mirror of
https://github.com/blakeblackshear/frigate.git
synced 2025-02-05 00:15:51 +01:00
* swap sqlite_vec for chroma in requirements * load sqlite_vec in embeddings manager * remove chroma and revamp Embeddings class for sqlite_vec * manual minilm onnx inference * remove chroma in clip model * migrate api from chroma to sqlite_vec * migrate event cleanup from chroma to sqlite_vec * migrate embedding maintainer from chroma to sqlite_vec * genai description for sqlite_vec * load sqlite_vec in main thread db * extend the SqliteQueueDatabase class and use peewee db.execute_sql * search with Event type for similarity * fix similarity search * install and add comment about transformers * fix normalization * add id filter * clean up * clean up * fully remove chroma and add transformers env var * readd uvicorn for fastapi * readd tokenizer parallelism env var * remove chroma from docs * remove chroma from UI * try removing custom pysqlite3 build * hard code limit * optimize queries * revert explore query * fix query * keep building pysqlite3 * single pass fetch and process * remove unnecessary re-embed * update deps * move SqliteVecQueueDatabase to db directory * make search thumbnail take up full size of results box * improve typing * improve model downloading and add status screen * daemon downloading thread * catch case when semantic search is disabled * fix typing * build sqlite_vec from source * resolve conflict * file permissions * try build deps * remove sources * sources * fix thread start * include git in build * reorder embeddings after detectors are started * build with sqlite amalgamation * non-platform specific * use wget instead of curl * remove unzip -d * remove sqlite_vec from requirements and load the compiled version * fix build * avoid race in db connection * add scale_factor and bias to description zscore normalization
318 lines
10 KiB
TypeScript
318 lines
10 KiB
TypeScript
import { useEventUpdate, useModelState } from "@/api/ws";
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import ActivityIndicator from "@/components/indicators/activity-indicator";
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import { useApiFilterArgs } from "@/hooks/use-api-filter";
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import { useTimezone } from "@/hooks/use-date-utils";
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import { FrigateConfig } from "@/types/frigateConfig";
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import { SearchFilter, SearchQuery, SearchResult } from "@/types/search";
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import { ModelState } from "@/types/ws";
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import SearchView from "@/views/search/SearchView";
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import { useCallback, useEffect, useMemo, useState } from "react";
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import { LuCheck, LuExternalLink, LuX } from "react-icons/lu";
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import { TbExclamationCircle } from "react-icons/tb";
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import { Link } from "react-router-dom";
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import useSWR from "swr";
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import useSWRInfinite from "swr/infinite";
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const API_LIMIT = 25;
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export default function Explore() {
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// search field handler
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const { data: config } = useSWR<FrigateConfig>("config", {
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revalidateOnFocus: false,
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});
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const timezone = useTimezone(config);
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const [search, setSearch] = useState("");
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const [searchFilter, setSearchFilter, searchSearchParams] =
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useApiFilterArgs<SearchFilter>();
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const searchTerm = useMemo(
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() => searchSearchParams?.["query"] || "",
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[searchSearchParams],
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);
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const similaritySearch = useMemo(
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() => searchSearchParams["search_type"] == "similarity",
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[searchSearchParams],
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);
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useEffect(() => {
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if (!searchTerm && !search) {
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return;
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}
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// switch back to normal search when query is entered
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setSearchFilter({
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...searchFilter,
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search_type:
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similaritySearch && search ? undefined : searchFilter?.search_type,
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event_id: similaritySearch && search ? undefined : searchFilter?.event_id,
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query: search.length > 0 ? search : undefined,
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});
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// only update when search is updated
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// eslint-disable-next-line react-hooks/exhaustive-deps
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}, [search]);
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const searchQuery: SearchQuery = useMemo(() => {
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// no search parameters
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if (searchSearchParams && Object.keys(searchSearchParams).length === 0) {
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return null;
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}
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// parameters, but no search term and not similarity
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if (
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searchSearchParams &&
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Object.keys(searchSearchParams).length !== 0 &&
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!searchTerm &&
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!similaritySearch
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) {
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return [
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"events",
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{
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cameras: searchSearchParams["cameras"],
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labels: searchSearchParams["labels"],
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sub_labels: searchSearchParams["sub_labels"],
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zones: searchSearchParams["zones"],
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before: searchSearchParams["before"],
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after: searchSearchParams["after"],
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time_range: searchSearchParams["time_range"],
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search_type: searchSearchParams["search_type"],
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limit:
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Object.keys(searchSearchParams).length == 0 ? API_LIMIT : undefined,
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timezone,
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in_progress: 0,
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include_thumbnails: 0,
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},
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];
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}
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// parameters and search term
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if (!similaritySearch) {
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setSearch(searchTerm);
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}
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return [
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"events/search",
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{
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query: similaritySearch ? undefined : searchTerm,
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cameras: searchSearchParams["cameras"],
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labels: searchSearchParams["labels"],
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sub_labels: searchSearchParams["sub_labels"],
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zones: searchSearchParams["zones"],
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before: searchSearchParams["before"],
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after: searchSearchParams["after"],
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time_range: searchSearchParams["time_range"],
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search_type: searchSearchParams["search_type"],
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event_id: searchSearchParams["event_id"],
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timezone,
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include_thumbnails: 0,
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},
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];
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}, [searchTerm, searchSearchParams, similaritySearch, timezone]);
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// paging
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const getKey = (
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pageIndex: number,
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previousPageData: SearchResult[] | null,
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): SearchQuery => {
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if (previousPageData && !previousPageData.length) return null; // reached the end
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if (!searchQuery) return null;
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const [url, params] = searchQuery;
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// If it's not the first page, use the last item's start_time as the 'before' parameter
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if (pageIndex > 0 && previousPageData) {
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const lastDate = previousPageData[previousPageData.length - 1].start_time;
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return [
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url,
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{ ...params, before: lastDate.toString(), limit: API_LIMIT },
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];
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}
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// For the first page, use the original params
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return [url, { ...params, limit: API_LIMIT }];
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};
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const { data, size, setSize, isValidating, mutate } = useSWRInfinite<
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SearchResult[]
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>(getKey, {
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revalidateFirstPage: true,
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revalidateOnFocus: true,
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revalidateAll: false,
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});
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const searchResults = useMemo(
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() => (data ? ([] as SearchResult[]).concat(...data) : []),
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[data],
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);
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const isLoadingInitialData = !data && !isValidating;
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const isLoadingMore =
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isLoadingInitialData ||
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(size > 0 && data && typeof data[size - 1] === "undefined");
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const isEmpty = data?.[0]?.length === 0;
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const isReachingEnd =
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isEmpty || (data && data[data.length - 1]?.length < API_LIMIT);
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const loadMore = useCallback(() => {
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if (!isReachingEnd && !isLoadingMore) {
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if (searchQuery) {
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const [url] = searchQuery;
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// for embeddings, only load 100 results for description and similarity
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if (url === "events/search" && searchResults.length >= 100) {
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return;
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}
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}
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setSize(size + 1);
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}
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}, [isReachingEnd, isLoadingMore, setSize, size, searchResults, searchQuery]);
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// mutation and revalidation
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const eventUpdate = useEventUpdate();
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useEffect(() => {
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mutate();
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// mutate / revalidate when event description updates come in
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// eslint-disable-next-line react-hooks/exhaustive-deps
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}, [eventUpdate]);
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// model states
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const { payload: minilmModelState } = useModelState(
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"sentence-transformers/all-MiniLM-L6-v2-model.onnx",
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);
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const { payload: minilmTokenizerState } = useModelState(
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"sentence-transformers/all-MiniLM-L6-v2-tokenizer",
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);
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const { payload: clipImageModelState } = useModelState(
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"clip-clip_image_model_vitb32.onnx",
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);
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const { payload: clipTextModelState } = useModelState(
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"clip-clip_text_model_vitb32.onnx",
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);
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const allModelsLoaded = useMemo(() => {
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return (
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minilmModelState === "downloaded" &&
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minilmTokenizerState === "downloaded" &&
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clipImageModelState === "downloaded" &&
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clipTextModelState === "downloaded"
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);
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}, [
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minilmModelState,
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minilmTokenizerState,
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clipImageModelState,
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clipTextModelState,
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]);
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const renderModelStateIcon = (modelState: ModelState) => {
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if (modelState === "downloading") {
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return <ActivityIndicator className="size-5" />;
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}
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if (modelState === "downloaded") {
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return <LuCheck className="size-5 text-success" />;
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}
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if (modelState === "not_downloaded" || modelState === "error") {
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return <LuX className="size-5 text-danger" />;
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}
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return null;
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};
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if (
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!minilmModelState ||
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!minilmTokenizerState ||
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!clipImageModelState ||
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!clipTextModelState
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) {
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return (
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<ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
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);
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}
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return (
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<>
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{!allModelsLoaded ? (
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<div className="absolute inset-0 left-1/2 top-1/2 flex h-96 w-96 -translate-x-1/2 -translate-y-1/2">
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<div className="flex flex-col items-center justify-center space-y-3 rounded-lg bg-background/50 p-5">
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<div className="my-5 flex flex-col items-center gap-2 text-xl">
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<TbExclamationCircle className="mb-3 size-10" />
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<div>Search Unavailable</div>
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</div>
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<div className="max-w-96 text-center">
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Frigate is downloading the necessary embeddings models to support
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semantic searching. This may take several minutes depending on the
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speed of your network connection.
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</div>
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<div className="flex w-96 flex-col gap-2 py-5">
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<div className="flex flex-row items-center justify-center gap-2">
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{renderModelStateIcon(clipImageModelState)}
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CLIP image model
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</div>
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<div className="flex flex-row items-center justify-center gap-2">
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{renderModelStateIcon(clipTextModelState)}
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CLIP text model
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</div>
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<div className="flex flex-row items-center justify-center gap-2">
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{renderModelStateIcon(minilmModelState)}
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MiniLM sentence model
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</div>
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<div className="flex flex-row items-center justify-center gap-2">
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{renderModelStateIcon(minilmTokenizerState)}
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MiniLM tokenizer
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</div>
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</div>
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{(minilmModelState === "error" ||
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clipImageModelState === "error" ||
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clipTextModelState === "error") && (
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<div className="my-3 max-w-96 text-center text-danger">
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An error has occurred. Check Frigate logs.
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</div>
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)}
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<div className="max-w-96 text-center">
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You may want to reindex the embeddings of your tracked objects
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once the models are downloaded.
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</div>
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<div className="flex max-w-96 items-center text-primary-variant">
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<Link
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to="https://docs.frigate.video/configuration/semantic_search"
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target="_blank"
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rel="noopener noreferrer"
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className="inline"
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>
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Read the documentation{" "}
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<LuExternalLink className="ml-2 inline-flex size-3" />
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</Link>
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</div>
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</div>
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</div>
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) : (
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<SearchView
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search={search}
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searchTerm={searchTerm}
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searchFilter={searchFilter}
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searchResults={searchResults}
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isLoading={(isLoadingInitialData || isLoadingMore) ?? true}
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setSearch={setSearch}
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setSimilaritySearch={(search) => {
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setSearchFilter({
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...searchFilter,
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search_type: ["similarity"],
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event_id: search.id,
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});
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}}
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setSearchFilter={setSearchFilter}
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onUpdateFilter={setSearchFilter}
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loadMore={loadMore}
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hasMore={!isReachingEnd}
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/>
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)}
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</>
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);
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}
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