Lexi - AI Legal Assistant

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\n\n\n`;\n}\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 const { PDFExtract, PDFExtractOptions } = await import(\"npm:pdf.js-extract\");\n const CORS_HEADERS = {\n \"Access-Control-Allow-Origin\": \"*\",\n \"Access-Control-Allow-Methods\": \"POST, GET, OPTIONS\",\n \"Access-Control-Allow-Headers\": \"Content-Type, Accept\",\n };\n if (req.method === \"OPTIONS\") { return new Response(null, { status: 204, headers: CORS_HEADERS }); }\n const url = new URL(req.url);\n const format = url.searchParams.get(\"format\");\n const action = url.searchParams.get(\"action\");\n const sourceUrl = import.meta.url.replace(\"esm.town\", \"val.town\");\n const openai = new OpenAI();\n const MAX_TEXT_LENGTH_SUGGESTION = 20000;\n const MAX_TEXT_LENGTH_ANALYSIS = 30000;\n async function extractPdfTextNative(data: ArrayBuffer, fileName: string, log: LogEntry[]): Promise {\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 async function callOpenAI(\n openaiInstance: OpenAI,\n systemPrompt: string,\n userMessage: string,\n model = \"gpt-4o\",\n expectJson = true,\n log: LogEntry[],\n agentName: string,\n ): Promise