Showing 1774 open source projects for "forum source code"

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  • 1
    LazyCodex

    LazyCodex

    The one and only agent harness for complex codebases

    LazyCodex is an agent harness for using Codex on complex software projects. It is designed to add structure around AI coding sessions through memory, planning, execution, verification, skills, hooks, routing, and diagnostics. The project helps developers move beyond one-off prompts by giving the agent a more organized workflow inside a codebase. It supports project memory so context can persist across sessions and decisions do not need to be repeatedly reintroduced. LazyCodex also emphasizes...
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  • 2
    agents-best-practices

    agents-best-practices

    Provider-neutral Agent Skill for Codex, Claude Code

    agents-best-practices is a provider-neutral Agent Skill for designing, auditing, refactoring, and explaining agentic harnesses. It is built around the principle that the model proposes actions, while the harness validates, authorizes, executes, records, and returns observations. The project applies to coding agents, research agents, support agents, operations agents, sales agents, finance agents, healthcare agents, education agents, and workflow automation agents. It helps users reason about...
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  • 3
    Guizang Social Card Skill

    Guizang Social Card Skill

    Claude Code / Codex skill — generate Xiaohongshu carousels

    Guizang Social Card Skill is an AI-agent skill for generating polished social image packages in a Guizang-inspired visual style. It is designed for formats such as Xiaohongshu or Rednote carousels, WeChat Official Account covers, article covers, product update graphics, thumbnails, and screenshot-heavy posts. The skill turns articles, scripts, screenshots, product notes, subtitles, or photos into structured social card outputs. It supports editorial magazine layouts and Swiss-style visual...
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  • 4
    OpenMonoAgent

    OpenMonoAgent

    Terminal-native coding agent powered by local LLMs

    OpenMonoAgent.ai is a self-hosted coding agent designed to run entirely on the user’s own hardware. It pairs a .NET CLI with a local llama.cpp inference server so developers can use agentic coding workflows without cloud subscriptions or per-token billing. The project emphasizes privacy, local control, and ownership of the model, compute, and project data. It includes a terminal-native workflow, built-in tools, Docker sandboxing, and code intelligence features. The system can run on CPU or...
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  • 5
    native-feel.skill

    native-feel.skill

    An Agent Skill for designing cross-platform desktop apps

    native-feel-skill is an agent skill for designing cross-platform desktop apps that still feel native. It is based on architectural lessons from Raycast’s 2.0 rewrite and reverse engineering of a shipping Raycast beta app. The skill helps AI assistants reason about when to use native code, when to share web-based interface layers, and how to avoid the common failures of Electron-style or WebView-based products. It includes eight architectural tenets, a four-layer architecture model, WebKit...
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  • 6
    adversarial-spec

    adversarial-spec

    A Claude Code plugin that iteratively refines product specifications

    adversarial-spec is a framework focused on designing and testing systems using adversarial thinking to uncover weaknesses and improve robustness. It encourages developers to define specifications that anticipate failure modes, edge cases, and malicious inputs before implementing solutions. The project emphasizes proactive design, ensuring that systems are built with resilience in mind from the beginning. It provides structured approaches for identifying vulnerabilities and stress-testing...
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  • 7
    Claude Codex Settings

    Claude Codex Settings

    My personal Claude Code and OpenAI Codex setup

    Claude Codex Settings is a configuration-focused repository that provides curated settings, prompts, and workflow optimizations for improving AI-assisted coding environments. It is designed to help developers fine-tune how Claude and similar models behave within coding workflows, ensuring more consistent and high-quality outputs. The project emphasizes practical usability, offering ready-to-use configurations that can be directly integrated into development environments. It also includes...
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  • 8
    Ollama JavaScript Library

    Ollama JavaScript Library

    Ollama JavaScript library

    Ollama JavaScript is the official JavaScript client for integrating Ollama into JS and TS applications with a lightweight, developer-friendly API. It is designed around the Ollama REST API, so it feels consistent with the platform while making common tasks easier to handle in application code. The library supports standard chat interactions, text generation, embeddings, and model management, which makes it useful for both simple chat interfaces and more advanced AI-powered workflows. It...
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  • 9
    apfel

    apfel

    Apple Intelligence from the command line

    apfel is a lightweight and likely experimental development project focused on building efficient and minimal tools or frameworks, typically emphasizing simplicity, performance, and clean abstractions. The project appears to follow a philosophy of reducing unnecessary complexity while still enabling practical functionality for developers who prefer lean systems over heavy frameworks. It is designed to be adaptable, allowing developers to extend or modify its behavior depending on their...
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  • 10
    SEO Machine

    SEO Machine

    A specialized Claude Code workspace for creating long-form

    SEO Machine is an AI-powered content production system built as a structured workspace for generating long-form, SEO-optimized blog content through automated workflows. It integrates research, writing, analysis, and optimization into a single pipeline, allowing users to produce high-quality articles tailored to search engine performance. The system uses specialized commands and agents to perform tasks such as keyword research, competitor analysis, content drafting, and optimization. It...
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  • 11
    Desloppify

    Desloppify

    Agent harness to make your slop code well-engineered and beautiful

    Desloppify is a utility-focused project aimed at improving the quality, structure, and clarity of generated or written text by removing redundancy, noise, and unnecessary verbosity. It is designed to “clean up” outputs, particularly those produced by AI systems, making them more concise, readable, and professional. The system likely applies heuristics or transformation rules to identify repetitive patterns, filler content, and stylistic inconsistencies. This makes it especially useful in...
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  • 12
    Oh My OpenCode Slim

    Oh My OpenCode Slim

    Slimmed, cleaned and fine-tuned oh-my-opencode fork

    Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents,...
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  • 13
    markstream-vue

    markstream-vue

    A Vue 3 renderer specifically built for AI-powered streaming Markdown

    markstream-vue is a specialized Vue 3 rendering engine designed to handle AI-generated streaming Markdown content with high performance and visual stability. It is built specifically for real-time applications such as chat interfaces, AI assistants, and live documentation systems where content is incrementally streamed rather than rendered all at once. The framework focuses on eliminating jitter and reflow issues that commonly occur when rendering progressively generated text, ensuring a...
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  • 14
    NLP

    NLP

    Open source NLP guide with models, methods, and real use cases

    ...Designed for accessibility, the project evolves over time, allowing updates and improvements as NLP techniques advance. It reflects a practical approach to learning, where readers can explore code, experiment with models, and build foundational skills in machine learning-driven language processing.
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  • 15
    ZML

    ZML

    Any model. Any hardware. Zero compromise

    ZML is a high-performance machine learning inference stack designed to run AI models efficiently across heterogeneous hardware environments using a modern systems programming approach. Built with technologies such as Zig, MLIR, and Bazel, it focuses on production-grade deployment where performance, portability, and scalability are critical. The system allows models to be compiled and executed across multiple types of accelerators, including GPUs and TPUs, even when distributed across...
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  • 16
    PySpur

    PySpur

    Visual tool for building, testing, and deploying AI agent workflows

    PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation...
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  • 17
    TypeAgent Python

    TypeAgent Python

    Structured RAG: ingest, index, query

    TypeAgent Python is an experimental Python implementation of Microsoft’s TypeAgent architecture designed to explore how large language models can interact with structured software systems. The project focuses on implementing structured Retrieval-Augmented Generation workflows that allow agents to ingest information, index it in structured form, and answer queries using language models. Instead of relying solely on free-form prompts, the architecture emphasizes converting natural language...
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  • 18
    KG-LLM-Papers

    KG-LLM-Papers

    Papers integrating knowledge graphs (KGs) and large language models

    KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge...
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  • 19
    All Agentic Architectures

    All Agentic Architectures

    Implementation of 17+ agentic architectures

    All Agentic Architectures is an open educational repository that provides hands-on implementations of modern AI agent architectures. The project acts as a practical learning resource that bridges the gap between theoretical research on autonomous agents and real software implementations. It contains more than a dozen agent architectures implemented using frameworks such as LangChain and LangGraph. Each architecture is explained through runnable notebooks that illustrate how the agent works...
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  • 20
    mergekit

    mergekit

    Tools for merging pretrained large language models

    ...The library is designed to operate efficiently even in environments with limited hardware resources by using memory-efficient processing methods that can run entirely on CPUs. It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code.
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  • 21
    micrograd

    micrograd

    A tiny scalar-valued autograd engine and a neural net library

    micrograd is a tiny, educational automatic differentiation engine focused on scalar values, built to show how backpropagation works end to end with minimal code. It constructs a dynamic computation graph as you perform math operations and then computes gradients by walking that graph backward, making it an approachable “from scratch” autograd reference. On top of the core autograd “Value” concept, the project includes a small neural network library that lets you define and train simple...
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  • 22
    Maestro AI Orchestration

    Maestro AI Orchestration

    Agent Orchestration Command Center

    Maestro is a cross-platform desktop application designed for power users to orchestrate and manage fleets of AI agents and project workflows from a keyboard-centric interface. It provides a high-performance experience for running multiple agent sessions in parallel, integrating with tools such as Claude Code, OpenAI Codex, and other agent tooling to automate tasks, perform unattended execution, and organize long-running work flows. Users can collaborate with AI to draft specifications, break...
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  • 23
    Kong Konnect MCP

    Kong Konnect MCP

    A Model Context Protocol server for interacting with Kong Konnect

    MCP Konnect is a Model Context Protocol (MCP) server implementation that enables AI assistants and agents to interact with Kong Konnect, the API management and gateway platform from Kong. This server exposes Kong Konnect’s APIs through standardized MCP interfaces so that tools like conversational AI or agent systems can query analytics, inspect configuration, and manage Kong Gateway resources using natural language or programmable agents. By bridging MCP clients to Kong’s control plane, the...
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  • 24
    GetProfile

    GetProfile

    User profile and long-term memory for your AI agent

    GetProfile is a drop-in proxy layer that sits in front of your LLM provider to turn otherwise stateless chat requests into a system with persistent user profiles and long-term memory. Instead of forcing you to redesign your application, you route your model calls through GetProfile and it captures conversation context automatically as traffic flows. It then extracts structured traits and “memories” from those conversations, stores them, and injects the most relevant profile context back into...
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  • 25
    D4RL

    D4RL

    Collection of reference environments, offline reinforcement learning

    D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm...
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