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Opens the source database (`db/AmItheAsshole.sqlite`)\n2. Creates a new target database (`db/Top100AmItheAsshole.sqlite`)\n3. Extracts the top 100 posts from the source database based on score\n4. Extracts all comments associated with those posts\n5. Preserves all original data including IDs, timestamps, and relationships\n\n## Database Schema\n\nThe script maintains the original schema structure:\n\n### Submission Table\n```sql\nCREATE TABLE IF NOT EXISTS \"submission\" (\n \"id\" INTEGER NOT NULL PRIMARY KEY,\n \"submission_id\" VARCHAR(255) NOT NULL,\n \"title\" TEXT NOT NULL,\n \"selftext\" TEXT NOT NULL,\n \"created_utc\" DATE NOT NULL,\n \"permalink\" TEXT NOT NULL,\n \"score\" INTEGER NOT NULL\n);\nCREATE UNIQUE INDEX \"submission_submission_id\" ON \"submission\" (\"submission_id\");\n```\n\n### Comment Table\n```sql\nCREATE TABLE IF NOT EXISTS \"comment\" (\n \"id\" INTEGER NOT NULL PRIMARY KEY,\n \"submission_id\" INTEGER NOT NULL,\n \"message\" TEXT NOT NULL,\n \"comment_id\" VARCHAR(255) NOT NULL,\n \"parent_id\" VARCHAR(255) NOT NULL,\n \"created_utc\" DATE NOT NULL,\n \"score\" INTEGER NOT NULL,\n FOREIGN KEY (\"submission_id\") REFERENCES \"submission\" (\"id\")\n);\nCREATE INDEX \"comment_submission_id\" ON \"comment\" (\"submission_id\");\nCREATE UNIQUE INDEX \"comment_comment_id\" ON \"comment\" 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\"$schema\": \"https://raw.githubusercontent.com/denoland/deno/348900b8b79f4a434cab4c74b3bc8d4d2fa8ee74/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": false,\n \"types\": [\n \"https://www.val.town/types/valtown.d.ts\"\n ],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"dom.asynciterable\",\n \"deno.ns\",\n \"deno.unstable\"\n ]\n },\n \"lint\": {\n \"files\": {\n \"include\": [\n \"deno:/https/esm.town/**/*\"\n ]\n },\n \"rules\": {\n \"exclude\": [\n \"no-explicit-any\"\n ]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n }\n}","label",[154],"c709d896-67f2-11f0-8ec1-0224a6c84d84","01983875-e8ca-7735-b93b-e26da749ec93",16,["D",1753295286718],"# Am I The Asshole? Guessing Game\n\nA web-based guessing game built with React and Hono where users try to guess what percentage of Reddit users thought the poster was the asshole in posts from the r/AmITheAsshole subreddit.\n\n## Game Description\n\nIn this game, players are presented with a post from the \"Am I The Asshole?\" subreddit, where people share situations and ask if they were in the wrong. Players use a slider to guess what percentage of Reddit users voted that the original poster was the asshole. After submitting their guess, they see how close they were to the actual percentage.\n\n## Features\n\n- Beautiful, Reddit-inspired UI\n- Interactive slider for making guesses\n- Feedback on how close your guess was to the actual percentage\n- Responsive design that works on mobile and desktop\n\n## Technical Structure\n\n- **Frontend**: React with TypeScript, modern CSS\n- **Backend**: Hono (lightweight web framework)\n- **Data**: Currently uses static data, with plans to connect to SQL later\n\n## Project Structure\n\n- `/backend/index.ts` - The main server entry point\n- `/backend/data/posts.ts` - Static AITA post data\n- `/frontend/components/AITAGame.tsx` - The main game component\n- `/frontend/components/App.tsx` - The root React component\n- `/frontend/style.css` - Styles for the application\n\n## Future Enhancements\n\n- Connect to a SQL database for storing and retrieving posts\n- Add multiple posts with the ability to cycle through them\n- Add user accounts to track scores\n- 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python3\n\nimport os\nimport sqlite3\nimport sys\nfrom pathlib import Path\n\n\"\"\"\nThis script extracts the top 100 most popular posts (by score) and all their comments\nfrom AmItheAsshole.sqlite database to a new SQLite database file.\n\"\"\"\n\nSOURCE_DB_PATH = \"../db/AmItheAsshole.sqlite\"\nTARGET_DB_PATH = \"../db/top100.sqlite\"\n\n\ndef main():\n print(f\"Extracting top 100 posts from {SOURCE_DB_PATH} to {TARGET_DB_PATH}...\")\n\n # Check if source file exists before opening\n source_path = Path(SOURCE_DB_PATH)\n if not source_path.exists():\n print(f\"Error: Source database file not found: {SOURCE_DB_PATH}. Please ensure the file exists.\")\n sys.exit(1)\n elif not source_path.is_file():\n print(f\"Error: Source database path exists but is not a file: {SOURCE_DB_PATH}\")\n sys.exit(1)\n\n # Create directory for target database if needed\n target_dir = os.path.dirname(TARGET_DB_PATH)\n os.makedirs(target_dir, exist_ok=True)\n print(f\"Ensured directory {target_dir} exists.\")\n\n # Remove target file if it exists\n if os.path.exists(TARGET_DB_PATH):\n os.remove(TARGET_DB_PATH)\n print(\"Removed existing target database.\")\n\n try:\n # Open source database\n print(\"Opening source database...\")\n source_conn = sqlite3.connect(SOURCE_DB_PATH)\n source_conn.row_factory = sqlite3.Row # Use Row to access columns by name\n source_cursor = source_conn.cursor()\n print(\"Source database opened successfully.\")\n\n # Create target database\n print(\"Creating target database...\")\n target_conn = sqlite3.connect(TARGET_DB_PATH)\n target_conn.row_factory = sqlite3.Row\n target_cursor = target_conn.cursor()\n print(\"Target database created successfully.\")\n\n # Create tables in target database\n target_cursor.executescript(\"\"\"\n CREATE TABLE IF NOT EXISTS \"submission\" (\n \"id\" INTEGER NOT NULL PRIMARY KEY,\n \"submission_id\" VARCHAR(255) NOT NULL,\n \"title\" TEXT NOT NULL,\n \"selftext\" TEXT NOT NULL,\n \"created_utc\" DATE NOT NULL,\n \"permalink\" TEXT NOT NULL,\n \"score\" INTEGER NOT NULL\n );\n CREATE UNIQUE INDEX \"submission_submission_id\" ON \"submission\" (\"submission_id\");\n\n CREATE TABLE IF NOT EXISTS \"comment\" (\n \"id\" INTEGER NOT NULL PRIMARY KEY,\n \"submission_id\" INTEGER NOT NULL,\n \"message\" TEXT NOT NULL,\n \"comment_id\" VARCHAR(255) NOT NULL,\n \"parent_id\" VARCHAR(255) NOT NULL,\n \"created_utc\" DATE NOT NULL,\n \"score\" INTEGER NOT NULL,\n FOREIGN KEY (\"submission_id\") REFERENCES \"submission\" (\"id\")\n );\n CREATE INDEX \"comment_submission_id\" ON \"comment\" (\"submission_id\");\n CREATE UNIQUE INDEX \"comment_comment_id\" ON \"comment\" (\"comment_id\");\n \"\"\")\n print(\"Target database tables created.\")\n\n # Begin transaction for better performance and data integrity\n target_conn.execute('BEGIN TRANSACTION')\n\n # Get top 100 submissions by score\n source_cursor.execute(\"\"\"\n SELECT id, submission_id, title, selftext, created_utc, permalink, score \n FROM submission \n ORDER BY score DESC \n LIMIT 100\n \"\"\")\n top_submissions = source_cursor.fetchall()\n print(f\"Found {len(top_submissions)} top submissions.\")\n\n # Insert submissions into target database\n insert_submission_sql = \"\"\"\n INSERT INTO submission (id, submission_id, title, selftext, created_utc, permalink, score) \n VALUES (?, ?, ?, ?, ?, ?, ?)\n \"\"\"\n\n # Keep track of submission_id values (not the id field) for comment lookup\n submission_id_list = []\n for submission in top_submissions:\n # Convert from sqlite3.Row to tuple\n target_cursor.execute(\n insert_submission_sql, \n (\n submission['id'],\n submission['submission_id'],\n submission['title'],\n submission['selftext'],\n submission['created_utc'],\n submission['permalink'],\n submission['score']\n )\n )\n # Store the actual submission_id (Reddit ID) for comment lookup\n submission_id_list.append(submission['submission_id'])\n print(\"Inserted submissions into target database.\")\n\n # Get and insert comments for each submission\n total_comments = 0\n\n # Updated query to use submission_id instead of id\n get_comments_sql = \"\"\"\n SELECT c.id, c.submission_id, c.message, c.comment_id, c.parent_id, c.created_utc, c.score \n FROM comment c\n WHERE c.submission_id = ?\n \"\"\"\n\n insert_comment_sql = \"\"\"\n INSERT INTO comment (id, submission_id, message, comment_id, parent_id, created_utc, score) \n VALUES (?, ?, ?, ?, ?, ?, ?)\n \"\"\"\n\n for i, submission in enumerate(top_submissions):\n # Use the submission_id field (Reddit ID) to find comments\n reddit_submission_id = submission['submission_id']\n source_cursor.execute(get_comments_sql, (reddit_submission_id,))\n comments = source_cursor.fetchall()\n\n for comment in comments:\n target_cursor.execute(\n insert_comment_sql,\n (\n comment['id'],\n comment['submission_id'],\n comment['message'],\n comment['comment_id'],\n comment['parent_id'],\n comment['created_utc'],\n comment['score']\n )\n )\n\n total_comments += len(comments)\n print(f\"Processed {len(comments)} comments for submission '{reddit_submission_id}' (score: {submission['score']}).\")\n\n print(f\"Total comments processed: {total_comments}\")\n\n # Commit transaction\n target_conn.execute('COMMIT')\n print('Database transaction committed successfully.')\n\n # Close connections\n source_conn.close()\n target_conn.close()\n\n print(\"\\nExtraction complete!\")\n print(f\"Original database: {SOURCE_DB_PATH}\")\n print(f\"New database with top 100 posts: {TARGET_DB_PATH}\")\n print(f\"Total posts extracted: {len(top_submissions)}\")\n print(f\"Total comments extracted: {total_comments}\")\n\n except sqlite3.Error as e:\n print(f\"SQLite error: {e}\")\n try:\n # Try to rollback transaction if possible\n target_conn.execute('ROLLBACK')\n print('Transaction rolled back due to error.')\n except Exception as rollback_error:\n print(f\"Error during rollback: {rollback_error}\")\n sys.exit(1)\n except Exception as e:\n print(f\"Error during extraction: {e}\")\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()",[],[186,351],"03ba4cb8-67fc-11f0-8b06-0224a6c84d84","analyse_posts.py","03ba4d62-67fc-11f0-8b06-0224a6c84d84",107,["D",1753299254039],"#!/usr/bin/env python3\n\nimport os\nimport sqlite3\nimport sys\nimport re\nimport json\nfrom pathlib import Path\n\n\"\"\"\nThis script analyzes the top 100 posts from top100.sqlite and calculates\nthe percentage of comments that contain \"YTA\" (You're The Asshole).\nResults are stored in a new database with enhanced submission data and a JSONL file.\n\"\"\"\n\nSOURCE_DB_PATH = \"../db/top100.sqlite\"\nTARGET_DB_PATH = \"../db/top100_analyzed.sqlite\"\nOUTPUT_JSONL_PATH = \"../backend/data/top100_analyzed.jsonl\"\n\n\ndef contains_yta(comment_text):\n \"\"\"\n Check if a comment contains YTA (You're The Asshole).\n This looks for YTA as a standalone word to avoid false positives.\n \"\"\"\n if not comment_text:\n return False\n \n # Use regex to find YTA as a standalone word (case insensitive)\n # \\b ensures word boundaries to avoid matching \"YTAL\" or \"MYTA\" etc.\n pattern = r'\\bYTA\\b'\n return bool(re.search(pattern, comment_text, re.IGNORECASE))\n\n\ndef main():\n print(f\"Analyzing top 100 posts from {SOURCE_DB_PATH}...\")\n\n # Check if source file exists\n source_path = Path(SOURCE_DB_PATH)\n if not source_path.exists():\n print(f\"Error: Source database file not found: {SOURCE_DB_PATH}\")\n print(\"Please run extract_top_posts.py first to create the top100.sqlite database.\")\n sys.exit(1)\n\n # Create directory for target database if needed\n target_dir = os.path.dirname(TARGET_DB_PATH)\n os.makedirs(target_dir, exist_ok=True)\n print(f\"Ensured directory {target_dir} exists.\")\n\n # Remove target files if they exist\n if os.path.exists(TARGET_DB_PATH):\n os.remove(TARGET_DB_PATH)\n print(\"Removed existing target database.\")\n \n if os.path.exists(OUTPUT_JSONL_PATH):\n os.remove(OUTPUT_JSONL_PATH)\n print(\"Removed existing JSONL file.\")\n\n try:\n # Open source database\n print(\"Opening source database...\")\n source_conn = sqlite3.connect(SOURCE_DB_PATH)\n source_conn.row_factory = sqlite3.Row\n source_cursor = source_conn.cursor()\n print(\"Source database opened successfully.\")\n\n # Create target database\n print(\"Creating target database...\")\n target_conn = sqlite3.connect(TARGET_DB_PATH)\n target_conn.row_factory = sqlite3.Row\n target_cursor = target_conn.cursor()\n print(\"Target database created successfully.\")\n\n # Create enhanced submission table with YTA percentage - separate statements\n target_cursor.execute(\"\"\"\n CREATE TABLE IF NOT EXISTS \"submission_analysis\" (\n \"id\" INTEGER NOT NULL PRIMARY KEY,\n \"submission_id\" VARCHAR(255) NOT NULL,\n \"title\" TEXT NOT NULL,\n \"selftext\" TEXT NOT NULL,\n \"created_utc\" DATE NOT NULL,\n \"permalink\" TEXT NOT NULL,\n \"score\" INTEGER NOT NULL,\n \"total_comments\" INTEGER NOT NULL DEFAULT 0,\n \"yta_comments\" INTEGER NOT NULL DEFAULT 0,\n \"yta_percentage\" REAL NOT NULL DEFAULT 0.0\n )\n \"\"\")\n \n # Create the index in a separate statement\n target_cursor.execute(\"\"\"\n CREATE UNIQUE INDEX \"submission_analysis_submission_id\" ON \"submission_analysis\" (\"submission_id\")\n \"\"\")\n \n print(\"Target database table created.\")\n\n # Begin transaction\n target_conn.execute('BEGIN TRANSACTION')\n\n # Get all submissions from source\n source_cursor.execute(\"\"\"\n SELECT id, submission_id, title, selftext, created_utc, permalink, score \n FROM submission \n ORDER BY score DESC\n \"\"\")\n submissions = source_cursor.fetchall()\n print(f\"Found {len(submissions)} submissions to analyze.\")\n\n # Analyze each submission\n insert_sql = \"\"\"\n INSERT INTO submission_analysis \n (id, submission_id, title, selftext, created_utc, permalink, score, \n total_comments, yta_comments, yta_percentage) \n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\n \"\"\"\n\n # Open JSONL file for writing\n with open(OUTPUT_JSONL_PATH, 'w', encoding='utf-8') as jsonl_file:\n total_analyzed = 0\n analyzed_posts = []\n \n for i, submission in enumerate(submissions):\n submission_db_id = submission['submission_id']\n \n # Get all comments for this submission\n source_cursor.execute(\"\"\"\n SELECT message FROM comment \n WHERE submission_id = ?\n \"\"\", (submission_db_id,))\n \n comments = source_cursor.fetchall()\n total_comments = len(comments)\n \n # Count YTA comments\n yta_comments = 0\n for comment in comments:\n if contains_yta(comment['message']):\n yta_comments += 1\n \n # Calculate percentage\n yta_percentage = (yta_comments / total_comments * 100) if total_comments > 0 else 0.0\n \n # Create a post object\n post_data = {\n \"id\": submission['id'],\n \"submission_id\": submission['submission_id'],\n \"title\": submission['title'],\n \"selftext\": submission['selftext'],\n \"created_utc\": submission['created_utc'],\n \"permalink\": submission['permalink'],\n \"score\": submission['score'],\n \"total_comments\": total_comments,\n \"yta_comments\": yta_comments,\n \"yta_percentage\": round(yta_percentage, 2)\n }\n \n # Insert into target database\n target_cursor.execute(insert_sql, (\n submission['id'],\n submission['submission_id'],\n submission['title'],\n submission['selftext'],\n submission['created_utc'],\n submission['permalink'],\n submission['score'],\n total_comments,\n yta_comments,\n round(yta_percentage, 2)\n ))\n \n # Write to JSONL file\n jsonl_file.write(json.dumps(post_data) + '\\n')\n \n total_analyzed += 1\n \n # Show progress for first 10 and every 10th after that\n if i < 10 or (i + 1) % 10 == 0:\n print(f\"Analyzed submission {i+1}: '{submission['submission_id']}' - \"\n f\"{total_comments} comments, {yta_comments} YTA ({yta_percentage:.1f}%)\")\n\n # Commit transaction\n target_conn.execute('COMMIT')\n print('Database transaction committed successfully.')\n\n # Show summary statistics\n target_cursor.execute(\"\"\"\n SELECT \n COUNT(*) as total_posts,\n AVG(yta_percentage) as avg_yta_percentage,\n MIN(yta_percentage) as min_yta_percentage,\n MAX(yta_percentage) as max_yta_percentage,\n SUM(total_comments) as total_comments_analyzed,\n SUM(yta_comments) as total_yta_comments\n FROM submission_analysis\n \"\"\")\n \n stats = target_cursor.fetchone()\n \n print(\"\\n=== ANALYSIS SUMMARY ===\")\n print(f\"Total posts analyzed: {stats['total_posts']}\")\n print(f\"Total comments analyzed: {stats['total_comments_analyzed']}\")\n print(f\"Total YTA comments: {stats['total_yta_comments']}\")\n print(f\"Average YTA percentage: {stats['avg_yta_percentage']:.2f}%\")\n print(f\"Minimum YTA percentage: {stats['min_yta_percentage']:.2f}%\")\n print(f\"Maximum YTA percentage: {stats['max_yta_percentage']:.2f}%\")\n\n # Show top 5 posts with highest YTA percentage\n target_cursor.execute(\"\"\"\n SELECT submission_id, title, total_comments, yta_comments, yta_percentage\n FROM submission_analysis \n WHERE total_comments > 0\n ORDER BY yta_percentage DESC \n LIMIT 5\n \"\"\")\n \n top_yta_posts = target_cursor.fetchall()\n \n print(\"\\n=== TOP 5 POSTS WITH HIGHEST YTA PERCENTAGE ===\")\n for i, post in enumerate(top_yta_posts, 1):\n print(f\"{i}. {post['submission_id']} ({post['yta_percentage']:.1f}% YTA)\")\n print(f\" Comments: {post['yta_comments']}/{post['total_comments']}\")\n print(f\" Title: {post['title'][:80]}{'...' if len(post['title']) > 80 else ''}\")\n print()\n\n # Close connections\n source_conn.close()\n target_conn.close()\n\n print(\"Analysis complete!\")\n print(f\"Source database: {SOURCE_DB_PATH}\")\n print(f\"Analysis results database: {TARGET_DB_PATH}\")\n print(f\"Analysis results JSONL: {OUTPUT_JSONL_PATH}\")\n print(f\"Total posts analyzed: {total_analyzed}\")\n\n except sqlite3.Error as e:\n print(f\"SQLite error: {e}\")\n try:\n # Check if transaction is active before rolling back\n target_conn.execute(\"SELECT 1 FROM sqlite_master LIMIT 1\")\n target_conn.execute('ROLLBACK')\n print('Transaction rolled back due to error.')\n except Exception as rollback_error:\n print(f\"Error during rollback: {rollback_error}\")\n sys.exit(1)\n except Exception as e:\n print(f\"Error during analysis: {e}\")\n sys.exit(1)\n\n\nif __name__ == \"__main__\":\n main()",[],[186,359],"03c2fae8-67fc-11f0-a319-0224a6c84d84",["D",1753299254045],[],[186,32],["D",1753299236474],[330,331,332],[186],"c6f58288-67f2-11f0-ade2-0224a6c84d84","style.css","01983875-e8ca-7735-b93b-d99a041ace23",13,["D",1753295286556],"body {\n font-family: -apple-system, Arial, sans-serif;\n color: #333;\n background-color: #f8f9fa;\n margin: 0;\n padding: 0;\n}\n\n.container {\n max-width: 800px;\n margin: 0 auto;\n padding: 20px;\n}\n\n.header {\n background-color: #ff4500; /* Reddit orange */\n color: white;\n padding: 20px 0;\n text-align: center;\n margin-bottom: 30px;\n box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);\n}\n\n.header h1 {\n margin: 0;\n font-size: 2.5rem;\n}\n\n.header p {\n margin: 10px 0 0;\n opacity: 0.9;\n}\n\n.post-card {\n background-color: white;\n border-radius: 8px;\n padding: 25px;\n margin-bottom: 30px;\n box-shadow: 0 2px 15px rgba(0, 0, 0, 0.05);\n}\n\n.post-title {\n font-size: 1.6rem;\n margin-top: 0;\n margin-bottom: 20px;\n color: #1a1a1b;\n}\n\n.post-content {\n line-height: 1.6;\n margin-bottom: 30px;\n white-space: pre-wrap;\n}\n\n.slider-container {\n margin: 40px 0;\n}\n\n.slider-label {\n display: block;\n font-weight: bold;\n margin-bottom: 15px;\n text-align: center;\n font-size: 1.2rem;\n}\n\n.slider {\n width: 100%;\n -webkit-appearance: none;\n height: 10px;\n border-radius: 5px;\n background: #d3d3d3;\n outline: none;\n margin-bottom: 10px;\n}\n\n.slider::-webkit-slider-thumb {\n -webkit-appearance: none;\n appearance: none;\n width: 25px;\n height: 25px;\n border-radius: 50%;\n background: #ff4500;\n cursor: pointer;\n}\n\n.slider::-moz-range-thumb {\n width: 25px;\n height: 25px;\n border-radius: 50%;\n background: #ff4500;\n cursor: pointer;\n border: none;\n}\n\n.slider-value {\n text-align: center;\n font-size: 1.5rem;\n font-weight: bold;\n margin-top: 10px;\n color: #ff4500;\n}\n\nbutton {\n background-color: #ff4500;\n color: white;\n border: none;\n padding: 12px 24px;\n border-radius: 4px;\n cursor: pointer;\n font-size: 1rem;\n font-weight: bold;\n display: block;\n margin: 30px auto 0;\n transition: background-color 0.2s;\n}\n\nbutton:hover {\n background-color: #e03d00;\n}\n\nbutton:disabled {\n background-color: #cccccc;\n cursor: not-allowed;\n}\n\n.result {\n background-color: #f0f7ff;\n border-radius: 8px;\n padding: 20px;\n margin-top: 30px;\n text-align: center;\n animation: fadeIn 0.5s;\n}\n\n.result-heading {\n font-size: 1.3rem;\n margin-top: 0;\n margin-bottom: 15px;\n color: #1a1a1b;\n}\n\n.result-message {\n margin-bottom: 15px;\n font-size: 1.1rem;\n}\n\n.actual-value {\n font-weight: bold;\n font-size: 1.4rem;\n color: #ff4500;\n}\n\n.difference {\n margin-top: 10px;\n font-style: italic;\n}\n\n.play-again {\n background-color: #0079d3; /* Reddit blue */\n margin-top: 20px;\n}\n\n.play-again:hover {\n background-color: #0061a9;\n}\n\n@keyframes fadeIn {\n from { opacity: 0; transform: translateY(10px); }\n to { opacity: 1; transform: translateY(0); }\n}\n\n/* Responsive adjustments */\n@media (max-width: 600px) {\n .header h1 {\n font-size: 2rem;\n }\n\n .post-title {\n font-size: 1.4rem;\n }\n\n .slider-value {\n font-size: 1.3rem;\n }\n}",[],[193,374],"9158d358-67ef-11f0-97a8-0224a6c84d84","index.tsx","01983875-e8ca-7735-b93b-d722f7851bd0",["D",1753293908093],"script","/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { createRoot } from \"https://esm.sh/react-dom@18.2.0/client\";\nimport { App } from \"./components/App.tsx\";\n\nconst root = document.getElementById(\"root\");\nif (!root) {\n throw new Error(\"No root element found\");\n}\n\ncreateRoot(root).render();",[],[193,382],"c6e7bc5c-67f2-11f0-847e-0224a6c84d84","index.html","01983875-e8ca-7735-b93b-d349eb214392",11,["D",1753295286504],"\n\n \n \n \n Am I The Asshole? Guessing Game\n \n \n \n \n

\n \n \n \n",[],[193,390],"c6fdc826-67f2-11f0-8c08-0224a6c84d84","favicon.svg","01983875-e8ca-7735-b93b-cf7591f06a1e",14,["D",1753295286663],"\n",[],[193,398],"c6ec4380-67f2-11f0-8ed4-0224a6c84d84","App.tsx","01983875-e8ca-7735-b93b-c77249497ad5","01983875-e8ca-7735-b93b-cae8cf68bf65",12,["D",1753295286516],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { AITAGame } from \"./AITAGame.tsx\";\n\nexport function App() {\n return ;\n}",[],[193,414,406],"components","c6bdd8ba-67f2-11f0-bf9d-0224a6c84d84","AITAGame.tsx","c6bdd950-67f2-11f0-bf9d-0224a6c84d84",6,["D",1753295286172],"/** @jsxImportSource https://esm.sh/react@18.2.0 */\nimport { useState, useEffect } from \"https://esm.sh/react@18.2.0\";\n\ninterface AITAPost {\n id: string;\n title: string;\n content: string;\n}\n\ninterface GuessResult {\n actualPct: number;\n difference: number;\n message: string;\n}\n\nexport function AITAGame() {\n const [post, setPost] = useState(null);\n const [loading, setLoading] = useState(true);\n const [error, setError] = useState(null);\n const [guess, setGuess] = useState(50);\n const [result, setResult] = useState(null);\n\n // Fetch the AITA post when component mounts\n useEffect(() => {\n fetchPost();\n }, []);\n\n const fetchPost = async () => {\n setLoading(true);\n setError(null);\n setResult(null);\n\n try {\n const response = await fetch(`/api/posts/1`);\n if (!response.ok) {\n throw new Error('Failed to fetch post');\n }\n const data = await response.json();\n setPost(data);\n } catch (err) {\n setError('Error loading post. Please try again.');\n console.error(err);\n } finally {\n setLoading(false);\n }\n };\n\n const handleSliderChange = (e: React.ChangeEvent) => {\n setGuess(parseInt(e.target.value, 10));\n };\n\n const submitGuess = async () => {\n if (!post) return;\n\n try {\n const response = await fetch(`/api/posts/${post.id}/check`, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json'\n },\n body: JSON.stringify({ guess })\n });\n\n if (!response.ok) {\n throw new Error('Failed to submit guess');\n }\n\n const result = await response.json();\n setResult(result);\n } catch (err) {\n setError('Error submitting guess. Please try again.');\n console.error(err);\n }\n };\n\n const playAgain = () => {\n setGuess(50);\n setResult(null);\n // In a real app with multiple posts, we would fetch a new post here\n // For now, we'll just reset the state\n };\n\n if (loading) {\n return

;\n }\n\n if (error) {\n return (\n

{error}

\n \n

\n );\n }\n\n if (!post) {\n return

No post found.

;\n }\n\n return (\n

Am I The Asshole?

Guess what percentage of Reddit users thought the poster was the asshole

\n\n

{post.title}

{post.content}

\n\n {!result ? (\n

\n What percentage of people thought this person was the asshole?\n \n

{guess}%

\n \n

\n ) : (\n

Results

{result.message}

{result.actualPct}% of people thought OP was the asshole

(You were off by {result.difference}%)

\n \n

\n )}\n

\n );\n}\n",[],[193,414,416],"9158c8f4-67ef-11f0-97a8-0224a6c84d84",["D",1753293908093],[323,324],[193,414],["D",1753293908093],[322,325,326,327,328],[193],["D",1753299236795],[],[198],["D",1753295627106],[],[204],"c7037906-67f2-11f0-bf9d-0224a6c84d84","index.ts",15,["D",1753295286686],"http","import { serveFile } from \"https://esm.town/v/std/utils@85-main/index.ts\";\nimport { Hono } from \"npm:hono\";\nimport { posts } from \"./data/posts.ts\";\n\nconst app = new Hono();\n\n// Serve index.html at the root /\napp.get(\"/\", async c => {\n return serveFile(\"/frontend/index.html\", import.meta.url);\n});\n\n// Serve all /frontend files\napp.get(\"/frontend/**/*\", c => serveFile(c.req.path, import.meta.url));\n\n// API route to get a specific post\napp.get(\"/api/posts/:id\", c => {\n const id = c.req.param(\"id\");\n const post = posts.find(p => p.id === id);\n\n if (!post) {\n return c.json({ error: \"Post not found\" }, 404);\n }\n\n return c.json(post);\n});\n\n// API route to get all posts (without the assholePct to avoid spoilers)\napp.get(\"/api/posts\", c => {\n const postsWithoutPct = posts.map(({ id, title, content }) => ({ id, title, content }));\n return c.json(postsWithoutPct);\n});\n\n// API route to check a guess\napp.post(\"/api/posts/:id/check\", async c => {\n const id = c.req.param(\"id\");\n const post = posts.find(p => p.id === id);\n\n if (!post) {\n return c.json({ error: \"Post not found\" }, 404);\n }\n\n const body = await c.req.json();\n const userGuess = body.guess;\n\n if (typeof userGuess !== \"number\" || userGuess < 0 || userGuess > 100) {\n return c.json({ error: \"Invalid guess\" }, 400);\n }\n\n const difference = Math.abs(userGuess - post.assholePct);\n let message = \"\";\n\n if (difference <= 5) {\n message = \"Excellent guess! You really understand Reddit!\";\n } else if (difference <= 15) {\n message = \"Good guess! You're pretty close.\";\n } else if (difference <= 30) {\n message = \"Not bad, but you were a bit off.\";\n } else {\n message = \"Wow, you were way off! The Reddit hivemind surprised you.\";\n }\n\n return c.json({\n actualPct: post.assholePct,\n difference,\n message\n });\n});\n\n// Unwrap and rethrow Hono errors as the original error\n// If you delete this, all errors will be \"Internal Server Error\"\napp.onError((err, c) => {\n throw err;\n});\n\n// HTTP vals expect an exported \"fetch handler\"\n// This is how you \"run the server\" in Val Town with Hono\nexport default app.fetch;",[],[210,437],"c6b2364a-67f2-11f0-9530-0224a6c84d84","posts.ts","c6b236ea-67f2-11f0-9530-0224a6c84d84","c6975654-67f2-11f0-97a0-0224a6c84d84",4,["D",1753295286169],"// Static AITA post data for the game\n\nexport interface AITAPost {\n id: string;\n title: string;\n content: string;\n assholePct: number;\n}\n\nexport const posts: AITAPost[] = [\n {\n id: \"1\",\n title: \"AITA for refusing to babysit my sister's kids after she showed up 3 hours late last time?\",\n content: \"My sister has 3 kids (ages 4, 6, and 8) and she often asks me to babysit them when she and her husband want to go out. I usually don't mind and I love spending time with my nieces and nephews. Last weekend, she asked if I could watch them from 6pm to 11pm. I agreed, but she didn't show up until 2am. No calls, no texts, nothing. When she finally arrived, she wasn't apologetic at all and just said 'you don't have kids, so it's not like you had anything better to do anyway.' I was furious but didn't want to argue in front of the kids. Yesterday she called asking if I could babysit again this weekend. I told her no, and that I wouldn't be babysitting for her anymore unless she starts respecting my time. She called me selfish and said family should help each other out. Our parents are now calling me saying I should forgive her and help my sister. AITA?\",\n assholePct: 12\n 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Diff · v109