peterVG

My project for the Vancouver Personal AI Hackday (March 29, 2025) was to familiarize myself with the Hugging Face AI Community Hub.

I decided to build and host an object detection model pipeline by re-creating the infamous "not hot dog" app from the Silicon Valley tv show.

You can try it yourself here: https://huggingface.co/spaces/gvjp/object-detection-1

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peterVG

More About Personal AI

March 29, 2025 -- Vancouver Hack Day - Personal AI

An overview of personal AI that is not owned by big tech and can be controlled by individuals.

Why It Matters

• Privacy: No profiling. Personal data stays local.
• Customization: Fine-tune and personalize models.
• Ownership: Full control over your tools, integrations, features roadmap.
• Resilience: No censorship or sudden API pricing or access changes.

peterVG

Dweb YVR: June 2024 Hackday

Step 0: Pick a hack project

• Logos Network HelloWorld!
  • Logos is a fully decentralised, privacy-preserving, and politically neutral technology stack
  • Logos is composed of three primary protocols: Nomos, Codex, and Waku, for consensus, file storage, and communication respectively.
• Install a Nomos node and connect to a local testnet ✅

peterVG

<?xml version='1.0' encoding='UTF-8'?>
<mets:mets xmlns:mets="http://www.loc.gov/METS/" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/version1121/mets.xsd">
  <mets:metsHdr CREATEDATE="2020-06-11T23:05:01"/>
  <mets:dmdSec ID="dmdSec_1">
    <mets:mdWrap MDTYPE="PREMIS:OBJECT">
      <mets:xmlData>
        <premis:object xmlns:premis="http://www.loc.gov/premis/v3" xsi:type="premis:intellectualEntity" xsi:schemaLocation="http://www.loc.gov/premis/v3 http://www.loc.gov/standards/premis/v3/premis.xsd" version="3.0">
          <premis:objectIdentifier>
            <premis:objectIdentifierType>UUID</premis:objectIdentifierType>
            <premis:objectIdentifierValue>248772ca-9f53-4972-bcd7-f77afb1fae4f</premis:objectIdentifierValue>

peterVG

import base64

sample_string_bytes = base64.b64decode("KFukvivpCM5QXl5SqKe41g==")

print(f"Bytes: {sample_string_bytes}")

try:
    sample_string = sample_string_bytes.decode("utf-8")
    print(f"Decoded string: {sample_string}")
except Exception as e:

peterVG

I put IPFS on a Raspberry Pi and so should you!

Total cost of joining the decentralized storage revolution with your own lo-fi node: $124 USD

• Raspberry Pi 3 B: $43
• Micro SD card: $11
• [Raspberry Pi charger](ht

peterVG

import pymysql.cursors
import sqlite3

mysqlConnection = pymysql.connect(
    host="localhost",
    user="grafana",
    password="grafana",
    db="grafana",
    charset="utf8mb4",
    cursorclass=pymysql.cursors.DictCursor,

peterVG

# pip install pymysql
import pymysql.cursors
import sqlite3
import datetime

sqliteDbName = "am_es_cdd02460-c432-4bdc-bca3-34ae3fb006a6.db"
atomSiteURL = "http://10.10.10.10/"

# Connect to the am-2-atom-metadata-migrator Sqlite database
sqliteDb = sqlite3.connect(sqliteDbName)

peterVG

import datetime
import sys
import json
import os.path
import sqlite3
from elasticsearch import Elasticsearch
from elasticsearch.exceptions import RequestError, NotFoundError


# Connect to Elasticsearch

peterVG

 curl -H 'Content-Type: application/json' -X GET 'http://localhost:9200/_search' -d'
  {
     "query": {
       "match_all": {}
     }
  }' > es.json
  
  
  curl -s -XGET  http://localhost:9200/aipfiles/_doc/_count?q=fileExtension:jpg | jq '.count'