1912 Realty - Loan Assumption Assistant

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\n\n\n\n`;\n}\n\n// --- Main Request Handler (Server Code - MODIFIED) ---\nexport default async function(req: Request) {\n const { OpenAI } = await import(\"https://esm.town/v/std/openai\");\n const { fetch } = await import(\"https://esm.town/v/std/fetch\");\n // PDFExtract is kept if you want to add document features later, but not primary for this use case.\n const { PDFExtract, PDFExtractOptions } = await import(\"npm:pdf.js-extract\");\n\n const CORS_HEADERS = {/* ... (same as original) ... */};\n if (req.method === \"OPTIONS\") { /* ... (same as original) ... */ }\n\n const url = new URL(req.url);\n const format = url.searchParams.get(\"format\");\n const action = url.searchParams.get(\"action\"); // New: \"loanAssumptionInfo\"\n const sourceUrl = import.meta.url.replace(\"esm.town\", \"val.town\");\n const openai = new OpenAI();\n const MAX_TEXT_LENGTH_ANALYSIS = 10000; // Reduced as input is smaller now\n\n // extractPdfTextNative function (same as original, less used now)\n async function extractPdfTextNative(data: ArrayBuffer, fileName: string, log: LogEntry[]): Promise {\n // ... (implementation from original)\n const agent = \"PDF Extraction Agent (Val Server)\";\n log.push({ agent, type: \"step\", message: `Processing PDF: ${fileName} using npm:pdf.js-extract` });\n try {\n const pdfExtract = new PDFExtract();\n const options: PDFExtractOptions = {};\n const pdfData = await pdfExtract.extractBuffer(data, options);\n const text = pdfData.pages.map(page => page.content.map(item => item.str).join(\" \")).join(\"\\\\n\\\\n\");\n if (!text || text.trim().length === 0) {\n log.push({ agent, type: \"error\", message: \"PDF extraction resulted in empty text content.\" });\n return null;\n }\n log.push({ agent, type: \"info\", message: `Successfully extracted ~${text.length} characters from PDF.` });\n return text;\n } catch (error) {\n const errorMessage = `Failed to extract text from PDF: ${error.message}`;\n log.push({ agent, type: \"error\", message: errorMessage });\n console.error(agent, errorMessage, error);\n return null;\n }\n }\n\n // callOpenAI function (same as original, but uses gpt-4o by default)\n async function callOpenAI(\n openaiInstance: OpenAI,\n systemPrompt: string,\n userMessage: string, // For this app, userMessage to AI might be empty if all info is in systemPrompt\n model = \"gpt-4o\",\n expectJson = true,\n log: LogEntry[],\n agentName: string,\n ): Promise

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