Best AI tools for< Process Pdf Inputs >

PDFgen is an AI-powered tool that allows users to generate PDF documents by providing simple text prompts. It uses artificial intelligence to create PDF templates for various purposes such as invoices, lease agreements, event tickets, and freelance contracts. The tool simplifies the process of document creation by automating the layout and design based on the input text.

ChatWithPDF is a ChatGPT plugin that allows users to query against small or large PDF documents directly in ChatGPT. It offers a convenient way to process and semantically search PDF documents based on your queries. By providing a temporary PDF URL, the plugin fetches relevant information from the PDF file and returns the most suitable matches according to your search input.

Quick Resume is an AI resume creation tool that allows users to generate professional resumes and CVs in seconds using advanced AI models. The tool offers a simple and quick process where users can select the type of resume they want, input their personal information, work experience, education, and skills, and then download the resume in PDF or LaTeX format. Quick Resume utilizes Google Gemini AI, a state-of-the-art artificial intelligence system, to ensure that resumes stand out in the job market. The tool is designed to be ATS-friendly, making it easier for users to pass through Applicant Tracking Systems used by companies.

Sourcely is an AI-powered academic search assistant designed to help students and researchers find, summarize, and add credible academic sources efficiently. With access to over 200 million research papers and advanced search filters, Sourcely streamlines the research process by simplifying source discovery, providing targeted citations, offering free PDF downloads, organizing citations in a personal library, generating credible summaries, and exporting references in various formats. The tool aims to save time, enhance the quality of work, and improve academic productivity.

Sprinkle AI is a website that allows users to create personalized storybooks for children. The storybooks are AI-powered, meaning that they are tailored to the child's individual interests and preferences. Users can choose from a variety of templates and themes, and then add their own text and images to create a truly unique storybook. Sprinkle AI also offers a variety of features to make the storybook creation process easy and fun, such as a built-in AI assistant that can help users with writing and editing. The finished product is a high-quality PDF file that can be printed or shared online.

ResumeSkool is a free AI resume building platform that simplifies the process of creating professional resumes. It utilizes artificial intelligence to analyze user input and generate well-structured resumes tailored to specific job requirements. With a user-friendly interface, ResumeSkool offers a seamless experience for individuals looking to enhance their job application prospects. The platform eliminates the need for manual formatting and content structuring, saving users time and effort. Whether you are a recent graduate or a seasoned professional, ResumeSkool equips you with the tools to craft compelling resumes that stand out to potential employers.

Autoppt is an AI PowerPoint maker that allows users to create stunning slide presentations effortlessly. It offers a user-friendly platform where you can input your topic or upload documents to generate beautifully designed AI slideshows. With Autoppt, you can convert PDF and Word files into PowerPoint presentations, choose from a variety of templates, customize your slides, and share your work seamlessly. The application leverages Artificial Intelligence to streamline the presentation creation process, making it ideal for professionals, educators, and anyone looking to enhance their presentations with AI technology.

Vectorizer.AI is an online tool that allows users to convert PNG and JPG images to SVG vectors quickly and easily using artificial intelligence. The application utilizes deep learning networks and classical algorithms to analyze, process, and convert images from pixels to geometric shapes. It offers a full-featured deep vector engine, clean corners, high performance, symmetry modeling, and adaptive simplification, among other advanced features. Vectorizer.AI supports various input and output formats, including SVG, PDF, EPS, DXF, and PNG, making it a versatile tool for creating scalable vector graphics.

ResumeWiz is an AI-powered resume builder that allows users to create professional resumes quickly and easily. With a user-friendly interface, ResumeWiz guides users through the resume building process, providing templates and recommendations to optimize the resume for Applicant Tracking Systems (ATS). Users can input personal information, work experience, education, and skills into the AI-powered form and receive an ATS score to understand how well their resume will perform. The platform offers the option to download the resume as a PDF or PNG file for convenient sharing.

Text To Resume is an AI-powered tool that helps users create professional resumes effortlessly. By utilizing advanced AI technology (GPT-4), the tool transforms users' career information into visually appealing and ATS-friendly resumes. Users can input their work experience, skills, education, and contact details, and the tool generates four unique PDF resume designs within minutes. Additionally, users have the option to further customize their resumes using Markdown and LaTeX files. Text To Resume simplifies the resume creation process by eliminating the need for design expertise and streamlining the editing process.

PaperTyper is an AI-driven essay writing tool that helps users by proposing ideas, streamlining academic tasks, and instantly generating original content for various essay types. Users can access a meticulously crafted essay on their chosen subject with the free paper typer, selecting from 19 different essay genres and 5 distinct essay tones. The tool simplifies the writing process by allowing users to pick an essay type and tone, input their details, generate content aligned with their specifications, and easily copy or download the resulting content. With features like plagiarism assurance, AI detector tool, and the ability to export work as a PDF file, PaperTyper offers a user-friendly experience without requiring any technical expertise.

The Excel Formula Generator is an AI-driven tool that simplifies the process of creating and understanding Excel formulas. It helps users convert text instructions into formulas or input existing formulas to have them explained. The tool also offers capabilities for data analysis, data visualization, and advanced data models, making it valuable for entry-level professionals in various industries.

Chat PDF AI Online is an advanced AI tool that revolutionizes the way users interact with PDF documents. It offers cutting-edge AI features to enhance the PDF experience, providing seamless solutions for reading, summarizing, analyzing, and translating PDF files. With features like longer context support, powerful tabular data analysis, and advanced LLM support, Chat PDF AI Online ensures smarter and faster document processing. Users can securely upload and process large PDF files, benefiting from high accuracy and efficiency in document handling.

Collate for Mac OS is a free application designed to help users organize, summarize, and chat with PDF documents on their Mac computers. The app simplifies the process of managing PDF files by offering features such as organizing PDFs in a user-friendly library, summarizing PDFs to provide instant insights with zero effort, and enabling users to chat with PDFs to ask questions and get answers. Collate runs locally on your Mac and is available for download on the Mac App Store. With a focus on user privacy, the application ensures a secure and seamless experience for managing PDF documents.

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

Chat With PDF AI Tool is an innovative online application that allows users to interact with a virtual assistant powered by artificial intelligence to convert and manipulate PDF files. The tool simplifies the process of working with PDFs by offering a conversational interface for tasks such as conversion, editing, and extraction. Users can upload PDF files, ask questions, and receive instant responses and actions from the AI assistant. With its user-friendly design and advanced AI capabilities, Chat With PDF AI Tool revolutionizes the way users handle PDF documents.

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.

The Chat With PDF AI Tool is an innovative application that allows users to interact with PDF documents using artificial intelligence technology. Users can engage in conversations with the AI tool to extract information, ask questions, and receive instant responses. The tool simplifies the process of working with PDF files by providing a conversational interface, making it user-friendly and efficient. With its advanced AI capabilities, the tool can understand natural language queries and provide accurate results, enhancing productivity and workflow efficiency.

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.

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.

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.

This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

The serverless-pdf-chat repository contains a sample application that allows users to ask natural language questions of any PDF document they upload. It leverages serverless services like Amazon Bedrock, AWS Lambda, and Amazon DynamoDB to provide text generation and analysis capabilities. The application architecture involves uploading a PDF document to an S3 bucket, extracting metadata, converting text to vectors, and using a LangChain to search for information related to user prompts. The application is not intended for production use and serves as a demonstration and educational tool.

MiniCPM-V is a series of end-side multimodal LLMs designed for vision-language understanding. The models take image and text inputs to provide high-quality text outputs. The series includes models like MiniCPM-Llama3-V 2.5 with 8B parameters surpassing proprietary models, and MiniCPM-V 2.0, a lighter model with 2B parameters. The models support over 30 languages, efficient deployment on end-side devices, and have strong OCR capabilities. They achieve state-of-the-art performance on various benchmarks and prevent hallucinations in text generation. The models can process high-resolution images efficiently and support multilingual capabilities.

Groma is a grounded multimodal assistant that excels in region understanding and visual grounding. It can process user-defined region inputs and generate contextually grounded long-form responses. The tool presents a unique paradigm for multimodal large language models, focusing on visual tokenization for localization. Groma achieves state-of-the-art performance in referring expression comprehension benchmarks. The tool provides pretrained model weights and instructions for data preparation, training, inference, and evaluation. Users can customize training by starting from intermediate checkpoints. Groma is designed to handle tasks related to detection pretraining, alignment pretraining, instruction finetuning, instruction following, and more.

**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.

InfLLM is a training-free memory-based method that unveils the intrinsic ability of LLMs to process streaming long sequences. It stores distant contexts into additional memory units and employs an efficient mechanism to lookup token-relevant units for attention computation. Thereby, InfLLM allows LLMs to efficiently process long sequences while maintaining the ability to capture long-distance dependencies. Without any training, InfLLM enables LLMs pre-trained on sequences of a few thousand tokens to achieve superior performance than competitive baselines continually training these LLMs on long sequences. Even when the sequence length is scaled to 1, 024K, InfLLM still effectively captures long-distance dependencies.

NExT-GPT is an end-to-end multimodal large language model that can process input and generate output in various combinations of text, image, video, and audio. It leverages existing pre-trained models and diffusion models with end-to-end instruction tuning. The repository contains code, data, and model weights for NExT-GPT, allowing users to work with different modalities and perform tasks like encoding, understanding, reasoning, and generating multimodal content.

otto-m8 is a flowchart based automation platform designed to run deep learning workloads with minimal to no code. It provides a user-friendly interface to spin up a wide range of AI models, including traditional deep learning models and large language models. The tool deploys Docker containers of workflows as APIs for integration with existing workflows, building AI chatbots, or standalone applications. Otto-m8 operates on an Input, Process, Output paradigm, simplifying the process of running AI models into a flowchart-like UI.

EvalPlus is a rigorous evaluation framework for LLM4Code, providing HumanEval+ and MBPP+ tests to evaluate large language models on code generation tasks. It offers precise evaluation and ranking, coding rigorousness analysis, and pre-generated code samples. Users can use EvalPlus to generate code solutions, post-process code, and evaluate code quality. The tool includes tools for code generation and test input generation using various backends.

SimAI is the industry's first full-stack, high-precision simulator for AI large-scale training. It provides detailed modeling and simulation of the entire LLM training process, encompassing framework, collective communication, network layers, and more. This comprehensive approach offers end-to-end performance data, enabling researchers to analyze training process details, evaluate time consumption of AI tasks under specific conditions, and assess performance gains from various algorithmic optimizations.

Cortex is a tool that simplifies and accelerates the process of creating applications utilizing modern AI models like chatGPT and GPT-4. It provides a structured interface (GraphQL or REST) to a prompt execution environment, enabling complex augmented prompting and abstracting away model connection complexities like input chunking, rate limiting, output formatting, caching, and error handling. Cortex offers a solution to challenges faced when using AI models, providing a simple package for interacting with NL AI models.

LogicStudio.ai is a powerful visual canvas-based tool for building, managing, and visualizing complex logic flows involving AI agents, data inputs, and outputs. It provides an intuitive interface to streamline development processes by offering features like drag-and-drop canvas design, dynamic components, real-time connections, import/export capabilities, zoom & pan controls, file management, AI integration, editable views, and various output formats. Users can easily add, connect, configure, and manage components to create interactive systems and workflows.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

Refly.AI is an open-source AI-native creation engine that empowers users to transform ideas into production-ready content. It features a free-form canvas interface with multi-threaded conversations, knowledge base integration, contextual memory, intelligent search, WYSIWYG AI editor, and more. Users can leverage AI-powered capabilities, context memory, knowledge base integration, quotes, and AI document editing to enhance their content creation process. Refly offers both cloud and self-hosting options, making it suitable for individuals, enterprises, and organizations. The tool is designed to facilitate human-AI collaboration and streamline content creation workflows.

Codellm-devkit (CLDK) is a Python library that serves as a multilingual program analysis framework bridging traditional static analysis tools and Large Language Models (LLMs) specialized for code (CodeLLMs). It simplifies the process of analyzing codebases across multiple programming languages, enabling the extraction of meaningful insights and facilitating LLM-based code analysis. The library provides a unified interface for integrating outputs from various analysis tools and preparing them for effective use by CodeLLMs. Codellm-devkit aims to enable the development and experimentation of robust analysis pipelines that combine traditional program analysis tools and CodeLLMs, reducing friction in multi-language code analysis and ensuring compatibility across different tools and LLM platforms. It is designed to seamlessly integrate with popular analysis tools like WALA, Tree-sitter, LLVM, and CodeQL, acting as a crucial intermediary layer for efficient communication between these tools and CodeLLMs. The project is continuously evolving to include new tools and frameworks, maintaining its versatility for code analysis and LLM integration.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Indexify is an open-source engine for building fast data pipelines for unstructured data (video, audio, images, and documents) using reusable extractors for embedding, transformation, and feature extraction. LLM Applications can query transformed content friendly to LLMs by semantic search and SQL queries. Indexify keeps vector databases and structured databases (PostgreSQL) updated by automatically invoking the pipelines as new data is ingested into the system from external data sources. **Why use Indexify** * Makes Unstructured Data **Queryable** with **SQL** and **Semantic Search** * **Real-Time** Extraction Engine to keep indexes **automatically** updated as new data is ingested. * Create **Extraction Graph** to describe **data transformation** and extraction of **embedding** and **structured extraction**. * **Incremental Extraction** and **Selective Deletion** when content is deleted or updated. * **Extractor SDK** allows adding new extraction capabilities, and many readily available extractors for **PDF**, **Image**, and **Video** indexing and extraction. * Works with **any LLM Framework** including **Langchain**, **DSPy**, etc. * Runs on your laptop during **prototyping** and also scales to **1000s of machines** on the cloud. * Works with many **Blob Stores**, **Vector Stores**, and **Structured Databases** * We have even **Open Sourced Automation** to deploy to Kubernetes in production.

The Keras-llm-robot Web UI project is an open-source tool designed for offline deployment and testing of various open-source models from the Hugging Face website. It allows users to combine multiple models through configuration to achieve functionalities like multimodal, RAG, Agent, and more. The project consists of three main interfaces: chat interface for language models, configuration interface for loading models, and tools & agent interface for auxiliary models. Users can interact with the language model through text, voice, and image inputs, and the tool supports features like model loading, quantization, fine-tuning, role-playing, code interpretation, speech recognition, image recognition, network search engine, and function calling.

Formal ops consultant with PDF integration

Fill legal forms & complex PDF documents easily! Upload a file, provide data sources and I'll handle the rest.

Upload your process map and I will analyse and suggest improvements

Friendly process engineer for Coda.io

Guides clear BPMN process design with ASCII art

Optimizes production processes for improved efficiency and quality.

Optimizes business operations through process enhancements.

Optimizes production processes for efficient large-scale operations.

Improves operational efficiency by optimizing processes and reducing waste.

Discover Process Talks: Your Next Investment!

Optimizes manufacturing processes for efficiency and quality.

Emulating Whitehead's insights on 'Process and Reality'

Process Documentation for serving GPTs.

Trademark Process Assistant, Not an Attorney & Definitely Not Legal Advice (independently verify info received). Gain insights on U.S. trademark process & concepts, USPTO resources, application steps & more - all while being reminded of the importance of consulting legal pros 4 specific guidance.

Structured process for prioritizing marketing tasks based on strategic alignment. Outputs in Eisenhower, RACI and other methodologies.

Assists in the caregiving process for seniors.

Guides future parents through the adoption process with empathy and information.

Insurance providers collect and process personal health, financial, and property information, making it crucial to implement comprehensive data protection strategies.

Formal SBIR process expert for Air Force/Space Force

To streamline the process of creating scripts for Brut-style videos by providing structured guidance in researching, strategizing, and writing, ensuring the final script is rich in content and visually captivating.