Search Results for "artificial intelligence projects" - Page 23
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Showing 3036 open source projects for "artificial intelligence projects"
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Eigent
The Open Source Cowork Desktop to Unlock Your Exceptional Productivity
Eigent is an open-source cowork desktop application designed to help you build, manage, and deploy a custom AI workforce. It enables multiple specialized AI agents to collaborate in parallel, turning complex workflows into automated, end-to-end tasks. Built on the CAMEL-AI multi-agent framework, Eigent emphasizes productivity, flexibility, and transparent system design. You can run Eigent fully locally for maximum privacy and data control, or choose a cloud-connected experience for quick... -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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Sprix SAGE Router
State-aware SELF/COLLABORATE/HANDOFF routing for A2A agent networks
Sprix SAGE Router is an open-source routing layer for coordinating agents in Agent2Agent networks. It decides whether an active agent should continue alone, recruit collaborators, or hand a task to another specialist. Routing decisions account for current progress, capability coverage, context-transfer costs, permissions, budgets, and deadlines. The system assigns remaining requirements to agents through task dependency graphs and estimates execution schedules. It learns contextual... -
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iFixAi
Independent Auditing of AI Agents
iFixAi is an independent auditing toolkit for evaluating whether an AI agent performs the business job it was assigned. Instead of measuring only latency, token use, or prompt-injection resistance, it examines operational behavior, organizational alignment, and task outcomes. A standard run performs 32 inspections across five evaluation pillars and produces an A-to-F grade. Users can configure and launch audits through a guided CLI, explicit command flags, or an agent plugin and skill. The... -
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Harness Engineering
Field guide, and agent context bundle for harness engineering
Harness Engineering is a retrieval-optimized anthology, field guide, and agent context bundle for improving AI coding-agent performance. It treats the model and agent as fixed while strengthening the surrounding context, tools, constraints, and proof mechanisms. The repository organizes developed arguments, practical cases, source evidence, evaluations, and reusable playbooks into distinct layers. Its agent guide routes each task to the smallest relevant set of materials instead of loading... -
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Three.js Object Sculptor
Codex plugin that turns attached object images into code-only
Three.js Object Sculptor is a Codex plugin that converts a reference image into a procedural Three.js object written entirely in code. It first evaluates whether the image is suitable and produces an ObjectSculptSpec describing geometry, materials, lighting, hierarchy, pivots, and quality targets. Codex then follows staged passes from blockout and structural work through surface detail, interaction design, and optimization. Generated models include meaningful sockets and anchors for... -
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Windows Copilot API
Reverse engineered Windows Copilot into an OpenAI-compatible API
Windows Copilot API is an unofficial Python project that exposes the consumer Microsoft Copilot web experience through a programmable interface. It can be used directly as a Python library or launched as a local server compatible with the OpenAI API format. The client supports streamed responses, multi-turn conversations, and conversation identifiers. Browser-based sign-in stores a reusable session and refreshes it automatically for later requests. Because compatible applications can target... -
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The Fable Method
How Claude Fable 5 worked, distilled into skills
The Fable Method is a structured workflow for improving how AI agents reason, act, verify, and report. It converts observed problem-solving habits into explicit steps that different language models can follow. The core process classifies the request, defines completion criteria, gathers primary evidence, chooses one recommendation, makes the smallest correct change, and verifies the result. Four included skills cover planning, execution, judging completed work, and generating domain-specific... -
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DocuBrowse
This does for Documents what repo-browser does for repos
DocuBrowse is a local AI-powered document search engine for personal or professional file collections. It indexes documents such as PDFs, Word files, spreadsheets, presentations, ebooks, HTML, text, and Markdown. The system combines SQLite FTS5 keyword search with local semantic embeddings for meaning-based retrieval. Users can click search results to generate an AI synopsis before opening the original file. It runs entirely on the user’s machine with Ollama models, so it does not require... -
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zhengxi-views
Zheng Xi (Efonda Fund Manager) Investment Research Agent Skill
zhengxi-views is a traceable investment research Agent Skill centered on the public views of Zheng Xi, a fund manager at E Fund. It is built to reduce unsupported AI answers by grounding responses in original public statements, fund reports, interviews, and documented methodology. The project organizes a corpus of Zheng Xi’s views from 2012 to 2026, then connects those materials to an extracted investment framework. It also includes real fund data snapshots for managed funds and broader fund... -
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Hiring Agent
AI agent to evaluate and score resumes
Hiring Agent is an AI-powered resume evaluation pipeline for screening technical candidates. It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence,... -
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PixelRAG
The beginning of scalable pixel-native search
PixelRAG is a visual retrieval-augmented generation system that searches documents by how they look, not only by the text they contain. It renders web pages, PDFs, and images into screenshot tiles, then performs retrieval over those visual representations. This approach preserves layout, tables, charts, diagrams, infographics, and other visual structure that traditional HTML or text parsing can miss. The project includes tools for rendering, chunking, embedding, indexing, and serving visual... -
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MathCode
A Frontier Mathematical Coding Agent
MathCode is a terminal-based AI coding assistant focused on mathematical formalization and theorem proving. It is designed to transform plain-language mathematical reasoning into verified Lean 4 code and formal proofs. The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive... -
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Clawith
OpenClaw for Teams
Clawith is an AI-driven agent system focused on enabling intelligent task execution, coordination, and interaction across complex environments. It is designed to function as a control layer where agents can perform actions, manage workflows, and respond dynamically to changing conditions. The system likely emphasizes integration with external tools and services, allowing agents to extend their capabilities beyond internal reasoning. Its architecture suggests support for multi-agent... -
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MetaClaw
Just talk to your agent
MetaClaw is an AI or agent-oriented system that appears to focus on advanced control, coordination, or training of autonomous agents, potentially within reinforcement learning or tool-using environments. The project likely emphasizes meta-level reasoning, where agents are not only executing tasks but also adapting their strategies based on feedback and performance signals. It may incorporate mechanisms for learning from interactions, improving decision-making over time, and generalizing... -
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MedgeClaw
Open-source AI research assistant for biomedicine
MedgeClaw is a specialized AI-powered research assistant tailored for biomedical and scientific workflows, built on top of OpenClaw and Claude Code architectures. It integrates a large library of domain-specific skills, enabling it to perform complex analyses in areas such as genomics, drug discovery, and clinical research. The system connects conversational interfaces with computational environments, allowing users to initiate research tasks through messaging platforms while the backend... -
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ML Retreat
Machine Learning Journal for Intermediate to Advanced Topics
ML Retreat is an open-source learning repository that serves as a structured journal documenting advanced topics in machine learning and artificial intelligence. The project compiles detailed notes, technical explanations, and curated resources that guide readers through complex concepts across modern AI research. Rather than functioning as a traditional tutorial series, the repository is organized as a learning journey that progressively explores increasingly advanced subjects. ... -
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PentestAgent
AI agent framework for black-box security testing
PentestAgent is an open-source autonomous security testing platform designed to help organizations identify vulnerabilities and assess security posture by simulating real-world attack scenarios without manual intervention. It brings a modular and automated approach to penetration testing by orchestrating a suite of tools and scripts that can emulate common exploitation techniques, reconnaissance workflows, and post-exploitation activities across targets. Users configure rules, policies, and... -
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AWorld
Build, evaluate and train General Multi-Agent Assistance with ease
AWorld (Agent World) is an agent runtime/framework. It supports building, evaluating, and training self-improving intelligent agents and multi-agent systems (MAS). It is designed to provide infrastructure for agent orchestration, iterative learning, and environment interaction at scale. Scalable training across environments and distributed setups. Support for multi-agent collaboration/orchestration (MAS). The system is intended to help agents evolve via experience. It provides features to... -
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Portia SDK Python
Portia Labs Python SDK for building agentic workflows
portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g. OpenAI, Anthropic, Mistral, Gemini) and... -
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AndroidEnv
RL research on Android devices
android_env is a reinforcement learning (RL) environment developed by Google DeepMind that enables agents to interact with Android applications directly as a learning environment. It provides a standardized API for training agents to perform tasks on Android apps, supporting tasks ranging from games to productivity apps, making it suitable for research in real-world RL settings. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
MiniSom is a minimalistic and Numpy-based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial Neural Network able to convert complex, nonlinear statistical relationships between high-dimensional data items into simple geometric relationships on a low-dimensional display. Minisom is designed to allow researchers to easily build on top of it and to give students the ability to quickly grasp its details. The project initially aimed for a minimalistic implementation of... -
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. An AI system can behave unfairly for a variety of reasons. -
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SageMaker Python SDK
Training and deploying machine learning models on Amazon SageMaker
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker-compatible Docker... -
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Causal ML
Uplift modeling and causal inference with machine learning algorithms
Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data. Essentially, it estimates the causal impact of intervention T on outcome Y for users with observed features X, without strong assumptions on...
