Best AI tools for< Build Retrieval System >

Shaped is a cloud-based platform that provides APIs and tools for building and deploying ranking systems. It offers a variety of features to help developers quickly and easily create and manage ranking models, including a multi-connector SQL interface, a real-time feature store, and a library of pre-built models. Shaped is designed to be scalable, cost-efficient, and easy to use, making it a great option for businesses of all sizes.

Helix AI is a private GenAI platform that enables users to build AI applications using open source models. The platform offers tools for RAG (Retrieval-Augmented Generation) and fine-tuning, allowing deployment on-premises or in a Virtual Private Cloud (VPC). Users can access curated models, utilize Helix API tools to connect internal and external APIs, embed Helix Assistants into websites/apps for chatbot functionality, write AI application logic in natural language, and benefit from the innovative RAG system for Q&A generation. Additionally, users can fine-tune models for domain-specific needs and deploy securely on Kubernetes or Docker in any cloud environment. Helix Cloud offers free and premium tiers with GPU priority, catering to individuals, students, educators, and companies of varying sizes.

Superlinked is a compute framework for your information retrieval and feature engineering systems, focused on turning complex data into vector embeddings. Vectors power most of what you already do online - hailing a cab, finding a funny video, getting a date, scrolling through a feed or paying with a tap. And yet, building production systems powered by vectors is still too hard! Our goal is to help enterprises put vectors at the center of their data & compute infrastructure, to build smarter and more reliable software.

Exa is a search engine that uses embeddings-based search to retrieve the best content on the web. It is trusted by companies and developers from all over the world. Exa is like Google, but it is better at understanding the meaning of your queries and returning results that are more relevant to your needs. Exa can be used for a variety of tasks, including finding information on the web, conducting research, and building AI applications.

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.

StartKit.AI is a boilerplate code for AI products that helps users build their AI startups 100x faster. It includes pre-built REST API routes for all common AI functionality, a pre-configured Pinecone for text embeddings and Retrieval-Augmented Generation (RAG) for chat endpoints, and five React demo apps to help users get started quickly. StartKit.AI also provides a license key and magic link authentication, user & API limit management, and full documentation for all its code. Additionally, users get access to guides to help them get set up and one year of updates.

GoSearch is an AI-powered Enterprise Search and Resource Discovery platform that enables users to search all internal apps and resources in seconds with the help of AI technology. It offers features like AI workplace assistant, unified knowledge hub, multimodal AI, custom GPTs, and a no-code AI chatbot builder. GoSearch aims to streamline knowledge management and boost productivity by providing instant answers and information discovery through advanced search innovations.

AI Builders Summit is a 4-week virtual training event designed to equip data scientists, ML and AI engineers, and innovators with the latest advancements in large language models (LLMs), AI agents, and Retrieval-Augmented Generation (RAG). The summit emphasizes hands-on learning and real-world applications, with interactive workshops, platform credits, and direct exposure to industry-leading tools. Attendees can learn progressively over four weeks, building practical skills through expert-led sessions, cutting-edge tools, and industry insights.

Motific.ai is a responsible GenAI tool powered by data at scale. It offers a fully managed service with natural language compliance and security guardrails, an intelligence service, and an enterprise data-powered, end-to-end retrieval augmented generation (RAG) service. Users can rapidly deliver trustworthy GenAI assistants and API endpoints, configure assistants with organization's data, optimize performance, and connect with top GenAI model providers. Motific.ai enables users to create custom knowledge bases, connect to various data sources, and ensure responsible AI practices. It supports English language only and offers insights on usage, time savings, and model optimization.

Clarifai is an AI Workflow Orchestration Platform that helps businesses establish an AI Operating Model and transition from prototype to production efficiently. It offers end-to-end solutions for operationalizing AI, including Retrieval Augmented Generation (RAG), Generative AI, Digital Asset Management, Visual Inspection, Automated Data Labeling, and Content Moderation. Clarifai's platform enables users to build and deploy AI faster, reduce development costs, ensure oversight and security, and unlock AI capabilities across the organization. The platform simplifies data labeling, content moderation, intelligence & surveillance, generative AI, content organization & personalization, and visual inspection. Trusted by top enterprises, Clarifai helps companies overcome challenges in hiring AI talent and misuse of data, ultimately leading to AI success at scale.

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.

Gen AI For Enterprise is an AI application that offers a secure, scalable, and customizable platform for enterprises. It provides a private chat feature, enhanced knowledge retrieval, and custom business case development. The application is trusted by various industries and empowers teams to work better by leveraging advanced AI models and APIs. It ensures robust security, compliance with industry standards, and simplified user management. Gen AI For Enterprise aims to transform businesses by providing innovative AI solutions.

Cohere is the leading AI platform for enterprise, offering generative AI, search and discovery, and advanced retrieval solutions. Their models are designed to enhance the global workforce, empowering businesses to thrive in the AI era. With features like Cohere Command, Cohere Embed, and Cohere Rerank, the platform enables the development of scalable and efficient AI-powered applications. Cohere focuses on optimizing enterprise data through language-based models, supporting over 100 languages for enhanced accuracy and efficiency.

SID is a data ingestion, storage, and retrieval pipeline that provides real-time context for AI applications. It connects to various data sources, handles authentication and permission flows, and keeps information up-to-date. SID's API allows developers to retrieve the right piece of data for a given task, enabling them to build AI apps that are fast, accurate, and scalable. With SID, developers can focus on building their products and leave the data management to SID.

RquestR is an AI-powered knowledge management platform designed specifically for procurement professionals. It streamlines projects, enables instant answers retrieval, and facilitates informed decision-making. The platform offers features such as intelligent document querying, automated Q&A generation, and knowledge base building. RquestR helps in reducing response time by up to 40% and enhancing decision-making accuracy by 30%. It provides a centralized knowledge hub for managing RFPs, security questionnaires, and Q&As, all while ensuring enterprise-grade security. The platform revolutionizes the procurement process by leveraging advanced AI for lightning-fast information retrieval, accurate responses, and adaptive learning.

TrainMyAI is a comprehensive solution for creating AI chatbots using retrieval augmented generation (RAG) technology. It allows users to build custom AI chatbots on their servers, enabling interactions over WhatsApp, web, and private APIs. The platform offers deep customization options, fine-grained user management, usage history tracking, content optimization, and linked citations. With TrainMyAI, users can maintain full control over their AI models and data, either on-premise or in the cloud.

Keymate.AI is an AI application that allows users to build GPTs with advanced search, browse, and long-term memory capabilities. It offers a personalized long-term memory on ChatGPT, parallel search functionality, and privacy features using Google API. Keymate.AI aims to elevate research, projects, and daily tasks by providing efficient AI memory management and real-time data retrieval from the web.

GoCharlie is a leading Generative AI company specializing in developing cognitive agents and models optimized for businesses. Its AI technology enables professionals and businesses to amplify their productivity and create high-performing content tailored to their needs. GoCharlie's AI assistant, Charlie, automates repetitive tasks, allowing teams to focus on more strategic and creative work. It offers a suite of proprietary LLM and multimodal models, a Memory Vault to build an AI Brain for businesses, and Agent AI to deliver the full power of AI to operations. GoCharlie can automate mundane tasks, drive complex workflows, and facilitate instant, precise data retrieval.

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.

Cognee is an AI application that helps users build deterministic AI memory by perfecting exceptional AI apps with intelligent data management. It acts as a semantic memory layer, uncovering hidden connections within data and infusing it with company-specific language and principles. Cognee offers data ingestion and enrichment services, resulting in relevant data retrievals and lower infrastructure costs. The application is suitable for various industries, including customer engagement, EduTech, company onboarding, recruitment, marketing, and tourism.

RAG Time is a 5-week AI learning series focusing on Retrieval-Augmented Generation (RAG) concepts. The repository contains code samples, step-by-step guides, and resources to help users master RAG. It aims to teach foundational and advanced RAG concepts, demonstrate real-world applications, and provide hands-on samples for practical implementation.

ZenML is an extensible, open-source MLOps framework for creating portable, production-ready machine learning pipelines. By decoupling infrastructure from code, ZenML enables developers across your organization to collaborate more effectively as they develop to production.

A curated list of Generative AI projects, tools, artworks, and models

Welcome to the envisioning workshop designed to help you build your own custom Copilot using Microsoft's Copilot stack. This workshop aims to rethink user experience, architecture, and app development by leveraging reasoning engines and semantic memory systems. You will utilize Azure AI Foundry, Prompt Flow, AI Search, and Semantic Kernel. Work with Miyagi codebase, explore advanced capabilities like AutoGen and GraphRag. This workshop guides you through the entire lifecycle of app development, including identifying user needs, developing a production-grade app, and deploying on Azure with advanced capabilities. By the end, you will have a deeper understanding of leveraging Microsoft's tools to create intelligent applications.

This open-source course teaches how to build an advanced RAG and LLM system using LLMOps and ML systems best practices. It helps you create an AI assistant that leverages your personal knowledge base to answer questions, summarize documents, and provide insights. The course covers topics such as LLM system architecture, pipeline orchestration, large-scale web crawling, model fine-tuning, and advanced RAG features. It is suitable for ML/AI engineers and data/software engineers & data scientists looking to level up to production AI systems. The course is free, with minimal costs for tools like OpenAI's API and Hugging Face's Dedicated Endpoints. Participants will build two separate Python applications for offline ML pipelines and online inference pipeline.

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.

RAGElo is a streamlined toolkit for evaluating Retrieval Augmented Generation (RAG)-powered Large Language Models (LLMs) question answering agents using the Elo rating system. It simplifies the process of comparing different outputs from multiple prompt and pipeline variations to a 'gold standard' by allowing a powerful LLM to judge between pairs of answers and questions. RAGElo conducts tournament-style Elo ranking of LLM outputs, providing insights into the effectiveness of different settings.

Haystack is an end-to-end LLM framework that allows you to build applications powered by LLMs, Transformer models, vector search and more. Whether you want to perform retrieval-augmented generation (RAG), document search, question answering or answer generation, Haystack can orchestrate state-of-the-art embedding models and LLMs into pipelines to build end-to-end NLP applications and solve your use case.

LLMInterviewQuestions is a repository containing over 100+ interview questions for Large Language Models (LLM) used by top companies like Google, NVIDIA, Meta, Microsoft, and Fortune 500 companies. The questions cover various topics related to LLMs, including prompt engineering, retrieval augmented generation, chunking, embedding models, internal working of vector databases, advanced search algorithms, language models internal working, supervised fine-tuning of LLM, preference alignment, evaluation of LLM system, hallucination control techniques, deployment of LLM, agent-based system, prompt hacking, and miscellaneous topics. The questions are organized into 15 categories to facilitate learning and preparation.

The AI Tutor RAG System repository contains Jupyter notebooks supporting the RAG course, focusing on enhancing AI models with retrieval-based methods. It covers foundational and advanced concepts in retrieval-augmented generation, including data retrieval techniques, model integration with retrieval systems, and practical applications of RAG in real-world scenarios.

Gen-AI-Experiments is a structured collection of Jupyter notebooks and AI experiments designed to guide users through various AI tools, frameworks, and models. It offers valuable resources for both beginners and experienced practitioners, covering topics such as AI agents, model testing, RAG systems, real-world applications, and open-source tools. The repository includes folders with curated libraries, AI agents, experiments, LLM testing, open-source libraries, RAG experiments, and educhain experiments, each focusing on different aspects of AI development and application.

R2R (RAG to Riches) is a fast and efficient framework for serving high-quality Retrieval-Augmented Generation (RAG) to end users. The framework is designed with customizable pipelines and a feature-rich FastAPI implementation, enabling developers to quickly deploy and scale RAG-based applications. R2R was conceived to bridge the gap between local LLM experimentation and scalable production solutions. **R2R is to LangChain/LlamaIndex what NextJS is to React**. A JavaScript client for R2R deployments can be found here. ### Key Features * **🚀 Deploy** : Instantly launch production-ready RAG pipelines with streaming capabilities. * **🧩 Customize** : Tailor your pipeline with intuitive configuration files. * **🔌 Extend** : Enhance your pipeline with custom code integrations. * **⚖️ Autoscale** : Scale your pipeline effortlessly in the cloud using SciPhi. * **🤖 OSS** : Benefit from a framework developed by the open-source community, designed to simplify RAG deployment.

TaskingAI brings Firebase's simplicity to **AI-native app development**. The platform enables the creation of GPTs-like multi-tenant applications using a wide range of LLMs from various providers. It features distinct, modular functions such as Inference, Retrieval, Assistant, and Tool, seamlessly integrated to enhance the development process. TaskingAI’s cohesive design ensures an efficient, intelligent, and user-friendly experience in AI application development.

Buildel is an AI automation platform that empowers users to create versatile workflows without writing code. It supports multiple providers and interfaces, offers pre-built use cases, and allows users to bring their own API keys. Ideal for AI-powered document retrieval, conversational interfaces, and data integration. Users can get started at app.buildel.ai or run Buildel locally with Node.js, Elixir/Erlang, Docker, Git, and JQ installed. Join the community on Discord for support and discussions.

AI Audio Datasets List (AI-ADL) is a comprehensive collection of datasets consisting of speech, music, and sound effects, used for Generative AI, AIGC, AI model training, and audio applications. It includes datasets for speech recognition, speech synthesis, music information retrieval, music generation, audio processing, sound synthesis, and more. The repository provides a curated list of diverse datasets suitable for various AI audio tasks.

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**

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

This repository focuses on Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). It provides code and resources to augment LLMs with real-time data for dynamic, context-aware applications. The content covers topics such as semantic search, fine-tuning embeddings, building RAG chatbots, evaluating LLMs, and using knowledge graphs in RAG. Prerequisites include Python skills, knowledge of machine learning and LLMs, and introductory experience with NLP and AI models.

The Python Redis Vector Library (RedisVL) is a tailor-made client for AI applications leveraging Redis. It enhances applications with Redis' speed, flexibility, and reliability, incorporating capabilities like vector-based semantic search, full-text search, and geo-spatial search. The library bridges the gap between the emerging AI-native developer ecosystem and the capabilities of Redis by providing a lightweight, elegant, and intuitive interface. It abstracts the features of Redis into a grammar that is more aligned to the needs of today's AI/ML Engineers or Data Scientists.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

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