\n {getLabel()} (Credibility Score: {score}%)\n

\n );\n}\n\nfunction App() {\n const [newsText, setNewsText] = useState('');\n const [analysisResult, setAnalysisResult] = useState(null);\n const [isLoading, setIsLoading] = useState(false);\n\n const handleAnalyze = async () => {\n setIsLoading(true);\n setAnalysisResult(null);\n try {\n const response = await fetch('/analyze', {\n method: 'POST',\n body: JSON.stringify({ text: newsText })\n });\n const result = await response.json();\n setAnalysisResult(result);\n } catch (error) {\n console.error('Analysis failed', error);\n } finally {\n setIsLoading(false);\n }\n };\n\n return (\n

🕵️‍♀️ Advanced Fake News Detector

setNewsText(e.target.value)}\n      />\n      <button \n        onClick={handleAnalyze} \n        disabled={isLoading || !newsText}\n        style={{\n          backgroundColor: '#2196F3', \n          color: 'white', \n          padding: '12px 20px',\n          border: 'none',\n          borderRadius: '5px',\n          fontSize: '16px',\n          cursor: 'pointer'\n        }}\n      >\n        {isLoading ? '🔍 Analyzing...' : '🕵️ Detect Misinformation'}\n      </button>\n\n      {isLoading && (\n        <div style={{\n          textAlign: 'center', \n          marginTop: '20px', \n          color: '#2196F3'\n        }}>\n          Analyzing text... This may take a moment\n        </div>\n      )}\n\n      {analysisResult && (\n        <div style={{\n          marginTop: '20px', \n          padding: '20px', \n          backgroundColor: '#f4f4f4',\n          borderRadius: '10px'\n        }}>\n          <CredibilityIndicator score={analysisResult.score} />\n          \n          <div style={{ marginTop: '20px' }}>\n            <h3>Detailed Analysis:</h3>\n            \n            <div style={{\n              display: 'grid',\n              gridTemplateColumns: '1fr 1fr',\n              gap: '10px'\n            }}>\n              <div>\n                <h4>🚩 Potential Red Flags:</h4>\n                <ul>\n                  {analysisResult.redFlags.map((flag, index) => (\n                    <li key={index} style={{ marginBottom: '5px' }}>{flag}</li>\n                  ))}\n                </ul>\n              </div>\n              \n              <div>\n                <h4>✅ Credibility Indicators:</h4>\n                <ul>\n                  {analysisResult.credibilitySignals.map((signal, index) => (\n                    <li key={index} style={{ marginBottom: '5px' }}>{signal}</li>\n                  ))}\n                </ul>\n              </div>\n            </div>\n\n            <div style={{ marginTop: '20px' }}>\n              <h4>🔍 Contextual Analysis:</h4>\n              <p>{analysisResult.contextualInsight}</p>\n            </div>\n          </div>\n        </div>\n      )}\n\n      <p style={{\n        fontSize: '0.8em', \n        marginTop: '20px', \n        textAlign: 'center',\n        color: '#666'\n      }}>\n        AI-powered analysis for informational awareness\n        <br />\n        <a \n          href={import.meta.url.replace(\"esm.town\", \"val.town\")} \n          target=\"_top\"\n          style={{ color: '#2196F3', textDecoration: 'none' }}\n        >\n          View Source\n        </a>\n      </p>\n    </div>\n  );\n}\n\nfunction client() {\n  createRoot(document.getElementById(\"root\")).render(<App />);\n}\nif (typeof document !== \"undefined\") { client(); }\n\nexport default async function server(request: Request): Promise<Response> {\n  if (request.method === 'POST' && new URL(request.url).pathname === '/analyze') {\n    const { OpenAI } = await import(\"https://esm.town/v/std/openai\");\n    const openai = new OpenAI();\n    \n    const { text } = await request.json();\n    \n    const completion = await openai.chat.completions.create({\n      messages: [\n        { \n          role: \"system\", \n          content: `You are an advanced AI news credibility analyzer. \n          Respond ONLY with a JSON object containing:\n          - credibilityScore (number from 0-100)\n          - redFlags (array of strings)\n          - credibilitySignals (array of strings)\n          - contextualInsight (string)\n\n          JSON Analysis Requirements:\n          - Analyze text for emotional manipulation\n          - Check logical inconsistencies\n          - Evaluate source reliability\n          - Detect potential bias\n          - Verify claims\n          - Consider historical context`\n        },\n        { \n          role: \"user\", \n          content: text \n        }\n      ],\n      model: \"gpt-4o-mini\",\n      response_format: { type: \"json_object\" }\n    });\n\n    const analysis = JSON.parse(completion.choices[0].message.content);\n\n    return new Response(JSON.stringify({\n      score: analysis.credibilityScore || 50,\n      redFlags: analysis.redFlags || ['No specific red flags detected'],\n      credibilitySignals: analysis.credibilitySignals || ['No strong credibility indicators'],\n      contextualInsight: analysis.contextualInsight || 'Unable to provide detailed contextual analysis'\n    }), {\n      headers: { 'Content-Type': 'application/json' }\n    });\n  }\n\n  return new Response(`\n    <html>\n      <head>\n        <title>Advanced Fake News Detector</title>\n        <meta name=\"viewport\" content=\"width=device-width, initial-scale=1\">\n      </head>\n      <body>\n        <div id=\"root\"></div>\n        <script src=\"https://esm.town/v/std/catch\"></script>\n        <script type=\"module\" src=\"${import.meta.url}\"></script>\n      </body>\n    </html>\n  `, {\n    headers: { 'Content-Type': 'text/html' }\n  });\n}","deleted","label",[98],"permalink","https://www.val.town/x/veer16/Factify/code/main.tsx","extension","actionData","errors"]
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