Best AI tools for< Read Documents >

PopAi is a personal AI workspace that revolutionizes document interaction, offering seamless navigation, enhanced readability, and universal accessibility. It allows users to effortlessly navigate through intricate documents, magnify details, and tailor the layout for supreme clarity. PopAi also generates images on command, provides access to image prompts and generation codes, and offers image-based homework help, enriching educational support with visual aids. Additionally, it can effortlessly turn ideas into PowerPoint slides with customizable outlines, smart layouts, and automatic illustrations.

JENOVA is an AI tool that provides users with access to the best intelligence and expertise by synthesizing advanced AI models and tools into one unified AI experience. It ensures users always get the best answers by routing queries to the most optimal model for their needs. JENOVA offers an expanding suite of useful tools and capabilities, including document reading for various formats, image comprehension powered by multi-modal AI models, and web search for up-to-date information. Privacy is a priority, as conversations and data are never used for training and are securely stored in a protected database.

NaturalReader is a text-to-speech software that converts text, PDF, and other formats into spoken audio. It is designed for personal, commercial, and educational use. NaturalReader has a variety of features, including cross-platform compatibility, an AI voice generator, and support for students with dyslexia or other learning disabilities.

Novo AI is an AI application that empowers financial institutions by leveraging Generative AI and Large Language Models to streamline operations, maximize insights, and automate processes like claims processing and customer support traditionally handled by humans. The application helps insurance companies understand claim documents, automate claims processing, optimize pricing strategies, and improve customer satisfaction. For banks, Novo AI automates document processing across multiple languages and simplifies adverse media screenings through efficient research on live internet data.

Docalysis is an AI-powered tool that allows you to chat with your PDF files. It can answer your questions about your files within seconds, saving you hours of time. Docalysis is secure and easy to use. Simply upload your PDF file and start chatting with the AI.

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.

Skimming is an AI tool that enables users to interact with various types of data, including audio, video, and text, to extract knowledge. It offers features like chatting with documents, YouTube videos, websites, audio, and video, as well as custom prompts and multilingual support. Skimming is trusted by over 100,000 users and is designed to save time and enhance information extraction. The tool caters to a diverse audience, including teachers, students, businesses, researchers, scholars, lawyers, HR professionals, YouTubers, and podcasters.

Unriddle is an AI-powered research and writing tool that helps users quickly find information in documents, simplify complex topics, take notes, and write with the power of AI. It generates an AI assistant on top of any document, allowing users to quickly find, summarize, and understand information. Unriddle also understands the meaning behind users' writing and automatically links them to relevant information they've read and written about in the past. Additionally, it offers a Chrome extension for summarizing articles with a single click and supports over 90 languages.

DocsChat is an AI-powered document conversation tool that revolutionizes the way users interact with various types of documents. It leverages OCR-powered AI technology to streamline document interactions, making it easier to comprehend, exchange knowledge, troubleshoot, and navigate through different document types. With a focus on enhancing user experiences across reading, research, business, legal, and training domains, DocsChat offers a versatile platform for effortless and personalized document engagement.

Unriddle is an AI-powered research and writing tool that helps users quickly find, summarize, and understand information from documents. It uses natural language processing and machine learning to generate AI assistants that can be placed on top of any document, providing users with real-time insights and summaries. Unriddle also offers a variety of features to help users write better, including AI-powered autocomplete and grammar checking. With Unriddle, users can save time on research and writing, and produce higher-quality work.

Paperguide is an AI Research Platform that offers an all-in-one solution for researchers and students to discover, read, write, manage research papers with ease. It provides AI-powered Reference Manager and Writing Assistant to help users understand papers, manage references, annotate/take notes, and supercharge their writing process. With features like AI Search, Instant Summaries, Effortless Annotations, and Flawless Citations, Paperguide aims to streamline the academic and research workflow for its users.

AIReads is a revolutionary AI-powered tool that helps you read and understand text more efficiently. With its advanced natural language processing capabilities, AIReads can summarize long documents, extract key insights, and even translate text into multiple languages. Whether you're a student, researcher, or professional, AIReads can help you save time and improve your comprehension.

TanyaPDF is an AI-powered tool that helps users to learn and understand PDF documents more efficiently. By leveraging AI technology, TanyaPDF can read and summarize research files, allowing users to interact with the content through an interactive chat interface. Users can save and review conversations, ask questions, receive accurate answers, and enhance their learning experience without losing track of their progress. TanyaPDF is suitable for students, researchers, and professionals who seek assistance in tasks such as thesis writing, research analysis, legal document comprehension, financial report review, and interactive document creation.

Bunni is a revolutionary tool that allows you to chat with your PDF documents, making it easier than ever to summarize, extract information, and ask questions about any PDF file. With Bunni, you can quickly and easily get the information you need from your PDFs, without having to read through the entire document. Bunni is perfect for students, researchers, professionals, and anyone else who needs to work with PDFs on a regular basis.

Iflow is an AI assistant application designed to help users efficiently acquire knowledge in various areas, whether it's for daily entertainment, general life knowledge, or professional academic research. It provides real-time answers to questions, summarizes lengthy articles, and assists in structuring documents to enhance creativity and productivity. With Iflow, users can easily enter a state of flow where knowledge flows effortlessly. The application covers a wide range of topics and is equipped with advanced natural language processing capabilities to cater to diverse user needs.

Bearly is an AI-powered tool that enhances your workflow by providing advanced AI capabilities. It integrates seamlessly with your existing workflow, allowing you to read, write, and create content with ease. With Bearly, you can interact with documents, analyze and ask questions, transcribe audio and video, access real-time web information, and generate meeting minutes. Its open AI platform provides access to various AI models, ensuring you find the perfect fit for your needs. Bearly prioritizes security, with zero logging, chat and document encryption, and a secure infrastructure to safeguard your data.

Speak4Me is a text-to-speech application that converts any text file, including PDFs and websites, into audible content. It enables users to listen to their documents or school materials anytime, anywhere. With features like scanning physical or digital text, reading web pages aloud, and a new ChatWithMe function, Speak4Me aims to enhance reading experiences and improve focus for individuals with reading issues. The application is trusted by over 15,000 people on the App Store and offers a free version for schools, making education more accessible for everyone.

Chat-docs AI is an innovative AI application that allows users to interact with PDF documents through natural language conversations. The tool leverages advanced artificial intelligence algorithms to summarize long documents, explain complex concepts, and find key information with cited sources in seconds. It transforms PDFs into intelligent entities capable of dialogue, making learning, research, and analysis more interactive and personalized. Chat-docs AI is designed to be intuitive, secure, and accessible to users from various backgrounds, revolutionizing the way individuals engage with textual content.

Aethera is a collaborative knowledge discovery platform that leverages advanced AI models to help teams and individuals understand documents, YouTube videos, and websites without the need to read them. It offers powerful features for organizing, personalizing, and discovering information, along with document management tools, multilingual support, and the ability to summarize and compare multiple documents. Aethera also allows users to create personalized AI assistants, chat with sets of documents using personas, and work collaboratively within organizations. The platform is designed to streamline knowledge discovery processes and boost productivity by providing tailored insights and summaries from various sources.

Google Patents is a search engine that allows users to search through the full text of patents that have been granted by the United States Patent and Trademark Office (USPTO). The database includes patents from 1790 to the present day, and users can search by keyword, inventor, assignee, or patent number. Google Patents also provides access to images of the original patent documents, as well as links to related patents and articles.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

Talemate is a roleplay tool that allows users to interact with AI agents for dialogue, narration, summarization, direction, editing, world state management, character/scenario creation, text-to-speech, and visual generation. It supports multiple AI clients and APIs, offers long-term memory using ChromaDB, and provides tools for managing NPCs, AI-assisted character creation, and scenario creation. Users can customize prompts using Jinja2 templates and benefit from a modern, responsive UI. The tool also integrates with Runpod for enhanced functionality.

BotSharp is an open-source machine learning framework for building AI bot platforms. It provides a comprehensive set of tools and components for developing and deploying intelligent virtual assistants. BotSharp is designed to be modular and extensible, allowing developers to easily integrate it with their existing systems and applications. With BotSharp, you can quickly and easily create AI-powered chatbots, virtual assistants, and other conversational AI applications.

VectorFlow is an open source, high throughput, fault tolerant vector embedding pipeline. It provides a simple API endpoint for ingesting large volumes of raw data, processing, and storing or returning the vectors quickly and reliably. The tool supports text-based files like TXT, PDF, HTML, and DOCX, and can be run locally with Kubernetes in production. VectorFlow offers functionalities like embedding documents, running chunking schemas, custom chunking, and integrating with vector databases like Pinecone, Qdrant, and Weaviate. It enforces a standardized schema for uploading data to a vector store and supports features like raw embeddings webhook, chunk validation webhook, S3 endpoint, and telemetry. The tool can be used with the Python client and provides detailed instructions for running and testing the functionalities.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

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.

RAPTOR introduces a novel approach to retrieval-augmented language models by constructing a recursive tree structure from documents. This allows for more efficient and context-aware information retrieval across large texts, addressing common limitations in traditional language models. Users can add documents to the tree, answer questions based on indexed documents, save and load the tree, and extend RAPTOR with custom summarization, question-answering, and embedding models. The tool is designed to be flexible and customizable for various NLP tasks.

Redbox Copilot is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License.

Redbox is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License. Security measures are in place to ensure user data privacy and considerations are being made to make the core-api secure.

This project is a tutorial on developing large model applications for novice developers. It aims to provide a comprehensive introduction to large model development, focusing on Alibaba Cloud servers and integrating personal knowledge assistant projects. The tutorial covers the following topics: 1. **Introduction to Large Models**: A simplified introduction for novice developers on what large models are, their characteristics, what LangChain is, and how to develop an LLM application. 2. **How to Call Large Model APIs**: This section introduces various methods for calling APIs of well-known domestic and foreign large model products, including calling native APIs, encapsulating them as LangChain LLMs, and encapsulating them as Fastapi calls. It also provides a unified encapsulation for various large model APIs, such as Baidu Wenxin, Xunfei Xinghuo, and Zh譜AI. 3. **Knowledge Base Construction**: Loading, processing, and vector database construction of different types of knowledge base documents. 4. **Building RAG Applications**: Integrating LLM into LangChain to build a retrieval question and answer chain, and deploying applications using Streamlit. 5. **Verification and Iteration**: How to implement verification and iteration in large model development, and common evaluation methods. The project consists of three main parts: 1. **Introduction to LLM Development**: A simplified version of V1 aims to help beginners get started with LLM development quickly and conveniently, understand the general process of LLM development, and build a simple demo. 2. **LLM Development Techniques**: More advanced LLM development techniques, including but not limited to: Prompt Engineering, processing of multiple types of source data, optimizing retrieval, recall ranking, Agent framework, etc. 3. **LLM Application Examples**: Introduce some successful open source cases, analyze the ideas, core concepts, and implementation frameworks of these application examples from the perspective of this course, and help beginners understand what kind of applications they can develop through LLM. Currently, the first part has been completed, and everyone is welcome to read and learn; the second and third parts are under creation. **Directory Structure Description**: requirements.txt: Installation dependencies in the official environment notebook: Notebook source code file docs: Markdown documentation file figures: Pictures data_base: Knowledge base source file used

Local-GenAI Search is a local generative search engine powered by the Llama3 model, allowing users to ask questions about their local files and receive concise answers with relevant document references. It utilizes MS MARCO embeddings for semantic search and can run locally on a 32GB laptop or computer. The tool can be used to index local documents, search for information, and provide generative search services through a user interface.

Chroma is an open-source embedding database that provides a simple, scalable, and feature-rich way to build Python or JavaScript LLM apps with memory. It offers a fully-typed, fully-tested, and fully-documented API that makes it easy to get started and scale your applications. Chroma also integrates with popular tools like LangChain and LlamaIndex, and supports a variety of embedding models, including Sentence Transformers, OpenAI embeddings, and Cohere embeddings. With Chroma, you can easily add documents to your database, query relevant documents with natural language, and compose documents into the context window of an LLM like GPT3 for additional summarization or analysis.

ChatData is a robust chat-with-documents application designed to extract information and provide answers by querying the MyScale free knowledge base or uploaded documents. It leverages the Retrieval Augmented Generation (RAG) framework, millions of Wikipedia pages, and arXiv papers. Features include self-querying retriever, VectorSQL, session management, and building a personalized knowledge base. Users can effortlessly navigate vast data, explore academic papers, and research documents. ChatData empowers researchers, students, and knowledge enthusiasts to unlock the true potential of information retrieval.

pyLLMSearch is an advanced RAG system that offers a convenient question-answering system with a simple YAML-based configuration. It enables interaction with multiple collections of local documents, with improvements in document parsing, hybrid search, chat history, deep linking, re-ranking, customizable embeddings, and more. The package is designed to work with custom Large Language Models (LLMs) from OpenAI or installed locally. It supports various document formats, incremental embedding updates, dense and sparse embeddings, multiple embedding models, 'Retrieve and Re-rank' strategy, HyDE (Hypothetical Document Embeddings), multi-querying, chat history, and interaction with embedded documents using different models. It also offers simple CLI and web interfaces, deep linking, offline response saving, and an experimental API.

Awesome LLM Security is a curated collection of tools, documents, and projects related to Large Language Model (LLM) security. It covers various aspects of LLM security including white-box, black-box, and backdoor attacks, defense mechanisms, platform security, and surveys. The repository provides resources for researchers and practitioners interested in understanding and safeguarding LLMs against adversarial attacks. It also includes a list of tools specifically designed for testing and enhancing LLM security.

The `sec-parser` project simplifies extracting meaningful information from SEC EDGAR HTML documents by organizing them into semantic elements and a tree structure. It helps in parsing SEC filings for financial and regulatory analysis, analytics and data science, AI and machine learning, causal AI, and large language models. The tool is especially beneficial for AI, ML, and LLM applications by streamlining data pre-processing and feature extraction.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

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.

Dolma is a dataset and toolkit for curating large datasets for (pre)-training ML models. The dataset consists of 3 trillion tokens from a diverse mix of web content, academic publications, code, books, and encyclopedic materials. The toolkit provides high-performance, portable, and extensible tools for processing, tagging, and deduplicating documents. Key features of the toolkit include built-in taggers, fast deduplication, and cloud support.

Expert in paleography for genealogical document analysis.

Ask about your documents to see how you could make them easier to read for everyone and more accessible for people with disabilities. NOTE: It does not always get everything right on the first go. Feel free to hit the regenerate button or ask for more info if you want to get richer feedback.

Cantonese TTS assistant for seniors.

Japanese OCR and text reader　日本語OCR　読み取り失敗文字の修復機能つき。テスト中

画像中の文章を日本語に翻訳します。（使い方：画像をアップロードするだけ。プロンプトの文章は不要です。）　2023/12/29 より自然な日本語になるように修正

Your personal assistant for Algorand subscription lookups, Subtopia API and platform documentation

Reads text from screenshots aloud

I'm eager to read your work and give you feedback to improve your skills.

Give me the name of a student and what you want to say and I'll help you write your reports. Upload your comments and I will proof read them.

上传一个PDF文件，先解释文件中的主题，然后提出一个多项选择题来帮助您理解文件中的核心概念，根据您掌握的情况，调整难易程度！

This GPT can read all Streamlit Documantation and helps you about Streamlit.

用生活所感去读书,用读书所得去生活

Interprets images of coffee cups for personalized readings.

I am a scholar of Plato's 'Gorgias'.

Your quirky guide to the literary enlightenment.

Upload a picture of your hand, your aura, or your handwriting. I'll draw the tarot cards (you can upload a photo as well) and read your destiny through Tarot, Palmistry, Runes, Numerology, Graphology, Aura Reading, and more.

Learn how to read other people's body langauge, and us your own to communicate powerfully.

read your life towards palm

Ancient mystic from another dimension here to read your mind within 20 questions!

I read and analyze annual reports of companies. Just upload the annual report PDF and start asking me questions!