Best AI tools for< Process Pdfs >

PDFMerse is an AI-powered data extraction tool that revolutionizes how users handle document data. It allows users to effortlessly extract information from PDFs with precision, saving time and enhancing workflow. With cutting-edge AI technology, PDFMerse automates data extraction, ensures data accuracy, and offers versatile output formats like CSV, JSON, and Excel. The tool is designed to dramatically reduce processing time and operational costs, enabling users to focus on higher-value tasks.

PDFsummarizer.net is an AI tool designed to simplify how users interact with PDF documents. It instantly generates AI summaries of PDF content, breaks language barriers, and offers organized conversations with direct citations. Whether for studying, research, or professional purposes, this tool enhances understanding and accessibility of information across various fields. It improves productivity by streamlining the process of extracting vital information.

The AI PDF redaction tool App is a powerful application designed to assist users in redacting sensitive information from PDF documents with ease and efficiency. By leveraging artificial intelligence technology, this tool automates the process of identifying and removing confidential data, ensuring data privacy and security. With a user-friendly interface, users can quickly upload PDF files, select the information to redact, and generate secure, sanitized documents for sharing or storage. The tool is ideal for individuals and organizations that handle sensitive information and require a reliable solution for data redaction.

PDF GPT is an AI-powered tool that allows users to read PDFs with the help of artificial intelligence. It can summarize long documents, find information, translate content, and generate citations from PDF files in various languages. With features like document tagging, group chat functionality, and advanced search capabilities, PDF GPT aims to streamline the document management process for researchers and professionals. The tool is trusted by over 50,000 users and offers both free and premium subscription plans to cater to different user needs.

Tablize is a powerful data extraction tool that helps you turn unstructured data into structured, tabular format. With Tablize, you can easily extract data from PDFs, images, and websites, and export it to Excel, CSV, or JSON. Tablize uses artificial intelligence to automate the data extraction process, making it fast and easy to get the data you need.

FreeAIChatbot.org is an AI chatbot application that allows users to interact with an AI-powered chatbot for various tasks. Users can chat locally, generate images, switch models, process Excel/CSV files, and chat with PDFs or images. The application requires users to be on the unlimited plan to use certain features.

Linnk AI is a powerful web research assistant and PDF summarizer tool designed to help professionals analyze and summarize content quickly and efficiently. It allows users to skim through news and articles effortlessly, grasp complex research insights, and summarize lengthy PDFs in seconds. With features like cross-language summarization, automatic knowledge base creation, and browser extension integration, Linnk AI empowers users to accelerate insight acquisition and creation. Join over 30,000 professionals and experience faster analysis and smarter content creation with Linnk AI.

Dreamwriter is an AI-powered content creation tool that allows users to design beautiful, on-brand premium content in minutes. By leveraging the power of AI and the user's brand voice, Dreamwriter helps in developing hard-hitting PDFs & PPTs tailored to the exact target audience. The tool features an intuitive UI editor, real-time collaboration, simplified daily content generation, and the ability to write in multiple languages. Dreamwriter aims to streamline the content creation process by providing a toolbox of leading solutions to produce premium content at unprecedented speeds.

My Real Estate Listing AI is an innovative AI-powered tool designed to help real estate professionals create custom real estate brochures quickly and efficiently. By leveraging artificial intelligence technology, the application streamlines the process of generating polished PDF brochures for property listings, saving time and resources for users. With a user-friendly interface and a range of customizable templates, My Real Estate Listing AI empowers users to create professional marketing materials that can attract potential buyers or tenants. The tool offers a seamless experience from uploading property details to selecting themes and reviewing the final output, making it a valuable asset for real estate agents, developers, and property managers.

Arlinear is a free AI Quiz Maker that allows users to create quizzes and worksheets instantly using their own files. The AI-powered quiz maker works across various subjects like math, science, grammar, and more. Users can utilize Google Docs, Slides, PDFs, PowerPoints, Word Documents, or YouTube videos to generate personalized quizzes. The platform automatically grades quizzes and provides students with valuable feedback to enhance their learning experience. Arlinear simplifies the quiz creation process by analyzing file content and generating relevant questions to challenge students' understanding.

Focal is an AI-powered tool that helps users summarize and organize their research and reading materials. It offers features such as AI-generated summaries, document highlighting, and collaboration tools. Focal is designed for researchers, students, professionals, and anyone who needs to efficiently process large amounts of information.

SlideNotes is a web application that transforms presentations and PDF files into readable notes automatically. It simplifies the process of converting lengthy slides into concise and comprehensive notes, making studying and post-meeting tasks more efficient. SlideNotes caters to both students and professionals, offering a practical solution to streamline the research process and boost productivity. The tool aims to save time and effort by distilling information into digestible nuggets, ultimately enhancing the quality of writing and communication.

GetSearchablePDF is an online tool that allows users to convert scanned or image-based PDF documents into searchable PDFs. With its advanced OCR (Optical Character Recognition) technology, the tool accurately extracts text from images, making the resulting PDFs easy to search, edit, and share. The process is simple and straightforward: users simply connect their Dropbox or OneDrive account, drag and drop their PDF files into the designated folder, and the tool automatically converts them into searchable PDFs.

ScholarAI is an AI-powered scientific research tool that offers a wide range of features to help users navigate and extract insights from scientific literature. With access to over 200 million peer-reviewed articles, ScholarAI allows users to conduct abstract searches, literature mapping, PDF reading, literature reviews, gap analysis, direct Q&A, table and figure extraction, citation management, and project management. The tool is designed to accelerate the research process and provide tailored scientific insights to users.

v0 Report is an advanced AI Document Generator that allows users to effortlessly create, customize, and manage professional-quality documents. The tool is designed to automate the writing process, enhance workflow productivity, and elevate the quality of documents for students, researchers, and professionals. With features like AI writing research capabilities, user-friendly interface, and cost-effective writing generation, v0 Report aims to revolutionize document creation through artificial intelligence technology.

Text2Quiz is an AI-powered tool that allows users to easily convert text into engaging quizzes with just a click. Say goodbye to the time-consuming process of manual quiz creation and embrace the future of quiz generation. With Text2Quiz, users can quickly generate questions and answers, create printable PDFs and PowerPoint presentations for their quizzes, and save time on content creation. The tool is designed to simplify the quiz creation process and help users focus on other aspects of their work, such as marketing and business growth.

Slideoo is an AI-powered tool for creating captivating presentations and professional documents in minutes. It offers real-time collaboration features, chatbot assistance, and AI-generated content to enhance productivity and streamline the document creation process. With over 10,000 customers from 10 countries, Slideoo revolutionizes the way presentations are made by transforming ideas from various sources into dynamic slides and documents effortlessly.

ChatInDoc is an AI-powered tool designed to revolutionize the way people interact with and comprehend lengthy documents. By leveraging cutting-edge AI technology, ChatInDoc offers users the ability to efficiently analyze, summarize, and extract key information from various file formats such as PDFs, Office documents, and text files. With features like IR analysis, term lookup, PDF viewing, and AI-powered chat capabilities, ChatInDoc aims to streamline the process of digesting complex information and enhance productivity. The application's user-friendly interface and advanced AI algorithms make it a valuable tool for students, professionals, and anyone dealing with extensive document reading tasks.

Sourcely is an AI-powered tool designed to help students and researchers find academic sources quickly and efficiently. It offers features such as summarizing sources, exporting references, advanced filters, and PDF downloads. Sourcely aims to streamline the research process and save users time by providing credible sources for academic papers.

Quizbot.ai is an advanced AI question generator designed to revolutionize the process of question and exam development. It offers a cutting-edge artificial intelligence system that can generate various types of questions from different sources like PDFs, Word documents, videos, images, and more. Quizbot.ai is a versatile tool that caters to multiple languages and question types, providing a personalized and engaging learning experience for users across various industries. The platform ensures scalability, flexibility, and personalized assessments, along with detailed analytics and insights to track learner performance. Quizbot.ai is secure, user-friendly, and offers a range of subscription plans to suit different needs.

The receipt-scanner repository is an AI-Powered Receipt and Invoice Scanner for Laravel that allows users to easily extract structured receipt data from images, PDFs, and emails within their Laravel application using OpenAI. It provides a light wrapper around OpenAI Chat and Completion endpoints, supports various input formats, and integrates with Textract for OCR functionality. Users can install the package via composer, publish configuration files, and use it to extract data from plain text, PDFs, images, Word documents, and web content. The scanned receipt data is parsed into a DTO structure with main classes like Receipt, Merchant, and LineItem.

rag-chatbot is a tool that allows users to chat with multiple PDFs using Ollama and LlamaIndex. It provides an easy setup for running on local machines or Kaggle notebooks. Users can leverage models from Huggingface and Ollama, process multiple PDF inputs, and chat in multiple languages. The tool offers a simple UI with Gradio, supporting chat with history and QA modes. Setup instructions are provided for both Kaggle and local environments, including installation steps for Docker, Ollama, Ngrok, and the rag_chatbot package. Users can run the tool locally and access it via a web interface. Future enhancements include adding evaluation, better embedding models, knowledge graph support, improved document processing, MLX model integration, and Corrective RAG.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.

Chat-xiuliu is a bidirectional voice assistant powered by ChatGPT, capable of accessing the internet, executing code, reading/writing files, and supporting GPT-4V's image recognition feature. It can also call DALL·E 3 to generate images. The project is a fork from a background of a virtual cat girl named Xiuliu, with removed live chat interaction and added voice input. It can receive questions from microphone or interface, answer them vocally, upload images and PDFs, process tasks through function calls, remember conversation content, search the web, generate images using DALL·E 3, read/write local files, execute JavaScript code in a sandbox, open local files or web pages, customize the cat girl's speaking style, save conversation screenshots, and support Azure OpenAI and other API endpoints in openai format. It also supports setting proxies and various AI models like GPT-4, GPT-3.5, and DALL·E 3.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

PandaETL is an open-source, no-code ETL tool designed to extract and parse data from various document types including PDFs, emails, websites, audio files, and more. With an intuitive interface and powerful backend, PandaETL simplifies the process of data extraction and transformation, making it accessible to users without programming skills.

Lumentis is a tool that allows users to generate beautiful and comprehensive documentation from meeting transcripts and large documents with a single command. It reads transcripts, asks questions to understand themes and audience, generates an outline, and creates detailed pages with visual variety and styles. Users can switch models for different tasks, control the process, and deploy the generated docs to Vercel. The tool is designed to be open, clean, fast, and easy to use, with upcoming features including folders, PDFs, auto-transcription, website scraping, scientific papers handling, summarization, and continuous updates.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

The 'END TO END GENERATIVE AI PROJECTS' repository is a collection of awesome industry projects utilizing Large Language Models (LLM) for various tasks such as chat applications with PDFs, image to speech generation, video transcribing and summarizing, resume tracking, text to SQL conversion, invoice extraction, medical chatbot, financial stock analysis, and more. The projects showcase the deployment of LLM models like Google Gemini Pro, HuggingFace Models, OpenAI GPT, and technologies such as Langchain, Streamlit, LLaMA2, LLaMAindex, and more. The repository aims to provide end-to-end solutions for different AI applications.

LLM Document OCR is a Node.js tool that utilizes GPT4 and Claude3 for OCR and data extraction. It converts PDFs into PNGs, crops white-space, cleans up JSON strings, and supports various image formats. Users can customize prompts for data extraction. The tool is sponsored by Mercoa, offering API for BillPay and Invoicing.

Resume Job Matcher is a Python script that automates the process of matching resumes to a job description using AI. It leverages the Anthropic Claude API or OpenAI's GPT API to analyze resumes and provide a match score along with personalized email responses for candidates. The tool offers comprehensive resume processing, advanced AI-powered analysis, in-depth evaluation & scoring, comprehensive analytics & reporting, enhanced candidate profiling, and robust system management. Users can customize font presets, generate PDF versions of unified resumes, adjust logging level, change scoring model, modify AI provider, and adjust AI model. The final score for each resume is calculated based on AI-generated match score and resume quality score, ensuring content relevance and presentation quality are considered. Troubleshooting tips, best practices, contribution guidelines, and required Python packages are provided.

SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: * Benchmarks of equation solver implementations * Speed and robustness comparisons of methods for parameter estimation / inverse problems * Training universal differential equations (and subsets like neural ODEs) * Training of physics-informed neural networks (PINNs) * Surrogate comparisons, including radial basis functions, neural operators (DeepONets, Fourier Neural Operators), and more The SciML Bench suite is made to be a comprehensive open source benchmark from the ground up, covering the methods of computational science and scientific computing all the way to AI for science.

MouseTooltipTranslator is a Chrome extension that allows users to translate any text on a webpage by simply hovering over it. It supports both Google Translate and Bing Translate, and can also be used to listen to the pronunciation of words and phrases. Additionally, the extension can be used to translate text in input boxes and highlighted text, and to display translated tooltips for PDFs and YouTube videos. It also supports OCR, allowing users to translate text in images by holding down the left shift key and hovering over the image.

The Second Brain AI Agent Project is a tool designed to empower personal knowledge management by automatically indexing markdown files and links, providing a smart search engine powered by OpenAI, integrating seamlessly with different note-taking methods, and enhancing productivity by accessing information efficiently. The system is built on LangChain framework and ChromaDB vector store, utilizing a pipeline to process markdown files and extract text and links for indexing. It employs a Retrieval-augmented generation (RAG) process to provide context for asking questions to the large language model. The tool is beneficial for professionals, students, researchers, and creatives looking to streamline workflows, improve study sessions, delve deep into research, and organize thoughts and ideas effortlessly.

Extractor is an AI-powered data extraction library for Laravel that leverages OpenAI's capabilities to effortlessly extract structured data from various sources, including images, PDFs, and emails. It features a convenient wrapper around OpenAI Chat and Completion endpoints, supports multiple input formats, includes a flexible Field Extractor for arbitrary data extraction, and integrates with Textract for OCR functionality. Extractor utilizes JSON Mode from the latest GPT-3.5 and GPT-4 models, providing accurate and efficient data extraction.

The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of `unstructured` revolve around streamlining and optimizing the data processing workflow for LLMs. `unstructured` modular functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

DataChain is an open-source Python library for processing and curating unstructured data at scale. It supports AI-driven data curation using local ML models and LLM APIs, handles large datasets, and is Python-friendly with Pydantic objects. It excels at optimizing batch operations and is designed for offline data processing, curation, and ETL. Typical use cases include Computer Vision data curation, LLM analytics, and validation.

Gemini is an open-source model designed to handle multiple modalities such as text, audio, images, and videos. It utilizes a transformer architecture with special decoders for text and image generation. The model processes input sequences by transforming them into tokens and then decoding them to generate image outputs. Gemini differs from other models by directly feeding image embeddings into the transformer instead of using a visual transformer encoder. The model also includes a component called Codi for conditional generation. Gemini aims to effectively integrate image, audio, and video embeddings to enhance its performance.

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