Best AI tools for< Retriever >

RAGnexus is a company that specializes in creating personalized AI assistants using RAG (Retriever-Augmented Generation) technology. Their assistants are designed to provide highly personalized and contextually relevant responses to clients' individual needs. RAGnexus uses private information provided by customers to ensure that responses are accurate and tailored to each specific use case. Retriever-Augmented Generation (RAG) technology uses a two-step approach for generating responses: first, it retrieves relevant information from a database, and then it uses that information to generate accurate and context-specific answers.

FlowHunt is an AI chatbot platform that offers a new no-code visual way to build AI tools and chatbots for websites. It provides a template library with ready-to-use options, from simple AI tools to complex chatbots, and integrates with popular services like Smartsupp, LiveChat, HubSpot, and LiveAgent. The platform also features components like Task Decomposition, Query Expansion, Chat Input, Chat Output, Document Retriever, Document to Text, Generator, and GoogleSearch, enabling users to create customized chatbots for various contexts. FlowHunt aims to simplify the process of building and deploying AI-powered solutions for customer service and content generation.

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.

Exa is a web API designed to provide AI applications with powerful access to the web by organizing and retrieving the best content using embeddings. It offers features like semantic search, similarity search, content scraping, and powerful filters to help developers and companies gather and process data for AI training and analysis. Exa is trusted by thousands of developers and companies for its speed, quality, and ability to provide up-to-date information from various sources on the web.

Sourcely is an AI-powered tool designed to help students and researchers find academic sources quickly and efficiently. It offers features such as summarizing sources, exporting references, advanced filters, and PDF downloads. Sourcely aims to streamline the research process and save users time by providing credible sources for academic papers.

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.

Denser Retriever is an enterprise-grade AI retriever designed to streamline AI integration into applications, combining keyword-based searches, vector databases, and machine learning rerankers using xgboost. It provides state-of-the-art accuracy on MTEB Retrieval benchmarking and supports various heterogeneous retrievers for end-to-end applications like chatbots and semantic search.

The DALM (Domain Adapted Language Modeling) toolkit is designed to unify general LLMs with vector stores to ground AI systems in efficient, factual domains. It provides developers with tools to build on top of Arcee's open source Domain Pretrained LLMs, enabling organizations to deeply tailor AI according to their unique intellectual property and worldview. The toolkit contains code for fine-tuning a fully differential Retrieval Augmented Generation (RAG-end2end) architecture, incorporating in-batch negative concept alongside RAG's marginalization for efficiency. It includes training scripts for both retriever and generator models, evaluation scripts, data processing codes, and synthetic data generation code.

This directory contains samples for a QA chain using an AmazonKendraRetriever class. For more info see the samples README. Note : If you are using an older version of the repo which contains the aws_langchain package, please clone this repo in a new location to avoid any conflicts with the older environment. We are deprecating the aws_langchain package, since the kendra retriever class is available in LangChain starting v0.0.213.

SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.

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.

LightRAG is a PyTorch library designed for building and optimizing Retriever-Agent-Generator (RAG) pipelines. It follows principles of simplicity, quality, and optimization, offering developers maximum customizability with minimal abstraction. The library includes components for model interaction, output parsing, and structured data generation. LightRAG facilitates tasks like providing explanations and examples for concepts through a question-answering pipeline.

NTTU Chatbot is a student support chatbot developed using LLM + Document Retriever (RAG) technology in Vietnamese. It provides assistance to students by answering their queries and retrieving relevant documents. The chatbot aims to enhance the student support system by offering quick and accurate responses to user inquiries. It utilizes advanced language models and document retrieval techniques to deliver efficient and effective support to users.

This repository contains the code for LongRAG, a framework that enhances retrieval-augmented generation with long-context LLMs. LongRAG introduces a 'long retriever' and a 'long reader' to improve performance by using a 4K-token retrieval unit, offering insights into combining RAG with long-context LLMs. The repo provides instructions for installation, quick start, corpus preparation, long retriever, and long reader.

LLM4IR-Survey is a collection of papers related to large language models for information retrieval, organized according to the survey paper 'Large Language Models for Information Retrieval: A Survey'. It covers various aspects such as query rewriting, retrievers, rerankers, readers, search agents, and more, providing insights into the integration of large language models with information retrieval systems.

RAGHack is a hackathon focused on building AI applications using the power of RAG (Retrieval Augmented Generation). RAG combines large language models with search engine knowledge to provide contextually relevant answers. Participants can learn to build RAG apps on Azure AI using various languages and retrievers, explore frameworks like LangChain and Semantic Kernel, and leverage technologies such as agents and vision models. The hackathon features live streams, hack submissions, and prizes for innovative projects.

This repository contains data and code for the experiments in the SummHay paper. It includes publicly released Haystacks in conversational and news domains, along with scripts for running the pipeline, visualizing results, and benchmarking automatic evaluation. The data structure includes topics, subtopics, insights, queries, retrievers, summaries, evaluation summaries, and documents. The pipeline involves scripts for retriever scores, summaries, and evaluation scores using GPT-4o. Visualization scripts are provided for compiling and visualizing results. The repository also includes annotated samples for benchmarking and citation information for the SummHay paper.

RAGLAB is a modular, research-oriented open-source framework for Retrieval-Augmented Generation (RAG) algorithms. It offers reproductions of 6 existing RAG algorithms and a comprehensive evaluation system with 10 benchmark datasets, enabling fair comparisons between RAG algorithms and easy expansion for efficient development of new algorithms, datasets, and evaluation metrics. The framework supports the entire RAG pipeline, provides advanced algorithm implementations, fair comparison platform, efficient retriever client, versatile generator support, and flexible instruction lab. It also includes features like Interact Mode for quick understanding of algorithms and Evaluation Mode for reproducing paper results and scientific research.

LangChain.dart is a Dart port of the popular LangChain Python framework created by Harrison Chase. LangChain provides a set of ready-to-use components for working with language models and a standard interface for chaining them together to formulate more advanced use cases (e.g. chatbots, Q&A with RAG, agents, summarization, extraction, etc.). The components can be grouped into a few core modules: * **Model I/O:** LangChain offers a unified API for interacting with various LLM providers (e.g. OpenAI, Google, Mistral, Ollama, etc.), allowing developers to switch between them with ease. Additionally, it provides tools for managing model inputs (prompt templates and example selectors) and parsing the resulting model outputs (output parsers). * **Retrieval:** assists in loading user data (via document loaders), transforming it (with text splitters), extracting its meaning (using embedding models), storing (in vector stores) and retrieving it (through retrievers) so that it can be used to ground the model's responses (i.e. Retrieval-Augmented Generation or RAG). * **Agents:** "bots" that leverage LLMs to make informed decisions about which available tools (such as web search, calculators, database lookup, etc.) to use to accomplish the designated task. The different components can be composed together using the LangChain Expression Language (LCEL).

Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.

LangChain for Swift. Optimized for iOS, macOS, watchOS (part) and visionOS.(beta) This is a pure client library, no server required

Chat-with-code is a codebase chatbot that enables users to interact with their codebase using the OpenAI Language Model. It provides a user-friendly chat interface where users can ask questions and interact with their code. The tool clones, chunks, and embeds the codebase, allowing for natural language interactions. It is designed to assist users in exploring and understanding their codebase more intuitively.

BaoGPT is an AI project designed to facilitate asking questions about YouTube videos. It features a web UI based on Gradio and Discord integration. The tool utilizes a pipeline that routes input questions to either a greeting-like branch or a query & answer branch. The query analysis is performed by the LLM, which extracts attributes as filters and optimizes and rewrites questions for better vector retrieval in the vector DB. The tool then retrieves top-k candidates for grading and outputs final relative documents after grading. Lastly, the LLM performs summarization based on the reranking output, providing answers and attaching sources to the user.

LMOps is a research initiative focusing on fundamental research and technology for building AI products with foundation models, particularly enabling AI capabilities with Large Language Models (LLMs) and Generative AI models. The project explores various aspects such as prompt optimization, longer context handling, LLM alignment, acceleration of LLMs, LLM customization, and understanding in-context learning. It also includes tools like Promptist for automatic prompt optimization, Structured Prompting for efficient long-sequence prompts consumption, and X-Prompt for extensible prompts beyond natural language. Additionally, LLMA accelerators are developed to speed up LLM inference by referencing and copying text spans from documents. The project aims to advance technologies that facilitate prompting language models and enhance the performance of LLMs in various scenarios.

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.

AdalFlow is a library designed to help developers build and optimize Large Language Model (LLM) task pipelines. It follows a design pattern similar to PyTorch, offering a light, modular, and robust codebase. Named in honor of Ada Lovelace, AdalFlow aims to inspire more women to enter the AI field. The library is tailored for various GenAI applications like chatbots, translation, summarization, code generation, and autonomous agents, as well as classical NLP tasks such as text classification and named entity recognition. AdalFlow emphasizes modularity, robustness, and readability to support users in customizing and iterating code for their specific use cases.

Golden Retriever training expert providing advice and tips

Comprehensive training and wellness guide for Chesapeake Bay Retrievers.

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.

Retrieve data on DeFi protocols and blockchains

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

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

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.

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.

I'm your content retrieval assistant for published articles.

Expert in real-time web content retrieval and analysis