Search Results for "no code" - Page 31
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Showing 1791 open source projects for "no code"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Techniques
Techniques for deep learning with satellite & aerial imagery
This repository is a comprehensive, curated collection of deep learning techniques and best practices specifically applied to satellite and aerial imagery. It covers everything from preprocessing and annotation to model architectures and open datasets. The guide includes code snippets, links to research papers, and hands-on tools, making it valuable for researchers, engineers, and enthusiasts working in remote sensing and geospatial AI. -
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Andromity
A terminal AI coding agent. Autonomous by choice, gated by trust
Andromity is an open-source AI coding agent that runs inside VS Code or as a standalone terminal workspace. It can analyze a codebase, propose a step-by-step implementation plan, and wait for approval before editing files. Multiple trust levels control whether plans, file changes, and terminal commands require confirmation. Parallel subagents can research, implement, and test different workstreams while maintaining separate session histories. -
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Cumora
Where agent teams gather. Cross-platform team chat
...Agents can maintain personas and memory, claim tasks, coordinate with one another, send and receive email, and use shared Kanban and calendar views. Teams can run agents through Cumora Cloud or bring their own Claude Code or Codex environment from a Mac or VPS. Cloud agents receive isolated runtime pods with access to tools such as shell commands, files, browsers, email, memory, and skills. Coordination safeguards help prevent agents from duplicating or overwriting one another's work. The interface is available across desktop, web, iOS, and Android clients built from a shared React-based frontend. -
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Vulnhuntr
AI tool for detecting complex vulnerabilities in Python codebases
Vulnhuntr is an open source security tool that uses large language models to analyze codebases and identify remotely exploitable vulnerabilities. It focuses on Python projects and applies static code analysis combined with LLM reasoning to trace how user input flows through an application. Instead of scanning entire repositories at once, it builds call chains step by step, allowing deeper inspection of complex, multi-stage issues that traditional tools may miss. Vulnhuntr can generate detailed findings, including vulnerability explanations and potential exploit paths, helping developers and security teams understand risks faster. ... -
One Monitoring Tool for IT, OT and Cloud | Free TrialModern infrastructure spans data centers, cloud platforms and factory floors, and every blind spot between them is a risk. PRTG supports SNMP, WMI, SSH and other standard protocols to monitor IT, OT and hybrid environments through one customizable dashboard. Build the views your team needs, from network health to application performance, without switching tools. Try PRTG free for 30 days now.
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Preswald
Python tool for browser-based interactive data apps in one file
...It packages application logic, data processing, and user interface components into a single self-contained output, enabling easy sharing and deployment without requiring local dependencies. Preswald leverages a WebAssembly runtime along with technologies like Pyodide and DuckDB to execute Python code directly in the browser environment. This approach allows developers to create dashboards, reports, notebooks, and data tools that are portable, fast, and capable of running offline. Preswald emphasizes a code-first workflow where users define applications entirely in Python while using built-in UI components such as tables, charts, and forms. ... -
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Open SaaS
Open source SaaS boilerplate for React, NodeJS apps with Wasp stack
Open SaaS is a free and open source starter template designed to help developers quickly build and launch Software-as-a-Service applications. It is built on the Wasp full stack framework, which combines React, NodeJS, and Prisma to manage both client and server code within a unified architecture. Open SaaS provides a production-ready foundation that includes common SaaS functionality such as authentication, payments, analytics, and file uploads. Developers can use it as a boilerplate to avoid writing repetitive setup code and instead focus on building product features. It integrates several commonly used services and tools, including payment processing systems, email providers, analytics platforms, and AI integrations. ... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis. The repository integrates numerous popular machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face. ... -
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Kaggle Solutions
Collection of Kaggle Solutions and Ideas
Kaggle Solutions is an open-source repository that compiles winning solutions, insights, and educational resources from hundreds of Kaggle data science competitions. The repository acts as a knowledge base for competitive machine learning by collecting solution write-ups, discussion threads, code notebooks, and tutorial resources shared by top Kaggle participants. Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques used by high-ranking competitors. The repository also highlights important machine learning concepts such as feature engineering, cross-validation strategies, ensemble modeling, and post-processing methods commonly used in winning solutions. ... -
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Agentless
An agentless approach to automatically solve software development
Agentless is an open-source framework that applies large language models to automatically resolve software development issues without relying on complex autonomous agent systems. The project proposes an alternative approach to AI-driven code repair that avoids the overhead of multi-agent orchestration by using a structured pipeline for identifying and fixing bugs. When solving a problem, the system first performs localization to determine which files, functions, or code segments are most likely responsible for the issue. It then generates multiple candidate patches for the identified locations using language model reasoning and diff-style edits. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
...The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. By building agents incrementally, the project helps learners grasp concepts such as decision loops, task decomposition, and environment interaction. -
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llms-from-scratch-cn
Build a large language model from 0 only with Python foundation
...Through a collection of notebooks, code examples, and translated learning materials, users can explore how to implement components such as multi-head attention, data loaders, and training pipelines using Python and PyTorch. -
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MemFree
Hybrid AI Search Engine & AI Page Generator
...It supports multiple AI models and search providers, enabling flexible configuration depending on cost, performance, or privacy requirements. Beyond search, memfree includes an AI Page Generator that can transform text or images into production-ready frontend code using modern web stacks. The platform emphasizes productivity by automatically organizing information and reducing the need for manual bookmarking or note management. Overall, memfree positions itself as an all-in-one knowledge assistant and rapid UI generation tool for developers and power users. -
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. Agent-Lightning introduces a lightweight training pipeline that observes agents’ execution traces, converts them into structured data, and feeds them into training algorithms, enabling users to improve agent behaviors systematically. ... -
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AI Agents Masterclass
Follow along with my AI Agents Masterclass videos
AI Agents Masterclass is an educational open-source repository designed to teach developers how to build, train, and deploy intelligent AI agents using modern tooling and workflow patterns. The project includes structured lessons, code examples, and practical exercises that cover foundational concepts like prompt engineering, chaining agents, tool usage, plan execution, evaluation, and safety considerations. It breaks down how autonomous agents interact with external systems, handle iterative reasoning, and integrate with third-party services or APIs to perform real tasks — for example, web search, browsing, scheduling, or coding assistance. ... -
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Live Agent Studio
Open source AI Agents hosted on the oTTomator Live Agent Studio
...Each agent in the collection is designed for a specific use case — such as content summarization, task automation, travel planning, or RAG workflows — and is provided with the code or configuration needed to explore and extend it on your own, making the repository both a learning resource and a practical starting point for real projects. The repository is community focused, with sample agents like tweet generators, smart selectors, research assistants, and multi-tool workflows that show how agents can integrate with tools like n8n or custom Python code. ... -
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Context Engineering Template
Context engineering is the new vibe coding
...The repository provides templates such as CLAUDE.md for defining global project rules, INITIAL.md for feature requests, and folders for examples, PRPs, validation scripts, and settings to support systematic prompt generation and execution with tools like Claude Code. By using this template, teams can ensure consistency across AI outputs, reduce errors that stem from contextual misunderstandings, and build reusable patterns. -
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4M
4M: Massively Multimodal Masked Modeling
...The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things like depth tokenizers, input masks for generation, and CUDA build questions, signaling active research iteration. The design leans into flexibility and steerability, so prompts and masks can shape behavior without bespoke heads per task. ... -
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MGIE
Guiding Instruction-based Image Editing via Multimodal Large Language
...The project focuses on making edits explainable and controllable: the model interprets text guidance, reasons over image content, and outputs edits aligned with user intent. It’s positioned as an ICLR 2024 Spotlight work, with code and references that show how to connect language planning to concrete image operations. This bridges a gap between free-form prompts and precise edits by letting users describe “what” and “where” in everyday language. The repo includes instructions, examples, and links that situate MGIE within Apple’s broader line of multimodal research. ... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
...The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval, detection, and segmentation—often requiring little or no fine-tuning. The repository includes code for training, evaluating, and feature extraction, with utilities to run k-NN or linear evaluation baselines to assess representation quality. Pretrained checkpoints cover multiple model sizes so practitioners can trade accuracy for speed and memory depending on their deployment constraints. -
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OpenAI Cookbook
Examples and guides for using the OpenAI API
openai-cookbook is a repository containing example code, tutorials, and guidance for how to build real applications on top of the OpenAI API. It covers a wide range of use cases: prompt engineering, embeddings and semantic search, fine-tuning, agent architectures, function calling, working with images, chat workflows, and more. The content is primarily in Python (notebooks, scripts), but the conceptual guidance is applicable across languages. -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. -
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NoneBot
Asynchronous multi-platform robot framework written in Python
...Supports multiple platforms and multiple incident response methods. Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. It is based on Python's type annotations and asynchronous features, and can provide convenient and flexible support for your needs. NoneBot2 is written based on Python asyncio , and has a certain degree of synchronous function compatibility based on the asynchronous mechanism. ... -
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AI Copywriter
An AI copywriter that uses real copywriting skills + real marketing
...It refuses to invent product facts or unsupported numbers and requests stronger evidence when a claim needs proof. Because the core artifact is a single SKILL.md file, it can run in Claude Code, ChatGPT, Manus, and other instruction-compatible agent systems. -
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i-have-adhd
A skill for your coding agent to stop it from burying the answer
...The style also restates the current state, makes completed progress visible, and describes errors without unnecessary drama. Every response should end with one concrete next step rather than a generic invitation or closing phrase. The skill can be installed as a plugin for Claude Code and Codex, with guidance available for other coding agents. Because its behavior is defined in an editable skill file, users can fork and tune the rules for their own workflow. -
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Edgee
AI gateway with token compression for Claude Code, Codex, and more
Edgee is an edge-native execution platform designed to run AI-driven logic and data processing directly at the network edge, reducing latency and improving responsiveness for modern applications. It enables developers to deploy functions and workflows closer to users, allowing real-time processing without relying heavily on centralized cloud infrastructure. The platform is built to support event-driven architectures, where actions are triggered by incoming requests, user behavior, or...
