Jump to content

Connect SuperML | Leeroopedia MCP: Equip your AI agents with best practices, code verification, and debugging knowledge. Powered by Leeroo — building Organizational Superintelligence. Contact us at founders@leeroo.com.

Principle:Infiniflow Ragflow Document Processing Trigger

From Leeroopedia
Knowledge Sources
Domains RAG, Task_Queue, Data_Engineering
Last Updated 2026-02-12 06:00 GMT

Overview

An asynchronous task dispatch pattern that splits documents into page-range tasks and enqueues them to a Redis-backed worker queue.

Description

Document Processing Trigger initiates the document-to-chunks pipeline by creating Task records in the database and enqueuing them to Redis for consumption by background worker processes. For PDFs, the document is split into page-range tasks based on task_page_size to enable parallel processing. For spreadsheets, splitting is by row ranges. Each task carries a content hash (digest) computed from chunking configuration and page range, enabling incremental re-processing where only changed chunks are recomputed.

Usage

Trigger after documents are uploaded and parser configuration is finalized. This is the entry point to the asynchronous processing pipeline.

Theoretical Basis

The task dispatch follows a fan-out pattern:

  • Task splitting: Large documents are divided into page-range tasks for parallel processing across multiple workers
  • Content-addressed deduplication: Each task has a digest hash; if the digest matches a previous task, its chunks are reused
  • Priority queuing: Tasks can be assigned priorities (0=default) for scheduling control

Related Pages

Implemented By

Page Connections

Double-click a node to navigate. Hold to expand connections.
Principle
Implementation
Heuristic
Environment