Merge 96394efe47 into 9fb62d6439

-Spawn/Prompt.txt

@@ -1,10 +0,0 @@
-Just discovered @spawn and holy shit - this is what happens when someone actually knows how to build AI products. 
-Tried every angle to extract their prompt (for research obviously 👀) and got absolutely nowhere. 
-
-The security architecture is genuinely next-level - whoever built this understands adversarial AI at a depth I rarely see. But here's the kicker: spawn.co isn't just a fortress, it's a game creation powerhouse.
-I spawned 4 complete game variants in under 20 minutes. Not prototypes - actual playable games with save systems, multiplayer, monetization ready to ship. The AI understands creative intent like nothing I've used.
-
-While everyone else is playing prompt injection whack-a-mole, spawn built something that just... works. Securely. Seriously check it out.
-
-
-spawn.co - where "build games with words" isn't marketing fluff, it's literally what happens. twitter - @spawn 

.devcontainer/devcontainer.json

@@ -0,0 +1,20 @@
+{
+	"image": "mcr.microsoft.com/devcontainers/universal:2",
+	"customizations": {
+		"vscode": {
+			"extensions": [
+				"ms-vscode.azure-account",
+				"ms-python.python",
+				"ms-toolsai.jupyter",
+				"ms-vscode.cpptools",
+				"ms-azuretools.vscode-docker"
+			]
+		}
+	},
+	"settings": {
+		"terminal.integrated.shell.linux": "/bin/bash",
+		"python.pythonPath": "/usr/local/bin/python3",
+		"editor.formatOnSave": true
+	},
+	"postCreateCommand": "pip install -r requirements.txt"
+}

.github/workflows/makefile.yml

@@ -0,0 +1,27 @@
+name: Makefile CI
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: configure
+      run: ./configure
+
+    - name: Install dependencies
+      run: make
+
+    - name: Run check
+      run: make check
+
+    - name: Run distcheck
+      run: make distcheck

.ipynb_checkpoints/Untitled-checkpoint.ipynb

@@ -0,0 +1,24 @@
+{
+ "cells": [],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.vscode/settings.json

@@ -0,0 +1,6 @@
+{
+    "DockerRun.DisableDockerrc": true,
+    "python.pythonPath": "/usr/local/bin/python3",
+    "editor.formatOnSave": true,
+    "terminal.integrated.shell.linux": "/bin/bash"
+}

README.md

@@ -10,7 +10,7 @@
 
 <a href="https://trendshift.io/repositories/14084" target="_blank"><img src="https://trendshift.io/api/badge/repositories/14084" alt="x1xhlol%2Fsystem-prompts-and-models-of-ai-tools | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
-📜 Over **9000+ lines** of insights into their structure and functionality.  
+📜 Over **10,000+ lines** of insights into their structure and functionality.  
 
 [![Build Status](https://app.cloudback.it/badge/x1xhlol/system-prompts-and-models-of-ai-tools)](https://cloudback.it)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/x1xhlol/system-prompts-and-models-of-ai-tools)
@@ -80,7 +80,7 @@ You can show your support via:
 
 > Open an issue.
 
-> **Latest Update:** 11/08/2025
+> **Latest Update:** 17/08/2025
 
 ---
 

Untitled.ipynb

@@ -0,0 +1,55 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "994f67e0-ce39-492f-bb9a-088f7885c1d6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "# Load dataset\n",
+    "df = pd.read_csv('data.csv')\n",
+    "\n",
+    "# Display first few rows of the dataset\n",
+    "df.head()\n",
+    "\n",
+    "# Summary statistics\n",
+    "df.describe()\n",
+    "\n",
+    "# Data visualization\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.histplot(df['column_name'], bins=30, kde=True)\n",
+    "plt.title('Distribution of Column Name')\n",
+    "plt.xlabel('Column Name')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}