||||
const [sourceDoc, setSourceDoc] = useState(null);
|
||||
const [totalFragments, setTotalFragments] = useState(0);
|
||||
@@ -99,7 +101,14 @@ export default function FragmentList({
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="px-6">
|
||||
<SearchView
|
||||
searchMode={searchMode}
|
||||
setSearchMode={setSearchMode}
|
||||
document={document}
|
||||
FragmentItem={Fragment}
|
||||
canEdit={canEdit}
|
||||
/>
|
||||
<div hidden={searchMode} className="px-6">
|
||||
{loading ? (
|
||||
<div>
|
||||
<PreLoader />
|
||||
@@ -140,17 +149,19 @@ export default function FragmentList({
|
||||
</table>
|
||||
)}
|
||||
</div>
|
||||
<DocumentListPagination
|
||||
pageCount={totalPages}
|
||||
currentPage={currentPage}
|
||||
gotoPage={handlePageChange}
|
||||
/>
|
||||
{!searchMode && (
|
||||
<DocumentListPagination
|
||||
pageCount={totalPages}
|
||||
currentPage={currentPage}
|
||||
gotoPage={handlePageChange}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
</>
|
||||
);
|
||||
}
|
||||
|
||||
const Fragment = ({
|
||||
export const Fragment = ({
|
||||
fragment,
|
||||
sourceDoc,
|
||||
canEdit,
|
||||
@@ -242,7 +253,7 @@ const Fragment = ({
|
||||
);
|
||||
};
|
||||
|
||||
const FullTextWindow = memo(
|
||||
export const FullTextWindow = memo(
|
||||
({ data, fragment }: { data: any; fragment: any }) => {
|
||||
return (
|
||||
<dialog id={`${fragment.id}-text`} className="w-1/2 rounded-lg">
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
import { SyntheticEvent, useState } from 'react';
|
||||
import { SyntheticEvent, useRef, useState } from 'react';
|
||||
import { ChevronDown, FileText, Search, Loader } from 'react-feather';
|
||||
import { CopyDocToModal } from '..';
|
||||
import truncate from 'truncate';
|
||||
@@ -42,17 +42,19 @@ export default function SearchView({
|
||||
stopSearching: VoidFunction;
|
||||
deleteDocument: (documentId: number) => void;
|
||||
}) {
|
||||
const formEl = useRef<HTMLFormElement>(null);
|
||||
const [searching, setSearching] = useState(false);
|
||||
const [showSearchMethods, setShowSearchMethods] = useState(false);
|
||||
const [searchBy, setSearchBy] = useState<ISearchTypes>('exactText');
|
||||
const [searchTerm, setSearchTerm] = useState<string>('');
|
||||
const [documents, setDocuments] = useState([]);
|
||||
const clearSearch = () => {
|
||||
setSearchBy('semantic');
|
||||
setSearchBy('exactText');
|
||||
setSearchTerm('');
|
||||
setDocuments([]);
|
||||
setSearching(false);
|
||||
stopSearching();
|
||||
(formEl.current as HTMLFormElement).reset();
|
||||
};
|
||||
const handleSearch = async (e: SyntheticEvent<HTMLElement, SubmitEvent>) => {
|
||||
e.preventDefault();
|
||||
|
||||
Reference in New Issue
Block a user