Use sqlite-vec extension instead of chromadb for embeddings (#14163)

* 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
This commit is contained in:
Josh Hawkins
2024-10-07 15:30:45 -05:00
committed by GitHub
parent 757150dec1
commit 24ac9f3e5a
42 changed files with 951 additions and 533 deletions

View File

@@ -1,11 +1,15 @@
import { useEventUpdate } from "@/api/ws";
import { useEventUpdate, useModelState } from "@/api/ws";
import ActivityIndicator from "@/components/indicators/activity-indicator";
import { useApiFilterArgs } from "@/hooks/use-api-filter";
import { useTimezone } from "@/hooks/use-date-utils";
import { FrigateConfig } from "@/types/frigateConfig";
import { SearchFilter, SearchQuery, SearchResult } from "@/types/search";
import { ModelState } from "@/types/ws";
import SearchView from "@/views/search/SearchView";
import { useCallback, useEffect, useMemo, useState } from "react";
import { LuCheck, LuExternalLink, LuX } from "react-icons/lu";
import { TbExclamationCircle } from "react-icons/tb";
import { Link } from "react-router-dom";
import useSWR from "swr";
import useSWRInfinite from "swr/infinite";
@@ -111,14 +115,10 @@ export default function Explore() {
// paging
// usually slow only on first run while downloading models
const [isSlowLoading, setIsSlowLoading] = useState(false);
const getKey = (
pageIndex: number,
previousPageData: SearchResult[] | null,
): SearchQuery => {
if (isSlowLoading && !similaritySearch) return null;
if (previousPageData && !previousPageData.length) return null; // reached the end
if (!searchQuery) return null;
@@ -143,12 +143,6 @@ export default function Explore() {
revalidateFirstPage: true,
revalidateOnFocus: true,
revalidateAll: false,
onLoadingSlow: () => {
if (!similaritySearch) {
setIsSlowLoading(true);
}
},
loadingTimeout: 15000,
});
const searchResults = useMemo(
@@ -168,7 +162,7 @@ export default function Explore() {
if (searchQuery) {
const [url] = searchQuery;
// for chroma, only load 100 results for description and similarity
// for embeddings, only load 100 results for description and similarity
if (url === "events/search" && searchResults.length >= 100) {
return;
}
@@ -188,17 +182,113 @@ export default function Explore() {
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [eventUpdate]);
// model states
const { payload: minilmModelState } = useModelState(
"sentence-transformers/all-MiniLM-L6-v2-model.onnx",
);
const { payload: minilmTokenizerState } = useModelState(
"sentence-transformers/all-MiniLM-L6-v2-tokenizer",
);
const { payload: clipImageModelState } = useModelState(
"clip-clip_image_model_vitb32.onnx",
);
const { payload: clipTextModelState } = useModelState(
"clip-clip_text_model_vitb32.onnx",
);
const allModelsLoaded = useMemo(() => {
return (
minilmModelState === "downloaded" &&
minilmTokenizerState === "downloaded" &&
clipImageModelState === "downloaded" &&
clipTextModelState === "downloaded"
);
}, [
minilmModelState,
minilmTokenizerState,
clipImageModelState,
clipTextModelState,
]);
const renderModelStateIcon = (modelState: ModelState) => {
if (modelState === "downloading") {
return <ActivityIndicator className="size-5" />;
}
if (modelState === "downloaded") {
return <LuCheck className="size-5 text-success" />;
}
if (modelState === "not_downloaded" || modelState === "error") {
return <LuX className="size-5 text-danger" />;
}
return null;
};
if (
!minilmModelState ||
!minilmTokenizerState ||
!clipImageModelState ||
!clipTextModelState
) {
return (
<ActivityIndicator className="absolute left-1/2 top-1/2 -translate-x-1/2 -translate-y-1/2" />
);
}
return (
<>
{isSlowLoading && !similaritySearch ? (
{!allModelsLoaded ? (
<div className="absolute inset-0 left-1/2 top-1/2 flex h-96 w-96 -translate-x-1/2 -translate-y-1/2">
<div className="flex flex-col items-center justify-center rounded-lg bg-background/50 p-5">
<p className="my-5 text-lg">Search Unavailable</p>
<TbExclamationCircle className="mb-3 size-10" />
<p className="max-w-96 text-center">
If this is your first time using Search, be patient while Frigate
downloads the necessary embeddings models. Check Frigate logs.
</p>
<div className="flex flex-col items-center justify-center space-y-3 rounded-lg bg-background/50 p-5">
<div className="my-5 flex flex-col items-center gap-2 text-xl">
<TbExclamationCircle className="mb-3 size-10" />
<div>Search Unavailable</div>
</div>
<div className="max-w-96 text-center">
Frigate is downloading the necessary embeddings models to support
semantic searching. This may take several minutes depending on the
speed of your network connection.
</div>
<div className="flex w-96 flex-col gap-2 py-5">
<div className="flex flex-row items-center justify-center gap-2">
{renderModelStateIcon(clipImageModelState)}
CLIP image model
</div>
<div className="flex flex-row items-center justify-center gap-2">
{renderModelStateIcon(clipTextModelState)}
CLIP text model
</div>
<div className="flex flex-row items-center justify-center gap-2">
{renderModelStateIcon(minilmModelState)}
MiniLM sentence model
</div>
<div className="flex flex-row items-center justify-center gap-2">
{renderModelStateIcon(minilmTokenizerState)}
MiniLM tokenizer
</div>
</div>
{(minilmModelState === "error" ||
clipImageModelState === "error" ||
clipTextModelState === "error") && (
<div className="my-3 max-w-96 text-center text-danger">
An error has occurred. Check Frigate logs.
</div>
)}
<div className="max-w-96 text-center">
You may want to reindex the embeddings of your tracked objects
once the models are downloaded.
</div>
<div className="flex max-w-96 items-center text-primary-variant">
<Link
to="https://docs.frigate.video/configuration/semantic_search"
target="_blank"
rel="noopener noreferrer"
className="inline"
>
Read the documentation{" "}
<LuExternalLink className="ml-2 inline-flex size-3" />
</Link>
</div>
</div>
</div>
) : (