Best AI tools for< Retrieve External Text >

Wondershare Help Center provides comprehensive support for Wondershare products, including video editing, video creation, diagramming, PDF solutions, and data management. It offers a wide range of resources such as tutorials, FAQs, troubleshooting guides, and access to customer support.

Extracta.ai is an AI data extraction tool for documents and images that automates data extraction processes with easy integration. It allows users to define custom templates for extracting structured data without the need for training. The platform can extract data from various document types, including invoices, resumes, contracts, receipts, and more, providing accurate and efficient results. Extracta.ai ensures data security, encryption, and GDPR compliance, making it a reliable solution for businesses looking to streamline document processing.

Ubblu is an AI-driven note-taking application that aims to help users search less and create more by providing a seamless experience for capturing, organizing, and retrieving ideas and information. It offers features like note capture, card writing, tag categorization, instant knowledge retrieval, and 'Ask' functionality for quick access to stored information. Ubblu is designed to liberate users' minds from information retention, allowing them to focus on innovation and creativity. The application is desktop-based with a mobile version in development.

ONERECOVERY is a professional data recovery solution for Windows that offers comprehensive and expert solutions to recover lost data from various storage devices. The software is designed to handle over 1,000 data loss scenarios, including accidental deletion, formatting errors, virus attacks, and more. ONERECOVERY provides a user-friendly interface, supports a wide range of file formats, and ensures data security and confidentiality. With a success rate of 95%, fast and easy recovery process, and reliable customer support, ONERECOVERY is a trusted tool for millions of users worldwide.

Pinecone is a vector database designed to build knowledgeable AI applications. It offers a serverless platform with high capacity and low cost, enabling users to perform low-latency vector search for various AI tasks. Pinecone is easy to start and scale, allowing users to create an account, upload vector embeddings, and retrieve relevant data quickly. The platform combines vector search with metadata filters and keyword boosting for better application performance. Pinecone is secure, reliable, and cloud-native, making it suitable for powering mission-critical AI applications.

IntelliumAI is a leading AI application provider specializing in secure AI solutions for data-sensitive industries. Their flagship AI-powered assistant, BoostBot, empowers organizations to unlock their knowledge potential securely. Additionally, AiBoost offers a comprehensive AI platform tailored for advanced engineering professionals, enabling teams to leverage powerful AI capabilities without extensive data science expertise. IntelliumAI is trusted by industry leaders for its transparent and compliance-ready AI solutions.

Pragma is an AI-powered knowledge assistant application designed to help organizations access and manage their knowledge sources efficiently. It offers features such as AI training on user data, instant information retrieval within Slack, multi-platform actions triggering, personalized privacy options, and knowledge repository refinement through user feedback. Pragma empowers sales teams with CRM assistance, competitor website insights, and content generation from organizational wisdom. It also facilitates customer support automation through AI chatbots. The application is praised for its ability to enhance productivity, streamline knowledge sharing, and improve customer interactions.

Ask Command is an AI-powered developer assistant application designed to help users quickly retrieve forgotten commands. The app sends user queries to a server utilizing Open AI's GPT-3 to generate the best command suggestions. Users are advised to verify the suggestions and not run any commands they do not understand. The app is currently available as a Beta version for macOS, with limited free credits. It aims to save users time by providing quick command reminders without the need to search extensively on Google.

Not Diamond is an AI-powered chatbot application designed to provide users with a seamless and efficient conversational experience. It serves as a virtual assistant capable of handling a wide range of tasks and inquiries. With its advanced natural language processing capabilities, Not Diamond aims to revolutionize the way users interact with technology by offering personalized and intelligent responses in real-time. Whether you need assistance with information retrieval, task management, or simply engaging in casual conversation, Not Diamond is the ultimate chatbot companion.

Hints is a sales AI assistant that helps sales reps to get more hours in a day while keeping CRM data accurate automatically. It works with Salesforce, Hubspot, and Pipedrive. With Hints, sales reps can log and retrieve CRM data on any device with chat and voice, get guidance on their next steps, and reminders of what's missing. Hints can also help sales reps to create complex CRM updates in seconds, find duplicates, suggest actions, automatically create associations, and look up sales data through chat and voice commands. Hints can assist sales reps in building the perfect sales process for their team and provides fast onboarding for new sales reps.

Mindset AI is an AI tool that enables users to create AI agents in seconds using simple language. It helps speed up teams' work by allowing the creation of AI agents without the need for coding. Users can write, retrieve information, brainstorm, and more securely using their company's knowledge in a collaborative workspace. Mindset AI offers features such as AI agent builder, integrated knowledge banks, guided conversational search, capabilities for process description, and AI model selector.

Moogle is a semantic search tool that provides users with the ability to find theorems quickly and efficiently. It offers a streamlined search experience over the mathlib4 database, enabling users to access relevant mathematical information with ease. Moogle is designed to enhance research productivity and facilitate the exploration of mathematical concepts in a user-friendly manner.

Phew AI Tab is an AI-powered tab management tool that helps users organize and retrieve tab information efficiently. It utilizes AI-based grouping and spaces in a vertical sidebar to streamline tab management. With features like AI Grouping & Auto Collapse, AI Analyzing, AI Search, and AI-based Space & Cloud Sync, Phew AI Tab aims to enhance productivity and user experience. The tool ensures privacy with military-grade protection and offers seamless synchronization across devices.

Knowledge Drive is the world's only self-organizing, self-maintaining, and fully integrated work knowledge system. It utilizes AI technology to automatically build a knowledge base by extracting useful information from documents. The system ensures knowledge freshness, easy access to information, and seamless integration across various platforms like Microsoft Office 365, Google Workspace, and Slack. Knowledge Drive aims to revolutionize knowledge management and boost productivity in teams by providing a central source of truth and eliminating the need for manual documentation.

xPDF AI by PDFChat is a personal AI assistant designed for PDF files. It offers advanced features to analyze tables, figures, and text from PDF documents, providing users with instant answers and insights. The AI assistant uses a chat interface for effortless interaction and is capable of summarizing PDF files, retrieving relevant figures, processing tables intelligently, and performing accurate calculations. Users can also benefit from voice chat, advanced search tools, performance analytics, report generation, and document assistance. With over 10,000 users trusting the platform, PDFChat aims to revolutionize document analysis and enhance productivity.

AI Placeholder is a free AI-Powered Fake or Dummy Data API for testing and prototyping. It utilizes OpenAI API to generate dummy content. Users can directly use the hosted version or self-host it. The application allows users to generate fake or dummy content using OpenAI's GPT-3.5-Turbo Model API. Users can specify the data they want to mock, retrieve specific data, and generate data with rules specified. The tool is useful for testing, prototyping, and generating various types of data for different purposes.

DataBanc is an AI-powered platform that serves as a data bank, allowing users to retrieve, store, and utilize their personal data for personalized experiences. It empowers individuals to take control of their data, enabling them to access insights and recommendations tailored to their preferences. DataBanc aims to revolutionize the way people interact with their data, offering a secure and user-friendly solution for managing personal information in the digital age.

neurons.bio is an AI application that offers a unique collection of over 100 AI agents designed for drug development, medicine, and life science research. These agents perform specific tasks efficiently, retrieve data from various sources, and provide insights to accelerate research processes. The platform aims to revolutionize drug discovery and development by integrating cutting-edge LLM technology with domain-specific agents, reducing research costs and time to clinic.

Cohere is the leading AI platform for enterprise, offering products optimized for generative AI, search and discovery, and advanced retrieval. Their models are designed to enhance the global workforce, enabling businesses to thrive in the AI era. Cohere provides Command R+, Cohere Command, Cohere Embed, and Cohere Rerank for building efficient AI-powered applications. The platform also offers deployment options for enterprise-grade AI on any cloud or on-premises, along with developer resources like Playground, LLM University, and Developer Docs.

Macro is a cloud AI workspace that combines document editing, file storage, collaboration, and LLMs. It allows users to understand content instantly by clicking or highlighting text to see its meaning. The application is particularly useful for analyzing financial documents, legal contracts, and academic papers. Macro offers different storage and AI compute plans to cater to various user needs.

Language Models is a Python package that provides building blocks to explore large language models with as little as 512MB of RAM. It simplifies the usage of large language models from Python, ensuring all inference is performed locally to keep data private. The package includes features such as text completions, chat capabilities, code completions, external text retrieval, semantic search, and more. It outperforms Hugging Face transformers for CPU inference and offers sensible default models with varying parameters based on memory constraints. The package is suitable for learners and educators exploring the intersection of large language models with modern software development.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

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.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

The serverless-rag-demo repository showcases a solution for building a Retrieval Augmented Generation (RAG) system using Amazon Opensearch Serverless Vector DB, Amazon Bedrock, Llama2 LLM, and Falcon LLM. The solution leverages generative AI powered by large language models to generate domain-specific text outputs by incorporating external data sources. Users can augment prompts with relevant context from documents within a knowledge library, enabling the creation of AI applications without managing vector database infrastructure. The repository provides detailed instructions on deploying the RAG-based solution, including prerequisites, architecture, and step-by-step deployment process using AWS Cloudshell.

The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.

VITA is an open-source interactive omni multimodal Large Language Model (LLM) capable of processing video, image, text, and audio inputs simultaneously. It stands out with features like Omni Multimodal Understanding, Non-awakening Interaction, and Audio Interrupt Interaction. VITA can respond to user queries without a wake-up word, track and filter external queries in real-time, and handle various query inputs effectively. The model utilizes state tokens and a duplex scheme to enhance the multimodal interactive experience.

AIO Launcher Scripts is a collection of Lua scripts that can be used with AIO Launcher to enhance its functionality. These scripts can be used to create widget scripts, search scripts, and side menu scripts. They provide various functions such as displaying text, buttons, progress bars, charts, and interacting with app widgets. The scripts can be used to customize the appearance and behavior of the launcher, add new features, and interact with external services.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

ShellGPT is a command-line productivity tool powered by AI large language models (LLMs). This command-line tool offers streamlined generation of shell commands, code snippets, documentation, eliminating the need for external resources (like Google search). Supports Linux, macOS, Windows and compatible with all major Shells like PowerShell, CMD, Bash, Zsh, etc.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

This starter project is designed to process `.mdx` files in the `pages` directory to use as custom context within OpenAI Text Completion prompts. It involves building a custom ChatGPT style doc search powered by Next.js, OpenAI, and Supabase. The project includes steps for pre-processing knowledge base, storing embeddings in Postgres, performing vector similarity search, and injecting content into OpenAI GPT-3 text completion prompt.

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.

GPTel is a simple Large Language Model chat client for Emacs, with support for multiple models and backends. It's async and fast, streams responses, and interacts with LLMs from anywhere in Emacs. LLM responses are in Markdown or Org markup. Supports conversations and multiple independent sessions. Chats can be saved as regular Markdown/Org/Text files and resumed later. You can go back and edit your previous prompts or LLM responses when continuing a conversation. These will be fed back to the model. Don't like gptel's workflow? Use it to create your own for any supported model/backend with a simple API.

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.

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.

Retrieve data on DeFi protocols and blockchains

This GPT allows to interact with the Unprotect DB to retrieve knowledge about malware evasion techniques

Never lose data again. Store entire conversations for later retrieve or sharing. Do not share sensible information, data is publicly available.

Connect and interact with your Google accounts. Organize, retrieve, and manipulate data with A.I

Unlock the power of your research with the AskYourPDF Research Assistant. Bring information to your fingertips today.

I search Lambeth's planning site to provide links to policies and documents.

Expert in Tiago Forte's Second Brain methodology for digital organization.

Download data from the internet. Fetch the content of sites and make it available to the session, given a URL.

myaidrive.com plugin to search across all your dive documents.

Efficient Assistant for task management, info retrieval, and scheduling. Offers dynamic, personalized support while ensuring user privacy and data security. Ideal for organizing tasks, setting reminders, and providing up-to-date information.

I browse docs to answer Svelte & Supabase queries.

Can't quite remember that thought you had? Use this GPT to help guide you back to your memory.

Finds and provides RSS feed URLs for given website links.

Expert at web navigation and information retrieval.

Write what you'd like researched. Get information in a table format.

Golden Retriever training expert providing advice and tips

Retrieves hunting-related data for each state. Providing insightful data analysis on trends in hunting statistics. (beta)

Comprehensive training and wellness guide for Chesapeake Bay Retrievers.