Best AI tools for< Launch Retrieval Server >

Launch Consulting Group is an AI and digital transformation consulting firm that empowers organizations to embrace AI transformation. They offer services such as AI guidance, predictive analytics, data architecture, and data governance to help businesses make smarter decisions, streamline workflows, and optimize performance. With a team of over 1200 Navigators worldwide, Launch Consulting Group is dedicated to helping businesses across various sectors leverage the power of artificial intelligence for success.

AI VisionBoard Launch App is an AI-powered application that allows users to create personalized vision boards to visualize their dreams and aspirations. Users can quickly visualize their dreams in seconds by typing them out or using random prompt ideas. The app also enables users to add their photos and see themselves in their dreams. Additionally, users can explore a community of shared dreams, share their vision board creations, and connect with like-minded individuals. The app also features an AI Life Coach chat function for personal growth and well-being support, providing users with a 24/7 companion. AI VisionBoard aims to help users turn their aspirations into reality through visualization and community support.

Zarla AI Website Builder is an AI-powered tool that allows users to create professional websites quickly and easily. The tool utilizes artificial intelligence to write, design, and build fully finished websites in a matter of minutes. With features like expert writing, free custom domain registration, mobile-first design, SSL security, and world-class support, Zarla offers a comprehensive solution for individuals and businesses looking to establish an online presence. The tool is designed to be user-friendly, efficient, and cost-effective, making website creation accessible to everyone, regardless of technical expertise.

Mixo is an AI website builder that allows users to launch professional websites in seconds with AI technology. It offers features such as custom styles, form builder, custom domains, SEO-ready content, third-party integrations, and GDPR and privacy controls. Mixo helps users bring their startup ideas to life effortlessly, connect with customers, and grow their audience. With over 2.7 million sites created, Mixo is trusted by over 650,000 creators worldwide for its reliability, quality, and cutting-edge features.

Satellitor is an AI-powered SEO tool that helps businesses create and manage SEO-optimized blogs. It automates the entire process of content creation, publishing, and ranking, freeing up business owners to focus on other aspects of their business. Satellitor's AI-generated content is of high quality and adheres to Google's best practices, ensuring that your blog ranks well in search results and attracts organic traffic to your website.

CryptoDo is a multichain, no-code web3 solution builder for businesses. It allows users to create smart contracts and web3 applications without any programming skills. CryptoDo uses an AI module to customize smart contracts, making blockchain technology more accessible and adaptable.

React Native Starter AI is an all-in-one development kit designed to help users quickly launch their mobile apps with AI functionality. The boilerplate template includes integrations such as AI tools, Firebase functions, analytics, authentication, in-app purchases, and more. It aims to save developers time by providing pre-built components and screens for building AI mobile applications. With React Native Starter AI, users can easily customize and publish their apps on mobile app stores, catering to both beginner and experienced developers.

AdCopy is an AI-powered advertising platform that helps businesses create high-quality ads and optimize their ad campaigns. The platform uses AI to generate ad copy, create ad creatives, and provide insights into ad performance. AdCopy is designed to help businesses save time and money on their advertising campaigns, while also improving their results.

NocodeBooth provides a template for launching an AI image generation application without coding. It includes features such as user registration, payments, automated image generation, an admin dashboard, and a referral program. The template is fully customizable and includes a landing page, user dashboard, and admin dashboard. It also provides a playground feature for testing prompts and styles. The template costs $149 for a one-time payment.

SvelteLaunch is a SaaS/AI boilerplate and development as a service agency that helps users launch their next SaaS, AI, or business app fast. It offers a comprehensive Svelte 5 boilerplate and full-service development agency to build cutting-edge digital experiences. The platform provides a technology stack with features like SvelteLaunch CLI for web app architecture, AI capabilities for emails, payments, authentication, databases, styles, and SEO optimization. Users can save time with various tools like TailwindCSS, OpenAI, and more. SvelteLaunch aims to save months of development time and enable users to ship high-quality SaaS apps efficiently.

Insyte is an AI-powered website builder that allows users to create landing pages in seconds. It is designed to be easy to use and intuitive, so you can focus on what matters most: your business. With Insyte, you can create a website for any purpose, from a simple landing page to a full-fledged online store. Insyte offers a variety of features to help you create a website that is both visually appealing and engaging. You can choose from a variety of templates, add your own content, and customize the look and feel of your site. Insyte also offers a number of advanced features, such as the ability to download the source code of your website and add custom domains. Insyte is a powerful tool that can help you create a website that will help you grow your business.

The Landing AI Landing Page Generator is a powerful tool that allows users to create beautiful, branded, and conversion-optimized landing pages in minutes with the help of artificial intelligence. It eliminates the need for design, development, and copywriting skills, enabling users to launch professional landing pages quickly and effortlessly. The tool offers features such as AI Copywriter for generating persuasive copy, AI Image Generator for creating stunning visuals, email forms for lead capture, AI Designer for on-brand landing pages, instant publishing with hosting and SSL, and the ability to add custom code for extended functionality. With Landing, users can scale their marketing efforts, drive growth, and supercharge their paid campaigns with perfectly-aligned pages for every ad group.

Lootgod is an AI-powered e-commerce platform that enables users to design merchandise, automate fulfillment, and support local small businesses. The platform allows users to create real products for sale in minutes using AI automation, merchandise their dreams quickly, and own their art forever. Lootgod collaborates with artists to define their intellectual property standards on the blockchain and builds a backbone for crypto based on utilities like energy, land, water, and food. The platform aims to make e-commerce setup easier than ever, offering features like print-on-demand fulfillment, locally sourced manufacturing, and high-quality products with zero inventory risk.

DeploySaaS is an AI tool designed to assist users in launching their SaaS products more effectively and efficiently. It provides guidance and support throughout the entire process, from idea validation to product launch. By leveraging AI technology, DeploySaaS aims to help users avoid common pitfalls in SaaS development and make data-driven decisions to achieve product-market fit.

Zeedle AI is an AI tool designed to help users launch their business with the power of artificial intelligence and ads. It offers a platform where users can explore business ideas, create top ads creatives, websites, and utilize AI technology to kickstart their ventures. With a user-friendly interface, Zeedle AI aims to streamline the process of starting a business by providing tools and resources to turn ideas into reality.

Alitu Showplanner is an AI-powered tool designed to help users launch their podcasts quickly and efficiently. By answering a few questions about their podcast idea, users can generate a personalized launch kit including a catchy name, trailer script, episode ideas, and more. The tool simplifies the podcast creation process by providing step-by-step guidance from planning to recording and publishing. Created by The Podcast Host & Alitu team, Alitu Showplanner aims to streamline the podcasting experience for beginners and experienced creators alike.

Launchpad Stack is an AI-powered platform that allows users to quickly launch new Rails services with AWS. It generates full-stack source code in minutes, covering infrastructure, application, CI/CD pipeline, monitoring, security, and more. The platform offers a suite of inter-operable code packages tailored to the user's project requirements, with no restrictive licenses. Users can launch enterprise-grade stacks in minutes, pay once for the components they need, and enjoy ongoing support for their projects.

Pietra is a one-stop platform that provides tools and resources to help e-commerce brands save time and money. It offers a range of services, including AI-powered creative tools for product design, a marketplace of vetted factories for sourcing and manufacturing, order fulfillment infrastructure, e-commerce storefront creation, email capture, SMS marketing, affiliate marketing, data and dashboards, print on demand, business planning tools, and weekly workshops.

Pietra is a one-stop platform that provides tools and resources to help e-commerce brands save time and money. It offers a range of services, including AI-powered creative tools for product design, a marketplace of vetted factories for sourcing and manufacturing, order fulfillment infrastructure, e-commerce storefront creation, email capture, SMS marketing, affiliate marketing, data and dashboards, print on demand, and business planning tools. Pietra also offers weekly workshops with professionals to help users maximize their use of the platform.

Meya is a chatbot platform that allows users to build and launch custom chatbots. It provides a variety of features, including a visual flow editor, a code editor, and a variety of integrations. Meya is designed to be easy to use, even for non-technical users. It is also highly extensible, allowing users to add their own custom code and integrations.

Search-R1 is a tool that trains large language models (LLMs) to reason and call a search engine using reinforcement learning. It is a reproduction of DeepSeek-R1 methods for training reasoning and searching interleaved LLMs, built upon veRL. Through rule-based outcome reward, the base LLM develops reasoning and search engine calling abilities independently. Users can train LLMs on their own datasets and search engines, with preliminary results showing improved performance in search engine calling and reasoning tasks.

Chat Your Doc is an experimental project exploring various applications based on LLM technology. It goes beyond being just a chatbot project, focusing on researching LLM applications using tools like LangChain and LlamaIndex. The project delves into UX, computer vision, and offers a range of examples in the 'Lab Apps' section. It includes links to different apps, descriptions, launch commands, and demos, aiming to showcase the versatility and potential of LLM applications.

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MiniPerplx is a minimalistic AI-powered search engine designed to help users find information on the internet. It utilizes AI technologies from providers like OpenAI, Anthropic, and Tavily to deliver accurate and relevant search results. Users can deploy their own instance of MiniPerplx by obtaining API keys, setting up environment variables, and running the development server. The tool aims to streamline the process of information retrieval by leveraging advanced AI capabilities in a user-friendly interface.

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.

RAGFlow is an open-source Retrieval-Augmented Generation (RAG) engine that combines deep document understanding with Large Language Models (LLMs) to provide accurate question-answering capabilities. It offers a streamlined RAG workflow for businesses of all sizes, enabling them to extract knowledge from unstructured data in various formats, including Word documents, slides, Excel files, images, and more. RAGFlow's key features include deep document understanding, template-based chunking, grounded citations with reduced hallucinations, compatibility with heterogeneous data sources, and an automated and effortless RAG workflow. It supports multiple recall paired with fused re-ranking, configurable LLMs and embedding models, and intuitive APIs for seamless integration with business applications.

RAGHub is a community-driven project focused on cataloging new and emerging frameworks, projects, and resources in the Retrieval-Augmented Generation (RAG) ecosystem. It aims to help users stay ahead of changes in the field by providing a platform for the latest innovations in RAG. The repository includes information on RAG frameworks, evaluation frameworks, optimization frameworks, citation frameworks, engines, search reranker frameworks, projects, resources, and real-world use cases across industries and professions.

Modus is an open-source, serverless framework for building APIs powered by WebAssembly. It simplifies integrating AI models, data, and business logic with sandboxed execution. Modus extracts metadata, compiles code with optimizations, caches compiled modules, prepares invocation plans, generates API schema, and activates endpoints. Users query the endpoint, and Modus loads compiled code into a sandboxed environment, runs code securely, queries data and AI models, and responds via API. It provides a production-ready scalable endpoint for AI-enabled apps, optimized for sub-second response times. Modus supports programming languages like AssemblyScript and Go, and can be hosted on Hypermode or any platform. Developed by Hypermode as an open-source project, Modus welcomes external contributions.

RAG-GPT is a tool that allows users to quickly launch an intelligent customer service system with Flask, LLM, and RAG. It includes frontend, backend, and admin console components. The tool supports cloud-based and local LLMs, enables deployment of conversational service robots in minutes, integrates diverse knowledge bases, offers flexible configuration options, and features an attractive user interface.

RAG-GPT is a tool that allows users to quickly launch an intelligent customer service system with Flask, LLM, and RAG. It includes frontend, backend, and admin console components. The tool supports cloud-based and local LLMs, offers quick setup for conversational service robots, integrates diverse knowledge bases, provides flexible configuration options, and features an attractive user interface.

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.

LLMWare is a framework for quickly developing LLM-based applications including Retrieval Augmented Generation (RAG) and Multi-Step Orchestration of Agent Workflows. This project provides a comprehensive set of tools that anyone can use - from a beginner to the most sophisticated AI developer - to rapidly build industrial-grade, knowledge-based enterprise LLM applications. Our specific focus is on making it easy to integrate open source small specialized models and connecting enterprise knowledge safely and securely.

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.

Mem0 is a tool that provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications. It offers persistent memory for users, sessions, and agents, self-improving personalization, a simple API for easy integration, and cross-platform consistency. Users can store memories, retrieve memories, search for related memories, update memories, get the history of a memory, and delete memories using Mem0. It is designed to enhance AI experiences by enabling long-term memory storage and retrieval.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output (objects). It provides a simple yet robust interface and supports llama-cpp-python and OpenAI endpoints with GBNF grammar support (like the llama-cpp-python server) and the llama.cpp backend server. It works by generating a formal GGML-BNF grammar of the user defined structures and functions, which is then used by llama.cpp to generate text valid to that grammar. In contrast to most GBNF grammar generators it also supports nested objects, dictionaries, enums and lists of them.

Intel® Extension for Transformers is an innovative toolkit designed to accelerate GenAI/LLM everywhere with the optimal performance of Transformer-based models on various Intel platforms, including Intel Gaudi2, Intel CPU, and Intel GPU. The toolkit provides the below key features and examples: * Seamless user experience of model compressions on Transformer-based models by extending [Hugging Face transformers](https://github.com/huggingface/transformers) APIs and leveraging [Intel® Neural Compressor](https://github.com/intel/neural-compressor) * Advanced software optimizations and unique compression-aware runtime (released with NeurIPS 2022's paper [Fast Distilbert on CPUs](https://arxiv.org/abs/2211.07715) and [QuaLA-MiniLM: a Quantized Length Adaptive MiniLM](https://arxiv.org/abs/2210.17114), and NeurIPS 2021's paper [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754)) * Optimized Transformer-based model packages such as [Stable Diffusion](examples/huggingface/pytorch/text-to-image/deployment/stable_diffusion), [GPT-J-6B](examples/huggingface/pytorch/text-generation/deployment), [GPT-NEOX](examples/huggingface/pytorch/language-modeling/quantization#2-validated-model-list), [BLOOM-176B](examples/huggingface/pytorch/language-modeling/inference#BLOOM-176B), [T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), [Flan-T5](examples/huggingface/pytorch/summarization/quantization#2-validated-model-list), and end-to-end workflows such as [SetFit-based text classification](docs/tutorials/pytorch/text-classification/SetFit_model_compression_AGNews.ipynb) and [document level sentiment analysis (DLSA)](workflows/dlsa) * [NeuralChat](intel_extension_for_transformers/neural_chat), a customizable chatbot framework to create your own chatbot within minutes by leveraging a rich set of [plugins](https://github.com/intel/intel-extension-for-transformers/blob/main/intel_extension_for_transformers/neural_chat/docs/advanced_features.md) such as [Knowledge Retrieval](./intel_extension_for_transformers/neural_chat/pipeline/plugins/retrieval/README.md), [Speech Interaction](./intel_extension_for_transformers/neural_chat/pipeline/plugins/audio/README.md), [Query Caching](./intel_extension_for_transformers/neural_chat/pipeline/plugins/caching/README.md), and [Security Guardrail](./intel_extension_for_transformers/neural_chat/pipeline/plugins/security/README.md). This framework supports Intel Gaudi2/CPU/GPU. * [Inference](https://github.com/intel/neural-speed/tree/main) of Large Language Model (LLM) in pure C/C++ with weight-only quantization kernels for Intel CPU and Intel GPU (TBD), supporting [GPT-NEOX](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox), [LLAMA](https://github.com/intel/neural-speed/tree/main/neural_speed/models/llama), [MPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/mpt), [FALCON](https://github.com/intel/neural-speed/tree/main/neural_speed/models/falcon), [BLOOM-7B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/bloom), [OPT](https://github.com/intel/neural-speed/tree/main/neural_speed/models/opt), [ChatGLM2-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/chatglm), [GPT-J-6B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptj), and [Dolly-v2-3B](https://github.com/intel/neural-speed/tree/main/neural_speed/models/gptneox). Support AMX, VNNI, AVX512F and AVX2 instruction set. We've boosted the performance of Intel CPUs, with a particular focus on the 4th generation Intel Xeon Scalable processor, codenamed [Sapphire Rapids](https://www.intel.com/content/www/us/en/products/docs/processors/xeon-accelerated/4th-gen-xeon-scalable-processors.html).

This repository provides sample applications and tutorials to showcase the power of Amazon Bedrock with Python. It helps Python developers understand how to harness Amazon Bedrock in building generative AI-enabled applications. The resources also demonstrate integration with vector databases using RAG (Retrieval-augmented generation) and services like Amazon Aurora, RDS, and OpenSearch. Additionally, it explores using langchain and streamlit to create effective experimental applications.

OmniSteward is an AI-powered steward system based on large language models that can interact with users through voice or text to help control smart home devices and computer programs. It supports multi-turn dialogue, tool calling for complex tasks, multiple LLM models, voice recognition, smart home control, computer program management, online information retrieval, command line operations, and file management. The system is highly extensible, allowing users to customize and share their own tools.

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