LM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease.
Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process.
With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.
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Gaffa is an API for web scraping and browser automation that gives developers control over real, full browsers with a single request, no headless-browser setup, proxy management, or infrastructure scaling required. Pages render with full JavaScript support by default, matching exactly what a real user would see.
The platform covers the full range of automation needs: scraping, AI-powered data extraction into structured JSON using custom schemas, full-page screenshots, PDF export, infinite-scroll scraping, automated form filling, and converting webpages into clean Markdown for AI and LLM workflows. Reliability is built in through a rotating residential proxy network and automatic CAPTCHA and anti-bot handling, so requests succeed even against protected sites.
Pricing follows a transparent, credit-based model tied to browser execution time and bandwidth, making costs predictable as usage scales. Gaffa is aimed at AI engineers, data-driven teams, and developers who need dependable, large-scale web data without the overhead of running their own scraping infrastructure.
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pdf2docx
pdf2docx is a Python library that utilizes PyMuPDF to extract data from PDF files, analyze their layouts according to defined rules, and generate .docx documents using python-docx. This library simplifies the conversion of numerous elements such as text, images, and tables, featuring capabilities for table extraction, formatting management, and preservation of layout integrity whenever feasible. Additionally, it provides both a command-line interface and a graphical user interface to suit various user needs. Its modular design includes separate packages for handling pages, layouts, tables, images, shape paths, text spans, and other components, offering precise control over the transformation of PDF content into Word files. Developers can utilize the API for batch processing or easily embed it within their existing systems. Extensive documentation is available, detailing installation (which can be sourced from PyPI or directly), usage guidelines, and in-depth technical information on layout parsing, table extraction, and the internal modules. The project is open-source and can be found on GitHub, published under its license and with a disclaimer of any warranties. Furthermore, pdf2docx not only streamlines the conversion process significantly but also serves as an invaluable resource for professionals regularly working with PDF and Word file formats, enhancing their productivity.
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PDF.co
An innovative API platform is specifically crafted for the intelligent extraction of data from PDF documents, enabling automated parsing of various files. This system allows users to develop reusable low-code templates for data extraction, accommodating multiple languages for OCR alongside tables and fields. It incorporates a built-in invoice parser and offers a range of functionalities such as splitting, merging, reordering, and removing pages from PDF files. Advanced splitting tools enable users to fill out PDF forms and seamlessly add text, images, and signatures to existing documents. Furthermore, it supports auto-filling for interactive fields and can generate PDFs from HTML templates, incorporating conditions, variables, and custom logic as needed. Users benefit from high-quality PDF output with comprehensive control over the production quality, ensuring both security and scalability in their operations. The PDF extraction engine efficiently converts documents into various formats, including raw JSON, CSV, XML, XLS, and XLSX, while retaining the original layout and effectively extracting tables. Additionally, the platform's OCR capabilities not only repair malformed text but also extract multiple types of barcodes, such as QR Codes, Code 128, Code 39, DataMatrix, and PDF417 from PDFs, scans, and images, all powered by an advanced barcode reading engine. With such a broad array of features, this platform is positioned as a comprehensive solution for addressing all PDF-related data extraction requirements, making it an invaluable tool for businesses and individuals alike.
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