Open-source alternatives to WriteGPT

dots.ocr is a suite of software utilities for document layout analysis, multilingual optical character recognition, and scene text digitization. It functions as an engine for extracting digital text and structured layout data from images and PDFs across various human scripts. The project includes a specialized transformer for converting charts, diagrams, and chemical formulas from raster images into scalable vector graphics. It also provides a pipeline to transform extracted text and structural layout from documents and web screenshots into formatted Markdown files. The system covers capabil

Pix2Text is an optical character recognition system and document conversion tool designed to transform images and PDFs into Markdown. It functions as a multilingual OCR engine supporting over 80 languages, a LaTeX formula recognizer for mathematical notations, and a parser integrated with vision language models. The project utilizes a hybrid pipeline to separate plain text from mathematical formulas and tabular structures within a single pass. It converts recognized formulas into LaTeX expressions and transforms detected tables and layouts into structured Markdown formatting. The system incl

GLM-130B is a pre-trained foundation model and bilingual large language model designed for natural language processing tasks in both English and Chinese. It functions as an autoregressive language model and text generator capable of producing long-form content and predicting missing phrases. The model utilizes an autoregressive blank-filling architecture and a bidirectional dense transformer to process text. This approach allows the system to transition between understanding context through masked language modeling and generating sequential text using specific mask tokens. The project covers

EasyOCR is a deep learning-based computer vision library designed to perform optical character recognition on images and video frames. It functions as a comprehensive pipeline that automates the transformation of visual text into machine-readable strings, enabling the digitization of physical documents, forms, and receipts into searchable data. The engine distinguishes itself through a multi-stage processing workflow that combines convolutional neural networks for spatial feature extraction with sequence-based decoding mechanisms. This architecture allows the system to identify and interpret

Docling is a multimodal content converter and document parser designed to transform PDFs, Office files, and HTML into structured Markdown or JSON for generative AI applications. It functions as an OCR document processor and a PDF layout analyzer that extracts tables, charts, and hierarchical structures while preserving the original page layout. The system operates as a local-first inference engine, allowing for the processing of sensitive data in air-gapped environments without external network connectivity. It can also be deployed as an API or a Model Context Protocol server to provide parsi

Kreuzberg is a document extraction engine that converts PDFs, Office files, images, and over 90 other formats into clean, structured text and metadata. It is built around a compiled Rust core that can be used as a native library, a command-line tool, a REST API server, or a WebAssembly module for browser-based processing. The system is designed to run entirely on self-hosted infrastructure, with no data leaving the user's environment. What distinguishes Kreuzberg is its breadth of integration surfaces and its pipeline architecture. It exposes extraction capabilities through native bindings fo

This project is a collection of transformer natural language processing tutorial notebooks and educational resources. It provides a guide for using the Hugging Face Transformers library through interactive coding exercises and demonstrations. The repository contains ready-to-run Jupyter notebooks that provide practical examples for implementing transformer models. These resources demonstrate how to execute specific natural language processing workflows using pre-trained models. The notebooks cover a range of natural language processing tasks, including text classification, automatic text sum

X-AnyLabeling is an AI-assisted annotation platform and computer vision labeling tool. It provides an interface for annotating images and videos using polygons and rectangles to create training sets for machine learning models. The project distinguishes itself through the integration of external AI models via a plugin-based inference backend, allowing for automated generation of candidate labels and the execution of specialized tasks like pose estimation and object detection. It also functions as an optical character recognition tool for extracting text and layout information from document im

This project is a document digitization utility that combines traditional optical character recognition with language model processing to convert scanned PDF files into structured markdown. It functions as an automated pipeline that extracts raw text from images and applies intelligent post-processing to refine the output. The system distinguishes itself by using language models to perform error correction, removing artifacts and formatting inconsistencies common in raw character recognition. It incorporates a modular design that decouples processing logic from specific model providers, allow

Deep OCR is a deep learning framework designed for the recognition of Chinese characters within images. It functions as an optical character recognition library that converts scanned documents or image files into digital text, providing an alternative to traditional template matching methods. The system utilizes a combination of convolutional neural networks for spatial feature extraction and recurrent sequence modeling to capture contextual relationships between characters. It employs connectionist temporal classification to map image sequences to character strings without requiring explicit

This project is a comprehensive educational curriculum and structured learning path covering the full lifecycle of large language models. It provides a guided progression through the theory, architecture, training, and deployment of these models. The curriculum includes specialized guides on transformer architecture, model training tutorials, and frameworks for designing autonomous agents. It also provides dedicated resources for studying model safety and ethics. The material covers a wide range of technical capabilities, including distributed training strategies, parameter-efficient fine-tu

OpenGpt is an agent orchestration platform and multimodal interface designed for building and deploying specialized AI personas. It allows users to create task-oriented agents with custom system prompts and behavioral constraints to automate professional, creative, and technical workflows. The project features a prompt engineering workflow that transforms simple user inputs into structured instructions to improve model accuracy. It integrates retrieval-augmented generation by connecting vector databases to the chat interface, enabling context-aware responses from private datasets. The platfo

HanLP is a natural language processing library and deep learning framework specifically optimized for the Chinese language, while also functioning as a multilingual text processor. It serves as a toolkit for performing linguistic analysis, semantic understanding, and script conversion. The project distinguishes itself through a dedicated focus on Chinese linguistic structures, including a specialized script converter for transforming text between Simplified Chinese, Traditional Chinese, and Pinyin. It further supports domain-specific model training to improve the recognition of professional t

chatGPTBox is a browser extension that integrates large language model chat interfaces and AI tools directly into the web browsing experience. It functions as an AI productivity toolkit and API client, allowing users to access AI assistants via a floating chat interface without leaving their active webpage. The project distinguishes itself by offering context-aware assistance and website-specific adaptations based on the current URL. It further enhances the browsing experience by displaying AI-generated responses alongside standard search engine results and providing a system to route chat re

BestBlogs is an AI-powered content aggregation and curation platform that integrates feed management with automated text analysis. It functions as a centralized reading space that collects updates from diverse digital sources, including RSS feeds and social media, to deliver personalized daily briefings and thematic digests. The platform distinguishes itself by using large language models to process, summarize, and score incoming content. It provides deep insights through generative summarization, thematic synthesis, and interactive question-answering, while also offering multilingual transla

This project is a scalable, containerized pipeline designed to transform digital documents and image-based ebooks into narrated audiobooks. It functions as an end-to-end production platform that integrates text-to-speech synthesis, optical character recognition, and automated workflow management to convert various file formats into spoken audio. The system distinguishes itself through advanced linguistic analysis and voice synthesis capabilities, including the ability to identify characters within a text and assign them distinct voice profiles for multi-speaker narration. Users can further pe

This project is a comprehensive framework for building and managing autonomous agent systems. It provides a unified architecture for orchestrating multi-agent societies, where specialized agents collaborate through roleplay to decompose and solve complex tasks. The system integrates language models with external environments, enabling agents to perform real-world actions through a standardized tool-calling abstraction layer. The framework distinguishes itself through its focus on iterative reasoning and data reliability. It employs automated feedback loops to refine agent outputs and self-eva

This project is a collection of pretrained transformer protein language models designed for sequence embedding, structure prediction, variant effect estimation, and generative inverse folding. It provides a framework for transforming amino acid sequences into high-dimensional numerical vectors and predicting biological properties through these embeddings. The system includes a generative model for inverse folding that designs amino acid sequences to fit a specific target protein backbone structure. It also features tools for protein variant analysis that use zero-shot prediction to estimate t

This project is an optical character recognition tool designed to extract hardcoded subtitles from video frames and convert them into synchronized subtitle files. It functions as a text processor that transforms embedded visual text into a written format to improve video accessibility and translation. The system uses graphics processing units to increase the speed and accuracy of text recognition. It includes a subtitle cleaning tool that applies custom mapping configurations to filter out watermarks, channel logos, and duplicate lines from the extracted text. The tool supports batch process

Baichuan2 is a collection of pre-trained large language models, including base and chat variants, designed for natural language generation and multi-turn conversational AI. It provides an inference engine and a fine-tuning framework to adapt these models to custom datasets and specialized domains. The project features a quantization toolkit and an inference engine that enable model execution across diverse hardware, including graphics processors, central processors, and specialized accelerators. These tools support low-bit weight quantization to reduce memory usage and increase inference spee

AI NovelGenerator is a tool for generating long-form fiction using large language models. It functions as a narrative architect and writing assistant, automating the creation of multi-chapter novels while managing the overall story structure and character tracking. The project distinguishes itself through a semantic context retrieval system and an AI story consistency checker. These tools use semantic search to recall specific story details from previous chapters and scan generated text for plot contradictions or behavioral inconsistencies. The system covers a full narrative lifecycle, inclu

This project is a PyTorch-based framework and toolkit for scene text recognition. It provides a deep learning pipeline for extracting characters and words from images of natural environments, covering the full process from training data preparation to model validation. The framework functions as a standardized benchmark for measuring the accuracy and inference speed of text recognition models. It includes tools for calculating recognition accuracy and measuring GPU processing time per image to evaluate model performance across consistent datasets. The system incorporates visual and sequentia

This project is a manual reconstruction of the Llama 3 transformer architecture implemented as a PyTorch neural network. It serves as a reference for the internal mathematical structure and tensor flow of a transformer-based language model designed for next token prediction. The implementation focuses on building the model from scratch using basic matrix operations and tensor manipulations. It demonstrates the manual construction of core components, including rotary positional embeddings, multi-head self-attention, and root mean square normalization. The codebase covers the full inference pi

This project is a transformer-based language model and natural language processing toolkit designed to generate deep contextual representations of text. By utilizing a transformer-based encoder architecture, the system processes input sequences through stacked self-attention layers to capture the semantic meaning of tokens based on their surrounding sentence structure. The model distinguishes itself through bidirectional contextual processing, which analyzes text in both directions simultaneously, and masked language modeling, which trains the system by predicting hidden tokens within a seque

mmocr is a PyTorch-based optical character recognition framework designed for training and deploying text detection, recognition, and key information extraction models. It serves as a comprehensive toolbox for scene text detection and recognition, providing specialized libraries for locating text regions and converting visual text into machine-encoded strings. The project distinguishes itself through a research framework for key information extraction and advanced text spotting capabilities. These include point-based spotting using transformers and the use of parameterized Bezier curves to id

DeepSeek-OCR is a vision processing framework designed to convert image-based text into machine-readable tokens for large language models. It functions as a document inference pipeline that encodes visual data into compact representations, enabling automated optical character recognition and document analysis workflows. The system distinguishes itself through a high-throughput architecture that utilizes hardware-accelerated batch inference to process large volumes of visual data. It incorporates dynamic resolution scaling to manage the balance between visual detail and token consumption, ensu

This application is a cross-platform desktop utility designed for automated translation, optical character recognition, and speech synthesis. It functions as a modular client that integrates various local and remote language services, allowing users to process text through hotkeys, clipboard monitoring, or direct input. The software distinguishes itself through a plugin-based architecture and a built-in automation framework. By exposing a local network interface, it enables external applications and scripts to programmatically trigger its translation and recognition workflows. Users can furth