Search Results for "code framework" - Page 2
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Showing 332 open source projects for "code framework"
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Inkeep
Create AI Agents in a No-Code Visual Builder or TypeScript SDK
Inkeep is an open-source framework for building and deploying AI agent workflows and interactive assistants that operate autonomously across applications, enterprise environments, and customer engagement use cases. It lets developers and non-technical users create, manage, and orchestrate multi-agent systems using both a no-code visual builder and a full TypeScript SDK, giving two ways to define agent behaviors that stay in sync with each other. -
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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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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. -
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PraisonAI
PraisonAI application combines AutoGen and CrewAI or similar framework
PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction. -
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weixin-agent-sdk
Bridging framework for connecting arbitrary AI agents
Weixin Agent SDK is an unofficial bridging framework for connecting arbitrary AI agents to Weixin through a simple programming interface. Developers implement an Agent interface that receives conversation identifiers, text, and optional media and returns text or media responses. An included ACP adapter can connect compatible agents such as Claude Code, Codex, and other command-line agents without custom integration code. -
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Harmonist
Portable AI agent orchestration with mechanical protocol enforcement
Harmonist is a portable multi-agent orchestration framework for AI coding assistants such as Cursor, Claude Code, Copilot, Windsurf, and Aider. It is designed to make agent workflows more reliable by enforcing protocol rules mechanically instead of trusting prompts alone. The framework includes a catalog of specialized agents, validated memory behavior, supply-chain checks, and hooks that gate code-changing turns. -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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omp (Oh My Pi)
AI Coding agent for the terminal
omp (Oh-My-Pi) is an open-source AI agent toolkit focused on creating intelligent coding assistants that operate directly from the terminal environment. The project provides a command-line coding agent capable of analyzing repositories, generating commits, editing code, and interacting with development tools through an integrated tool system. Instead of functioning as a simple prompt-based assistant, the system includes an agent architecture that can inspect Git repositories, analyze... -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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Automaton
The first AI that can earn its own existence, replicate, and evolve
Automaton is an open-source project designed to provide a flexible framework for building and simulating computational automata and related formal systems. The repository focuses on giving developers and researchers a programmable environment to experiment with state machines, language recognition models, and algorithmic behaviors that mirror theoretical computer science constructs. Its architecture emphasizes modularity so users can extend or customize automaton types without rewriting core... -
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Remotion
Make videos programmatically with React
...The framework supports exporting to standard video formats, audio synchronization, frame callbacks, and powerful tooling for previewing and debugging, so teams can iterate quickly and reliably. -
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MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. ... -
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Agent Development Kit (ADK) for Java
An open-source, code-first Java toolkit
Google’s Agent Development Kit for Java is an open-source toolkit that helps developers design, evaluate, and deploy advanced AI agents using the Java programming language. The framework follows a code-first approach that treats agent development as a structured software engineering task rather than a collection of prompt scripts. It provides abstractions and tools that allow developers to create agents capable of executing complex workflows, calling tools, and interacting with external services. ADK is designed to be flexible and modular so that developers can build simple automation agents or large distributed agent systems depending on their needs. ... -
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OpenSumi
A framework helps you quickly build Cloud or Desktop IDE products
A framework helps you quickly build Cloud or Desktop IDE products. Integrate with your coding frameworks with ease. Support the container, Electron and front-end frameworks. Also help to ship and deploy quickly. Support VS Code plugins, OpenSumi plugins and OpenSumi modules to meet various business requirements. Customize the UI design in any way you like, no matter to simply configure the built-in UI, or develop a UI template, or build your own UI through plugins. -
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Stagehand
An AI web browsing framework focused on simplicity and extensibility
An AI web browsing framework focused on simplicity and extensibility. Stagehand is the AI-powered successor to Playwright, offering three simple APIs (act, extract, and observe) that provide the building blocks for natural language-driven web automation. The goal of Stagehand is to provide a lightweight, configurable framework, without overly complex abstractions, as well as modular support for different models and model providers. -
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Mistral Vibe CLI
Minimal CLI coding agent by Mistral
Mistral Vibe is an AI-powered “vibe-coding” command-line interface (CLI) and coding-assistant framework built by Mistral AI to let developers write, refactor, search, and manage code through natural language and context-aware automation, rather than manual typing only. It aims to take developers out of repetitive boilerplate and let them stay “in the flow”: you can ask the tool to generate functions, refactor code, search across the codebase, manipulate files, commit changes via Git, or run commands — all from a unified CLI interface. ... -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best model and reduce training costs by using the latest optimization algorithms. ... -
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Qwen-Agent
Agent framework and applications built upon Qwen>=3.0
Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
...The framework emphasizes self-managing workflow generation, where it can infer steps, refine them, and adapt plans even when users cannot fully specify implementation details up front. It also describes resource orchestration and iterative self-improvement behaviors, including controlled code generation for building tools and agent capabilities when needed. -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. -
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HybridClaw
The enterprise operating layer for open agents
HybridClaw is an emerging open-source framework focused on enabling hybrid AI agent systems that combine local execution, tool integration, and multi-agent orchestration into a cohesive development environment. It is designed to work alongside modern agent ecosystems such as OpenClaw, Claude Code, and similar agentic coding tools, providing a flexible infrastructure for managing agent behaviors, workflows, and capabilities. -
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Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore cutting-edge techniques directly from the teams that developed them. ... -
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Magicoder
Empowering Code Generation with OSS-Instruct
Magicoder is an open-source family of large language models designed specifically for code generation and software development tasks. The project focuses on improving the quality and diversity of code generation by training models with a novel dataset construction approach known as OSS-Instruct. This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real... -
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HumanEval
Code for the paper "Evaluating Large Language Models Trained on Code"
human-eval is a benchmark dataset and evaluation framework created by OpenAI for measuring the ability of language models to generate correct code. It consists of hand-written programming problems with unit tests, designed to assess functional correctness rather than superficial metrics like text similarity. Each task includes a natural language prompt and a function signature, requiring the model to generate an implementation that passes all provided tests. -
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Laravel Boost
Laravel-focused MCP server for augmenting AI powered local development
Boost is a Laravel-first toolkit that supercharges AI-assisted development by giving assistants structured, Laravel-aware context. At its core it runs as an MCP server that exposes a battery of Laravel-specific tools, so an AI agent can explore your app, inspect code and config, and take targeted actions instead of guessing. It ships opinionated, composable guidelines tuned for popular Laravel packages, which helps keep generated code idiomatic and consistent with framework norms. The package also curates a large body of vectorized Laravel ecosystem knowledge that’s scoped to what you’ve actually installed, improving retrieval precision and response quality. ...
