Search Results for "no code" - Page 10
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Showing 2582 open source projects for "no code"
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o1-engineer
o1-engineer is a command-line tool designed to assist developers
o1-engineer is a command-line development assistant powered by OpenAI’s API. It helps developers interact with projects through commands for code generation, file editing, project planning, and code review. The tool can add, edit, and manage both files and folders directly from the terminal. Its planning command can create structured project plans that can then guide systematic file and directory generation. It also keeps conversation history and allows users to save or reset context as needed. ... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
...When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. In addition to code analysis, the tool can produce daily development summaries and notifications that help teams track progress and review activity across projects. -
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Google Toolbox for Mac
Google Toolbox for Mac
Google Toolbox for Mac (GTMSession) is a comprehensive collection of open source Objective-C utilities and frameworks developed by Google to support macOS and iOS application development. It consolidates reusable code components drawn from various internal Google projects, offering developers a wide range of tools for building efficient, maintainable Apple platform software. The library includes modules for networking, logging, testing, data handling, and user interface extensions, helping developers avoid reinventing common functionality. Its modular design allows developers to integrate only the components they need, improving project flexibility and performance. ... -
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gpt-oss
gpt-oss-120b and gpt-oss-20b are two open-weight language models
...Both models use a native MXFP4 quantization for efficient memory use and support OpenAI’s Harmony response format, enabling transparent full chain-of-thought reasoning and advanced tool integrations such as function calling, browsing, and Python code execution. The repository provides multiple reference implementations—including PyTorch, Triton, and Metal—for educational and experimental use, as well as example clients and tools like a terminal chat app and a Responses API server. -
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ModelScope
Bring the notion of Model-as-a-Service to life
...Model contributors of different areas can integrate models into the ModelScope ecosystem through the layered APIs, allowing easy and unified access to their models. Once integrated, model inference, fine-tuning, and evaluations can be done with only a few lines of code. -
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AgentHandover
AgentHandover observes, learns and teaches agents with skills
AgentHandover is a Mac-focused system that observes how a user works and converts repeated workflows into reusable, self-improving skills for AI agents. It is designed for tools such as Claude Code, OpenClaw, Codex, Hermes, Cursor, Windsurf, and other MCP-compatible environments. Instead of asking users to manually write long prompts or static automation instructions, it records real actions, infers decision logic, and produces skills that include steps, strategy, guardrails, selection criteria, and writing style. The project supports both focused recording for specific tasks and passive discovery for workflows that appear repeatedly over time. ... -
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Continuous Claude v3
Context management for Claude Code. Hooks maintain state via ledgers
Continuous Claude v3 is a persistent, multi-agent development environment built around the Claude Code CLI that aims to overcome the limitations of standard LLM context windows. Rather than relying on a single session’s context, Continuous Claude uses mechanisms like ledgers, YAML handoffs, and a memory system to preserve and recall state across multiple sessions, ensuring that learned insights and plans are not lost when context compaction occurs. -
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Python
The Python programming language
Python is a powerful, high-level programming language known for its readability, simplicity, and versatility. It supports multiple programming paradigms including procedural, object-oriented, and functional styles. CPython, the reference implementation, is developed and maintained by the Python Software Foundation and the global open-source community. The language includes a vast standard library that accelerates development by providing built-in modules for file handling, networking, data... -
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Mito
AI-powered Jupyter spreadsheet that converts workflows into Python
...Built for analysts, developers, and teams, it simplifies automation, reduces repetitive tasks, and accelerates the transition from data exploration to reusable code. -
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Ploomber
The fastest way to build data pipelines
Ploomber is an open-source framework designed to simplify the development and deployment of data science and machine learning pipelines. It allows developers to transform exploratory data analysis workflows into production-ready pipelines without rewriting large portions of code. The system integrates with common development environments such as Jupyter Notebook, VS Code, and PyCharm, enabling data scientists to continue working with familiar tools while building scalable workflows. Ploomber automatically manages task dependencies and execution order, allowing complex pipelines with multiple stages to run reliably. ... -
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UI UX Pro Max
AI SKILL that provide design intelligence
...It uses an AI reasoning engine to generate complete design systems tailored to project requirements, recommending layouts, typography, colors, spacing, and component structures automatically based on natural language prompts. Users can ask for specific UI/UX tasks or design patterns, and the skill will produce guidelines, code snippets, and responsive implementation suggestions that align with industry best practices and accessibility standards. It supports a broad range of tech stacks including HTML/Tailwind, React, Vue, mobile UI frameworks, and more, making it versatile for designers and developers alike. The project also includes CLI tooling and template generators that streamline scaffold creation and design system persistence across sessions. -
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Modin
Scale your Pandas workflows by changing a single line of code
Scale your pandas workflow by changing a single line of code. Modin uses Ray, Dask or Unidist to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. -
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AIBuildAI
An AI agent that automatically builds AI models
...The project explores recursive AI development, where models are used not only as tools but as builders capable of constructing other AI systems, workflows, or components. It provides a structured environment for orchestrating agents that can plan, execute, and refine tasks such as code generation, system design, and iterative improvement loops. The framework is designed to support experimentation with self-improving AI pipelines, allowing developers to test concepts like automated architecture search or adaptive system evolution. It integrates multiple components including prompt management, execution control, and feedback loops to ensure that generated outputs can be evaluated and improved over time. -
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Kubernetes Operator Pythonic Framework
A Python framework to write Kubernetes operators in just a few lines
...A full-featured operator in just 2 files: a Dockerfile + a Python file (*). Handling functions registered via decorators with a declarative approach. No infrastructure boilerplate code with K8s API communication. Both sync and async handlers, with sync ones being threaded under the hood. Detailed documentation with examples. -
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openbench
Provider-agnostic, open-source evaluation infrastructure
openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves. With a simple CLI interface (e.g. bench eval <benchmark> --model <model-id>), you can quickly evaluate any model supported by Groq or other providers (OpenAI, Anthropic, HuggingFace, local models, etc.). openbench also supports private/local evaluations: you can integrate your own custom benchmarks or data (e.g. internal test suites, domain-specific tasks) to evaluate models in a privacy-preserving way. -
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Agently
AI Agent Application Development Framework
Build AI agent native application in very little code. Easy to interact with AI agents in code using structure data and chained-calls syntax. Enhance AI Agent using plugins instead of rebuilding a whole new agent. Agently is a development framework that helps developers build AI agent native applications really fast. You can use and build AI agents in your code in an extremely simple way. -
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Anymail
Django email backends and webhooks for Amazon SES, Mailgun, Mailjet
Anymail lets you send and receive email in Django using your choice of transactional email service providers (ESPs). It extends the standard django.core.mail with many common ESP-added features, providing a consistent API that avoids locking your code to one specific ESP (and making it easier to change ESPs later if needed). Integration of each ESP’s sending APIs into Django’s built-in email package, including support for HTML, attachments, extra headers, and other standard email features. Extensions to expose common ESP-added functionality, like tags, metadata, and tracking, with code that’s portable between ESPs. ... -
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Typer
Typer, build great CLIs, based on Python type hints
...Designed to be easy to use and learn. Less time reading docs. It's easy to use for the final users. Automatic help, and automatic completion for all shells. Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. The simplest example adds only 2 lines of code to your app: 1 import, 1 function call. Grow in complexity as much as you want, create arbitrarily complex trees of commands and groups of subcommands, with options and arguments. And it's intended to be the FastAPI of CLIs. ... -
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Transcrypt
Python 3.7 to JavaScript compiler
Python in the browser, precompiled for speed. Transcrypt started out as a personal repo, owned by Jacques de Hooge. As the project caught on and the number of people contributing issues, ideas and code grew, the repo was transferred to the QQuick organization, to be able to form a developer team on GitHub. There's a simple parallel between the Python and the JavaScript code. In combination with the use of source maps, this enables efficient debugging. Also, code can be tested from the command prompt using stubs. Lightning-fast JavaScript 6 code: call caching, for-loop optimization, in-line JavaScript etc. ... -
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Unsloth-MLX
Bringing the Unsloth experience to Mac users via Apple's MLX framework
Unsloth-MLX offers developers the power of Unsloth’s efficient large language model fine-tuning experience on Apple Silicon Macs by wrapping Apple’s native MLX framework with an API fully compatible with Unsloth workflows. This project removes traditional barriers that prevent Mac users from prototyping and experimenting with LLM training locally by allowing the same code used in cloud GPU environments to run on M-series hardware, improving workflow continuity and reducing iteration costs. It supports loading and training Hugging Face models with fine-tuning strategies like SFT, DPO, ORPO, and GRPO and even handles exporting models to formats like GGUF for downstream use, although some limitations apply with quantized models. ... -
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Agently 4
Build GenAI application quick and easy
Agently is a Python framework for building generative-AI (“GenAI”) applications; it focuses on enabling developers to orchestrate AI agents, workflows, and event-driven logic in a robust, reusable way. With Agently, one can define agents that call different models, chain tasks, trigger workflows based on events, and switch models with minimal code changes. It abstracts away boilerplate around model API calls, tool usage, prompt management, and workflow state. The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. ... -
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Hello Python
Comprehensive tutorial repository aimed at teaching the Python program
Hello-Python is a comprehensive tutorial repository aimed at teaching the Python programming language from scratch for beginners. It includes over 100 classes and about 44 hours of video instruction, combined with code samples, projects, and a chat community for support. The material covers the fundamentals—variables, data types, loops, functions—as well as intermediate topics like date handling, list comprehensions, file IO, regular expressions, modules, and packages. The course is designed to be accessible: no prior programming experience required, and the resources are freely available. ... -
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latexify
A library to generate LaTeX expression from Python code
latexify_py converts small, math-heavy pieces of Python code into human-readable LaTeX that mirrors the intent of the computation, not just its surface syntax. It parses Python functions and expressions into an abstract syntax tree (AST), applies symbolic rewrites for common mathematical constructs, and then emits LaTeX that compiles cleanly in standard environments. Typical use cases include turning analytical utilities—like probability mass functions, activation formulas, or recurrence relations—into equations suitable for papers, notebooks, and slide decks. ... -
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DeepLabCut
Implementation of DeepLabCut
...Please see the original paper and the latest work below! This package is collaboratively developed by the Mathis Group & Mathis Lab at EPFL (releases prior to 2.1.9 were developed at Harvard University). The code is freely available and easy to install in a few clicks with Anaconda (and pypi). DeepLabCut is an open-source Python package for animal pose estimation. -
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ClearML
Streamline your ML workflow
ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. ...
