Best AI tools for< Create Rag System >

FutureSmart AI is a platform that provides custom Natural Language Processing (NLP) solutions. The platform focuses on integrating Mem0 with LangChain to enhance AI Assistants with Intelligent Memory. It offers tutorials, guides, and practical tips for building applications with large language models (LLMs) to create sophisticated and interactive systems. FutureSmart AI also features internship journeys and practical guides for mastering RAG with LangChain, catering to developers and enthusiasts in the realm of NLP and AI.

RAG ChatBot is a service that allows users to easily train and share chatbots. It can transform PDFs, URLs, and text into smart chatbots that can be embedded anywhere with an iframe. RAG ChatBot is designed to make knowledge sharing easier and more efficient. It offers a variety of features to help users create and manage their chatbots, including easy knowledge training, continuous improvement, seamless integration with OpenAI Custom GPTs, secure API key integration, continuous optimization, and online privacy control.

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.

LM-Kit.NET is a comprehensive AI toolkit for .NET developers, offering a wide range of features such as AI agent integration, data processing, text analysis, translation, text generation, and model optimization. The toolkit enables developers to create intelligent and adaptable AI applications by providing tools for language models, sentiment analysis, emotion detection, and more. With a focus on performance optimization and security, LM-Kit.NET empowers developers to build cutting-edge AI solutions seamlessly into their C# and VB.NET applications.

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.

Folderr.com is an AI platform that simplifies AI solutions by offering AI assistants, AI automations, and AI chatbots. The platform integrates cutting-edge Language Models (LLMs) and Retrieval-Augmented Generation (RAG) technology to transform business data management and decision-making. Folderr allows users to create AI-powered assistants and chatbots, automate business processes, and enhance productivity. The platform is designed to process various document types, including CSV and XLSX files, to derive critical insights from financial documents. Folderr also provides smart integrations, workflow automations, and secure data sharing options for teams and businesses.

Dify is an open-source platform for building AI applications that combines Backend-as-a-Service and LLMOps to streamline the development of generative AI solutions. It integrates support for mainstream LLMs, an intuitive Prompt orchestration interface, high-quality RAG engines, a flexible AI Agent framework, and easy-to-use interfaces and APIs. Dify allows users to skip complexity and focus on creating innovative AI applications that solve real-world problems. It offers a comprehensive, production-ready solution with a user-friendly interface.

ReadPo is an AI-powered reading and writing assistant designed for knowledge creators to collect, curate, and create content at lightning speed. It offers features such as aggregating multiple content sources, AI-assisted scoring and translation, RAG + Writing technology, beautiful sharing templates, and an Agent Mode. ReadPo is especially suitable for writers, bloggers, and content creators who seek to accelerate their reading and writing processes by leveraging AI technology and topic-based reading methods.

Krux AI is an advanced artificial intelligence tool designed to streamline and optimize various business processes. It leverages cutting-edge machine learning algorithms to provide actionable insights and predictions for data-driven decision-making. With its user-friendly interface and powerful capabilities, Krux AI empowers users to enhance efficiency, productivity, and profitability across different industries.

Create is a free-to-use AI app builder that lets you code using plain text and images. With Create, you can design and build apps like a pro, without having to write a single line of code. Create is perfect for building internal tools, prototypes, and even full-fledged applications.

This website allows users to create AI characters and chat with them. Users can customize their characters' appearance, personality, and interests. They can also choose from a variety of topics to chat about. The website uses artificial intelligence to generate the characters' responses, which are designed to be realistic and engaging.

RE:Create is an AI-powered app that provides endless content ideas and recreates any Instagram/Tiktok video in your style, tone, language, and even your voice! Our application streamlines the content creation process, eliminating the need for extensive planning and strategy. Save time and effort while achieving effective results. No need to hire a separate voiceover artist. Our application offers customizable voice options, ensuring your videos have the perfect audio to complement the visuals. No need to hire a professional scriptwriter. Our platform assists in creating engaging video scripts, guiding you through the process and ensuring your content flows seamlessly.

The website 'Create Next App Chat With the Algorithm' is an AI tool that allows users to generate chat applications using algorithms. It is a work in progress with the latest algorithm code updated on April 14, 2023. Users can leverage this tool to quickly create chat applications with the help of advanced algorithms.

Create A Meme (C.A.M) is an AI-powered platform that allows users to easily create personalized and unique memes. With features like Magic, Custom, Template, and Classic modes, users can unleash their creativity and make viral memes online for free. C.A.M offers basic functionalities for free and a Plus tier for enhanced meme capabilities. The platform supports multiple languages and AI technology ensures that memes are always funny and relevant.

Create AI Voiceovers is an online text-to-speech generator that allows users to convert text into realistic-sounding AI voices. With over 530 AI voices available in 220+ languages and dialects, users can create voiceovers for various purposes, including marketing, eLearning, explainer videos, and animations. The platform offers a range of features, including the ability to adjust voice attributes such as pitch, emphasis, and speed, as well as add background music and sound effects. Create AI Voiceovers also provides a library of pre-recorded sound effects and music that users can incorporate into their voiceovers.

Create a Meme is a website that allows users to create and share memes. It offers a variety of features, including a library of pre-made memes, the ability to upload your own images, and a variety of editing tools. Create a Meme is a popular website with over 100 million users. It is a great way to create and share funny and entertaining memes with your friends and family.

This website provides a tool that allows users to create ebooks in seconds. It is a simple and easy-to-use tool that can be used by anyone, regardless of their technical expertise. The tool provides a variety of templates and features that can be used to create professional-looking ebooks.

Google Workspace is a suite of productivity and collaboration tools designed for individuals, businesses, and enterprises. It includes popular applications like Gmail, Calendar, Drive, Meet, and more. With the addition of Gemini for Workspace, an AI-powered assistant integrated into various tools, users can enhance productivity and collaboration. The platform offers a range of plans tailored to meet diverse business needs, providing features for communication, document management, and team collaboration.

Freepik is a website that provides high-quality stock content for creatives. It offers a wide range of assets, including images, vectors, videos, PSDs, AI images, and icons. Freepik also has a number of tools that can help creatives with their projects, such as an AI image generator, a mockup generator, and a photo editor.

Photoroom is an AI photo editor application that offers a wide range of tools to enhance and edit images. It allows users to remove backgrounds, create product pictures, and generate professional visuals for various purposes. With features like AI Background Remover, AI Retouch, and AI Shadows, Photoroom simplifies the editing process and helps users create stunning images effortlessly. The application caters to individuals, small businesses, and creative teams, offering different subscription plans to suit varying needs. Photoroom is known for its user-friendly interface, affordable pricing, and efficient editing capabilities, making it a popular choice among online sellers, content creators, and small businesses.

RLAMA is a powerful AI-driven question-answering tool that seamlessly integrates with local Ollama models. It enables users to create, manage, and interact with Retrieval-Augmented Generation (RAG) systems tailored to their documentation needs. RLAMA follows a clean architecture pattern with clear separation of concerns, focusing on lightweight and portable RAG capabilities with minimal dependencies. The tool processes documents, generates embeddings, stores RAG systems locally, and provides contextually-informed responses to user queries. Supported document formats include text, code, and various document types, with troubleshooting steps available for common issues like Ollama accessibility, text extraction problems, and relevance of answers.

pgai simplifies the process of building search and Retrieval Augmented Generation (RAG) AI applications with PostgreSQL. It brings embedding and generation AI models closer to the database, allowing users to create embeddings, retrieve LLM chat completions, reason over data for classification, summarization, and data enrichment directly from within PostgreSQL in a SQL query. The tool requires an OpenAI API key and a PostgreSQL client to enable AI functionality in the database. Users can install pgai from source, run it in a pre-built Docker container, or enable it in a Timescale Cloud service. The tool provides functions to handle API keys using psql or Python, and offers various AI functionalities like tokenizing, detokenizing, embedding, chat completion, and content moderation.

LightRAG is a repository hosting the code for LightRAG, a system that supports seamless integration of custom knowledge graphs, Oracle Database 23ai, Neo4J for storage, and multiple file types. It includes features like entity deletion, batch insert, incremental insert, and graph visualization. LightRAG provides an API server implementation for RESTful API access to RAG operations, allowing users to interact with it through HTTP requests. The repository also includes evaluation scripts, code for reproducing results, and a comprehensive code structure.

LLM for Unity enables seamless integration of Large Language Models (LLMs) within the Unity engine, allowing users to create intelligent characters for immersive player interactions. The tool supports major LLM models, runs locally without internet access, offers fast inference on CPU and GPU, and is easy to set up with a single line of code. It is free for both personal and commercial use, tested on Unity 2021 LTS, 2022 LTS, and 2023. Users can build multiple AI characters efficiently, use remote servers for processing, and customize model settings for text generation.

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.

LLM-Powered-RAG-System is a comprehensive repository containing frameworks, projects, components, evaluation tools, papers, blogs, and other resources related to Retrieval-Augmented Generation (RAG) systems powered by Large Language Models (LLMs). The repository includes various frameworks for building applications with LLMs, data frameworks, modular graph-based RAG systems, dense retrieval models, and efficient retrieval augmentation and generation frameworks. It also features projects such as personal productivity assistants, knowledge-based platforms, chatbots, question and answer systems, and code assistants. Additionally, the repository provides components for interacting with documents, databases, and optimization methods using ML and LLM technologies. Evaluation frameworks, papers, blogs, and other resources related to RAG systems are also included.

Gurubase is an open-source RAG system that enables users to create AI-powered Q&A assistants ('Gurus') for various topics by integrating web pages, PDFs, YouTube videos, and GitHub repositories. It offers advanced LLM-based question answering, accurate context-aware responses through the RAG system, multiple data sources integration, easy website embedding, creation of custom AI assistants, real-time updates, personalized learning paths, and self-hosting options. Users can request Guru creation, manage existing Gurus, update datasources, and benefit from the system's features for enhancing user engagement and knowledge sharing.

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 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.

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

AutoArena is a tool designed to create leaderboards ranking Language Model outputs against one another using automated judge evaluation. It allows users to rank outputs from different LLMs, RAG setups, and prompts to find the best configuration of their system. Users can perform automated head-to-head evaluation using judges from various platforms like OpenAI, Anthropic, and Cohere. Additionally, users can define and run custom judges, connect to internal services, or implement bespoke logic. AutoArena enables users to run the application locally, providing full control over their environment and data.

Beyond LLM offers an all-in-one toolkit for experimentation, evaluation, and deployment of Retrieval-Augmented Generation (RAG) systems. It simplifies the process with automated integration, customizable evaluation metrics, and support for various Large Language Models (LLMs) tailored to specific needs. The aim is to reduce LLM hallucination risks and enhance reliability.

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

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

The UltraRAG framework is a researcher and developer-friendly RAG system solution that simplifies the process from data construction to model fine-tuning in domain adaptation. It introduces an automated knowledge adaptation technology system, supporting no-code programming, one-click synthesis and fine-tuning, multidimensional evaluation, and research-friendly exploration work integration. The architecture consists of Frontend, Service, and Backend components, offering flexibility in customization and optimization. Performance evaluation in the legal field shows improved results compared to VanillaRAG, with specific metrics provided. The repository is licensed under Apache-2.0 and encourages citation for support.

Simba is an open source, portable Knowledge Management System (KMS) designed to seamlessly integrate with any Retrieval-Augmented Generation (RAG) system. It features a modern UI and modular architecture, allowing developers to focus on building advanced AI solutions without the complexities of knowledge management. Simba offers a user-friendly interface to visualize and modify document chunks, supports various vector stores and embedding models, and simplifies knowledge management for developers. It is community-driven, extensible, and aims to enhance AI functionality by providing a seamless integration with RAG-based systems.

Kollektiv is a Retrieval-Augmented Generation (RAG) system designed to enable users to chat with their favorite documentation easily. It aims to provide LLMs with access to the most up-to-date knowledge, reducing inaccuracies and improving productivity. The system utilizes intelligent web crawling, advanced document processing, vector search, multi-query expansion, smart re-ranking, AI-powered responses, and dynamic system prompts. The technical stack includes Python/FastAPI for backend, Supabase, ChromaDB, and Redis for storage, OpenAI and Anthropic Claude 3.5 Sonnet for AI/ML, and Chainlit for UI. Kollektiv is licensed under a modified version of the Apache License 2.0, allowing free use for non-commercial purposes.

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.

Renumics RAG is a retrieval-augmented generation assistant demo that utilizes LangChain and Streamlit. It provides a tool for indexing documents and answering questions based on the indexed data. Users can explore and visualize RAG data, configure OpenAI and Hugging Face models, and interactively explore questions and document snippets. The tool supports GPU and CPU setups, offers a command-line interface for retrieving and answering questions, and includes a web application for easy access. It also allows users to customize retrieval settings, embeddings models, and database creation. Renumics RAG is designed to enhance the question-answering process by leveraging indexed documents and providing detailed answers with sources.

RAG with txtai is a Retrieval Augmented Generation (RAG) Streamlit application that helps generate factually correct content by limiting the context in which a Large Language Model (LLM) can generate answers. It supports two categories of RAG: Vector RAG, where context is supplied via a vector search query, and Graph RAG, where context is supplied via a graph path traversal query. The application allows users to run queries, add data to the index, and configure various parameters to control its behavior.

First, please say "Create an agent team to do 〇〇." / 最初に「〇〇をするためのエージェントチームを作成してください」とお伝え下さい

Let's get started by telling me about your business: What do you offer? Who do you serve? ------------------------------------------------------- Need help Prompt Engineering? Reach out on LinkedIn: StephenHnilica

AI tool for designing engaging, trendy Pinterest pins.

Generates 3D stereogram pairs for parallel viewing.

2500+ word stories in target language with images, for language learning.

Level up Now. Upload a selfie for some superhero flair. Create a backstory. Select a superpower, arch-villain, and crew. Answer trivia. Pow!

Tell me about your situation and the type of prayer you would like

利用专业的周易知识和命理知识进行头像设计 Generates and explains lucky profile pictures based on I Ching, zodiac.

创建你自己的数字人形象，Sponsor：小红书“ItsJoe就出行”

I'll recreate a competitor website for your business

Create a very detailed prompt from the image. 画像からめっちゃ詳細なプロンプトを作成します。まずは解析して欲しい画像を送ってみてください。

1) Input a URL, attachment, or copy/paste a bunch of info about your biz. 2) I will return a summary of what's important. 3) Use what I give you for other prompts, e.g.: marketing strategy, content ideas, competitive analysis, etc

Create a Mythological Creature for playing with imagination and possibilities

Autonomously creates complete TikTok scenarios with images.

Simulates advisory board meetings with investors. Get generated advice for your startup from a GPT educated by domain experts.

Advisor for hairstyles, top products, and salon recommendations matched with your hair type and location.

Replicate Image, Images Mergeve, Imaginative Edit, Style Transfer. Use "Help" for more info. 20+ features of the source image will be transferred. You also can call this GPT via @ in any chat (desktop only).

I create soothing cat images.

Create business processes using Flowscript markup

I create nursing care plans based on triage info.