Best AI tools for< Import Pdfs >

ElevenReader is a free read-aloud text app that elevates your listening experience by bringing any book, article, PDF, newsletter, or text to life with ultra-realistic AI narration. With a vast collection of literary classics, newsletters, and articles narrated with AI audio, ElevenReader offers a personalized audio experience with high-definition voices in 32 languages. Users can import their own content, create smart podcasts, and enjoy bimodal listening with synchronized highlighting. The app also features iconic voices and is available on iOS and Android devices.

LLMStack is an open-source platform that allows users to build AI Agents, workflows, and applications using their own data. It is a no-code AI app builder that supports model chaining from major providers like OpenAI, Cohere, Stability AI, and Hugging Face. Users can import various data sources such as Web URLs, PDFs, audio files, and more to enhance generative AI applications and chatbots. With a focus on collaboration, LLMStack enables users to share apps publicly or restrict access, with viewer and collaborator roles for multiple users to work together. Powered by React, LLMStack provides an easy-to-use interface for building AI applications.

SciSummary is an AI tool designed to summarize scientific articles and research papers quickly and efficiently. It utilizes advanced AI technology, specifically GPT-3.5 and GPT-4 models, to provide accurate and concise summaries for busy scientists, students, and enthusiasts. The platform allows users to submit documents via email, upload articles to the dashboard, or attach PDFs for summarization. With features like unlimited summaries, figure and table analysis, and chat messages, SciSummary is a valuable resource for researchers looking to stay updated with the latest trends in research.

AnkiDecks is an online tool that helps users generate flashcards from files or text using AI. It supports various file formats, including PDFs, Word documents, PowerPoint presentations, and text files. The generated flashcards can be used for studying purposes, particularly for language learning. AnkiDecks also offers features such as cloze (fill-in-the-blank) flashcards and text-to-speech functionality for language flashcards. Users can import the generated flashcards into the popular flashcard software Anki for further review and practice.

Doc2cart is an AI-powered platform that automates the extraction of product information from various documents such as invoices, price lists, and catalogs. It utilizes advanced OCR technology to convert paper or digital documents into structured e-commerce data that can be seamlessly integrated into popular e-commerce platforms and shopping carts. The platform focuses on data extraction and processing, providing users with the flexibility to utilize the extracted data in their systems efficiently.

AskCSV is a revolutionary AI-powered tool that empowers you to unlock valuable insights from your CSV files. Simply ask any question about your data, and AskCSV will provide you with instant, accurate answers and visualizations. Your data remains completely secure, processed directly in your browser's memory without any server uploads. With AskCSV, you can effortlessly analyze your data, identify trends, make informed decisions, and gain a deeper understanding of your business.

Page Pilot AI is a tool that helps e-commerce store owners create high-converting product pages and ad copy using artificial intelligence. It offers features such as product page generation, ad creative generation, and access to winning products. With Page Pilot AI, users can save time and money by automating the product testing phase and launching products faster.

BuildShip is a batch processing tool for ChatGPT that allows users to process ChatGPT tasks in parallel on a spreadsheet UI with CSV/JSON import and export. It supports various OpenAI models, including GPT4, Claude 3, and Gemini. Users can start with readymade templates and customize them with their own logic and models. The data generated is stored securely on the user's own Google Cloud project, and team collaboration is supported with granular access control.

nuvo is an AI-powered data import solution that offers fast, secure, and scalable data import solutions for software companies. It provides tools like nuvo Data Importer SDK and nuvo Data Pipeline to streamline manual and recurring ETL data imports, enabling users to manage data imports independently. With AI-enhanced automation, nuvo helps prepare clean data for preferred systems quickly and efficiently, reducing manual effort and improving data quality. The platform allows users to upload unlimited data in various formats, match imported data to system schemas, clean and validate data, and import clean data into target systems with just a click.

Kopy is an AI-powered tool designed for Shopify store owners to easily copy and import products from other stores with just one click. It offers features like native translation, AI copywriting, and easy-to-use interface. Kopy stands out with its instant product import, bulk import options, customization, translation to any language, and user-friendly interface. The tool saves time and money for dropshippers by automating product import and enhancing product details with AI. Kopy offers affordable pricing plans tailored to entrepreneurs' budgets, empowering their e-commerce journey. The tool supports copying products from platforms like Shopify, Aliexpress, CJ Dropshipping, Etsy, and Amazon.

Recipe Reactor is the ultimate kitchen companion that helps users unlock the full potential of their kitchen. It allows users to import, organize, plan meals, and explore new culinary horizons. With AI-powered recipe creation, effortless recipe importing, and comprehensive recipe management, Recipe Reactor simplifies, innovates, and masters the culinary world. Users can turn random ingredients into culinary masterpieces, reduce food waste, and enrich their cooking experience with educational insights.

The website offers a unique application that allows users to import and continue conversations with their ex-partners. By importing chat histories, users can interact with their exes through the app, enabling them to text or even date them post-breakup. Additionally, the platform provides AI tools for TikTok ad creative analytics.

Pozotron Studio is an AI-powered software suite designed to simplify scripted audio production processes for audiobooks, voiceovers, and other audio projects. It leverages state-of-the-art technology to enhance efficiency and accuracy in audio production, while allowing users to focus on creativity and core features. The tool automates tasks such as generating DAW marker files, pronunciation research, and script preparation, providing peace of mind about accuracy and highlighting errors for easy correction.

Superjoin is an AI-powered tool that allows users to automatically pull data from various tools into Google Sheets without the need for writing any code. It offers features like one-click connectors, auto-refresh schedules, data preview, and the ability to send report screenshots to Slack and Email. Superjoin is loved by thousands of users across hundreds of companies for its efficiency in automating workflows and data management.

Betafi is a cloud-based user research and product feedback platform that helps businesses capture, organize, and share customer feedback from various sources, including user interviews, usability testing, and product demos. It offers features such as timestamped note-taking, automatic transcription and translation, video clipping, and integrations with popular collaboration tools like Miro, Figma, and Notion. Betafi enables teams to gather qualitative and quantitative feedback from users, synthesize insights, and make data-driven decisions to improve their products and services.

xPage is an AI-powered landing page generator that helps e-commerce businesses create high-converting landing pages in seconds. With xPage, you can transform your product details or AliExpress link into a captivating landing page within seconds. xPage offers a variety of templates to choose from, so you can find the perfect one to captivate your audience and enhance your brand presence. xPage is also easy to use, with an intuitive design that makes it accessible to users of all skill levels. No coding or design expertise is required.

Voice Pen is a Speech to Text AI application available on the App Store for Apple devices. It allows users to record and transcribe speech into text, which can then be used to create notes, summaries, emails, messages, and blog posts. The app supports more than 50 languages and offers AI options for rewriting and transforming text. Voice Pen enhances productivity by providing features like background audio recording, language autodetection, and the ability to create various types of content. It also prioritizes user privacy by only collecting app usage analytics and not storing any audio or text data on its servers.

TurboScribe.ai is an AI transcription tool that converts audio and video files into text with high accuracy and efficiency. It utilizes advanced AI algorithms to transcribe content quickly, making it ideal for professionals, students, and anyone needing transcription services. The tool ensures security by verifying user identity and connection before processing the transcription. TurboScribe.ai is powered by Cloudflare for enhanced performance and security.

Dora is a no-code 3D animated website design platform that allows users to create stunning 3D and animated visuals without writing a single line of code. With Dora, designers, freelancers, and creative professionals can focus on what they do best: designing. The platform is tailored for professionals who prioritize design aesthetics without wanting to dive deep into the backend. Dora offers a variety of features, including a drag-and-connect constraint layout system, advanced animation capabilities, and pixel-perfect usability. With Dora, users can create responsive 3D and animated websites that translate seamlessly across devices.

Dora is an AI-powered platform that enables users to create 3D animated websites without the need for coding. It caters to designers, freelancers, and creative professionals who seek to design visually captivating websites effortlessly. With Dora, users can craft mesmerizing 3D and animated visuals that are responsive and seamlessly translate across devices. The platform is designed for professionals who prioritize design aesthetics and offers a no-code experience for those transitioning from other design tools. Dora leverages advanced AI algorithms to generate, customize, and deploy stunning landing pages, revolutionizing the web design process.

big-AGI is an AI suite designed for professionals seeking function, form, simplicity, and speed. It offers best-in-class Chats, Beams, and Calls with AI personas, visualizations, coding, drawing, side-by-side chatting, and more, all wrapped in a polished UX. The tool is powered by the latest models from 12 vendors and open-source servers, providing users with advanced AI capabilities and a seamless user experience. With continuous updates and enhancements, big-AGI aims to stay ahead of the curve in the AI landscape, catering to the needs of both developers and AI enthusiasts.

JabRef is an open-source, cross-platform citation and reference management tool that helps users collect, organize, cite, and share research sources. It offers features like searching across online scientific catalogues, importing references in various formats, extracting metadata from PDFs, customizable citation key generator, support for Word and LibreOffice/OpenOffice, and more. Users can organize their research items hierarchically, find and merge duplicates, attach related documents, and keep track of what they read. JabRef also supports sharing via various export options and syncs library contents in a team via a SQL database. It is actively developed, free of charge, and offers native BibTeX and Biblatex support.

The Neo4j GraphRAG package for Python is an official repository that provides features for creating and managing vector indexes in Neo4j databases. It aims to offer developers a reliable package with long-term commitment, maintenance, and fast feature updates. The package supports various Python versions and includes functionalities for creating vector indexes, populating them, and performing similarity searches. It also provides guidelines for installation, examples, and development processes such as installing dependencies, making changes, and running tests.

AIResume is an open-source resume creation platform that helps users easily create professional resumes, integrating AI technology to assist users in polishing their resumes. The project allows for template development using Vue 3, Vite, TypeScript, and Ant Design Vue. Users can edit resumes, export them as PDFs, switch between multiple resume templates, and collaborate on template development. AI features include resume refinement, deep optimization based on individual projects or experiences, and simulated interviews for user practice. Additional functionalities include theme color switching, high customization options, dark/light mode switching, real-time preview, drag-and-drop resume scaling, data export/import, data clearing, sample data prefilling, template market showcasing, and more.

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.

Markdrop is a Python package that facilitates the conversion of PDFs to markdown format while extracting images and tables. It also generates descriptive text descriptions for extracted tables and images using various LLM clients. The tool offers additional functionalities such as PDF URL support, AI-powered image and table descriptions, interactive HTML output with downloadable Excel tables, customizable image resolution and UI elements, and a comprehensive logging system. Markdrop aims to simplify the process of handling PDF documents and enhancing their content with AI-generated descriptions.

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.

This repository serves as a companion to the Build AI-Powered Apps with OpenAI and Node.js course on Frontend Masters. It includes course notes and provides alternative approaches for deprecated Langchain methods by installing the Langchain community module and importing loaders for document processing from PDFs and YouTube videos.

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.

AnyParser provides an API to accurately extract unstructured data (e.g., PDFs, images, charts) into a structured format. Users can set up their API key, run synchronous and asynchronous extractions, and perform batch extraction. The tool is useful for extracting text, numbers, and symbols from various sources like PDFs and images. It offers flexibility in processing data and provides immediate results for synchronous extraction while allowing users to fetch results later for asynchronous and batch extraction. AnyParser is designed to simplify data extraction tasks and enhance data processing efficiency.

MegaParse is a powerful and versatile parser designed to handle various types of documents such as text, PDFs, Powerpoint presentations, and Word documents with no information loss. It is fast, efficient, and open source, supporting a wide range of file formats. MegaParse ensures compatibility with tables, table of contents, headers, footers, and images, making it a comprehensive solution for document parsing.

Parsee AI is a high-level open source data extraction and structuring framework specialized for the extraction of data from a financial domain, but can be used for other use-cases as well. It aims to make the structuring of data from unstructured sources like PDFs, HTML files, and images as easy as possible. Parsee can be used locally in Python environments or through a hosted version for cloud-based jobs. It supports the extraction of tables, numbers, and other data elements, with the ability to create custom extraction templates and run jobs using different models.

Vision Parse is a tool that leverages Vision Language Models to parse PDF documents into beautifully formatted markdown content. It offers smart content extraction, content formatting, multi-LLM support, PDF document support, and local model hosting using Ollama. Users can easily convert PDFs to markdown with high precision and preserve document hierarchy and styling. The tool supports multiple Vision LLM providers like OpenAI, LLama, and Gemini for accuracy and speed, making document processing efficient and effortless.

The text-extract-api is a powerful tool that allows users to convert images, PDFs, or Office documents to Markdown text or JSON structured documents with high accuracy. It is built using FastAPI and utilizes Celery for asynchronous task processing, with Redis for caching OCR results. The tool provides features such as PDF/Office to Markdown and JSON conversion, improving OCR results with LLama, removing Personally Identifiable Information from documents, distributed queue processing, caching using Redis, switchable storage strategies, and a CLI tool for task management. Users can run the tool locally or on cloud services, with support for GPU processing. The tool also offers an online demo for testing purposes.

Chunkr is an open-source document intelligence API that provides a production-ready service for document layout analysis, OCR, and semantic chunking. It allows users to convert PDFs, PPTs, Word docs, and images into RAG/LLM-ready chunks. The API offers features such as layout analysis, OCR with bounding boxes, structured HTML and markdown output, and VLM processing controls. Users can interact with Chunkr through a Python SDK, enabling them to upload documents, process them, and export results in various formats. The tool also supports self-hosted deployment options using Docker Compose or Kubernetes, with configurations for different AI models like OpenAI, Google AI Studio, and OpenRouter. Chunkr is dual-licensed under the GNU Affero General Public License v3.0 (AGPL-3.0) and a commercial license, providing flexibility for different usage scenarios.

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.

Docling is a tool that bundles PDF document conversion to JSON and Markdown in an easy, self-contained package. It can convert any PDF document to JSON or Markdown format, understand detailed page layout, reading order, recover table structures, extract metadata such as title, authors, references, and language, and optionally apply OCR for scanned PDFs. The tool is designed to be stable, lightning fast, and suitable for macOS and Linux environments.

Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Deep Lake can be used for: 1. Storing data and vectors while building LLM applications 2. Managing datasets while training deep learning models Deep Lake simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more. Deep Lake works with data of any size, it is serverless, and it enables you to store all of your data in your own cloud and in one place. Deep Lake is used by Intel, Bayer Radiology, Matterport, ZERO Systems, Red Cross, Yale, & Oxford.

**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.

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