Essential Guide for Developers

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<aside> 👉 This document contains 55 development assistants, 22 tools you can use to develop AI applications, 15 no-code/low-code tools to help develop apps, 8 AI/ML communities to join, and 9 AI Twitter accounts to follow for a total of 105 excellent resources.

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Development Assistants

| Github Copilot | Your AI pair programmer. GitHub Copilot uses OpenAI Codex to suggest code and entire functions in real-time, right from your editor. | https://github.com/features/copilot | | --- | --- | --- | | Tabnine | AI assistant for software developers, Code faster with whole-line & full-function code completions. | https://www.tabnine.com/ | | Hey Github! | Write code without a keyboard (speech to code) | https://githubnext.com/ | | OpenAI Codex | AI system that translates natural language to code. Powers most of these tools | https://openai.com/blog/openai-codex/ | | AICommit | AI-generated Git commit messages | https://github.com/abi/autocommit | | Deep Code (snyk code) | Secure code with a developer-friendly experience. | https://www.deepcode.ai/ | | AI2Sql | With AI2sql, engineers and non-engineers can easily write efficient, error-free SQL queries without knowing SQL. | https://www.ai2sql.io/ | | Replit | Yesterday, coding was slow, repetitive, and hard to learn. Today, all that changes with Replit's in-browser coding AI. | https://replit.com/site/ghostwriter | | HTTPie AI | HTTPie is making APIs simple and intuitive for those building the tools of our time. | https://httpie.io/ | | Mutable | Another AI completion application, but uses speech-like prompting to complete. | https://mutable.ai/ | | Polycoder | Open source alternative to OpenAI’s Codex | https://github.com/VHellendoorn/Code-LMs | | CodeWP | AI Code Generator For WordPress Creators | https://codewp.ai/ | | AskCodi | AskCodi is a comprehensive toolkit that uses AI to assist programmers and developers in creating more quickly. | https://www.askcodi.com/ | | Codiga | Customizable static code analysis that works in your IDE, CI/CD pipelines and more | https://www.codiga.io/ | | Ponicode | You shouldn't have to trade between quality and efficiency. Reaching high coverage and building future-proof code does not have to be tedious. | https://www.ponicode.com/ | | Jedi | An autocompletion, static analysis and refactoring library for Python | https://github.com/davidhalter/jedi/ | | AutoRegex | Effortless conversions from English to Regex | https://www.autoregex.xyz/ | | AI CLI | Get answers for CLI commands from GPT3 | https://github.com/abhagsain/ai-cli | | Codeium | Natural language to code, boilerplate coding, find and use APIs, unit test generation. | https://www.codeium.com/ | | Duino Code Generator | Generate code for Arduino! | https://www.duinocodegenerator.com/ | | Kodezi | IDE with some unique features, like being able to CHAT with your codebase. | https://kodezi.com/ | | Maverick | AI Code suggestion for Python in VSCode | https://marketplace.visualstudio.com/items?itemName=YurtsAI.maverick | | Buildt | Buildt is an AI tool to help developers quickly search and understand large codebases | buildt.ai | | BlackBox | Another code completer? | https://www.useblackbox.io/ | | Spellbox | IDE with AI support. Code explanation, completion, bookmarking, also available as a VSCode extension. | https://spellbox.app/ | | CheatLayer | Cheat layer solves impossible business automation problems using a combination of no-code tools and machine learning to function as your personal software engineer. | https://cheatlayer.com/ | | Programming Helper | Generate code just by typing a text description. AI will create the code for you. Lots of interesting features. | https://www.programming-helper.com/ | | Fig | The next-generation command line. | https://fig.io/ | | Stenography | Automatic documentation. | https://stenography.dev/ | | What the diff | Your AI-powered code review assistant Save costly developer time by automating pull request summaries. Open a pull request and get a summary of the changes in seconds. Instantly understand the implications of small pull requests and get a huge headstart on big ones. | https://whatthediff.ai/ | | Code squire | Turn your thoughts into code AI code writing assistant for data scientists, engineers, and analysts. Get code completions and suggestions as you type. Press tab to insert. | https://codesquire.ai/ | | GPT Duck | Tell it a github repository, and then ask it questions about that repository. | https://www.gptduck.com/ | | Mintlify | Build the documentation you've always wanted. Beautiful out of the box, easy to maintain, and optimized for user engagement. | https://mintlify.com/ | | LangChain | is a framework for developing and deploying applications powered by large language models developed by the company with the same name. The tool provides modular building blocks and components for building custom chains, it allows inspection, monitoring and evaluation of applications and can turn any chain into a REST API. | https://github.com/langchain-ai/langchain | | PyTorch | PyTorch is a very popular General Purpose framework and library developed by Facebook’s AI Research lab and released in October 2016, with over 77,000 stars on GitHub. | https://github.com/pytorch/pytorch | | GPT4ALL | GPT4ALL is a client that can install and run AI models on consumer-grade and edge hardware provided by Nomic AI. Optimized for CPU-only, no-internet environments, GPT4All runs on Windows, OSX and Ubuntu and can run a series of models, including Alpaca, Llama, Pythia, Mosaic, Falcon, StablLM and custom GPT4All ones. | https://github.com/nomic-ai/gpt4all | | Ollama | Ollama is a tool which enables users to use open source LLMs locally on their Windows, macOS or Linux machine. With support for a variety of models, including Gemma, Llama, Mistral, Mixtral, Command-R and Llava, the tool gathered over 52,000 stars on GitHub since its launch in February 2023. | https://ollama.com/ https://github.com/ollama/ollama | | ColossalAI | ColossalAI provides a collection of parallelism components for distributed training and inference of models with a few lines of code. Their tools support data, pipeline, tensor and sequence parallelism, as well as a zero redundancy optimizer and a method for automatic management of parallelization. | https://github.com/hpcaitech/ColossalAI | | DeepSpeed | DeepSpeed, provided by Microsoft, is a deep learning optimization library for distributed training and inference. It is developed to support large to very large models that need to be trained at scale on hundreds and thousands of GPUs in resource constrained systems, and yet still deliver low latency and high throughput for inference | https://github.com/microsoft/DeepSpeed https://www.deepspeed.ai/ | | LlamaIndex | **LlamaIndex** is a data framework for LLM-based applications with Retrieval Augmented Generation. The tool provides the abstractions necessary to more easily ingest, structure, and access private or domain-specific data in order to inject them into LLMs. | https://github.com/run-llama/llama_index https://docs.llamaindex.ai/ | | Ray | Ray is an unified compute framework for scaling AI and Python workloads  — from reinforcement learning to deep learning to tuning, and model serving. It consists of a core distributed runtime and a set of AI libraries for simplifying ML compute, including ones that deal with datasets, distributed training, hyperparameter tuning and inference. Developed by Anyscale, Ray has over 30,000 stars on GitHub. | https://github.com/ray-project/ray https://ray.io/ | | Milvus | Milvus is a vector database built to power embedding similarity search and AI applications. It is used to make unstructured data search more accessible regardless of the deployment environment. Developed by The Linux Foundation AI & Data organization, Milvus has gathered over 36,000 stars | https://milvus.io/ https://github.com/milvus-io/milvus | | Faiss | Faiss (Facebook AI Similarity Search) ****is a library for efficient similarity search and clustering of dense vectors developed by Meta AI. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning | https://faiss.ai/ https://github.com/facebookresearch/faiss | | Autogen | Autogen is a multi-agent conversation framework that works as a high-level abstraction for building workflows using multiple LLMs.  Developed by Microsoft, it is meant to support the development of modular and complex agents to perform sophisticated tasks that use AI models, as well as a variety of other tools and components. | https://github.com/microsoft/autogen | | Mindsdb | Mindsdb is a platform which automates pipelines that connect real-time enterprise data to AI systems. It is used to train and customize models, automate tasks, define and execute trigger events and provide observability.  Since it launched in 2017, it has gathered over 21,000 stars on GitHub. | https://github.com/mindsdb/mindsdb https://mindsdb.com/ | | Semantic Kernel | Semantic Kernel from Microsoft is an SDK that lets developers build AI agents that can call on existing code. It lets them mix conventional programming languages, like C# and Python, with LLMs using prompt templating, chaining, and planning capabilities in order to build AI experiences into existing applications. | https://github.com/microsoft/semantic-kernel https://aka.ms/semantic-kernel | | Vllm | Vllm is a high-throughput and memory-efficient inference engine for LLMs that uses PagedAttention, an algorithm for the management of attention keys and values. | https://github.com/vllm-project/vllm | | MLC LLM | Machine Learning Compilation for Large Language Models (MLC LLM) is a universal deployment solution that allows native deployment of any large language models with native APIs with compiler acceleration. The mission of the project is to enable everyone to develop, optimize and deploy AI models natively on everyone’s devices with ML compilation techniques. Developed by researchers at Carnegie Mellon University, MLC LM has over 16,000 stars on GitHub. | https://github.com/mlc-ai/mlc-llm | | The Unity Machine Learning Agents Toolkit | The Unity Machine Learning Agents Toolkit enables games and simulations to serve as environments for training intelligent agents. It provides PyTorch-based algorithms to enable game developers to train intelligent agents for 2D, 3D and VR/AR games. The  agents can be used for multiple purposes, including controlling NPC behavior (in a variety of settings such as multi-agent and adversarial), automated testing of game builds and evaluating different game design decisions pre-release. The toolkit gathered over 16,000 stars on GitHub. | https://github.com/unity-Technologies/ml-agents | | Devin | Meet Devin, the world’s first fully autonomous AI software engineer. ‍ Devin is a tireless, skilled teammate, equally ready to build alongside you or independently complete tasks for you to review. | https://www.cognition-labs.com/introducing-devin | | SWE-agent | Researchers from Princeton NLP have developed SWE-agent, an open-source system that turns GPT-4 into an AI software engineering agent that can autonomously solve issues in GitHub repositories. | https://github.com/princeton-nlp/SWE-agent | | OpenDevin | OpenDevin, an open-source project aiming to replicate Devin, an autonomous AI software engineer who is capable of executing complex engineering tasks and collaborating actively with users on software development projects. This project aspires to replicate, enhance, and innovate upon Devin through the power of the open-source community. | https://github.com/OpenDevin/OpenDevin | | Devika | Devika is a sophisticated AI software engineer designed to comprehend complex human instructions, break them down into actionable steps, research pertinent information, and generate code to accomplish specified tasks | https://github.com/stitionai/devika | | AutoDev | Researchers at Microsoft, GitHub Copilot’s developer, recently uploaded a paper to the arXiv preprint server introducing AutoDev, which uses autonomous AI agents to generate code and test cases, run tests and check the results, and fix bugs within the test cases. | https://arxiv.org/abs/2403.08299 |

Develop with AI

• Get predictions, monitor predictions, and manage your models
• Expedites ML projects
• ML project on-premise or in the cloud
• Pre-configured Virtual Machines (VMs) | https://cloud.google.com/vertex-ai | | | Azure AI (Microsoft) | - Python-based automated ML service
• Machine translation
• Object, speech, and text recognition capabilities
• AI templates for creating bots | https://azure.microsoft.com/en-us/solutions/ai/ | | | IBM Watson | - Quick development and deployment for AI applications
• Speech-to-text capabilities
• NLP and NLU services
• Powerful mobile app APIs | https://www.ibm.com/watson | | | H20 (Open source) | - Includes AutoML functionality
• Supports many algorithms like gradient boosted machines, deep learning, generalized linear models, etc.
• Linearly scalable platform
• Develop mobile apps using R, Java, and Python | https://h2o.ai/ | | | TensorFlow | - Seamlessly deploy AI-based solutions on mobiles, desktop, edge devices, etc.
• Extensive set of tools, libraries, and community resources
• Deep analytics, service automation, unsupervised training, etc.
• Wide range of features and functionalities | https://www.tensorflow.org/ | | | MxNet (Apache) | - Open-source deep learning framework
• Enhances AI-based applications with NLP
• Highly scalable framework
• Define, train, and deploy neural networks | https://mxnet.apache.org/versions/1.9.1/ | | | Teachable Machine | Train a computer to recognize your own images, sounds, & poses. | https://teachablemachine.withgoogle.com/ | | | Helicone | Observe GPT-3 Logs to track usage, costs, and latency. | https://www.helicone.ai/ | | | Shaped | Recommendation/discovery engine for you applications. | https://www.shaped.ai/ | | | Retrune | Better(?) frontend for GPT-3 | https://retune.so/ | | | Chatbot Kit | It’s a kit… for chatbots | https://chatbotkit.com/ | | | Convei | Character chat SDK for games | https://www.convai.com/ | | | Riku | Learn how to build using AI | https://riku.ai/ | | | GPUx | Machines ready for your AI shenanigans | https://gpux.ai/ | | | Lightning AI | Train, deploy, and ship AI products Lightning fast | https://lightning.ai/ | | | Pipeline AI | Serverless GPU inference for ML models. Pay-per-millisecond API to run ML in production. | https://www.pipeline.ai/ | | | Liner AI | Liner is a free tool that lets you train your ML models easily. It takes your training data and gives you an easy-to-integrate ML model. No coding or expertise in machine learning required. | https://liner.ai/ | | | OpenAI’s Whisper | Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. | https://github.com/openai/whisper | | | Synthetic AI Data | Synthetic data is a cost-effective way to train and improve AI models. By using the syntheticAIdata, you can easily generate large synthetic datasets, which will significantly speed up the training of vision AI models for tasks such as image classification, image segmentation and object detection. Our solution will help you bring AI-powered applications to market faster. | https://syntheticaidata.com/ | | | Shumai | A fast, network-connected, differentiable tensor library for TypeScript (and JavaScript). Built with bun + flashlight for software engineers and researchers alike. | https://github.com/facebookresearch/shumai | | | Runpod.io | Rent Cloud GPUs from $0.2/hour | https://www.runpod.io/ | | | Dust | Design and Deploy Large Language Model Apps. | https://dust.tt/ | | | | | | |

No-code / Low-code

Communities