Best AI tools for< Extract Natural Language >

Vectorize is a fast, accurate, and production-ready AI tool that helps users turn unstructured data into optimized vector search indexes. It leverages Large Language Models (LLMs) to create copilots and enhance customer experiences by extracting natural language from various sources. With built-in support for top AI platforms and a variety of embedding models and chunking strategies, Vectorize enables users to deploy real-time vector pipelines for accurate search results. The tool also offers out-of-the-box connectors to popular knowledge repositories and collaboration platforms, making it easy to transform knowledge into AI-generated content.

expert.ai is an AI platform that offers natural language technologies and responsible AI integrations across various industries such as insurance, banking, publishing, and more. The platform helps streamline operations, extract critical data, drive revelations, ensure compliance, and analyze complex documents. It provides solutions for insurers, pharmaceuticals, publishers, and financial services companies, leveraging a hybrid AI approach and purpose-built natural language workflow. expert.ai's Green Glass Approach focuses on transparent, sustainable, practical, and human-centered AI solutions.

Datumbox is a machine learning platform that offers a powerful open-source Machine Learning Framework written in Java. It provides a large collection of algorithms, models, statistical tests, and tools to power up intelligent applications. The platform enables developers to build smart software and services quickly using its REST Machine Learning API. Datumbox API offers off-the-shelf Classifiers and Natural Language Processing services for applications like Sentiment Analysis, Topic Classification, Language Detection, and more. It simplifies the process of designing and training Machine Learning models, making it easy for developers to create innovative applications.

Envistudios offers AI-powered solutions for business excellence through their innovative SaaS products 'Documente' and 'Infomente'. These platforms leverage artificial intelligence, natural language processing, and machine learning to provide intelligent document processing and generative business intelligence. Envistudios aims to empower businesses by unlocking insights from data, facilitating data-driven decision-making, and optimizing workflows.

AgentQL is an AI-powered tool for painless data extraction and web automation. It eliminates the need for fragile XPath or DOM selectors by using semantic selectors and natural language descriptions to find web elements reliably. With controlled output and deterministic behavior, AgentQL allows users to shape data exactly as needed. The tool offers features such as extracting data, filling forms automatically, and streamlining testing processes. It is designed to be user-friendly and efficient for developers and data engineers.

RegexBot is an AI-powered Regex Builder that allows users to test and convert natural language into powerful regular expressions effortlessly. It leverages the power of AI to help users master regular expressions by providing tools to match specific patterns like URLs, email addresses, ZIP codes, and words containing only uppercase letters. With a user-friendly interface, RegexBot simplifies the process of creating and validating regular expressions, making it a valuable tool for developers, data analysts, and anyone working with text data.

expert.ai is an AI platform that offers natural language technologies and responsible AI integrations across various industries such as insurance, banking, publishing, and more. The platform helps streamline operations, extract critical data, drive revelations, ensure compliance, and deliver key information for businesses. With a focus on responsible AI, expert.ai provides solutions for insurers, pharmaceuticals, publishers, and financial services companies to reduce errors, save time, lower costs, and accelerate intelligent process automation.

FileGPT is a powerful GPT-AI application designed to enhance your workflow by providing quick and accurate responses to your queries across various file formats. It allows users to interact with different types of files, extract text from handwritten documents, and analyze audio and video content. With FileGPT, users can say goodbye to endless scrolling and searching, and hello to a smarter, more intuitive way of working with their documents.

Explosion is a software company specializing in developer tools and tailored solutions for AI, Machine Learning, and Natural Language Processing (NLP). They are the makers of spaCy, one of the leading open-source libraries for advanced NLP. The company offers consulting services and builds developer tools for various AI-related tasks, such as coreference resolution, dependency parsing, image classification, named entity recognition, and more.

Summarizer is a Chrome extension that allows users to summarize articles and webpages quickly and efficiently. With this tool, users can extract key information from lengthy texts, saving time and enhancing productivity. The extension provides concise summaries that capture the main points of the content, making it easier for users to grasp the essential details without having to read through the entire text. Summarizer is a valuable tool for students, researchers, professionals, and anyone who needs to process large amounts of information in a short time.

Petal is a document analysis platform powered by generative AI technology. It allows users to chat with their documents, providing fully sourced and reliable answers by linking to their own knowledge bases. Users can train AI on their documents to support their work, ensuring centralized knowledge management and document synchronization. Petal offers features such as automatic metadata extraction, file deduplication, and collaboration tools to enhance productivity and streamline workflows for researchers, faculty, and industry experts.

Insight7 is a powerful AI-powered tool that helps businesses extract insights from customer and employee interviews. It uses natural language processing and machine learning to analyze large volumes of unstructured data, such as transcripts, audio recordings, and videos. Insight7 can identify key themes, trends, and sentiment, which can then be used to improve products, services, and customer experiences.

Parsio is an AI-powered document parser that can extract structured data from PDFs, emails, and other documents. It uses natural language processing to understand the context of the document and identify the relevant data points. Parsio can be used to automate a variety of tasks, such as extracting data from invoices, receipts, and emails.

Tinq.ai is a natural language processing (NLP) tool that provides a range of text analysis capabilities through its API. It offers tools for tasks such as plagiarism checking, text summarization, sentiment analysis, named entity recognition, and article extraction. Tinq.ai's API can be integrated into applications to add NLP functionality, such as content moderation, sentiment analysis, and text rewriting.

BabblerAI is an advanced artificial intelligence tool designed to assist businesses in analyzing and extracting valuable insights from large volumes of text data. The application utilizes natural language processing and machine learning algorithms to provide users with actionable intelligence and automate the process of information extraction. With BabblerAI, users can streamline their data analysis workflows, uncover trends and patterns, and make data-driven decisions with confidence. The tool is user-friendly and offers a range of features to enhance productivity and efficiency in data analysis tasks.

Magic Marker is an AI tool that allows users to unlock document insights effortlessly by highlighting specific information using natural language queries. It can quickly identify skills in resumes, specific ingredients in recipes, and key information from book chapters to create quick summaries. The tool is designed to streamline various tasks related to document analysis through AI technology.

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.

MapDeduce is an AI-powered tool that helps users understand and analyze complex documents. It can be used to summarize documents, extract key information, and identify potential red flags. MapDeduce is designed to save users time and effort by automating the process of document analysis.

Docubase.ai is a powerful document analysis tool that uses advanced natural language processing and machine learning to extract information and provide relevant answers to your queries. It can automatically extract text content from uploaded documents, generate relevant questions, and extract answers from the document content. Docubase.ai supports a wide range of document formats, including PDF, Word, Excel, PowerPoint, and text documents. It also allows users to ask their own questions and provides options to export answers in different formats for easy sharing and documentation.

Suinfy is an AI-powered YouTube video summarizer that helps you save time by extracting the key ideas from long videos. With Suinfy, you can quickly understand the core message of any YouTube video using our cutting-edge summary AI technology. Our YouTube summary tool is designed to enhance your learning experience by extracting the most important points from lengthy videos, saving you time and effort. Suinfy also supports multilingual translations in over 40 languages, eliminating any obstacles to comprehension. Additionally, our detailed timestamp guides allow you to effortlessly move through video content with our detailed, timestamped summary paragraphs. You can easily disseminate video summaries and key takeaways with colleagues, friends, or across your social networks, enhancing the accessibility of video content.

cursor-tools is a CLI tool designed to enhance AI agents with advanced skills, such as web search, repository context, documentation generation, GitHub integration, Xcode tools, and browser automation. It provides features like Perplexity for web search, Gemini 2.0 for codebase context, and Stagehand for browser operations. The tool requires API keys for Perplexity AI and Google Gemini, and supports global installation for system-wide access. It offers various commands for different tasks and integrates with Cursor Composer for AI agent usage.

Note-gen is a simple tool for generating notes automatically based on user input. It uses natural language processing techniques to analyze text and extract key information to create structured notes. The tool is designed to save time and effort for users who need to summarize large amounts of text or generate notes quickly. With note-gen, users can easily create organized and concise notes for study, research, or any other purpose.

Midscene.js is an AI-powered automation SDK that allows users to control web pages, perform assertions, and extract data in JSON format using natural language. It offers features such as natural language interaction, understanding UI and providing responses in JSON, intuitive assertion based on AI understanding, compatibility with public multimodal LLMs like GPT-4o, visualization tool for easy debugging, and a brand new experience in automation development.

FeedCraft is a powerful tool to process your rss feeds as a middleware. Use it to translate your feed, extract fulltext, emulate browser to render js-heavy page, use llm such as google gemini to generate brief for your rss article, use natural language to filter your rss feed, and more! It is an open-source tool that can be self-deployed and used with any RSS reader. It supports AI-powered processing using Open AI compatible LLMs, custom prompt, saving rules to apply to different RSS sources, portable mode for on-the-go usage, and dock mode for advanced customization of RSS sources and processing parameters.

Stagehand is an AI web browsing framework that simplifies and extends web automation using three simple APIs: act, extract, and observe. It aims to provide a lightweight, configurable framework without complex abstractions, allowing users to automate web tasks reliably. The tool generates Playwright code based on atomic instructions provided by the user, enabling natural language-driven web automation. Stagehand is open source, maintained by the Browserbase team, and supports different models and model providers for flexibility in automation tasks.

Lector is a text analysis tool that helps users extract insights from unstructured text data. It provides functionalities such as sentiment analysis, keyword extraction, entity recognition, and text summarization. With Lector, users can easily analyze large volumes of text data to uncover patterns, trends, and valuable information. The tool is designed to be user-friendly and efficient, making it suitable for both beginners and experienced users in the field of natural language processing and text mining.

PromptClip is a tool that allows developers to create video clips using LLM prompts. Users can upload videos from various sources, prompt the video in natural language, use different LLM models, instantly watch the generated clips, finetune the clips, and add music or image overlays. The tool provides a seamless way to extract specific moments from videos based on user queries, making video editing and content creation more efficient and intuitive.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

Kor is a prototype tool designed to help users extract structured data from text using Language Models (LLMs). It generates prompts, sends them to specified LLMs, and parses the output. The tool works with the parsing approach and is integrated with the LangChain framework. Kor is compatible with pydantic v2 and v1, and schema is typed checked using pydantic. It is primarily used for extracting information from text based on provided reference examples and schema documentation. Kor is designed to work with all good-enough LLMs regardless of their support for function/tool calling or JSON modes.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

AskDB is a revolutionary application that simplifies the way users interact with SQL databases. It allows users to query databases in plain English, provides instant answers, and offers AI-assisted query writing and database exploration. AskDB benefits business analysts, data scientists, managers, developers, and database administrators by making querying databases intuitive, effortless, and safe. It offers features like natural language querying, instant insight from data, multi-database connectivity, intelligent query suggestions, data privacy, and easy data export.

`npcsh` is a python-based command-line tool designed to integrate Large Language Models (LLMs) and Agents into one's daily workflow by making them available and easily configurable through the command line shell. It leverages the power of LLMs to understand natural language commands and questions, execute tasks, answer queries, and provide relevant information from local files and the web. Users can also build their own tools and call them like macros from the shell. `npcsh` allows users to take advantage of agents (i.e. NPCs) through a managed system, tailoring NPCs to specific tasks and workflows. The tool is extensible with Python, providing useful functions for interacting with LLMs, including explicit coverage for popular providers like ollama, anthropic, openai, gemini, deepseek, and openai-like providers. Users can set up a flask server to expose their NPC team for use as a backend service, run SQL models defined in their project, execute assembly lines, and verify the integrity of their NPC team's interrelations. Users can execute bash commands directly, use favorite command-line tools like VIM, Emacs, ipython, sqlite3, git, pipe the output of these commands to LLMs, or pass LLM results to bash commands.

The development of Natural Language Interfaces to Databases (NLIDBs) has been greatly advanced by the advent of large language models (LLMs), which provide an intuitive way to translate natural language (NL) questions into Structured Query Language (SQL) queries. DBCopilot is a framework that addresses challenges in real-world scenarios of natural language querying over massive databases by employing a compact and flexible copilot model for routing. It decouples schema-agnostic NL2SQL into schema routing and SQL generation, utilizing a lightweight differentiable search index for semantic mappings and relation-aware joint retrieval. DBCopilot introduces a reverse schema-to-question generation paradigm for automatic learning and adaptation over massive databases, providing a scalable and effective solution for schema-agnostic NL2SQL.

This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

Instructor is a popular Python library for managing structured outputs from large language models (LLMs). It offers a user-friendly API for validation, retries, and streaming responses. With support for various LLM providers and multiple languages, Instructor simplifies working with LLM outputs. The library includes features like response models, retry management, validation, streaming support, and flexible backends. It also provides hooks for logging and monitoring LLM interactions, and supports integration with Anthropic, Cohere, Gemini, Litellm, and Google AI models. Instructor facilitates tasks such as extracting user data from natural language, creating fine-tuned models, managing uploaded files, and monitoring usage of OpenAI models.

This repository contains projects and notes on common practical techniques for fine-tuning Large Language Models (LLMs). It includes fine-tuning LLM notebooks, Colab links, LLM techniques and utils, and other smaller language models. The repository also provides links to YouTube videos explaining the concepts and techniques discussed in the notebooks.

LLMBox is a comprehensive library designed for implementing Large Language Models (LLMs) with a focus on a unified training pipeline and comprehensive model evaluation. It serves as a one-stop solution for training and utilizing LLMs, offering flexibility and efficiency in both training and utilization stages. The library supports diverse training strategies, comprehensive datasets, tokenizer vocabulary merging, data construction strategies, parameter efficient fine-tuning, and efficient training methods. For utilization, LLMBox provides comprehensive evaluation on various datasets, in-context learning strategies, chain-of-thought evaluation, evaluation methods, prefix caching for faster inference, support for specific LLM models like vLLM and Flash Attention, and quantization options. The tool is suitable for researchers and developers working with LLMs for natural language processing tasks.

The LLM-Aided OCR Project is an advanced system that enhances Optical Character Recognition (OCR) output by leveraging natural language processing techniques and large language models. It offers features like PDF to image conversion, OCR using Tesseract, error correction using LLMs, smart text chunking, markdown formatting, duplicate content removal, quality assessment, support for local and cloud-based LLMs, asynchronous processing, detailed logging, and GPU acceleration. The project provides detailed technical overview, text processing pipeline, LLM integration, token management, quality assessment, logging, configuration, and customization. It requires Python 3.12+, Tesseract OCR engine, PDF2Image library, PyTesseract, and optional OpenAI or Anthropic API support for cloud-based LLMs. The installation process involves setting up the project, installing dependencies, and configuring environment variables. Users can place a PDF file in the project directory, update input file path, and run the script to generate post-processed text. The project optimizes processing with concurrent processing, context preservation, and adaptive token management. Configuration settings include choosing between local or API-based LLMs, selecting API provider, specifying models, and setting context size for local LLMs. Output files include raw OCR output and LLM-corrected text. Limitations include performance dependency on LLM quality and time-consuming processing for large documents.

Qwen is a series of large language models developed by Alibaba DAMO Academy. It outperforms the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen models outperform the baseline models of similar model sizes on a series of benchmark datasets, e.g., MMLU, C-Eval, GSM8K, MATH, HumanEval, MBPP, BBH, etc., which evaluate the models’ capabilities on natural language understanding, mathematic problem solving, coding, etc. Qwen-72B achieves better performance than LLaMA2-70B on all tasks and outperforms GPT-3.5 on 7 out of 10 tasks.

Open Domain Relation Extractor

Expert in adapting responses to various keyword intents.

Extract insights seamlessly from diverse documents.

Put your prompt engineering skills to the ultimate test! Embark on a journey to outwit a mythical guardian of ancient secrets. Try to extract the secret passphrase hidden in the system prompt and enter it in chat when you think you have it and claim your glory. Good luck!

Assists with text extraction from PDFs

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A GPT specializing in historical primary source analysis

Expert in data extraction and context-driven analysis. Can read most filetypes including PDFS, XLSX, Word, TXT, CSV, EML, Etc.

Generate and explain regex patterns from your description, it support English and Chinese.

Converts tweet screenshots to text

📝 Multifaceted Document Transformation Expert

Keyword Extraction Tool: Efficiently extracts keywords from various texts, social media, and customer feedback with our user-friendly, scalable tool.

A sentiment analysis tool for evaluating management-related texts.

Expert in concise article summarization and key point extraction.

Expert in website summarization, providing clear and concise info summaries. You can also ask it to find specific info from the site.

I am a dog. Bite me

Analizo contenido web para una comprensión rápida y profunda.

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