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25 Commits

Author SHA1 Message Date
8f104cb8cc address 2026-07-19 12:49:36 -05:00
92281f33bd reprocessMissing only date 2026-07-16 18:27:18 -05:00
9a8a8c86e3 change context size 2026-07-16 15:44:03 -05:00
18f8f97a43 fixes 2026-07-16 10:47:38 -05:00
92e1f3235a sdfsd 2026-07-16 10:43:58 -05:00
e46f00c838 new 2026-07-14 18:52:19 -05:00
e367b6ac29 dfgdfg 2026-07-14 15:09:32 -05:00
7b99d18f2c dsgfds 2026-07-14 14:28:24 -05:00
db8e6cce21 dfgdfg 2026-07-14 14:17:18 -05:00
d8d62fa371 sdfsd 2026-07-14 14:01:11 -05:00
96eb7ad9b9 update 2026-07-14 12:34:44 -05:00
6c3786f200 gdfgdf 2026-07-12 22:59:50 -05:00
70f09fa9da sdfsdf 2026-07-12 22:59:21 -05:00
14699b5f26 dfgdfg 2026-07-12 18:07:58 -05:00
1ff5f429c4 asdasd 2026-07-12 17:36:58 -05:00
82cca38f29 asdsa 2026-07-12 17:34:29 -05:00
f44d998a7f sdf 2026-07-12 15:16:37 -05:00
d95b8c112d timestamp 2026-07-12 14:05:05 -05:00
6c3eadc2c3 name 2026-07-12 13:14:38 -05:00
6ead3d76ec dg 2026-07-12 13:00:07 -05:00
fe3f8f14fa new headers 2026-07-12 12:52:04 -05:00
06f7df3fe1 certs 2026-07-12 12:36:05 -05:00
0989c06b8f gfdfg 2026-07-12 12:30:20 -05:00
888c5c1543 dfgdfg 2026-07-11 17:08:41 -05:00
b8c862885e typescript ansatz 2026-07-11 15:56:14 -05:00
30 changed files with 4193 additions and 28 deletions

7
.gitignore vendored
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poc_out poc_out
node_modules
package-lock.json
*.json
*.log
*.txt

333
BuyerSheetParser.ts Normal file
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import * as pdfjsLib from 'pdfjs-dist/legacy/build/pdf.js';
import * as fs from 'fs';
export interface BuyerSheetData {
file_name: string; // NEU
is_buyer_sheet: boolean;
name_company: string | null;
prospective_buyer: string | null;
company: string | null;
phone: string | null;
cell: string | null;
email: string | null;
address: string | null;
state: string | null;
how_did_you_hear: string | null;
interested_in_updates: boolean | null;
types_of_business_raw: string | null;
background_experience: string | null;
total_purchase_price: string | null;
down_payment: string | null;
down_payment_raw: string | null;
date_of_introduction: string | null;
_checkbox_pending: boolean;
_parser: string;
_info_page: number | null;
_ca_page: number | null;
}
const LABELS = [
"NAME / COMPANY", "PHONE", "ADDRESS", "EMAIL ADDRESS",
"HOW DID YOU HEAR", "ARE YOU INTERESTED", "TYPES OF BUSINESSES",
"BACKGROUND", "TOTAL PURCHASE PRICE", "DOWN PAYMENT",
"INCOME REQUIREMENTS", "ACCOUNTANT", "ATTORNEY", "BANK",
];
export class DeterministicParser {
public async parsePdf(filePath: string, fileName: string): Promise<BuyerSheetData | null> {
const dataBuffer = fs.readFileSync(filePath);
const loadingTask = pdfjsLib.getDocument({ data: new Uint8Array(dataBuffer) });
const pdfDocument = await loadingTask.promise;
// Regel: Alles über 10 Seiten wird radikal ignoriert
if (pdfDocument.numPages > 10) {
return null;
}
let infoPageNum: number | null = null;
let caPageNum: number | null = null;
let infoPageObj: any = null;
let infoPageTextContent: any = null;
// ==========================================
// 1. Dynamische Seitensuche (Visuell sortiert & kugelsicher)
// ==========================================
for (let i = 1; i <= pdfDocument.numPages; i++) {
const page = await pdfDocument.getPage(i);
const textContent = await page.getTextContent();
// Elemente mit Koordinaten versehen und wie ein Mensch lesen (von oben nach unten, links nach rechts)
const sortedItems = textContent.items
.map((item: any) => ({
text: item.str,
x: item.transform[4],
y: item.transform[5]
}))
.sort((a: any, b: any) => {
// Y-Toleranz für Buchstaben auf derselben Zeile
if (Math.abs(b.y - a.y) > 5) {
return b.y - a.y;
}
return a.x - b.x;
});
// Wir werfen ALLE Leerzeichen, Striche, Punkte und unsichtbare Artefakte weg.
// Übrig bleibt eine reine, unverwüstliche Buchstabenkette.
const textRaw = sortedItems.map((i: any) => i.text).join('').toUpperCase().replace(/[^A-Z]/g, '');
// Anker-Suche in der sauberen Zeichenkette
if (textRaw.includes('BUYERINFORMATIONSHEET')) {
infoPageNum = i;
infoPageObj = page;
infoPageTextContent = textContent;
}
if (textRaw.includes('PROSPECTIVEBUYERAGREESTOKEEPANDHOLDCONFIDENTIAL')) {
caPageNum = i;
}
}
// ==========================================
// 2. Fallback für Bild/Scan PDFs
// ==========================================
if (!infoPageNum || !infoPageObj || !infoPageTextContent) {
return this.createEmptyFallback(fileName, filePath, infoPageNum, caPageNum);
}
// ==========================================
// 3. Werte-Extraktion (nur auf der Info-Seite!)
// ==========================================
const mappedItems = infoPageTextContent.items
.filter((item: any) => item.str.trim() !== '')
.map((item: any) => ({
text: item.str,
x: item.transform[4],
y: item.transform[5],
width: item.width
}))
.sort((a: any, b: any) => b.y - a.y || a.x - b.x);
const linesGrouped: { y: number, items: any[] }[] = [];
let currentY: number | null = null;
let currentItems = [];
for (const item of mappedItems) {
if (currentY === null || Math.abs(item.y - currentY) <= 3) {
currentItems.push(item);
currentY = currentY === null ? item.y : currentY;
} else {
linesGrouped.push({ y: currentY, items: currentItems });
currentItems = [item];
currentY = item.y;
}
}
if (currentItems.length > 0 && currentY !== null) {
linesGrouped.push({ y: currentY, items: currentItems });
}
const lines: { y: number, text: string }[] = [];
for (const group of linesGrouped) {
group.items.sort((a, b) => a.x - b.x);
let lineStr = "";
let prevEnd = -1;
for (const item of group.items) {
if (prevEnd !== -1) {
const gap = item.x - prevEnd;
if (gap > 4) lineStr += " ";
}
lineStr += item.text;
prevEnd = item.x + item.width;
}
lines.push({ y: group.y, text: lineStr });
}
const rawResults: Record<string, string[]> = {};
LABELS.forEach(lbl => rawResults[lbl] = []);
let currentLabel: string | null = null;
const sortedLabels = [...LABELS].sort((a, b) => b.length - a.length);
for (const line of lines) {
const textUpper = line.text.toUpperCase().replace(/\s+/g, '');
if (textUpper.includes("SELLERMAYREQUIREVERIFICATION")) continue;
let foundLabel: string | null = null;
for (const lbl of sortedLabels) {
const lblClean = lbl.toUpperCase().replace(/\s+/g, '');
if (textUpper.includes(lblClean)) {
foundLabel = lbl;
break;
}
}
if (foundLabel) {
currentLabel = foundLabel;
if (line.text.includes(':')) {
const parts = line.text.split(':');
const val = parts.slice(1).join(':').replace(/_+/g, '').trim();
if (val.length > 0) rawResults[currentLabel].push(val);
}
} else if (currentLabel) {
const cleanVal = line.text.replace(/_+/g, '').trim();
if (cleanVal.length > 0 && !cleanVal.includes("Doc ID") && !cleanVal.includes("Bizmatch")) {
rawResults[currentLabel].push(cleanVal);
}
}
}
const visualCheckboxResult = await this.detectGraphicCheckbox(infoPageObj, mappedItems);
return this.mapToTargetStructure(rawResults, filePath, fileName, visualCheckboxResult, infoPageNum, caPageNum);
}
private createEmptyFallback(fileName: string, filePath: string, infoPage: number | null, caPage: number | null): BuyerSheetData {
let dateOfIntro = null;
const dateMatch = filePath.match(/(\d{2})(\d{2})(\d{2})\.pdf$/);
if (dateMatch) dateOfIntro = `20${dateMatch[3]}-${dateMatch[1]}-${dateMatch[2]}`;
return {
file_name: fileName,
is_buyer_sheet: false,
name_company: null,
prospective_buyer: null,
company: null,
phone: null,
cell: null,
email: null,
address: null,
state: null,
how_did_you_hear: null,
interested_in_updates: null,
types_of_business_raw: null,
background_experience: null,
total_purchase_price: null,
down_payment: null,
down_payment_raw: null,
date_of_introduction: dateOfIntro,
_checkbox_pending: true,
_parser: "deterministic", // Signal für den AI-Pass
_info_page: infoPage,
_ca_page: caPage
};
}
private mapToTargetStructure(
raw: Record<string, string[]>,
filePath: string,
fileName: string,
visualCheckboxResult: boolean | null,
infoPageNum: number | null,
caPageNum: number | null
): BuyerSheetData {
const getVal = (label: string) => raw[label] && raw[label].length > 0 ? raw[label].join(' ') : null;
const nameCompany = getVal("NAME / COMPANY");
let phoneRaw = getVal("PHONE");
let phoneClean = null;
let cellClean = null;
if (phoneRaw) {
const phoneMatch = phoneRaw.split(/FAX:|CELL:/)[0];
phoneClean = phoneMatch ? phoneMatch.trim() : null;
const cellMatch = phoneRaw.match(/CELL:\s*(.*)/);
cellClean = cellMatch && cellMatch[1] ? cellMatch[1].trim() : null;
}
let addressClean = getVal("ADDRESS");
if (addressClean) {
addressClean = addressClean.replace(/PO BOX \/ STREET\s+CITY \/ STATE \/ ZIP/g, '').trim();
if (addressClean === '') addressClean = null;
}
const interestedRaw = getVal("ARE YOU INTERESTED");
let interestedInUpdates: boolean | null = null;
let checkboxPending = true;
if (interestedRaw) {
if (/(✔|☑|X|✓)\s*YES/i.test(interestedRaw) || /YES\s*(✔|☑|X|✓)/i.test(interestedRaw)) {
interestedInUpdates = true;
checkboxPending = false;
} else if (/(✔|☑|X|✓)\s*NO/i.test(interestedRaw) || /NO\s*(✔|☑|X|✓)/i.test(interestedRaw)) {
interestedInUpdates = false;
checkboxPending = false;
}
}
if (checkboxPending && visualCheckboxResult !== null) {
interestedInUpdates = visualCheckboxResult;
checkboxPending = false;
}
const downPaymentRaw = getVal("DOWN PAYMENT")?.replace(/[^0-9,]/g, '') || null;
const downPaymentClean = downPaymentRaw ? downPaymentRaw.replace(/,/g, '') : null;
let dateOfIntro = null;
const dateMatch = filePath.match(/(\d{2})(\d{2})(\d{2})\.pdf$/);
if (dateMatch) dateOfIntro = `20${dateMatch[3]}-${dateMatch[1]}-${dateMatch[2]}`;
return {
file_name: fileName,
is_buyer_sheet: true,
name_company: nameCompany,
prospective_buyer: nameCompany ? nameCompany.split('/')[0].trim() : null,
company: null,
phone: phoneClean,
cell: cellClean,
email: getVal("EMAIL ADDRESS"),
address: addressClean,
state: null,
how_did_you_hear: getVal("HOW DID YOU HEAR"),
interested_in_updates: interestedInUpdates,
types_of_business_raw: getVal("TYPES OF BUSINESSES"),
background_experience: getVal("BACKGROUND"),
total_purchase_price: getVal("TOTAL PURCHASE PRICE"),
down_payment: downPaymentClean,
down_payment_raw: downPaymentRaw,
date_of_introduction: dateOfIntro,
_checkbox_pending: checkboxPending,
_parser: "deterministic",
_info_page: infoPageNum,
_ca_page: caPageNum
};
}
private async detectGraphicCheckbox(page: any, textItems: any[]): Promise<boolean | null> {
let yesX = null, noX = null, targetY = null;
for (const item of textItems) {
const textUpper = item.text.toUpperCase().trim();
if (textUpper.includes("YES")) { yesX = item.x; targetY = item.y; }
}
for (const item of textItems) {
const textUpper = item.text.toUpperCase().trim();
if (textUpper.includes("NO") && targetY !== null && Math.abs(item.y - targetY) < 5) noX = item.x;
}
if (yesX === null || noX === null || targetY === null) return null;
const opList = await page.getOperatorList();
let currentTransform = [1, 0, 0, 1, 0, 0];
for (let i = 0; i < opList.fnArray.length; i++) {
const fn = opList.fnArray[i];
const args = opList.argsArray[i];
if (fn === pdfjsLib.OPS.transform) currentTransform = args;
else if (
fn === pdfjsLib.OPS.paintImageXObject ||
fn === pdfjsLib.OPS.paintInlineImageXObject ||
fn === pdfjsLib.OPS.paintJpegXObject
) {
const width = Math.abs(currentTransform[0]);
const height = Math.abs(currentTransform[3]);
const imgX = currentTransform[4];
const imgY = currentTransform[5];
if (width < 40 && height < 40 && Math.abs(imgY - targetY) < 50) {
const distToYes = Math.abs(imgX - yesX);
const distToNo = Math.abs(imgX - noX);
return distToYes < distToNo;
}
}
}
return null;
}
}

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add_name_from_filename.ts Normal file
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#!/usr/bin/env npx tsx
/**
* add_name_from_filename.ts
*
* Traegt das Feld "name_from_filename" in eine bestehende buyers_vision.json
* nach, OHNE die Vision-Ergebnisse anzufassen und OHNE GPU/Neuverarbeitung.
* Nutzt exakt dieselbe Logik wie der vision_runner, damit die Werte
* identisch zu kuenftigen Laeufen sind.
*
* Aufruf:
* npx tsx add_name_from_filename.ts out_Z/buyers_vision.json
* npx tsx add_name_from_filename.ts out_Z/buyers_vision.json --overwrite
*
* Ohne --overwrite werden nur Datensaetze ergaenzt, die das Feld noch nicht
* (oder null) haben. Ein Backup .bak wird immer angelegt.
*/
import { promises as fsp } from "node:fs";
// IDENTISCH zur Funktion im vision_runner.ts
function nameFromFilename(fileName: string): string | null {
let s = fileName.replace(/\.pdf$/i, "");
s = s.replace(/\([^)]*\)/g, " ").replace(/\s+/g, " ").trim();
const comma = s.indexOf(",");
if (comma < 0) {
const first = s.replace(/\b\d{4,8}\b.*$/, "").trim();
return first.length >= 2 ? first : null;
}
const last = s.slice(0, comma).trim();
const rest = s.slice(comma + 1).trim();
const firstName = (rest.match(/^[A-Za-zÀ-ÿ.'-]+/) || [""])[0];
if (!last || !firstName) return null;
return `${last}, ${firstName}`;
}
async function main() {
const args = process.argv.slice(2);
const file = args.find((a) => !a.startsWith("--"));
const overwrite = args.includes("--overwrite");
if (!file) {
console.error("Aufruf: npx tsx add_name_from_filename.ts <buyers_vision.json> [--overwrite]");
process.exit(1);
}
const raw = await fsp.readFile(file, "utf8");
const records: Array<Record<string, unknown>> = JSON.parse(raw);
// Backup
await fsp.writeFile(file + ".bak", raw);
let added = 0, skipped = 0, unchanged = 0;
for (const r of records) {
const fn = r["file_name"] as string | undefined;
if (!fn) { skipped++; continue; }
const has = r["name_from_filename"] != null && r["name_from_filename"] !== "";
if (has && !overwrite) { unchanged++; continue; }
const val = nameFromFilename(fn);
if (r["name_from_filename"] === val) { unchanged++; continue; }
r["name_from_filename"] = val;
added++;
}
await fsp.writeFile(file, JSON.stringify(records, null, 2));
console.log(`Datensaetze: ${records.length}`);
console.log(`Feld gesetzt: ${added}`);
console.log(`schon vorhanden: ${unchanged}`);
console.log(`ohne file_name: ${skipped}`);
console.log(`Backup: ${file}.bak`);
}
main().catch((e) => { console.error(e); process.exit(1); });

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batch_runner.ts Normal file
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import * as fs from 'fs';
import * as path from 'path';
import { DeterministicParser } from './BuyerSheetParser';
async function main() {
// 1. Argument-Check
const args = process.argv.slice(2);
// Verzeichnis Parameter
const dirArgIndex = args.indexOf('--dir');
if (dirArgIndex === -1 || !args[dirArgIndex + 1]) {
console.error("Fehler: Bitte ein Verzeichnis angeben!");
console.error("Nutzung: npx tsx batch_runner.ts --dir \"/Pfad/zum/Ordner\" [--limit 10]");
process.exit(1);
}
const dirPath = args[dirArgIndex + 1];
// Limit Parameter
const limitArgIndex = args.indexOf('--limit');
let limit = -1; // -1 bedeutet: Kein Limit, alle verarbeiten
if (limitArgIndex !== -1 && args[limitArgIndex + 1]) {
limit = parseInt(args[limitArgIndex + 1], 10);
}
if (!fs.existsSync(dirPath) || !fs.statSync(dirPath).isDirectory()) {
console.error(`Fehler: Der Pfad "${dirPath}" existiert nicht oder ist kein Verzeichnis.`);
process.exit(1);
}
// 2. PDFs finden und Metadaten (für die Sortierung) auslesen
const filesWithStats = fs.readdirSync(dirPath)
.filter(f => f.toLowerCase().endsWith('.pdf'))
.map(file => {
const fullPath = path.join(dirPath, file);
return {
file,
fullPath,
// Änderungsdatum der Datei auslesen (in Millisekunden)
mtime: fs.statSync(fullPath).mtimeMs
};
});
if (filesWithStats.length === 0) {
console.log("Keine PDFs in diesem Verzeichnis gefunden.");
process.exit(0);
}
// 3. Absteigend sortieren (Neueste zuerst)
filesWithStats.sort((a, b) => b.mtime - a.mtime);
// 4. Limit anwenden (falls gesetzt)
const filesToProcess = limit > 0 ? filesWithStats.slice(0, limit) : filesWithStats;
console.log(`Starte Verarbeitung: ${filesToProcess.length} von ${filesWithStats.length} PDFs ausgewählt (Sortierung: Neueste zuerst)...\n`);
const parser = new DeterministicParser();
const finalResults = [];
let skippedCounter = 0;
// 5. PDFs iterieren
for (const fileObj of filesToProcess) {
const { file, fullPath } = fileObj;
process.stdout.write(`-> Verarbeite: ${file} ... `);
try {
const data = await parser.parsePdf(fullPath, file);
if (data === null) {
console.log("ÜBERSPRUNGEN (> 10 Seiten)");
skippedCounter++;
} else if (data.is_buyer_sheet === false) {
console.log("IMAGE SCAN (Zuweisung an Vision AI)");
finalResults.push(data);
} else {
console.log("ERFOLGREICH");
finalResults.push(data);
}
} catch (error) {
console.log("FEHLER BEIM PARSEN");
console.error(error);
}
}
// 6. JSON Export unter ./out/buyers.json
const outDir = path.join(process.cwd(), 'out');
if (!fs.existsSync(outDir)) {
fs.mkdirSync(outDir);
}
const outPath = path.join(outDir, 'buyers.json');
fs.writeFileSync(outPath, JSON.stringify(finalResults, null, 2), 'utf-8');
console.log(`\n=================================================`);
console.log(`Zusammenfassung:`);
console.log(` Verarbeitet: ${finalResults.length}`);
console.log(` Verworfen (>10 Seiten): ${skippedCounter}`);
console.log(` Export gespeichert in: ${outPath}`);
console.log(`=================================================`);
}
main();

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# llama-server für Qwen3.6 Vision — NVIDIA RTX PRO 6000 Blackwell (sm_120)
#
# WICHTIG:
# - Muss aus aktuellem Source gebaut werden: Qwen3.6 nutzt ein neues
# Rope-Encoding (rope.dimension_sections 3 statt 4), alte Images/Builds
# brechen mit "wrong array length".
# - Blackwell braucht CUDA >= 12.8. KEIN CUDA 13.2 verwenden — erzeugt
# mit Qwen3.6 Gibberish (bekannter NVIDIA-Bug).
FROM nvidia/cuda:12.8.1-devel-ubuntu24.04 AS build
RUN apt-get update && apt-get install -y --no-install-recommends \
git cmake build-essential libcurl4-openssl-dev ca-certificates \
&& rm -rf /var/lib/apt/lists/*
RUN git clone --depth 1 https://github.com/ggml-org/llama.cpp /src
# 120 = Blackwell (RTX PRO 6000). Für andere Karten anpassen.
RUN cmake /src -B /build \
-DGGML_CUDA=ON \
-DCMAKE_CUDA_ARCHITECTURES=120 \
-DGGML_CUDA_FORCE_CUBLAS=OFF \
-DBUILD_SHARED_LIBS=OFF \
-DLLAMA_CURL=ON \
&& cmake --build /build --config Release -j --target llama-server
FROM nvidia/cuda:12.8.1-runtime-ubuntu24.04
RUN apt-get update && apt-get install -y --no-install-recommends \
libcurl4 libgomp1 curl ca-certificates \
&& rm -rf /var/lib/apt/lists/*
COPY --from=build /build/bin/llama-server /usr/local/bin/llama-server
EXPOSE 8000
ENTRYPOINT ["llama-server"]

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# llama-server für Qwen3.6 Vision — AMD Radeon AI Pro R9700, Vulkan-Backend
#
# Muss aus aktuellem Source gebaut werden (Qwen3.6-Rope-Änderung, s. Dockerfile.cuda).
# Vulkan statt ROCm — hat sich bei Vision als stabiler erwiesen.
FROM ubuntu:24.04 AS build
RUN apt-get update && apt-get install -y --no-install-recommends \
git cmake build-essential libcurl4-openssl-dev ca-certificates \
libvulkan-dev glslc spirv-headers \
&& rm -rf /var/lib/apt/lists/*
RUN git clone --depth 1 https://github.com/ggml-org/llama.cpp /src
RUN cmake /src -B /build \
-DGGML_VULKAN=ON \
-DBUILD_SHARED_LIBS=OFF \
-DLLAMA_CURL=ON \
&& cmake --build /build --config Release -j --target llama-server
FROM ubuntu:24.04
# mesa-vulkan-drivers = RADV-Treiber im Container (GPU via /dev/dri durchgereicht)
RUN apt-get update && apt-get install -y --no-install-recommends \
libvulkan1 mesa-vulkan-drivers vulkan-tools \
libcurl4 libgomp1 curl ca-certificates \
&& rm -rf /var/lib/apt/lists/*
COPY --from=build /build/bin/llama-server /usr/local/bin/llama-server
EXPOSE 8000
ENTRYPOINT ["llama-server"]

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@@ -1,47 +1,142 @@
# llama.cpp + Gemma-4-12B (Vision) auf CUDA (AWS G7e / RTX PRO 6000). # llama-server für Qwen3.6 Vision — zwei Profile:
# docker compose --profile cuda up -d --build (EC2, RTX PRO 6000 Blackwell)
# docker compose --profile vulkan up -d --build (inhouse, Radeon AI Pro R9700)
# #
# Bewusst SCHLANK gehalten: keine ROCm/Vulkan-Workarounds. Wir testen, ob # Modelle nach ./models legen (Haupt-GGUF + zugehöriger mmproj aus demselben Repo!):
# CUDA die Instabilitaeten von vornherein vermeidet. Nur die inhaltlich noetigen # CUDA: unsloth/Qwen3.6-27B-GGUF → Qwen3.6-27B-UD-Q4_K_XL.gguf + mmproj-BF16.gguf
# Flags (--reasoning off gegen leeres content) bleiben. # Vulkan: unsloth/Qwen3.6-35B-A3B-GGUF → Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf + mmproj-BF16.gguf
# #
# Voraussetzung: DLAMI mit NVIDIA Container Toolkit (docker --gpus all funktioniert). # Bewusst KEIN MTP: --mmproj + MTP ist laut Unsloth nicht unterstützt und hat
# # offene OOM-/Hänger-Bugs (llama.cpp #23371, #23430). Für Batch-Extraktion
# Start: docker compose -f docker-compose-cuda.yml up -d # irrelevant, da die Zeit im Image-Encoding steckt, nicht in der Generierung.
# Logs: docker compose -f docker-compose-cuda.yml logs -f
services: services:
llamacpp-gemma12b: llama-cuda:
image: ghcr.io/ggml-org/llama.cpp:server-cuda profiles: ["cuda"]
container_name: llamacpp-gemma12b build:
restart: unless-stopped context: .
init: true dockerfile: Dockerfile.cuda
# GPU-Zugriff ueber das NVIDIA Container Toolkit ports:
- "8000:8000"
volumes:
- ./models:/models
deploy: deploy:
resources: resources:
reservations: reservations:
devices: devices:
- driver: nvidia - driver: nvidia
count: 1 count: all
capabilities: [gpu] capabilities: [gpu]
ports:
- "8000:8080"
volumes:
- ~/.cache/llama.cpp:/root/.cache/llama.cpp
command: command:
- -hf - -m
- unsloth/gemma-4-12b-it-GGUF:UD-Q4_K_XL - /models/Qwen3.6-27B-UD-Q4_K_XL.gguf
- --mmproj
- /models/mmproj-BF16.gguf
- --host - --host
- 0.0.0.0 - 0.0.0.0
- --port - --port
- "8080" - "8000"
- --alias
- qwen3.6
- -ngl - -ngl
- "99" - "99"
- --ctx-size - -fa
- "16384" - "on"
- -c
- "65536"
- --parallel - --parallel
- "1" - "1"
- --jinja - --jinja
- --reasoning # Erlernte Stabilitäts-Settings (Vision + Checkpoints = OOM-Bug):
- "off" - --ctx-checkpoints
- "0"
# Qwen-VL braucht min. 1024 Image-Tokens für korrektes Grounding:
- --image-min-tokens
- "1024"
- --image-max-tokens
- "4096"
# Extraktion: niedrige Temperatur, kein Repeat-Penalty
- --temp
- "0.1"
- --top-p
- "0.95"
- --top-k
- "20"
- --repeat-penalty
- "1.0"
healthcheck:
test: ["CMD", "curl", "-sf", "http://localhost:8000/health"]
interval: 15s
timeout: 5s
retries: 40
start_period: 60s
restart: unless-stopped
llama-vulkan:
profiles: ["vulkan"]
build:
context: .
dockerfile: Dockerfile.vulkan
ports:
- "8000:8000"
volumes:
- ./models:/models
devices:
- /dev/dri:/dev/dri
- /dev/kfd:/dev/kfd
# Numerische HOST-GIDs verwenden — Namen wie "render" existieren im
# Container-Image nicht. GIDs prüfen mit: getent group video render
group_add:
- "44" # video (Host-GID ggf. anpassen)
- "991" # render (Host-GID ggf. anpassen)
security_opt:
- seccomp:unconfined
command:
- -m
- /models/Qwen3.6-35B-A3B-UD-Q4_K_M.gguf
- --mmproj
- /models/mmproj-BF16.gguf
- --host
- 0.0.0.0
- --port
- "8000"
- --alias - --alias
- gemma-4-12b - qwen3.6
- -ngl
- "99"
- -fa
- "on"
- -c
- "40960"
- --parallel
- "1"
# KV-Cache quantisieren — 32GB VRAM, 35B-A3B + mmproj + Bildkontext:
- -ctk
- q8_0
- -ctv
- q8_0
- --jinja
- --ctx-checkpoints
- "0"
- --image-min-tokens
- "1024"
- --image-max-tokens
- "6144"
- --temp
- "0.1"
- --top-p
- "0.95"
- --top-k
- "20"
- --repeat-penalty
- "1.0"
# NOTFALL-Fallback bei Vision-Hängern/OOM unter RADV — mmproj auf CPU,
# Bildverarbeitung wird DEUTLICH langsamer. Nur aktivieren wenn nötig:
# - --no-mmproj-offload
healthcheck:
test: ["CMD", "curl", "-sf", "http://localhost:8000/health"]
interval: 15s
timeout: 5s
retries: 40
start_period: 120s
restart: unless-stopped

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import * as pdfjsLib from 'pdfjs-dist/legacy/build/pdf.js';
import * as fs from 'fs';
async function debugText(filePath: string) {
console.log(`\nLese PDF für Text-Debugging: ${filePath}`);
const dataBuffer = fs.readFileSync(filePath);
const loadingTask = pdfjsLib.getDocument({ data: new Uint8Array(dataBuffer) });
const pdfDocument = await loadingTask.promise;
console.log(`Anzahl Seiten: ${pdfDocument.numPages}`);
// Wir nehmen uns Seite 1 vor
const page = await pdfDocument.getPage(1);
const textContent = await page.getTextContent();
console.log(`\n--- RAW TEXT ITEMS (Die ersten 40 Fragmente) ---`);
for (let i = 0; i < Math.min(40, textContent.items.length); i++) {
const item = textContent.items[i] as any;
console.log(`Y: ${item.transform[5].toFixed(1).padStart(6)} | X: ${item.transform[4].toFixed(1).padStart(6)} | Text: "${item.str}"`);
}
// Unsere Sortier- und Bereinigungslogik anwenden
const sortedItems = textContent.items
.map((item: any) => ({
text: item.str,
x: item.transform[4],
y: item.transform[5]
}))
.sort((a: any, b: any) => {
if (Math.abs(b.y - a.y) > 5) return b.y - a.y;
return a.x - b.x;
});
const textRaw = sortedItems.map((i: any) => i.text).join('').toUpperCase().replace(/[^A-Z]/g, '');
console.log(`\n--- BEREINIGTER SUCH-STRING (Die ersten 200 Zeichen) ---`);
console.log(textRaw.substring(0, 200));
console.log(`\nEnthält 'BUYERINFORMATIONSHEET'? -> ${textRaw.includes('BUYERINFORMATIONSHEET')}`);
}
const args = process.argv.slice(2);
const pdfArgIndex = args.indexOf('--pdf');
if (pdfArgIndex !== -1 && args[pdfArgIndex + 1]) {
debugText(args[pdfArgIndex + 1]).catch(console.error);
} else {
console.error("Bitte --pdf Parameter angeben.");
}

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#!/usr/bin/env npx tsx
/**
* enrich_and_anonymize.ts
*
* Zwei Aufgaben in einem Durchlauf auf einer buyers_vision.json:
* 1) Ergaenzt "name_from_filename" (falls fehlt) UND "_letter"
* (der A-Z-Unterordner, in dem das PDF liegt) fuer die PDF-Pfad-Aufloesung.
* 2) Optional (--anonymize): ersetzt PII-Felder (phone, cell, email, address)
* durch konsistente Faker-Dummydaten, damit das JSON weitergegeben werden
* kann. Leere Felder bleiben leer. Gleicher Originalwert -> gleicher Dummy.
*
* Der _letter wird aus dem Nachnamen (erstes Zeichen von name_from_filename)
* abgeleitet - das entspricht der Ordnerstruktur "...Buyers NDA's A-Z/<Letter>/".
*
* Aufruf:
* npx tsx enrich_and_anonymize.ts buyers_vision.json
* npx tsx enrich_and_anonymize.ts buyers_vision.json --anonymize
* npx tsx enrich_and_anonymize.ts buyers_vision.json --anonymize --overwrite
*/
import { promises as fsp } from "node:fs";
import { faker } from "@faker-js/faker";
faker.seed(1234); // reproduzierbar
// IDENTISCH zur Funktion im vision_runner.ts
function nameFromFilename(fileName: string): string | null {
let s = fileName.replace(/\.pdf$/i, "");
s = s.replace(/\([^)]*\)/g, " ").replace(/\s+/g, " ").trim();
const comma = s.indexOf(",");
if (comma < 0) {
const first = s.replace(/\b\d{4,8}\b.*$/, "").trim();
return first.length >= 2 ? first : null;
}
const last = s.slice(0, comma).trim();
const rest = s.slice(comma + 1).trim();
const firstName = (rest.match(/^[A-Za-zÀ-ÿ.'-]+/) || [""])[0];
if (!last || !firstName) return null;
return `${last}, ${firstName}`;
}
/** A-Z-Unterordner aus dem Nachnamen. Fallback: erstes Zeichen des Dateinamens. */
function letterFromName(fileName: string, nameFF: string | null): string | null {
const src = (nameFF ?? fileName).trim();
const ch = src.charAt(0).toUpperCase();
return /[A-Z]/.test(ch) ? ch : null;
}
const isEmpty = (v: unknown) => v === null || v === undefined || v === "";
// Konsistenz-Caches: gleicher Originalwert -> gleicher Dummy
const caches: Record<string, Map<string, string>> = {
phone: new Map(), cell: new Map(), email: new Map(), address: new Map(),
};
function fakePII(field: string, value: string): string {
const key = value.trim().toLowerCase();
const cache = caches[field];
if (cache.has(key)) return cache.get(key)!;
let dummy: string;
switch (field) {
case "phone":
case "cell": dummy = faker.phone.number(); break;
case "email": dummy = faker.internet.email(); break;
case "address": dummy = faker.location.streetAddress({ useFullAddress: true }); break;
default: dummy = faker.lorem.word();
}
cache.set(key, dummy);
return dummy;
}
async function main() {
const args = process.argv.slice(2);
const file = args.find((a) => !a.startsWith("--"));
const overwrite = args.includes("--overwrite");
const anonymize = args.includes("--anonymize");
if (!file) {
console.error("Aufruf: npx tsx enrich_and_anonymize.ts <buyers_vision.json> [--anonymize] [--overwrite]");
process.exit(1);
}
const raw = await fsp.readFile(file, "utf8");
const records: Array<Record<string, unknown>> = JSON.parse(raw);
await fsp.writeFile(file + ".bak", raw);
let nameSet = 0, letterSet = 0, anonFields = 0;
const PII = ["phone", "cell", "email", "address"];
for (const r of records) {
const fn = r["file_name"] as string | undefined;
if (!fn) continue;
// name_from_filename
const hasName = !isEmpty(r["name_from_filename"]);
if (!hasName || overwrite) {
const val = nameFromFilename(fn);
if (r["name_from_filename"] !== val) { r["name_from_filename"] = val; nameSet++; }
}
// _letter (A-Z-Unterordner)
const hasLetter = !isEmpty(r["_letter"]);
if (!hasLetter || overwrite) {
const lv = letterFromName(fn, (r["name_from_filename"] as string | null) ?? null);
if (r["_letter"] !== lv) { r["_letter"] = lv; letterSet++; }
}
// Anonymisierung
if (anonymize) {
for (const f of PII) {
if (!isEmpty(r[f])) { r[f] = fakePII(f, String(r[f])); anonFields++; }
}
}
}
await fsp.writeFile(file, JSON.stringify(records, null, 2));
console.log(`Datensaetze: ${records.length}`);
console.log(`name_from_filename: ${nameSet} gesetzt`);
console.log(`_letter: ${letterSet} gesetzt`);
if (anonymize) console.log(`PII anonymisiert: ${anonFields} Felder`);
console.log(`Backup: ${file}.bak`);
}
main().catch((e) => { console.error(e); process.exit(1); });

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import * as pdfjsLib from 'pdfjs-dist/legacy/build/pdf.js';
import * as fs from 'fs';
async function analyzeImages(filePath: string) {
console.log(`\nLese PDF für Bild-Analyse: ${filePath}`);
const dataBuffer = fs.readFileSync(filePath);
const loadingTask = pdfjsLib.getDocument({ data: new Uint8Array(dataBuffer) });
const pdfDocument = await loadingTask.promise;
// Wir analysieren nur Seite 1
const page = await pdfDocument.getPage(1);
const viewport = page.getViewport({ scale: 1.0 });
console.log(`Seitengröße: Breite = ${viewport.width.toFixed(2)}, Höhe = ${viewport.height.toFixed(2)}\n`);
const opList = await page.getOperatorList();
// Um die Koordinaten zu berechnen, müssen wir den Grafik-Status (Stack) verfolgen
let transformStack: number[][] = [[1, 0, 0, 1, 0, 0]]; // Standard-Matrix
let currentTransform = [1, 0, 0, 1, 0, 0];
let imageCount = 0;
console.log("--- GEFUNDENE BILDER AUF SEITE 1 ---");
for (let i = 0; i < opList.fnArray.length; i++) {
const fn = opList.fnArray[i];
const args = opList.argsArray[i];
// Status speichern (q)
if (fn === pdfjsLib.OPS.save) {
transformStack.push([...currentTransform]);
}
// Status wiederherstellen (Q)
else if (fn === pdfjsLib.OPS.restore) {
if (transformStack.length > 0) {
currentTransform = transformStack.pop()!;
}
}
// Transformation anwenden (cm) - In PDFs werden Matrizen multipliziert,
// für die einfache Bildanalyse reicht oft der letzte Transform-Befehl vor dem Bild,
// da dieser die Skalierung (Breite/Höhe) und Position (X/Y) des 1x1 Pixel Objekts setzt.
else if (fn === pdfjsLib.OPS.transform) {
currentTransform = args;
}
// Wenn ein Bild gezeichnet wird!
else if (
fn === pdfjsLib.OPS.paintImageXObject ||
fn === pdfjsLib.OPS.paintInlineImageXObject ||
fn === pdfjsLib.OPS.paintJpegXObject
) {
imageCount++;
// In der PDF-Matrix:
// currentTransform[0] = Skalierung X (entspricht der Bild-Breite)
// currentTransform[3] = Skalierung Y (entspricht der Bild-Höhe)
// currentTransform[4] = Position X
// currentTransform[5] = Position Y
const width = currentTransform[0];
const height = currentTransform[3];
const x = currentTransform[4];
const y = currentTransform[5];
const isPageFilling = (width >= viewport.width - 10 && height >= viewport.height - 10);
const mark = isPageFilling ? " <-- SEITENFÜLLENDER SCAN / HINTERGRUND" : "";
console.log(`Bild ${imageCount}:`);
console.log(` Position: X = ${x.toFixed(2)}, Y = ${y.toFixed(2)}`);
console.log(` Größe: Breite = ${width.toFixed(2)}, Höhe = ${height.toFixed(2)}${mark}`);
console.log(` Interner Name: ${args[0]}`);
console.log(`--------------------------------------------------`);
}
}
if (imageCount === 0) {
console.log("Keine Bilder gefunden. Das Dokument besteht rein aus Vektoren und Text.");
} else {
console.log(`\nInsgesamt ${imageCount} Bild(er) gefunden.`);
}
}
// Aufruf mit dem Pfad aus den Parametern
const args = process.argv.slice(2);
const pdfArgIndex = args.indexOf('--pdf');
if (pdfArgIndex !== -1 && args[pdfArgIndex + 1]) {
analyzeImages(args[pdfArgIndex + 1]).catch(console.error);
} else {
console.error("Bitte --pdf Parameter angeben.");
}

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#!/usr/bin/env npx tsx
/**
* notes_filter.ts — Notes-PDFs aussortieren und Seed-JSON erzeugen
*
* 1. Scannt alle PDFs unter --pdf-root rekursiv.
* 2. "Notes"-Dateien: prüft, ob eine Hauptdatei desselben Käufers existiert
* (Schlüssel: "Nachname, Vorname" — Datum wird ignoriert, da es abweicht).
* → mit Gegenstück: überspringen. Ohne Gegenstück: Report (out/notes_orphans.txt).
* 3. Schreibt Seed-JSON mit ALLEN Nicht-Notes-PDFs. Vorhandene Einträge aus
* --buyers (Gleis A / Vision) werden unverändert übernommen, neue Dateien
* bekommen einen Eintrag mit is_buyer_sheet:false (→ vision_runner nimmt sie).
*
* Aufruf:
* npx tsx notes_filter.ts \
* --pdf-root "/mnt/bizmatch-nas/AA Buyers NDA's/Buyers NDA's A-Z" \
* --buyers out/buyers.json \
* --out out/buyers_seed.json
*/
import * as fsp from "node:fs/promises";
import * as fs from "node:fs";
import * as path from "node:path";
import * as os from "node:os";
interface BuyerRecord { file_name: string; is_buyer_sheet: boolean; [k: string]: unknown }
function parseArgs() {
const a = process.argv.slice(2);
const get = (f: string, d: string | null = null) => {
const i = a.indexOf(f);
return i >= 0 && a[i + 1] !== undefined ? a[i + 1] : d;
};
const pdfRoot = get("--pdf-root");
if (!pdfRoot) { console.error("Fehler: --pdf-root fehlt."); process.exit(1); }
return {
pdfRoot: pdfRoot.replace(/^~(?=\/)/, os.homedir()),
buyers: get("--buyers", "out/buyers.json")!,
out: get("--out", "out/buyers_seed.json")!,
};
}
/** Erkennt "Notes", "Note" und verklebte Varianten ("Notesb102312").
* Es wird nur der Teil NACH dem ersten Komma durchsucht, damit Nachnamen
* wie "Note, John" nicht fälschlich als Notes-Datei gelten. */
function isNotes(base: string): boolean {
const comma = base.indexOf(",");
const scope = comma >= 0 ? base.slice(comma + 1) : base;
return /\bnotes?[a-z]?\d*\b/i.test(scope);
}
/** "Stone, Mike via Anna Stone 031220 Notes.pdf" → "stone,mike" */
function nameKey(base: string): string {
let s = base.replace(/\.pdf$/i, "");
s = s.replace(/\bnotes?[a-z]?\d*\b/gi, " "); // Note/Notes/Notesb102312 raus
s = s.replace(/\b\d{4,8}\b/g, " "); // Datums-Tokens raus
s = s.replace(/\s+/g, " ").trim();
const comma = s.indexOf(",");
if (comma < 0) return s.toLowerCase(); // Fallback: ganzer Rest
const last = s.slice(0, comma).trim();
const first = (s.slice(comma + 1).trim().split(" ")[0] ?? "");
return `${last},${first}`.toLowerCase();
}
async function collectPdfs(root: string): Promise<string[]> {
const result: string[] = [];
const stack = [root];
while (stack.length) {
const dir = stack.pop()!;
let entries: fs.Dirent[];
try { entries = await fsp.readdir(dir, { withFileTypes: true }); } catch { continue; }
for (const e of entries) {
const p = path.join(dir, e.name);
if (e.isDirectory()) stack.push(p);
else if (e.isFile() && e.name.toLowerCase().endsWith(".pdf")) result.push(e.name);
}
}
return result;
}
const EMPTY_FIELDS = {
name_company: null, prospective_buyer: null, company: null, phone: null,
cell: null, email: null, address: null, state: null, how_did_you_hear: null,
interested_in_updates: null, types_of_business_raw: null,
background_experience: null, total_purchase_price: null, down_payment: null,
down_payment_raw: null, date_of_introduction: null,
};
async function main() {
const args = parseArgs();
console.error(`Scanne ${args.pdfRoot} ...`);
const all = await collectPdfs(args.pdfRoot);
const notesFiles = all.filter(isNotes);
const mainFiles = all.filter((f) => !isNotes(f));
console.error(`${all.length} PDFs: ${mainFiles.length} Hauptdateien, ${notesFiles.length} Notes-Dateien`);
// Notes-Abgleich
const mainKeys = new Set(mainFiles.map(nameKey));
const skippable: string[] = [];
const orphans: string[] = [];
for (const n of notesFiles) (mainKeys.has(nameKey(n)) ? skippable : orphans).push(n);
console.error(`Notes mit Gegenstück (werden ignoriert): ${skippable.length}`);
console.error(`Notes OHNE Gegenstück (bitte prüfen): ${orphans.length}`);
if (orphans.length) {
const orphanPath = path.join(path.dirname(args.out), "notes_orphans.txt");
await fsp.mkdir(path.dirname(orphanPath), { recursive: true });
await fsp.writeFile(orphanPath, orphans.sort().join("\n") + "\n");
console.error(`${orphanPath}`);
}
// Vorhandene Ergebnisse laden
const existing = new Map<string, BuyerRecord>();
try {
const prev: BuyerRecord[] = JSON.parse(await fsp.readFile(args.buyers, "utf8"));
for (const r of prev) existing.set(r.file_name, r);
} catch {
console.error(`Hinweis: ${args.buyers} nicht gefunden — starte mit leerem Bestand.`);
}
// In die Extraktion gehen: alle Hauptdateien + Notes OHNE Gegenstück.
// Notes MIT Gegenstück fallen weg (auch deren alte Einträge).
const includeFiles = [...mainFiles, ...orphans];
let seeded = 0, carried = 0;
const out: BuyerRecord[] = includeFiles.sort().map((f) => {
const prev = existing.get(f);
if (prev) { carried++; return prev; }
seeded++;
return { file_name: f, is_buyer_sheet: false, ...EMPTY_FIELDS, _parser: "seed" };
});
await fsp.mkdir(path.dirname(args.out), { recursive: true });
await fsp.writeFile(args.out, JSON.stringify(out, null, 2));
console.error(
`Seed geschrieben: ${out.length} Einträge (${carried} übernommen, ${seeded} neu, davon ${orphans.length} Orphan-Notes) → ${args.out}`
);
}
main().catch((e) => { console.error("Abbruch:", e instanceof Error ? e.message : e); process.exit(1); });

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{
"dependencies": {
"@faker-js/faker": "^10.5.0",
"canvas": "^3.2.3",
"pdf-parse": "^1.1.1",
"pdfjs-dist": "^3.11.174"
},
"devDependencies": {
"@types/node": "^26.1.1",
"@types/pdf-parse": "^1.1.5",
"ts-node": "^10.9.2",
"typescript": "^7.0.2"
}
}

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// run_parser.ts
import { DeterministicParser } from './BuyerSheetParser.ts';
async function main() {
// Einfaches Auslesen der Kommandozeilenargumente
const args = process.argv.slice(2);
const pdfArgIndex = args.indexOf('--pdf');
if (pdfArgIndex === -1 || !args[pdfArgIndex + 1]) {
console.error("Usage: npx ts-node run_parser.ts --pdf <path_to_pdf>");
process.exit(1);
}
const pdfPath = args[pdfArgIndex + 1];
const parser = new DeterministicParser();
try {
console.log(`Lese PDF: ${pdfPath} ...\n`);
const result = await parser.parsePdf(pdfPath);
// JSON formatiert und farbig (optional) ausgeben
console.log(JSON.stringify(result, null, 2));
} catch (error) {
console.error("Fehler beim Parsen des PDFs:", error);
}
}
main();

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#!/usr/bin/env npx tsx
/**
* vision_runner.ts — Gleis B: Vision-LLM-Extraktion für Buyer Information Sheets
*
* Liest out/buyers.json (Ergebnis von Gleis A / batch_runner.ts), nimmt alle
* Einträge mit is_buyer_sheet === false, rendert die PDF-Seiten via pdftoppm
* (poppler-utils) zu PNGs und schickt sie an einen llama-server
* (OpenAI-kompatibel, Qwen3.6 + mmproj).
*
* Prinzip: Das VLM TRANSKRIBIERT nur (Rohwerte, verbatim). Sämtliche
* Normalisierung (Leer-Marker, State, down_payment, Datum) passiert
* deterministisch hier in TypeScript — identische Regeln wie Gleis A.
*
* Aufruf (AMD/Vulkan, inhouse):
* npx tsx vision_runner.ts \
* --input out/buyers.json \
* --pdf-root "/mnt/bizmatch-nas/AA Buyers NDA's/Buyers NDA's A-Z" \
* --api http://localhost:8000/v1 --limit 5
*
* Aufruf (NVIDIA/CUDA, EC2):
* npx tsx vision_runner.ts --input out/buyers.json \
* --pdf-root ~/data --api http://localhost:8000/v1 --limit 5
*
* Voraussetzungen: Node >= 18 (fetch), poppler-utils (pdftoppm) installiert.
*
* Outputs:
* out/buyers_vision.json — nur die Vision-Ergebnisse (Resume-Datei)
* out/buyers_merged.json — Gleis A + Gleis B zusammengeführt
*/
import { execFile } from "node:child_process";
import { promisify } from "node:util";
import * as fsp from "node:fs/promises";
import * as fs from "node:fs";
import * as path from "node:path";
import * as os from "node:os";
const execFileP = promisify(execFile);
// ---------------------------------------------------------------------------
// CLI
// ---------------------------------------------------------------------------
interface Args {
pdfRoot: string;
api: string;
limit: number;
only: string | null;
dpi: number | "auto";
maxPages: number;
force: boolean;
reprocessMissing: boolean;
outDir: string;
timeoutMs: number;
}
function parseArgs(): Args {
const a = process.argv.slice(2);
const get = (flag: string, def: string | null = null): string | null => {
const i = a.indexOf(flag);
return i >= 0 && a[i + 1] !== undefined ? a[i + 1] : def;
};
const pdfRoot = get("--pdf-root");
const api = (get("--api", "http://localhost:8000/v1") || "").replace(/\/+$/, "");
if (!pdfRoot) {
console.error("Fehler: --pdf-root <Verzeichnis> ist erforderlich.");
process.exit(1);
throw new Error("unreachable"); // hilft dem TS-Narrowing
}
return {
pdfRoot: pdfRoot.replace(/^~(?=\/)/, os.homedir()),
api,
limit: parseInt(get("--limit", "0")!, 10) || 0,
only: get("--only"),
dpi: ((): number | "auto" => {
const v = get("--dpi", "auto")!;
return v === "auto" ? "auto" : parseInt(v, 10) || 150;
})(),
// Nur PDFs mit HOECHSTENS so vielen Seiten werden per Vision gescannt.
maxPages: parseInt(get("--max-pages", "10")!, 10) || 10,
force: a.includes("--force"),
reprocessMissing: a.includes("--reprocess-missing"),
outDir: get("--out-dir", "out")!,
timeoutMs: (parseInt(get("--timeout", "180")!, 10) || 180) * 1000,
};
}
// ---------------------------------------------------------------------------
// Typen
// ---------------------------------------------------------------------------
interface BuyerRecord {
file_name: string;
is_buyer_sheet: boolean;
[k: string]: unknown;
}
/** Rohantwort des VLM — alles verbatim, Normalisierung erfolgt in TS. */
interface VisionRaw {
doc_type: "buyer_sheet" | "ca_only" | "other";
info_sheet_count: number;
info_page: number | null;
ca_page: number | null;
notes_page: number | null;
name_company: string | null;
prospective_buyer: string | null;
company: string | null;
phone: string | null;
cell: string | null;
email: string | null;
address: string | null;
state: string | null;
how_did_you_hear: string | null;
interested_in_updates: string | null;
types_of_business_raw: string | null;
notes_business_raw: string | null;
background_experience: string | null;
total_purchase_price: string | null;
down_payment_raw: string | null;
date_of_introduction_raw: string | null;
}
// ---------------------------------------------------------------------------
// Normalisierung — identisch zu Gleis A halten!
// (Falls BuyerSheetParser.ts diese Funktionen exportiert, stattdessen
// importieren, damit beide Gleise garantiert dieselbe Logik nutzen.)
// ---------------------------------------------------------------------------
const NULL_MARKERS = /^(n|na|n\/a|none|nil|x|-+|\.+)$/i;
function cleanStr(v: string | null | undefined): string | null {
if (v == null) return null;
const t = String(v).replace(/\s+/g, " ").trim();
if (!t || NULL_MARKERS.test(t)) return null;
return t;
}
const STATE_MAP: Record<string, string> = {
alabama: "AL", alaska: "AK", arizona: "AZ", arkansas: "AR", california: "CA",
colorado: "CO", connecticut: "CT", delaware: "DE", florida: "FL", georgia: "GA",
hawaii: "HI", idaho: "ID", illinois: "IL", indiana: "IN", iowa: "IA",
kansas: "KS", kentucky: "KY", louisiana: "LA", maine: "ME", maryland: "MD",
massachusetts: "MA", michigan: "MI", minnesota: "MN", mississippi: "MS",
missouri: "MO", montana: "MT", nebraska: "NE", nevada: "NV",
"new hampshire": "NH", "new jersey": "NJ", "new mexico": "NM",
"new york": "NY", "north carolina": "NC", "north dakota": "ND", ohio: "OH",
oklahoma: "OK", oregon: "OR", pennsylvania: "PA", "rhode island": "RI",
"south carolina": "SC", "south dakota": "SD", tennessee: "TN", texas: "TX",
utah: "UT", vermont: "VT", virginia: "VA", washington: "WA",
"west virginia": "WV", wisconsin: "WI", wyoming: "WY",
"district of columbia": "DC", "washington dc": "DC",
};
const STATE_CODES = new Set(Object.values(STATE_MAP));
function normState(v: string | null): string | null {
const c = cleanStr(v);
if (!c) return null;
const up = c.toUpperCase().replace(/\./g, "");
if (up.length === 2 && STATE_CODES.has(up)) return up;
const full = STATE_MAP[c.toLowerCase().replace(/\./g, "")];
return full ?? c; // unbekannt: bereinigt durchreichen, nicht raten
}
/** "$350,000" → "350000"; "1.5M" → "1500000"; sonst null + raw. */
function normDownPayment(raw: string | null): { value: string | null; raw: string | null } {
const c = cleanStr(raw);
if (!c) return { value: null, raw: null };
const m = c.match(/^\$?\s*(\d[\d,]*(?:\.\d+)?)\s*([kKmM])?\s*$/);
if (!m) return { value: null, raw: c };
let num = parseFloat(m[1].replace(/,/g, ""));
if (m[2]) num *= /k/i.test(m[2]) ? 1_000 : 1_000_000;
if (!Number.isFinite(num) || num <= 0) return { value: null, raw: c };
return { value: String(Math.round(num)), raw: c };
}
const MONTHS: Record<string, number> = {
jan: 1, feb: 2, mar: 3, apr: 4, may: 5, jun: 6,
jul: 7, aug: 8, sep: 9, oct: 10, nov: 11, dec: 12,
};
function isoDate(y: number, mo: number, d: number): string | null {
if (y < 100) y += 2000;
if (y < 1990 || y > 2100 || mo < 1 || mo > 12 || d < 1 || d > 31) return null;
return `${y}-${String(mo).padStart(2, "0")}-${String(d).padStart(2, "0")}`;
}
/** US-Formate: 6/25/26, 06-25-2026, "June 25, 2026" → YYYY-MM-DD. */
function normDate(raw: string | null): string | null {
let c = cleanStr(raw);
if (!c) return null;
// Leerzeichen um Trenner entfernen: "09 / 13 / 2021" -> "09/13/2021"
c = c.replace(/\s*([\/\-.])\s*/g, "$1").trim();
let m = c.match(/^(\d{1,2})[\/\-.](\d{1,2})[\/\-.](\d{2}|\d{4})$/);
if (m) return isoDate(parseInt(m[3], 10), parseInt(m[1], 10), parseInt(m[2], 10));
m = c.match(/^([A-Za-z]{3,9})\.?\s+(\d{1,2})(?:st|nd|rd|th)?,?\s+(\d{2}|\d{4})$/);
if (m) {
const mo = MONTHS[m[1].slice(0, 3).toLowerCase()];
if (mo) return isoDate(parseInt(m[3], 10), mo, parseInt(m[2], 10));
}
m = c.match(/^(\d{4})-(\d{2})-(\d{2})$/);
if (m) return isoDate(parseInt(m[1], 10), parseInt(m[2], 10), parseInt(m[3], 10));
return null;
}
// ---------------------------------------------------------------------------
// PDF-Index (rekursiv, Basename → voller Pfad) + Rendering
// ---------------------------------------------------------------------------
async function buildPdfIndex(root: string): Promise<Map<string, string>> {
const index = new Map<string, string>();
const stack = [root];
while (stack.length) {
const dir = stack.pop()!;
let entries: fs.Dirent[];
try {
entries = await fsp.readdir(dir, { withFileTypes: true });
} catch {
continue;
}
for (const e of entries) {
const p = path.join(dir, e.name);
if (e.isDirectory()) stack.push(p);
else if (e.isFile() && e.name.toLowerCase().endsWith(".pdf")) {
if (!index.has(e.name)) index.set(e.name, p);
}
}
}
return index;
}
/** Seitenzahl via pdfinfo (poppler-utils). -1 bei Fehler/beschaedigtem PDF. */
async function pdfPageCount(pdfPath: string): Promise<number> {
try {
const { stdout } = await execFileP("pdfinfo", [pdfPath], { timeout: 30_000 });
const m = stdout.match(/^Pages:\s+(\d+)/m);
return m ? parseInt(m[1], 10) : -1;
} catch {
return -1;
}
}
async function renderPdf(pdfPath: string, dpi: number, maxPages: number, tmpDir: string): Promise<string[]> {
const prefix = path.join(tmpDir, "page");
await execFileP("pdftoppm", ["-png", "-r", String(dpi), "-l", String(maxPages), pdfPath, prefix], {
timeout: 120_000,
});
const pageNum = (f: string) => parseInt(f.match(/-(\d+)\.png$/)?.[1] ?? "0", 10);
const files = (await fsp.readdir(tmpDir))
.filter((f) => f.endsWith(".png"))
.sort((a, b) => pageNum(a) - pageNum(b))
.map((f) => path.join(tmpDir, f));
if (files.length === 0) throw new Error("pdftoppm hat keine Seiten erzeugt");
return files;
}
/** Hat das PDF eine nennenswerte Textebene? (Hybrid: Werte getippt → 150 DPI
* reicht. Reiner Scan: keine Textebene, Handschrift möglich → 200 DPI.) */
async function hasTextLayer(pdfPath: string, maxPages: number): Promise<boolean> {
try {
const { stdout } = await execFileP("pdftotext", ["-l", String(maxPages), pdfPath, "-"], {
timeout: 30_000, maxBuffer: 10 * 1024 * 1024,
});
return stdout.replace(/\s+/g, "").length > 100;
} catch {
return false; // im Zweifel als Scan behandeln → hohe Auflösung
}
}
// ---------------------------------------------------------------------------
// VLM-Aufruf (llama-server, OpenAI-kompatibel, JSON-Schema)
// ---------------------------------------------------------------------------
const nullableString = { type: ["string", "null"] };
const nullableInt = { type: ["integer", "null"] };
const RESPONSE_SCHEMA = {
type: "object",
additionalProperties: false,
required: [
"doc_type", "info_sheet_count", "info_page", "ca_page", "notes_page", "name_company",
"prospective_buyer", "company", "phone", "cell", "email", "address",
"state", "how_did_you_hear", "interested_in_updates",
"types_of_business_raw", "notes_business_raw", "background_experience",
"total_purchase_price", "down_payment_raw", "date_of_introduction_raw",
],
properties: {
doc_type: { type: "string", enum: ["buyer_sheet", "ca_only", "other"] },
info_sheet_count: { type: "integer" },
info_page: nullableInt,
ca_page: nullableInt,
notes_page: nullableInt,
name_company: nullableString,
prospective_buyer: nullableString,
company: nullableString,
phone: nullableString,
cell: nullableString,
email: nullableString,
address: nullableString,
state: nullableString,
how_did_you_hear: nullableString,
interested_in_updates: nullableString,
types_of_business_raw: nullableString,
notes_business_raw: nullableString,
background_experience: nullableString,
total_purchase_price: nullableString,
down_payment_raw: nullableString,
date_of_introduction_raw: nullableString,
},
} as const;
const SYSTEM_PROMPT =
"You are a precise document transcription engine for scanned business forms. " +
"You transcribe handwritten and typed form fields EXACTLY as written (verbatim), " +
"including typos. You never guess, infer, or invent values. If a field is blank " +
"or unreadable, you return null.";
const USER_PROMPT = `You see all pages of one PDF, in order. Each image is preceded by a text marker "=== PAGE N ===" that tells you its exact page number. Use these markers to assign page numbers — never guess a page number.
Task: Identify the page types by their headings, then transcribe form fields from a business brokerage "BUYER INFORMATION SHEET" package.
STEP 1 — Identify each page by its UNIQUE marker text (pages can appear in ANY order):
- NOTES page: contains the text "Date NDA Scanned". It is a handwritten cover sheet with "Name:", "Date NDA Scanned:", a two-column table headed "Business Interested In:", and a free-text "Notes" area at the bottom. NOT every package has one.
- INFO SHEET page: contains the printed heading "BUYER INFORMATION SHEET" (usually with the BizMatch logo at the top).
- CA page: contains "CONFIDENTIALITY AGREEMENT" or "PROSPECTIVE BUYER AGREES TO KEEP AND HOLD CONFIDENTIAL".
Set notes_page, info_page, ca_page to the respective 1-based page numbers, or null if that page type is absent.
EXCLUSIVITY RULE — each page number may be assigned to AT MOST ONE of notes_page / info_page / ca_page. A single page is never two types at once. Decide by marker priority:
1. If the page shows "Date NDA Scanned" → it is the NOTES page. It is NEVER the info sheet, even if it is page 1 and even if it also lists businesses.
2. Else if it shows "BUYER INFORMATION SHEET" → info sheet.
3. Else if it shows the confidentiality wording → CA page.
So info_page and notes_page must be DIFFERENT numbers (or one of them null). If you were about to set them equal, you misread one — re-check which page carries "BUYER INFORMATION SHEET" versus "Date NDA Scanned".
STEP 2 — doc_type:
- "buyer_sheet": an INFO SHEET page exists.
- "ca_only": no info sheet, but a CA page exists.
- "other": none of the above — return null for every field and 0 for info_sheet_count.
2. info_sheet_count: how many separate INFO SHEET pages exist (some files contain two). 0 if none. If more than one, transcribe from the FIRST info sheet only.
STEP 3 — Transcribe VERBATIM (exactly as written, do not normalize or expand abbreviations), each field ONLY from the page type named:
5. From the INFO SHEET page (only if info_page is set):
- name_company: "Name/Company" line
- prospective_buyer: "Prospective Buyer" line
- company: separate "Company" line if present
- phone, cell, email
- address: the COMPLETE address on the "ADDRESS" line. The address field has TWO parts side by side: the left part is the street ("PO BOX / STREET"), the right part is the city/state/ZIP ("CITY / STATE / ZIP"). Transcribe BOTH parts as one full address, left to right (e.g. "2688 Grassina St. #631, San Jose, CA 95136"). Do NOT stop after the street — always include the city/state/ZIP part to the right, even if there is a wide gap between them or the right part is handwritten.
- state: the US state from the address (2-letter code if shown, e.g. "CA", "TX"), else null
- how_did_you_hear: "How did you hear about us"
- interested_in_updates: the marked updates answer/checkbox ("Yes"/"No"), else null
- types_of_business_raw: the "Type(s) of business interested in" list FROM THE INFO SHEET ONLY. This is usually a MULTI-LINE list with several entries stacked vertically (e.g. "RETAIL/TRADE", "FUEL STATIONS/CONVENIENCE STORES", "RESTAURANTS/BAKERY/CAFES", "TRANSPORT", "IT TELECOM"). Transcribe EVERY line of the list, not just the first one. Include entries even if they are struck through / crossed out (transcribe them as written). Join all entries with a comma in top-to-bottom order. This must come from the info sheet page, NEVER from the notes page.
- background_experience: "Background/Experience" (may span multiple lines)
- total_purchase_price: "Total Purchase Price" as written
- down_payment_raw: "Down Payment" as written (e.g. "$350,000", "1.5M", "TBD")
6. If doc_type is "ca_only": transcribe from the CA page — the prospective buyer's printed/signed name into prospective_buyer, plus address/phone/email if present. Everything else null.
7. date_of_introduction_raw: the "Date of Introduction" on the CA page (usually near the buyer's signature), transcribed EXACTLY as written including any spaces or separators (e.g. "09 / 13 / 2021", "6/25/26", "Sept 13 2021"). If a date is visible anywhere labeled "Date of Introduction", always return it verbatim — never leave it null just because the format looks unusual. Only null if truly no such date is present.
8. From the NOTES page (only if notes_page is set):
- notes_business_raw: the business name(s) written in the "Business Interested In" TABLE of the notes page, verbatim (join multiple with a comma). Take ONLY the table entries — do NOT include the free-text "Notes" area at the bottom of the page. If the table is empty, null.
The notes page and the info sheet are INDEPENDENT sources; never copy content from one into the other's field.
A blank field, "N/A", "n", or an empty line = transcribe it as written; if truly empty, use null.
Handwriting rules: Transcribe handwritten values letter by letter — do NOT complete them from context or from other fields. Email addresses are the most reliable spelling source on the page: read the email character by character, and if a handwritten name is ambiguous (e.g. B vs D), prefer the spelling that appears in the email address. Never alter the email itself to match your reading of the name.
Return only the JSON object.`;
async function fetchModelId(api: string): Promise<string> {
try {
const r = await fetch(`${api}/models`);
const j = (await r.json()) as { data?: Array<{ id?: string }> };
return j?.data?.[0]?.id ?? "unknown";
} catch {
return "unknown";
}
}
/** Wartet nach einem Server-Neustart (503/Verbindungsfehler), bis /health
* wieder OK meldet — Modell-Reload dauert 1-2 Minuten. */
async function waitForHealthy(api: string, timeoutMs: number): Promise<void> {
const healthUrl = api.replace(/\/v1\/?$/, "") + "/health";
const deadline = Date.now() + timeoutMs;
while (Date.now() < deadline) {
try {
const r = await fetch(healthUrl, { signal: AbortSignal.timeout(5000) });
if (r.ok) return;
} catch {
/* Server noch weg */
}
await new Promise((res) => setTimeout(res, 5000));
}
}
async function callVision(api: string, images: string[], timeoutMs: number): Promise<VisionRaw> {
const content: Array<Record<string, unknown>> = [{ type: "text", text: USER_PROMPT }];
// Vor jedes Bild einen Seiten-Marker setzen, damit das Modell zweifelsfrei
// weiss, welches Bild welche Seitennummer ist (loest Info/Notes-Verwechslung).
for (let i = 0; i < images.length; i++) {
const b64 = await fsp.readFile(images[i], { encoding: "base64" });
content.push({ type: "text", text: `=== PAGE ${i + 1} ===` });
content.push({ type: "image_url", image_url: { url: `data:image/png;base64,${b64}` } });
}
const body = {
model: "qwen3.6",
temperature: 0.1,
top_p: 0.95,
max_tokens: 1500,
chat_template_kwargs: { enable_thinking: false },
response_format: {
type: "json_schema",
json_schema: { name: "buyer_sheet", strict: true, schema: RESPONSE_SCHEMA },
},
messages: [
{ role: "system", content: SYSTEM_PROMPT },
{ role: "user", content },
],
};
const ctl = new AbortController();
const timer = setTimeout(() => ctl.abort(), timeoutMs);
try {
const r = await fetch(`${api}/chat/completions`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(body),
signal: ctl.signal,
});
if (!r.ok) throw new Error(`HTTP ${r.status}: ${(await r.text()).slice(0, 300)}`);
const j = (await r.json()) as { choices?: Array<{ message?: { content?: string } }> };
const text = j?.choices?.[0]?.message?.content;
if (!text) throw new Error("Leere Antwort vom Server");
return JSON.parse(text) as VisionRaw;
} finally {
clearTimeout(timer);
}
}
// ---------------------------------------------------------------------------
// Merge: deterministischer Datensatz + Vision-Rohwerte → Zielstruktur
// ---------------------------------------------------------------------------
/**
* Zieht den Namen deterministisch aus dem Dateinamen (verlaessliche Quelle,
* unabhaengig von der Vision-Transkription). Schema: "Nachname, Vorname <datum> [Zusatz].pdf".
* Gibt "Nachname, Vorname" zurueck, oder null wenn nicht erkennbar.
* Beeinflusst die Bilderkennung NICHT — reine String-Operation.
*/
function nameFromFilename(fileName: string): string | null {
let s = fileName.replace(/\.pdf$/i, "");
// Klammer-Zusaetze wie "(Gordon Greve)" / "(JF Lehman)" entfernen
s = s.replace(/\([^)]*\)/g, " ").replace(/\s+/g, " ").trim();
// Schema ist "Nachname, Vorname ...". Nimm den Nachnamen (vor dem Komma)
// und aus dem Rest nur das erste Wort als Vorname - alles Weitere
// (Zweitnamen, Datum, Notes/Oilfield-Zusaetze) faellt weg.
const comma = s.indexOf(",");
if (comma < 0) {
// kein Komma: erstes Wort als Ganzes nehmen, ohne Datum/Zusatz
const first = s.replace(/\b\d{4,8}\b.*$/, "").trim();
return first.length >= 2 ? first : null;
}
const last = s.slice(0, comma).trim();
const rest = s.slice(comma + 1).trim();
// erstes Token des Rests = Vorname (stoppt vor Datum/Zusatzwort)
const firstName = (rest.match(/^[A-Za-zÀ-ÿ.'-]+/) || [""])[0];
if (!last || !firstName) return null;
return `${last}, ${firstName}`;
}
function mergeRecord(det: BuyerRecord, vis: VisionRaw, model: string): BuyerRecord {
const base: BuyerRecord = {
...det,
_parser: "vision",
_vision_model: model,
_vision_ts: new Date().toISOString(),
name_from_filename: nameFromFilename(det.file_name),
_vision_error: undefined,
};
delete (base as Record<string, unknown>)["_vision_error"];
if (vis.doc_type === "other") {
return { ...base, is_buyer_sheet: false, _doc_type: "other", _info_page: null, _ca_page: null, _notes_page: vis.notes_page ?? null };
}
// buyer_sheet ODER ca_only: alles übernehmen, was das Dokument hergibt
const dp = normDownPayment(vis.down_payment_raw);
return {
...base,
is_buyer_sheet: vis.doc_type === "buyer_sheet",
_doc_type: vis.doc_type,
_info_sheet_count: vis.info_sheet_count ?? (vis.doc_type === "buyer_sheet" ? 1 : 0),
name_company: cleanStr(vis.name_company),
prospective_buyer: cleanStr(vis.prospective_buyer),
company: cleanStr(vis.company),
phone: cleanStr(vis.phone),
cell: cleanStr(vis.cell),
email: cleanStr(vis.email),
address: cleanStr(vis.address),
state: normState(vis.state),
how_did_you_hear: cleanStr(vis.how_did_you_hear),
interested_in_updates: cleanStr(vis.interested_in_updates),
types_of_business_raw: cleanStr(vis.types_of_business_raw),
notes_business_raw: cleanStr(vis.notes_business_raw),
background_experience: cleanStr(vis.background_experience),
total_purchase_price: cleanStr(vis.total_purchase_price),
down_payment: dp.value,
down_payment_raw: dp.raw,
// Vision-Datum bevorzugt; Fallback: deterministischer Wert (z.B. aus Dateinamen)
// Datum: ISO wenn parsebar, sonst ROHWERT behalten (Mitarbeiter korrigiert
// spaeter). Nie verwerfen, nur weil das Format ungewohnt ist.
date_of_introduction: normDate(vis.date_of_introduction_raw) ?? cleanStr(vis.date_of_introduction_raw) ?? (det.date_of_introduction as string | null) ?? null,
date_of_introduction_raw: cleanStr(vis.date_of_introduction_raw),
_info_page: vis.info_page,
_ca_page: vis.ca_page,
_notes_page: vis.notes_page,
};
}
// ---------------------------------------------------------------------------
// Main
// ---------------------------------------------------------------------------
const RETRIES = 3;
function progress(line: string): void {
// Im Log-Modus (Pipe/tee): vollständige Zeilen mit Timestamp statt \r-Überschreiben
if (!process.stderr.isTTY) {
process.stderr.write(`[${new Date().toISOString()}] ${line}\n`);
return;
}
const cols = process.stderr.columns ?? 120;
process.stderr.write("\r" + line.slice(0, cols - 1).padEnd(cols - 1));
}
async function main(): Promise<void> {
const args = parseArgs();
// pdftoppm vorhanden?
try {
await execFileP("pdftoppm", ["-v"]);
} catch {
console.error("Fehler: pdftoppm nicht gefunden. Installieren: sudo apt install poppler-utils");
process.exit(1);
}
const visionPath = path.join(args.outDir, "buyers_vision.json");
await fsp.mkdir(args.outDir, { recursive: true });
// Resume-Stand laden (bereits verarbeitete Dokumente)
const done = new Map<string, BuyerRecord>();
try {
const prev: BuyerRecord[] = JSON.parse(await fsp.readFile(visionPath, "utf8"));
for (const r of prev) done.set(r.file_name, r);
} catch {
/* kein Resume-Stand */
}
// ---------------------------------------------------------------------
// PHASE 1 — INDEX: alle PDFs scannen, file_name + _pages_total sofort
// ins buyers_vision.json eintragen (auch die zu grossen, dann markiert).
// ---------------------------------------------------------------------
console.error(`Phase 1: Indexiere PDFs unter ${args.pdfRoot} ...`);
const pdfIndex = await buildPdfIndex(args.pdfRoot);
const names = [...pdfIndex.keys()].sort();
console.error(`${names.length} PDFs gefunden. Ermittle Seitenzahlen ...`);
let idx = 0;
for (const name of names) {
idx++;
// schon indexiert (mit gueltiger Seitenzahl)? dann nicht neu zaehlen
const existing = done.get(name);
if (existing && typeof existing["_pages_total"] === "number" && existing["_pages_total"]! >= 0 && !args.force) {
if (idx % 50 === 0) progress(`Index ${idx}/${names.length}`);
continue;
}
const pdfPath = pdfIndex.get(name)!;
const pages = await pdfPageCount(pdfPath);
const tooMany = pages < 0 ? false : pages > args.maxPages;
const prev = done.get(name) ?? { file_name: name, is_buyer_sheet: false };
done.set(name, {
...prev,
file_name: name,
_pages_total: pages,
...(pages < 0 ? { _index_error: "pdfinfo fehlgeschlagen (beschaedigt?)" } : {}),
...(tooMany ? { _skipped_too_many_pages: true } : {}),
});
if (idx % 25 === 0 || idx === names.length) progress(`Index ${idx}/${names.length}`);
}
// Index sofort persistieren, bevor die teure Phase 2 startet
await fsp.writeFile(visionPath, JSON.stringify([...done.values()], null, 2));
process.stderr.write("\n");
// ---------------------------------------------------------------------
// PHASE 2 — INHALT: nur PDFs <= maxPages, noch nicht (fehlerfrei) erledigt.
// ---------------------------------------------------------------------
let candidates = [...done.values()].filter((r) => {
const pages = r["_pages_total"] as number | undefined;
return typeof pages === "number" && pages > 0 && pages <= args.maxPages;
});
if (args.only) candidates = candidates.filter((r) => r.file_name === args.only);
// Resume-Skip VOR dem Limit: fehlerfrei mit echtem Vision-Ergebnis = fertig.
// Mit --reprocess-missing gelten Datensaetze OHNE Datum als unvollstaendig
// und werden erneut verarbeitet (fuer gezielte Nachlaeufe, ohne JSON-Editieren).
const isIncomplete = (r: Record<string, unknown>): boolean => {
if (!args.reprocessMissing) return false;
// buyer_sheet/ca_only ohne Datum gilt als unvollstaendig
const dt = r["_doc_type"];
if (dt === "other") return false;
const hasDate = r["date_of_introduction"] != null && r["date_of_introduction"] !== "";
return !hasDate;
};
const pending = candidates.filter((r) => {
const prev = done.get(r.file_name);
const hasResult = prev && prev["_parser"] === "vision" && !prev["_vision_error"];
if (hasResult && prev && isIncomplete(prev)) return true; // unvollstaendig -> neu
return !(hasResult && !args.force);
});
const skipped = candidates.length - pending.length;
const targets = args.limit > 0 ? pending.slice(0, args.limit) : pending;
const tooManyCount = [...done.values()].filter((r) => r["_skipped_too_many_pages"]).length;
console.error(
`Phase 2: ${candidates.length} Kandidaten (<=${args.maxPages} Seiten), ` +
`${tooManyCount} zu gross (uebersprungen), ${skipped} bereits verarbeitet, ` +
`${targets.length} in diesem Lauf.`
);
const model = await fetchModelId(args.api);
console.error(`Modell: ${model} @ ${args.api}`);
let ok = 0, caOnly = 0, notSheet = 0, errors = 0;
for (let i = 0; i < targets.length; i++) {
const det = targets[i];
const tag = `[${i + 1}/${targets.length}] ${det.file_name}`;
const pdfPath = pdfIndex.get(det.file_name);
if (!pdfPath) {
done.set(det.file_name, { ...det, _vision_error: "PDF nicht gefunden", _vision_ts: new Date().toISOString() });
errors++;
progress(`${tag} … FEHLER: PDF nicht gefunden`);
continue;
}
const tmpDir = await fsp.mkdtemp(path.join(os.tmpdir(), "bvs-"));
try {
const dpi = args.dpi === "auto"
? ((await hasTextLayer(pdfPath, args.maxPages)) ? 150 : 200)
: args.dpi;
progress(`${tag} … rendere (${dpi} dpi)`);
const images = await renderPdf(pdfPath, dpi, args.maxPages, tmpDir);
let vis: VisionRaw | null = null;
let lastErr = "";
for (let attempt = 1; attempt <= RETRIES; attempt++) {
try {
progress(`${tag} … VLM (${images.length} Seiten, Versuch ${attempt})`);
vis = await callVision(args.api, images, args.timeoutMs);
break;
} catch (e) {
lastErr = e instanceof Error ? e.message : String(e);
if (attempt < RETRIES) {
if (/HTTP 50[23]|fetch failed|aborted|ECONNREFUSED|ECONNRESET/i.test(lastErr)) {
// Server crasht/lädt neu → auf /health warten (Modell-Reload dauert)
progress(`${tag} … Server neu am Laden, warte auf /health`);
await waitForHealthy(args.api, 300_000);
} else {
await new Promise((res) => setTimeout(res, 5000 * attempt));
}
}
}
}
if (!vis) {
done.set(det.file_name, { ...det, _vision_error: lastErr, _vision_ts: new Date().toISOString() });
errors++;
progress(`${tag} … FEHLER: ${lastErr}`);
} else {
const merged = mergeRecord(det, vis, model);
done.set(det.file_name, merged);
if (merged["_doc_type"] === "ca_only") { caOnly++; progress(`${tag} … CA only`); }
else if (merged.is_buyer_sheet) { ok++; progress(`${tag} … OK`); }
else { notSheet++; progress(`${tag} … kein Buyer Sheet`); }
}
} catch (e) {
const msg = e instanceof Error ? e.message : String(e);
done.set(det.file_name, { ...det, _vision_error: msg, _vision_ts: new Date().toISOString() });
errors++;
progress(`${tag} … FEHLER: ${msg}`);
} finally {
await fsp.rm(tmpDir, { recursive: true, force: true });
}
// Inkrementell sichern (Resume-fähig)
await fsp.writeFile(visionPath, JSON.stringify([...done.values()], null, 2));
}
await fsp.writeFile(visionPath, JSON.stringify([...done.values()], null, 2));
process.stderr.write("\n");
console.error(
`Fertig. OK: ${ok}, CA only: ${caOnly}, kein Buyer Sheet: ${notSheet}, Fehler: ${errors}, übersprungen: ${skipped}`
);
console.error(`${visionPath}`);
}
main().catch((e) => {
console.error("\nAbbruch:", e instanceof Error ? e.message : e);
process.exit(1);
});