{"repo": "adhaghani/antiturnitin", "files": {"app/api/analyze/route.ts": {"d7f3b5e5cbc37599bfd8d6f4af1b9284be7ef008": {"t": 1785745574.7405577, "n": 3857, "h": "757a0cdb53f29d1a", "c": "import { NextRequest, NextResponse } from \"next/server\";\n\nconst SYSTEM_PROMPT = `You are an expert linguistic analyzer. Evaluate the following text for 'Perplexity' and 'Burstiness'.\n- Perplexity measures the randomness and unpredictability of word choices. AI-generated text tends to have low perplexity (predictable, formulaic patterns). Human text has higher, more natural variability.\n- Burstiness measures variation in sentence structure and length. Human writing typically has high burstiness (mixing long complex sentences with short punchy ones). AI text tends toward uniform sentence patterns.\n\nReturn ONLY a valid JSON object (no markdown formatting, no code fences) with exactly this structure:\n{\n  \"human_score\": <number 0-100, where 100 = most human-like>,\n  \"burstiness_analysis\": \"<brief 1-2 sentence assessment of sentence variation>\",\n  \"perplexity_analysis\": \"<brief 1-2 sentence assessment of word predictability>\",\n  \"improvement_tips\": [\"<specific actionable tip 1>\", \"<specific actionable tip 2>\", \"<specific actionable tip 3>\"]\n}`;\n\nexport async function POST(request: NextRequest) {\n  try {\n    const { text } = await request.json();\n\n    if (!text || typeof text !== \"string\" || text.trim().length === 0) {\n      return NextResponse.json({ error: \"Text is required\" }, { status: 400 });\n    }\n\n    if (text.trim().length < 50) {\n      return NextResponse.json(\n        {\n          error:\n            \"Text must be at least 50 characters for a meaningful analysis\",\n        },\n        { status: 400 },\n      );\n    }\n\n    const apiKey = process.env.DEEPSEEK_API_KEY;\n    if (!apiKey) {\n      return NextResponse.json(\n        { error: \"Server configuration error\" },\n        { status: 500 },\n      );\n    }\n\n    const response = await fetch(\n      \"https://api.deepseek.com/v1/chat/completions\",\n      {\n        method: \"POST\",\n        headers: {\n          \"Content-Type\": \"application/json\",\n          Authorization: `Bearer ${apiKey}`,\n        },\n        body: JSON.stringify({\n          model: \"deepseek-v4-pro\",\n          messages: [\n            { role: \"system\", content: SYSTEM_PROMPT },\n            { role: \"user\", content: text.trim() },\n          ],\n          temperature: 0.1,\n          max_tokens: 4000,\n        }),\n      },\n    );\n\n    if (!response.ok) {\n      const errorBody = await response.text().catch(() => \"\");\n      console.error(`DeepSeek API error ${response.status}:`, errorBody);\n      return NextResponse.json(\n        { error: `Analysis service returned an error (${response.status})` },\n        { status: response.status },\n      );\n    }\n\n    const data = await response.json();\n    const content: string | undefined = data.choices?.[0]?.message?.content;\n\n    if (!content) {\n      console.error(\"DeepSeek returned empty content:\", data);\n      return NextResponse.json(\n        { error: \"No analysis returned from the service\" },\n        { status: 500 },\n      );\n    }\n\n    // DeepSeek may wrap JSON in markdown code fences — extract the raw JSON\n    const jsonMatch = content.match(/\\{[\\s\\S]*\\}/);\n    if (!jsonMatch) {\n      console.error(\"Failed to extract JSON from DeepSeek response:\", content);\n      return NextResponse.json(\n        { error: \"Failed to parse analysis result\" },\n        { status: 500 },\n      );\n    }\n\n    const analysis = JSON.parse(jsonMatch[0]) as {\n      human_score: number;\n      burstiness_analysis: string;\n      perplexity_analysis: string;\n      improvement_tips: string[];\n    };\n\n    // Clamp human_score to 0–100 range as a safety net\n    analysis.human_score = Math.max(\n      0,\n      Math.min(100, Math.round(analysis.human_score)),\n    );\n\n    return NextResponse.json(analysis);\n  } catch (error) {\n    console.error(\"Analyze route error:\", error);\n    return NextResponse.json(\n      { error: \"Internal server error\" },\n      { status: 500 },\n    );\n  }\n}\n"}, "ddd38f4b7ec20e30cb29e8ac632ffb45cdef613e": {"t": 1785754384.9115207, "n": 3857, "h": "8ee5dabf188722aa", "c": "import { NextRequest, NextResponse } from \"next/server\";\n\nconst SYSTEM_PROMPT = `You are an expert linguistic analyzer. Evaluate the following text for 'Perplexity' and 'Burstiness'.\n- Perplexity measures the randomness and unpredictability of word choices. AI-generated text tends to have low perplexity (predictable, formulaic patterns). Human text has higher, more natural variability.\n- Burstiness measures variation in sentence structure and length. Human writing typically has high burstiness (mixing long complex sentences with short punchy ones). AI text tends toward uniform sentence patterns.\n\nReturn ONLY a valid JSON object (no markdown formatting, no code fences) with exactly this structure:\n{\n  \"human_score\": <number 0-100, where 100 = most human-like>,\n  \"burstiness_analysis\": \"<brief 1-2 sentence assessment of sentence variation>\",\n  \"perplexity_analysis\": \"<brief 1-2 sentence assessment of word predictability>\",\n  \"improvement_tips\": [\"<specific actionable tip 1>\", \"<specific actionable tip 2>\", \"<specific actionable tip 3>\"]\n}`;\n\nexport async function POST(request: NextRequest) {\n  try {\n    const { text } = await request.json();\n\n    if (!text || typeof text !== \"string\" || text.trim().length === 0) {\n      return NextResponse.json({ error: \"Text is required\" }, { status: 400 });\n    }\n\n    if (text.trim().length < 50) {\n      return NextResponse.json(\n        {\n          error:\n            \"Text must be at least 50 characters for a meaningful analysis\",\n        },\n        { status: 400 },\n      );\n    }\n\n    const apiKey = process.env.DEEPSEEK_API_KEY;\n    if (!apiKey) {\n      return NextResponse.json(\n        { error: \"Server configuration error\" },\n        { status: 500 },\n      );\n    }\n\n    const response = await fetch(\n      \"https://api.deepseek.com/v1/chat/completions\",\n      {\n        method: \"POST\",\n        headers: {\n          \"Content-Type\": \"application/json\",\n          Authorization: `Bearer ${apiKey}`,\n        },\n        body: JSON.stringify({\n          model: \"deepseek-v4-pro\",\n          messages: [\n            { role: \"system\", content: SYSTEM_PROMPT },\n            { role: \"user\", content: text.trim() },\n          ],\n          temperature: 0.1,\n          max_tokens: 1000,\n        }),\n      },\n    );\n\n    if (!response.ok) {\n      const errorBody = await response.text().catch(() => \"\");\n      console.error(`DeepSeek API error ${response.status}:`, errorBody);\n      return NextResponse.json(\n        { error: `Analysis service returned an error (${response.status})` },\n        { status: response.status },\n      );\n    }\n\n    const data = await response.json();\n    const content: string | undefined = data.choices?.[0]?.message?.content;\n\n    if (!content) {\n      console.error(\"DeepSeek returned empty content:\", data);\n      return NextResponse.json(\n        { error: \"No analysis returned from the service\" },\n        { status: 500 },\n      );\n    }\n\n    // DeepSeek may wrap JSON in markdown code fences — extract the raw JSON\n    const jsonMatch = content.match(/\\{[\\s\\S]*\\}/);\n    if (!jsonMatch) {\n      console.error(\"Failed to extract JSON from DeepSeek response:\", content);\n      return NextResponse.json(\n        { error: \"Failed to parse analysis result\" },\n        { status: 500 },\n      );\n    }\n\n    const analysis = JSON.parse(jsonMatch[0]) as {\n      human_score: number;\n      burstiness_analysis: string;\n      perplexity_analysis: string;\n      improvement_tips: string[];\n    };\n\n    // Clamp human_score to 0–100 range as a safety net\n    analysis.human_score = Math.max(\n      0,\n      Math.min(100, Math.round(analysis.human_score)),\n    );\n\n    return NextResponse.json(analysis);\n  } catch (error) {\n    console.error(\"Analyze route error:\", error);\n    return NextResponse.json(\n      { error: \"Internal server error\" },\n      { status: 500 },\n    );\n  }\n}\n"}}}}