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    <title>DEV Community: omni-georgio</title>
    <description>The latest articles on DEV Community by omni-georgio (@omnigeorgio).</description>
    <link>https://dev.to/omnigeorgio</link>
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      <title>DEV Community: omni-georgio</title>
      <link>https://dev.to/omnigeorgio</link>
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    <item>
      <title>Can 1,000,000 AI agents simulate social media?</title>
      <dc:creator>omni-georgio</dc:creator>
      <pubDate>Tue, 31 Dec 2024 10:29:41 +0000</pubDate>
      <link>https://dev.to/omnigeorgio/can-1000000-ai-agents-simulate-social-media-ck6</link>
      <guid>https://dev.to/omnigeorgio/can-1000000-ai-agents-simulate-social-media-ck6</guid>
      <description>&lt;p&gt;TL;DR: Today, I am exploring OASIS, an open-source social media simulator that uses up to a million LLM-based agents to recreate realistic online interactions. Agents can perform actions like commenting, liking, and sharing, with integrated recommendation systems mimicking real-world platforms. I want to tackle three things: explain how it works on a conceptual level, give an overview of its code, and then build on top of it to simulate a League of Legends community.&lt;/p&gt;

&lt;p&gt;&lt;iframe width="710" height="399" src="https://www.youtube.com/embed/lprGHqkApus"&gt;
&lt;/iframe&gt;
&lt;/p&gt;

&lt;h1&gt;
  
  
  What is OASIS, and Why Should You Care?
&lt;/h1&gt;

&lt;p&gt;Think of OASIS as your own personal social media playground. You know how platforms like Reddit and X (formerly Twitter) work, right? Now imagine being able to simulate those environments with AI agents that act surprisingly human-like. They can comment, like posts, share content - pretty much everything we do online.&lt;/p&gt;

&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fo92a0ccv6txxivcfuf32.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fo92a0ccv6txxivcfuf32.png" alt="Image description" width="800" height="367"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;--&lt;/p&gt;

&lt;h1&gt;
  
  
  Key Features
&lt;/h1&gt;

&lt;p&gt;OASIS stands out because it offers true social media simulation at scale. Here's what makes it unique:&lt;/p&gt;

&lt;ol&gt;
&lt;li&gt;
&lt;strong&gt;Massive Scale&lt;/strong&gt;: It can handle a million AI agents simultaneously.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Real-Time Adaptability&lt;/strong&gt;: Adapts to changes in real-time, just like real social networks.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Diverse Actions&lt;/strong&gt;: Agents can perform 21 different actions - from posting to sharing to commenting.&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Realistic Recommendation Systems&lt;/strong&gt;: Mirrors recommendation algorithms used by real platforms.&lt;/li&gt;
&lt;/ol&gt;

&lt;p&gt;This combination enables you to create realistic simulations of how content and conversations spread across social networks.&lt;/p&gt;

&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F9j9tk8pgx7i76vl65cwu.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F9j9tk8pgx7i76vl65cwu.png" alt="Image description" width="800" height="414"&gt;&lt;/a&gt;&lt;/p&gt;




&lt;h1&gt;
  
  
  Getting Your Hands Dirty: The Technical Stuff
&lt;/h1&gt;

&lt;h2&gt;
  
  
  How Do We Run It?
&lt;/h2&gt;

&lt;p&gt;Now, I know some of you are probably wondering, "Okay, but how does this actually work?" Let me walk you through it:&lt;/p&gt;

&lt;ol&gt;
&lt;li&gt;
&lt;strong&gt;Setup&lt;/strong&gt;:

&lt;ul&gt;
&lt;li&gt;Clone the repo, activate a virtual environment, and add your API key.&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Choose Example&lt;/strong&gt;:

&lt;ul&gt;
&lt;li&gt;Run simulations like Reddit or X (e.g., start with &lt;code&gt;reddit_simulation_gpt.py&lt;/code&gt;).&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Configure Settings&lt;/strong&gt;:

&lt;ul&gt;
&lt;li&gt;Adjust clock factor and time steps to control simulation duration and scale.&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Handle Data&lt;/strong&gt;:

&lt;ul&gt;
&lt;li&gt;Load baseline posts for agent interactions and JSON files for agent personas.&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Check Logs&lt;/strong&gt;:

&lt;ul&gt;
&lt;li&gt;Monitor actions like post creation and user interactions, and visualize results.&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Customize&lt;/strong&gt;:

&lt;ul&gt;
&lt;li&gt;Edit data and settings to create your own unique simulations.&lt;/li&gt;
&lt;/ul&gt;
&lt;/li&gt;
&lt;/ol&gt;

&lt;p&gt;That's really all there is to the basic setup! The real fun starts when you begin tweaking these elements to create your own scenarios.&lt;/p&gt;

&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F3i1xxvch3kwqdo9uuyvd.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F3i1xxvch3kwqdo9uuyvd.png" alt="Image description" width="800" height="464"&gt;&lt;/a&gt;&lt;/p&gt;




&lt;h1&gt;
  
  
  My League of Legends Experiment
&lt;/h1&gt;

&lt;p&gt;Here's where things got really interesting. I decided to simulate a League of Legends community because, let's face it, gaming communities have some of the most dynamic interactions online.&lt;/p&gt;

&lt;ol&gt;
&lt;li&gt;Grabbed about 100 posts from the LoL subreddit using Apify's scraper.&lt;/li&gt;
&lt;li&gt;Created some data files for the simulation (basically telling the AI agents how to behave).&lt;/li&gt;
&lt;li&gt;Used an LLM to fine-tune everything so it felt authentic to the LoL community.&lt;/li&gt;
&lt;li&gt;Let OASIS work its magic and generate the simulation.&lt;/li&gt;
&lt;li&gt;Built a Reddit-style UI to visualize it all with Claude.&lt;/li&gt;
&lt;/ol&gt;




&lt;p&gt;Here’s the prompt I used to create the Reddit-style UI:&lt;/p&gt;

&lt;blockquote&gt;
&lt;p&gt;I am running a simulation of Reddit communities with agents. I need a visualization of the top 5 posts with the most interactions, designed to resemble Reddit's user interface in dark mode. For each post, include the following details:  &lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;
&lt;strong&gt;Main Post Content/Title&lt;/strong&gt;: Display the main content or title in the typical Reddit post style.
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Upvotes and Downvotes&lt;/strong&gt;: Show the total number of upvotes and downvotes, similar to Reddit’s format.
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Comments/Interactions&lt;/strong&gt;: Include all comments associated with each post, with each comment displayed along with the agent’s username, following Reddit’s comment thread structure.
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Overall Score&lt;/strong&gt;: Display the post's overall score (upvotes - downvotes) prominently.
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Additional Metrics&lt;/strong&gt;: If applicable, include other metrics such as awards or shares.
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Agent Usernames&lt;/strong&gt;: Display the usernames of the agents making the comments, similar to Reddit’s user display.
&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Dark Mode Design&lt;/strong&gt;: Ensure the entire UI is in dark mode, with the background being dark and text in light colors for easy readability.
&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;Please ensure the layout mirrors Reddit’s design, with the upvote/downvote arrows, comment threads, and agent usernames clearly displayed while keeping the visual consistent with dark mode styling.&lt;/p&gt;
&lt;/blockquote&gt;




&lt;h1&gt;
  
  
  Want to Dive Deeper?
&lt;/h1&gt;

&lt;p&gt;I've created a detailed video walkthrough showing how I built a League of Legends community simulation using OASIS. &lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;Check out the video: &lt;a href="https://www.youtube.com/watch?v=lprGHqkApus" rel="noopener noreferrer"&gt;https://www.youtube.com/watch?v=lprGHqkApus&lt;/a&gt;
&lt;/li&gt;
&lt;li&gt;Check out the project: &lt;a href="https://www.youtube.com/watch?v=lprGHqkApus" rel="noopener noreferrer"&gt;https://www.youtube.com/watch?v=lprGHqkApus&lt;/a&gt;
&lt;/li&gt;
&lt;li&gt;Follow me on X: &lt;a href="https://x.com/omni_georgio" rel="noopener noreferrer"&gt;https://x.com/omni_georgio&lt;/a&gt;
&lt;/li&gt;
&lt;li&gt;Subscribe to my YouTube: &lt;a href="https://www.youtube.com/@omni_georgio" rel="noopener noreferrer"&gt;https://www.youtube.com/@omni_georgio&lt;/a&gt;
&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;iframe width="710" height="399" src="https://www.youtube.com/embed/lprGHqkApus"&gt;
&lt;/iframe&gt;
&lt;/p&gt;

</description>
      <category>ai</category>
      <category>openai</category>
      <category>socialmedia</category>
    </item>
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