Best AI tools for< Develop Ai Applications >

Dify.AI is a generative AI application development platform that allows users to create AI agents, chatbots, and other AI-powered applications. It provides a variety of tools and services to help developers build, deploy, and manage their AI applications. Dify.AI is designed to be easy to use, even for those with no prior experience in AI development.

Salieri is a multi-agent LLM home multiverse platform that offers an efficient, trustworthy, and automated AI workflow. The innovative Multiverse Factory allows developers to elevate their projects by generating personalized AI applications through an intuitive interface. The platform aims to optimize user queries via LLM API calls, reduce expenses, and enhance the cognitive functions of AI agents. Salieri's team comprises experts from top AI institutes like MIT and Google, focusing on generative AI, neural knowledge graph, and composite AI models.

MeetFebin is an AI tool developed by Febin, an individual with a passion for exploring emerging technology and creating user-friendly products. Through MeetFebin, Febin shares his insights and experiments on the future of AI applications. The tool focuses on modernizing customer support for businesses using chatbots, leveraging Febin's expertise in engineering, design, and writing.

ThirdEye Data is a data and AI services & solutions provider that enables enterprises to improve operational efficiencies, increase production accuracies, and make informed business decisions by leveraging the latest Data & AI technologies. They offer services in data engineering, data science, generative AI, computer vision, NLP, and more. ThirdEye Data develops bespoke AI applications using the latest data science technologies to address real-world industry challenges and assists enterprises in leveraging generative AI models to develop custom applications. They also provide AI consulting services to explore potential opportunities for AI implementation. The company has a strong focus on customer success and has received positive reviews and awards for their expertise in AI, ML, and big data solutions.

Snorkel AI is a data-centric AI application designed for enterprise use. It offers tools and platforms to programmatically label and curate data, accelerate AI development, and build high-quality generative AI applications. The application aims to help users develop AI models 100x faster by leveraging programmatic data operations and domain knowledge. Snorkel AI is known for its expertise in computer vision, data labeling, generative AI, and enterprise AI solutions. It provides resources, case studies, and research papers to support users in their AI development journey.

fast.ai is an AI tool that offers courses and resources on deep learning and practical applications of artificial intelligence. The platform provides high-level components for practitioners to achieve state-of-the-art results in standard deep learning tasks. It aims to increase diversity in the field of deep learning and lower barriers to entry for everyone.

Defined.ai is a leading provider of high-quality and ethical data for AI applications. Founded in 2015, Defined.ai has a global presence with offices in the US, Europe, and Asia. The company's mission is to make AI more accessible and ethical by providing a marketplace for buying and selling AI data, tools, and models. Defined.ai also offers professional services to help deliver success in complex machine learning projects.

LabLab.ai is an online community and platform for artificial intelligence (AI) enthusiasts, developers, and innovators. The platform hosts AI hackathons, provides access to state-of-the-art AI technologies, and offers educational resources on AI. LabLab.ai aims to foster collaboration and innovation in the AI field and to make AI accessible to everyone.

Synthesis AI is a synthetic data platform that enables more capable and ethical computer vision AI. It provides on-demand labeled images and videos, photorealistic images, and 3D generative AI to help developers build better models faster. Synthesis AI's products include Synthesis Humans, which allows users to create detailed images and videos of digital humans with rich annotations; Synthesis Scenarios, which enables users to craft complex multi-human simulations across a variety of environments; and a range of applications for industries such as ID verification, automotive, avatar creation, virtual fashion, AI fitness, teleconferencing, visual effects, and security.

The NVIDIA Toronto AI Lab is a research laboratory focused on advancing the state-of-the-art in artificial intelligence. The lab's researchers are working on a wide range of AI topics, including deep learning, machine learning, computer vision, natural language processing, and robotics.

Dan Rose AI is a platform focused on applied artificial intelligence, providing insights and strategies on how AI can be utilized in the present time for real value. The website features blog posts, speaking engagements, and consulting services related to AI applications and strategies. Dan Rose Johansen, the founder, emphasizes practical approaches to AI implementation and its strategic use.

Mo Ai Jobs is a job board for artificial intelligence (AI) professionals. It lists jobs in machine learning, engineering, research, data science, and other AI-related fields. The site is designed to help AI professionals find jobs at next-generation AI companies. Mo Ai Jobs is a valuable resource for anyone looking for a job in the AI industry.

Denvr DataWorks AI Cloud is a cloud-based AI platform that provides end-to-end AI solutions for businesses. It offers a range of features including high-performance GPUs, scalable infrastructure, ultra-efficient workflows, and cost efficiency. Denvr DataWorks is an NVIDIA Elite Partner for Compute, and its platform is used by leading AI companies to develop and deploy innovative AI solutions.

BRIA.ai is a visual generative AI platform that provides developers and businesses with the tools they need to build and deploy AI-powered applications. The platform includes a suite of pre-trained foundation models, APIs, and tools that can be used to generate and modify images, videos, and other visual content. BRIA.ai is committed to responsible AI practices and ensures that all of its models are trained on licensed and safe-to-use data.

Infrabase.ai is a directory of AI infrastructure products that helps users discover and explore a wide range of tools for building world-class AI products. The platform offers a comprehensive directory of products in categories such as Vector databases, Prompt engineering, Observability & Analytics, Inference APIs, Frameworks & Stacks, Fine-tuning, Audio, and Agents. Users can find tools for tasks like data storage, model development, performance monitoring, and more, making it a valuable resource for AI projects.

YourGPT is a suite of next-generation AI products designed to empower businesses with the potential of Large Language Models (LLMs). Its products include a no-code AI Chatbot solution for customer support and LLM Spark, a developer platform for building and deploying production-ready LLM applications. YourGPT prioritizes data security and is GDPR compliant, ensuring the privacy and protection of customer data. With over 2,000 satisfied customers, YourGPT has earned trust through its commitment to quality and customer satisfaction.

MTS AI is a platform offering AI-based products and solutions, leveraging artificial intelligence technologies to create voice assistants, chatbots, video analysis solutions, and more. They develop AI solutions using natural language processing, computer vision, and edge computing technologies, collaborating with leading tech companies and global experts. MTS AI aims to find the most viable AI applications for the benefit of society, providing automation for customer service systems, security control, and voice and video data analysis.

ConvoStack is a free and open-source full-stack framework that makes it easy for developers to embed a customizable AI chatbot widget into a website with just a few lines of code. It supports popular frameworks such as Pinecone DB, Express, and React, and allows developers to integrate their own AI models using LangChain. ConvoStack is built on a tech stack that is used and loved by developers, and it is designed to be customizable for any use case.

Neoform AI is an innovative AI tool that focuses on developing AI models specifically for African dialects. The platform aims to bridge the gap in AI technology by providing solutions tailored to the linguistic diversity of Africa. With a commitment to inclusivity and cultural representation, Neoform AI is revolutionizing the field of artificial intelligence by addressing the unique challenges faced by African languages. Through cutting-edge research and development, Neoform AI is paving the way for greater accessibility and accuracy in AI applications across the continent.

般若AI is an AI-powered platform that provides a variety of AI tools and services to help businesses and individuals with their AI needs. The platform offers a range of features, including AI training, AI consulting, and AI development. 般若AI also has a large community of AI experts who can provide support and guidance to users.

This repository is for the book 'Building AI Applications with ChatGPT APIs' published by Packt. It provides code examples and instructions for mastering ChatGPT, Whisper, and DALL-E APIs through building innovative AI projects. Readers will learn to develop AI applications using ChatGPT APIs, integrate them with frameworks like Flask and Django, create AI-generated art with DALL-E APIs, and optimize ChatGPT models through fine-tuning.

This repository contains samples to help design AI applications using data from an Azure SQL Database. It showcases technical concepts and workflows integrating Azure SQL data with popular AI components both within and outside Azure. The samples cover various AI features such as Azure Cognitive Services, Promptflow, OpenAI, Vanna.AI, Content Moderation, LangChain, and more. Additionally, there are end-to-end samples like Similar Content Finder, Session Conference Assistant, Chatbots, Vectorization, SQL Server Database Development, Redis Vector Search, and Similarity Search with FAISS.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

AI-For-Beginners is a comprehensive 12-week, 24-lesson curriculum designed by experts at Microsoft to introduce beginners to the world of Artificial Intelligence (AI). The curriculum covers various topics such as Symbolic AI, Neural Networks, Computer Vision, Natural Language Processing, Genetic Algorithms, and Multi-Agent Systems. It includes hands-on lessons, quizzes, and labs using popular frameworks like TensorFlow and PyTorch. The focus is on providing a foundational understanding of AI concepts and principles, making it an ideal starting point for individuals interested in AI.

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

Learn Cloud Applied Generative AI Engineering (GenEng) is a course focusing on the application of generative AI technologies in various industries. The course covers topics such as the economic impact of generative AI, the role of developers in adopting and integrating generative AI technologies, and the future trends in generative AI. Students will learn about tools like OpenAI API, LangChain, and Pinecone, and how to build and deploy Large Language Models (LLMs) for different applications. The course also explores the convergence of generative AI with Web 3.0 and its potential implications for decentralized intelligence.

Dynamiq is an orchestration framework designed to streamline the development of AI-powered applications, specializing in orchestrating retrieval-augmented generation (RAG) and large language model (LLM) agents. It provides an all-in-one Gen AI framework for agentic AI and LLM applications, offering tools for multi-agent orchestration, document indexing, and retrieval flows. With Dynamiq, users can easily build and deploy AI solutions for various tasks.

The .NET Conf Focus on AI 2024 repository contains content from the event focusing on incorporating AI into .NET applications and services. It includes slides and demos showcasing various AI-powered web apps, AI models, generative AI apps, and more. The repository serves as a resource for developers looking to explore AI integration with .NET technologies.

AgentOps is a toolkit for evaluating and developing robust and reliable AI agents. It provides benchmarks, observability, and replay analytics to help developers build better agents. AgentOps is open beta and can be signed up for here. Key features of AgentOps include: - Session replays in 3 lines of code: Initialize the AgentOps client and automatically get analytics on every LLM call. - Time travel debugging: (coming soon!) - Agent Arena: (coming soon!) - Callback handlers: AgentOps works seamlessly with applications built using Langchain and LlamaIndex.

AI-resources is a repository containing links to various resources for learning Artificial Intelligence. It includes video lectures, courses, tutorials, and open-source libraries related to deep learning, reinforcement learning, machine learning, and more. The repository categorizes resources for beginners, average users, and advanced users/researchers, providing a comprehensive collection of materials to enhance knowledge and skills in AI.

Awesome LLM Courses is a curated list of online courses focused on Large Language Models (LLMs). The repository aims to provide a comprehensive collection of free available courses covering various aspects of LLMs, including fundamentals, engineering, and applications. The courses are suitable for individuals interested in natural language processing, AI development, and machine learning. The list includes courses from reputable platforms such as Hugging Face, Udacity, DeepLearning.AI, Cohere, DataCamp, and more, offering a wide range of topics from pretraining LLMs to building AI applications with LLMs. Whether you are a beginner looking to understand the basics of LLMs or an intermediate developer interested in advanced topics like prompt engineering and generative AI, this repository has something for everyone.

Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

This project is a Node.js API example that utilizes the OpenAI API for grammar correction and speech-to-text conversion. It helps users correct their English sentences to standard English by leveraging the capabilities of the OpenAI API. The project consists of two applications: Angular and Node.js. Users can follow the installation steps to set up the project in their environment and utilize the OpenAI implementation to correct English sentences. The project also provides guidelines for contribution and support.

LLM Cookbook is a developer-oriented comprehensive guide focusing on LLM for Chinese developers. It covers various aspects from Prompt Engineering to RAG development and model fine-tuning, providing guidance on how to learn and get started with LLM projects in a way suitable for Chinese learners. The project translates and reproduces 11 courses from Professor Andrew Ng's large model series, categorizing them for beginners to systematically learn essential skills and concepts before exploring specific interests. It encourages developers to contribute by replicating unreproduced courses following the format and submitting PRs for review and merging. The project aims to help developers grasp a wide range of skills and concepts related to LLM development, offering both online reading and PDF versions for easy access and learning.

Senparc.AI is an AI extension package for the Senparc ecosystem, focusing on LLM (Large Language Models) interaction. It provides modules for standard interfaces and basic functionalities, as well as interfaces using SemanticKernel for plug-and-play capabilities. The package also includes a library for supporting the 'PromptRange' ecosystem, compatible with various systems and frameworks. Users can configure different AI platforms and models, define AI interface parameters, and run AI functions easily. The package offers examples and commands for dialogue, embedding, and DallE drawing operations.

Awesome AI is a repository that collects and shares resources in the fields of large language models (LLM), AI-assisted programming, AI drawing, and more. It explores the application and development of generative artificial intelligence. The repository provides information on various AI tools, models, and platforms, along with tutorials and web products related to AI technologies.

LlamaIndex.TS is a data framework for your LLM application. Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in Typescript and Javascript.

A comprehensive repository of resources for Chinese large language models (LLMs), including data processing tools, fine-tuning frameworks, inference libraries, evaluation platforms, RAG engines, agent frameworks, books, courses, tutorials, and tips. The repository covers a wide range of tools and resources for working with LLMs, from data labeling and processing to model fine-tuning, inference, evaluation, and application development. It also includes resources for learning about LLMs through books, courses, and tutorials, as well as insights and strategies from building with LLMs.

This open-source project, also known as **Deep Learning System** or **AI System (AISys)**, aims to explore and learn about the system design of artificial intelligence and deep learning. The project is centered around the full-stack content of AI systems that ZOMI has accumulated,整理, and built during his work. The goal is to collaborate with all friends who are interested in AI open-source projects to jointly promote learning and discussion.

Academic assistant for SICP study, referencing solutions

Leading AI & Media Expert: In-depth, Ethical, Insightful, developed on OpenAI

Expert in synthetic neurobiology, brain organoids, and AI applications in neuroscience. Powered by Breebs (www.breebs.com)

StarkNet & Cairo 1.0 Docs Integrated Expert

書籍「ROS2ではじめよう 次世代ロボットプログラミング」の内容を基にROS 2に関する質問に回答します。

Guides the design, development, and optimization of mobile applications.

基于WTF LangChain极简入门课程系列内容的AI助理，为LangChain小白答疑解惑

AI-driven web engineering expert

Learn C++ by Hands-on Labs and AI

Professional assistant for Oracle APEX and web tech

GPT expert in Neuroscience, BCI, and ML/DL developed by NICE Research Group@XMUM

Advanced IoE-focused GPT, excelling in domain knowledge, security awareness, and problem-solving, powered by OpenAI

Provides expert guidance on Matrix-themed project development.

Implement specific web applications based on sketches submitted by users

Expert in telecom, VoIP, SMS, 5G, IoT, SMPP, SIP logs, CPaaS, and exchange platforms.

Neurotechnology Expert BCI GPT with Enhanced Knowledge

Expert in TALL stack, aiding in rapid app development

Leader in Metaverse Design, Powered by OpenAI

Validates and evolves your ideas for AI application and strategy

Professional yet friendly WebXR coding assistant, utilizing primarily A-frame and Three.js frameworks.