Developing an End-to-End Document Intelligence Pipeline with docTR for OCR, Layout Analysis, KIE, Benchmarking, and Searchable PDFs

import os, sys, io, json, time, math, re, subprocess, warnings from collections import Counter, defaultdict warnings.filterwarnings(“ignore”) os.environ.setdefault(“USE_TORCH”, “1”) def _pip(*pkgs): subprocess.run([sys.executable, “-m”, “pip”, “install”, “-q”, *pkgs], check=False) try: import doctr except ImportError: print(“>> Installing python-doctr (this takes ~1-2 min on Colab)…”) _pip(“python-doctr[viz]”) try: import reportlab except ImportError: _pip(“reportlab”) import numpy as np import torch import…

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DeepSeek AI Releases DeepSeek Harness in Developer Preview: An MIT-Licensed Agent Harness Where Everything is a Plugin

DeepSeek released DeepSeek Harness v0.1 in developer preview and published the full source code under the MIT license. The project ships as dsh at deepseek-ai/deepseek-harness. A harness is the layer between a model and the environment it acts in — the tools, files, sandboxes, and control loop that let an agent keep working. DeepSeek frames…

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