Rene Fichtmueller 8bb3b586f3 feat: Phase 5 — OCR pipeline + document/news search
Docling-powered OCR pipeline: PDF → markdown → chunks → Ollama embed → Qdrant.
News embedding seeder for news_embeddings collection.
Document and news semantic search API endpoints.

- embeddings/ocr-pipeline.ts: Docling convert → chunk → embed pipeline
- embeddings/seed-news.ts: Batch embed news_articles into Qdrant
- routes/documents.ts: POST /api/documents/process, GET /api/documents
- routes/search.ts: GET /search/documents, GET /search/news endpoints
- sql/005-documents.sql: Add chunks_count, processed_at to documents table
- Ollama + nomic-embed-text installed on Erik (CPU mode)
- 89 products + 40 datasheet chunks + 33 news articles in Qdrant
2026-03-28 00:22:01 +13:00

218 lines
7.1 KiB
TypeScript

/**
* Document processing API routes (OCR Pipeline)
*
* POST /api/documents/process — Submit a document URL for OCR + embedding
* GET /api/documents — List processed documents
* GET /api/documents/:id — Get document chunks
*/
import { Router, Request, Response } from "express";
import { embed, upsertPoints, CollectionName } from "../embeddings/client";
import { pool } from "../db/client";
import { randomUUID } from "crypto";
export const documentRouter = Router();
const DOCLING_URL = process.env.DOCLING_URL || "http://localhost:8100";
interface DoclingResult {
success: boolean;
content: string;
format: string;
pages: number | null;
error?: string;
}
/** Chunk markdown into overlapping sections */
function chunkMarkdown(
markdown: string,
maxChunkSize: number = 1500,
overlapSize: number = 200,
): Array<{ heading: string; text: string }> {
const sections = markdown.split(/(?=^#{1,3}\s)/m);
const chunks: Array<{ heading: string; text: string }> = [];
for (const section of sections) {
const trimmed = section.trim();
if (!trimmed || trimmed.length < 20) continue;
const headingMatch = trimmed.match(/^(#{1,3})\s+(.+)/);
const heading = headingMatch ? headingMatch[2].trim() : "Introduction";
const body = headingMatch ? trimmed.slice(headingMatch[0].length).trim() : trimmed;
if (body.length <= maxChunkSize) {
chunks.push({ heading, text: body });
} else {
const paragraphs = body.split(/\n\n+/);
let currentChunk = "";
for (const para of paragraphs) {
if (currentChunk.length + para.length > maxChunkSize && currentChunk.length > 0) {
chunks.push({ heading, text: currentChunk.trim() });
const overlapText = currentChunk.slice(-overlapSize);
currentChunk = overlapText + "\n\n" + para;
} else {
currentChunk += (currentChunk ? "\n\n" : "") + para;
}
}
if (currentChunk.trim().length > 20) {
chunks.push({ heading, text: currentChunk.trim() });
}
}
}
return chunks;
}
// POST /api/documents/process — Process a document URL
documentRouter.post("/process", async (req: Request, res: Response) => {
const { url, title, doc_type, vendor, collection } = req.body as {
url?: string;
title?: string;
doc_type?: string;
vendor?: string;
collection?: string;
};
if (!url) {
res.status(400).json({ success: false, error: "Missing 'url' in request body" });
return;
}
const targetCollection = (collection || "datasheet_chunks") as CollectionName;
if (!["datasheet_chunks", "manual_chunks"].includes(targetCollection)) {
res.status(400).json({ success: false, error: "collection must be 'datasheet_chunks' or 'manual_chunks'" });
return;
}
try {
// Convert via Docling
const docResp = await fetch(`${DOCLING_URL}/convert`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ url, format: "markdown" }),
signal: AbortSignal.timeout(120000),
});
if (!docResp.ok) {
res.status(502).json({ success: false, error: "Docling conversion failed", detail: await docResp.text() });
return;
}
const docResult = (await docResp.json()) as DoclingResult;
if (!docResult.success) {
res.status(502).json({ success: false, error: "Docling conversion failed", detail: docResult.error });
return;
}
const documentId = randomUUID();
const docTitle = title || url.split("/").pop()?.replace(/\.[^.]+$/, "") || "untitled";
const docType = doc_type || "datasheet";
const docVendor = vendor || "Unknown";
// Chunk
const chunks = chunkMarkdown(docResult.content);
// Embed and store
const BATCH_SIZE = 5;
let stored = 0;
for (let i = 0; i < chunks.length; i += BATCH_SIZE) {
const batch = chunks.slice(i, i + BATCH_SIZE);
const points = await Promise.all(
batch.map(async (chunk, idx) => {
const chunkIndex = i + idx;
const embeddingText = `${docTitle}. ${chunk.heading}. ${chunk.text}`;
const vector = await embed(embeddingText);
return {
id: randomUUID(),
vector,
payload: {
document_id: documentId,
source_url: url,
document_type: docType,
chunk_index: chunkIndex,
total_chunks: chunks.length,
title: docTitle,
section_heading: chunk.heading,
text: chunk.text,
page_estimate: docResult.pages,
vendor: docVendor,
product_slug: docTitle.replace(/\s+/g, "-").toLowerCase(),
},
};
}),
);
await upsertPoints(targetCollection, points);
stored += points.length;
}
// Record in documents table (existing schema)
try {
await pool.query(
`INSERT INTO documents (id, entity_type, doc_type, title, r2_key, source_url, page_count, chunks_count, ocr_status, ocr_text, processed_at)
VALUES ($1, 'transceiver', $2, $3, $4, $5, $6, $7, 'completed', $8, NOW())
ON CONFLICT ON CONSTRAINT documents_pkey DO UPDATE
SET processed_at = NOW(), chunks_count = $7, ocr_status = 'completed'`,
[documentId, docType, docTitle, `ocr/${documentId}`, url, docResult.pages, chunks.length, docResult.content.slice(0, 50000)],
);
} catch {
// ignore if insert fails
}
res.json({
success: true,
document_id: documentId,
title: docTitle,
pages: docResult.pages,
chunks: chunks.length,
collection: targetCollection,
markdown_length: docResult.content.length,
});
} catch (err) {
res.status(503).json({
success: false,
error: "Document processing failed",
detail: (err as Error).message,
});
}
});
// GET /api/documents — List processed documents
documentRouter.get("/", async (_req: Request, res: Response) => {
try {
const result = await pool.query(
`SELECT id, title, source_url, doc_type, entity_type, page_count, chunks_count, ocr_status, processed_at, created_at
FROM documents
ORDER BY COALESCE(processed_at, created_at) DESC
LIMIT 100`,
);
res.json({ success: true, documents: result.rows, count: result.rows.length });
} catch {
// Table may not exist — return empty
res.json({ success: true, documents: [], count: 0, note: "documents table not yet created" });
}
});
// GET /api/documents/:id — Get document details
documentRouter.get("/:id", async (req: Request, res: Response) => {
try {
const result = await pool.query(
`SELECT id, title, source_url, doc_type, entity_type, page_count, chunks_count, ocr_status, processed_at, created_at
FROM documents WHERE id = $1::uuid`,
[req.params.id],
);
if (result.rows.length === 0) {
res.status(404).json({ success: false, error: "Document not found" });
return;
}
res.json({ success: true, document: result.rows[0] });
} catch {
res.status(404).json({ success: false, error: "Document not found or table not created" });
}
});