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· 7 min read
Haunani Pao

In 2023, I embarked on a hands-on “maker” journey in tech and creativity with the goal of expanding my knowledge and tech skills with Web3 projects and experiences. I participated in several immersive learning opportunities from coding in a hackathon and Web3 developer relations to conceptualising, creating and hosting a series of Fusion Talks, having rich conversations with people in Web3 to finishing 2023 on a high with other women in Shefi S9.

Thirdweb Learn!

Thirdweb
I 💜 Thirdweb, one of my favourite Web3 tools.

In mid-2023, I crossed paths with Josh Howard during the Thirdweb Learn pilot cohort. Thirdweb was introduced to me when I participated in the "Ready Player 3 | thirdweb's Web3 Gaming hackathon" early in 2023. It was the first time I coded in a game hackathon. I learned alot and made some amazing new friends.

Josh introduced his latest project, Art Locatia, a cool Web3 App empowering artists to showcase their work on the Polygon blockchain, while giving explorers and fans a way to view their art through augmented reality (AR) on their mobile devices. I recognised that it behaved like "Pokemon Go!" but with the blockchain for ownership and transactions. He was inspired by real life art projects he discovered in his local neighbourhood and used the thirdweb sdk to craft this digital concept. I got to know him because he was always willing to answer my questions about technology and coding for my own NFT project.

Buildspace S4

Buildspace Season 4
Meet the Buildspace S4 Cohort 2023 / Alot of ideas and experimentation.

After completing Thirdweb Learn, we joined season 4 of Buildspace to cultivate our individual projects. Each week, the founder of Buildspace shared insightful stories about iterating ideas and the valuable lessons that shaped the Buildspace project.

These stories included:

  • exploring your idea and setting small, tangible goals,
  • seeking feedback from others through social media,
  • adapting ideas based on feedback,
  • then presenting your refined project to the massive cohort, make connections and take further steps.

These steps resonated with my design process. This framework enables you to align with your time constraints, explore many ideas quickly, and challenge yourself. Josh dug in and took Art Locatia to the next level, while I delved into Fusion Talks – a series of conversations with people I’ve met on my Web3 journey. Together we unpack our origin stories, what we are doing in Web3, what we have learned and what we are doing next.

Fusion Talks

Fusion Talks with Josh Howard, founder of Art Locatia

The turning point came when Josh joined me for his Fusion Talk to share his adventures in Web3 and the outcomes from his Buildspace project for Art Locatia. Little did I know, this Fusion Talk would spark a collaborative journey and allow me to share my design skills and human journey of a hobby artist to the blockchain world.

Challenges along the way

To prepare for his Fusion Talk, I prepared my own piece of traditional art for Art Locatia. One of the challenges for me was learning Blender to make 3D models. Blender has a rich tool set to make pretty much anything, especially animation, but when you are new to it, it feels overwhelming and complex. I needed it to take a digital copy of my 2d acrylic painting and transform it into a 3D *glb model. I work on my Windows machine, so trying to make a model for Apple iOS, was not simple to do but Josh helped me out.

Another challenge was managing the many steps to get my art prepared and onto the Blockchain using thirdweb dashboard. Up until this time, I was using thirdweb SDK to deal with wallets or using NFTs to claim and play a game, but now I’m making ERC1155 contracts and adding my art to it through a JSON file. There wasn’t anything insurmountable, but it is important to understand the end-to-end process to avoid mistakes and find efficiencies in the process. And learning takes time. After I successfully saw my artwork on the Art Locatia test map, I felt accomplished and ready to share.😍

Shattered by Haunani Pao   Shattered Artwork on Art Locatia
Success! I can find my art on the Art Locatia test app!

From Collaboration to Contribution

When I unpacked my novice journey and challenges of the 3D models with Josh, he reasoned that offering a Studio feature to help new artists traverse these key steps could be useful especially with blockchain and smart contacts. If you are an artist that is already comfortable making NFTs for the blockchain, the process made sense and was straightforward to execute. But if you’re new, this Studio feature could be tremendously helpful.

Wireframes for Ideation
Using wireframes as part of the ideation process and invite meaningful conversations.

My collaboration includes using my UX research skills to describe my art journey, identify potential hiccups and ideate wireframes in Figma for Josh to consider in the Art Locatia Studio feature. It helped us to use our time wisely for decision making and next steps. We took pragmatic heuristic steps to give an artist an easy flow to make the NFT JSON file needed by other parts of the process. Even with our busy schedules full of our responsibilities and living in different parts of the world, we found ways to keep in touch over time, even if it was making videos or just chatting on discord to share statuses and updates.

After Josh coded a prototype for Art Locatia Studio, I leveraged my "Dev Rel" experience to contribute to its product documentation, starting with a draft version for feedback before using markup, javascript and git skills on Docusaurus for the production version. One of the things I appreciate about the collaboration is that Josh grew to trust my skills and he appreciates my contributions. He’s very generous with his time and knowledge when we catch up.

Imagining an Artful Future

Now that we are in 2024, I'm anticipating the results of collaboration come together for Art Locatia and Studio. As a UX researcher, I would love to follow up with other artists and fans to ask questions to understand how they used the Studio feature to get their art on the blockchain. I would be keen to know their ideas for Art Locatia and I wonder if there's other exemplars making similar projects for artists.

Other Ideas and Musings

  • I imagine that Art Locatia could be a fun app to use at an art event where we walk around to view art installations, and use the app to see more info and make transactions, like buying a t-shirt at the giftshop at the end of the walk.
  • A way to sponsor art from favourite artists for an event like Burning Man. And buy an NFT after the event. Perhaps camps can use it for pre-playa fundraising and on-playa events.
  • I look back at a scavenger hunt I created for my tech colleagues for a Friday work event, and wonder how this could be used for that scavenger hunt. I think they would have loved the tech of it.
  • And I think the types of artwork could be other than a 3D model, maybe a song or an animation or movie.

But it would be neat to find out and grow my coding skills and contributions, starting with using Art Locatia Studio and make my artwork accessible in Art Locatia.

Cheers and Happy Lunar New Year 🐉,

Haunani Pao

Product Designer 🦄 Full Stack Dev from Auckland, New Zealand.
Seasoned Web2 Product Designer eager to leverage UX skills and community focus and craft user-centric Web3 experiences.

· 18 min read
Josh Howard

In this guide you will learn how to add a search engine to your NFT project. We will be using the nft-searcher package to fetch NFTs from the blockchain and OpenAI to enhance the search results.

Here is an outline of what we will be doing:

  1. Add an NFT searchbar to your third web project
  2. Create a trait filter component to sort through the fetched collections
  3. Add Open Ai results to enhance your search results

This is the final result of what we will be building.

Diagram of how it works

Diagram

Prerequisites:

Step 1: Set up your thirdweb project

We are going to start with the thirdweb next-typescript-starter template

npx thirdweb create --template next-typescript-starter

Install the default packages to your project.

yarn install

Step 2: Install packages

yarn add @thirdweb-dev/react @thirdweb-dev/sdk nextjs-progressbar openai react react-dom

Now that we have all the third web packages up to date, let’s import the nft-searcher package.

yarn add nft-searcher

You can check out the package on npmjs: https://www.npmjs.com/package/nft-searcher. I’ve provided the general configuration setup in the readme.

info

Note: If you are using the nft-searcher-template you may need to uninstall and reinstall the package after updating the third web packages. React, react-dom and the thirdweb react package are all peer dependencies.

Step 3: Update next.config.js

/** @type {import('next').NextConfig} */
const nextConfig = {
reactStrictMode: true,
basePath: "",
webpack5: true,
webpack: config => {
config.resolve.fallback = {
fs: false,
};
return config;
}
};

module.exports = nextConfig;

Step 4: Add SQLlite3 wasm file loader

Under the public folder create a folder named db and add the sql-wasm-595817d88d82727f463bc4b73e0a64cf.wasm file to it. You can download the file from here or in the src file of this package.

Step 5: Create declaration file

Create an nft-searcher.d.ts file under the typings folder of your project and the following declaration.

declare module 'nft-searcher';

Step 6: Create a component

Create a component in your project and import the NFTSearcher component from the nft-searcher package.

import NFTSearcher from "nft-searcher"
import { useState, useEffect, useCallback } from "react";

export default function NFTSearcherPackNOSSR(){
const [fetchedNFTs, setFetchedNFTs] = useState<any[]>([]);
const [loading, setLoading] = useState<boolean>(false);

const handleNFTsFetched = useCallback((nfts: any[]) => {
setLoading(true);
setFetchedNFTs(nfts);
setInterval(() => {
setLoading(false);
}, 1000);
}, [setLoading, setFetchedNFTs]);

return (
<div>
<NFTSearcher
activeNetwork={"ethereum"}
theme={"dark"}
onNFTsFetched={handleNFTsFetched}
/>
</div>
)
}

Next, dynamically import the NFTSearcherPackNOSSR component in your home page.

import dynamic from "next/dynamic";
const NFTSearcherPackNOSSR = dynamic(() => import('../components/NFTSearcher/Searcher'), { ssr: false });

export default function Home() {
return (
<div>
<NFTSearcherPackNOSSR />
</div>
)
}

Props

  • activeNetwork: The active blockchain network. Default is 'ethereum'.
  • limit: The maximum number of NFTs to fetch.
  • start: The starting index for fetching NFTs.
  • where: An array of conditions for fetching NFTs.
  • select: The fields to select from the fetched NFTs.
  • dbURL: The URL of the database to fetch NFTs from.
  • theme: The theme of the search bar. Can be 'dark' or 'light'.
  • onNFTsFetched: A callback function that is called when NFTs are fetched. It receives the fetched NFTs as an argument.
  • style: An object containing CSS styles for various elements of the search bar.
  • classNames: An object containing class names for various elements of the search bar.

Styles and classNames

You can customize the appearance of the search bar by providing CSS styles and class names for various elements. The style prop is an object where the keys are the names of the elements and the values are CSS style objects. The classNames prop is similar, but the values are class names.

Here's an example of how you can use the style and classNames props to customize the appearance of the NFTSearcher component:

import NFTSearcher from 'nft-searcher';

<NFTSearcher
activeNetwork={"ethereum"}
limit={10}
start={0}
where={[]} // for nft-indexer collections only, not used for thirdweb contract fetches
select={"*"} // for nft-indexer collections only, not used for thirdweb contract fetches
dbURL={""} // for nft-indexer collections only, not used for thirdweb contract fetches
theme={"dark"} // or "light"
onNFTsFetched={(nfts) => console.log(nfts)}
style={{
searchContainer: {
backgroundColor: '#f5f5f5',
padding: '10px',
},
searchInput: {
fontSize: '18px',
padding: '10px',
},
searchButton: {
backgroundColor: '#007bff',
color: 'white',
padding: '10px 20px',
},
resultsContainer: {
marginTop: '20px',
},
resultItem: {
borderBottom: '1px solid #ddd',
padding: '10px 0',
},
}}
classNames={{
searchContainer: 'my-search-container',
searchInput: 'my-search-input',
searchButton: 'my-search-button',
resultsContainer: 'my-results-container',
resultItem: 'my-result-item',
}}
/>

In this example, the style prop is used to provide CSS styles for the search container, search input, search button, results container, and result items. The classNames prop is used to provide custom class names for the same elements.

Please note that the actual style and class names that you can use will depend on the implementation of the NFTSearcher component. The keys used in the style and classNames objects (like searchContainer, searchInput, etc.) are just examples and might not correspond to the actual elements in the NFTSearcher component. You'll need to refer to the NFTSearcher documentation or source code to find out the correct keys to use.

Fetching NFTs

When the user types in the search bar, the component fetches NFTs that match the user's input. The fetched NFTs are passed to the onNFTsFetched callback function.

Suggestions are displayed in a dropdown menu below the search bar. The user can click on a suggestion to select it. When a suggestion is selected, the onNFTsFetched callback function is called with the selected NFTs as an argument.

A contract address can also be entered in the search bar. When a contract address is entered, the component fetches all the NFTs from that contract and passes them to the onNFTsFetched callback function.

If a collection does not appear it has not been indexed yet. To request a collection to be indexed, please submit a request at https://indexer.locatia.app. Once the collection is indexed it will also appear in the suggestions dropdown.

If you would like your thirdweb collection added to the directory, please open an issue at https://github.com/Zerobeings/nft-indexer with the collection name and contract address.

Network Support

The component supports multiple blockchain networks. The active network can be set using the activeNetwork prop. The default network is 'ethereum'.

The following networks are supported:

  • Ethereum: "ethereum"
  • Polygon: "polygon"
  • Fantom Opera: "fantom"
  • Avalanche: "avalanche"

Step 7: Add NFTCard component

Under the components folder create a folder named NFTCard and add the following files.

NFTCard.tsx

import styles from './NFTCard.module.css';
import Image from 'next/image';
import { MediaRenderer } from "@thirdweb-dev/react";
import { useEffect, useState } from 'react';

interface Props {
nft: any;
network: string;
onAttributeSelect: (selectedAttribute: string, tokenStart: number) => Promise<void>;
tokenStart: number;
}

interface Attribute {
trait_type: string;
value: string;
}

export default function NFTCard({ nft, network, onAttributeSelect, tokenStart}: Props) {

const handleAttributeClick = (attribute: string) => {
onAttributeSelect(attribute, tokenStart);
};

return (
<>
{nft?.metadata?.name !== "Failed to load NFT metadata" &&
<div className={styles.container}>
<div className={styles.item}>
<h4 className={styles.heading}>{nft.name || nft?.metadata?.name}</h4>
<MediaRenderer src={nft.image || nft?.metadata?.image} alt="image" height="233px" width="233px" />
<table className={styles.table}>
<tbody>
{nft.metadata && nft.metadata.attributes!==undefined ? Object.entries(nft.metadata.attributes).map(([_, attribute]: [string, any], i) => {
const traitType = (attribute as Attribute).trait_type;
const value = (attribute as Attribute).value;
return (
<tr key={i} onClick={() => handleAttributeClick(`"${traitType}" = "${String(value)}"`)}>
<td>{traitType}</td>
<td>{String(value)}</td>
</tr>
);
}
) : nft.attributes && (
Object.entries(nft.attributes).map(([key, value], i) => {
return (
<tr key={i} onClick={() => handleAttributeClick(`"${key}" = "${String(value)}"`)}>
<td>{key}</td>
<td>{String(value)}</td>
</tr>
);
})
)}
</tbody>
</table>
</div>
</div>
}
</>
);
}

NFTCard.module.css

.container {
display: flex;
flex-wrap: wrap;
justify-content: center;
padding: 10px 0;
margin-top: 30px;
}

.heading {
color: #252405;
text-align: center;
font-size: 20px;
margin-top: 10px;
margin-bottom: 5px;
padding: 0;
}

.item {
width: 255px;
padding: 10px;
box-sizing: border-box;
background-color: #ccc;
border-radius: 10px;
margin-right: 10px;
box-shadow: 0px 3px 10px rgb(38, 37, 5, 0.2);
border: 1px solid #252405;
}

.item img {
width: 100%;
margin-bottom: 10px;
margin-top: 10px;
/* margin-left: -8px; */
transition: transform 0.3s ease-in-out;
background-color: #ccc;
}

.item img:hover {
transform: scale(2);
}

.table {
table-layout: fixed;
width: 100%;
border-spacing: 0;
border-color: white;
border-collapse: separate;
}

.table tbody tr {
border-radius: 6px;
box-shadow: 0px 3px 10px rgb(38, 37, 5, 0.2);
margin-bottom: 10px;
}

/* top-left border-radius */
.container tr:first-child td:first-child {
border-top-left-radius: 6px;
}

/* top-right border-radius */
.container tr:first-child td:last-child {
border-top-right-radius: 6px;
}

/* bottom-left border-radius */
.container tr:last-child td:first-child {
border-bottom-left-radius: 6px;
}

/* bottom-right border-radius */
.container tr:last-child td:last-child {
border-bottom-right-radius: 6px;
}

.table td {
vertical-align: top;
word-wrap:break-word;
padding: 7px;
box-sizing: border-box;
font-size: 10px;
cursor: pointer;
color: #252405;
}

.container td:nth-child(1) {
font-weight: bold;
}
.container td {
border: 2px solid #252405;
}
.container tr:hover td {
background: #EC9E72;
color:black;
}

Step 8: Create a trait filter component

Under the components folder create a folder named Filter and add the following files.

Filter.tsx

import React, { useState } from 'react';
import styles from './Filter.module.css'; // Import your CSS file
import {FilterSVG} from './FilterSVG';
import { useEffect } from 'react';

interface Props {
attributes: Attributes;
onAttributeSelect: (attribute: string, startToken: number) => void;
}

interface Attributes {
[key: string]: string[];
}

export default function Filter({ attributes, onAttributeSelect}: Props){
const [showPopup, setShowPopup] = useState(false);
const [startToken, setStartToken] = useState(0);
const [totalNFTs, setTotalNFTs] = useState(10000);

const togglePopup = () => setShowPopup(!showPopup);

const handleSelection = (e:any) => {
const selectedName = e.target.getAttribute('data-attribute-label');
const selectedValue = e.target.value;
const finalSelection = `"${selectedName}" = "${selectedValue}"` !== undefined ? `"${selectedName}" = "${selectedValue}"` : "";
onAttributeSelect(finalSelection, startToken);
};

const handleTokenChange = (e:any) => {
const newStartToken = e.target.value;
setStartToken(newStartToken);
const finalSelection = "";
onAttributeSelect(finalSelection, newStartToken);
};


return (
<div className={styles.popupContainer}>
<button className={styles.togglePopup} onClick={togglePopup}>
<FilterSVG />
</button>
{showPopup && (
<div className={styles.popup}>
<div className={styles.popupItem}>
<label>Token Start</label>
<select
id="tokenStart"
name="tokenStart"
value={startToken}
onChange={handleTokenChange}
>
<option value={0}>{0}</option>
<option value={50}>{50}</option>
{
Array.from({ length: Math.ceil(totalNFTs / 100) }, (_, index) => (
<option key={index} value={(index + 1) * 100}>{(index + 1) * 100}</option>
))
}
</select>
</div>
<div className={styles.popupItem}>
<label>Traits</label>
{Object.entries(attributes).map(([attributeLabel, values], index) => (
<select
key={index}
data-attribute-label={attributeLabel}
onChange={handleSelection}
>
<optgroup label={attributeLabel}>
{Array.isArray(values) && values.map((value, valueIndex) => (
<option key={valueIndex} value={value}>{value}</option>
))}
</optgroup>
</select>
))}
</div>
</div>
)}
</div>
);
};

Filter.module.css

.popupContainer {
position: relative;
display: inline-block;
max-width: 1200px;
justify-content: space-between;
}

.popup {
position: absolute;
left: 50%;
transform: translateX(-15%);
top: 100%;
width: 200px;
margin-top: 10px;
padding: 10px;
border: 1px solid #ddd;
background-color: #e7e8e8;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
z-index: 1000;
display: flex;
flex-direction: column;
border-radius: 15px;
}

.popupItem {
margin-bottom: 10px;
}

.popupItem label {
display: block;
margin-bottom: 5px;
}

.popupItem input, .popupItem select, .popupItem button {
width: 100%;
padding: 8px;
border: 1px solid #ccc;
border-radius: 4px;
box-sizing: border-box;
margin-top: 5px;
}

.togglePopup{
border: none;
padding: 10px;
height: 52px;
width: 52px;
border-radius: 30%;
}

.togglePopup:hover {
cursor: pointer;
box-shadow: 0px 3px 10px rgb(38, 37, 5, 0.2);
border-color: #D1CEBA;
}

@media (max-width: 768px) {
.popupContainer {
margin-left: 0px;
margin-right: 30px;
}
}

FilterSVG.tsx

export const FilterSVG: React.FC = () => {
return (
<div>
<svg
width="24"
height="24"
viewBox="0 0 24 24"
fill="none"
xmlns="http://www.w3.org/2000/svg"
>
<line x1="2" y1="6" x2="22" y2="6" stroke="black" strokeWidth="2"/>
<line x1="4" y1="12" x2="20" y2="12" stroke="black" strokeWidth="2"/>
<line x1="6" y1="18" x2="18" y2="18" stroke="black" strokeWidth="2"/>
</svg>
</div>
);
};

Step 9: Add OpenAI results

Under the components folder create a folder named NFTInfo and add the following files.

NFTInfo.tsx

import React from 'react';
import styles from './NFTInfo.module.css'; // Ensure this path is correct

interface NFTInfoProps {
data: string | { [key: string]: any }; // Accepting either a JSON string or an object
}

const NFTInfo: React.FC<NFTInfoProps> = ({ data }) => {
const jsonData = typeof data === 'string' ? JSON.parse(data) : data;

const formatTitle = (key: string) => {
return key.replace(/_/g, ' ').replace(/\b\w/g, l => l.toUpperCase());
};

const renderData = (obj: { [key: string]: any }) => {
return Object.keys(obj).map((key) => {
const value = obj[key];
if (typeof value === 'object' && value !== null) {
return (
<div key={key} className={styles.item}>
<strong>{formatTitle(key)}:</strong>
<div style={{ marginLeft: '20px' }}>{renderData(value)}</div>
</div>
);
} else {
return (
<div key={key} className={styles.item}>
<strong>{formatTitle(key)}:</strong> {value}
</div>
);
}
});
};

return <div className={styles.container}>{renderData(jsonData)}</div>;
};

export default NFTInfo;

NFTInfo.module.css

.container {
border: 1px solid #ddd;
padding: 15px;
margin-bottom: 10px;
border-radius: 8px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
max-width: 1400px;
}

.item {
margin-bottom: 10px;
}

Step 10: Add NFTSearcher component

Under the components folder create a folder named NFTSearcher and add the following files.

Searchbar.tsx

import NFTSearcher from "nft-searcher"
import { useState, useEffect, useCallback } from "react";
import styles from "./Searchbar.module.css";
import NFTCard from "../NFTCard/NFTCard";
import Filter from "../Filter/Filter";
import Image from "next/image";
import { useChain, ConnectWallet } from "@thirdweb-dev/react";
import NFTInfo from "../NFTInfo/NFTInfo";

interface Attributes {
[key: string]: string[];
}

export default function NFTSearcherPackNOSSR(){
const [fetchedNFTs, setFetchedNFTs] = useState<any[]>([]);
const [loading, setLoading] = useState<boolean>(false);
const [darkMode, setDarkMode] = useState<boolean>(false);
const [attributes, setAttributes] = useState<Attributes>({});
const [allNFTs, setAllNFTs] = useState<any[]>([]);
const chain = useChain();
const [network, setNetwork] = useState<string>("");
const [aiAnalysis, setAiAnalysis] = useState(null);

// set network and feed into searcher tool
useEffect(() => {
if (chain && chain.chain.toLowerCase() === "eth") {
setNetwork("ethereum");
} else if (chain && chain.chain.toLowerCase() === "polygon") {
setNetwork("polygon");
} else if (chain && chain.chain.toLowerCase() === "avax") {
setNetwork("avalanche");
} else if (chain && chain.chain.toLowerCase() === "ftm") {
setNetwork("fantom");
}
}, [chain]);

const extractAttributes = useCallback((nfts: any[]) => {
const attributeMap: Attributes = {};
nfts.forEach(nft => {
if (nft.metadata && nft.metadata.attributes) {
nft.metadata.attributes.forEach((attribute: any) => {
if (!attributeMap[attribute.trait_type]) {
attributeMap[attribute.trait_type] = [];
}

if (!attributeMap[attribute.trait_type].includes(attribute.value)) {
attributeMap[attribute.trait_type].push(attribute.value);
}
});
} else if (nft.attributes) {
Object.entries(nft.attributes || {}).forEach(([key, value]) => {
if (!attributeMap[key]) {
attributeMap[key] = [];
}

if (typeof value === 'string' && !attributeMap[key].includes(String(value))) {
attributeMap[key].push(value);
}
});
}
});

return attributeMap;
}, []);

const handleNFTsFetched = useCallback((nfts: any[]) => {
setLoading(true);
setFetchedNFTs(nfts);
setAllNFTs(nfts);
const attributes = extractAttributes(nfts);
setAttributes(attributes);
setInterval(() => {
setLoading(false);
}, 1000);
}, [setLoading, setFetchedNFTs, setAllNFTs, setAttributes, extractAttributes]);

console.log("fetchedNFTs", fetchedNFTs);

// search params
const [limit, setLimit] = useState<number>(100);
const [start, setStart] = useState<number>(0);
const [where, setWhere] = useState<any[]>([]); //only required for nft-indexer searches, does not apply thirdweb contract searches
const [select, setSelect] = useState<string>("*"); //only required for nft-indexer searches, does not apply thirdweb contract searches

const handleAttributeFromCard = async (selectedAttribute:string, tokenStart:number) => {
setStart(tokenStart);
const updateNFTs = fetchedNFTs.filter((nft) => {
if (nft.metadata && nft.metadata.attributes) {
return nft.metadata.attributes.some((attribute: any) => {
return selectedAttribute.includes(attribute.trait_type) && selectedAttribute.includes(attribute.value);
});
} else if (nft.attributes) {
const whereNew = selectedAttribute !== "" ? [selectedAttribute] as any[] : [] as any[];
setWhere(whereNew);
return Object.entries(nft.attributes || {}).some(([key, value]) => {
return selectedAttribute.includes(key) && selectedAttribute.includes(String(value));
});
}
});
setFetchedNFTs(updateNFTs);
}

const handleClearSearch = () => {
const clear = "";
handleAttributeFromCard(clear, 0);
setFetchedNFTs(allNFTs);
}


// fetch AI analysis
useEffect(() => {
const fetchAIAnalysis = async () => {
if (fetchedNFTs && fetchedNFTs.length > 0) {
const tokenName = fetchedNFTs[1]?.metadata?.name ? fetchedNFTs[1].metadata.name : fetchedNFTs[1].name;
const tokenDescription = fetchedNFTs[1]?.metadata?.description ? fetchedNFTs[1].metadata.description : fetchedNFTs[1].description;
try {
const response = await fetch('/api/openai', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({tokenName, tokenDescription}),
});

if (!response.ok) {
throw new Error('Network response was not ok');
}

const data = await response.json();
setAiAnalysis(data.data);
} catch (error) {
console.error('There has been a problem with your fetch operation:', error);
}
}
}
fetchAIAnalysis();
}, [fetchedNFTs]);


return (
<>
<h1 className={styles.mainHeading}>A searchbar for
<a href="https://thirdweb.com"
target="_blank"
rel="noopener noreferrer"
className={styles.link}
> thirdweb </a>
projects & more
</h1>
<h3 className={styles.heading}>yarn add nft-searcher</h3>
<div className={styles.container}>
<div className={styles.mixtape}>
<button className={styles.button} onClick={() => setDarkMode(!darkMode)}>Toggle Searchbar Theme</button>
<NFTSearcher
activeNetwork={network}
theme={darkMode ? "dark" : "light"} // "light" or "dark"
onNFTsFetched={handleNFTsFetched}
limit={limit}
start={start}
where={where}
select={select}
/>
</div>
<div className={styles.console}>
<h4>NFT Console</h4>
{fetchedNFTs.length === 0 ? (
<p>No NFTs fetched yet...</p>
) : (
<>
{!loading ? fetchedNFTs.map((nft, index) => (
<div key={index}>
<pre>{JSON.stringify(nft, null, 2)}</pre>
</div>
))
: <div style={{ marginLeft: "auto", marginRight: "auto", }}>Loading...</div>}
</>
)}
</div>
</div>
<div className={styles.aiconsole}>
{aiAnalysis ? (
<div>
<h3>OpenAI generated Collection Insights</h3>
<NFTInfo data={aiAnalysis} />
</div>
)
:
<div>
<h3>OpenAI generated Collection Insights</h3>
<p>Search a collection to generate insights...</p>
</div>
}
</div>
<div className={styles.selectorContainer}>
<Filter attributes={attributes} onAttributeSelect={handleAttributeFromCard}></Filter>
<p className={styles.instructions}>&larr; filter by token and trait or reset trait selection &rarr;</p>
<div className={styles.selection}>
<button className={styles.resetBtn} onClick={handleClearSearch}><Image src="/images/reset.png" width={22} height={22} alt="reset"/></button>
</div>
</div>
<div className={styles.gridContainer}>
<div className={styles.grid}>
{fetchedNFTs.length === 0 ? (
<p>No NFTs fetched yet...</p>
) : fetchedNFTs && fetchedNFTs.length > 0 ? (
fetchedNFTs.map((nft, i) => (
<NFTCard
nft={nft}
key={i}
network={network}
tokenStart={start}
onAttributeSelect={handleAttributeFromCard}
></NFTCard>
))
) : ( <div style={{ marginLeft: "auto", marginRight: "auto", }}>Loading...</div>)}
</div>
</div>
</>


)
}

Searchbar.module.css

.heading {
margin-left: auto;
margin-right: auto;
text-align: center;
margin-bottom: 50px;
background-color: #333;
width: 300px;
padding: 10px;
border-radius: 15px;
}

.mainHeading {
margin-left: auto;
margin-right: auto;
text-align: center;
margin-bottom: 50px;
width: 100%;
padding: 10px;
border-radius: 15px;
}

.container {
display: flex;
position: relative;
width: 100%;
}

.button{
background-color: #333;
color: lime;
font-family: monospace;
padding: 10px;
border-radius: 15px;
width: 300px;
margin-bottom: 30px;
cursor: pointer;
}

.mixtape {
flex:1;
min-height: 300px;
text-align: center;
}

.console {
background-color: #333;
color: lime;
font-family: monospace;
padding: 10px;
overflow: auto;
max-height: 300px;
border-radius: 15px;
width: 800px;
flex: 1;
margin-right: 55px;
margin-left: 30px;
}

.aiconsole {
background-color: #333;
color: lime;
font-family: monospace;
padding: 10px;
overflow: auto;
height: 300px;
max-height: 300px;
border-radius: 15px;
width: 1300px;
flex: 1;
margin-right: auto;
margin-left: auto;
margin-top: 10px;
}

.link:hover {
text-decoration: underline;
}

.grid {
display: flex;
align-items: center;
justify-content: center;
flex-wrap: wrap;
max-width: 1200px;
margin-top: 30px;
}

.gridContainer {
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
}


.selectorContainer {
display: flex;
justify-content: space-between;
align-items: center;
max-width: 1080px;
max-height: 83.5px;
width: 100%;
margin-left: auto;
margin-right: auto;
margin-top: 75px !important;
padding: 10px;
background-color: #333;
border-radius: 15px;
}

.selection {
display: flex;
flex-direction: column;
align-items: center;
}

.resetBtn {
border: none;
padding: 10px;
height: 52px;
width: 52px;
border-radius: 30%;
}

.resetBtn:hover {
cursor: pointer;
box-shadow: 0px 3px 10px rgb(38, 37, 5, 0.2);
border-color: #D1CEBA;
}

.instructions{
font-size: 20px;
}

@media (max-width: 768px) {
.container {
flex-direction: column;
align-items: center;
width: 100%;
}

.instructions{
font-size: 12px;
margin-right: 25px;
text-align: center;
}

.console {
width: 350px;
margin-top: -110px;
margin-right: 0px;
margin-left: 0px;
}
}

Step 11: Add OpenAI API

Under the pages folder create a folder named api and add the following files.

openai.ts

import OpenAI from 'openai';
import type { NextApiRequest, NextApiResponse } from 'next';

export default async function handler(req: NextApiRequest, res: NextApiResponse) {
if (req.method === 'POST') {
const { tokenName, tokenDescription } = req.body;

try {
const openai = new OpenAI({
apiKey: process.env.OPENAI_KEY,
});

const response = await openai.chat.completions.create({
model: "gpt-3.5-turbo-1106",
response_format: { "type": "json_object" },
messages: [
{
role: "system",
content: "You are a knowledgeable assistant about NFT collections and provide output in JSON format."
}, {
role: "user",
content: `Provide a summary about the NFT collection with the token named ${tokenName} which is described as ${tokenDescription} and provide a overview of the collection`
}],
});

res.status(200).json({ data: response.choices[0].message.content});
} catch (error) {
if (error instanceof OpenAI.APIError) {
console.error(error.status); // e.g. 401
console.error(error.message); // e.g. The authentication token you passed was invalid...
console.error(error.code); // e.g. 'invalid_api_key'
console.error(error.type); // e.g. 'invalid_request_error'
} else {
// Non-API error
console.log(error);
}
}
} else {
res.setHeader('Allow', 'POST');
res.status(405).end('Method Not Allowed');
}
}

Step 12: Add a home page

Under the pages folder create a file named index.tsx and add the following code.

import { ConnectWallet, useAddress } from "@thirdweb-dev/react";
import styles from "../styles/Home.module.css";
import Image from "next/image";
import { NextPage } from "next";
import {PoweredBy} from "../components/PoweredBy/PoweredBy";
import {GitHub} from "../components/PoweredBy/GitHub";
import {Request} from "../components/PoweredBy/Request";
import Link from "next/link";
import { useEffect, useState } from "react";
import { useRouter } from 'next/router';
import dynamic from 'next/dynamic';
const NFTSearcherPackNOSSR = dynamic(() => import('../components/NFTSearcher/Searchbar'), { ssr: false });

const Home: NextPage = () => {

return (
<main>
<div className={styles.container}>
<NFTSearcherPackNOSSR/>
</div>
<div className={styles.headerBg}>
<div className={styles.wallet}>
<ConnectWallet />
</div>
</div>
</main>
);
};

export default Home;

Step 13: Add a styles file to Home.module.css

Under the styles folder create a file named Home.module.css and add the following code.

.container {
width: 100%;
max-width: 1440px;
padding: 1rem;
margin-left: auto;
margin-right: auto;
margin-top: 150px;
}

.title {
margin-top: 150px;
line-height: 1.15;
font-size: 3rem;
text-align: center;

}


.headerBg{
background-color: #333;
font-family: monospace;
padding: 10px;
width: 100%;
height: 83px;
top:0;
position: fixed;
}

.wallet{
float: right;
}

@media (max-width: 768px) {

.container {
margin-left: auto;
margin-right: auto;
margin-top: 50px;
}

.title {
margin-top: 180px;
line-height: 1;
font-size: 1.5rem;
text-align: center;
}

.headerBg{
height: 70px;
}

}

Enjoy your new NFT searchbar!

· One min read
Joshua Howard

Welcome to Locatia! This is a decentralized augmented reality platform for geolocated artwork and more. It started as a simple NFT collection and has grown into a full fledged platform. I have been working on this project for a while now and I am excited to share it with you. I am looking for feedback. I am also looking for artists to create artwork for the platform. If you are interested in collaborating or creating artwork for the platform please reach out to me on discord or twitter.

I am also sharing all the tools and collections I've developed on the journey to create this platform. I hope you find them useful. I am looking for feedback to help me improve the tools and collections.

· One min read
Josh Howard

I have been working working towards creating a decentralized augmented reality platform for geolocated artwork and more. I am excited to announce that we have a beta version of the platform. We are calling it Locatia. It is a decentralized augmented reality platform for geolocated artwork and more. It is built on the ethereum blockchain and IPFS. It is a progressive web app that can be accessed on any device with a web browser. It is a work in progress and we are looking for feedback and collaborators.