@good-i-deer/node-red-contrib-chromadb 1.0.5

ChromaDB Node for Node-RED

npm install @good-i-deer/node-red-contrib-chromadb

@good-i-deer/node-red-contrib-chromadb

platform npm version GitHub license

This module provides a node that connects and operates with ChromaDB in Node-RED.

These nodes require node.js version 18.16.1 and Node-RED version 3.1.0.


Description

This node is part of the Facial Recognition with AI package.
If you would like to see the entire package, please go to the link. @good-i-deer/node-red-contrib-vision-ai

ChromaDB is the open-source embedding database. ChromaDB makes it easy to store and query embedded values. This node makes it possible to run ChromaDB operations(create/delete collection, insert/query/delete embedding) in Node-RED.


Pre-requisites

The Node-Red-Contrib-ChromaDB requires Node-RED to be installed and requires a running Chroma-DB server.

If necessary, you can install and run the chromaDB server on local. Please refer to Getting Started.


Install

cd ~/.node-red
npm install @good-i-deer/node-red-contrib-chromadb

Restart your Node-RED instance.


Input

Single Embedding

  • The input could be an embedding value in the form of an array of real numbers.
  • Used for input of insert or query operation.

Embedding Array

  • The input could be embedding values in the form of an array of real number arrays.
  • Used for input of insert or query operation.

ID Array

  • The input could be one or more ids in the form of an array of string.
  • Used for input of delete operation.

property

image

Name

  • The name of the node displayed on the screen.

Host

  • The addreess where ChromaDB server is running.

Port

  • The port number where ChromDB server is running.

Operation

  • The operation that want to run on ChromaDB.

  • Operation Types

    • list: list all collections in ChromaDB server.

    • create: create collection. Does not create if the collection with same name already exists.

    • insert: insert embedding value(s) into the collection.

    • query: query the N nearest distance embeddings.

    • delete: delete embedding with id.

    • drop: drop collection.

DB Name

  • The name of DB(collection) that you want to create, delete, or apply the operation.

Dist Method

  • The distance method for calculating distances between embeddings.

  • You can set the distance method when you create DB.

Result Count

  • The number of result you want to get when you run query operation.

  • Query operation return N(=result count) nearest distance for each embedding.


Output

Collection list

  • After list operation, collection list in the form of a string array are passed within msg.payload.

ID Array

  • After inserting embeddings, IDs in the form of a string array are passed within msg.result.

Query Response

  • After querying embeddings, the query response, which contains IDs, distances, metadatas, and documents in the form of an object, is passed within msg.payload.

Result

  • After create, drop operation, the result explaining success of operation in the form of a string is passed within msg.result.

Examples

The following are example flows using Good ChromaDB.

image

JSON

[
    {
        "id": "1e6ef671efdf6e7b",
        "type": "tab",
        "label": "ChromaDB",
        "disabled": false,
        "info": "",
        "env": []
    },
    {
        "id": "4792f9f4b8190c2f",
        "type": "inject",
        "z": "1e6ef671efdf6e7b",
        "name": "",
        "props": [],
        "repeat": "",
        "crontab": "",
        "once": false,
        "onceDelay": 0.1,
        "topic": "",
        "x": 290,
        "y": 320,
        "wires": [
            [
                "a8efe2228a20081d"
            ]
        ]
    },
    {
        "id": "c6332d85335a6f9f",
        "type": "debug",
        "z": "1e6ef671efdf6e7b",
        "name": "Result",
        "active": true,
        "tosidebar": true,
        "console": false,
        "tostatus": false,
        "complete": "result",
        "targetType": "msg",
        "statusVal": "",
        "statusType": "auto",
        "x": 750,
        "y": 320,
        "wires": []
    },
    {
        "id": "1d56935af7702c2d",
        "type": "comment",
        "z": "1e6ef671efdf6e7b",
        "name": "Good I Deer ChromaDB",
        "info": "",
        "x": 320,
        "y": 200,
        "wires": []
    },
    {
        "id": "d667ed331e78790d",
        "type": "inject",
        "z": "1e6ef671efdf6e7b",
        "name": "Embeddings",
        "props": [
            {
                "p": "payload"
            },
            {
                "p": "topic",
                "vt": "str"
            }
        ],
        "repeat": "",
        "crontab": "",
        "once": false,
        "onceDelay": 0.1,
        "topic": "",
        "payload": "[[1.2, 2.4, 4.5], [2.2, 4.4, 4.5]]",
        "payloadType": "jsonata",
        "x": 310,
        "y": 380,
        "wires": [
            [
                "c203de7681166255"
            ]
        ]
    },
    {
        "id": "e778da936ae795f4",
        "type": "debug",
        "z": "1e6ef671efdf6e7b",
        "name": "Result",
        "active": true,
        "tosidebar": true,
        "console": false,
        "tostatus": false,
        "complete": "result",
        "targetType": "msg",
        "statusVal": "",
        "statusType": "auto",
        "x": 750,
        "y": 380,
        "wires": []
    },
    {
        "id": "6ae163d47c1f45cf",
        "type": "inject",
        "z": "1e6ef671efdf6e7b",
        "name": "Embeddings",
        "props": [
            {
                "p": "payload"
            },
            {
                "p": "topic",
                "vt": "str"
            }
        ],
        "repeat": "",
        "crontab": "",
        "once": false,
        "onceDelay": 0.1,
        "topic": "",
        "payload": "[[1.2, 2.4, 4.5], [2.2, 4.4, 4.5]]",
        "payloadType": "jsonata",
        "x": 310,
        "y": 440,
        "wires": [
            [
                "5f7cd9e19723b46e"
            ]
        ]
    },
    {
        "id": "32ea1864d84fdb4e",
        "type": "debug",
        "z": "1e6ef671efdf6e7b",
        "name": "Payload",
        "active": true,
        "tosidebar": true,
        "console": false,
        "tostatus": false,
        "complete": "payload",
        "targetType": "msg",
        "statusVal": "",
        "statusType": "auto",
        "x": 760,
        "y": 440,
        "wires": []
    },
    {
        "id": "8c25f32070d63b87",
        "type": "inject",
        "z": "1e6ef671efdf6e7b",
        "name": "IDs",
        "props": [
            {
                "p": "payload"
            },
            {
                "p": "topic",
                "vt": "str"
            }
        ],
        "repeat": "",
        "crontab": "",
        "once": false,
        "onceDelay": 0.1,
        "topic": "",
        "payload": "[\"id-1\", \"id-2\"]",
        "payloadType": "jsonata",
        "x": 290,
        "y": 500,
        "wires": [
            [
                "cf75be103178217a"
            ]
        ]
    },
    {
        "id": "67946cfb0b10bac5",
        "type": "debug",
        "z": "1e6ef671efdf6e7b",
        "name": "Result",
        "active": true,
        "tosidebar": true,
        "console": false,
        "tostatus": false,
        "complete": "payload",
        "targetType": "msg",
        "statusVal": "",
        "statusType": "auto",
        "x": 750,
        "y": 500,
        "wires": []
    },
    {
        "id": "4acb518fd1eb8271",
        "type": "inject",
        "z": "1e6ef671efdf6e7b",
        "name": "",
        "props": [],
        "repeat": "",
        "crontab": "",
        "once": false,
        "onceDelay": 0.1,
        "topic": "",
        "x": 290,
        "y": 260,
        "wires": [
            [
                "603eb6e696d796f2"
            ]
        ]
    },
    {
        "id": "63358d81ceaa24de",
        "type": "debug",
        "z": "1e6ef671efdf6e7b",
        "name": "Payload",
        "active": true,
        "tosidebar": true,
        "console": false,
        "tostatus": false,
        "complete": "payload",
        "targetType": "msg",
        "statusVal": "",
        "statusType": "auto",
        "x": 760,
        "y": 260,
        "wires": []
    },
    {
        "id": "624f10863faede9f",
        "type": "inject",
        "z": "1e6ef671efdf6e7b",
        "name": "",
        "props": [],
        "repeat": "",
        "crontab": "",
        "once": false,
        "onceDelay": 0.1,
        "topic": "",
        "x": 290,
        "y": 560,
        "wires": [
            [
                "30f9b81713d706aa"
            ]
        ]
    },
    {
        "id": "796b026101abc5f9",
        "type": "debug",
        "z": "1e6ef671efdf6e7b",
        "name": "Result",
        "active": true,
        "tosidebar": true,
        "console": false,
        "tostatus": false,
        "complete": "result",
        "targetType": "msg",
        "statusVal": "",
        "statusType": "auto",
        "x": 750,
        "y": 560,
        "wires": []
    },
    {
        "id": "a8efe2228a20081d",
        "type": "good-chroma-db",
        "z": "1e6ef671efdf6e7b",
        "name": "Create Collection",
        "dbIp": "http://localhost",
        "dbPort": "8000",
        "dbName": "MyCollection",
        "distance": "cosine",
        "operation": "create",
        "nResults": "1",
        "x": 530,
        "y": 320,
        "wires": [
            [
                "c6332d85335a6f9f"
            ]
        ]
    },
    {
        "id": "c203de7681166255",
        "type": "good-chroma-db",
        "z": "1e6ef671efdf6e7b",
        "name": "Insert Embeddings",
        "dbIp": "http://localhost",
        "dbPort": "8000",
        "dbName": "MyCollection",
        "distance": "cosine",
        "operation": "insert",
        "nResults": "1",
        "x": 530,
        "y": 380,
        "wires": [
            [
                "e778da936ae795f4"
            ]
        ]
    },
    {
        "id": "5f7cd9e19723b46e",
        "type": "good-chroma-db",
        "z": "1e6ef671efdf6e7b",
        "name": "Query Embeddings",
        "dbIp": "http://localhost",
        "dbPort": "8000",
        "dbName": "MyCollection",
        "distance": "cosine",
        "operation": "query",
        "nResults": "10",
        "x": 530,
        "y": 440,
        "wires": [
            [
                "32ea1864d84fdb4e"
            ]
        ]
    },
    {
        "id": "cf75be103178217a",
        "type": "good-chroma-db",
        "z": "1e6ef671efdf6e7b",
        "name": "Delete Embeddings",
        "dbIp": "http://localhost",
        "dbPort": "8000",
        "dbName": "MyCollection",
        "distance": "cosine",
        "operation": "delete",
        "nResults": "1",
        "x": 530,
        "y": 500,
        "wires": [
            [
                "67946cfb0b10bac5"
            ]
        ]
    },
    {
        "id": "30f9b81713d706aa",
        "type": "good-chroma-db",
        "z": "1e6ef671efdf6e7b",
        "name": "Drop Collection",
        "dbIp": "http://localhost",
        "dbPort": "8000",
        "dbName": "MyCollection",
        "distance": "cosine",
        "operation": "drop",
        "nResults": "1",
        "x": 520,
        "y": 560,
        "wires": [
            [
                "796b026101abc5f9"
            ]
        ]
    },
    {
        "id": "603eb6e696d796f2",
        "type": "good-chroma-db",
        "z": "1e6ef671efdf6e7b",
        "name": "List Collections",
        "dbIp": "http://localhost",
        "dbPort": "8000",
        "dbName": "MyCollection",
        "distance": "cosine",
        "operation": "list",
        "nResults": "1",
        "x": 520,
        "y": 260,
        "wires": [
            [
                "63358d81ceaa24de"
            ]
        ]
    }
]

Discussions and suggestions

Use GitHub Issues to ask questions or to discuss new features.


Authors

GOOD-I-DEER in SSAFY(Samsung Software Academy for Youth) 9th


Copyright and license

Copyright Samsung Automation Studio Team under the Apache 2.0 license


Reference

Node Info

Version: 1.0.5
Updated 1 year, 3 months ago
License: Apache-2.0
Rating: 5.0 2

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Nodes

  • good-chroma-db

Keywords

  • node-red
  • vector
  • database
  • chromadb
  • embedding