THE STANDARD OS

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BACKEND: TYPE DEFINITIONS & LOGIC\n// ==========================================\n\ninterface AlphaOmegaAnalysis {\n meta: {\n id: string;\n title: string;\n executive_summary: string;\n tone_vector: string;\n complexity_rating: number;\n risk_score: number;\n created_at: string;\n };\n entities: Array<{\n id: string;\n name: string;\n role: string;\n obligations: string[];\n rights: string[];\n }>;\n codex: Array<{\n id: string;\n domain: string;\n directives: Array<{\n id: string;\n text: string;\n modality: \"MANDATORY\" | \"PROHIBITORY\" | \"PERMISSIVE\";\n strength: \"ABSOLUTE\" | \"CONDITIONAL\";\n loopholes: string[];\n }>;\n }>;\n tribal_wisdom: Array<{\n id: string;\n axiom: string;\n derivation: string;\n enforcement_risk: \"HIGH\" | \"MEDIUM\" | \"LOW\";\n }>;\n friction_points: Array<{\n id: string;\n conflict: string;\n description: string;\n severity: \"CRITICAL\" | \"MAJOR\" | \"MINOR\";\n }>;\n lexicon: Array<{\n term: string;\n definition: string;\n category: \"JARGON\" | \"ACRONYM\" | \"SLANG\";\n }>;\n}\n\nconst SYSTEM_PROMPT = `\nYou are the 'Forensic Information Architect', the central intelligence of The Standard OS.\nYour mandate is to ingest chaotic text streams and crystallize them into structured Truth.\n\nPERFORM THESE LOGICAL CHECKS:\n1. **Entity Extraction**: Identify 'actors' (e.g., 'The Employee', 'The System'). Map rights vs. duties.\n2. **Modality Analysis**: Distinguish between mandates (\"MUST\"), prohibitions (\"MUST NOT\"), and permissions (\"MAY\").\n3. **Friction Detection**: Look for logical contradictions.\n4. **Subtext Analysis**: What is the 'Tribal Knowledge'—implied but not stated?\n\nOutput strictly in the JSON schema provided in the prompt.\n`;\n\nasync function analyzeText(\n text: string,\n filename: string,\n): Promise {\n const openai = new OpenAI();\n\n // Truncate to avoid token limits, though real production would chunk this.\n const slice = text.substring(0, 35000);\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: SYSTEM_PROMPT },\n {\n role: \"user\",\n content: `Analyze this document (${filename}):\\n\\n${slice}`,\n },\n ],\n response_format: { type: \"json_object\" },\n temperature: 0.2,\n });\n\n const raw = JSON.parse(completion.choices[0].message.content);\n\n // Hydrate IDs\n return {\n ...raw,\n meta: { ...raw.meta, id: nanoid(), created_at: new Date().toISOString() },\n entities: (raw.entities || []).map((e: any) => ({ ...e, id: nanoid() })),\n codex: (raw.codex || []).map((c: any) => ({\n ...c,\n id: nanoid(),\n directives: (c.directives || []).map((d: any) => ({\n ...d,\n id: nanoid(),\n })),\n })),\n tribal_wisdom: (raw.tribal_wisdom || []).map((t: any) => ({\n ...t,\n id: nanoid(),\n })),\n friction_points: (raw.friction_points || []).map((f: any) => ({\n ...f,\n id: nanoid(),\n })),\n lexicon: (raw.lexicon || []),\n };\n}\n\nasync function createJob(text: string, filename: string) {\n const id = `JOB-${nanoid(8)}`.toUpperCase();\n // Initial state\n await blob.setJSON(id, {\n id,\n status: \"processing\",\n filename,\n step: \"Ingesting\",\n progress: 10,\n });\n\n // Background Process\n (async () => {\n try {\n await blob.setJSON(id, {\n id,\n status: \"processing\",\n filename,\n step: \"Deciphering Entities\",\n progress: 30,\n });\n // Simulate specialized sub-agent processing time\n await new Promise((r) => setTimeout(r, 800));\n\n const result = await analyzeText(text, filename);\n\n await blob.setJSON(id, {\n id,\n status: \"processing\",\n filename,\n step: \"Finalizing Codex\",\n progress: 90,\n });\n await blob.setJSON(id, {\n id,\n status: \"complete\",\n filename,\n result,\n progress: 100,\n });\n } catch (e) {\n console.error(e);\n await blob.setJSON(id, {\n id,\n status: \"error\",\n error: e.message || \"Unknown Error\",\n });\n }\n })();\n\n return id;\n}\n\n// ==========================================\n// 2. FRONTEND: THE STANDARD OS (HTML GENERATION)\n// ==========================================\n\nfunction generateHtml() {\n // NOTE: All backticks and ${} inside this return string are escaped\n // so they are processed by the Browser, not the Server.\n return `\n\n\n\n \n \n THE STANDARD OS\n \n \n \n \n \n \n \n \n \n\n\n

\n \n\n\n `;\n}\n\n// ==========================================\n// 3. SERVER HANDLER\n// ==========================================\n\nexport default async function (req: Request): Promise {\n const url = new URL(req.url);\n\n // --- API ROUTER ---\n\n if (req.method === \"POST\" && url.pathname === \"/analyze\") {\n try {\n const { text, filename } = await req.json();\n if (!text) throw new Error(\"No text provided\");\n const id = await createJob(text, filename);\n return Response.json({ id });\n } catch (e) {\n return Response.json({ error: e.message }, { status: 400 });\n }\n }\n\n if (req.method === \"GET\" && url.pathname === \"/status\") {\n const id = url.searchParams.get(\"id\");\n const job = await blob.getJSON(id);\n return Response.json(job || { status: \"not_found\" });\n }\n\n // --- HTML SERVE ---\n\n return new Response(generateHtml(), {\n headers: { \"Content-Type\": \"text/html\" },\n });\n}","function generateHtml() {\n // FIXED: Added full height to html, body, and #root so the desktop renders visible\n return `\n\n\n\n \n \n THE STANDARD OS\n \n \n \n \n \n \n \n \n \n\n\n

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