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So you want to take away everyone's freedom!\"\n },\n { \n name: \"Appeal to Authority\", \n description: \"Claiming something is true because an authority figure says so\",\n example: \"This celebrity says this diet works, so it must be true.\"\n },\n { \n name: \"False Dichotomy\", \n description: \"Presenting only two options when more exist\",\n example: \"Either you support this policy completely, or you're against progress.\"\n },\n { \n name: \"Slippery Slope\", \n description: \"Arguing that a small step will lead to extreme consequences\",\n example: \"If we allow this, soon everything will be chaos!\"\n },\n { \n name: \"Circular Reasoning\", \n description: \"Using the conclusion as part of the premise\",\n example: \"This book is true because the book says it's true.\"\n },\n { \n name: \"Hasty Generalization\", \n description: \"Drawing broad conclusions from insufficient evidence\",\n example: \"I met one person from that country, and they were rude, so all people from there must be rude.\"\n }\n];\n\n// Mock fallacy detection for when OpenAI fails\nfunction mockFallacyDetection(text) {\n const lowercaseText = text.toLowerCase();\n const mockFallacies = [];\n\n const fallacyChecks = [\n { \n name: \"Ad Hominem\", \n check: (txt) => txt.includes(\"you are\") || txt.includes(\"they are\"),\n explanation: \"Detected potential personal attack language\"\n },\n { \n name: \"Straw Man\", \n check: (txt) => txt.includes(\"so you mean\") || txt.includes(\"that means\"),\n explanation: \"Detected potential misrepresentation of argument\"\n },\n { \n name: \"Hasty Generalization\", \n check: (txt) => txt.includes(\"all\") || txt.includes(\"always\") || txt.includes(\"never\"),\n explanation: \"Detected broad generalization language\"\n }\n ];\n\n fallacyChecks.forEach(fallacy => {\n if (fallacy.check(lowercaseText)) {\n mockFallacies.push({\n type: fallacy.name,\n text: text.substring(0, 100) + \"...\",\n explanation: fallacy.explanation\n });\n }\n });\n\n return mockFallacies;\n}\n\nfunction FallacyDetector() {\n const [text, setText] = useState('');\n const [analysis, setAnalysis] = useState(null);\n const [isLoading, setIsLoading] = useState(false);\n const [error, setError] = useState(null);\n\n async function detectFallacies() {\n if (!text.trim()) {\n setError('Please enter some text to analyze');\n return;\n }\n\n setIsLoading(true);\n setError(null);\n setAnalysis(null);\n\n try {\n // Dynamically import OpenAI with error handling\n const openAIModule = await import(\"https://esm.town/v/std/openai\").catch(err => {\n console.error(\"Failed to import OpenAI module:\", err);\n throw new Error(\"Could not load AI analysis module\");\n });\n\n const OpenAI = openAIModule.OpenAI;\n const openai = new OpenAI();\n\n const response = await openai.chat.completions.create({\n model: \"gpt-4o-mini\",\n messages: [\n {\n role: \"system\", \n content: `You are an expert logical fallacy detector. \n Analyze the following text and identify any logical fallacies. \n IMPORTANT: Always return a valid JSON with this exact structure:\n {\n \"fallacies\": [\n {\n \"type\": \"Specific Fallacy Name\",\n \"text\": \"Exact problematic text excerpt\",\n \"explanation\": \"Detailed explanation of why this is a fallacy\"\n }\n ]\n }\n \n If NO fallacies are found, return:\n {\n \"fallacies\": []\n }\n \n Possible fallacy types include: \n ${FALLACY_TYPES.map(f => f.name).join(', ')}`\n },\n {\n role: \"user\", \n content: text\n }\n ],\n response_format: { type: \"json_object\" },\n max_tokens: 300\n });\n\n try {\n const result = JSON.parse(response.choices[0].message.content);\n \n // Validate the response structure\n if (!Array.isArray(result.fallacies)) {\n throw new Error('Invalid response format');\n }\n \n setAnalysis(result.fallacies || []);\n } catch (parseError) {\n console.error('Parsing error:', parseError);\n // Fallback to mock detection\n const mockFallacies = mockFallacyDetection(text);\n setAnalysis(mockFallacies);\n setError('AI analysis failed. Using basic fallacy detection.');\n }\n } catch (err) {\n console.error('Detailed error:', err);\n \n // Fallback to mock detection\n const mockFallacies = mockFallacyDetection(text);\n setAnalysis(mockFallacies);\n \n setError(`Failed to analyze text: ${err.message || 'Unknown error'}. Using basic fallacy detection.`);\n } finally {\n setIsLoading(false);\n }\n }\n\n return (\n

🕵️ Logical Fallacy Detector

setText(e.target.value)}\n        placeholder=\"Enter text to analyze for logical fallacies...\"\n        rows={6}\n      />\n      <button \n        onClick={detectFallacies} \n        disabled={isLoading}\n      >\n        {isLoading ? 'Analyzing...' : 'Detect Fallacies'}\n      </button>\n\n      {error && (\n        <div className=\"error-message\">\n          {error}\n        </div>\n      )}\n\n      {analysis && (\n        <div className=\"analysis-results\">\n          <h2>\n            {analysis.length === 0 \n              ? '✅ No logical fallacies detected!' \n              : '⚠️ Fallacies Found:'}\n          </h2>\n          {analysis.map((fallacy, index) => (\n            <div key={index} className=\"fallacy-result\">\n              <h3>{fallacy.type}</h3>\n              <p><strong>Problematic Text:</strong> \"{fallacy.text}\"</p>\n              <p><strong>Explanation:</strong> {fallacy.explanation}</p>\n            </div>\n          ))}\n        </div>\n      )}\n\n      <div className=\"fallacy-types\">\n        <h3>Common Logical Fallacies</h3>\n        <ul>\n          {FALLACY_TYPES.map((fallacy, index) => (\n            <li key={index}>\n              <strong>{fallacy.name}</strong>: {fallacy.description}\n            </li>\n          ))}\n        </ul>\n      </div>\n\n      <a \n        href={import.meta.url.replace(\"esm.town\", \"val.town\")} \n        target=\"_top\" \n        className=\"source-link\"\n      >\n        View Source\n      </a>\n    </div>\n  );\n}\n\nfunction client() {\n  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Code